1 00:00:06,706 --> 00:00:07,374 Good morning. 2 00:00:07,374 --> 00:00:09,542 Welcome from the National Library of Medicine, 3 00:00:09,542 --> 00:00:11,344 the National Institutes of Health. 4 00:00:11,344 --> 00:00:12,612 My name is Jeff Reznick. 5 00:00:12,612 --> 00:00:14,981 I'm chief of the History of Medicine Division. 6 00:00:15,548 --> 00:00:18,985 On behalf of the Office of the Interim Director, I have the great privilege 7 00:00:18,985 --> 00:00:22,288 of offering these welcome words and moderating today's proceedings. 8 00:00:22,756 --> 00:00:25,692 I also have the great privilege of thanking our co-sponsor, 9 00:00:25,692 --> 00:00:28,528 the Friends of the National Library of Medicine, the lab. 10 00:00:29,162 --> 00:00:32,365 The friends are indeed wonderful friends of our institution, 11 00:00:32,365 --> 00:00:33,900 and we are very grateful to each 12 00:00:33,900 --> 00:00:36,970 and every one of them, and especially to their board of directors. 13 00:00:37,637 --> 00:00:40,106 I also wish to thank the outstanding media 14 00:00:40,106 --> 00:00:43,376 and communications team here at the NLM and at the NIH 15 00:00:43,710 --> 00:00:47,013 for their time and their talent dedicated to this very special program. 16 00:00:47,647 --> 00:00:51,051 And of course, my colleagues and I thank you for joining us today, 17 00:00:51,051 --> 00:00:55,789 all of you from near and far for the annual NLM Lindbergh Lecture, 18 00:00:55,789 --> 00:00:59,559 which is part of our scientific symposium, Science Society 19 00:00:59,559 --> 00:01:02,095 and the legacy of Donald A.B. Lindbergh, M.D.. 20 00:01:03,063 --> 00:01:04,330 One housekeeping note. 21 00:01:04,330 --> 00:01:07,434 You will see a live feedback button under your video stream. 22 00:01:07,834 --> 00:01:10,170 If you have a question during the course of our proceedings 23 00:01:10,170 --> 00:01:13,039 or comment, please use this button and send it to us. 24 00:01:13,406 --> 00:01:14,441 Now let's begin. 25 00:01:14,441 --> 00:01:16,209 I'm going to turn things over to my colleague 26 00:01:16,209 --> 00:01:18,078 Gerry Sheehan, who will get us started 27 00:01:18,078 --> 00:01:20,413 with welcome remarks on this very exciting day. 28 00:01:20,480 --> 00:01:22,082 Gerry, over to you. 29 00:01:22,549 --> 00:01:25,919 Thank you very much, Jeff, and hello and welcome to everyone. 30 00:01:25,919 --> 00:01:29,189 It's great to see so many people joining us for today's event. 31 00:01:29,622 --> 00:01:31,091 My name is Jerry Sheehan. 32 00:01:31,091 --> 00:01:32,492 I'm the deputy director 33 00:01:32,492 --> 00:01:36,162 of the National Library of Medicine for Policy and External Affairs. 34 00:01:36,763 --> 00:01:39,999 And I am honored and privileged to welcome you to the fourth 35 00:01:39,999 --> 00:01:43,870 annual Lindbergh King Lecture and Scientific Symposium. 36 00:01:44,938 --> 00:01:48,274 This lecture series was established in 2015 37 00:01:48,675 --> 00:01:52,045 as a forum to bring together insights on the current state 38 00:01:52,278 --> 00:01:56,149 and the future of bioinformatics and pathobiology, 39 00:01:56,583 --> 00:02:00,353 and convey them to a broad, scientific and public audience. 40 00:02:01,621 --> 00:02:04,691 Today's Lindbergh King lecture honors the legacy 41 00:02:04,691 --> 00:02:08,194 and contributions of the namesakes of the lecture series. 42 00:02:08,928 --> 00:02:11,564 Former NLM director Donald A.B. 43 00:02:11,564 --> 00:02:16,603 Lindbergh and former NLM Deputy Director for Research and Education, Dr. 44 00:02:16,603 --> 00:02:18,872 Donald West King. 45 00:02:18,872 --> 00:02:21,741 I am sure that they, like many of us, would have wished 46 00:02:21,741 --> 00:02:24,310 that we could gather for today's event in person. 47 00:02:25,178 --> 00:02:26,279 But knowing Dr. 48 00:02:26,279 --> 00:02:30,283 Lindbergh as the leader who first brought computers into the library 49 00:02:30,483 --> 00:02:33,887 and arguably brought libraries into the world of computing, 50 00:02:34,420 --> 00:02:38,358 it seems altogether fitting and proper to to honor the legacy of doctors 51 00:02:38,358 --> 00:02:39,359 Lindbergh and King. 52 00:02:39,359 --> 00:02:41,394 Even in this virtual forum today. 53 00:02:41,394 --> 00:02:42,595 And thank you for doing so. 54 00:02:43,930 --> 00:02:46,900 I am pleased that we have a diverse lineup of speakers 55 00:02:47,267 --> 00:02:50,670 and as well so many of you in the audience who are here with us today 56 00:02:50,904 --> 00:02:54,240 to help us honor the legacies of the great doctors, Lindbergh and King. 57 00:02:54,874 --> 00:02:57,310 And I thank you all for joining what is sure to be 58 00:02:57,310 --> 00:02:59,746 an enjoyable, exciting and interesting day. 59 00:03:01,080 --> 00:03:04,050 It's now my pleasure to introduce the first 60 00:03:04,217 --> 00:03:07,420 among today's distinguished list of speakers, Dr. 61 00:03:07,420 --> 00:03:08,821 Heidi Rehm. 62 00:03:09,455 --> 00:03:13,826 Dr. Reem is the chief genomics officer at the Center for Genomic Medicine 63 00:03:14,027 --> 00:03:17,630 and the Department of Medicine at Massachusetts General Hospital. 64 00:03:18,198 --> 00:03:23,069 She also has the distinction of serving as the chair of the NLM Board of Regents. 65 00:03:23,803 --> 00:03:25,138 Welcome, Dr. Tim. 66 00:03:25,138 --> 00:03:27,240 I'll turn over to you. 67 00:03:27,473 --> 00:03:28,241 Thank you, Jerry. 68 00:03:28,241 --> 00:03:32,545 It's it's my distinct pleasure to welcome everybody to today's scientific 69 00:03:32,545 --> 00:03:36,583 symposium on Science, Society and the legacy of Donald Lindbergh. 70 00:03:37,183 --> 00:03:40,086 We just have an outstanding lineup of sessions and speakers, 71 00:03:40,086 --> 00:03:43,656 and I'm sure you are all going to enjoy the day, the whole day. 72 00:03:44,357 --> 00:03:48,528 But before we kick things off, a few of us will make some introductory remarks. 73 00:03:48,995 --> 00:03:51,998 And I just wanted to share some personal perspectives 74 00:03:52,298 --> 00:03:55,268 as we think about the legacy of Donald Lindbergh. 75 00:03:56,069 --> 00:04:00,173 He directed the NLM for over 30 years and made a major 76 00:04:00,173 --> 00:04:03,309 and lasting impact on biomedical science in that period. 77 00:04:03,776 --> 00:04:06,512 He extensively engaged his Board of Regents, 78 00:04:06,512 --> 00:04:10,883 and I'm very delighted to be on that board and chairing it this year. 79 00:04:11,651 --> 00:04:15,355 And he also engaged many outside constituent groups to ensure 80 00:04:15,355 --> 00:04:19,492 that NLM would provide important and useful services to the community. 81 00:04:20,059 --> 00:04:20,793 Today, we take 82 00:04:20,793 --> 00:04:24,731 for granted that we have a pub bed and other basic tools at our disposal. 83 00:04:24,731 --> 00:04:25,632 But it was actually Dr. 84 00:04:25,632 --> 00:04:29,202 Lindbergh who established many of these tools and made sure 85 00:04:30,136 --> 00:04:31,104 importantly that they were 86 00:04:31,104 --> 00:04:35,241 freely available to the community and also near and dear to my heart. 87 00:04:35,241 --> 00:04:37,377 Is his work in establishing and CBI, 88 00:04:37,377 --> 00:04:41,314 the National Center for Biotechnology Information, which has provided data 89 00:04:41,314 --> 00:04:46,486 storage access, annotation resources to the genomics community for many years. 90 00:04:46,786 --> 00:04:51,424 And I did want to share one example of the important role of Dr. 91 00:04:51,424 --> 00:04:54,460 Lindbergh's work and his establishment of NCB 92 00:04:54,794 --> 00:04:56,996 , and that is the launch of the Clean Bar database. 93 00:04:56,996 --> 00:04:58,231 And any of you who know me 94 00:04:58,231 --> 00:05:01,567 know just how near and dear that database is to my heart. 95 00:05:02,168 --> 00:05:03,169 So a little history. 96 00:05:03,169 --> 00:05:06,706 About ten years ago, a group of clinical laboratory geneticists, 97 00:05:06,706 --> 00:05:09,842 including myself, were working to develop a database 98 00:05:09,842 --> 00:05:13,346 to share classified variants that we were generating in our labs. 99 00:05:13,346 --> 00:05:15,848 And we really recognized we needed to all come together. 100 00:05:16,316 --> 00:05:19,719 Unfortunately, our first endeavor to create such a database 101 00:05:19,719 --> 00:05:23,523 and get buy in to contribute to it was actually unsuccessful. 102 00:05:25,191 --> 00:05:26,292 But then we discovered that 103 00:05:26,292 --> 00:05:29,896 NCBA was thinking about creating a variant database of this sort. 104 00:05:30,263 --> 00:05:35,168 And so we abandoned our first approach and partnered with MPI to provide 105 00:05:35,168 --> 00:05:38,538 input to the development of clean air with the NCI team. 106 00:05:38,971 --> 00:05:41,307 So it would fit our needs and we worked to support it 107 00:05:41,474 --> 00:05:45,078 as the location for all of the clinical labs to share their data. 108 00:05:45,845 --> 00:05:49,182 This time the effort took off and now, as many of you 109 00:05:49,182 --> 00:05:53,186 know, clean air has become the go to place for not only U.S. 110 00:05:53,186 --> 00:05:56,622 labs, but actually the world to share classified variants. 111 00:05:56,923 --> 00:06:00,226 And I actually credit the reputation of NCI 112 00:06:00,460 --> 00:06:06,299 as a trusted resource for long term sustainability of key genomic resources, 113 00:06:06,566 --> 00:06:10,236 as well as the ability to remain free from commercial bias 114 00:06:10,703 --> 00:06:12,839 as the key to the success of clean air 115 00:06:12,839 --> 00:06:16,442 when we were not able to do that through another endeavor before that. 116 00:06:17,110 --> 00:06:20,780 And in fact, the voluntary willingness of commercial labs and other submitters 117 00:06:20,780 --> 00:06:26,285 to willingly share their data in clean air for no strings attached access 118 00:06:26,619 --> 00:06:29,956 by the broader community really is a testament 119 00:06:29,956 --> 00:06:33,393 to the reputation of TBI and what has been built. 120 00:06:33,693 --> 00:06:36,863 And in clear indeed clean air has become a core resource 121 00:06:37,130 --> 00:06:40,266 for both clinical and research applications of human genetics 122 00:06:40,566 --> 00:06:44,003 and has contributed to the accurate diagnosis of millions 123 00:06:44,003 --> 00:06:46,839 of patients receiving genetic testing every year. 124 00:06:47,173 --> 00:06:49,442 It's just a wonderful success story. 125 00:06:49,442 --> 00:06:52,311 I'm sure that my colleagues and other speakers today 126 00:06:52,311 --> 00:06:56,282 will include their own stories of the many lasting impacts that Dr. 127 00:06:56,282 --> 00:06:58,551 Lindbergh has had on our field. 128 00:06:58,551 --> 00:07:02,088 But with that, I will turn it over to our next speaker. 129 00:07:02,121 --> 00:07:04,123 Thank you very much for joining us today. 130 00:07:06,159 --> 00:07:07,660 Thank you for those remarks, Dr. 131 00:07:07,660 --> 00:07:10,363 Reem, and for getting us started today. 132 00:07:10,363 --> 00:07:13,299 Jeff Resnick, I'm going to turn back to you for the rest of the program. 133 00:07:15,001 --> 00:07:15,735 Thank you, Jerry. 134 00:07:15,735 --> 00:07:17,637 And thanks indeed, Dr. Reed. 135 00:07:17,637 --> 00:07:20,406 Now, it's my pleasure to introduce Glen Campbell, 136 00:07:20,473 --> 00:07:23,209 who for more than a decade has served masterfully 137 00:07:23,409 --> 00:07:26,112 as chair of the Friends of the National Library of Medicine. 138 00:07:26,846 --> 00:07:29,649 And most recently, Glen was managing director 139 00:07:29,649 --> 00:07:32,752 for the British Medical Journal, the BMJ in the Americas. 140 00:07:33,252 --> 00:07:36,756 And prior to his time with the BMJ, he was executive vice president 141 00:07:36,756 --> 00:07:41,160 for global medical research at Elsevier, where he had publishing responsibility 142 00:07:41,160 --> 00:07:44,230 for more than 420 journals in the health sciences, 143 00:07:44,664 --> 00:07:47,667 more than half of which were published in partnership with society. 144 00:07:48,000 --> 00:07:50,203 Welcome to you, Glen, and thanks for joining us today. 145 00:07:50,203 --> 00:07:51,270 Thanks, Jeff. 146 00:07:51,270 --> 00:07:52,472 And thank you, Dr. 147 00:07:52,472 --> 00:07:55,374 Ream and Gerry, for the kind words of introduction. 148 00:07:55,842 --> 00:07:57,310 And on behalf of Dr. 149 00:07:57,310 --> 00:08:01,781 Redman, Barbara Redmond, our President and the Board of Directors of the Friends 150 00:08:01,781 --> 00:08:04,250 of the National Library of Medicine and all friends 151 00:08:04,550 --> 00:08:06,686 of the National Library of Medicine. 152 00:08:06,686 --> 00:08:09,622 It's my pleasure and an honor to welcome you as well 153 00:08:09,922 --> 00:08:13,259 to the 2000 2022 Lindbergh 154 00:08:13,593 --> 00:08:17,730 King Lecture and the scientific symposium, the legacy of Dr. 155 00:08:17,730 --> 00:08:19,866 Donald AB Lindbergh. 156 00:08:19,866 --> 00:08:24,136 The friends are pleased to co-sponsor the annual Lindbergh King Lecture 157 00:08:24,136 --> 00:08:25,071 once again 158 00:08:25,071 --> 00:08:27,006 with our friends and distinguished colleagues 159 00:08:27,006 --> 00:08:29,842 of the American Medical Informatics Association. 160 00:08:30,142 --> 00:08:32,912 And we're particularly enthusiastic to hear from Dr. 161 00:08:32,912 --> 00:08:36,749 Cohan, whose passion for using data and new tools 162 00:08:36,749 --> 00:08:41,854 to accelerate the clinical application of biomedical research was shared by Dr. 163 00:08:41,854 --> 00:08:44,657 Lindbergh and Dr. King. 164 00:08:44,657 --> 00:08:48,327 We are pleased as well with to join with our colleagues 165 00:08:48,327 --> 00:08:52,632 at the National Library of Medicine to sponsor today's scientific 166 00:08:52,632 --> 00:08:54,800 symposium on Dr. 167 00:08:54,800 --> 00:08:57,270 King's legacy. Dr. King. 168 00:08:58,037 --> 00:09:00,273 I'm sorry, Dr. Lindbergh's legacy. Dr. 169 00:09:00,273 --> 00:09:03,910 Lindbergh was a great communicator, 170 00:09:04,410 --> 00:09:09,448 a candid and caring person in his exchanges with every individual 171 00:09:10,016 --> 00:09:14,520 and active listener and a lifelong learner with a wry sense of humor. 172 00:09:14,820 --> 00:09:18,891 His impact on the public health is for one who was a 173 00:09:19,926 --> 00:09:21,661 highly valued 174 00:09:21,661 --> 00:09:24,196 one, who highly valued measurable outcomes 175 00:09:24,564 --> 00:09:26,465 immeasurable. 176 00:09:29,902 --> 00:09:33,072 And incorporating this year's King Lindbergh lecture 177 00:09:33,072 --> 00:09:36,208 into the scientific symposium on the legacy of Dr. 178 00:09:36,208 --> 00:09:40,246 Lindbergh provides the opportunity to hear from those whose leadership 179 00:09:40,246 --> 00:09:44,016 today in biomedical informatics, leadership, training and library 180 00:09:44,350 --> 00:09:47,720 research builds on his roundtable groundbreaking work. 181 00:09:48,287 --> 00:09:50,423 Over the 30 plus years that Dr. 182 00:09:50,423 --> 00:09:54,994 Lindbergh was director of the NLM, he transformed the library from the 183 00:09:54,994 --> 00:09:59,732 passive to active player in delivering improved health care outcomes. 184 00:10:00,132 --> 00:10:03,869 Today, his successor, the cheerfully dynamic Dr. 185 00:10:03,869 --> 00:10:06,939 Brennan and her leadership team, recognize Dr. 186 00:10:06,939 --> 00:10:10,109 Lindbergh's legacy as the library evolves, 187 00:10:10,109 --> 00:10:13,613 as a center of biomedical discovery and data powered health. 188 00:10:14,113 --> 00:10:18,217 The friends are very grateful and appreciative of Jeff Resnick 189 00:10:18,217 --> 00:10:21,320 and everyone at the library and AMIA, as well 190 00:10:21,320 --> 00:10:25,291 as today's speakers and preventers, for their tremendous efforts to ensure 191 00:10:25,291 --> 00:10:29,161 that today's event will be an engaging and thrilling one. 192 00:10:29,595 --> 00:10:30,196 Thank you. 193 00:10:34,266 --> 00:10:35,201 Thank you, Glenn. 194 00:10:35,201 --> 00:10:36,636 And thanks again to you 195 00:10:36,636 --> 00:10:39,639 and everyone on the board of the Friends of the National Library of Medicine. 196 00:10:40,940 --> 00:10:43,609 Now it's my distinct pleasure to introduce Dr. 197 00:10:43,609 --> 00:10:47,380 Gretchen Purcell, Jackson, President and chair of the Board of Directors 198 00:10:47,380 --> 00:10:50,182 for the American Medical Informatics Association, AMIA, 199 00:10:50,816 --> 00:10:54,654 also vice president and scientific medical officer at Intuitive Surgical 200 00:10:54,920 --> 00:10:59,091 and Associate Professor of Surgery, Pediatrics and biomedical informatics 201 00:10:59,392 --> 00:11:01,594 at the Vanderbilt University Medical Center. 202 00:11:02,194 --> 00:11:05,831 Dr. Jackson is an internationally recognized biomedical musician, 203 00:11:06,132 --> 00:11:09,468 an accomplished clinical surgeon with over 30 years of contributions 204 00:11:09,468 --> 00:11:12,104 to informatics, research and surgical science. 205 00:11:12,805 --> 00:11:15,374 In her current position at Intuitive Surgical. Dr. 206 00:11:15,374 --> 00:11:20,279 Jackson is a health care technology executive focused on scientific strategy, 207 00:11:20,579 --> 00:11:24,917 and she practices pediatric surgery at Vanderbilt Vanderbilt Children's Hospital. 208 00:11:25,251 --> 00:11:25,851 Welcome to you. 209 00:11:25,851 --> 00:11:28,354 Dr. Jackson, thanks for joining us today. 210 00:11:28,354 --> 00:11:28,821 Over to you. 211 00:11:29,789 --> 00:11:30,823 Thank you so much. 212 00:11:30,823 --> 00:11:34,460 I am so grateful for this opportunity to speak at this National Library 213 00:11:34,460 --> 00:11:38,064 of Medicine Symposium on honoring the legacy of Dr. 214 00:11:38,064 --> 00:11:40,366 Donald A.B. Lindbergh. 215 00:11:40,366 --> 00:11:44,270 I am not only the board chair for the American Medical 216 00:11:44,270 --> 00:11:48,074 Informatics Association, but also a great cold former recipient 217 00:11:48,307 --> 00:11:51,010 of a National Library of Medicine pre doctoral fellowship 218 00:11:51,243 --> 00:11:54,880 which supported my Biomedical Informatics Training and Ph.D. 219 00:11:54,947 --> 00:11:57,349 research at Stanford University. 220 00:11:59,351 --> 00:12:01,320 I'm excuse me. 221 00:12:01,320 --> 00:12:02,421 I am honored today 222 00:12:02,421 --> 00:12:07,226 to speak on behalf of the American Medical Informatics Association, or AMIA, 223 00:12:07,460 --> 00:12:11,430 which I am sure, as most of you know, is the leading scientific health 224 00:12:11,430 --> 00:12:14,433 informatics professional organization in the United States. 225 00:12:14,734 --> 00:12:17,203 And it's really an important part of Dr. 226 00:12:17,203 --> 00:12:18,871 Lindbergh's legacy. 227 00:12:18,871 --> 00:12:23,843 AMIA now represents over 5000 biomedical and health informatics professionals 228 00:12:24,076 --> 00:12:29,381 who work across academics, industry, health systems, nonprofits and government. 229 00:12:29,715 --> 00:12:34,453 And AMIA now hosts three well-attended scientific meetings each year, 230 00:12:34,887 --> 00:12:39,125 including the Informatics Summit, focused on bio and clinical research 231 00:12:39,125 --> 00:12:41,961 informatics, the clinical informatics meeting, 232 00:12:42,228 --> 00:12:45,064 and, of course, the annual symposium in November. 233 00:12:46,298 --> 00:12:49,068 Some of the most important of Dr. 234 00:12:49,068 --> 00:12:53,939 Lindbergh's contributions to informatics were his organization in the development 235 00:12:53,939 --> 00:12:56,942 of scientific activities and professional societies, 236 00:12:57,143 --> 00:12:59,612 which supported the growth and evolution of our field. 237 00:13:00,012 --> 00:13:03,516 And I will speak briefly about these contributions to conferences 238 00:13:03,516 --> 00:13:06,919 in professional organizations to review this piece of history. 239 00:13:07,720 --> 00:13:10,823 So as many of you know, in 1977, Dr. 240 00:13:10,823 --> 00:13:13,926 Lindbergh presented at the first symposium 241 00:13:13,926 --> 00:13:17,997 on computer applications in Medical Care, or Shamsi, 242 00:13:18,230 --> 00:13:21,300 which then was a local meeting in the Washington, D.C. 243 00:13:21,300 --> 00:13:26,272 area of engineers, scientists and clinicians who met to discuss scientific 244 00:13:26,572 --> 00:13:31,610 but clinically relevant papers at the intersection of computers and medicine. 245 00:13:32,144 --> 00:13:36,348 The first Proceedings of Shamsi was published by Triple E, and it featured 246 00:13:36,348 --> 00:13:39,819 67 papers, and the meeting hosted 250 247 00:13:39,819 --> 00:13:42,388 attendees with no concurrent sessions. 248 00:13:43,022 --> 00:13:47,560 Dr. Lindbergh attended this meeting regularly as interest increased, 249 00:13:47,693 --> 00:13:51,130 and he was recruited to the first board of directors as the first member 250 00:13:51,130 --> 00:13:55,601 from outside of Washington when Shamsi was legally incorporated 251 00:13:55,768 --> 00:13:58,971 and began to attract a national and international audience. 252 00:13:59,405 --> 00:14:03,108 This meeting rapidly evolved with the introduction of posters, 253 00:14:03,108 --> 00:14:07,546 parallel tracks, panels, tutorial system demonstrations 254 00:14:07,546 --> 00:14:10,816 in the student paper competition within five years. 255 00:14:11,150 --> 00:14:15,020 In 1987, the chairman, Daniel Harris, 256 00:14:15,421 --> 00:14:18,891 noted that just reading the scientific work was not enough. 257 00:14:18,891 --> 00:14:22,995 You had to be there for the informal conversations in the hallways 258 00:14:22,995 --> 00:14:26,565 that often led to significant collaborations and innovations. 259 00:14:26,866 --> 00:14:31,971 And this was certainly my experience when I attended my first Shamsi meeting 260 00:14:32,271 --> 00:14:36,308 as a student in 1991, and at that time, Dr. 261 00:14:36,308 --> 00:14:38,777 Lindbergh was the president of AMIA. 262 00:14:39,845 --> 00:14:41,947 AMIA, as we know it today, 263 00:14:42,348 --> 00:14:46,619 came from the convergence of professional societies and conferences, and Dr. 264 00:14:46,619 --> 00:14:49,788 Lindbergh played a key role in each component. 265 00:14:50,122 --> 00:14:53,225 At the 1982 CMC meeting, Maurice Cohen 266 00:14:53,225 --> 00:14:56,495 hosted a small meeting of informatics leaders, including Dr. 267 00:14:56,495 --> 00:14:58,430 Lindbergh, to propose the creation 268 00:14:58,430 --> 00:15:01,734 of the American College of Medical Informatics, or Acmi. 269 00:15:02,301 --> 00:15:04,770 Acmi elected its first class of fellows 270 00:15:04,770 --> 00:15:07,940 in 1985 and subsequently incorporated. 271 00:15:08,374 --> 00:15:11,577 Academy Fellowship remains one of the highest honors one can receive 272 00:15:11,577 --> 00:15:15,848 for substantive and sustained contributions to the field of informatics. 273 00:15:16,515 --> 00:15:20,352 Now, in the early 1980s, the American Association 274 00:15:20,352 --> 00:15:24,189 for Medical Systems and Informatics, MCI, emerged 275 00:15:24,223 --> 00:15:28,160 as the leading professional organization for computer systems in medical care 276 00:15:28,394 --> 00:15:31,730 as a result of the merger of the Society for Computer Medicine 277 00:15:32,031 --> 00:15:35,234 and the Society for Advanced Medical Systems. 278 00:15:35,634 --> 00:15:38,604 M.S. held its own scientific meeting in the spring, 279 00:15:38,637 --> 00:15:42,041 usually on the West Coast, so as not to conflict with Shamsi. 280 00:15:42,374 --> 00:15:42,942 And Dr. 281 00:15:42,942 --> 00:15:47,179 Lindbergh served on the board of AMC in the mid 1980s. 282 00:15:47,913 --> 00:15:50,783 By the late 1980s, the overlap of the interest 283 00:15:50,783 --> 00:15:55,955 and the leaderships across AMC, Shamsi and Acmi was substantial, 284 00:15:56,255 --> 00:15:59,024 and their three boards agreed that a merger to create 285 00:15:59,024 --> 00:16:01,927 a single organization would be in the best interest of all. 286 00:16:02,761 --> 00:16:06,565 Dr. Lindbergh was selected as the founding president of this 287 00:16:06,565 --> 00:16:10,602 new organization, the American Medical Informatics Association, 288 00:16:10,769 --> 00:16:14,206 which was legally incorporated in 1993. 289 00:16:14,540 --> 00:16:20,145 Acme became a self-governing entity as part of Aimia, and AMC was dissolved. 290 00:16:20,479 --> 00:16:24,350 The annual meeting of AMIA was called Shamsi for the first five years 291 00:16:24,350 --> 00:16:27,920 after this merger and in 1987 became 292 00:16:27,920 --> 00:16:31,557 the AMIA annual symposium . Now, Dr. 293 00:16:31,557 --> 00:16:35,094 Lindbergh's contributions to AMIA during his tenure as president 294 00:16:35,661 --> 00:16:38,397 included the creation of the Acme Retreats, 295 00:16:38,897 --> 00:16:40,366 Amy as committees, 296 00:16:40,366 --> 00:16:43,702 the professional specialty groups, which are now known as working groups, 297 00:16:43,936 --> 00:16:49,074 and the executive executive director role as well as direction to the Publications 298 00:16:49,074 --> 00:16:53,412 Committee to create a new journal which eventually became the Journal 299 00:16:53,412 --> 00:16:56,215 of the American Medical Informatics Association. 300 00:16:56,515 --> 00:17:00,953 Our flagship journal, This Wonderful History of AMIA and Dr. 301 00:17:00,953 --> 00:17:04,823 Lindbergh Center roles are described in this publication, shown on this slide 302 00:17:05,190 --> 00:17:09,528 authored by Jan Van Den, Marian, Bob and Ted Short live. 303 00:17:11,096 --> 00:17:12,364 Dr. Lindbergh led the 304 00:17:12,364 --> 00:17:15,567 evolution of medical informatics societies and meetings 305 00:17:15,567 --> 00:17:18,237 not only in the United States, but also globally. 306 00:17:18,604 --> 00:17:21,740 The International Medical Informatics Association image 307 00:17:22,107 --> 00:17:25,010 was created in 1967, and Dr. 308 00:17:25,010 --> 00:17:26,645 Lindbergh served as the U.S. 309 00:17:26,645 --> 00:17:30,582 representative to MDA for the American Federation of Information 310 00:17:30,582 --> 00:17:34,086 Processing Societies Ethics in the 1980s. 311 00:17:34,586 --> 00:17:38,891 Dr. Lindbergh also served as the chair of the Organizing Committee for India's 312 00:17:38,924 --> 00:17:44,263 1986 international meeting med info, which took place in Washington, D.C. 313 00:17:44,763 --> 00:17:47,633 when metadata when med info returned to 314 00:17:47,633 --> 00:17:50,569 the United States in 2004 in San Francisco. 315 00:17:50,836 --> 00:17:55,207 Dr. Lindbergh personally arranged for the Nelms Fogarty International Center 316 00:17:55,374 --> 00:17:58,911 to provide support for attendees from Third World countries. 317 00:17:59,845 --> 00:18:04,216 As the current board chair for AMIA, which has been my professional home 318 00:18:04,216 --> 00:18:07,119 for three decades, and the scientific program chair 319 00:18:07,119 --> 00:18:12,658 for the 2022 AMIA Annual Symposium in Washington, DC . 320 00:18:12,658 --> 00:18:15,360 I am so grateful for the contributions of Dr. 321 00:18:15,360 --> 00:18:19,231 Lindbergh to informatics societies and scientific forums, 322 00:18:19,431 --> 00:18:22,101 which are only a teeny tiny piece of Dr. 323 00:18:22,101 --> 00:18:23,602 Lindbergh's legacy. 324 00:18:23,602 --> 00:18:26,872 I thank you all again for the opportunity to provide 325 00:18:26,872 --> 00:18:30,042 opening remarks for this symposium, and I hope you will enjoy the day 326 00:18:30,042 --> 00:18:30,909 as much as I will. 327 00:18:34,880 --> 00:18:35,514 Thank you, Dr. 328 00:18:35,514 --> 00:18:36,081 Jackson. 329 00:18:36,081 --> 00:18:41,153 A fantastic history lesson and much to learn there and to explore. 330 00:18:41,320 --> 00:18:43,388 Thank you very, very much. 331 00:18:43,722 --> 00:18:47,292 It's now my pleasure to introduce Shannon Jones, who is director 332 00:18:47,292 --> 00:18:51,663 of libraries for the Medical University of South Carolina Libraries in Charleston. 333 00:18:52,264 --> 00:18:55,501 She is also director for Region Two of the network 334 00:18:55,501 --> 00:18:59,371 of the National Library of Medicine, a longtime volunteer 335 00:18:59,371 --> 00:19:02,141 for the Medical Library Association, or MLA. 336 00:19:02,407 --> 00:19:07,212 Shannon currently serves as president of the association in 2018. 337 00:19:07,212 --> 00:19:11,517 Shannon co-founded the MLA reads Virtual Book Discussion Club 338 00:19:11,917 --> 00:19:15,354 to provide a forum where participants can learn, discuss 339 00:19:15,621 --> 00:19:20,225 and process the implications of a variety of topics on their work 340 00:19:20,559 --> 00:19:23,962 as information professionals and in their personal lives. 341 00:19:24,596 --> 00:19:27,699 She is also coeditor of Diversity and Inclusion 342 00:19:27,699 --> 00:19:31,637 in Libraries A Call to Action and Strategies for Success, 343 00:19:32,137 --> 00:19:36,575 as well as the forthcoming volume entitled Cultural Humility in Libraries. 344 00:19:37,109 --> 00:19:39,611 Shannon Jones, welcome and thank you for joining us today 345 00:19:39,611 --> 00:19:42,047 to represent the Medical Library Association. 346 00:19:42,047 --> 00:19:44,049 Thank you and good morning, everyone. 347 00:19:44,049 --> 00:19:46,451 I'm bringing you greetings from Charleston, South Carolina. 348 00:19:47,019 --> 00:19:52,124 I am both humbled and honored to welcome each of you to the Limburg Lecture 349 00:19:52,124 --> 00:19:56,261 and Scientific Symposium on behalf of the nearly 3000 health 350 00:19:56,261 --> 00:19:59,831 information professionals that comprise the Medical Library Association, 351 00:20:00,165 --> 00:20:04,403 or, as we affectionately call it, my life as an association. 352 00:20:04,403 --> 00:20:05,871 The Marley community believes 353 00:20:05,871 --> 00:20:08,907 that quality information is essential for improved health. 354 00:20:09,408 --> 00:20:12,311 We aspire to be the association of the most visible, 355 00:20:12,544 --> 00:20:15,647 valued and trusted health information experts. 356 00:20:16,648 --> 00:20:19,484 And most importantly, we strive to enhance the quality 357 00:20:19,484 --> 00:20:23,121 of health care, education and research in our environments. 358 00:20:23,622 --> 00:20:26,191 Since 2003 to honor Dr. 359 00:20:26,191 --> 00:20:30,329 Lindbergh's legacy, Emily awards the Limburg Research Fellowship 360 00:20:30,562 --> 00:20:34,099 annually aimed at expanding the research knowledge base, 361 00:20:34,099 --> 00:20:38,003 linking the information services provided by librarians to improve 362 00:20:38,003 --> 00:20:40,939 health care and advances in biomedical research. 363 00:20:42,107 --> 00:20:43,508 For 30 years, Dr. 364 00:20:43,508 --> 00:20:47,112 Lemberg supported the Mission and Goals of Medical Association 365 00:20:47,412 --> 00:20:51,016 and was a strong champion and advocate for health science librarians 366 00:20:51,016 --> 00:20:53,018 throughout the nation and the world. 367 00:20:53,018 --> 00:20:58,156 I'm one of those librarians that remembers leadership, service and advocacy. 368 00:20:58,690 --> 00:21:01,026 So 20 years ago today, 369 00:21:01,193 --> 00:21:04,363 I arrived in Bethesda and I am for my first day 370 00:21:04,363 --> 00:21:09,568 as a member of the 2002 cohort of alum, Associate Fellows and alum. 371 00:21:09,568 --> 00:21:12,571 I launched my career as a health sciences librarian. 372 00:21:12,838 --> 00:21:14,840 I met some wonderful professionals. 373 00:21:14,840 --> 00:21:18,910 I had the opportunity to post, to participate in meaningful projects, 374 00:21:19,211 --> 00:21:21,780 and I was exposed to tools and good information 375 00:21:21,780 --> 00:21:24,082 that have made the journey to standard for you to date. 376 00:21:24,082 --> 00:21:25,984 And amazing, right? 377 00:21:25,984 --> 00:21:30,922 In that Lindbergh's 24 or his three posts on Emily website 378 00:21:30,922 --> 00:21:34,126 and you all go and check it out that the Lindbergh mentions 379 00:21:34,426 --> 00:21:36,962 that he learned two things at Amherst College. 380 00:21:37,195 --> 00:21:41,266 One was a love for biology, and the other was the thrill of discovery. 381 00:21:41,800 --> 00:21:43,568 I share in this love. 382 00:21:43,568 --> 00:21:46,672 I too love discovering new things, new information 383 00:21:46,672 --> 00:21:49,941 and new concepts, which is what I'm most excited about today. 384 00:21:50,375 --> 00:21:53,512 I hope today's program and the speakers who will come before you. 385 00:21:55,347 --> 00:21:58,216 Excuse me, evoke the same sentiment for you. 386 00:22:00,085 --> 00:22:01,586 I also hope that you discover 387 00:22:01,586 --> 00:22:04,156 new information that would enhance your professional journey. 388 00:22:05,257 --> 00:22:07,225 A sincere thanks to the program 389 00:22:07,225 --> 00:22:10,462 organizers for the invitation to join today. 390 00:22:10,462 --> 00:22:12,931 And to each of you, I say welcome to the program. 391 00:22:17,269 --> 00:22:18,337 Thank you very much. 392 00:22:18,337 --> 00:22:19,037 And it's a privilege 393 00:22:19,037 --> 00:22:22,341 to have you here and appreciate your your welcome remarks tremendously. 394 00:22:22,974 --> 00:22:26,812 It is a day of discovery, and you could not have framed that more beautifully. 395 00:22:26,812 --> 00:22:27,646 Thank you. 396 00:22:28,046 --> 00:22:30,782 It's now my pleasure to introduce Kent Smith, 397 00:22:31,083 --> 00:22:33,685 who will introduce our keynote speaker for today. 398 00:22:34,820 --> 00:22:37,489 Ken Smith was deputy director of the National Library 399 00:22:37,489 --> 00:22:41,493 Medicine from 1980 to 24, and previous to 400 00:22:41,493 --> 00:22:45,831 that was also director of administration at the NLM for eight years. 401 00:22:46,631 --> 00:22:49,701 As deputy, he was responsible for program development 402 00:22:49,701 --> 00:22:52,871 and evaluation policy for formulation 403 00:22:52,871 --> 00:22:55,407 and coordination of library activities. 404 00:22:56,208 --> 00:22:59,511 Notably, he served as president of the National Federation 405 00:22:59,511 --> 00:23:02,681 of Advanced Information Services and also 406 00:23:02,681 --> 00:23:06,351 of the International Committee on Scientific and Technical Information. 407 00:23:06,852 --> 00:23:09,454 Ken Smith, welcome and thank you for joining us today. 408 00:23:10,155 --> 00:23:10,622 Over to you. 409 00:23:11,690 --> 00:23:12,858 Oh, thanks. 410 00:23:12,858 --> 00:23:15,460 Thank you for the introduction, Jeff. 411 00:23:15,460 --> 00:23:18,296 You know, it's a real pleasure to be part of this year's 412 00:23:19,431 --> 00:23:23,301 lecture and symposium that has been established, 413 00:23:23,602 --> 00:23:26,605 as you know, in the honor of Don Limbaugh and Don King. 414 00:23:27,672 --> 00:23:28,306 You know, Dr. 415 00:23:28,306 --> 00:23:31,209 King was also a key member of the Anaheim family. 416 00:23:31,877 --> 00:23:35,447 He was a noted scholar, a great pathologist. 417 00:23:36,581 --> 00:23:39,351 A lover of medical history 418 00:23:39,351 --> 00:23:42,921 and really a wonderful, kind and most generous colleague. 419 00:23:44,122 --> 00:23:46,291 And of course, it is particular 420 00:23:46,291 --> 00:23:48,860 pleasure to be here to celebrate 421 00:23:49,628 --> 00:23:52,397 the legacy of Donald AB Lombard. 422 00:23:53,432 --> 00:23:57,002 A man I had the honor and privilege of working beside 423 00:23:57,302 --> 00:24:00,605 during his first 20 years as the director. 424 00:24:01,840 --> 00:24:04,609 He was a brilliant man, a born leader. 425 00:24:05,911 --> 00:24:10,782 And one who brought with him a clear vision as to how to provide better 426 00:24:10,782 --> 00:24:14,453 and wider access to biomedical information, 427 00:24:14,453 --> 00:24:17,422 not only for the benefit of the nation's health professionals, 428 00:24:18,023 --> 00:24:19,558 but also the general public. 429 00:24:20,659 --> 00:24:22,427 His leadership and motivating 430 00:24:22,427 --> 00:24:26,131 skills created a team that brought success 431 00:24:26,264 --> 00:24:29,568 and realized his vision that he stated 432 00:24:29,568 --> 00:24:31,603 early on when he arrived. 433 00:24:32,604 --> 00:24:34,873 And so it seems totally appropriate, 434 00:24:34,873 --> 00:24:39,277 as we remember, Don, that our keynote speaker today 435 00:24:39,277 --> 00:24:43,114 is also a very successful visionary in medical science. 436 00:24:44,316 --> 00:24:48,386 Dr. Isaac on is the main Marian B Nelson, 437 00:24:48,386 --> 00:24:52,123 professor of biomedical informatics at the Harvard Medical School. 438 00:24:52,924 --> 00:24:56,561 Chair of its Department of Biomedical Informatics 439 00:24:57,262 --> 00:25:02,267 and is the Associate Professor of medicine at the Brigham and Women's Hospital. 440 00:25:02,901 --> 00:25:06,004 Now, some of you may also be interested knowing that he previously 441 00:25:06,004 --> 00:25:10,242 had been the director of the Conway Medical Library at Harvard's. 442 00:25:11,309 --> 00:25:13,645 Now I'm going to tell you right up front 443 00:25:13,645 --> 00:25:17,682 that I will not try to cover all of his honors and accomplishments 444 00:25:17,682 --> 00:25:21,286 contained in his 66 three page 445 00:25:21,286 --> 00:25:24,523 CV, but just highlight a few of them. 446 00:25:25,891 --> 00:25:27,092 He began his formal 447 00:25:27,092 --> 00:25:31,663 education at the International School of Geneva, Switzerland. 448 00:25:32,531 --> 00:25:35,700 He received, with honors his Bachelor of Science 449 00:25:35,901 --> 00:25:40,171 in Biology from Brown University and his M.D. 450 00:25:40,171 --> 00:25:41,273 m.p.h., Ph.D. 451 00:25:41,273 --> 00:25:45,076 from Boston University, including some doctoral work, 452 00:25:45,076 --> 00:25:49,114 I might add, with the clinical decision making group at the M.I.T. 453 00:25:49,114 --> 00:25:51,383 lab for computer science. 454 00:25:52,617 --> 00:25:57,989 Now he has published well over 500 papers in the medical literature 455 00:25:58,456 --> 00:26:02,027 and is the author of the widely used book entitled 456 00:26:02,394 --> 00:26:05,931 Microarrays for an Integrated OMICS. 457 00:26:06,998 --> 00:26:09,034 He's a distinguished member 458 00:26:09,034 --> 00:26:11,970 of the Institute for Medicine. 459 00:26:11,970 --> 00:26:15,140 The American Society for Clinical Investigation 460 00:26:15,907 --> 00:26:20,011 and of course, the American College of Medicine for Max. 461 00:26:20,712 --> 00:26:24,583 And that explains effort have been driven by his vision 462 00:26:25,183 --> 00:26:27,719 of what biomedical researchers could do 463 00:26:28,253 --> 00:26:31,923 to find new cures and deliver the best patient care. 464 00:26:33,325 --> 00:26:34,025 As Dr. 465 00:26:34,025 --> 00:26:36,962 William Tierney put it, and I quote from him, Dr. 466 00:26:36,962 --> 00:26:41,600 Cohan has revolutionized many areas of biomedical informatics 467 00:26:42,033 --> 00:26:46,171 and has changed the way we practice patient care delivery. 468 00:26:47,339 --> 00:26:49,741 That statement actually was made when Dr. 469 00:26:49,741 --> 00:26:55,080 Cohan was awarded the prestigious Maurice Colin Award of Excellence 470 00:26:55,080 --> 00:26:57,182 from the American College of Medicine Medical. 471 00:27:00,018 --> 00:27:02,153 With this recognition, one could say 472 00:27:02,921 --> 00:27:07,592 perhaps that he completed the AMIA trifecta, having also received 473 00:27:07,592 --> 00:27:11,396 the Williams Stead Award for Thought Leadership in Informatics 474 00:27:11,930 --> 00:27:15,100 and the Donna Lab Limburg Award for Innovation 475 00:27:15,634 --> 00:27:17,769 in Informatics. 476 00:27:18,336 --> 00:27:21,339 Highlight among many of his accomplishments 477 00:27:21,673 --> 00:27:25,210 is his initiative in translating genomic research 478 00:27:25,910 --> 00:27:28,947 into the clinical environment. 479 00:27:28,947 --> 00:27:32,984 Its name sort of brings back sort of that essence of the George 480 00:27:32,984 --> 00:27:37,422 Lucas Star Wars, as is call it to be true 481 00:27:38,289 --> 00:27:42,794 or informatic for integrating biology and the bedside 482 00:27:43,628 --> 00:27:49,000 I to be to provides sort of a technical solution to informatics to exchange 483 00:27:49,634 --> 00:27:53,571 across institutions and is now a standard component 484 00:27:54,239 --> 00:27:57,442 of hundreds of analytic projects throughout the world. 485 00:27:58,943 --> 00:27:59,511 In Dr. 486 00:27:59,511 --> 00:28:03,882 Paddy Brennan's musings from the mezzanine, I learned the Dr. 487 00:28:03,948 --> 00:28:06,351 Guy has a little motto called 488 00:28:06,951 --> 00:28:09,487 Make our data work for US. 489 00:28:10,555 --> 00:28:11,056 Data. 490 00:28:11,056 --> 00:28:13,191 Our speaker said, and I quote from him, 491 00:28:13,191 --> 00:28:17,062 It means that let's not just use it for the real reason. 492 00:28:17,062 --> 00:28:20,732 Most of it is accumulated at present, which is in order 493 00:28:20,732 --> 00:28:24,069 to satisfy administrate or reimbursement process. 494 00:28:24,803 --> 00:28:27,772 But instead, let's use it to improve health care. 495 00:28:28,873 --> 00:28:32,477 So, folks, I'm pleased to present to you from way up there 496 00:28:32,477 --> 00:28:36,614 in God's country our distinguished keynote speaker, Dr. 497 00:28:36,614 --> 00:28:38,616 Isaac Culhane. 498 00:28:40,552 --> 00:28:42,153 Thank you, Dr. 499 00:28:42,153 --> 00:28:42,587 Smith. 500 00:28:42,587 --> 00:28:45,924 What a remarkable introduction. 501 00:28:48,293 --> 00:28:49,260 It's in the can. 502 00:28:49,260 --> 00:28:53,298 I will now use that recording for all future introductions. 503 00:28:53,364 --> 00:28:57,001 Thank you. That was. That was wonderful. 504 00:28:57,001 --> 00:29:01,306 I am so honored to be the keynote speaker 505 00:29:02,407 --> 00:29:03,675 today and truly 506 00:29:03,675 --> 00:29:07,579 gratified because Dr. 507 00:29:07,579 --> 00:29:12,984 Lindbergh, Don, was an oversize figure in my entire career. 508 00:29:13,685 --> 00:29:19,290 And I'm going to say it now just because I'm what I'm going to otherwise forget. 509 00:29:19,357 --> 00:29:23,228 I do want to thank everybody who has participated in this program 510 00:29:23,528 --> 00:29:28,099 from Jeff Resnick, all the public participants, the Friends 511 00:29:28,099 --> 00:29:31,136 of National Library of Medicine, the National Library of Medicine, 512 00:29:31,770 --> 00:29:34,606 or colleagues for making this moment possible. 513 00:29:35,640 --> 00:29:37,575 It is indeed 514 00:29:38,276 --> 00:29:42,480 frustrating and sad that we have not been able to come together for two years. 515 00:29:42,480 --> 00:29:45,583 And this is, I think, a first step towards 516 00:29:46,017 --> 00:29:49,187 remediating some of that disturbing 517 00:29:50,221 --> 00:29:53,825 trend. So. 518 00:29:54,125 --> 00:29:57,228 I would like to say, first of all, that Dr. 519 00:29:57,228 --> 00:30:01,533 Lindbergh really embodied what those of us who trained in pediatrics 520 00:30:01,933 --> 00:30:05,603 like to say is the most important part of teaching, which is modeling. 521 00:30:06,271 --> 00:30:09,607 He modeled for us what leaders looked like 522 00:30:09,607 --> 00:30:12,510 in bio embodied medicine, period. 523 00:30:13,244 --> 00:30:14,279 As Dr. 524 00:30:14,279 --> 00:30:16,614 Smith said, he was a born leader. 525 00:30:16,614 --> 00:30:19,117 I don't know if he was a born leader, but by the time I met him, 526 00:30:19,117 --> 00:30:21,686 he was without a doubt a leader and a statesman. 527 00:30:22,053 --> 00:30:23,588 And he showed how to be a leader, 528 00:30:25,657 --> 00:30:28,726 not just in the modern sense 529 00:30:28,760 --> 00:30:34,599 of visionary and brashness, but also in dealing 530 00:30:34,599 --> 00:30:39,871 with a complex ecosystem which at times can be frustrating as I'll touch upon. 531 00:30:40,305 --> 00:30:42,273 He really 532 00:30:42,373 --> 00:30:45,143 drove innovations that have transformed 533 00:30:45,977 --> 00:30:49,214 so many parts of medicine, but it was not all smooth sailing 534 00:30:49,781 --> 00:30:52,951 and less of a statesman , less of a leader may have gone frustrated 535 00:30:52,951 --> 00:30:58,089 and said things that might have actually impeded further progress. But 536 00:30:58,523 --> 00:31:02,594 at least in his public face, he was always calm, 537 00:31:03,561 --> 00:31:06,731 steadfast and optimistic. 538 00:31:07,532 --> 00:31:10,001 He would say wry jokes 539 00:31:10,001 --> 00:31:12,136 about some of the obstacles, 540 00:31:12,303 --> 00:31:15,840 but he would not actually let 541 00:31:16,174 --> 00:31:19,010 civility falter at any point. 542 00:31:19,644 --> 00:31:21,880 And in that respect, I think. 543 00:31:23,181 --> 00:31:25,183 We are all reminded what leadership 544 00:31:25,183 --> 00:31:27,285 looks like and. 545 00:31:28,920 --> 00:31:31,489 Although I feel often I 546 00:31:32,590 --> 00:31:37,295 use this moment to remind myself of what that looks like. So 547 00:31:39,731 --> 00:31:40,431 without further 548 00:31:40,431 --> 00:31:43,668 ado, let's start the keynote. 549 00:31:44,602 --> 00:31:46,838 So in thinking about what I wanted 550 00:31:46,838 --> 00:31:50,475 to say about Van Limburg. 551 00:31:50,842 --> 00:31:52,377 There was a recurrent theme 552 00:31:52,377 --> 00:31:54,379 in all my discussions with him. 553 00:31:55,346 --> 00:32:00,184 And frankly, and much of the programs that he funded, 554 00:32:00,952 --> 00:32:03,221 including some of my own grants, 555 00:32:04,055 --> 00:32:07,792 and that was in making information 556 00:32:08,559 --> 00:32:11,663 and knowledge get distributed out 557 00:32:12,363 --> 00:32:14,465 not only to doctors. 558 00:32:15,366 --> 00:32:18,036 But to patients. 559 00:32:18,603 --> 00:32:22,006 And although I will not make up this point later on. 560 00:32:23,341 --> 00:32:24,309 Now Dr. 561 00:32:24,309 --> 00:32:26,878 Reem pointed out about clinic bar. 562 00:32:27,445 --> 00:32:30,081 Important resource for both 563 00:32:30,615 --> 00:32:34,519 clinical labs and. 564 00:32:34,652 --> 00:32:36,688 Doctors throughout the world. But. 565 00:32:38,356 --> 00:32:41,893 Dr. Lindbergh also sponsored the genetic home reference, 566 00:32:42,093 --> 00:32:44,429 which was a genetic reference 567 00:32:45,163 --> 00:32:47,332 specifically targeted towards. 568 00:32:48,299 --> 00:32:51,035 Consumers understanding two things. 569 00:32:51,402 --> 00:32:51,803 Okay. 570 00:32:51,803 --> 00:32:55,606 Unfortunately, most doctors don't know enough genetics to be able to explain it 571 00:32:55,606 --> 00:32:59,210 well to patients and sick of all that patients deserve 572 00:32:59,577 --> 00:33:02,880 and can profit personally 573 00:33:03,314 --> 00:33:06,951 in their health by understanding genetics better. 574 00:33:07,452 --> 00:33:12,123 And so I decided that the theme I would 575 00:33:13,424 --> 00:33:14,592 address, 576 00:33:14,592 --> 00:33:18,429 although there could have been many other themes and many other dimensions of Dr. 577 00:33:18,429 --> 00:33:21,899 Lindbergh's accomplishments, the theme I would ask for was. 578 00:33:23,701 --> 00:33:25,503 Who will be the primary purveyor 579 00:33:25,503 --> 00:33:28,306 of authoritative medical knowledge to the US patient. 580 00:33:29,107 --> 00:33:31,175 And I will outline. 581 00:33:32,176 --> 00:33:34,712 Dr. Bloomberg's contributions, 582 00:33:35,413 --> 00:33:37,715 which are very impressive. 583 00:33:38,716 --> 00:33:43,221 I don't think I am taking anything away to say that Dr. 584 00:33:43,221 --> 00:33:44,789 Lindbergh's work. 585 00:33:45,256 --> 00:33:48,659 Has been very successful, but it's not completed. 586 00:33:48,860 --> 00:33:50,962 And you'd want us to continue. 587 00:33:52,463 --> 00:33:55,533 Pushing forward in the direction he started us. 588 00:33:56,601 --> 00:34:01,072 And I will articulate some of the gap and then I will close 589 00:34:01,639 --> 00:34:04,609 by putting down my bets, 590 00:34:04,609 --> 00:34:06,644 my chips, as to where 591 00:34:07,779 --> 00:34:09,313 the future lies. 592 00:34:09,313 --> 00:34:11,949 And I would I have the conceit. 593 00:34:12,917 --> 00:34:16,554 Which I think is based somewhat on facts that Dr. 594 00:34:16,554 --> 00:34:20,091 Lindbergh would agree with the way I have laid down my chips. 595 00:34:20,324 --> 00:34:22,760 If only because he had inspired 596 00:34:23,895 --> 00:34:26,697 many of my prejudices in that regard. 597 00:34:28,866 --> 00:34:34,972 So let me just tell you what the themes. 598 00:34:35,907 --> 00:34:38,810 I'm going to address R first of all. 599 00:34:40,244 --> 00:34:42,380 What are the necessary ingredients 600 00:34:42,580 --> 00:34:45,183 to having these 601 00:34:45,616 --> 00:34:48,186 this information and data go towards patients? 602 00:34:48,586 --> 00:34:50,655 First of all, there has to be 603 00:34:51,389 --> 00:34:54,392 mechanisms of sharing, 604 00:34:54,859 --> 00:34:57,061 mechanisms of data and knowledge sharing 605 00:34:57,395 --> 00:35:00,231 and a culture of data sharing. 606 00:35:00,631 --> 00:35:05,203 A culture that begets trust and more data sharing. 607 00:35:05,970 --> 00:35:08,739 There has to be transparency and accountability. 608 00:35:09,974 --> 00:35:12,143 And we tend to forget about the accountability 609 00:35:12,143 --> 00:35:14,545 part of it. But. 610 00:35:15,980 --> 00:35:18,015 Having people. 611 00:35:18,149 --> 00:35:21,352 Not only share data, but follow up 612 00:35:22,286 --> 00:35:25,056 has had a theories been proven. 613 00:35:25,389 --> 00:35:29,060 Have the hypotheses been tested and going to that 614 00:35:30,695 --> 00:35:32,130 full cycle 615 00:35:32,130 --> 00:35:34,732 in the scientific discovery cycle? 616 00:35:35,800 --> 00:35:38,603 The other theme is optimism and innovation, 617 00:35:38,870 --> 00:35:45,076 that there is a continued opportunity for all of us to advance. 618 00:35:46,110 --> 00:35:48,846 Medicine and biomedical science 619 00:35:49,380 --> 00:35:52,049 because of the ingenuity 620 00:35:52,049 --> 00:35:54,752 of the human spirit, especially as 621 00:35:56,220 --> 00:35:58,322 embodied in America 622 00:35:58,322 --> 00:36:00,625 by the National Library of Medicine at the NIH. 623 00:36:01,425 --> 00:36:03,594 That the other is scientific skepticism. 624 00:36:03,728 --> 00:36:06,864 Skepticism, which is not to accept all theories 625 00:36:08,466 --> 00:36:12,670 from the beginning as being God's word. 626 00:36:12,670 --> 00:36:14,372 And in fact. 627 00:36:14,572 --> 00:36:16,974 Assuming very much in the spirit of science 628 00:36:17,175 --> 00:36:20,978 that most theories will, in the backs of worlds, 629 00:36:21,179 --> 00:36:25,183 be proven to be approximate and will have to be refined. 630 00:36:26,984 --> 00:36:29,387 Very importantly. 631 00:36:29,921 --> 00:36:31,656 That data. 632 00:36:31,656 --> 00:36:32,757 Actual data. 633 00:36:32,757 --> 00:36:36,227 The raw data are so crucial 634 00:36:36,427 --> 00:36:39,997 to actually distinguishing truth from fiction. 635 00:36:40,831 --> 00:36:43,100 Hypotheses from. 636 00:36:45,069 --> 00:36:47,738 Well found the science. 637 00:36:47,738 --> 00:36:52,510 Finally again, I do not think I am taking over from Dr. 638 00:36:52,510 --> 00:36:54,011 Lindbergh. In fact, 639 00:36:54,378 --> 00:36:57,815 I know he was proud about the fact that his success. 640 00:36:59,183 --> 00:37:00,551 Lay and 641 00:37:00,551 --> 00:37:04,255 finding superb colleagues to. 642 00:37:05,923 --> 00:37:07,658 Take his vision 643 00:37:07,658 --> 00:37:11,128 and translate it into what ultimately became success. 644 00:37:11,462 --> 00:37:13,698 And that includes. 645 00:37:13,698 --> 00:37:14,832 Colleagues such as Dr. 646 00:37:14,832 --> 00:37:15,733 Smith. 647 00:37:16,434 --> 00:37:18,069 Colleagues such as Dr. 648 00:37:18,069 --> 00:37:21,239 K colleagues as such as Dr. 649 00:37:21,239 --> 00:37:25,243 Humphries, colleagues such as Dr. 650 00:37:25,243 --> 00:37:29,180 Macrae, who I mentioned in their names 651 00:37:29,180 --> 00:37:32,817 now and I have missed others and apologies for all of you. 652 00:37:33,150 --> 00:37:36,654 But these were colleagues and our colleagues of Dr. 653 00:37:36,654 --> 00:37:41,626 King who made several of the projects, I should say, and David Lipman, 654 00:37:42,093 --> 00:37:45,963 several of his projects that I will appropriately 655 00:37:45,963 --> 00:37:48,899 credit to his leadership actually come to fruition. 656 00:37:49,467 --> 00:37:53,471 And so part of his inspiration and genius were finding 657 00:37:53,471 --> 00:37:56,807 the right colleagues to actually. 658 00:37:57,675 --> 00:38:00,578 Do the trusted job of actually 659 00:38:01,245 --> 00:38:03,281 moving forward. So. 660 00:38:07,818 --> 00:38:10,821 I put this slide here to remind me to make the following statement. 661 00:38:12,523 --> 00:38:14,992 I think there is a risk. 662 00:38:15,326 --> 00:38:19,063 That we forget how crucial. 663 00:38:21,365 --> 00:38:23,734 Academic and scientific leaders 664 00:38:24,535 --> 00:38:27,738 in biomedicine. And. 665 00:38:29,073 --> 00:38:30,808 I am reminded 666 00:38:31,008 --> 00:38:33,611 by the fact that the current 667 00:38:34,512 --> 00:38:36,614 director of the National Library Medicine 668 00:38:36,614 --> 00:38:39,250 is a. 669 00:38:40,318 --> 00:38:43,554 Doctor and a nursing professional 670 00:38:43,721 --> 00:38:47,358 that perhaps I should have used the word health professional rather than doctors. 671 00:38:47,358 --> 00:38:52,930 But nonetheless, in this slide, it's doctors that doctors can 672 00:38:52,930 --> 00:38:59,337 and should lead in and this vision of innovation 673 00:38:59,437 --> 00:39:03,307 and scientific discovery and that we should not. 674 00:39:04,875 --> 00:39:07,411 Only defer to. 675 00:39:09,280 --> 00:39:14,085 Individuals who have perhaps training in business and commerce 676 00:39:14,085 --> 00:39:18,456 but do not understand some of the underlying 677 00:39:20,291 --> 00:39:24,028 goals and science of the biomedical enterprise. 678 00:39:24,395 --> 00:39:26,564 And so you see here, Dr. 679 00:39:26,564 --> 00:39:30,000 Limberg and although we're not gonna talk about it today, Dr. 680 00:39:30,000 --> 00:39:33,838 Limberg was also a pioneer, for example, in artificial intelligence. 681 00:39:34,271 --> 00:39:35,573 He created the A.I. 682 00:39:35,573 --> 00:39:39,844 Room, the expert system that did expert diagnosis 683 00:39:40,111 --> 00:39:43,848 of drugs, logical disorders, and. 684 00:39:46,684 --> 00:39:47,952 That's. 685 00:39:48,352 --> 00:39:50,454 Tells me that 686 00:39:50,454 --> 00:39:54,492 there is plenty of precedent for doctors leading efforts 687 00:39:54,792 --> 00:39:58,262 in the knowledge, discovery and artificial intelligence. 688 00:39:58,596 --> 00:40:02,433 And we should encourage more doctors to be in that role. 689 00:40:02,800 --> 00:40:05,336 Shown also there, too, 690 00:40:05,503 --> 00:40:09,540 on the left on the screen is Dr. 691 00:40:09,540 --> 00:40:12,343 Octo Barnette, a colleague of 692 00:40:13,744 --> 00:40:16,981 Dan's at Maastricht, Massachusetts General Hospital, 693 00:40:17,181 --> 00:40:20,151 who, along with four MIT undergrads, undergraduates, 694 00:40:21,318 --> 00:40:25,823 built the mumps system that now underlies 695 00:40:26,056 --> 00:40:28,626 most of the electronic health record systems 696 00:40:29,894 --> 00:40:32,229 in the world, including 697 00:40:32,229 --> 00:40:34,632 EPIC, for example. And. 698 00:40:36,100 --> 00:40:40,037 Those that huge innovation back in the 1960s, mind 699 00:40:40,037 --> 00:40:43,407 you, was led by doctors, 700 00:40:44,308 --> 00:40:47,478 leading undergraduates from MIT. 701 00:40:48,012 --> 00:40:50,080 And I do think this this model. 702 00:40:53,150 --> 00:40:55,853 Can and should be emulated because these individuals 703 00:40:56,587 --> 00:40:59,957 have many of the concerns 704 00:41:00,291 --> 00:41:03,828 that the health care system and patients need to have. 705 00:41:04,128 --> 00:41:05,463 And just parenthetically, 706 00:41:05,463 --> 00:41:09,099 we see Randy Miller back there in the background, who is also 707 00:41:09,767 --> 00:41:12,703 has been a leader in many aspects 708 00:41:12,870 --> 00:41:17,174 of biomedical informatics, but also a pioneer in artificial intelligence. 709 00:41:20,778 --> 00:41:22,880 I think that for the 710 00:41:23,781 --> 00:41:27,218 younger folks on this call, it's important 711 00:41:28,085 --> 00:41:30,654 that we remind ourselves, 712 00:41:31,388 --> 00:41:35,025 the world that we lived in when Dr. 713 00:41:35,025 --> 00:41:38,629 Lindbergh took the helm of the National Library of Medicine. 714 00:41:40,130 --> 00:41:41,966 Unfortunately, I am old enough 715 00:41:41,966 --> 00:41:44,768 so that I can remember what that world looked like. 716 00:41:45,603 --> 00:41:48,839 So in 1984, 717 00:41:49,306 --> 00:41:51,742 I was a. A 718 00:41:54,478 --> 00:41:57,181 third year medical student and. 719 00:41:58,782 --> 00:42:00,150 When? 720 00:42:00,918 --> 00:42:04,088 I wanted to. 721 00:42:04,555 --> 00:42:05,589 Search. 722 00:42:05,890 --> 00:42:08,659 Medical literature, I had two options. 723 00:42:08,993 --> 00:42:14,532 One is to look at these books that had indexes of all the published literature. 724 00:42:15,533 --> 00:42:16,834 Index medicus. 725 00:42:16,834 --> 00:42:20,170 Or I could see something very priestly 726 00:42:20,170 --> 00:42:26,076 and remote looking librarians typing into a terminal 727 00:42:26,510 --> 00:42:30,781 that linked to Medline that would, in some arcane 728 00:42:30,781 --> 00:42:33,217 query language, return the. 729 00:42:35,085 --> 00:42:37,488 Articles that were up to date 730 00:42:37,821 --> 00:42:42,893 on the queries that we are rounding on patients needed to have. 731 00:42:43,561 --> 00:42:45,229 That's where it was that 732 00:42:46,297 --> 00:42:47,531 you had to be 733 00:42:47,531 --> 00:42:53,037 part of a medical school or have access to this paid Medline. 734 00:42:53,637 --> 00:42:56,740 This paid service that accessed Medline. 735 00:42:58,375 --> 00:43:00,878 Trials were shrouded in mystery. 736 00:43:02,012 --> 00:43:05,783 A trial would be started by an academic center 737 00:43:05,783 --> 00:43:07,818 or a company. And. 738 00:43:08,886 --> 00:43:12,056 Sometimes the primary endpoint 739 00:43:12,256 --> 00:43:14,458 would be met, would not be met. 740 00:43:15,292 --> 00:43:18,228 These and either the secondary endpoint 741 00:43:18,462 --> 00:43:21,365 would be substituted as the headline of the publication. 742 00:43:22,066 --> 00:43:23,300 You really can track it. 743 00:43:23,300 --> 00:43:25,603 And so all bets are off. 744 00:43:25,603 --> 00:43:28,572 When something was published, was that that original hypothesis 745 00:43:28,572 --> 00:43:32,776 that was tested, or was this just a hypothesis that 746 00:43:34,144 --> 00:43:36,880 survived multiple hypothesis 747 00:43:36,880 --> 00:43:39,650 testing after the primary hypothesis failed? 748 00:43:39,883 --> 00:43:42,653 That's where we were in clinical trials. 749 00:43:43,887 --> 00:43:46,123 And the patients have access 750 00:43:46,123 --> 00:43:49,493 to their medical records? No. 751 00:43:49,493 --> 00:43:53,430 In theory, in some abstract, legalistic sense. 752 00:43:53,464 --> 00:43:54,264 Maybe they did. 753 00:43:55,432 --> 00:43:59,536 But. Probably the most 754 00:44:00,270 --> 00:44:03,273 glaring example of an amusing example 755 00:44:03,507 --> 00:44:07,478 of the fact that they had no access to the record is a Seinfeld skit 756 00:44:07,945 --> 00:44:11,815 where Elaine essentially gets blacklisted by her doctors 757 00:44:11,949 --> 00:44:17,154 for daring to ask her doctor what exactly was written in the record. 758 00:44:18,022 --> 00:44:19,757 There was no such access. 759 00:44:19,757 --> 00:44:24,161 And that meant, among other things, that incorrect assessments of the patient 760 00:44:24,361 --> 00:44:27,297 just mistakes would go on for decades. 761 00:44:27,898 --> 00:44:29,466 Uncorrected. 762 00:44:29,700 --> 00:44:31,735 Data was not shared. 763 00:44:31,735 --> 00:44:34,438 You'd have a scientific discovery, a genomic sequence 764 00:44:34,672 --> 00:44:38,976 discovered in one place, not shared with any other center 765 00:44:39,176 --> 00:44:42,479 unless you had a special relationship 766 00:44:42,579 --> 00:44:46,083 or a friendship or a material transfer agreement. 767 00:44:46,550 --> 00:44:49,119 Incredible delays, therefore, 768 00:44:49,253 --> 00:44:51,955 in the progress of science. 769 00:44:54,224 --> 00:44:55,893 But paradoxically. 770 00:44:55,893 --> 00:44:57,428 And we'll get back to this. 771 00:44:57,428 --> 00:45:00,931 Trust in expertize was in a max at a maximum. 772 00:45:01,799 --> 00:45:04,802 I would actually like to hypothesize. 773 00:45:06,136 --> 00:45:07,905 The reason this trust was so high 774 00:45:07,905 --> 00:45:10,607 was because everything was so opaque. 775 00:45:11,341 --> 00:45:15,946 People did not know what was going on underneath the hood and therefore. 776 00:45:16,947 --> 00:45:19,183 Pronouncements could go 777 00:45:19,183 --> 00:45:22,286 essentially unchallenged because the underlying data, 778 00:45:22,753 --> 00:45:26,023 the underlying knowledge was not broadly available. 779 00:45:26,190 --> 00:45:29,860 But nonetheless, this is a. 780 00:45:29,927 --> 00:45:31,028 The fact that 781 00:45:31,028 --> 00:45:34,565 the trust expertize is now at historic lows, as I will describe, 782 00:45:35,299 --> 00:45:38,435 is a challenge that we must face and. 783 00:45:39,436 --> 00:45:42,439 I think if you had predicted this back in 1984. 784 00:45:43,741 --> 00:45:46,944 People would be confused by this paradoxical, 785 00:45:46,977 --> 00:45:49,780 apparently paradoxical effect. 786 00:45:50,948 --> 00:45:53,817 So let's enter. 787 00:45:53,817 --> 00:45:55,686 The multiple. 788 00:45:57,287 --> 00:45:58,822 Dimensions of Dr. 789 00:45:58,822 --> 00:46:00,691 Lindbergh's success. 790 00:46:00,691 --> 00:46:03,093 So instead of. 791 00:46:04,228 --> 00:46:06,930 A few individuals fortunate to have accounts 792 00:46:06,930 --> 00:46:09,666 with commercial services accessing Medline. 793 00:46:10,501 --> 00:46:14,671 Medline became a free service open to the public, 794 00:46:15,239 --> 00:46:18,208 and then the web got wrapped 795 00:46:18,208 --> 00:46:21,145 around it in PubMed. 796 00:46:21,512 --> 00:46:25,983 And what you see here is the exponential rise of. 797 00:46:28,452 --> 00:46:30,654 The data available 798 00:46:31,155 --> 00:46:34,091 through PubMed and the CBI. 799 00:46:34,892 --> 00:46:39,196 And if you look on the Y axis to the right, 800 00:46:40,063 --> 00:46:41,398 you see 801 00:46:42,599 --> 00:46:44,835 the millions of users per day. 802 00:46:44,835 --> 00:46:45,836 So it's phenomenal. 803 00:46:45,836 --> 00:46:47,838 Millions of users per day. Per day. 804 00:46:47,838 --> 00:46:50,307 But I think among the most cheering 805 00:46:50,607 --> 00:46:54,411 aspects of these millions of users a day is different. 806 00:46:54,411 --> 00:46:59,016 Surveys have shown that between 25 to 50% of those users 807 00:46:59,016 --> 00:47:01,952 are not institutional researchers, 808 00:47:02,419 --> 00:47:05,589 they're educators, they're the public. 809 00:47:06,223 --> 00:47:11,995 And so there's been this huge efflorescence of data 810 00:47:11,995 --> 00:47:16,400 sharing, of information sharing that previously did not exist. 811 00:47:17,768 --> 00:47:19,970 Back in 1984. 812 00:47:19,970 --> 00:47:21,705 And this is because of Dr. 813 00:47:21,705 --> 00:47:25,809 Ginsburg's direct investments in these programs. And. 814 00:47:26,877 --> 00:47:31,181 Picking the leaders to bring forward these efforts. 815 00:47:32,349 --> 00:47:34,651 This also pertains to the growth 816 00:47:34,651 --> 00:47:38,055 of sharing of genomic data. 817 00:47:39,056 --> 00:47:40,224 So that again, 818 00:47:42,092 --> 00:47:43,627 GenBank. 819 00:47:44,161 --> 00:47:46,830 Then within CBI. 820 00:47:48,265 --> 00:47:50,000 Demonstrated that there was 821 00:47:50,000 --> 00:47:54,438 enormous synergies, not multiplicative, but exponential synergies 822 00:47:54,638 --> 00:47:57,708 by having sharing so that you could now discover 823 00:47:58,675 --> 00:48:03,113 through simple search all the variance. 824 00:48:04,615 --> 00:48:06,350 Discovered so far and find out 825 00:48:06,350 --> 00:48:10,220 that your patients have that variant has. 826 00:48:10,621 --> 00:48:13,290 What is the consequence on protein function 827 00:48:13,657 --> 00:48:16,660 of a change in a DNA sequence? 828 00:48:17,361 --> 00:48:21,131 And this spread to all the other kinds of high throughput measurements 829 00:48:21,431 --> 00:48:24,902 that the genomic and post genomic revolution have led to. 830 00:48:25,502 --> 00:48:27,738 And these did not happen by accident. 831 00:48:28,338 --> 00:48:33,977 These were specific programs that had to be fought for 832 00:48:34,177 --> 00:48:37,848 in budgetary allocations through Congress that Dr. 833 00:48:37,848 --> 00:48:40,717 Lindbergh and his colleagues 834 00:48:40,717 --> 00:48:44,421 advocated for and succeeded to do. 835 00:48:44,888 --> 00:48:48,926 But it was by no means assured of success. 836 00:48:53,030 --> 00:48:53,864 Next. 837 00:48:53,864 --> 00:48:56,733 There was really no communities 838 00:48:57,234 --> 00:49:01,972 of information sharing even within academic campuses. 839 00:49:01,972 --> 00:49:07,411 That would be the medical library, the medical school, the hospitals. 840 00:49:07,945 --> 00:49:13,951 And because this program is no longer present, but I you probably don't know 841 00:49:13,951 --> 00:49:17,587 the acronym I AIM's Integrated Advanced Information Management Systems. 842 00:49:17,888 --> 00:49:19,589 These were generous grants 843 00:49:19,589 --> 00:49:23,126 that were led out of the National Library of Medicine that allowed the integration 844 00:49:23,694 --> 00:49:27,898 of data across these academic health centers 845 00:49:28,098 --> 00:49:32,669 and sometimes community health centers in a way that created a culture of sharing, 846 00:49:33,136 --> 00:49:35,806 a culture of democratization, of data 847 00:49:36,039 --> 00:49:38,041 that had not existed. 848 00:49:38,809 --> 00:49:41,645 So again, we take this for granted now, 849 00:49:41,845 --> 00:49:44,848 but it took specific programs to generate. 850 00:49:47,884 --> 00:49:49,486 In 1984, 851 00:49:49,486 --> 00:49:53,690 there was a babble of a variety of terminologies 852 00:49:54,424 --> 00:49:56,860 that described 853 00:49:56,860 --> 00:50:00,030 pathologic pathological samples, that described 854 00:50:00,263 --> 00:50:02,265 billing codes, that described 855 00:50:03,266 --> 00:50:05,302 terms for two index 856 00:50:06,370 --> 00:50:07,537 journals. 857 00:50:07,537 --> 00:50:12,042 And each of those had their own or their own vocabularies. 858 00:50:12,709 --> 00:50:15,412 And yet they were describing different parts of the elephant, 859 00:50:15,412 --> 00:50:18,882 different parts of the biomedical research knowledge base. 860 00:50:19,616 --> 00:50:21,284 But they were not. 861 00:50:22,886 --> 00:50:24,388 Immediately comparable 862 00:50:24,388 --> 00:50:28,225 if someone had described their thing in snow bed, the pathology language, 863 00:50:29,092 --> 00:50:31,862 you could not say if it was anything like 864 00:50:32,329 --> 00:50:35,332 the thing that had been described in mesh. 865 00:50:35,632 --> 00:50:41,972 The terminology for journals and some of the book covers 866 00:50:41,972 --> 00:50:46,410 were not only not linked to these other vocabularies, but they were 867 00:50:47,911 --> 00:50:48,879 proprietary. 868 00:50:48,879 --> 00:50:51,081 You'd have to pay money to access them. 869 00:50:51,081 --> 00:50:54,851 And so in a in a far reaching. 870 00:50:55,886 --> 00:50:56,953 Effort, Dr. 871 00:50:56,953 --> 00:50:58,121 Limberg. 872 00:50:59,289 --> 00:51:03,160 Got both funding and the political alignment 873 00:51:03,226 --> 00:51:07,364 to allow these different vocabularies to be put together. 874 00:51:08,298 --> 00:51:11,902 Into the unified medical language system led by many, 875 00:51:12,169 --> 00:51:14,805 including leaders such as 876 00:51:16,073 --> 00:51:16,840 Duck. Dr. 877 00:51:16,840 --> 00:51:20,777 Humphreys on this zoom to provide 878 00:51:20,777 --> 00:51:25,749 a tool that is now used all the time to actually compare 879 00:51:26,349 --> 00:51:28,819 and align data generated from all these 880 00:51:28,819 --> 00:51:30,487 different systems. 881 00:51:32,022 --> 00:51:33,990 I mentioned before 882 00:51:33,990 --> 00:51:36,927 the obscure state of trials in 1984. 883 00:51:38,528 --> 00:51:42,599 It was a significant act of political leadership 884 00:51:43,233 --> 00:51:47,504 to convince Congress that despite their constituencies 885 00:51:47,904 --> 00:51:51,074 from pharmaceutical companies and other research organizations 886 00:51:51,241 --> 00:51:54,511 in various states, it was in the public interest 887 00:51:55,112 --> 00:51:57,614 for trials to be registered ahead of time 888 00:51:58,248 --> 00:52:00,417 so that the primary endpoints 889 00:52:01,118 --> 00:52:03,920 that the trial was intended to test 890 00:52:04,621 --> 00:52:07,891 were made explicit before the trial was run, 891 00:52:08,492 --> 00:52:11,461 and then to have journals adopt those standards 892 00:52:11,461 --> 00:52:15,632 so that our leading journals, medical journals, would require 893 00:52:15,899 --> 00:52:18,635 registration in clinical trials dot gov 894 00:52:18,835 --> 00:52:22,539 before a trial was published. 895 00:52:23,273 --> 00:52:25,542 All that we take for granted 896 00:52:25,542 --> 00:52:29,312 and with the leadership of Dr. 897 00:52:29,312 --> 00:52:30,480 Lindbergh and Dr. 898 00:52:30,480 --> 00:52:36,019 McCrae, this act of political and technical leadership actually happened. 899 00:52:36,353 --> 00:52:38,922 I should also point out that patients 900 00:52:39,089 --> 00:52:42,125 use clinical trials that or all 901 00:52:42,125 --> 00:52:44,594 the time to find out when they have, 902 00:52:45,162 --> 00:52:49,366 unfortunately, an advanced cancer or a rare disease. 903 00:52:49,533 --> 00:52:51,735 Is there a study out there anywhere 904 00:52:52,836 --> 00:52:56,072 that actually studies this disease that they can 905 00:52:56,072 --> 00:52:59,109 and what its enrollment status can they enroll in it? 906 00:52:59,309 --> 00:53:03,046 It's been used extremely broadly in ways that were never 907 00:53:03,480 --> 00:53:05,582 previously thought of. 908 00:53:06,550 --> 00:53:08,718 I put this last, 909 00:53:08,785 --> 00:53:10,654 but it could end up being 910 00:53:10,654 --> 00:53:13,857 the most impactful work of Dr. 911 00:53:13,857 --> 00:53:14,591 Limburg. 912 00:53:14,925 --> 00:53:18,528 He was absolutely convinced, not least of all, 913 00:53:18,528 --> 00:53:21,531 because of his early work in artificial intelligence, 914 00:53:22,032 --> 00:53:25,402 that that clinical data had to be available 915 00:53:25,402 --> 00:53:29,239 in electronic format and had to be widely sharable 916 00:53:29,839 --> 00:53:33,276 and ultimately had to be in the control of patients. 917 00:53:33,710 --> 00:53:38,281 And with his patients, statesman like patients, 918 00:53:38,281 --> 00:53:44,487 which I described at the beginning, he funded a multiple set of initiatives 919 00:53:44,721 --> 00:53:50,660 from a early 1999 to use electronic health record initiative. 920 00:53:50,660 --> 00:53:53,296 That actually ended up being the first grant I ever got 921 00:53:54,631 --> 00:53:56,099 from the NIH 922 00:53:56,099 --> 00:53:59,603 all the way through to 923 00:53:59,803 --> 00:54:02,272 efforts I'll describe later. 924 00:54:02,772 --> 00:54:03,373 Much. 925 00:54:03,373 --> 00:54:04,941 Not only was 926 00:54:05,342 --> 00:54:08,111 it personally important to me because I was involved in some of 927 00:54:08,111 --> 00:54:12,682 these efforts and but was funded by the National Library Medicine, but 928 00:54:12,682 --> 00:54:16,586 it really led, as I hope I will convince you to, 929 00:54:17,020 --> 00:54:19,389 a transformation of the way 930 00:54:21,191 --> 00:54:22,492 electronic health record 931 00:54:22,492 --> 00:54:24,761 data is shared and disseminated. 932 00:54:26,896 --> 00:54:30,200 So let's talk about that first grant that I got. 933 00:54:30,667 --> 00:54:35,939 The first grant that I got was a new one through the National Library of Medicine. 934 00:54:36,406 --> 00:54:38,541 And it was part of this vision that Dr. 935 00:54:38,541 --> 00:54:42,012 Lindbergh had of data sharing through electronic health records. 936 00:54:42,012 --> 00:54:44,848 So tracking health records already existed by that time. 937 00:54:44,881 --> 00:54:48,618 Again, I mentioned that they already were around in the 1960s 938 00:54:48,918 --> 00:54:52,155 due to visionaries like Dr. Barnett. 939 00:54:54,024 --> 00:54:56,092 But the RFA asked for 940 00:54:56,493 --> 00:54:59,195 ways to share across institutions, 941 00:54:59,195 --> 00:55:05,969 and I proposed back in 1995, I believe, a mechanism 942 00:55:06,136 --> 00:55:10,440 to share data using something that at the time was completely novel. 943 00:55:10,540 --> 00:55:14,511 The World Wide Web and what we proposed was to share 944 00:55:14,511 --> 00:55:18,648 data across health care institutions and working with Dr. 945 00:55:18,648 --> 00:55:23,953 Barnett and Charlie Safran and others with funding from the National Library 946 00:55:23,953 --> 00:55:26,856 of Medicine, which, by the way, was key to my career development. 947 00:55:27,490 --> 00:55:32,562 Harvard sometimes runs a very Darwinian system, which is you don't get funded. 948 00:55:32,696 --> 00:55:33,963 You are. 949 00:55:34,431 --> 00:55:36,533 As they say, history. 950 00:55:36,933 --> 00:55:38,802 So through this 951 00:55:39,102 --> 00:55:44,107 grant we actually have running in 1996 as published in this 952 00:55:45,342 --> 00:55:47,344 scam article stamps 953 00:55:47,344 --> 00:55:50,780 either being that conference that Gretchen reference 954 00:55:51,147 --> 00:55:57,520 we had running in 1996 a program that in real time access data 955 00:55:57,520 --> 00:56:04,461 at the Beth Israel at Children's Hospital and MDH so that in real time you can see. 956 00:56:05,528 --> 00:56:08,098 If the patient had been seen at any one of those institutions 957 00:56:08,298 --> 00:56:11,968 and if they had been seen at multiple institutions, data would be collated 958 00:56:12,202 --> 00:56:15,905 on the fly to create a history of that 959 00:56:17,340 --> 00:56:20,110 patient. Many 960 00:56:20,343 --> 00:56:23,613 subsequent developments turn that into 961 00:56:24,881 --> 00:56:27,450 programs that others used. 962 00:56:28,385 --> 00:56:30,954 Beth Israel integrated multiple health care systems 963 00:56:30,954 --> 00:56:34,090 around that around that technology, but also the 964 00:56:35,158 --> 00:56:38,461 the various regional 965 00:56:38,461 --> 00:56:40,263 data aggregation efforts 966 00:56:40,263 --> 00:56:43,700 that were implemented under President Obama's 967 00:56:45,368 --> 00:56:47,704 high tech act used that on the fly 968 00:56:47,704 --> 00:56:50,840 integration approach. 969 00:56:50,940 --> 00:56:53,309 At the same time, 970 00:56:53,343 --> 00:56:55,378 something rather bizarre. 971 00:56:55,378 --> 00:56:57,781 And at the time impudent 972 00:56:59,482 --> 00:57:02,318 was also funded by the National Library of Medicine, 973 00:57:02,318 --> 00:57:05,622 something called the personal Internet work Notary and Garden. 974 00:57:05,855 --> 00:57:10,160 This is the work that I did with my thesis. 975 00:57:10,760 --> 00:57:15,165 Also for my thesis about former thesis advisor Professor Peter Sullivan of MIT. 976 00:57:16,399 --> 00:57:19,135 He had previously described 977 00:57:19,135 --> 00:57:22,305 in a project called the Garden Angel Project that was funded by ARPA. 978 00:57:23,807 --> 00:57:26,976 A mechanism for having conflicts 979 00:57:27,043 --> 00:57:30,346 or agents safeguarding patients health, I said. 980 00:57:30,413 --> 00:57:33,383 The first step is to actually have a patient control 981 00:57:33,683 --> 00:57:36,686 of those data. 982 00:57:36,686 --> 00:57:39,489 And in fact, what we did was we actually showed 983 00:57:39,489 --> 00:57:42,959 how we could actually use web simple web pages to encrypt. 984 00:57:45,795 --> 00:57:48,865 This example, formatted 985 00:57:48,865 --> 00:57:51,634 data of the patient that had been extracted out of trunk 986 00:57:51,801 --> 00:57:56,873 health record systems, and that this data would then be under patient control 987 00:57:57,307 --> 00:58:01,110 and could be shared with others for research and for clinical care. 988 00:58:01,778 --> 00:58:04,481 And this ended up being the. 989 00:58:06,249 --> 00:58:09,118 This effort, funded by the National Library of Medicine, 990 00:58:09,419 --> 00:58:13,590 ended up being the progenitor of multiple projects. 991 00:58:13,790 --> 00:58:18,761 Some of them, the somewhat ill fated health vault and Google 992 00:58:18,761 --> 00:58:24,000 health efforts of the 1990s ultimately led to 993 00:58:25,168 --> 00:58:28,605 the intellectual descendant, which I'll get to, 994 00:58:28,738 --> 00:58:32,242 which is the person controlled Apple health record 995 00:58:32,909 --> 00:58:36,112 that now accesses over 800 996 00:58:36,946 --> 00:58:40,250 academic health centers and provides patients control 997 00:58:40,250 --> 00:58:42,719 over their own data. 998 00:58:45,488 --> 00:58:46,789 The early work 999 00:58:46,789 --> 00:58:51,127 that I just described led to many other large projects 1000 00:58:51,127 --> 00:58:53,630 actually not funded by the National Library of Medicine, 1001 00:58:53,830 --> 00:58:56,699 but were direct users of technology 1002 00:58:56,699 --> 00:58:59,702 that have been funded by the National Library Medicine. 1003 00:58:59,903 --> 00:59:04,807 So for example, a more across the United States pathology 1004 00:59:05,575 --> 00:59:08,278 data sharing network called the Shared Pathology Informatics 1005 00:59:08,278 --> 00:59:12,215 Network, funded by the National Cancer Institute, was a direct 1006 00:59:12,215 --> 00:59:16,486 use repurposing of the code base that we've actually developed 1007 00:59:16,786 --> 00:59:19,722 for the W3 EMR system that I described at the beginning 1008 00:59:20,623 --> 00:59:22,926 under the CSA. 1009 00:59:22,926 --> 00:59:26,262 We actually actually demonstrated, actually used and published 1010 00:59:26,629 --> 00:59:31,367 several studies that cost whole academic health centers 1011 00:59:31,768 --> 00:59:36,506 that use this distributed sharing mechanism that we had first 1012 00:59:36,839 --> 00:59:39,842 demonstrated through that first grant 1013 00:59:40,176 --> 00:59:42,345 that I got through the National Academies. 1014 00:59:42,912 --> 00:59:44,781 But that was definitely 1015 00:59:46,182 --> 00:59:48,551 following the script written. 1016 00:59:48,585 --> 00:59:53,089 RFA That National Library of Medicine had written an important point 1017 00:59:53,089 --> 00:59:55,858 of all these efforts is that in these distributed queries, 1018 00:59:55,858 --> 00:59:59,462 and I think this is something that we're a revisit in spades 1019 00:59:59,762 --> 01:00:03,766 in the coming years, is given the fact that it is 1020 01:00:04,033 --> 01:00:06,169 unlikely for reasons of privacy, 1021 01:00:06,903 --> 01:00:09,439 property and culture that we're not going to be able 1022 01:00:09,439 --> 01:00:14,577 to generate one huge planetary database of all patients, 1023 01:00:14,711 --> 01:00:19,315 that we're going to have distributed queries that allows us to have 1024 01:00:19,782 --> 01:00:23,953 a statistically well-grounded pursuit of health. 1025 01:00:25,121 --> 01:00:27,690 The understanding that distributed queries. 1026 01:00:27,690 --> 01:00:30,793 Allow us to create the paradigmatic. 1027 01:00:30,960 --> 01:00:33,630 The whole is greater than the sum of the parts results. 1028 01:00:34,163 --> 01:00:38,034 And this again, thanks to the National Library, 1029 01:00:38,034 --> 01:00:40,470 Medicine's funding was amply demonstrated. 1030 01:00:43,206 --> 01:00:44,540 The kind words of 1031 01:00:45,642 --> 01:00:46,476 Dr. Smith that 1032 01:00:46,476 --> 01:00:50,613 reference the eye to be to and yes that that's I'm sure 1033 01:00:50,613 --> 01:00:54,384 when we came up with the name R2-D2 wasn't too far from our thinking, 1034 01:00:54,384 --> 01:00:57,020 but informatics for integrating biology at bedside. 1035 01:00:57,253 --> 01:01:00,323 This is a collection of open source modules that allowed us 1036 01:01:00,323 --> 01:01:03,993 to liberate the data in a multiplicity of different vendors 1037 01:01:03,993 --> 01:01:07,230 electronic health record systems, so that first, for the first time, 1038 01:01:07,997 --> 01:01:11,200 academic quality improvement researchers 1039 01:01:11,467 --> 01:01:17,006 and geneticists could actually access data from the health care system 1040 01:01:17,340 --> 01:01:19,475 and analyze it. 1041 01:01:20,977 --> 01:01:24,614 This this system because it was free 1042 01:01:24,614 --> 01:01:29,352 and open source and funded, by the way people think of it 1043 01:01:29,352 --> 01:01:33,823 because it's funded under the CDC Office of director program of as Dr. 1044 01:01:33,823 --> 01:01:36,192 Zerhouni, think of it as just 1045 01:01:37,193 --> 01:01:40,229 a direct program. 1046 01:01:40,229 --> 01:01:44,333 In fact, the National Library of Medicine stepped in specifically 1047 01:01:44,333 --> 01:01:47,804 to support the HIV two project 1048 01:01:48,037 --> 01:01:50,940 and added their own budget to it in order. 1049 01:01:52,442 --> 01:01:53,943 To fulfill what 1050 01:01:53,943 --> 01:01:57,213 they saw as a realization of their own vision. 1051 01:01:57,847 --> 01:02:00,083 And what we showed was the following. 1052 01:02:00,450 --> 01:02:04,620 And we showed it multiple studies that if you merely used. 1053 01:02:05,655 --> 01:02:09,525 The samples that were drawn every day out of patients 1054 01:02:10,226 --> 01:02:15,631 shown here on the on the x axis is time in weeks. 1055 01:02:15,665 --> 01:02:17,100 So this is weeks. 1056 01:02:17,100 --> 01:02:21,504 And on the x axis is occurring, on the y axis is number of patients. 1057 01:02:22,171 --> 01:02:24,707 And we show that just in one health care system. 1058 01:02:25,641 --> 01:02:27,977 You could accumulate. 1059 01:02:28,611 --> 01:02:31,080 Thousands of samples per year. 1060 01:02:32,415 --> 01:02:36,219 For common diseases like depression or mudslide arthritis. 1061 01:02:36,819 --> 01:02:39,789 And links them to their clinical characterizations. 1062 01:02:39,789 --> 01:02:41,924 An electronic health record. 1063 01:02:41,924 --> 01:02:46,262 Allowing us to do genomic studies at literally 1% of the cost 1064 01:02:46,629 --> 01:02:49,966 and hundred times the speed of. 1065 01:02:52,068 --> 01:02:53,503 The old school method 1066 01:02:53,503 --> 01:02:56,639 of taking decades to complete a cohort. 1067 01:02:57,273 --> 01:02:59,909 And I think this inspired many other efforts 1068 01:03:00,243 --> 01:03:04,413 to use health care systems as living laboratories 1069 01:03:04,680 --> 01:03:09,252 for genomic discovery research, where we use both the biomaterials 1070 01:03:09,552 --> 01:03:14,123 of our patients with their consent and the electronic health record phenotype 1071 01:03:14,223 --> 01:03:17,860 or clinical characterization to drive and accelerate research. 1072 01:03:18,394 --> 01:03:21,430 I have to note parenthetically that many of us as patients 1073 01:03:21,631 --> 01:03:23,633 assumed that the health care system was doing this 1074 01:03:23,633 --> 01:03:25,935 along with learning with every new patient. 1075 01:03:26,402 --> 01:03:28,237 Of course that's not true. 1076 01:03:28,237 --> 01:03:32,275 But this really helped drive for many health care systems. 1077 01:03:32,542 --> 01:03:36,445 Health care systems drive that realization forward. 1078 01:03:41,784 --> 01:03:45,021 I show this diagram that my colleague 1079 01:03:46,189 --> 01:03:49,192 and collaborator Ken Mandell actually generated 1080 01:03:49,525 --> 01:03:52,328 to show a 1081 01:03:52,328 --> 01:03:54,831 interesting outcome 1082 01:03:55,565 --> 01:03:59,969 of that early investment in the personal Internet work. 1083 01:03:59,969 --> 01:04:02,305 Notary and Garden Ping Project. 1084 01:04:02,338 --> 01:04:06,175 I told you about a patient's control of electronic health record. 1085 01:04:07,009 --> 01:04:09,145 And because we developed those technologies, 1086 01:04:09,412 --> 01:04:12,315 we were very prepared in 2009 1087 01:04:12,849 --> 01:04:16,652 when President Obama had announced the high tech 1088 01:04:16,652 --> 01:04:19,522 act to actually propose in the human genome medicine, 1089 01:04:19,822 --> 01:04:24,627 the somewhat impertinent suggestion, well, why can't health I.T. 1090 01:04:24,627 --> 01:04:28,998 be more like the iPhone if I don't like my camera app 1091 01:04:29,165 --> 01:04:31,934 or I don't like my. 1092 01:04:34,170 --> 01:04:35,004 Mapping app. 1093 01:04:35,004 --> 01:04:37,173 I can download a new one and substitute it 1094 01:04:37,807 --> 01:04:43,079 not so for a order entry system where I have to replace the whole system. 1095 01:04:43,346 --> 01:04:45,781 So we ask why could there not be such modularity? 1096 01:04:46,082 --> 01:04:47,884 And the government actually 1097 01:04:49,352 --> 01:04:50,786 supported 1098 01:04:51,387 --> 01:04:53,689 that question by investing in us. 1099 01:04:54,123 --> 01:04:57,693 As part of the own sees the Office of National Coordinators 1100 01:04:57,693 --> 01:05:01,297 funding under President Obama's direction of 1101 01:05:02,798 --> 01:05:05,268 these strategic initiatives. 1102 01:05:05,468 --> 01:05:09,906 And that led to something called the Smart on Fire Project. 1103 01:05:10,172 --> 01:05:13,409 This is a project that's created an application programing interface 1104 01:05:13,542 --> 01:05:16,712 that was independent of the underlying electronics health record vendor. 1105 01:05:16,979 --> 01:05:19,982 It was adopted by multiple electronic health record vendors, 1106 01:05:20,249 --> 01:05:25,655 including the leading ones, so that you could have a common access point to data. 1107 01:05:26,555 --> 01:05:29,025 And in a great example of doctors 1108 01:05:29,292 --> 01:05:33,529 leading the charge, in the sense of Dr. 1109 01:05:33,529 --> 01:05:36,599 Limberg and Dr. 1110 01:05:36,599 --> 01:05:39,168 Barnett, we had two doctors, 1111 01:05:41,037 --> 01:05:45,241 Dr. Josh Mandel now at Microsoft, and Dr. 1112 01:05:45,441 --> 01:05:48,344 Ricky Bloomfield now at Apple Computer, 1113 01:05:48,678 --> 01:05:51,213 who actually led the 1114 01:05:52,281 --> 01:05:54,717 migration of that 1115 01:05:55,351 --> 01:05:57,820 initial API into a common standard 1116 01:05:58,621 --> 01:06:02,425 that it was now part of the 21st Century Cures Act that Congress passed. 1117 01:06:03,526 --> 01:06:05,861 And that Apple 1118 01:06:05,861 --> 01:06:08,331 made part of its Apple health 1119 01:06:09,398 --> 01:06:12,435 technology stack so that now today patients 1120 01:06:13,602 --> 01:06:15,638 can access through their iPhones 1121 01:06:15,771 --> 01:06:19,275 their data from over 800 hospitals and growing of thousands. 1122 01:06:19,275 --> 01:06:24,613 And there is for the Android platform a similar effort going forward 1123 01:06:24,847 --> 01:06:28,684 so that we already have tens of millions of Americans who can access their data, 1124 01:06:28,684 --> 01:06:29,285 their labs, 1125 01:06:29,285 --> 01:06:34,056 their medications, their procedures in ways that were previously not possible. 1126 01:06:34,357 --> 01:06:38,194 And so and this is under their control, and they can actually choose 1127 01:06:38,194 --> 01:06:39,795 to share that data with others. 1128 01:06:39,795 --> 01:06:43,299 So that's a pretty long reach for 1129 01:06:44,367 --> 01:06:45,701 efforts that Dr. 1130 01:06:45,701 --> 01:06:49,538 Lindbergh started back in the 1990s. 1131 01:06:49,538 --> 01:06:52,842 And it's just the beginning. 1132 01:06:53,142 --> 01:06:55,177 I mentioned that 1133 01:06:55,177 --> 01:06:59,148 trust was at an all time high back when Dr. 1134 01:06:59,148 --> 01:07:01,917 Lindbergh started his leadership of national medicine. 1135 01:07:02,618 --> 01:07:07,923 Unfortunately, there's been a collapse of lead of trust and 1136 01:07:09,625 --> 01:07:11,227 trust in 1137 01:07:11,227 --> 01:07:15,698 expertize and leadership across multiple domains. 1138 01:07:16,599 --> 01:07:20,669 And I want to point out that even before COVID way before COVID, 1139 01:07:20,703 --> 01:07:23,739 this study done in 2013, 1140 01:07:24,273 --> 01:07:26,942 in the JAMA in JAMA internal medicine, 1141 01:07:27,543 --> 01:07:30,046 I found it very surprising at the time, but 1142 01:07:30,046 --> 01:07:32,148 it ended up being. 1143 01:07:33,182 --> 01:07:34,350 Predictive. 1144 01:07:34,450 --> 01:07:37,319 And this was a study looking at how consumers 1145 01:07:38,788 --> 01:07:42,158 perceived favorable or unfavorable, 1146 01:07:42,391 --> 01:07:45,061 different uses of their data. 1147 01:07:45,961 --> 01:07:50,032 And I don't think we would be surprised to hear 1148 01:07:50,332 --> 01:07:52,334 that because of their history 1149 01:07:54,070 --> 01:07:55,638 with the health care system. 1150 01:07:55,638 --> 01:07:59,275 African-Americans, for example, were less trusting of various 1151 01:08:00,476 --> 01:08:02,578 users of their data 1152 01:08:02,578 --> 01:08:04,880 than those of European origin. 1153 01:08:05,581 --> 01:08:08,250 What was surprising was that across all ethnicities, 1154 01:08:09,018 --> 01:08:12,521 there was a high degree of trust for the doctors using the data. 1155 01:08:13,823 --> 01:08:17,526 And not surprisingly, there was a large amount of distrust 1156 01:08:17,526 --> 01:08:22,498 of commercial use by drug companies or insurance companies of data. 1157 01:08:22,965 --> 01:08:25,768 But what surprised me was that. 1158 01:08:27,103 --> 01:08:29,105 Public health was also 1159 01:08:29,405 --> 01:08:34,343 seen as a less trusted user of their data, 1160 01:08:35,111 --> 01:08:37,480 patient data, than the doctors. 1161 01:08:38,380 --> 01:08:41,550 And I think that's a problem that we have to deal with. 1162 01:08:41,684 --> 01:08:45,254 And this problem only got accentuated 1163 01:08:45,654 --> 01:08:48,691 by the pandemic. 1164 01:08:49,158 --> 01:08:52,595 And the leadership of the CDC has acknowledged 1165 01:08:53,028 --> 01:08:56,565 that we have a problem here and they have undertaken 1166 01:08:57,166 --> 01:09:03,239 a massive rethinking of how we communicate and how we present data 1167 01:09:03,506 --> 01:09:06,175 so that we can actually restore confidence. 1168 01:09:06,609 --> 01:09:09,578 And I do believe that. 1169 01:09:11,180 --> 01:09:12,481 We will see historically. 1170 01:09:12,481 --> 01:09:16,018 We will see historically that we went from high confidence 1171 01:09:16,018 --> 01:09:19,455 in the 1980s to low confidence currently. 1172 01:09:19,722 --> 01:09:23,893 But as we develop along the path that Dr. 1173 01:09:23,893 --> 01:09:28,964 Lindbergh laid out for us, better access to the primary data, 1174 01:09:29,198 --> 01:09:32,101 allowing a rich ecosystem, a reinterpretation, 1175 01:09:32,101 --> 01:09:35,738 a reanalysis that there's going to be a regrowth. 1176 01:09:37,106 --> 01:09:38,474 Of the faith 1177 01:09:38,474 --> 01:09:43,045 and the expertize in expertize and in data 1178 01:09:43,045 --> 01:09:46,282 driven analysis. 1179 01:09:46,282 --> 01:09:48,817 So what is the way forward? 1180 01:09:49,885 --> 01:09:52,021 How do we go from here? 1181 01:09:54,723 --> 01:09:56,792 So one path is clearly 1182 01:09:57,726 --> 01:10:01,230 just starting, which is the CDC is really revisiting 1183 01:10:01,297 --> 01:10:05,801 how it looks at the aggregate of data for public health 1184 01:10:06,001 --> 01:10:08,904 as gathered from various health care systems. 1185 01:10:09,071 --> 01:10:12,074 And by the way, as a point of pride, 1186 01:10:13,609 --> 01:10:16,312 I want to point out that those of you who have used 1187 01:10:16,812 --> 01:10:20,149 QR codes in various states from Massachusetts to 1188 01:10:21,350 --> 01:10:25,554 the to California documenting your vaccination, are actually using smart 1189 01:10:25,554 --> 01:10:30,326 inspired technology that, again, Apple, Microsoft and others helped 1190 01:10:30,893 --> 01:10:33,896 push into the public domain. 1191 01:10:34,830 --> 01:10:36,799 There is another alternative 1192 01:10:36,799 --> 01:10:40,936 which may happen and looks like it's happening, 1193 01:10:40,936 --> 01:10:45,274 which is large data companies are going to step in. 1194 01:10:45,908 --> 01:10:47,843 And this is 1195 01:10:49,278 --> 01:10:49,645 a new 1196 01:10:49,645 --> 01:10:53,482 story about Amazon acquiring one medical 1197 01:10:53,782 --> 01:10:58,754 a large health care distributed concierge like health care system. 1198 01:10:59,088 --> 01:11:02,958 So now Amazon, in addition to having access to 1199 01:11:04,093 --> 01:11:06,795 the widgets and movies that you buy, will also, 1200 01:11:07,229 --> 01:11:11,700 for a certain group of patients, know a lot about their health care status. 1201 01:11:12,701 --> 01:11:15,771 Amazon also has 1202 01:11:15,971 --> 01:11:19,942 pharmacies in several of its Wholefoods stores 1203 01:11:20,242 --> 01:11:22,378 and also has a 1204 01:11:24,413 --> 01:11:27,049 pharmaceutical delivery service. 1205 01:11:27,049 --> 01:11:31,420 And they also have a polypill service 1206 01:11:31,987 --> 01:11:33,956 that a recent New England Journal of Medicine, 1207 01:11:33,956 --> 01:11:37,259 talking about different people show has been very effective, actually reducing 1208 01:11:37,793 --> 01:11:40,496 disease. So. 1209 01:11:40,796 --> 01:11:44,400 Caution to the academic health centers or commercial 1210 01:11:44,433 --> 01:11:46,935 or community health care centers. 1211 01:11:48,971 --> 01:11:50,205 The notion of the power 1212 01:11:50,205 --> 01:11:53,075 of data enabling better decision making. 1213 01:11:53,342 --> 01:11:56,145 It's not restricted to. 1214 01:11:56,145 --> 01:11:59,148 Just the conventional health care system. 1215 01:11:59,415 --> 01:12:03,052 But large data players have already figured out how to. 1216 01:12:04,853 --> 01:12:08,724 Commoditize and add value to individuals. 1217 01:12:08,724 --> 01:12:10,993 Data are jumping into the fray. 1218 01:12:13,629 --> 01:12:16,498 Apple Computer similarly to the fray. 1219 01:12:16,732 --> 01:12:21,737 I have to say, they have an impressive model of privacy 1220 01:12:21,737 --> 01:12:25,207 where any data that I described in the Apple 1221 01:12:25,207 --> 01:12:28,577 health record is actually not accessible to them or searchable by them. 1222 01:12:28,610 --> 01:12:31,580 It remains only under patient control. 1223 01:12:33,182 --> 01:12:37,686 Google has many important efforts in this space 1224 01:12:37,853 --> 01:12:41,323 and multiple relationships with large health care systems to help them 1225 01:12:41,957 --> 01:12:44,893 apply knowledge, discovery and 1226 01:12:46,061 --> 01:12:49,231 and clinical management 1227 01:12:49,431 --> 01:12:52,968 to these large databases that they have developed. 1228 01:12:55,771 --> 01:12:57,506 There is an alternative model, 1229 01:12:57,506 --> 01:13:00,809 one I happen to like a lot, which is Consumer Reports. 1230 01:13:01,610 --> 01:13:05,247 Consumer Reports is a nonprofit agency and. 1231 01:13:06,382 --> 01:13:08,417 They are. 1232 01:13:08,751 --> 01:13:11,053 Have really only one 1233 01:13:11,053 --> 01:13:13,856 customer, the consumer, and they rate 1234 01:13:15,357 --> 01:13:16,992 various. 1235 01:13:18,327 --> 01:13:19,762 Household. 1236 01:13:20,095 --> 01:13:22,564 Or automotive products. 1237 01:13:22,564 --> 01:13:25,234 And give you some sense 1238 01:13:25,234 --> 01:13:28,270 of the best dollar performance tradeoff. 1239 01:13:29,972 --> 01:13:31,573 Would be, would we be so lucky 1240 01:13:31,573 --> 01:13:37,179 to have a comparison of all the checkpoint inhibitors 1241 01:13:37,379 --> 01:13:41,283 in such a fashion or of all the heart medications? 1242 01:13:41,550 --> 01:13:45,421 Wouldn't it be great to see which one give you the best efficacy? 1243 01:13:46,655 --> 01:13:50,025 Now, unfortunately, Consumer Reports does not have that 1244 01:13:50,893 --> 01:13:53,162 role, does not see himself taking on that 1245 01:13:53,162 --> 01:13:53,829 role. 1246 01:13:57,366 --> 01:13:58,734 The FDA, 1247 01:13:58,734 --> 01:14:01,170 unfortunately, also doesn't see itself taking on the role 1248 01:14:01,437 --> 01:14:05,908 if it validates drugs as meeting its endpoints. 1249 01:14:06,141 --> 01:14:07,409 But it's not. 1250 01:14:07,776 --> 01:14:09,878 Running a Consumer Reports like function 1251 01:14:10,212 --> 01:14:13,048 and where it's, you know, looking at 1252 01:14:13,048 --> 01:14:15,884 how do we compare the top ten 1253 01:14:16,919 --> 01:14:20,856 cancer drugs that's not in the FDA's remit, 1254 01:14:21,623 --> 01:14:25,461 although they do a fine job of evaluating individual 1255 01:14:26,128 --> 01:14:30,632 agents and devices under the terms of the trials 1256 01:14:31,133 --> 01:14:33,702 that clinicaltrials.gov specify. 1257 01:14:36,905 --> 01:14:38,207 The National Library of Medicine. 1258 01:14:39,842 --> 01:14:41,810 Actually does a pretty good job 1259 01:14:41,810 --> 01:14:46,281 of providing through access from clinicaltrials.gov 1260 01:14:46,615 --> 01:14:51,687 to the literature of trials, to lecture a basic science to the actual 1261 01:14:51,687 --> 01:14:58,227 underlying data, provides access to all of those data and permits 1262 01:14:58,660 --> 01:15:03,265 a multiplicity of private, nonprofit and commercial efforts 1263 01:15:03,432 --> 01:15:06,134 to try to make sense of that for the consumer. 1264 01:15:06,702 --> 01:15:10,973 But it does not actually do that job of synthesizing. 1265 01:15:12,040 --> 01:15:14,743 All that data for the individual. 1266 01:15:14,743 --> 01:15:18,647 It has chosen not to for a variety of reasons, 1267 01:15:18,881 --> 01:15:21,917 and as one would wonder, whether it's 1268 01:15:21,917 --> 01:15:25,454 even possible for it to do it for the multiplicity of purposes. 1269 01:15:25,687 --> 01:15:30,025 I think it's done a fantastic job for the task 1270 01:15:30,025 --> 01:15:33,962 it has set itself for, which is to make the data maximally available 1271 01:15:34,029 --> 01:15:38,667 to the largest group of individuals and notably the larger public. 1272 01:15:40,736 --> 01:15:43,338 So I would actually like to argue that Dr. 1273 01:15:43,338 --> 01:15:46,241 Lindbergh and this is going to be in closing, that Dr. 1274 01:15:46,241 --> 01:15:50,746 Lindbergh actually showed us the real way forward and. 1275 01:15:51,713 --> 01:15:54,116 I'm going to cite. 1276 01:15:55,350 --> 01:15:57,886 I guess myself and Jeremy Berg 1277 01:15:58,086 --> 01:16:01,890 in an article that we published in Science In Memoriam 1278 01:16:02,090 --> 01:16:07,563 for Donald Abe Limber, and I was writing with this with Jeremy. 1279 01:16:07,563 --> 01:16:11,833 I had the opportunity to read through many transcripts. 1280 01:16:12,801 --> 01:16:13,802 Of interviews with Dr. 1281 01:16:13,802 --> 01:16:18,473 Limberg and many of which were great music because the man actually 1282 01:16:18,473 --> 01:16:21,176 did have a wry sense of wry and dry sense of humor. 1283 01:16:22,844 --> 01:16:25,581 But this one is a really good one. 1284 01:16:26,582 --> 01:16:30,586 Early on, Don recognized that medicine needed to be more data driven. 1285 01:16:31,553 --> 01:16:34,356 During his residency training, his data driven approach 1286 01:16:34,523 --> 01:16:37,926 to medicine landed him in hot water with a surgery department. 1287 01:16:38,727 --> 01:16:42,564 When he showed the silicone that the silicone used for cardiac bypass 1288 01:16:42,998 --> 01:16:48,270 was causing extensive embolization, that means bits of blood and gunk 1289 01:16:48,537 --> 01:16:51,873 going through your arteries, causing stroke and death. 1290 01:16:52,474 --> 01:16:57,946 Only upon showing the surgeon's imaging data was he able to change their practice. 1291 01:16:58,914 --> 01:17:02,884 So. There's many things that are interesting about this story. 1292 01:17:03,719 --> 01:17:06,688 A he had a finding 1293 01:17:07,456 --> 01:17:11,426 that implicated a patient health. B. 1294 01:17:12,394 --> 01:17:16,098 He didn't just say, Hey, you idiots. 1295 01:17:16,298 --> 01:17:18,266 You're hurting your patients. No. 1296 01:17:18,266 --> 01:17:19,401 He met with them. 1297 01:17:19,401 --> 01:17:23,171 He showed them the primary data and convinced them through their own 1298 01:17:23,171 --> 01:17:27,743 conscience and the visibility of data, what the right thing is to do. 1299 01:17:28,410 --> 01:17:30,846 But the part that's less obvious 1300 01:17:31,680 --> 01:17:34,483 is this went through the mind of Dr. 1301 01:17:34,483 --> 01:17:35,584 Limberg. 1302 01:17:36,084 --> 01:17:39,888 The doctor, the care for the patient. 1303 01:17:41,189 --> 01:17:43,458 And I do think. 1304 01:17:43,558 --> 01:17:46,061 That what we will see in the future. 1305 01:17:46,061 --> 01:17:48,563 The future Don Lindbergh's of the world, 1306 01:17:48,563 --> 01:17:51,700 whether they have the title M.D. 1307 01:17:52,200 --> 01:17:56,471 or nurse practitioner or physician associate or either. 1308 01:17:56,905 --> 01:18:00,542 Or maybe some other new term that we have yet to determine. 1309 01:18:01,109 --> 01:18:06,281 There will be this expert who understands the biology, the medicine, 1310 01:18:06,581 --> 01:18:09,685 the clinical concerns of the patient 1311 01:18:10,419 --> 01:18:13,155 and brings it together. 1312 01:18:13,155 --> 01:18:14,389 In full understanding. 1313 01:18:15,924 --> 01:18:17,759 And I have to say, 1314 01:18:17,759 --> 01:18:20,195 since it was 2022, assisted 1315 01:18:20,696 --> 01:18:23,632 by machine learning. 1316 01:18:23,632 --> 01:18:25,600 Agents that look at across 1317 01:18:25,600 --> 01:18:27,769 the entire corpus of. 1318 01:18:29,037 --> 01:18:31,440 Human knowledge, medical knowledge, particularly 1319 01:18:31,440 --> 01:18:35,210 including the National Library of Medicine, to bring to that expert. 1320 01:18:36,445 --> 01:18:38,980 In a caring, patient, specific way. 1321 01:18:39,247 --> 01:18:41,750 What's the right thing to do? 1322 01:18:41,750 --> 01:18:43,852 I do think that 1323 01:18:44,686 --> 01:18:48,323 there's huge value in the health professional. 1324 01:18:48,457 --> 01:18:52,194 I'll use the term doctor as a useful handle as a doctor 1325 01:18:52,194 --> 01:18:55,497 who knows you, who knows what your preferences are, 1326 01:18:56,665 --> 01:19:00,135 truly understands literature, who makes available to themselves 1327 01:19:00,969 --> 01:19:03,839 the knowledge of science, 1328 01:19:04,506 --> 01:19:06,708 and who brings to you that expert judgment? 1329 01:19:06,908 --> 01:19:10,412 I think that is the place that we are going and in doing 1330 01:19:10,612 --> 01:19:12,848 and going in that direction. I. 1331 01:19:14,049 --> 01:19:16,151 Do hope and I trust 1332 01:19:16,418 --> 01:19:19,488 that we're heading in the direction that Dr. 1333 01:19:19,488 --> 01:19:23,525 Limberg so ably started us so many years ago. 1334 01:19:24,059 --> 01:19:25,227 Thank you for your attention. 1335 01:19:25,227 --> 01:19:26,661 I hope I did not 1336 01:19:28,363 --> 01:19:30,532 bore and 1337 01:19:30,532 --> 01:19:33,835 I'm glad to take any questions if there's any time 1338 01:19:33,835 --> 01:19:34,803 remaining. 1339 01:19:38,140 --> 01:19:38,774 Thank you, Dr. 1340 01:19:38,774 --> 01:19:41,409 Galani, for that outstanding presentation. 1341 01:19:41,710 --> 01:19:44,980 Very thought provoking, of course. 1342 01:19:45,313 --> 01:19:47,048 So those of you who are watching 1343 01:19:47,048 --> 01:19:51,153 look for the live feedback button under your video stream. 1344 01:19:51,153 --> 01:19:55,457 And that's the button you can use to send questions or comments to Dr. 1345 01:19:55,457 --> 01:19:58,727 Carney via me. 1346 01:19:58,727 --> 01:20:00,462 We do have one comment that's come in. 1347 01:20:00,462 --> 01:20:02,998 In communicating with patients 1348 01:20:03,532 --> 01:20:06,401 either individually or on mass, communicating 1349 01:20:06,468 --> 01:20:10,472 or caring about them is essential to their reception of your message. 1350 01:20:11,139 --> 01:20:15,410 I was privileged to know Don Wennberg throughout my entire association with NLM, 1351 01:20:15,410 --> 01:20:17,445 beginning in 1979 1352 01:20:17,445 --> 01:20:20,649 when he was on the board of Scientific Counselors of the Lister Hill Center. 1353 01:20:21,249 --> 01:20:25,086 Don communicated caring in every interaction I had with him 1354 01:20:25,420 --> 01:20:28,924 and he ever saw and ever saw him have with others. 1355 01:20:29,191 --> 01:20:32,861 He may not have agreed with everyone, but he was never disagreeable. 1356 01:20:32,994 --> 01:20:37,332 I believe that that was essential to why we are honoring him today 1357 01:20:37,332 --> 01:20:38,466 and why, of course, Dr. 1358 01:20:38,466 --> 01:20:41,002 Varney, in the way that you did, honoring Dr. 1359 01:20:41,002 --> 01:20:43,038 Lindbergh's scientific and leadership legacy. 1360 01:20:43,605 --> 01:20:45,340 So sharing that comment. 1361 01:20:45,340 --> 01:20:50,245 So that's a terribly eloquent common and then a far better job 1362 01:20:50,245 --> 01:20:54,349 than I did of summarizing the fact that a. 1363 01:20:56,218 --> 01:20:57,986 Did not advance. 1364 01:20:57,986 --> 01:21:02,757 He did not advance his views by confrontation or by 1365 01:21:03,792 --> 01:21:07,696 piling on instead by persuasion and data. 1366 01:21:08,230 --> 01:21:10,899 And absolutely, yes, there's nothing 1367 01:21:10,899 --> 01:21:13,268 that substitutes for knowing that someone cares about you. 1368 01:21:13,902 --> 01:21:17,939 And it's that clinical relationship that I think that relationship between 1369 01:21:18,206 --> 01:21:22,744 the care provider and the recipient of that care, that relationship 1370 01:21:22,944 --> 01:21:27,182 which has to be data driven because it's it's not enough to be caring. 1371 01:21:27,515 --> 01:21:30,852 You have to be caring and truly expert and up to date. 1372 01:21:31,253 --> 01:21:33,588 And in fact, back in the 1980s, 1373 01:21:34,189 --> 01:21:36,791 I remember being taught by medical in my medical school 1374 01:21:37,025 --> 01:21:41,162 that unfortunately, many well known doctors were famous and respected, 1375 01:21:41,162 --> 01:21:47,135 even though they were not stated that informed because they were charming 1376 01:21:47,402 --> 01:21:50,438 and persuasive, but they did not have the underlying science. 1377 01:21:50,472 --> 01:21:51,539 We need both. 1378 01:21:51,539 --> 01:21:55,844 We need a data driven expert who is genuinely caring, 1379 01:21:56,711 --> 01:22:01,349 and that's going to be the essence of the biomedical profession. 1380 01:22:02,918 --> 01:22:04,853 For its future and otherwise. 1381 01:22:04,853 --> 01:22:08,023 I will predict and I'm not predicting this because I don't think we'll go there. 1382 01:22:08,590 --> 01:22:11,259 There will not be a medical profession if we don't actually 1383 01:22:12,661 --> 01:22:15,597 grab that challenge of being trusted 1384 01:22:16,231 --> 01:22:18,300 or being dedicated to the patient's 1385 01:22:19,834 --> 01:22:23,004 well-being, making that clear where our 1386 01:22:24,172 --> 01:22:28,443 priorities are, and demonstrating that we are truly data driven. 1387 01:22:28,710 --> 01:22:30,645 So that's a very insightful comment. 1388 01:22:30,645 --> 01:22:31,479 Thank you. 1389 01:22:32,180 --> 01:22:34,082 Thank you. Yes, indeed. 1390 01:22:34,082 --> 01:22:35,650 Another comment has come in. 1391 01:22:35,650 --> 01:22:38,853 Dr. Lundberg was also never condescending in manner 1392 01:22:38,853 --> 01:22:41,923 when he shared his knowledge and expertize as Dr. 1393 01:22:41,923 --> 01:22:44,426 Kahane's last anecdote illustrated. 1394 01:22:45,593 --> 01:22:48,897 So further further to your point. 1395 01:22:48,897 --> 01:22:52,300 How dare you make that not? Yes. 1396 01:22:52,300 --> 01:22:55,403 Condescending is just. 1397 01:22:55,503 --> 01:22:58,606 And in fact, condescension, I would 1398 01:22:58,606 --> 01:23:01,443 say, is probably one of the dominant notes of Twitter 1399 01:23:01,710 --> 01:23:06,147 and probably among its most destructive, I think condescension, 1400 01:23:08,083 --> 01:23:11,453 which is often unearned and always wrong, 1401 01:23:11,853 --> 01:23:15,457 is something that you never, never, 1402 01:23:15,457 --> 01:23:17,559 ever saw in a leader 1403 01:23:18,593 --> 01:23:20,462 such as Don, Dr. Lindbergh. 1404 01:23:20,462 --> 01:23:25,934 And I think any hint of it is incredibly destructive 1405 01:23:26,201 --> 01:23:29,304 to the tissue of trust that we have to reestablish. 1406 01:23:30,872 --> 01:23:31,506 Yes, indeed. 1407 01:23:31,506 --> 01:23:35,443 And much of social media is confrontational and divisive 1408 01:23:35,777 --> 01:23:40,482 and only only reinforces that condescension in the worst way. 1409 01:23:40,682 --> 01:23:42,017 Unfortunately. 1410 01:23:43,318 --> 01:23:44,586 Can you tell us? 1411 01:23:44,586 --> 01:23:48,623 Questions come in about the medical humanities, the way in which 1412 01:23:49,924 --> 01:23:51,926 the medical humanities can serve 1413 01:23:51,926 --> 01:23:57,766 as a vehicle to educate practitioners of medicine 1414 01:23:58,433 --> 01:24:01,970 to to augment their empathy to patients. 1415 01:24:02,337 --> 01:24:04,973 The comment is really a comment that's come in that can you speak 1416 01:24:04,973 --> 01:24:08,576 to the current state, perhaps of the medical humanities 1417 01:24:08,576 --> 01:24:12,981 and in the advancement of the culture of medicine that you described? 1418 01:24:14,549 --> 01:24:16,551 That's a very insightful question. 1419 01:24:16,885 --> 01:24:20,355 I will first answer it tangentially and then 1420 01:24:21,956 --> 01:24:23,024 the center. 1421 01:24:23,391 --> 01:24:27,962 I think that's medical humanities and is art and incredibly point. 1422 01:24:28,430 --> 01:24:31,232 First of all in the history of medicine. 1423 01:24:31,232 --> 01:24:33,701 We like to think how modern we are, but 1424 01:24:34,002 --> 01:24:36,805 much of what we experience has happened before. 1425 01:24:37,238 --> 01:24:39,808 So, for example, understanding what 1426 01:24:39,941 --> 01:24:45,713 a revolution antibiotics was in the 1940s, 1427 01:24:46,114 --> 01:24:49,784 but then how there was arrests of multiple antibiotics 1428 01:24:49,918 --> 01:24:54,689 with similar properties and how claims were made for certain antibiotics 1429 01:24:54,889 --> 01:25:00,161 being different than other antibiotics, which were not actually data driven . 1430 01:25:00,161 --> 01:25:05,100 Understanding that history, I think would give will give the doctors 1431 01:25:05,100 --> 01:25:10,171 who understand it certain amount of humility and looking at current 1432 01:25:10,738 --> 01:25:12,841 trials, let's say about state of the art. 1433 01:25:14,909 --> 01:25:18,346 Cancer or viral therapies. 1434 01:25:18,580 --> 01:25:21,983 And so I think understanding the way medical progress has 1435 01:25:23,852 --> 01:25:25,954 humanity is such as the history of medicine 1436 01:25:26,421 --> 01:25:30,291 will really give us appropriate 1437 01:25:31,459 --> 01:25:32,327 humility. 1438 01:25:32,327 --> 01:25:35,563 And that in this broad march forward of science, 1439 01:25:35,930 --> 01:25:38,600 we've got to the individual patient relationship. 1440 01:25:39,601 --> 01:25:42,070 I think understanding how much. 1441 01:25:43,671 --> 01:25:45,406 Value patients get. 1442 01:25:45,406 --> 01:25:49,144 And when I say value, I mean not just reassurance 1443 01:25:49,477 --> 01:25:52,046 but actual positive health outcomes 1444 01:25:52,547 --> 01:25:55,617 are obtained out of a vital. 1445 01:25:56,584 --> 01:25:59,521 And trusting and informed relationship 1446 01:25:59,954 --> 01:26:02,857 above and beyond any scientific breakthrough, 1447 01:26:02,857 --> 01:26:05,493 above and beyond any 1448 01:26:06,861 --> 01:26:08,196 specific therapies. 1449 01:26:08,196 --> 01:26:10,698 Understanding that from the medical community, humanities 1450 01:26:11,032 --> 01:26:14,169 and the value of that human interaction. 1451 01:26:14,335 --> 01:26:16,871 And I'm not even talking about the important placebo effects. 1452 01:26:17,305 --> 01:26:20,341 I'm talking about how we actually influence patients 1453 01:26:20,575 --> 01:26:22,744 in ways that are helpful. 1454 01:26:24,345 --> 01:26:27,382 And that change the utilities 1455 01:26:27,382 --> 01:26:29,817 their outcomes in important ways. 1456 01:26:31,286 --> 01:26:33,521 There are few other ways to understand that without 1457 01:26:34,289 --> 01:26:36,491 really engaging with the medical humanities. 1458 01:26:36,758 --> 01:26:41,296 So I could not agree more with the implication of that question. 1459 01:26:42,730 --> 01:26:43,498 Thank you. 1460 01:26:43,798 --> 01:26:48,436 We have time for one more question on the very heels of your response. 1461 01:26:48,937 --> 01:26:52,807 Let me ask it to you, because it is it is a great follow on. 1462 01:26:53,107 --> 01:26:56,377 What are the unintended consequences of patients 1463 01:26:56,377 --> 01:26:59,147 receiving test results before their clinicians? 1464 01:26:59,647 --> 01:27:03,751 My experience, this person writes, is that without the support of content 1465 01:27:03,785 --> 01:27:07,422 of the clinician context, it can be anxiety producing. 1466 01:27:10,091 --> 01:27:13,461 I fully agree and I don't want to get too personal, 1467 01:27:14,028 --> 01:27:20,068 but I remember all too well getting a very, very disturbing 1468 01:27:20,401 --> 01:27:24,372 report through a portal of result 1469 01:27:24,372 --> 01:27:28,142 on a family member and. 1470 01:27:28,343 --> 01:27:29,844 Unfortunately understanding its meaning 1471 01:27:29,844 --> 01:27:32,380 and it was very, very depressing. 1472 01:27:32,914 --> 01:27:35,617 And if I had not been a medical professional, 1473 01:27:36,384 --> 01:27:38,753 I'm not sure what I would have done with it. 1474 01:27:39,320 --> 01:27:44,726 And there is there are many opportunities for misreading of those results. 1475 01:27:46,261 --> 01:27:48,329 There is no doubt about that. 1476 01:27:48,329 --> 01:27:53,101 But I think we have to always you know, there's in medicine, we always worry about 1477 01:27:53,101 --> 01:27:57,071 false positives and false negatives and it comes down to a trade off. 1478 01:27:57,939 --> 01:27:59,941 And if I would look it. 1479 01:28:00,208 --> 01:28:03,945 There's been so much that's been done unintentionally 1480 01:28:04,479 --> 01:28:07,415 by not in a bad way, by not communicating 1481 01:28:07,415 --> 01:28:10,451 in a timely way with patients. 1482 01:28:10,652 --> 01:28:11,786 That. 1483 01:28:14,622 --> 01:28:17,025 That, for example, 1484 01:28:17,025 --> 01:28:18,526 is a slightly amusing example. 1485 01:28:18,526 --> 01:28:21,296 My doctor took my 1486 01:28:22,764 --> 01:28:25,967 lipid levels in anticipation of deciding 1487 01:28:25,967 --> 01:28:29,103 whether or not to do a STEM intervention 1488 01:28:29,771 --> 01:28:33,641 and basically never looked up the results because he got busy. 1489 01:28:34,108 --> 01:28:36,811 But I looked at my own results and I was able to close the loop with him. 1490 01:28:37,845 --> 01:28:39,847 That happens all the time. 1491 01:28:39,847 --> 01:28:41,416 And I think on balance. 1492 01:28:42,450 --> 01:28:43,451 We're better off 1493 01:28:43,451 --> 01:28:47,188 having more and faster access to our data than not. 1494 01:28:47,722 --> 01:28:51,492 Now, that's not a stretch to say we have to accept the way things are. 1495 01:28:51,759 --> 01:28:53,428 I do think. 1496 01:28:53,461 --> 01:28:55,763 That in a smarter. 1497 01:28:57,865 --> 01:29:00,068 Adrian, the health care system, 1498 01:29:00,068 --> 01:29:02,103 if there was a meaningful result 1499 01:29:02,870 --> 01:29:05,807 with possibly dire consequences, 1500 01:29:06,474 --> 01:29:09,377 there would be a many technological means 1501 01:29:09,510 --> 01:29:13,381 to mutely loop in the expert clinician 1502 01:29:13,715 --> 01:29:16,117 to have a conversation with the patient. 1503 01:29:16,751 --> 01:29:19,554 It just so happens that our 1504 01:29:20,788 --> 01:29:23,591 billing oriented. 1505 01:29:24,192 --> 01:29:26,794 Health automation is not oriented that way, 1506 01:29:26,961 --> 01:29:28,629 so it doesn't have to be this way. 1507 01:29:28,629 --> 01:29:32,266 But given the current sum of cards that we've been dealt, 1508 01:29:32,900 --> 01:29:37,805 I would rather err on the side of more faster sharing than less sharing. 1509 01:29:38,172 --> 01:29:42,009 But at the same time, through personal experience, I totally agree. 1510 01:29:42,276 --> 01:29:47,048 We could do far better in providing expert oversight, 1511 01:29:47,415 --> 01:29:52,286 especially in cases of dire information shared with the patient. 1512 01:29:53,321 --> 01:29:54,989 Thank you very much. 1513 01:29:54,989 --> 01:29:56,657 Thank you, Dr. Krone, very much. 1514 01:29:56,657 --> 01:29:59,727 And again, for your outstanding thought provoking presentation. 1515 01:30:00,928 --> 01:30:02,230 We're going to leave it there. 1516 01:30:02,230 --> 01:30:06,401 And on behalf of the National Library Medicine, thank you again very, very much. 1517 01:30:07,068 --> 01:30:08,269 To all of our viewers. 1518 01:30:08,269 --> 01:30:10,271 We're going to take a short break. 1519 01:30:10,271 --> 01:30:14,075 We will reconvene at 10:45 a.m. 1520 01:30:14,075 --> 01:30:14,876 Eastern Time. 1521 01:30:14,876 --> 01:30:17,011 So join us back here in about 15 minutes. 1522 01:30:17,311 --> 01:30:18,446 And we look forward to seeing you. 1523 01:30:18,446 --> 01:30:21,616 Thank you again for joining us this morning and again 1524 01:30:21,949 --> 01:30:23,317 throughout our proceedings. 1525 01:30:23,317 --> 01:30:25,553 If you have a question or comment, please send it to 1526 01:30:26,421 --> 01:30:29,157 to us by the live feedback button underneath the video stream. 1527 01:30:29,557 --> 01:30:32,226 So we're going to take our break and we'll see you back here in 15 minutes. 1528 01:30:32,293 --> 01:30:34,061 Thank you. Thank you again very much. 1529 01:30:50,211 --> 01:30:52,814 Welcome back to the 2022 Lindbergh 1530 01:30:52,814 --> 01:30:56,651 King Lecture and Scientific Symposium here at the National Library of Medicine. 1531 01:30:56,651 --> 01:30:58,419 National Institutes of Health. 1532 01:30:58,419 --> 01:30:59,420 I'm Jeff Resnick. 1533 01:30:59,420 --> 01:31:02,190 I'm chief of the History Medicine Division at the National Library of Medicine 1534 01:31:02,190 --> 01:31:04,959 and have the distinct pleasure of moderating today's proceedings. 1535 01:31:05,693 --> 01:31:09,096 For those of you who are just joining us, please use the live feedback 1536 01:31:09,096 --> 01:31:12,066 button under your video stream to send us questions or comments. 1537 01:31:13,100 --> 01:31:17,505 We're going to proceed now with the first panel of our outstanding program of today 1538 01:31:17,572 --> 01:31:21,409 entitled Lindbergh and the Advancement of Science through Research Training. 1539 01:31:22,310 --> 01:31:23,077 It's my pleasure. 1540 01:31:23,077 --> 01:31:25,580 Now to introduce the chair of this panel, Dr. 1541 01:31:25,580 --> 01:31:29,584 Lucila Honor Machado, who is associate dean for informatics 1542 01:31:29,584 --> 01:31:33,654 and technology at the University of California, San Diego, where she is 1543 01:31:33,654 --> 01:31:38,593 also founding chair of the UCSD Health Department of Biomedical Informatics. 1544 01:31:39,560 --> 01:31:40,428 Previously, Dr. 1545 01:31:40,428 --> 01:31:44,332 Ana machado was on the faculty of Brigham and Women's Hospital, Harvard 1546 01:31:44,332 --> 01:31:48,202 Medical School, and affiliated with the MIT Division of Health. 1547 01:31:49,170 --> 01:31:51,639 Sciences and technology. 1548 01:31:51,639 --> 01:31:54,909 Her own research focuses on privacy, preserving distributed 1549 01:31:54,909 --> 01:31:58,312 analytics for health care and the biomedical sciences. 1550 01:31:58,779 --> 01:32:01,415 In this regard, she directs the patient centered, 1551 01:32:01,415 --> 01:32:04,785 scalable National Network for Effectiveness Research 1552 01:32:05,052 --> 01:32:10,024 and the NIH funded National Center for Biomedical Computing, known as DASH. 1553 01:32:10,758 --> 01:32:13,995 We're honored to welcome her today as chair of our first panel, Dr. 1554 01:32:13,995 --> 01:32:14,762 Ana machado. 1555 01:32:14,762 --> 01:32:18,099 Thank you very much for your valuable time and your engagement with us. 1556 01:32:18,132 --> 01:32:19,834 And I'm going to turn things over to you. 1557 01:32:19,834 --> 01:32:20,568 Thank you. 1558 01:32:21,736 --> 01:32:24,972 Thank you so much for the invitation to moderate this panel. 1559 01:32:25,540 --> 01:32:29,577 As we have just heard from Professor Cohen, his presentation by Dr. 1560 01:32:29,577 --> 01:32:31,913 Lindbergh's legacy is unparalleled. 1561 01:32:32,246 --> 01:32:35,650 And it touched the lives of so many people, so many faculty, 1562 01:32:35,650 --> 01:32:39,387 trainees and professionals in academia, industry and government. 1563 01:32:39,954 --> 01:32:44,225 This panel will address his legacy on the advancement of science 1564 01:32:44,225 --> 01:32:48,930 through research training, and it includes prominent informatics experts 1565 01:32:48,930 --> 01:32:52,733 who are leading impactful initiatives in their institutions in the country 1566 01:32:52,934 --> 01:32:54,402 and in the world. 1567 01:32:54,402 --> 01:32:58,573 Dr. Josh Denny is director of the All of US Research Program NIH 1568 01:32:58,806 --> 01:33:02,209 Flagship Precision Medicine Initiative, and will discuss 1569 01:33:02,209 --> 01:33:06,314 the role of electronic health records in computing medicine in the development 1570 01:33:06,314 --> 01:33:10,351 of an unprecedented resource for scientists everywhere 1571 01:33:10,585 --> 01:33:14,789 who will have free access to genomes, electronic health records and participant 1572 01:33:14,789 --> 01:33:18,859 reported data from the most diverse cohort in the world. 1573 01:33:20,094 --> 01:33:21,729 Dr. Graziella Gonzalez. 1574 01:33:21,729 --> 01:33:23,030 Aaron Enders, professor 1575 01:33:23,030 --> 01:33:26,801 of computational biomedicine at Cedars-Sinai Medical Center. 1576 01:33:27,101 --> 01:33:28,169 We'll speak about Dr. 1577 01:33:28,169 --> 01:33:32,073 Lindbergh's vision and investment in training without many, 1578 01:33:33,574 --> 01:33:37,211 without which many of the speakers might have taken career 1579 01:33:37,211 --> 01:33:40,648 directions much different than they have today. 1580 01:33:41,382 --> 01:33:45,319 Biomedical informatics might not have succeeded as an independent discipline 1581 01:33:45,486 --> 01:33:46,554 if those investments 1582 01:33:46,554 --> 01:33:50,358 were not made at a critical time when computers were just starting 1583 01:33:50,358 --> 01:33:54,095 to become an essential component of health sciences and health care. 1584 01:33:54,996 --> 01:33:57,231 And Dr. Nicholas detonated. 1585 01:33:57,231 --> 01:34:00,768 Associate professor of biomedical informatics at Columbia University 1586 01:34:01,035 --> 01:34:05,373 will speak about how observational data can and has been used for 1587 01:34:05,373 --> 01:34:09,944 biomedical discovery, including the role in generating new hypotheses 1588 01:34:09,944 --> 01:34:13,848 in addition to the known role of testing those hypotheses. 1589 01:34:14,515 --> 01:34:19,186 This distinguished panel consists of a small sample of outstanding researchers 1590 01:34:19,186 --> 01:34:23,257 who benefited from research training at the leading institutions that held 1591 01:34:23,257 --> 01:34:27,461 the prestigious T 15 training grants from the National Library of Medicine. 1592 01:34:28,529 --> 01:34:31,432 Not only those who were recipients of scholarships 1593 01:34:31,432 --> 01:34:35,569 and fellowships from this grants benefited from an alumni investment. 1594 01:34:35,903 --> 01:34:39,840 All their students included benefited from the curriculum, 1595 01:34:39,840 --> 01:34:42,376 the social structure, and from being around 1596 01:34:42,376 --> 01:34:47,081 the exceptional trainees funded by the Teach 15 program such as Dr. 1597 01:34:47,081 --> 01:34:51,252 Gretchen Purcell , Jackson and many other current leaders in the field. 1598 01:34:52,019 --> 01:34:56,991 Our three speakers cover a small portion of what biomedical informatics has become. 1599 01:34:57,458 --> 01:35:01,629 For example, trends for research funding from NLM over the years 1600 01:35:01,629 --> 01:35:06,400 indicate that II artificial intelligence was funded since the eighties, 1601 01:35:06,667 --> 01:35:09,503 and the impacts of electronic health 1602 01:35:09,503 --> 01:35:12,139 records would have on 1603 01:35:12,907 --> 01:35:15,443 health care was anticipated early on. 1604 01:35:15,876 --> 01:35:19,947 This trends are described in a recently highly recommended book about Dr. 1605 01:35:19,947 --> 01:35:25,252 Lindbergh's legacy, edited by Doctors Humphreys, Logan, Miller and SIEGEL 1606 01:35:25,453 --> 01:35:29,957 entitled Transforming Biomedical Informatics and Health Information Access. 1607 01:35:30,424 --> 01:35:32,393 As this book documents, Dr. 1608 01:35:32,393 --> 01:35:36,897 Lindbergh's impact in the field was profound, his legacy lives 1609 01:35:36,897 --> 01:35:40,434 on, and this panel was emblematic of his achievements. 1610 01:35:40,901 --> 01:35:43,804 It is an honor to close this panel, 1611 01:35:44,171 --> 01:35:47,441 and I will introduce our first speaker, who was Dr. 1612 01:35:47,441 --> 01:35:52,012 Josh Denny, chief executive officer of the NIH. 1613 01:35:52,246 --> 01:35:54,115 All of us research program. 1614 01:35:54,115 --> 01:35:57,485 He has been involved in all of us from its inception 1615 01:35:57,785 --> 01:36:01,455 and served as the principal investigator for the all of us data 1616 01:36:01,455 --> 01:36:03,157 and Research Center. 1617 01:36:03,157 --> 01:36:06,060 He's an elected member of the National Academy of Medicine, 1618 01:36:06,060 --> 01:36:09,063 the American Society for Clinical Investigation 1619 01:36:09,063 --> 01:36:11,565 and the American College of Medical Informatics. 1620 01:36:12,233 --> 01:36:14,168 As a physician scientist, Dr. 1621 01:36:14,168 --> 01:36:17,438 Dean is deeply committed to improving patient care 1622 01:36:17,772 --> 01:36:19,874 through the advancement of precision medicine. 1623 01:36:20,307 --> 01:36:23,844 Before joining NIH, he was both a practicing internist 1624 01:36:23,844 --> 01:36:27,281 and a researcher was professor of biomedical informatics 1625 01:36:27,281 --> 01:36:30,885 and medicine at Vanderbilt University Medical Center. 1626 01:36:32,019 --> 01:36:35,689 His research interests include use of electronic health records 1627 01:36:35,689 --> 01:36:39,360 and genomics to better understand disease and drug response. 1628 01:36:39,760 --> 01:36:44,365 He also led efforts implementing precision medicine to improve patient outcomes. 1629 01:36:44,765 --> 01:36:48,636 Joshua was a leader in the development of genome wide association 1630 01:36:48,803 --> 01:36:52,106 studies for use in phenotype risk scores. 1631 01:36:52,506 --> 01:36:53,607 Please welcome Dr. 1632 01:36:53,607 --> 01:36:57,344 Denny, who will speak about a legacy of computing medicine. 1633 01:36:57,344 --> 01:36:59,780 Accelerating precision medicine using. 1634 01:37:02,783 --> 01:37:04,618 Thank you so much, Lucille. 1635 01:37:04,618 --> 01:37:10,457 It's a real pleasure to come to you today and share some stories from my life 1636 01:37:10,457 --> 01:37:14,361 and how I see the transformational leadership of Dr. 1637 01:37:14,361 --> 01:37:18,599 Lynn really impacting and setting a course for a future of precision 1638 01:37:18,599 --> 01:37:23,637 medicine that can really impact people, people at really the point of care 1639 01:37:23,771 --> 01:37:27,775 and advancing knowledge and learning for really every patient encounter. 1640 01:37:28,042 --> 01:37:31,045 And, you know, if we think back at the time of where we were, 1641 01:37:31,745 --> 01:37:35,382 we really weren't there this time before his leadership. 1642 01:37:35,382 --> 01:37:40,154 And so, as we still have mentioned also, I just want to recognize 1643 01:37:40,154 --> 01:37:43,791 I was one of those 15 trainees as well 1644 01:37:43,791 --> 01:37:48,162 and the support of the innovation and idea 1645 01:37:48,162 --> 01:37:52,166 that doctors could engage following the model of Dr. 1646 01:37:52,166 --> 01:37:55,536 Lundberg himself and so many others, trained through these training programs 1647 01:37:55,836 --> 01:38:00,174 and become leaders in intersections of computer science, information 1648 01:38:00,641 --> 01:38:06,247 management and delivery of care really impacted my life and my trajectory. 1649 01:38:06,280 --> 01:38:10,284 So thanks so much, the organizers, to have a chance to present 1650 01:38:10,284 --> 01:38:12,286 to you and talk to you about this. 1651 01:38:15,289 --> 01:38:15,923 Process. 1652 01:38:15,923 --> 01:38:21,195 And so I want to just reflect back a little bit on how far medicine 1653 01:38:21,195 --> 01:38:24,732 has advanced really in this case, we'll say in the last 60 years 1654 01:38:25,633 --> 01:38:29,570 through research that was done on carefully organized, 1655 01:38:30,237 --> 01:38:34,208 often small cohorts of individuals carefully followed, 1656 01:38:34,608 --> 01:38:37,311 using paper in means, research projects 1657 01:38:37,978 --> 01:38:41,982 and intersections through phone calls. 1658 01:38:42,349 --> 01:38:44,418 Not so much the electronic health record. 1659 01:38:44,985 --> 01:38:48,689 And these efforts have really had transformational impacts 1660 01:38:48,689 --> 01:38:51,225 on medicine, the Framingham Heart Study being one of them. 1661 01:38:51,425 --> 01:38:54,595 There are so many others, and they gave us intervening 1662 01:38:54,762 --> 01:38:58,198 risk factors by which we had been able to change care. 1663 01:38:58,198 --> 01:39:00,501 And I would argue that 1664 01:39:00,501 --> 01:39:04,571 the goal of precision or maybe personalized medicine has really been 1665 01:39:04,571 --> 01:39:08,709 since the inception of medicine of how we tailor care to an individual. 1666 01:39:08,709 --> 01:39:12,780 But what we've learned through beginning these cohorts is how we could 1667 01:39:13,280 --> 01:39:16,383 use data to get smarter about intervening on things 1668 01:39:16,383 --> 01:39:20,587 that may be less visible and doing it using data in evidence basis. 1669 01:39:20,921 --> 01:39:24,992 And so, you know, one of our goals is how and our hope is how can we 1670 01:39:24,992 --> 01:39:29,596 similarly transform health with precision interventions over the next six years? 1671 01:39:29,730 --> 01:39:33,567 I think the goal of precision medicine and how we think about how we want 1672 01:39:33,567 --> 01:39:36,904 a personalized care is much bigger than, of course, 1673 01:39:37,371 --> 01:39:39,940 a a term like personalized medicine. 1674 01:39:39,940 --> 01:39:44,812 It is really about getting to the patient and really how we can improve their 1675 01:39:44,812 --> 01:39:48,949 trajectory of health beyond just disease, but also prevention, resilience 1676 01:39:49,383 --> 01:39:52,152 and the way in which they live their life 1677 01:39:52,920 --> 01:39:55,622 successfully in how they would define it. 1678 01:39:56,223 --> 01:40:00,427 And a lot of this, I think you can even look back 1679 01:40:00,427 --> 01:40:03,630 at the 1987 long range plan that Dr. 1680 01:40:03,630 --> 01:40:06,567 Lindbergh authored with input from others. 1681 01:40:06,767 --> 01:40:10,437 And in this, I just include a quote here about how 1682 01:40:10,738 --> 01:40:14,408 the most encouraging aspect of this report is the recommendation that the library 1683 01:40:14,408 --> 01:40:18,112 move as quickly as possible to translate existing raw technology of computers, 1684 01:40:18,245 --> 01:40:21,749 information and engineering sciences into products and services. 1685 01:40:22,082 --> 01:40:23,650 That, through its insight and understanding 1686 01:40:23,650 --> 01:40:28,288 of the special biomedical practices and needs, can improve health care in America. 1687 01:40:28,789 --> 01:40:33,260 And as I look through this in this book that was still just recommended 1688 01:40:33,427 --> 01:40:36,263 and thought about the impact and legacy of Dr. 1689 01:40:36,263 --> 01:40:40,200 Ellenberg on Precision Medicine, I really saw three points that emerged 1690 01:40:40,200 --> 01:40:45,372 next to me, and one of these was moving from the creation of not just literature 1691 01:40:45,472 --> 01:40:46,040 and making, 1692 01:40:46,040 --> 01:40:49,910 of course, that much more accessible than it ever had been to a wider audience, 1693 01:40:50,277 --> 01:40:53,547 but also storage and cataloging, emerging and digital data. 1694 01:40:53,680 --> 01:40:57,851 It's kind of obvious today that we needed to do this, but, you know, at the time, 1695 01:40:58,052 --> 01:41:01,622 moving the library into a library, not just to the published articles, 1696 01:41:01,622 --> 01:41:04,291 but of things like the genome and the Human Genome Project. 1697 01:41:04,291 --> 01:41:07,895 And and, you know, all those things were essential to accomplishing those goals. 1698 01:41:08,028 --> 01:41:10,564 And laying the foundation to build upon 1699 01:41:10,564 --> 01:41:14,301 the intellect has really been key and critical and called out from this long 1700 01:41:14,301 --> 01:41:17,971 range plan to develop electronic health records, repositories 1701 01:41:18,138 --> 01:41:20,641 and support things like clinical decision support. 1702 01:41:20,841 --> 01:41:24,812 And clinical decision support, I would argue, has never its need 1703 01:41:24,812 --> 01:41:27,981 has never become more obvious than what we see through 1704 01:41:28,849 --> 01:41:31,952 implementation of genetic data into health care. 1705 01:41:31,952 --> 01:41:34,922 And I think this will only continue whether or not, you know, 1706 01:41:35,255 --> 01:41:37,257 start to variant, start three variant 1707 01:41:37,291 --> 01:41:39,827 and how they're fundamentally different than a start 17 variant. 1708 01:41:39,993 --> 01:41:44,431 If you look at interpretation of a given genetic variant on drug metabolism 1709 01:41:44,798 --> 01:41:48,769 and so that evolving medicine really needs decision support that can 1710 01:41:48,769 --> 01:41:52,473 seamlessly partner with a physician to help guide them to the right solution. 1711 01:41:52,840 --> 01:41:57,444 And then a real premise and foundation and computational tools to link, search, 1712 01:41:57,444 --> 01:42:00,714 compare and analyze these kinds of resources such that 1713 01:42:00,714 --> 01:42:05,652 not just people reading the ledger, but, you know, computers and algorithms 1714 01:42:05,786 --> 01:42:09,590 can be consumer of the consumers of this kind of information as well. 1715 01:42:09,756 --> 01:42:14,495 And that, you know, march forward through so many tools has really helped. 1716 01:42:14,695 --> 01:42:18,832 And, you know, we have available, you know, big data resources across 1717 01:42:18,832 --> 01:42:21,902 all sorts of domains that are mineable accessible and clinically relevant 1718 01:42:22,136 --> 01:42:26,140 due to the last really now you can mark to the success 1719 01:42:26,140 --> 01:42:29,209 of the implementation of this long range strategic plan. 1720 01:42:29,977 --> 01:42:32,412 And so these are some of the many tools. 1721 01:42:32,412 --> 01:42:38,452 And Heidi, in their opening that Zach also highlighted some of these 1722 01:42:38,585 --> 01:42:42,656 and there are so many that aren't on here, I'm going to lean towards referencing 1723 01:42:42,656 --> 01:42:45,792 some of these that really have more of a clinical impact 1724 01:42:45,926 --> 01:42:49,930 as I talk about intersection of really a story of precision medicine 1725 01:42:50,130 --> 01:42:54,501 that I think is leading us to where the all of us research program is now. 1726 01:42:55,068 --> 01:42:57,771 And, you know, of these things, we have things that target 1727 01:42:58,305 --> 01:43:00,140 patients and people directly. 1728 01:43:00,140 --> 01:43:04,111 They're non-medical, as well as medical and research scientists 1729 01:43:04,211 --> 01:43:07,581 and really bringing them together so that we can build on knowledge. 1730 01:43:08,348 --> 01:43:10,617 I also want to reflect on how 1731 01:43:10,617 --> 01:43:14,755 my clinic space and our docket, our clinical charts. 1732 01:43:14,855 --> 01:43:15,122 What? 1733 01:43:15,122 --> 01:43:19,159 When I was just starting medicine, we were fortunate to be pretty early 1734 01:43:19,159 --> 01:43:22,529 adopters, actually, of information technology 1735 01:43:22,529 --> 01:43:24,031 and electronic medical records . 1736 01:43:24,031 --> 01:43:25,599 But the outpatient clinic, 1737 01:43:25,599 --> 01:43:28,302 as I was starting, had it, was just getting digitized. 1738 01:43:28,402 --> 01:43:30,170 And so imagine trying to look through these 1739 01:43:30,170 --> 01:43:33,540 to figure out who was on a given drug gets pulled from the market. 1740 01:43:33,674 --> 01:43:35,842 Imagine trying to do cross patient research. 1741 01:43:36,743 --> 01:43:39,179 You know, it was just so hard and so time consuming. 1742 01:43:39,546 --> 01:43:42,783 And so, you know, as we move to 1743 01:43:42,783 --> 01:43:45,485 electronic health records and this is a screenshot of our electronic 1744 01:43:46,119 --> 01:43:50,624 health records in the 2000, how can we use this for research? 1745 01:43:50,624 --> 01:43:53,427 And it turns out moving from clinical care 1746 01:43:53,627 --> 01:43:56,797 to research, use cases and doing 1747 01:43:56,797 --> 01:44:00,267 trends across patient kinds of research 1748 01:44:00,267 --> 01:44:03,437 was not something that was how these were originally architected. 1749 01:44:03,637 --> 01:44:06,974 In my initial queries, for instance, to try to look across patients 1750 01:44:07,174 --> 01:44:07,741 would require 1751 01:44:07,741 --> 01:44:11,678 lots of coding and algorithms to scan across serially different charts. 1752 01:44:11,678 --> 01:44:13,747 And so that was an evolution of time 1753 01:44:14,281 --> 01:44:16,783 and supported by a lot of research from the NLM. 1754 01:44:17,284 --> 01:44:21,221 And I want to give an example of what was the first cross 1755 01:44:22,522 --> 01:44:24,758 patient cross our 1756 01:44:24,758 --> 01:44:28,262 genome genome wide association study that had a new finding, 1757 01:44:28,395 --> 01:44:31,999 really relying purely on data in the R and in this case, 1758 01:44:32,599 --> 01:44:36,470 that algorithm on the left just shows you all the different information pieces 1759 01:44:36,470 --> 01:44:36,937 we had to pull. 1760 01:44:36,937 --> 01:44:39,973 I mean, to do things like manually coding for spelling errors, for instance, 1761 01:44:40,107 --> 01:44:42,175 and guessing how people would misspell things 1762 01:44:42,175 --> 01:44:45,379 and looking at all the different ICD nine codes and ZIP codes. 1763 01:44:45,512 --> 01:44:48,515 And that was doctors looking through charts and thinking through, Hey, 1764 01:44:48,515 --> 01:44:50,917 how might this get built? And coming up with this. 1765 01:44:50,917 --> 01:44:53,287 And this took us really about two years to execute 1766 01:44:53,420 --> 01:44:57,791 across these five medical record systems that each individually executed 1767 01:44:57,791 --> 01:45:00,193 within their site. It could take some time to do this. 1768 01:45:00,360 --> 01:45:03,096 And but they found that the algorithms work well. 1769 01:45:03,230 --> 01:45:07,134 Overall, we had more than a 90% positive values for our cases. 1770 01:45:07,134 --> 01:45:10,137 The controls, we could deploy this across different systems. 1771 01:45:10,137 --> 01:45:11,872 We could use genetic data. 1772 01:45:11,872 --> 01:45:15,375 It was derived for other purposes and know we could find something 1773 01:45:15,375 --> 01:45:18,712 that was new, a new association of a thyroid transcription factor 1774 01:45:18,912 --> 01:45:22,749 that was associated with people who had autoimmune thyroid disease. 1775 01:45:23,083 --> 01:45:26,219 And so it showed a promise of using this kind of technology. 1776 01:45:26,219 --> 01:45:28,555 Of course, this has been commonplace, really. 1777 01:45:28,555 --> 01:45:32,459 All major research cohort studies at this point are using electronic health records 1778 01:45:32,726 --> 01:45:35,729 as part of their research foundation. 1779 01:45:36,496 --> 01:45:38,899 And we also, because of resources like 1780 01:45:39,866 --> 01:45:43,003 Klingon and sorry at this point, Pub Med and then CBI and 1781 01:45:43,203 --> 01:45:45,972 and cataloging of genome wide association studies, 1782 01:45:46,106 --> 01:45:49,509 we were easily able to find things like this study which looked at people 1783 01:45:49,509 --> 01:45:55,248 who had a scheme stroke that we didn't realize 1784 01:45:55,248 --> 01:45:59,019 that they had any sort of atrial fibrillation or cardiac arrhythmias. 1785 01:45:59,152 --> 01:46:01,922 But through genetics, they identified a locus 1786 01:46:01,922 --> 01:46:05,192 that was associated strongly with atrial fibrillation. 1787 01:46:05,459 --> 01:46:09,563 And so, you know, you could basically do a study in one disease and define it 1788 01:46:09,763 --> 01:46:11,031 and carefully curated. 1789 01:46:11,031 --> 01:46:12,999 And the genetics actually told you 1790 01:46:12,999 --> 01:46:15,435 that there's an underlying cause you were probably missing. 1791 01:46:16,036 --> 01:46:18,605 And this is shown in other kind of clinical studies. 1792 01:46:18,772 --> 01:46:22,275 But even when this deep dove had really helped sort of elucidate 1793 01:46:22,442 --> 01:46:25,245 how in its early study how genetics 1794 01:46:25,779 --> 01:46:28,882 can start to tell you things that we don't clinically see. 1795 01:46:29,082 --> 01:46:32,219 And it's certainly been our model also as we think about drug discovery. 1796 01:46:33,987 --> 01:46:35,155 We still mentioned that 1797 01:46:35,155 --> 01:46:38,625 genome wide association studies, and that's been a case by which, 1798 01:46:38,658 --> 01:46:42,162 you know, we can use the richness of the electronic health record, really 1799 01:46:42,162 --> 01:46:46,900 categorizing all diseases, all drug exposures, all these lab results. 1800 01:46:47,067 --> 01:46:50,036 And instead of looking at just one disease, just like hypothyroidism, 1801 01:46:50,270 --> 01:46:53,240 you know, where those were derived from other studies 1802 01:46:53,240 --> 01:46:54,574 and we looked at a new disease, 1803 01:46:54,574 --> 01:46:57,744 we could take that and expand that into the scale of the genome 1804 01:46:57,978 --> 01:47:00,781 and figure out ways to map against different diseases 1805 01:47:01,848 --> 01:47:02,883 comprehensively. 1806 01:47:02,883 --> 01:47:05,852 And here I'm using the example of atrial fibrillation again. 1807 01:47:06,019 --> 01:47:09,289 And this really large study was study of 400,000 people. 1808 01:47:09,556 --> 01:47:13,693 You know, when they do that, when the gwas for atrial fibrillation 1809 01:47:14,027 --> 01:47:16,963 developed and shows across 1810 01:47:16,963 --> 01:47:20,000 the genome, all sorts of different associations. 1811 01:47:20,167 --> 01:47:22,102 And you can do this really fast. 1812 01:47:22,102 --> 01:47:25,906 Once you have these data, pull together and see all these associations. 1813 01:47:25,906 --> 01:47:28,975 But you can also ask the question, well, the genomics point all this. 1814 01:47:29,009 --> 01:47:33,113 What happens if I adjust for people who have atrial fibrillation? 1815 01:47:33,280 --> 01:47:37,217 Do we still have all these association with the genetics or are the genetics 1816 01:47:37,217 --> 01:47:38,185 actually more specific? 1817 01:47:38,185 --> 01:47:41,087 And there are clinical associations and you can see when you take away 1818 01:47:41,087 --> 01:47:44,825 those people have a fib, all the other stations and associations go away. 1819 01:47:45,091 --> 01:47:49,362 So it helps, you know, clinically, again, we're able to use tools and power 1820 01:47:49,362 --> 01:47:51,631 and scope of things like the electronic health record 1821 01:47:51,832 --> 01:47:55,168 to to understand derived genetics and then understand 1822 01:47:55,168 --> 01:47:58,138 the impact of those genetics much more quickly than we would. 1823 01:47:58,271 --> 01:48:03,410 And in a more maybe I would say reliable, confident way of of what we're finding. 1824 01:48:04,744 --> 01:48:06,780 So I want to give an example of how 1825 01:48:06,780 --> 01:48:09,649 all these kind of technologies, especially like the use of M.S., 1826 01:48:09,850 --> 01:48:13,353 which really has been foundational for my work early with natural language 1827 01:48:13,353 --> 01:48:16,356 processing, are moving to things like 1828 01:48:17,591 --> 01:48:20,827 in how we just use as an inter lingua 1829 01:48:21,061 --> 01:48:24,297 among different vocabularies ICD nine and ICD ten. 1830 01:48:24,498 --> 01:48:28,535 Great work that Ellen did there in making this more consumable, 1831 01:48:28,635 --> 01:48:33,139 not to mention making things like snowmen available for everyone in the US. 1832 01:48:33,306 --> 01:48:38,545 So helpful to not have to work through and make those those linkages manually. 1833 01:48:38,845 --> 01:48:43,049 And so what we did is we took the Emerge Network, which had ten clinical centers, 1834 01:48:43,650 --> 01:48:46,953 ICD nine, ICD ten in and of themselves 1835 01:48:47,187 --> 01:48:51,391 may be hard to work between a clinical repository and the UK 1836 01:48:51,391 --> 01:48:55,428 Biobank, which has 500,000 people collected in the United Kingdom 1837 01:48:55,562 --> 01:48:59,332 , 200,000 of which, when we did the study, had whole exome sequencing 1838 01:48:59,599 --> 01:49:02,302 and clinical data derived from the UK. 1839 01:49:02,636 --> 01:49:06,273 And by use, by pulling it together, you know, we have standards around 1840 01:49:06,273 --> 01:49:07,340 sequencing data. 1841 01:49:07,340 --> 01:49:10,610 We have lots of journey data, things like the your mosque 1842 01:49:10,777 --> 01:49:13,980 and all the work that has been done around these codes. 1843 01:49:14,247 --> 01:49:17,918 We could map all those things relatively quickly together to around 3000 1844 01:49:17,918 --> 01:49:18,885 different phenotypes. 1845 01:49:18,885 --> 01:49:22,489 We can use Klingon and determine among these cancer 1846 01:49:22,489 --> 01:49:26,126 causing genes that we wanted to look at and see who had pathogenic variants 1847 01:49:26,393 --> 01:49:29,462 and essentially moving and adding a whole nother 1848 01:49:29,462 --> 01:49:32,599 country's data and interpreting all their genomes or something. 1849 01:49:32,599 --> 01:49:34,634 That is a process of weeks 1850 01:49:34,634 --> 01:49:38,438 after process approvals and all these things are compatible. 1851 01:49:38,705 --> 01:49:42,742 And we were able to analyze this huge dataset with rare variance in these 1852 01:49:43,043 --> 01:49:48,515 26 cancer genes and look at things like these associations across the difference. 1853 01:49:48,515 --> 01:49:52,986 So here we have a combined sets of 23 genes on the x axis 1854 01:49:53,186 --> 01:49:56,756 and a genome with each of those genes and using these data 1855 01:49:56,756 --> 01:49:58,592 sets across all these different sites. 1856 01:49:58,592 --> 01:50:02,162 We were able to, if one study, replicate all of the strong 1857 01:50:02,362 --> 01:50:05,332 gene cancer associations for these genes 1858 01:50:06,399 --> 01:50:09,035 in cleansed an omen and concludes non cancer 1859 01:50:09,102 --> 01:50:10,704 being a lot of non-cancer phenotypes 1860 01:50:10,704 --> 01:50:13,740 and there we were able to replicate in the study 70% of those 1861 01:50:13,907 --> 01:50:16,176 and then we identified 50 new associations, 1862 01:50:16,376 --> 01:50:17,811 most of which were not cancer. 1863 01:50:17,811 --> 01:50:20,847 But some are related to cancers as well and we actually can 1864 01:50:20,847 --> 01:50:23,249 look at their temporality as well in that 1865 01:50:23,917 --> 01:50:27,921 and show it in at least two cohorts, all enabled by the underpinnings 1866 01:50:27,921 --> 01:50:32,325 of all of these information technologies that we can use in a very rapid fashion 1867 01:50:32,492 --> 01:50:35,261 and not even have to think about the languages we're using. 1868 01:50:35,495 --> 01:50:39,199 That's really some of the power of all those tools that enables this 1869 01:50:39,199 --> 01:50:41,201 and similarly, countless other studies like it. 1870 01:50:42,235 --> 01:50:45,405 And so I've talked about how we began with things 1871 01:50:45,405 --> 01:50:49,976 like Framingham and manually derive survey instruments and exams 1872 01:50:50,210 --> 01:50:54,981 to incorporation of genomic data in those early atrial fibrillation studies 1873 01:50:55,315 --> 01:50:58,618 that also were using things like exams to derive that 1874 01:50:59,252 --> 01:51:01,821 and then the power of using health records. 1875 01:51:02,088 --> 01:51:06,126 But, you know, precision medicine and how we dissect individualize health 1876 01:51:06,359 --> 01:51:08,094 is much, much bigger than that. 1877 01:51:08,094 --> 01:51:11,231 And I just want to recognize there's so many plays to this 1878 01:51:11,231 --> 01:51:15,201 and the interrelations between them and getting them really powerfully 1879 01:51:15,669 --> 01:51:18,438 incorporated within one population of individuals 1880 01:51:18,638 --> 01:51:22,475 to share as much of this and coming technologies, imaging data, 1881 01:51:23,376 --> 01:51:26,312 mobile devices and other sorts of sensor technologies, 1882 01:51:26,746 --> 01:51:27,947 search and geospatial 1883 01:51:27,947 --> 01:51:30,450 and other determinations of social determinants of health 1884 01:51:30,617 --> 01:51:32,452 that we know are so important to understand 1885 01:51:32,452 --> 01:51:35,789 the diversity of our populations and their influences on health. 1886 01:51:36,523 --> 01:51:39,693 You know, these things come together and we really designed 1887 01:51:40,326 --> 01:51:44,931 the All of us research program that to help us think about how we can, 1888 01:51:45,131 --> 01:51:49,235 you know , think about the many inputs to help over time. 1889 01:51:49,469 --> 01:51:52,238 And we want to accelerate health research and medical breakthroughs 1890 01:51:52,372 --> 01:51:56,109 to enable individualized prevention and treatment and care for all of us. 1891 01:51:56,276 --> 01:51:58,645 We really want to focus on a diverse population 1892 01:51:58,645 --> 01:52:01,815 and understanding the variability that we all experience. 1893 01:52:01,815 --> 01:52:05,552 And we want to have a large size of at least a million participants 1894 01:52:05,552 --> 01:52:07,587 that do reflect the diversity of United States. 1895 01:52:08,321 --> 01:52:12,625 Over 95% of all genomic studies right now are of people of European ancestry. 1896 01:52:12,959 --> 01:52:16,396 We wanted to change that story, and you'll see that in a minute. 1897 01:52:17,330 --> 01:52:17,931 We really want to 1898 01:52:17,931 --> 01:52:20,967 make that large, rich biomedical dataset 1899 01:52:20,967 --> 01:52:23,670 following in a lens model and Dan's call 1900 01:52:24,471 --> 01:52:27,273 to as available to researchers as we can. 1901 01:52:27,474 --> 01:52:29,943 And it's really important that this be an ecosystem 1902 01:52:29,943 --> 01:52:34,280 where people can share data and follow their data practices to 1903 01:52:34,848 --> 01:52:38,051 ensure and promote reproducibility and interactivity, 1904 01:52:38,485 --> 01:52:41,121 share ability, find ability, index ability, all that kind of stuff. 1905 01:52:41,421 --> 01:52:45,992 And we really wanted to commit to a set of core values as well in this process. 1906 01:52:46,292 --> 01:52:47,994 And, you know, we've been successful, 1907 01:52:47,994 --> 01:52:51,531 I think, in enrolling a diverse audience and a large audience. 1908 01:52:51,798 --> 01:52:52,999 COVID has been challenging, 1909 01:52:52,999 --> 01:52:57,070 but we still enrolled over 520,000 participants that have consented. 1910 01:52:57,504 --> 01:52:58,605 It's very much ongoing. 1911 01:52:58,605 --> 01:53:02,108 We launched in 2018 and over 1912 01:53:02,108 --> 01:53:06,646 365,000 have contributed all the basic steps because participants 1913 01:53:06,646 --> 01:53:09,716 share longitudinal data as part of this. 1914 01:53:10,583 --> 01:53:12,352 Same with digital health technology. 1915 01:53:12,352 --> 01:53:15,755 They can link in their Fitbit data that they may have had for ten years 1916 01:53:15,922 --> 01:53:18,458 there, in some cases go back 40 years. 1917 01:53:18,792 --> 01:53:21,494 So we have longitudinal data that people are to share. 1918 01:53:21,628 --> 01:53:24,731 Even though this study started really in 2018, 1919 01:53:24,898 --> 01:53:27,567 we had this record of data that people are sharing with us. 1920 01:53:27,567 --> 01:53:29,702 It's really powerful that help us think about things. 1921 01:53:30,670 --> 01:53:31,938 And we recently 1922 01:53:31,938 --> 01:53:36,776 released our first set of genetic data, which included 100,000 genomes, 1923 01:53:37,010 --> 01:53:41,381 165,000 people with a race in those whole genomes. 1924 01:53:41,381 --> 01:53:44,284 We've observed 600 million variants so far. 1925 01:53:44,551 --> 01:53:49,255 400 million of those variants are not in common resources now. 1926 01:53:49,289 --> 01:53:50,356 Now, why is that? 1927 01:53:50,356 --> 01:53:52,458 So why are we seeing so many new variants? 1928 01:53:52,458 --> 01:53:54,961 And I think it's largely because we have a population 1929 01:53:54,961 --> 01:53:58,832 that generally hasn't been sequenced before, with over 50% diversity 1930 01:53:58,832 --> 01:54:01,801 by race and ethnicity, over 80% by 1931 01:54:02,635 --> 01:54:05,205 larger metrics, including disability, 1932 01:54:05,605 --> 01:54:08,942 social, sexual, gender, minorities, rural location, things such as that. 1933 01:54:09,576 --> 01:54:13,046 One of the challenges been mapping across different electronic health records 1934 01:54:13,246 --> 01:54:17,016 using common data models like OMAP and terminology work 1935 01:54:17,016 --> 01:54:20,520 such as you have was again, we've been able to do that and and now 1936 01:54:20,620 --> 01:54:23,890 you can see that we're getting greener our quality metrics 1937 01:54:23,890 --> 01:54:27,093 across our 17 or so different vendors represented 1938 01:54:27,093 --> 01:54:30,463 in many different versions because of the terminology systems. 1939 01:54:30,463 --> 01:54:34,968 Again, you can go from cancer to a term like malignant neoplastic disease 1940 01:54:35,168 --> 01:54:38,872 and lots of different terminologies that are mapped in without the user 1941 01:54:38,872 --> 01:54:41,541 having to do the work that all we had to do with hypothyroidism. 1942 01:54:42,141 --> 01:54:45,011 And what does this mean when you actually come to our participants 1943 01:54:45,011 --> 01:54:48,414 are a researcher doing a study and this is open now for researchers. 1944 01:54:49,415 --> 01:54:51,351 This is an example of my last Ph.D. 1945 01:54:51,351 --> 01:54:54,721 student at Vanderbilt before I moved to the NIH. 1946 01:54:54,888 --> 01:54:58,358 He defended in March 2021, he did a study 1947 01:54:58,358 --> 01:55:01,227 where he pulled together lots of data, including the Vanderbilt clinical data, 1948 01:55:01,427 --> 01:55:06,132 and found medications that might affect lipid response. 1949 01:55:06,332 --> 01:55:11,571 And known medications were the most powerful, as is is not unexpected. 1950 01:55:11,871 --> 01:55:14,240 But then a question from the audience, which was not me 1951 01:55:14,474 --> 01:55:16,943 after his three years of work. You know, you did this at Vanderbilt. 1952 01:55:17,076 --> 01:55:18,344 Can you replicate? 1953 01:55:18,344 --> 01:55:21,414 And so he was able to apply to all of us 1954 01:55:22,682 --> 01:55:23,917 for the first time. 1955 01:55:23,917 --> 01:55:28,655 Come in, do the training, come in and take his code from Vanderbilt, 1956 01:55:29,255 --> 01:55:33,893 basically cut and paste it and replicate this in about a week and send me 1957 01:55:33,893 --> 01:55:37,997 to a near final figure with all of us data combined 1958 01:55:37,997 --> 01:55:41,034 with Vanderbilt data and show very similar results. 1959 01:55:41,935 --> 01:55:45,838 And so I think that really shows a power of these kinds of things available across 1960 01:55:46,072 --> 01:55:47,674 60 plus medical centers. 1961 01:55:47,674 --> 01:55:51,544 He was able to combine this data really seamlessly because of the hard work 1962 01:55:51,711 --> 01:55:54,514 of all the decades before pulling these things together. 1963 01:55:54,881 --> 01:55:58,751 So using modern cloud technologies, you can work through things like this 1964 01:55:58,751 --> 01:56:03,022 where you can come in, describe with our tools 1965 01:56:03,523 --> 01:56:06,225 visually and point and click in the resource. 1966 01:56:06,292 --> 01:56:07,627 And this is not just all of us. 1967 01:56:07,627 --> 01:56:11,464 Now these models are being adopted elsewhere where you can build a cohort, 1968 01:56:11,764 --> 01:56:15,902 build a dataset, come in and bring technology at the end. 1969 01:56:15,902 --> 01:56:20,606 You write in our system and many others, you still do have to write some code, 1970 01:56:20,606 --> 01:56:24,844 but it can be a team enabled science where you had different 1971 01:56:24,844 --> 01:56:27,847 people from clinicians who don't know how to code, to people 1972 01:56:27,847 --> 01:56:32,085 who are data scientists and and biostatistician that work in the data. 1973 01:56:32,185 --> 01:56:35,154 And you can actually go and run as you like this 1974 01:56:35,355 --> 01:56:37,490 now using a cloud environment in 30 minutes 1975 01:56:37,824 --> 01:56:41,861 and find known associations or new associations. 1976 01:56:42,128 --> 01:56:46,532 And after building your cohort instead of a year's worth of work 1977 01:56:46,532 --> 01:56:50,837 and thousands of emails that studies like the hypothyroidism study originally took. 1978 01:56:51,637 --> 01:56:53,873 So with that, I want to thank everyone again. 1979 01:56:53,873 --> 01:56:57,310 Thanks so much to the organizers for inviting me to attend and 1980 01:56:58,211 --> 01:57:03,182 just appreciate the legacy Don left and created through the lab 1981 01:57:03,182 --> 01:57:06,686 that is now continuing and had such a big impact in my life. 1982 01:57:09,722 --> 01:57:11,591 Thank you so much, 1983 01:57:11,691 --> 01:57:13,559 Josh. It's impressive. 1984 01:57:13,559 --> 01:57:15,795 Where we will be. 1985 01:57:17,764 --> 01:57:21,100 All as a community have been achieving an impressive. 1986 01:57:21,100 --> 01:57:25,605 What you have in particular by leading the all of us program 1987 01:57:26,372 --> 01:57:29,742 we will have a set of questions at the end 1988 01:57:29,742 --> 01:57:33,813 and people will be able to use the Q&A button 1989 01:57:33,813 --> 01:57:37,917 or the chat depending on which group you are in. 1990 01:57:38,384 --> 01:57:41,821 And we will go ahead with the other two speakers 1991 01:57:41,821 --> 01:57:45,892 and then again to have the questions at the end. Dr. 1992 01:57:46,225 --> 01:57:50,630 Graziella Gonzales Hernandez is Vice Chair for Research and Education 1993 01:57:50,630 --> 01:57:54,667 in the Department of Computer Biomedicine at Cedars-Sinai Medical Center. 1994 01:57:55,168 --> 01:57:58,805 Prior to joining Cedars-Sinai, she was an associate professor 1995 01:57:58,805 --> 01:58:01,741 of informatics at University of Pennsylvania. 1996 01:58:02,842 --> 01:58:05,178 Her health language processing lab 1997 01:58:05,978 --> 01:58:09,315 moved to Cedars-Sinai and focuses 1998 01:58:09,315 --> 01:58:11,317 on natural language processing and machine 1999 01:58:11,317 --> 01:58:15,521 learning for knowledge, discovery, extracting and structured information 2000 01:58:15,521 --> 01:58:19,292 from clinical records, journal articles and social media postings 2001 01:58:19,926 --> 01:58:23,329 to elucidate data patterns, trends and relationships 2002 01:58:23,329 --> 01:58:26,532 that can aid the discovery process in areas such 2003 01:58:26,532 --> 01:58:29,802 as far more pharmacoepidemiology clinical research 2004 01:58:30,069 --> 01:58:32,438 or public health monitoring and surveillance. 2005 01:58:33,172 --> 01:58:37,410 Dr. Gonzalez Hernandez and her team have made available 2006 01:58:37,410 --> 01:58:41,948 to the Health Research Community novel approaches to complete pipelines 2007 01:58:41,948 --> 01:58:46,018 for information extraction from different sources using an LP. 2008 01:58:46,652 --> 01:58:49,755 Her experience includes mentoring of more than 50 2009 01:58:49,789 --> 01:58:54,961 new faculty, investigators, fellows, graduate students at the Masters and Ph.D. 2010 01:58:54,961 --> 01:58:59,765 levels, and she currently serves as a member of the NLM Scientific Board 2011 01:58:59,765 --> 01:59:05,071 of Advisors, as well as a member of the NIH BMA Grants Review Panel. 2012 01:59:05,805 --> 01:59:06,939 Please welcome Dr. 2013 01:59:06,939 --> 01:59:09,342 Gonzales and Hernandez talking about Dr. 2014 01:59:09,342 --> 01:59:12,512 Lindbergh's legacy to the advancement of biomedical 2015 01:59:12,512 --> 01:59:16,149 informatics, his vision of a new field or a new way. 2016 01:59:19,152 --> 01:59:20,119 Thank you so much. 2017 01:59:20,119 --> 01:59:22,855 It's a pleasure to be here. 2018 01:59:23,589 --> 01:59:28,194 When I was first asked to speak about Dr. 2019 01:59:28,194 --> 01:59:32,632 Lindbergh's legacy and this new feel 2020 01:59:32,632 --> 01:59:35,902 for a new age, it has always fascinated me. How? 2021 01:59:36,402 --> 01:59:41,707 How broad 2022 01:59:41,707 --> 01:59:44,577 and how wide his influence has been. 2023 01:59:44,911 --> 01:59:49,081 So just to share a little bit about about Dr. 2024 01:59:49,081 --> 01:59:53,219 Lindbergh being a lamb and my relationship and how I benefited 2025 01:59:53,653 --> 01:59:56,222 from from his wonderful contributions. 2026 01:59:56,489 --> 02:00:00,560 I remember being the first the first interaction 2027 02:00:00,560 --> 02:00:05,031 I had with him as a member of the of the review panel for the NLM. 2028 02:00:05,264 --> 02:00:08,201 We will sit at the NLM library 2029 02:00:08,201 --> 02:00:10,903 and the and then wait eagerly 2030 02:00:10,903 --> 02:00:15,775 for the morning update that he will bring to the review to the panelists. 2031 02:00:15,775 --> 02:00:17,743 Then he was, I think it was 2032 02:00:18,844 --> 02:00:21,647 one of the of the things that most impacted me 2033 02:00:21,647 --> 02:00:25,218 when I first arrive at the NLM and was there and was able to hear 2034 02:00:26,352 --> 02:00:30,756 his update on science and his views, and we will just sit there 2035 02:00:30,756 --> 02:00:34,227 and absorb all his of his 2036 02:00:35,294 --> 02:00:37,029 insights into this. 2037 02:00:37,029 --> 02:00:39,165 So I do not pretend to do 2038 02:00:40,566 --> 02:00:42,902 an overview of his legacy in this. 2039 02:00:42,902 --> 02:00:45,271 In this sense, there is a book actually on him 2040 02:00:45,271 --> 02:00:47,473 and I gather the cover of the book right there 2041 02:00:48,808 --> 02:00:53,079 that, if you want to check it out, is fascinating and said certainly 2042 02:00:53,079 --> 02:00:58,117 this morning again gave an excellent overview of all his legacy. 2043 02:00:58,651 --> 02:01:02,421 The thing that I want to emphasize is how 2044 02:01:03,456 --> 02:01:07,393 just like me, there's many researchers across the United States and even 2045 02:01:08,494 --> 02:01:12,064 around the world that have been their careers 2046 02:01:13,232 --> 02:01:15,434 undoubtedly reflect 2047 02:01:15,434 --> 02:01:18,371 a lot of his find a lot of his findings a lot of his 2048 02:01:21,207 --> 02:01:23,576 emphasis on information 2049 02:01:23,576 --> 02:01:26,579 as a means to improve health. 2050 02:01:26,912 --> 02:01:31,350 He will always emphasize the latest findings, the latest publications, 2051 02:01:31,350 --> 02:01:36,422 the latest ways that we could improve health and we will improve 2052 02:01:37,556 --> 02:01:39,659 the way that people are care 2053 02:01:39,659 --> 02:01:42,495 for the public health, individuals health. 2054 02:01:42,962 --> 02:01:45,765 So in my particular 2055 02:01:48,000 --> 02:01:49,201 career path, 2056 02:01:49,201 --> 02:01:53,939 I got to the NLM early on, the NLM got to me 2057 02:01:54,073 --> 02:02:00,646 finally on the, the, the data, but they share the funding. 2058 02:02:00,680 --> 02:02:03,549 So a lot of my funding comes 2059 02:02:03,549 --> 02:02:05,685 even to this day from the NLM. 2060 02:02:06,752 --> 02:02:11,791 Through the years, I like this little screenshot of how the NLM peppered 2061 02:02:11,891 --> 02:02:16,696 all my all my funding from the beginning and I'm eternally grateful, 2062 02:02:17,029 --> 02:02:20,266 but also for the opportunity to review proposals 2063 02:02:20,666 --> 02:02:23,069 I've served to this day in around 50 or so 2064 02:02:23,703 --> 02:02:26,138 NIH panels. 2065 02:02:26,639 --> 02:02:29,909 And through that, those of you that have reviewed proposals needs that 2066 02:02:29,909 --> 02:02:33,312 I've seen about 2000 or so proposals 2067 02:02:33,512 --> 02:02:36,282 from researchers around the nation. 2068 02:02:37,149 --> 02:02:41,887 And what is striking is how many of them used 2069 02:02:41,887 --> 02:02:45,825 the resources that have been developed by the NLM and NCBI. 2070 02:02:46,625 --> 02:02:49,395 Jam band PubMed is just. 2071 02:02:51,964 --> 02:02:54,033 The influence that the DNA. 2072 02:02:54,033 --> 02:02:54,834 LIM And Dr. 2073 02:02:54,834 --> 02:02:57,203 Limbaugh has got in in all of our research 2074 02:02:57,970 --> 02:03:00,473 is is is tremendous. 2075 02:03:00,840 --> 02:03:02,675 So this is the current year. 2076 02:03:02,675 --> 02:03:06,011 Again, the Olympics takes the lion's share 2077 02:03:06,011 --> 02:03:08,481 of of of what I am able to do 2078 02:03:09,048 --> 02:03:11,417 thanks to them and the continuous support. 2079 02:03:12,251 --> 02:03:13,552 One very important thing. 2080 02:03:13,552 --> 02:03:16,689 So when I was thinking how to focus this, this dog 2081 02:03:16,689 --> 02:03:19,058 and on the important contribution 2082 02:03:19,992 --> 02:03:22,928 the most important way that that I can 2083 02:03:24,864 --> 02:03:27,867 that the decided to go with was how 2084 02:03:27,867 --> 02:03:32,104 the NLM was an early supported supporter of real world data. 2085 02:03:32,671 --> 02:03:35,608 I think I have the the very first 2086 02:03:35,608 --> 02:03:38,110 or the oldest of grant 2087 02:03:38,944 --> 02:03:41,680 funded for the study of real world data. 2088 02:03:42,181 --> 02:03:45,050 And I remember that when I proposed that it was 2089 02:03:45,050 --> 02:03:49,422 there was hardly anything published on how to use social media data. 2090 02:03:49,989 --> 02:03:53,092 And I think the most interesting thing that I discovered 2091 02:03:53,092 --> 02:03:58,230 is that my proposal wasn't about any specific solutions. 2092 02:03:58,264 --> 02:04:01,500 What I propose was to study how it will be used, 2093 02:04:02,001 --> 02:04:06,439 how real world data from social media could be used for pharmacovigilance. 2094 02:04:07,273 --> 02:04:11,477 And so I never promised that I was going to find early signals 2095 02:04:11,477 --> 02:04:15,448 of adverse effects or actually the problem is what I was going to find at all. 2096 02:04:15,448 --> 02:04:18,851 All I wanted to do was to find 2097 02:04:18,851 --> 02:04:21,520 that those develop that those decibels of pool enable it. 2098 02:04:22,054 --> 02:04:25,157 So just like like social media, electronic health 2099 02:04:25,157 --> 02:04:28,527 records, of course, are foremost one of the 2100 02:04:29,829 --> 02:04:33,966 most important sources of real world data. 2101 02:04:33,966 --> 02:04:38,404 So coded, unstructured notes, large repository of clinical and genomic data 2102 02:04:39,271 --> 02:04:42,341 containing the they could then be built on an entry text 2103 02:04:42,341 --> 02:04:45,244 that that that that could address many knowledge gaps. 2104 02:04:45,711 --> 02:04:46,712 And one would think 2105 02:04:46,712 --> 02:04:49,982 we have been hearing about then the technical records being used 2106 02:04:51,150 --> 02:04:53,285 for all research and or studies. 2107 02:04:53,419 --> 02:04:56,655 One would think that they will be widely used, 2108 02:04:57,089 --> 02:05:00,993 that all these data from all these people out there will. 2109 02:05:00,993 --> 02:05:01,527 Certainly. 2110 02:05:01,527 --> 02:05:05,798 And just this presentation highlights that the importance of that 2111 02:05:06,131 --> 02:05:11,103 and it is one of the efforts, I think, that is more striking 2112 02:05:11,403 --> 02:05:14,473 on on its reach. 2113 02:05:14,473 --> 02:05:18,410 Social media can still contribute their stories in social media 2114 02:05:19,311 --> 02:05:21,447 that people share openly, 2115 02:05:21,447 --> 02:05:25,351 that people share without the structure of of of a questionnaire, 2116 02:05:26,185 --> 02:05:29,288 they sometimes go back in their history . 2117 02:05:29,288 --> 02:05:32,992 So this search that I like showing is I'm diagnosed with. 2118 02:05:33,726 --> 02:05:38,731 And if you if you focus on the middle story, they a medical student 2119 02:05:40,099 --> 02:05:42,468 diagnosed with obsessive compulsive disorder 2120 02:05:42,501 --> 02:05:45,237 disorder as it gives a lot of the the bills 2121 02:05:46,305 --> 02:05:50,109 and what kinds of medications this person has use. 2122 02:05:51,110 --> 02:05:54,713 Then there's a lot of what we call a follow up story. 2123 02:05:54,713 --> 02:05:58,484 So many people retweet them, put their own little $0.02 on it, or 2124 02:05:58,617 --> 02:06:01,520 they share a similar story. 2125 02:06:01,520 --> 02:06:05,291 There's also obviously the things that are not the right thing, 2126 02:06:05,291 --> 02:06:07,259 like that other one. 2127 02:06:07,259 --> 02:06:09,228 So these tweets come from the feed directly, 2128 02:06:09,228 --> 02:06:11,697 and that's exactly how we see them. 2129 02:06:11,697 --> 02:06:15,701 So this one is it is is a contrast with the same search. 2130 02:06:15,701 --> 02:06:19,738 You can get really valuable information and you can get a lot of the noise. 2131 02:06:20,239 --> 02:06:24,009 The challenge is distinguishing the two and being able to develop the systems 2132 02:06:24,009 --> 02:06:25,210 that can distinguish the two. 2133 02:06:28,180 --> 02:06:31,517 The the, the, the the next striking factor 2134 02:06:31,517 --> 02:06:33,819 that I discovered through this through this. 2135 02:06:35,721 --> 02:06:39,959 Analysis of real world data is that is grossly underutilized. 2136 02:06:40,025 --> 02:06:43,228 I was invited to to write a paper 2137 02:06:43,562 --> 02:06:46,365 on biases in data. 2138 02:06:46,365 --> 02:06:49,501 And through this I started thinking like, okay, so how much of it. 2139 02:06:49,868 --> 02:06:52,171 How much of the data is in the structure portion 2140 02:06:52,471 --> 02:06:56,475 of all of the each other is a versus the coded portion. 2141 02:06:56,475 --> 02:06:58,844 So there are some studies on it. 2142 02:06:58,844 --> 02:07:02,348 That is a very interesting, though, beyond what I can talk about right now. 2143 02:07:02,348 --> 02:07:07,019 But it's about 70 to 80% of usable, actionable data 2144 02:07:07,486 --> 02:07:10,155 is in the unstructured portions of the data. 2145 02:07:11,690 --> 02:07:15,861 However, only about 40.5%. 2146 02:07:15,861 --> 02:07:20,065 And I'm being a little generous there of the studies based on each other's 2147 02:07:20,165 --> 02:07:21,700 use this free text. 2148 02:07:22,901 --> 02:07:25,004 99.5% of 2149 02:07:25,004 --> 02:07:27,806 them focus on just go to data. 2150 02:07:28,907 --> 02:07:33,212 And this is not so much the fault of the researchers running this study. 2151 02:07:33,312 --> 02:07:35,381 It's just data is not easily accessible. 2152 02:07:35,381 --> 02:07:38,984 Unstructured portions of the data are very hard to get. 2153 02:07:39,551 --> 02:07:41,654 You will have 2154 02:07:42,488 --> 02:07:45,491 every institution with few exceptions. 2155 02:07:45,858 --> 02:07:48,827 You will have a very hard time getting free access to it. 2156 02:07:49,094 --> 02:07:55,267 And even if you can access it and use it, there are not many standards on it. 2157 02:07:55,267 --> 02:07:57,002 So revisit that one. 2158 02:07:57,002 --> 02:07:59,138 Social media data. 2159 02:07:59,138 --> 02:08:01,940 Another foreign data is not officially used at this point 2160 02:08:01,940 --> 02:08:04,043 by any regulatory agency. 2161 02:08:04,043 --> 02:08:07,713 And I say officially, because unofficially it is. 2162 02:08:07,713 --> 02:08:11,450 And actually, if you if you count the FDA's declaration 2163 02:08:11,450 --> 02:08:17,089 that they use social media to to get early early signals about 2164 02:08:18,424 --> 02:08:19,625 COVID 2165 02:08:19,625 --> 02:08:23,028 treatments or fake COVID treatments, they mention that that's 2166 02:08:23,028 --> 02:08:25,130 how they get them, but they don't mention how 2167 02:08:25,130 --> 02:08:27,166 they use social media on their website. 2168 02:08:27,433 --> 02:08:32,271 So I guess a declaration on an official website could be seen as an official use 2169 02:08:32,871 --> 02:08:33,706 of social media. 2170 02:08:33,706 --> 02:08:36,709 However, there's like little information as to how it is done. 2171 02:08:38,911 --> 02:08:40,145 Social media data is used 2172 02:08:40,145 --> 02:08:43,048 mainly to inform other studies, like systematic reviews. 2173 02:08:43,215 --> 02:08:48,520 So like there's also references to finding mentions in social media to go back 2174 02:08:48,554 --> 02:08:52,324 and look at what is published about them and then add them to studies. 2175 02:08:52,758 --> 02:08:53,892 So, so 2176 02:08:54,359 --> 02:08:56,495 all of this data that we're surrounded 2177 02:08:56,495 --> 02:08:59,765 by needs a little bit more of a systematic approach. 2178 02:08:59,765 --> 02:09:02,267 So this is the paper I was referring to. 2179 02:09:02,267 --> 02:09:05,771 Best practices from big data analytics to address specific biases 2180 02:09:05,938 --> 02:09:06,972 in our understanding of the. 2181 02:09:08,340 --> 02:09:12,678 So in writing it, I saw, for example, 2182 02:09:13,011 --> 02:09:16,715 that studies that use our data 2183 02:09:17,316 --> 02:09:21,286 and that specifically have a finding that refers 2184 02:09:21,286 --> 02:09:24,089 to biological sex as a factor a difference 2185 02:09:25,624 --> 02:09:27,760 in in their in their studies 2186 02:09:28,327 --> 02:09:34,433 vary widely in the use of male and female records. 2187 02:09:34,767 --> 02:09:37,603 So we come 2188 02:09:37,603 --> 02:09:41,340 from 75% male, 25% female 2189 02:09:41,340 --> 02:09:45,210 all the way through the other way around 65%, 70%. 2190 02:09:45,444 --> 02:09:48,280 Many studies in between with a great imbalance 2191 02:09:48,680 --> 02:09:50,682 in the data that they use, 2192 02:09:52,017 --> 02:09:54,052 even if the finding is 2193 02:09:54,153 --> 02:09:57,523 specifically related to a biological sex. 2194 02:09:58,590 --> 02:10:01,760 So the data imbalance is one of the of the things 2195 02:10:02,161 --> 02:10:05,564 and the rate of use of this unstructured data. 2196 02:10:05,631 --> 02:10:09,401 Going back to that point that was making 2197 02:10:09,468 --> 02:10:10,702 these studies 2198 02:10:10,702 --> 02:10:13,672 as you saw the complete in that graph showed that you saw 2199 02:10:13,672 --> 02:10:17,309 all the studies we found that actually use unstructured portions. 2200 02:10:17,843 --> 02:10:21,146 So the way we write this is we found four, 2201 02:10:21,180 --> 02:10:25,117 six related terms and disparities for difference terms and try to get 2202 02:10:25,117 --> 02:10:29,721 the ones that had a finding that had to do with biological sex. 2203 02:10:30,589 --> 02:10:33,959 And found 67,424 2204 02:10:33,959 --> 02:10:37,963 articles in Medline, but only 469 2205 02:10:37,963 --> 02:10:40,999 made it across to include machine 2206 02:10:40,999 --> 02:10:45,103 learning A and B related terms. So 2207 02:10:46,905 --> 02:10:48,073 we use that as 2208 02:10:48,073 --> 02:10:51,076 a proxy for the use of unstructured data, 2209 02:10:51,109 --> 02:10:54,847 because that's the only possible way that you can really process this. 2210 02:10:55,881 --> 02:10:58,217 So when we saw six specific 2211 02:10:58,350 --> 02:11:01,486 differences, Dems only would get the 67,006. 2212 02:11:01,987 --> 02:11:06,892 And when we add the text mining or in a beat terms, we go down to less than 1%. 2213 02:11:07,426 --> 02:11:10,195 And it might seem that it's like, well, it's okay. 2214 02:11:10,729 --> 02:11:13,165 It might remind you what 1% means. 2215 02:11:13,999 --> 02:11:18,770 It sends you rushing to finding your your charger. 2216 02:11:18,770 --> 02:11:22,574 So that's how we how I think we shall feel about this is like 2217 02:11:22,574 --> 02:11:24,910 what are only 1% or less than 1%. 2218 02:11:25,043 --> 02:11:28,547 There's this urgency to correct that and not sit 2219 02:11:28,547 --> 02:11:31,583 and think that is already done is not done by any means. 2220 02:11:31,817 --> 02:11:33,752 And there's a lot that we can be done. 2221 02:11:33,752 --> 02:11:36,054 There's a lot that we can learn. 2222 02:11:36,054 --> 02:11:40,859 Though, we could be missing key information, key actionable information 2223 02:11:41,126 --> 02:11:45,764 by not using these unstructured portions of the electronic health record. 2224 02:11:46,231 --> 02:11:48,834 So the anecdote that Assad 2225 02:11:48,867 --> 02:11:52,004 included about the finding that Dr. 2226 02:11:52,004 --> 02:11:57,776 Linder had and the images of the use of silicone for cardiovascular surgery, 2227 02:11:58,110 --> 02:12:02,481 something like this might be already happening in one after another study here. 2228 02:12:02,848 --> 02:12:06,218 So if we just use coded data in this particular paper, 2229 02:12:06,218 --> 02:12:09,788 they were looking at hypoglycemic occurrence and severity extracted 2230 02:12:09,821 --> 02:12:14,660 from each other data when they use only codes, ICD nine codes for it, 2231 02:12:15,594 --> 02:12:20,699 they found about an even number of of a serious of 2232 02:12:20,933 --> 02:12:23,435 I mean they use any any of this 2233 02:12:23,735 --> 02:12:27,773 sorry with severity extracted only from gold. 2234 02:12:28,540 --> 02:12:30,142 Hypoglycemic occurrence 2235 02:12:30,142 --> 02:12:34,146 seemed to be about 46,000 from the from the dataset that they were using. 2236 02:12:34,413 --> 02:12:38,684 When they threw in an OBE, they found 83,000 about twice 2237 02:12:38,684 --> 02:12:42,354 as many occurrences were in a were identified. 2238 02:12:43,221 --> 02:12:46,892 And the actual balance of them also varied a little bit. 2239 02:12:46,892 --> 02:12:50,262 So we found they found a lot more of them mild and moderate. 2240 02:12:50,595 --> 02:12:51,463 Recorded their 2241 02:12:53,966 --> 02:12:57,269 cereals were still a. A 2242 02:12:57,469 --> 02:12:59,271 good number deals with an upbeat. 2243 02:12:59,271 --> 02:13:01,940 When you combine them though, the power comes through. 2244 02:13:02,607 --> 02:13:04,876 So when you combine A.P. 2245 02:13:04,876 --> 02:13:08,780 and ICD nine data, they file in the same dataset 2246 02:13:09,548 --> 02:13:12,451 about three times as many events. 2247 02:13:12,884 --> 02:13:16,421 Even if you discount the mild and moderate, they're still looking at 2248 02:13:16,421 --> 02:13:21,059 about twice as many using an API and ICD nine combined. 2249 02:13:21,526 --> 02:13:24,963 So the power structure, the structure portions of the record 2250 02:13:25,964 --> 02:13:28,900 is still untapped given the few that are there. 2251 02:13:28,934 --> 02:13:31,803 So moving from real world data 2252 02:13:32,104 --> 02:13:35,874 to real world evidence requires this advance 2253 02:13:35,874 --> 02:13:39,778 and AP machine learning and artificial intelligence approaches 2254 02:13:39,778 --> 02:13:43,749 that can really get everything that's there and put it into 2255 02:13:44,950 --> 02:13:47,753 the right conclusions and the right studies. 2256 02:13:47,753 --> 02:13:51,757 So just to give a sampling of of this challenges, 2257 02:13:51,890 --> 02:13:56,528 the challenges, obviously, real world leaders start from extracting the data . 2258 02:13:56,528 --> 02:13:58,930 So the methods are not widely available. 2259 02:13:59,131 --> 02:14:01,833 Many are just adult to the specific institution. 2260 02:14:01,833 --> 02:14:07,105 This example of of being able to deploy something that was done in one institution 2261 02:14:07,472 --> 02:14:10,675 and then applied to like the all of us data. 2262 02:14:11,109 --> 02:14:13,211 Those are the kinds of things that we're looking for. 2263 02:14:13,211 --> 02:14:18,817 We're looking for ways that we can deploy methods generically 2264 02:14:19,418 --> 02:14:22,354 or with minimal adaptation in different datasets. 2265 02:14:23,188 --> 02:14:27,526 This steps, unfortunately or this method unfortunately, 2266 02:14:27,759 --> 02:14:30,829 are inaccessible to the average healthcare researcher in general. 2267 02:14:31,763 --> 02:14:35,200 And then it's very hard to make sure that the data 2268 02:14:35,200 --> 02:14:39,271 that you're getting is high quality or was done in the proper way. 2269 02:14:39,604 --> 02:14:42,974 So that's also throws a little bit of a over 2270 02:14:43,875 --> 02:14:46,111 the dampening effect 2271 02:14:46,111 --> 02:14:48,480 on the use of the ATO, the extraction of the data. 2272 02:14:49,081 --> 02:14:50,415 The guidelines are lacking. 2273 02:14:50,415 --> 02:14:54,786 So using the data becomes challenging because the researchers don't have 2274 02:14:54,786 --> 02:14:59,157 a specific pathway to incorporate the data into traditional studies. 2275 02:15:00,625 --> 02:15:03,128 There is specific things that need to get to be done 2276 02:15:03,128 --> 02:15:05,964 before this can even happen, like normalizing terms. 2277 02:15:06,198 --> 02:15:07,899 So we're talking about adverse effects. 2278 02:15:07,899 --> 02:15:12,104 You need to normalize them so that all of the references to specific 2279 02:15:12,104 --> 02:15:15,006 adverse effects will be accounted for. 2280 02:15:16,007 --> 02:15:19,611 And then even probing the value of the data, it becomes difficult. 2281 02:15:20,278 --> 02:15:23,782 Many times it is dismissed as violence or very noisy. 2282 02:15:24,549 --> 02:15:26,551 It is difficult to think for funding. 2283 02:15:26,551 --> 02:15:29,988 Not impossible, but difficult because then you have to go through 2284 02:15:29,988 --> 02:15:32,958 many hoops that people are not familiar with and on. 2285 02:15:33,024 --> 02:15:37,095 Try to demonstrate that you're doing things the right way in order to 2286 02:15:38,997 --> 02:15:40,065 extract this data. 2287 02:15:40,065 --> 02:15:43,034 Use this data on a on a blight on the board. 2288 02:15:44,136 --> 02:15:46,037 Publication process is also difficult. 2289 02:15:46,037 --> 02:15:48,807 There is no standards, as there has been for a long time, 2290 02:15:49,441 --> 02:15:51,743 a standard of sharing data like genomic data. 2291 02:15:52,177 --> 02:15:55,714 But sharing data extracted from unstructured portions 2292 02:15:55,714 --> 02:15:58,817 of of records has a double 2293 02:16:00,785 --> 02:16:03,555 barrier there in privacy 2294 02:16:04,523 --> 02:16:09,528 and in just the practicality of sharing for reproducibility. 2295 02:16:10,095 --> 02:16:12,264 So there's still many challenges. 2296 02:16:12,264 --> 02:16:16,835 I will briefly, in the time that I have with me that I have, still 2297 02:16:17,435 --> 02:16:19,771 will share a couple of the projects that we've done 2298 02:16:19,971 --> 02:16:22,741 with funding from the NLM 2299 02:16:22,741 --> 02:16:25,277 and that we have share for general use. 2300 02:16:25,944 --> 02:16:29,915 We have datasets, we have annotated datasets 2301 02:16:29,915 --> 02:16:34,119 and we also have this pipeline for for processing this. 2302 02:16:34,119 --> 02:16:38,523 The Baby Minor is of the first end 2303 02:16:38,523 --> 02:16:41,793 to end pipeline for adverse event detection from social media. 2304 02:16:42,194 --> 02:16:44,596 It is now usable. 2305 02:16:44,863 --> 02:16:45,830 Actionable. 2306 02:16:45,830 --> 02:16:48,600 You can take data from the streaming API 2307 02:16:49,100 --> 02:16:51,703 and filter mentioned. 2308 02:16:51,703 --> 02:16:54,539 This is collected using drug names and variants 2309 02:16:54,539 --> 02:16:57,809 of drug names and then filters and classifies. 2310 02:16:57,809 --> 02:17:01,079 The user post for drug mentions identifies 2311 02:17:01,079 --> 02:17:04,816 a span of a name entity for ideas. 2312 02:17:05,850 --> 02:17:08,720 And then normalizes to the Arabs. 2313 02:17:08,720 --> 02:17:11,223 And he has been validated 2314 02:17:11,223 --> 02:17:14,526 and it can really be used 2315 02:17:14,793 --> 02:17:18,730 for taking advantage of this as a constant flash of data 2316 02:17:20,365 --> 02:17:23,468 that is still being directly from from users. 2317 02:17:23,902 --> 02:17:28,039 So we have numerous publications that they will do like 30 or so in 2318 02:17:28,039 --> 02:17:31,109 different findings from different analysis for different studies. 2319 02:17:32,410 --> 02:17:34,980 One of the, the the other was that 2320 02:17:34,980 --> 02:17:36,982 we have running on this 2321 02:17:38,550 --> 02:17:40,785 here is where the social media data 2322 02:17:40,785 --> 02:17:43,922 can be seen as complementary to a lot of the 2323 02:17:44,356 --> 02:17:47,092 of the studies that we have traditionally done in pregnancy. 2324 02:17:47,892 --> 02:17:50,829 We collected a cohorts of over 500,000 pregnant 2325 02:17:50,829 --> 02:17:54,599 women over now five years at three years at the beginning. 2326 02:17:54,599 --> 02:17:57,102 And then we would find it 2327 02:17:57,402 --> 02:18:00,739 have run studies on birth defects. 2328 02:18:00,905 --> 02:18:02,340 We have run studies on. 2329 02:18:04,342 --> 02:18:05,577 Now the latest ones 2330 02:18:05,577 --> 02:18:08,947 are on Kobe vaccine and other medications. 2331 02:18:09,314 --> 02:18:11,316 But basically, 2332 02:18:11,583 --> 02:18:14,886 just so you understand how this longitudinal data can contribute 2333 02:18:15,520 --> 02:18:18,290 to the body of knowledge that we have, 2334 02:18:18,290 --> 02:18:20,992 we get a. 2335 02:18:20,992 --> 02:18:25,664 Identify of women that announced a pregnancy and social media. 2336 02:18:26,231 --> 02:18:29,100 And then after filtering and classifying, 2337 02:18:29,100 --> 02:18:34,306 we can get the whole pregnancy timeline and tweets done during the pregnancy, 2338 02:18:34,306 --> 02:18:38,209 particularly in early pregnancy, and then after the baby's born. 2339 02:18:38,443 --> 02:18:41,880 So we can identify birth defects, we can identify 2340 02:18:42,380 --> 02:18:45,150 either illness or medications that we're taking at the beginning 2341 02:18:45,150 --> 02:18:48,153 of pregnancy, even before the woman herself 2342 02:18:48,420 --> 02:18:52,157 knows that that she's pregnant. 2343 02:18:52,157 --> 02:18:54,159 So we have 2344 02:18:54,459 --> 02:18:58,430 a very valuable data set that can be mined for four, 2345 02:18:58,430 --> 02:19:01,132 four different health studies. 2346 02:19:03,401 --> 02:19:07,238 Then we have also my social media 2347 02:19:07,238 --> 02:19:10,141 for the admission of changes in medication treatment. 2348 02:19:11,009 --> 02:19:13,144 So people share openly why 2349 02:19:13,144 --> 02:19:16,014 they change their medications or when they change their medications. 2350 02:19:16,381 --> 02:19:19,884 On mining, the resources becomes very important for us 2351 02:19:19,884 --> 02:19:23,221 studies in adherence and tolerability because many mild 2352 02:19:23,855 --> 02:19:27,325 adverse effects that are not even reported sometimes to payers. 2353 02:19:27,325 --> 02:19:31,162 The data database are the cause, 2354 02:19:31,162 --> 02:19:33,798 the underlying cost for switching medications. 2355 02:19:34,299 --> 02:19:36,401 So we have findings on 2356 02:19:36,901 --> 02:19:39,471 on this particular aspect of it. 2357 02:19:44,609 --> 02:19:45,844 Just to give you an idea. 2358 02:19:45,844 --> 02:19:50,415 So the adverse drug reaction was mentioned as a reason for medication switching, 2359 02:19:50,415 --> 02:19:56,154 about 99.2% of the of the 2360 02:19:57,589 --> 02:20:01,359 tweets that we found that mentioned changes in medication. 2361 02:20:01,693 --> 02:20:05,764 So so adverse effect was number one, the number one reason. 2362 02:20:06,064 --> 02:20:10,101 And so studying them in relationship to specific medications 2363 02:20:11,002 --> 02:20:14,305 will be something that can be done with social media. 2364 02:20:15,306 --> 02:20:21,312 Unique findings from social media can also be done by reducing the volumes. 2365 02:20:21,312 --> 02:20:24,616 To avoid that, it can be used in a mixed method study. 2366 02:20:24,816 --> 02:20:27,185 So this one in JAMA Network Open 2367 02:20:27,786 --> 02:20:31,189 was a box that is posted on Twitter and it was a qualitative study. 2368 02:20:31,189 --> 02:20:33,825 It was done by hand, but the only way that it can be done 2369 02:20:33,825 --> 02:20:38,129 by hand is by having all the automatic methods that can reduce it to the point 2370 02:20:38,363 --> 02:20:40,031 that humans can look at it. 2371 02:20:40,031 --> 02:20:43,368 And we found an interesting and interesting thing 2372 02:20:43,368 --> 02:20:46,905 that was not published in any other study about the use of statins 2373 02:20:48,173 --> 02:20:51,042 is that people were using them 2374 02:20:52,243 --> 02:20:54,479 as a as a way, 2375 02:20:54,846 --> 02:20:58,917 as a license to leave a eat and unhealthy diet 2376 02:20:59,250 --> 02:21:02,854 and not exercise because they are on studies. 2377 02:21:02,854 --> 02:21:04,889 Therefore, they no longer have to do any of that. 2378 02:21:05,490 --> 02:21:08,726 So so this 2379 02:21:08,893 --> 02:21:10,929 risk compensation behavior 2380 02:21:10,929 --> 02:21:14,732 became evident in not just one week, but in a number of the tweets. 2381 02:21:15,099 --> 02:21:19,270 And it required I mean, it is the way we took it is location lives. 2382 02:21:19,270 --> 02:21:22,874 Now, try to see if we can do another study, traditional study. 2383 02:21:22,874 --> 02:21:25,176 So in equal feed, 2384 02:21:25,176 --> 02:21:27,712 a traditional study says, well. 2385 02:21:27,712 --> 02:21:30,615 So all findings continue or data sets continue. 2386 02:21:31,115 --> 02:21:35,720 And I can say without a doubt that my career continues 2387 02:21:36,321 --> 02:21:40,058 because of all of this wonderful, wonderful 2388 02:21:41,359 --> 02:21:42,594 contributions that Dr. 2389 02:21:42,594 --> 02:21:44,696 Limber brought to our field. 2390 02:21:44,696 --> 02:21:50,001 And I can say that that basically is the birth of the field of medical informatics 2391 02:21:51,102 --> 02:21:53,638 is because of his vision 2392 02:21:53,938 --> 02:21:57,008 and his contribution to our. 2393 02:21:57,475 --> 02:21:59,878 Health studies. 2394 02:22:00,044 --> 02:22:00,712 Thank you. 2395 02:22:01,045 --> 02:22:02,981 Thank you so much, Graziella. 2396 02:22:02,981 --> 02:22:06,918 I think that was a great overview of your body of work 2397 02:22:06,918 --> 02:22:11,022 and also how an alum has been so influential 2398 02:22:11,823 --> 02:22:14,459 in that work. 2399 02:22:14,659 --> 02:22:19,197 I would like to introduce our final speaker, Dr. 2400 02:22:19,197 --> 02:22:23,668 Nicholas Seto Nati, who is Associate Professor of Biomedical Informatics 2401 02:22:23,668 --> 02:22:27,772 in the Departments of Biomedical Informatics Systems, Biology and Medicine 2402 02:22:28,106 --> 02:22:32,310 and is Director of Clinical Informatics at the Institute for Genomic Medicine 2403 02:22:32,610 --> 02:22:35,613 in the Comprehensive Cancer Center at Columbia. 2404 02:22:36,047 --> 02:22:37,482 He received his Ph.D. 2405 02:22:37,482 --> 02:22:41,819 from Stanford, where he focused on the development of novel, statistical 2406 02:22:41,819 --> 02:22:45,523 and conventional methods for observational data mining. 2407 02:22:45,990 --> 02:22:50,194 He applied his methods to drug safety surveillance and for the discovery 2408 02:22:50,194 --> 02:22:53,798 of dangerous adverse drug effects and in fact, 2409 02:22:53,798 --> 02:22:56,901 has identified and validated 2410 02:22:57,268 --> 02:23:00,805 previously unknown in serious drug drug interactions. 2411 02:23:01,239 --> 02:23:04,709 His lab at Columbia is focused on using this massive scale, 2412 02:23:04,709 --> 02:23:08,780 real clinical and molecular data for making robust and validated 2413 02:23:08,780 --> 02:23:12,584 scientific discoveries with a particular focus on detecting, 2414 02:23:12,584 --> 02:23:16,588 explaining and validating drug effects and drug interactions. 2415 02:23:17,221 --> 02:23:21,359 Dr. Antonetti is passionate about the integration of real world data, 2416 02:23:21,593 --> 02:23:24,162 such as those stored in electronic health records 2417 02:23:24,529 --> 02:23:28,900 into high dimensional data captured with next generation 2418 02:23:28,900 --> 02:23:33,104 sequencing, high throughput screening and other omics technologies. 2419 02:23:33,504 --> 02:23:37,976 And he does that to reimagine and rescale the scientific scientific method. 2420 02:23:38,276 --> 02:23:40,445 So please welcome Dr. S.A. 2421 02:23:40,712 --> 02:23:44,449 speaking on observational data for biomedical discovery. 2422 02:23:46,117 --> 02:23:48,886 Thank you for that amazing introduction. 2423 02:23:49,520 --> 02:23:53,725 And just to start, I just want to say super honored to be here 2424 02:23:53,725 --> 02:23:58,396 and speaking one with my amazing co panelists. 2425 02:23:58,663 --> 02:24:01,899 And then also for today and talking about Dr. 2426 02:24:01,899 --> 02:24:03,034 Lindbergh. 2427 02:24:03,101 --> 02:24:03,768 It's interesting. 2428 02:24:03,768 --> 02:24:06,938 I never got a chance to meet Dr. 2429 02:24:06,938 --> 02:24:09,273 Lindbergh in person, 2430 02:24:09,273 --> 02:24:11,876 which is unfortunate for me, especially because 2431 02:24:12,210 --> 02:24:15,747 it sounds like the more I read about him and hear about him from stories, 2432 02:24:16,280 --> 02:24:19,717 that his sense of humor is something that I would have really appreciated. 2433 02:24:20,251 --> 02:24:24,756 And but through all this reading, which has been just fantastic, 2434 02:24:25,556 --> 02:24:28,793 I've got to read some of his work and some of his writings, 2435 02:24:28,793 --> 02:24:32,897 but also a lot about perspectives on his impact on the field. 2436 02:24:33,531 --> 02:24:38,069 And it's been fantastic to see and kind of eye opening to see 2437 02:24:38,336 --> 02:24:41,773 all the ways that he's influenced me and even to the point 2438 02:24:41,773 --> 02:24:43,041 of some of the things I say 2439 02:24:43,041 --> 02:24:46,210 and some of the things I think, which I think are totally my ideas 2440 02:24:46,544 --> 02:24:50,048 were so clearly derived from his ideas 2441 02:24:50,048 --> 02:24:54,552 and planting the seeds far before I ever had a chance to learn them. 2442 02:24:55,486 --> 02:24:58,423 So I think it's really been a wonderful journey of self 2443 02:24:58,423 --> 02:25:03,628 and of exploration to rediscover Don in this way through his writing. 2444 02:25:03,828 --> 02:25:07,665 I just want to highlight one thing I read about him, which I thought was so cool, 2445 02:25:08,433 --> 02:25:11,369 which is in the sixties he was, 2446 02:25:11,536 --> 02:25:14,639 you know, like a lot of us in our early days, hacking 2447 02:25:14,639 --> 02:25:18,042 around, figuring out how to turn computers into things that do work for us. 2448 02:25:18,042 --> 02:25:21,612 But in the sixties that a lot of different technology than what we have now. So 2449 02:25:23,181 --> 02:25:25,750 so they were using punch cards and he actually built 2450 02:25:25,750 --> 02:25:29,554 the first laboratory information system using punch card programing. 2451 02:25:30,021 --> 02:25:33,958 And just 20 years later, he built the first A.I. 2452 02:25:33,991 --> 02:25:36,961 system to diagnose Rheumatologic disease. 2453 02:25:37,628 --> 02:25:41,599 So to go from developing on punch cards, which is something very advanced 2454 02:25:41,599 --> 02:25:45,369 laboratory information system on punch cards to developing a first say I for you 2455 02:25:45,403 --> 02:25:49,240 it's a logical diagnosis is one amazing and then think about that 2456 02:25:49,240 --> 02:25:53,244 just 2030 years later he was there to see the emergence of these tools, 2457 02:25:53,911 --> 02:25:55,913 these tools that we think of now 2458 02:25:56,647 --> 02:26:00,084 and all of the groundwork that he laid to make that happen. 2459 02:26:00,084 --> 02:26:01,819 So it's just been super great. 2460 02:26:01,819 --> 02:26:03,554 So I'm going to tell. 2461 02:26:03,554 --> 02:26:06,824 So I was also one of these trainees of the TI 2462 02:26:06,824 --> 02:26:10,928 15 program during my, my pre doctoral period. 2463 02:26:11,262 --> 02:26:15,199 And so I thought it would be fun to kind of dust off some slides. 2464 02:26:15,199 --> 02:26:17,835 So you'll see these slides are actually square shaped, they're very old 2465 02:26:18,770 --> 02:26:24,142 and tell the story of my Ph.D. work and then kind of couple 2466 02:26:24,142 --> 02:26:28,946 that with a newer version of that story that we've done then at Columbia. 2467 02:26:29,413 --> 02:26:31,215 And that I think is actually 2468 02:26:32,383 --> 02:26:34,018 really I didn't realize this 2469 02:26:34,018 --> 02:26:38,189 at the time, but really follows the philosophy that Dr. 2470 02:26:38,189 --> 02:26:39,223 Lumbergh had. 2471 02:26:39,223 --> 02:26:41,592 So I'm just going to dove into it a little bit here. 2472 02:26:42,693 --> 02:26:44,796 I love observational data 2473 02:26:44,862 --> 02:26:47,532 because observations start everything. 2474 02:26:48,132 --> 02:26:52,503 Charles Darwin sailed around the world to collect observations 2475 02:26:52,503 --> 02:26:55,573 of the biological world so that he could form new hypotheses, 2476 02:26:55,573 --> 02:27:00,611 hypotheses that we now know developed into the theory of evolution 2477 02:27:01,045 --> 02:27:05,783 in pharmacovigilance and drug safety, or some famous seminal scientist. 2478 02:27:05,783 --> 02:27:09,954 MacBride and once clinician scientists who discovered the association 2479 02:27:09,954 --> 02:27:14,192 between thalidomide use and birth defects, really kicking off 2480 02:27:14,192 --> 02:27:17,161 modern drug safety surveillance as we know it today. 2481 02:27:18,062 --> 02:27:20,932 And they all did it because they were making observations. 2482 02:27:20,932 --> 02:27:23,901 Darwin of the biological world, McBride and Lenz 2483 02:27:24,135 --> 02:27:27,071 of the clinical world, the patients that they were taking care of. 2484 02:27:28,172 --> 02:27:30,274 Now we're making observations at a scale 2485 02:27:30,508 --> 02:27:34,946 that dwarfs what these early scientists were able to do. 2486 02:27:35,646 --> 02:27:38,149 They were collecting data with their human senses. 2487 02:27:38,149 --> 02:27:41,185 It's an amount of data that you could describe on a 2488 02:27:41,185 --> 02:27:45,089 on a very small disk drive with bytes or terabytes of data. 2489 02:27:46,090 --> 02:27:48,192 Lindbergh could have coded this on his 20 2490 02:27:48,192 --> 02:27:51,996 kilobytes of RAM and his first laboratory information machine. 2491 02:27:51,996 --> 02:27:54,098 Right. Very small amount. 2492 02:27:54,098 --> 02:27:57,535 And now with new technologies like sequencing data and sequencing 2493 02:27:57,535 --> 02:28:00,071 hundreds of thousands, even millions of patients, 2494 02:28:00,605 --> 02:28:03,875 we have huge, massive datasets to trawl through. 2495 02:28:03,908 --> 02:28:08,279 To look for new hypotheses, to make new discoveries from. 2496 02:28:09,914 --> 02:28:14,752 So it's gone from being where we had just to observe our patients. 2497 02:28:14,752 --> 02:28:18,222 Maybe when they walk into the clinic and just clinician scientists 2498 02:28:18,222 --> 02:28:21,859 really having the opportunity to now having these electronic health records, 2499 02:28:21,859 --> 02:28:22,994 which you've seen, mentioned 2500 02:28:22,994 --> 02:28:26,964 multiple different ways and across y different strains of projects 2501 02:28:27,632 --> 02:28:30,201 that give us the ability to form hypotheses. 2502 02:28:30,201 --> 02:28:33,304 All of us gives all of us the ability to form hypotheses 2503 02:28:33,304 --> 02:28:36,974 using this data as a secondary data set, using it for discovering. 2504 02:28:37,975 --> 02:28:40,211 Now very widely used around the world. 2505 02:28:40,678 --> 02:28:43,814 I like to think of every drug order as an experiment. 2506 02:28:45,516 --> 02:28:46,851 As Josh said, 2507 02:28:46,851 --> 02:28:49,253 we can learn from every clinical observation. 2508 02:28:50,121 --> 02:28:52,356 And how do we do observational analysis? 2509 02:28:52,390 --> 02:28:54,792 How do we form hypotheses? 2510 02:28:54,792 --> 02:28:59,163 Well, when we're trying to do something that on an order of magnitude 2511 02:28:59,163 --> 02:29:01,666 much greater than traditional scientists has been able to, 2512 02:29:01,699 --> 02:29:04,635 we have to employ computers to help us do that. 2513 02:29:04,902 --> 02:29:07,905 I think part of Bloomberg's vision was really about 2514 02:29:08,172 --> 02:29:13,210 how do we use computers to help with every phase of the scientific method. 2515 02:29:13,377 --> 02:29:16,647 And one of those being generation of hypotheses. 2516 02:29:17,248 --> 02:29:19,784 And I like to think of data mining as really this phase. 2517 02:29:19,817 --> 02:29:23,587 It's using computational tools, informatics tools, 2518 02:29:23,788 --> 02:29:26,958 data science tools, whatever you want to call them today. 2519 02:29:27,224 --> 02:29:29,760 But it's using these advanced tools 2520 02:29:30,027 --> 02:29:33,164 to get computers to generate that hypotheses for us. 2521 02:29:34,732 --> 02:29:37,301 There's a problem with using these types of tools 2522 02:29:37,301 --> 02:29:41,372 and using observational data, and that has to do with confounding bias. 2523 02:29:41,806 --> 02:29:45,643 So I love to illustrate this with a picture of a couple of birds. 2524 02:29:46,143 --> 02:29:48,212 And here we have a blue bird and a red bird. 2525 02:29:48,679 --> 02:29:52,750 And so imagine that you live I live across the street from Central Park. 2526 02:29:53,217 --> 02:29:58,189 And so imagine we're walking around Central Park one day and we want to know 2527 02:29:58,189 --> 02:30:01,292 the relative populations of these birds that live in Central Park. 2528 02:30:01,792 --> 02:30:05,096 And so you walk around and you make tick marks on a notebook. 2529 02:30:05,096 --> 02:30:07,665 Every time you see a blue bird, you make a tick mark on the left. 2530 02:30:07,665 --> 02:30:10,167 And every time you see a red bird, you make a tick mark on the right. 2531 02:30:10,768 --> 02:30:15,039 And we get back to the apartment and we notice that we observed 2532 02:30:15,039 --> 02:30:19,043 five times as many blue birds as red birds in our walk through Central Park. 2533 02:30:19,910 --> 02:30:23,848 Now, what does this tell you about the simple question you wanted to ask, 2534 02:30:23,848 --> 02:30:27,985 which is what is the relative populations of these birds in Central Park? 2535 02:30:29,153 --> 02:30:29,320 Well, 2536 02:30:29,320 --> 02:30:31,756 in fact, it tells you absolutely nothing, 2537 02:30:32,356 --> 02:30:34,492 because I'm going to tell you something else about these birds. 2538 02:30:35,593 --> 02:30:38,662 These birds like bluebirds, you might be able figure out by looking at this image. 2539 02:30:38,662 --> 02:30:39,430 They're very friendly. 2540 02:30:39,430 --> 02:30:43,267 When they hear people come into the park, they fly to them and they treated them 2541 02:30:43,467 --> 02:30:45,970 and you notice them. The red birds, they hide. 2542 02:30:46,170 --> 02:30:48,939 They don't like people at all and they flutter and fly away. 2543 02:30:49,407 --> 02:30:52,877 And so the behaviors of these birds have actually confounded the data 2544 02:30:52,877 --> 02:30:55,913 that you were able to collect, making it impossible 2545 02:30:56,080 --> 02:30:58,582 to answer the simple question you have. 2546 02:30:59,116 --> 02:31:01,252 And this is not just true in our hypothetical example, 2547 02:31:01,252 --> 02:31:04,088 but this is true every day in the hospital system. 2548 02:31:04,522 --> 02:31:08,359 Patients, providers, health care practitioners are all making decisions 2549 02:31:08,359 --> 02:31:09,860 and their behaviors change. 2550 02:31:09,860 --> 02:31:12,430 What we can observe and these are observational data sets, 2551 02:31:12,763 --> 02:31:16,333 and their behaviors may invalidate them for very simple questions 2552 02:31:16,333 --> 02:31:18,202 that we think we could answer using these data. 2553 02:31:19,370 --> 02:31:20,204 I'm going to show 2554 02:31:20,204 --> 02:31:22,873 how we can focus on example of drug drug interactions 2555 02:31:23,174 --> 02:31:27,878 and through multiple data modality integration, we can actually address 2556 02:31:27,878 --> 02:31:30,981 some of those limitations and make real discoveries. 2557 02:31:31,816 --> 02:31:35,019 So drug interactions are a common cause of adverse events. 2558 02:31:35,186 --> 02:31:39,990 And understanding them will lead to better outcomes is very common for patients 2559 02:31:39,990 --> 02:31:43,961 to take multiple drugs at the same time, and that increases with age. 2560 02:31:44,829 --> 02:31:48,466 Right now, the main way in which we monitor the safety of drugs 2561 02:31:48,466 --> 02:31:51,902 when used in combination is through observational studies. 2562 02:31:52,203 --> 02:31:55,906 Clinical trials don't have the sample size or the power really to investigate 2563 02:31:56,173 --> 02:31:58,943 drug drug interactions holistically. 2564 02:31:58,943 --> 02:31:59,610 So we turn 2565 02:31:59,610 --> 02:32:03,280 to these large observational databases like the electronic health records 2566 02:32:03,447 --> 02:32:07,451 and like other databases that governments or inter-governmental organizations 2567 02:32:07,451 --> 02:32:11,956 maintain, like the FDA spontaneous adverse event reporting system. 2568 02:32:12,623 --> 02:32:15,126 And these are collections of adverse event reports 2569 02:32:15,126 --> 02:32:18,095 which are submitted by physicians and patients and providers 2570 02:32:18,395 --> 02:32:21,866 that we as pharmacy pharmacovigilance scientists can use to look 2571 02:32:21,866 --> 02:32:25,069 and see if there are any early signals of drug safety concern. 2572 02:32:25,936 --> 02:32:29,106 We decided to use this to study drug interactions. 2573 02:32:29,540 --> 02:32:34,945 The problem is most of the reports that are submitted submit spurious annotations. 2574 02:32:35,179 --> 02:32:37,414 Most of these drugs don't cause these adverse events, 2575 02:32:37,414 --> 02:32:40,484 and it becomes very difficult to decipher any one report. 2576 02:32:41,152 --> 02:32:42,153 As you can see here, 2577 02:32:43,120 --> 02:32:43,954 so what we did is we 2578 02:32:43,954 --> 02:32:49,560 identified some common sources of bias, one that came from concomitant drug use. 2579 02:32:49,693 --> 02:32:52,596 Basically, if two drugs are used together, it's very common for them 2580 02:32:52,596 --> 02:32:55,399 to be associated with the other drugs side effect. 2581 02:32:55,933 --> 02:32:59,637 And another bias that came from indication, namely that if a drug 2582 02:32:59,637 --> 02:33:03,507 is really commonly used for a specific indication, it's often reported with 2583 02:33:03,507 --> 02:33:08,379 that indication signs and symptoms and not actual those actual drug effects. 2584 02:33:09,246 --> 02:33:13,784 We use these to design a new algorithm, which we call the statistical correction 2585 02:33:13,784 --> 02:33:17,354 of uncharacterized bias that implicitly corrects for confounding. 2586 02:33:18,255 --> 02:33:21,192 We were able to apply this to discover 2587 02:33:21,225 --> 02:33:23,527 drug effects much with much more accuracy. 2588 02:33:25,863 --> 02:33:29,633 In one example, we were able to show that we can reduce 2589 02:33:29,633 --> 02:33:33,571 false positive rates very significantly while maintaining positive signals. 2590 02:33:34,004 --> 02:33:37,074 Now, what I'm showing you here is a set of antiarrhythmic acts 2591 02:33:37,408 --> 02:33:41,378 antiarrhythmic were commonly associated or reported with arrhythmia. 2592 02:33:41,579 --> 02:33:44,048 Many of those associations are actually spurious. They're 2593 02:33:44,048 --> 02:33:47,484 because of the indication being treated and not because of the drug itself. 2594 02:33:48,352 --> 02:33:49,253 But dope, it's allied 2595 02:33:49,253 --> 02:33:53,357 is one example of an antiarrhythmic that has a very narrow therapeutic window. 2596 02:33:53,524 --> 02:33:57,695 And in fact, it is known to increase arrhythmia in many patients. 2597 02:33:58,162 --> 02:34:01,198 And so what you can see here is in these circles, 2598 02:34:01,198 --> 02:34:05,035 our corrected measurement after we apply our method to correct for these signals. 2599 02:34:05,469 --> 02:34:08,439 And in the diamond's the original estimate, 2600 02:34:08,672 --> 02:34:12,710 we see that we've reduced the signal in most of these cases, but maintained it 2601 02:34:12,843 --> 02:34:15,613 for some important pro review signals. 2602 02:34:16,347 --> 02:34:19,250 Overall, we're able to show that we can implicitly correct 2603 02:34:19,250 --> 02:34:23,087 for age differences in these large observational cohorts. 2604 02:34:23,520 --> 02:34:26,323 We were showing you here are the 20 most biassed drugs 2605 02:34:26,323 --> 02:34:29,560 in terms of the average age of a patient taking these medications. 2606 02:34:29,793 --> 02:34:33,831 So then the top here, zanamivir is a drug whose average age of a patient 2607 02:34:33,864 --> 02:34:37,901 taking this is about 30 years younger than the average of the entire data set. 2608 02:34:38,335 --> 02:34:41,138 If you did a naive analysis without accounting for age, 2609 02:34:41,405 --> 02:34:44,241 then that would be a significant confounder. 2610 02:34:44,575 --> 02:34:47,244 But what we're able to show is that many of these top 20 2611 02:34:47,411 --> 02:34:52,816 we can implicitly correct for this without modeling age itself using our models. 2612 02:34:54,652 --> 02:34:56,920 So we're able to show that we can correct these biases. 2613 02:34:56,954 --> 02:35:00,224 Now, can we actually infer missing data stuff 2614 02:35:00,224 --> 02:35:03,227 that might not be directly reported or even observed? 2615 02:35:03,594 --> 02:35:05,963 Now, drug drug interactions are really common, 2616 02:35:07,431 --> 02:35:09,199 are commonly affected by this 2617 02:35:09,199 --> 02:35:12,503 in that there are not a lot of reports for drug interactions 2618 02:35:12,603 --> 02:35:15,072 and they may not be observed even when they do occur. 2619 02:35:15,139 --> 02:35:17,975 So we'd like to be able to implicitly identify them. 2620 02:35:18,976 --> 02:35:21,245 We built a model, supervised machine learning model 2621 02:35:21,245 --> 02:35:24,448 that was inspired by the way that physicians diagnose disease. 2622 02:35:24,948 --> 02:35:28,652 So when you walk into the hospital, you may have diabetes, 2623 02:35:28,652 --> 02:35:31,588 but you don't have diabetes written across your forehead. 2624 02:35:32,222 --> 02:35:34,958 Instead, it lies under some level of detection. 2625 02:35:35,659 --> 02:35:39,897 And so but so the doctor will instead use certain signs and symptoms. 2626 02:35:39,897 --> 02:35:43,000 So you might have pain in your extremities, 2627 02:35:43,000 --> 02:35:46,503 might have sweetened urine, or you might have high blood glucose. 2628 02:35:46,804 --> 02:35:49,139 These collectively can be used to form 2629 02:35:49,139 --> 02:35:52,409 a diagnosis of diabetes, even though it can't be directly seen. 2630 02:35:53,110 --> 02:35:54,712 So we're going to do something very similar. 2631 02:35:54,712 --> 02:35:58,816 But for adverse events, we hypothesize that there's a very severe adverse event, 2632 02:35:58,882 --> 02:36:02,453 drug interaction that is being unmeasured or unobserved, 2633 02:36:02,986 --> 02:36:06,890 but that through a collection of different signs and symptoms or other side effects 2634 02:36:06,890 --> 02:36:10,728 that are commonly associated with that more severe event, we can build a model 2635 02:36:10,728 --> 02:36:14,798 that can identify and then infer the presence of the drug interaction. 2636 02:36:15,866 --> 02:36:17,935 So we did that for several different types of models. 2637 02:36:18,202 --> 02:36:20,337 One was for a type two diabetes model. 2638 02:36:20,337 --> 02:36:23,807 We're able to predict if or try to identify 2639 02:36:23,841 --> 02:36:27,711 if drug combinations were increasing blood glucose. 2640 02:36:29,279 --> 02:36:33,684 Our top prediction from this was between paroxetine and Pravastatin. 2641 02:36:34,084 --> 02:36:37,421 Now, paroxetine was an anti is an antidepressant 2642 02:36:37,421 --> 02:36:39,089 that was commonly used at the time. 2643 02:36:39,089 --> 02:36:40,891 And Pravastatin was a cholesterol lowering drug, 2644 02:36:40,891 --> 02:36:44,661 one of a class of statins, which of course are very popular drugs over. 2645 02:36:44,695 --> 02:36:47,364 We estimate about a million patients are on this combination. 2646 02:36:48,031 --> 02:36:50,968 Back in about 2010. 2647 02:36:51,468 --> 02:36:53,871 So we did, though, as we went to a new database, 2648 02:36:53,871 --> 02:36:58,208 the totally different source of data and the electronic health records, 2649 02:36:58,208 --> 02:37:01,178 which was pretty novel at the time, and analyzed blood 2650 02:37:01,178 --> 02:37:04,348 glucose values for patients taking those combinations of drugs. 2651 02:37:04,882 --> 02:37:08,385 And what we found was that in patients taking the combination of drugs, 2652 02:37:08,385 --> 02:37:12,189 there was a significant increase in the blood 2653 02:37:12,189 --> 02:37:16,059 glucose values exposed for those patients exposed to that combination and no 2654 02:37:16,059 --> 02:37:17,294 change for the controls. 2655 02:37:19,263 --> 02:37:22,533 And when we include diabetics, we actually see an exaggerated increase 2656 02:37:22,533 --> 02:37:25,869 of 60 milligrams per deciliter increase in the blood glucose values, 2657 02:37:25,869 --> 02:37:28,839 something that could complicate diabetes therapy and treatment. 2658 02:37:30,073 --> 02:37:32,643 Now, this is where another parallel that I found between Dr. 2659 02:37:32,643 --> 02:37:34,278 and Bird existed, 2660 02:37:34,278 --> 02:37:37,981 because when I would normally give this talk, I would get to this point. 2661 02:37:38,015 --> 02:37:39,783 It was very early in my career. 2662 02:37:39,783 --> 02:37:42,886 I was very excited about this and I would give talks to maybe 2663 02:37:43,153 --> 02:37:46,657 different faculty or different seminars on campus and ended up 2664 02:37:46,657 --> 02:37:50,194 giving a talk to an epidemiology seminar. 2665 02:37:50,961 --> 02:37:54,331 And at this point they were very excited and thought that was very cool. 2666 02:37:54,331 --> 02:37:57,901 But they're also very concerned about confounders that I hadn't considered. 2667 02:37:58,402 --> 02:38:00,904 What times of day are these glucose values take in? 2668 02:38:01,205 --> 02:38:02,372 What are the patient populations? 2669 02:38:02,372 --> 02:38:04,741 Patients who are taking multiple drugs, probably sicker than patients 2670 02:38:04,741 --> 02:38:07,945 who take a single drug coming up with all different ways. 2671 02:38:08,345 --> 02:38:09,480 Kind of like Dr. 2672 02:38:09,480 --> 02:38:12,082 Linder faced a lot of pushback when he was first showing 2673 02:38:12,783 --> 02:38:15,419 the adverse events that he was discovering during surgery. 2674 02:38:16,653 --> 02:38:17,788 So ultimately, 2675 02:38:17,788 --> 02:38:21,024 what I ended up trying to do is go one step further. 2676 02:38:21,358 --> 02:38:25,095 And despite the weird build problem here, I did a mouse experiment 2677 02:38:25,362 --> 02:38:29,733 where we took mice and we gave we fed them this combination of drugs 2678 02:38:31,168 --> 02:38:35,706 and we measured their blood glucose to see if we could see the change there. 2679 02:38:35,939 --> 02:38:38,642 Can we establish this as a real causal relationship 2680 02:38:38,909 --> 02:38:42,312 rather than simply an association derived from observational sources? 2681 02:38:43,080 --> 02:38:43,981 So we had these mice 2682 02:38:43,981 --> 02:38:47,017 that we fed this high fat diet, put them on a pre-diabetic state, 2683 02:38:47,751 --> 02:38:49,686 and then we fed them combinations of these drugs. 2684 02:38:49,686 --> 02:38:53,857 And what we found was a 60 milligrams per deciliter increase in their blood 2685 02:38:53,857 --> 02:38:55,125 glucose values for 2686 02:38:55,125 --> 02:38:59,129 for the mice that were exposed to the combination versus the controls, 2687 02:38:59,696 --> 02:39:04,034 which is almost exactly what we found in humans and like Lindbergh 2688 02:39:04,034 --> 02:39:07,704 making headway with his fellow surgeons after he showed them the imaging data. 2689 02:39:07,971 --> 02:39:10,040 This really change the conversation for me. 2690 02:39:10,574 --> 02:39:14,311 And instead of being questions about confounding and why, 2691 02:39:14,344 --> 02:39:18,081 what other explanations there could be, the questions turned into biological 2692 02:39:18,081 --> 02:39:21,351 questions, questions about what the mechanism was. 2693 02:39:21,351 --> 02:39:24,221 Was it pharmacokinetic or was it pharmacodynamic? 2694 02:39:24,421 --> 02:39:25,689 How could we follow up? 2695 02:39:25,689 --> 02:39:28,091 What additional experiments could we do? 2696 02:39:28,825 --> 02:39:32,396 And it really changed what my entire career from that point on, 2697 02:39:32,796 --> 02:39:35,198 realizing the power of 2698 02:39:35,432 --> 02:39:38,402 using observational data coupled 2699 02:39:38,402 --> 02:39:42,205 with experiments and other validation techniques to establish causality 2700 02:39:43,206 --> 02:39:44,174 has been kind of 2701 02:39:44,174 --> 02:39:46,510 a hallmark of my career ever since. 2702 02:39:48,345 --> 02:39:51,615 And so that's the story I wanted to tell you today and another part of it. 2703 02:39:51,615 --> 02:39:52,616 But I was more fun 2704 02:39:52,616 --> 02:39:56,787 to kind of talk about my experience with kind of learning about Dr. 2705 02:39:56,787 --> 02:39:58,622 Ellenbogen and the many parallels. 2706 02:39:58,622 --> 02:40:02,759 And so I'm going to leave it at that, and I look forward to taking questions 2707 02:40:02,759 --> 02:40:05,195 and discussing with our my fellow members. 2708 02:40:05,195 --> 02:40:06,163 Thank you. 2709 02:40:07,831 --> 02:40:08,665 Thank you, Nick. 2710 02:40:08,665 --> 02:40:13,937 I think that's fascinating to to see how things evolved over time. 2711 02:40:13,937 --> 02:40:20,310 And this flashback of square slides was interesting, too. 2712 02:40:20,310 --> 02:40:21,678 Thank you so much. 2713 02:40:21,678 --> 02:40:23,880 So we have 10 minutes for questions. 2714 02:40:23,880 --> 02:40:29,252 And and I would like to start with one to to which one of you 2715 02:40:29,753 --> 02:40:31,955 if you were to pick one thing 2716 02:40:32,422 --> 02:40:35,525 in, we saw there are so many that Dr. 2717 02:40:35,525 --> 02:40:37,761 Lindbergh has done. 2718 02:40:37,761 --> 02:40:39,796 But what would you pick as like? 2719 02:40:39,963 --> 02:40:41,431 You know, I want to be like him. 2720 02:40:41,431 --> 02:40:44,101 I want to do X as well. 2721 02:40:44,534 --> 02:40:48,872 So why don't I started in the same order with Josh and Christi Island and Nick. 2722 02:40:51,375 --> 02:40:53,610 That's a that's a big question. 2723 02:40:53,910 --> 02:40:58,315 You know, I think a profound impact in leadership of an airline would be through 2724 02:40:58,315 --> 02:41:02,452 all the resources that were created and CBI, you know, sort of driven, 2725 02:41:02,486 --> 02:41:06,123 you know, has gone John Pub Mad Puppets, etc.. 2726 02:41:06,490 --> 02:41:10,260 But, you know, when you when you phrase it as you did around 2727 02:41:10,260 --> 02:41:14,698 a personal characteristic, it would be that, you know, a doctor 2728 02:41:14,698 --> 02:41:18,835 wearing a computational hat, exploring the world 2729 02:41:19,703 --> 02:41:21,972 in a humble, 2730 02:41:22,906 --> 02:41:25,442 dry sort of way, at times 2731 02:41:25,809 --> 02:41:28,745 influencing a culture to investigate, 2732 02:41:28,745 --> 02:41:31,782 explore, learn and improve care. 2733 02:41:31,782 --> 02:41:35,252 You know, and that's a much more personal aspect of taking it. 2734 02:41:35,285 --> 02:41:38,055 And I think that character of his was so influential 2735 02:41:38,522 --> 02:41:40,090 on so many people. 2736 02:41:45,395 --> 02:41:47,731 Actually, I think we saw you may have been muted briefly. 2737 02:41:48,231 --> 02:41:50,600 Oh, thank you. Thank you, Josh Graziano. 2738 02:41:51,601 --> 02:41:53,637 Well, I think from 2739 02:41:53,870 --> 02:41:58,408 from my personal interactions with him, one of the things that struck me 2740 02:41:58,408 --> 02:42:03,113 and that I would like to emulate, I guess, is his capacity to listen. 2741 02:42:03,747 --> 02:42:06,850 So he will listen with attention. 2742 02:42:07,451 --> 02:42:09,953 And you sometimes 2743 02:42:10,454 --> 02:42:14,391 you get the feeling that the people like seem to be listening. 2744 02:42:14,391 --> 02:42:15,692 But the first thing they say, after 2745 02:42:15,692 --> 02:42:18,762 you finish something, they say something about themselves or something 2746 02:42:18,762 --> 02:42:21,998 about like totally different things that you were talking about. 2747 02:42:22,332 --> 02:42:26,570 But he will like question and he will bring examples. 2748 02:42:26,570 --> 02:42:29,773 So I remember on a more personal level, we were like 2749 02:42:29,773 --> 02:42:33,543 registering for one of the NLM events and he was by me 2750 02:42:34,010 --> 02:42:37,114 and he noticed that I had my nine year old with me. 2751 02:42:37,447 --> 02:42:39,516 So I took her on that occasion 2752 02:42:40,350 --> 02:42:45,322 and he started telling me about taking his own kids to conferences 2753 02:42:45,322 --> 02:42:50,360 and as, as he traveled and, and how much she'd made it made a difference to them. 2754 02:42:50,961 --> 02:42:53,530 And so so he's just a simple example, 2755 02:42:53,530 --> 02:42:57,234 I guess, nothing of the grandiose things in data that he did. 2756 02:42:57,234 --> 02:43:02,105 But I think it just reflects a way to go through life and listening 2757 02:43:02,105 --> 02:43:07,611 and noticing and then making making sure that the person that you're with. 2758 02:43:08,545 --> 02:43:12,849 Can understand or can see things the way you see them. 2759 02:43:13,150 --> 02:43:15,652 And by doing that, you learn. 2760 02:43:15,986 --> 02:43:18,789 What is it that it will take to show 2761 02:43:18,789 --> 02:43:24,461 this person, be it a group of physicians or whatever 2762 02:43:24,461 --> 02:43:29,499 it is that you're communicating with the best set of data 2763 02:43:29,800 --> 02:43:33,970 that that that exemplifies or that makes a point that grows better. 2764 02:43:35,839 --> 02:43:38,108 Thank you so much, Graciela and Nick. 2765 02:43:39,543 --> 02:43:42,579 Yeah, I think you know, I think it's the 2766 02:43:42,579 --> 02:43:45,248 I love those comments and the ability to listen. 2767 02:43:46,049 --> 02:43:47,651 I think that's so important. 2768 02:43:47,651 --> 02:43:48,852 And I think that's coming through. 2769 02:43:48,852 --> 02:43:52,022 What I hear and read about is leadership style. 2770 02:43:52,022 --> 02:43:56,893 And just I know I've been affected by the ability, if I could emulate 2771 02:43:56,893 --> 02:44:03,233 anything would be kind of the ability to lead by example and not by dictation. 2772 02:44:03,233 --> 02:44:08,471 And I think that that is a critical skill that is sometimes forgotten. 2773 02:44:08,471 --> 02:44:13,210 But when people have it and they do it right, it has such a broad impact. 2774 02:44:13,210 --> 02:44:14,611 And I think you're seeing that 2775 02:44:14,611 --> 02:44:18,682 with all the people that have been so strongly influenced by by Dr. 2776 02:44:18,682 --> 02:44:19,482 Lindbergh. 2777 02:44:20,550 --> 02:44:21,985 Thank you so much, Nick. 2778 02:44:21,985 --> 02:44:25,322 And abusing a little bit my moderator role. 2779 02:44:25,555 --> 02:44:29,426 Let me include my own account of what 2780 02:44:29,426 --> 02:44:34,397 I think is a tremendous and most influential 2781 02:44:36,066 --> 02:44:37,801 aspect of all his work. 2782 02:44:37,801 --> 02:44:40,737 I would say even though we cannot 2783 02:44:40,737 --> 02:44:45,842 measure directly, PubMed saved more lives than anything 2784 02:44:46,076 --> 02:44:49,746 any other computer intervention that I've ever seen. 2785 02:44:50,213 --> 02:44:52,048 And I like Zach. 2786 02:44:52,048 --> 02:44:56,620 I remember the times when we didn't have free access to that information. 2787 02:44:56,620 --> 02:45:00,090 It was so hard to get into a library, 2788 02:45:01,258 --> 02:45:03,526 go through books, or even the CDs 2789 02:45:03,526 --> 02:45:09,299 that were sold at the time in PubMed made such a difference in PubMed central 2790 02:45:09,466 --> 02:45:12,168 with Betsy and his work as well 2791 02:45:12,836 --> 02:45:16,172 is just extending that to yet another level. 2792 02:45:16,606 --> 02:45:19,743 So with that, I would like to conclude 2793 02:45:19,743 --> 02:45:22,312 and say that the legacy is 2794 02:45:23,546 --> 02:45:26,650 so large that we can with three panelists 2795 02:45:27,083 --> 02:45:29,753 in an abusive 2796 02:45:29,753 --> 02:45:31,421 moderator. 2797 02:45:31,521 --> 02:45:33,790 Praise everything that Dr. 2798 02:45:33,790 --> 02:45:34,858 Lindbergh has done. 2799 02:45:34,858 --> 02:45:38,995 But it has been such an honor to host this panel 2800 02:45:39,296 --> 02:45:44,968 and to be able to comment on this so many great achievements of Dr. 2801 02:45:44,968 --> 02:45:45,802 Lindbergh. 2802 02:45:45,802 --> 02:45:49,139 So thank you all and we'll see you next session. 2803 02:45:54,077 --> 02:45:56,479 Jeff, back to you. 2804 02:45:56,880 --> 02:45:58,348 Yes. Thank you, Dr. 2805 02:45:58,348 --> 02:46:01,318 Machado. Doctors Danny Gonzales. 2806 02:46:01,484 --> 02:46:05,322 Gonzales, Hernandez and and Nettie, thank you 2807 02:46:05,322 --> 02:46:09,259 very, very much, all three of you, for your outstanding presentations. 2808 02:46:09,259 --> 02:46:10,360 And Dr. 2809 02:46:10,360 --> 02:46:13,763 Machado, thank you for your chairing this very thought 2810 02:46:13,763 --> 02:46:17,167 provoking panel, and we appreciate it tremendously. 2811 02:46:17,167 --> 02:46:21,171 A lot to think about, a lot to reflect on for today and certainly for tomorrow. 2812 02:46:21,171 --> 02:46:22,205 With respect to Dr. 2813 02:46:22,205 --> 02:46:25,608 Lindbergh's legacy in science and and leadership 2814 02:46:26,109 --> 02:46:28,912 and also certainly on on your outstanding research 2815 02:46:29,446 --> 02:46:33,283 programs as you continue them and especially respectfully, Dr. 2816 02:46:33,283 --> 02:46:38,621 Denny, with respect to your work here at NIH, with regard to the key all of us 2817 02:46:38,621 --> 02:46:42,125 program that you continue to lead so wonderfully and excellent. 2818 02:46:43,293 --> 02:46:46,496 We're going to take a break now for 90 minutes 2819 02:46:46,796 --> 02:46:51,101 and we're going to return at 130 Eastern Time. 2820 02:46:51,668 --> 02:46:53,503 We welcome you back then 2821 02:46:53,503 --> 02:46:57,273 and we wish you a good break as we will all take one here as well. 2822 02:46:57,273 --> 02:46:59,442 So thank you again for joining us today 2823 02:46:59,442 --> 02:47:03,480 for the 2022 and Working Lecture and Scientific Symposium. 2824 02:47:03,480 --> 02:47:05,648 We'll see you back here in 90 minutes. Thank you. 2825 02:47:29,239 --> 02:47:29,939 Welcome back, 2826 02:47:29,939 --> 02:47:34,511 everyone, to the 2022 Lindbergh Kean Lecture and Scientific Symposium 2827 02:47:34,511 --> 02:47:37,414 here at the National Library of Medicine, National Institutes of Health. 2828 02:47:37,947 --> 02:47:39,215 My name is Jeff Resnick. 2829 02:47:39,215 --> 02:47:42,152 I'm chief of the National Library Medicine History Medicine Division. 2830 02:47:42,152 --> 02:47:45,221 And it's a distinct privilege for me today to be moderating our proceedings. 2831 02:47:45,922 --> 02:47:49,192 For those of you who are just joining, please look for the live feedback 2832 02:47:49,192 --> 02:47:52,462 button under your video stream to send us questions or comments. 2833 02:47:53,229 --> 02:47:55,498 Continuing our symposium, I'm going to turn things 2834 02:47:55,498 --> 02:47:57,901 right over to my National Library Medicine colleague, Jerry. 2835 02:47:58,368 --> 02:47:59,869 Jerry, over to you. 2836 02:48:00,437 --> 02:48:01,638 Thank you, Jeff. 2837 02:48:01,638 --> 02:48:03,840 Hello again to everyone and welcome back. 2838 02:48:03,940 --> 02:48:07,243 I hope you're enjoying today's event as much as I am. 2839 02:48:08,044 --> 02:48:09,179 I am Jerry Sheehan. 2840 02:48:09,179 --> 02:48:10,613 I'm the deputy director 2841 02:48:10,613 --> 02:48:14,350 of the National Library of Medicine for Policy and External Affairs. 2842 02:48:14,717 --> 02:48:15,685 And I had the great pleasure 2843 02:48:15,685 --> 02:48:19,589 of serving with both doctors, Lindbergh and King, during their time here at ILM. 2844 02:48:19,589 --> 02:48:22,158 And I'm pleased to be part of the leadership team 2845 02:48:22,158 --> 02:48:26,563 that's building on their legacy and helping carry them into the future. 2846 02:48:27,330 --> 02:48:29,966 We're joined in that effort, of course, by many, many capable 2847 02:48:29,966 --> 02:48:32,802 colleagues here at NIH and beyond, 2848 02:48:33,369 --> 02:48:37,707 all of us working under the inspired leadership of our two next speakers. 2849 02:48:38,741 --> 02:48:39,209 It's my 2850 02:48:39,209 --> 02:48:42,946 great pleasure to introduce them to you, Dr. 2851 02:48:42,946 --> 02:48:45,148 Laurence Tayback and Dr. 2852 02:48:45,148 --> 02:48:47,984 Patricia Flatley. Brannon 2853 02:48:47,984 --> 02:48:51,087 They will I will introduce them both and then they will continue 2854 02:48:51,087 --> 02:48:52,422 with with their remarks. 2855 02:48:52,422 --> 02:48:54,924 So let me do the two introductions. 2856 02:48:54,924 --> 02:48:58,695 Dr. Tayback has been performing the duties of the director 2857 02:48:58,695 --> 02:49:03,099 of the National Institutes of Health since December 20th of 2021. 2858 02:49:03,967 --> 02:49:07,237 He previously served as the principal deputy director 2859 02:49:07,604 --> 02:49:12,208 and the deputy ethics counselor of NIH, and before that, as the director 2860 02:49:12,208 --> 02:49:16,179 of the National Institute of Dental and Craniofacial Research. 2861 02:49:17,380 --> 02:49:18,982 Before coming to NIH, Dr. 2862 02:49:18,982 --> 02:49:20,150 Tayback was a professor 2863 02:49:20,150 --> 02:49:23,286 and dean at the University of Rochester in the great state of New York, 2864 02:49:23,920 --> 02:49:26,956 being trained as a doctor of dental surgery and has a Ph.D. 2865 02:49:26,956 --> 02:49:28,958 in optics. 2866 02:49:28,958 --> 02:49:31,961 His major research focus has been on the biochemistry and 2867 02:49:31,961 --> 02:49:33,997 function of glycoproteins. 2868 02:49:34,931 --> 02:49:37,267 Dr. Tayback continues work in this area, in fact, 2869 02:49:37,300 --> 02:49:41,204 maintaining an active research laboratory within the NIH intramural program. 2870 02:49:41,638 --> 02:49:43,840 In addition to his administrative duties, 2871 02:49:44,741 --> 02:49:47,577 he is an elected member of the National Academy of Medicine, 2872 02:49:47,710 --> 02:49:50,947 Fellow of the American Association for the Advancement of Science. 2873 02:49:51,648 --> 02:49:53,950 It has been a great friend to the NLM 2874 02:49:53,950 --> 02:49:56,719 during his time here at NIH. 2875 02:49:57,854 --> 02:50:01,291 After Toback's remarks will be followed by those of Patricia Brennan, 2876 02:50:01,424 --> 02:50:03,960 the director of the National Library of Medicine 2877 02:50:05,094 --> 02:50:07,197 and alum, as you have heard today. 2878 02:50:07,330 --> 02:50:09,232 If you didn't know before, is there a leader 2879 02:50:09,232 --> 02:50:11,501 in biomedical informatics and data science? 2880 02:50:11,501 --> 02:50:16,372 Research also oversees and manages vast literature resources 2881 02:50:16,372 --> 02:50:21,311 that span ten centuries, including print and a lot of electronic resources 2882 02:50:21,311 --> 02:50:26,149 that are used billions of times each year by millions of people in the U.S. 2883 02:50:26,149 --> 02:50:26,983 and abroad. 2884 02:50:28,151 --> 02:50:30,520 As NLM director Dr. 2885 02:50:30,520 --> 02:50:35,191 Brennan has positioned as a hub of data science nationally and internationally 2886 02:50:36,092 --> 02:50:39,462 and a lims extensive data information resources 2887 02:50:39,462 --> 02:50:44,000 are used to accelerate discovery, to engage better with new users 2888 02:50:44,500 --> 02:50:47,904 and help advance a workforce for a data driven future. 2889 02:50:48,805 --> 02:50:51,975 Dr. Brennan has a master of science degree in nursing from the University 2890 02:50:51,975 --> 02:50:53,710 of Pennsylvania and a Ph.D. 2891 02:50:53,710 --> 02:50:57,380 in industrial engineering from the University of Wisconsin, Madison. 2892 02:50:58,047 --> 02:51:00,350 She, too, is a member of the National Academy of Medicine 2893 02:51:00,783 --> 02:51:03,553 and holds fellowships in the American Academy of Nursing, 2894 02:51:04,087 --> 02:51:06,422 the American College of Medical Informatics 2895 02:51:06,756 --> 02:51:10,159 and the American Institute for Medical and Biological Engineering. 2896 02:51:10,860 --> 02:51:12,061 When to welcome both Dr. 2897 02:51:12,061 --> 02:51:13,363 Tabak and Dr. Brennan. 2898 02:51:13,363 --> 02:51:15,632 Thank them for joining today's symposium. 2899 02:51:16,065 --> 02:51:18,935 And I want to turn things over to you now to start us off. 2900 02:51:18,968 --> 02:51:20,069 Back to back. 2901 02:51:20,069 --> 02:51:21,571 Thank you again. 2902 02:51:21,771 --> 02:51:23,640 Well, thank you very much. 2903 02:51:23,640 --> 02:51:26,676 It's certainly a great pleasure to be joining you 2904 02:51:26,676 --> 02:51:30,747 all today for the Lindbergh King Lecture and Scientific Symposium. 2905 02:51:31,814 --> 02:51:34,083 And it's a particular honor 2906 02:51:34,083 --> 02:51:36,986 to be here to discuss the science, 2907 02:51:36,986 --> 02:51:40,323 society and the legacy of the Dr. 2908 02:51:40,323 --> 02:51:42,358 Donald Lindbergh. 2909 02:51:42,358 --> 02:51:46,663 I want to thank the hosts, the National Library of Medicine 2910 02:51:47,230 --> 02:51:49,699 and the Friends of the Lab, and, 2911 02:51:49,699 --> 02:51:52,201 of course, the many excellent speakers. 2912 02:51:53,870 --> 02:51:54,437 Now. Dr. 2913 02:51:54,437 --> 02:51:57,407 Lindbergh was a true visionary and pioneer. 2914 02:51:58,074 --> 02:51:59,275 As many of you know. 2915 02:51:59,275 --> 02:52:03,613 He was the director of the NLM for more than 30 years, 2916 02:52:04,180 --> 02:52:07,150 from 1984 to 2015, 2917 02:52:07,150 --> 02:52:11,020 and indeed was one of our longest serving leaders 2918 02:52:11,354 --> 02:52:13,456 at the National Institutes of Health. 2919 02:52:14,924 --> 02:52:17,560 Dr. Lindbergh received his M.D. 2920 02:52:17,560 --> 02:52:21,097 from the College of Physicians and Surgeons at Columbia University. 2921 02:52:21,731 --> 02:52:24,901 And I received my doctorate dental surgery degree 2922 02:52:24,901 --> 02:52:29,872 from the School of Dental Surgery, same institution a few years later. 2923 02:52:30,540 --> 02:52:33,343 But we did share stories 2924 02:52:33,776 --> 02:52:39,682 about faculty that we knew in common, and in particular what the surrounding 2925 02:52:39,682 --> 02:52:44,420 community was like during each of our tenures at the institution. 2926 02:52:45,655 --> 02:52:49,392 Dr. Lindbergh was always forward looking. 2927 02:52:50,793 --> 02:52:54,864 He was one of the very first to predict that computers would become 2928 02:52:54,864 --> 02:52:59,335 increasingly useful in biomedical research and in patient care. 2929 02:53:00,036 --> 02:53:03,773 And he he foresaw that medical informatics 2930 02:53:04,240 --> 02:53:08,778 would emerge as a formal research field and academic discipline. 2931 02:53:09,812 --> 02:53:14,384 Again, as some of you know, his training initially was as a pathologist, 2932 02:53:15,151 --> 02:53:18,921 but remarkably, he was able to reinvent himself 2933 02:53:19,522 --> 02:53:23,192 to become a leader in the use of computers, in medicine. 2934 02:53:24,460 --> 02:53:27,930 Dr. Lindbergh helped establish the American Medical Informatics 2935 02:53:27,930 --> 02:53:31,868 Association and became its founding president. 2936 02:53:32,535 --> 02:53:35,238 And he made notable contributions 2937 02:53:35,838 --> 02:53:37,940 to advanced information science 2938 02:53:38,241 --> 02:53:40,476 for use in medical diagnosis, 2939 02:53:41,043 --> 02:53:44,981 artificial intelligence and educational programs. 2940 02:53:46,249 --> 02:53:50,253 He created programs that transformed our approach 2941 02:53:50,653 --> 02:53:53,189 to information. 2942 02:53:53,423 --> 02:53:57,360 While Director of NLM, he developed long range plans 2943 02:53:57,860 --> 02:54:02,031 that really help deliver on these predictions that he made. 2944 02:54:03,266 --> 02:54:03,766 Under his 2945 02:54:03,766 --> 02:54:07,303 leadership, NLM embraced the Internet, 2946 02:54:07,870 --> 02:54:12,475 enabling the public health care providers and scientists 2947 02:54:12,975 --> 02:54:16,679 to have far more access to the medical literature, 2948 02:54:17,113 --> 02:54:20,116 clinical trials and consumer 2949 02:54:20,116 --> 02:54:22,385 health information than ever imagined. 2950 02:54:23,419 --> 02:54:26,189 He was committed to delivering high quality health 2951 02:54:26,189 --> 02:54:30,226 information to all from health professionals to the public, 2952 02:54:30,693 --> 02:54:34,230 no matter where they worked, lived, and at no cost to them. 2953 02:54:35,998 --> 02:54:38,367 Many of the resources he pioneered 2954 02:54:38,568 --> 02:54:40,736 remain in wide use today. 2955 02:54:41,771 --> 02:54:43,840 PubMed and PubMed central 2956 02:54:44,507 --> 02:54:46,776 repositories for medical literature. 2957 02:54:47,577 --> 02:54:50,012 ClinicalTrials.gov which provides 2958 02:54:50,012 --> 02:54:52,949 access to clinical trials and their results. 2959 02:54:53,616 --> 02:54:56,219 And Medline plus, which provides 2960 02:54:56,219 --> 02:54:58,221 consumer health information. 2961 02:54:59,989 --> 02:55:02,892 Dr. Lindbergh was integral to the establishment 2962 02:55:02,892 --> 02:55:08,698 of the National Center for Biotechnology Information, or NCI, 2963 02:55:09,365 --> 02:55:12,101 which is a division of the National Library of Medicine 2964 02:55:12,568 --> 02:55:15,872 that provides access to biomedical 2965 02:55:15,872 --> 02:55:19,041 and genomic information . 2966 02:55:19,041 --> 02:55:23,145 The NCB became a focal point for big data 2967 02:55:23,346 --> 02:55:25,882 before that term even became fashionable 2968 02:55:26,215 --> 02:55:28,885 and remains so even today. 2969 02:55:28,885 --> 02:55:31,521 NCB I supported databases 2970 02:55:31,521 --> 02:55:34,991 includes things like GenBank or Debugger. 2971 02:55:36,926 --> 02:55:37,860 Edition. Dr. 2972 02:55:37,860 --> 02:55:41,697 Lindbergh led important inter-agency programs. 2973 02:55:42,231 --> 02:55:45,334 He was the founding director of the National Coordination Office 2974 02:55:45,735 --> 02:55:48,571 for High Performance Computing and Communication 2975 02:55:49,038 --> 02:55:52,742 in the White House Office of Science and Technology Policy. 2976 02:55:53,476 --> 02:55:54,677 And he was the U.S. 2977 02:55:54,677 --> 02:55:58,080 national coordinator for the G-7 Global 2978 02:55:58,314 --> 02:56:00,583 Health Care Applications Project, 2979 02:56:01,083 --> 02:56:04,086 a framework for international cooperation 2980 02:56:04,554 --> 02:56:08,190 in medical informatics. 2981 02:56:08,591 --> 02:56:11,027 I'm so very pleased to see that Dr. 2982 02:56:11,027 --> 02:56:15,531 Lindbergh's scientific legacy is well-represented here today 2983 02:56:16,065 --> 02:56:19,702 by a diverse group of inspiring advocates 2984 02:56:20,202 --> 02:56:23,272 for bioinformatics, precision medicine, 2985 02:56:23,806 --> 02:56:27,076 computational sciences and library management. 2986 02:56:28,611 --> 02:56:30,546 We've certainly come a long way over the years, 2987 02:56:30,546 --> 02:56:32,548 yet much remains to be done. 2988 02:56:33,549 --> 02:56:36,319 My hope is that today's distinguished speakers, 2989 02:56:36,786 --> 02:56:39,789 along with all of you who are listening to their words, 2990 02:56:40,423 --> 02:56:44,560 will work together in concert to continue to advance 2991 02:56:44,894 --> 02:56:49,298 back to Lindbergh's exciting vision for the future of biomedical research. 2992 02:56:50,466 --> 02:56:51,834 Dad, I thank you, 2993 02:56:51,834 --> 02:56:55,271 and I'm very pleased to turn it over to my colleague, Dr. 2994 02:56:55,438 --> 02:56:56,806 Patricia Brennan. 2995 02:56:57,440 --> 02:56:58,708 Thank you very much, Larry. 2996 02:56:58,708 --> 02:57:02,044 Let me begin by thanking you for taking the time to be with us here today. 2997 02:57:02,411 --> 02:57:06,182 You are a colleague and a mentor to me, and I'm grateful for that. 2998 02:57:06,882 --> 02:57:10,353 I want to thank all of the people who worked to make this session come to 2999 02:57:10,586 --> 02:57:15,491 to for lots of planning, Jerry and and Jeff and in particular, 3000 02:57:15,491 --> 02:57:18,160 our friends at the friends of the National Library of Medicine. 3001 02:57:18,194 --> 02:57:19,929 This has been an important day. 3002 02:57:19,929 --> 02:57:22,598 My thanks also to all the speakers. 3003 02:57:22,598 --> 02:57:25,368 As I prepared my remarks, I reflected on the question, 3004 02:57:26,235 --> 02:57:29,672 What do you get when you stand on the shoulders of a giant? 3005 02:57:29,672 --> 02:57:31,540 What can you see? 3006 02:57:31,540 --> 02:57:33,743 I've had the good fortune of becoming the director 3007 02:57:33,743 --> 02:57:36,779 of the National Library of Medicine and l'm immediately 3008 02:57:36,779 --> 02:57:39,949 following the 30 plus year tenure of Donald A.B. Lindbergh. 3009 02:57:40,383 --> 02:57:44,954 I'm sure that each of you today treasure your own recollections of Don, 3010 02:57:45,621 --> 02:57:48,791 maybe from a conversation you've had or a laugh you've shared 3011 02:57:49,158 --> 02:57:52,962 with this great leader, this teacher, this visionary and colleague 3012 02:57:53,129 --> 02:57:57,833 who is also a husband to Mary, a father, a grandfather and friend. 3013 02:57:58,567 --> 02:58:01,604 I am both proud and humbled to stand on the shoulders 3014 02:58:01,604 --> 02:58:04,774 of this giant as I leave this incredible organization. 3015 02:58:05,941 --> 02:58:08,177 I know more viscerally than most of you. 3016 02:58:08,377 --> 02:58:11,514 Don's legacy as the director of the National Library of Medicine. 3017 02:58:11,914 --> 02:58:14,183 I sit in the office he occupied. 3018 02:58:14,183 --> 02:58:16,352 I walked down the halls. He walked. 3019 02:58:16,352 --> 02:58:21,323 I work with many of the people he hired, and I see and experience every day 3020 02:58:21,323 --> 02:58:24,760 the fruits of his judgment, his investments and his vision. 3021 02:58:25,828 --> 02:58:29,131 I also now sit where Don once set representing 3022 02:58:29,131 --> 02:58:32,635 the National Library of Medicine at the leadership table of the NIH, 3023 02:58:32,935 --> 02:58:35,538 along with the other institute and center directors. 3024 02:58:36,305 --> 02:58:40,309 Because Don paved the way, I have a platform to extend 3025 02:58:40,543 --> 02:58:41,944 the National Library of Medicine's 3026 02:58:41,944 --> 02:58:45,815 thought, leadership and technical assistance to guide the NIH, 3027 02:58:45,815 --> 02:58:49,218 its continued efforts to advance data driven discovery. 3028 02:58:49,685 --> 02:58:53,923 The goodwill and collaborative spirit engendered by Don across the NIH 3029 02:58:53,923 --> 02:58:58,561 opened doors for me and helped me deliver on his legacy to advance the promise 3030 02:58:58,561 --> 02:59:02,164 of science accelerated by broad access to the literature and data. 3031 02:59:03,699 --> 02:59:05,935 Don and I shared a particular commitment 3032 02:59:06,102 --> 02:59:10,773 to ensuring that the public benefits from indolence, efforts to assemble, 3033 02:59:10,840 --> 02:59:15,244 organize, preserve and disseminate biomedical knowledge for society. 3034 02:59:15,811 --> 02:59:19,515 It was his early vision that made Medline plus a trusted resource 3035 02:59:19,515 --> 02:59:23,219 for consumer health information and ensured that the Medline 3036 02:59:23,552 --> 02:59:27,990 excuse me, the PubMed Citation database and the PubMed central literature 3037 02:59:27,990 --> 02:59:32,728 repository were made open and accessible to everyone everywhere 3038 02:59:32,928 --> 02:59:35,664 with an internet connection at any time and place. 3039 02:59:36,065 --> 02:59:39,468 Please watch this video to take us back almost 25 years 3040 02:59:39,468 --> 02:59:42,872 to see the beginning of this effort. 3041 02:59:45,908 --> 02:59:48,344 Today on Capitol Hill, the National Library 3042 02:59:48,344 --> 02:59:51,781 of Medicine's Medline Internet database is made free to the public. 3043 02:59:52,348 --> 02:59:55,284 The superhighway on medical information 3044 02:59:55,284 --> 02:59:57,620 will now become a freeway. 3045 02:59:58,287 --> 03:00:00,689 This development by itself 3046 03:00:01,457 --> 03:00:07,530 may do more to reform and improve the quality of health care 3047 03:00:07,730 --> 03:00:11,534 in the United States than anything else we've done in a long time. 3048 03:00:11,567 --> 03:00:16,105 We actually it nlm alone answer a million inquiries a day, a day, a day. 3049 03:00:16,172 --> 03:00:17,273 It's a staggering amount. 3050 03:00:17,273 --> 03:00:19,341 It's going for 400 million a year. 3051 03:00:19,341 --> 03:00:22,678 We have tens of thousands of genomes, not just one. 3052 03:00:22,678 --> 03:00:24,313 And all of that has to be assembled 3053 03:00:24,313 --> 03:00:27,349 in a place where people can compute on it and learn from it. 3054 03:00:27,817 --> 03:00:30,052 And that's where in L.A. 3055 03:00:30,052 --> 03:00:33,255 is just a central hub of information that we all depend on. 3056 03:00:33,422 --> 03:00:37,927 Researchers are downloading data equivalent in size to the contents 3057 03:00:37,927 --> 03:00:41,263 of the entire Library of Congress every week. 3058 03:00:41,997 --> 03:00:43,032 That's amazing. 3059 03:00:43,032 --> 03:00:45,467 The real heart of Pupkin is 3060 03:00:46,435 --> 03:00:48,804 the links from each chemical 3061 03:00:49,038 --> 03:00:52,775 to other sources of information about its its biological properties. 3062 03:00:54,510 --> 03:00:57,713 When we were formulating the Framingham Share Program, 3063 03:00:58,347 --> 03:01:02,418 which in which we wanted to genotype the 10,000 participants 3064 03:01:02,818 --> 03:01:05,788 in the Framingham Heart Study, we wanted to put the genotypes 3065 03:01:05,788 --> 03:01:07,990 in the phenotypes together in a common database. 3066 03:01:07,990 --> 03:01:11,227 And before we knew it, there was DB gap database, 3067 03:01:11,227 --> 03:01:13,762 genotype and phenotype. 3068 03:01:14,396 --> 03:01:16,532 Oftentimes the National Library of Medicine 3069 03:01:16,532 --> 03:01:20,536 that I turn to, and not just as a reporter but also as a doctor, 3070 03:01:20,769 --> 03:01:23,572 there are 23 million citations on PubMed. 3071 03:01:23,806 --> 03:01:26,809 ClinicalTrials.gov is a place that I often send my patients. 3072 03:01:27,042 --> 03:01:30,412 I push Medline, plus I eat. 3073 03:01:30,613 --> 03:01:31,647 Breathe. 3074 03:01:31,647 --> 03:01:34,516 Medline Plus is just amazing, you know, 3075 03:01:34,516 --> 03:01:37,319 the amount of information that they have on the website. 3076 03:01:37,853 --> 03:01:41,190 You know, today there is virtually no lag between, 3077 03:01:41,757 --> 03:01:44,727 you know, is coming out of any kind of research activity. 3078 03:01:44,727 --> 03:01:46,795 And it's it's a clinical application. 3079 03:01:46,962 --> 03:01:50,432 The basic reason for that is what the National Library has done, 3080 03:01:50,532 --> 03:01:53,969 taking advantage of the new technology for the transmission of information. 3081 03:01:59,808 --> 03:02:02,978 Commitment to the public was also evident in his efforts 3082 03:02:02,978 --> 03:02:06,215 to educate the next generation of biomedical informatics scholars. 3083 03:02:06,615 --> 03:02:09,818 Frankly, I believe that of all the aspects of his job, 3084 03:02:10,152 --> 03:02:12,955 Don's engagement with the trainees was his favorite. 3085 03:02:13,989 --> 03:02:17,626 When you stand on the shoulders of a giant, you have a great advantage. 3086 03:02:17,893 --> 03:02:20,763 The foundation Don built and the relationships he established 3087 03:02:20,996 --> 03:02:24,099 provided me with a playbook right out of the gate. 3088 03:02:24,533 --> 03:02:27,303 However, I know that it is not enough to solely 3089 03:02:27,303 --> 03:02:30,205 rely on his vision to guide our future. 3090 03:02:31,140 --> 03:02:34,843 In one of our last conversations, he said to me, This is your game. 3091 03:02:35,177 --> 03:02:37,346 Make sure you play it well. 3092 03:02:37,346 --> 03:02:40,683 Well, in order to do that, I cannot simply stand on the shoulders of a giant. 3093 03:02:40,950 --> 03:02:45,487 I must keep my head up and my eyes forward to the future, to envision new pathways 3094 03:02:45,688 --> 03:02:48,324 and find new opportunities to bring forward the richness 3095 03:02:48,324 --> 03:02:52,061 of the National Library of Medicine for the benefit of science and society. 3096 03:02:52,895 --> 03:02:56,765 I close by inviting you to stand with me on the shoulders of this giant 3097 03:02:57,032 --> 03:03:01,203 to meld your sites with his , for it is not by holding tight 3098 03:03:01,403 --> 03:03:04,573 to that which he could see, but by using his vision 3099 03:03:04,573 --> 03:03:08,310 as a stepping point for our own that we will best serve his legacy. 3100 03:03:08,844 --> 03:03:10,012 Thank you and welcome. 3101 03:03:12,915 --> 03:03:13,983 Thank you, Dr. 3102 03:03:13,983 --> 03:03:16,752 Brennan. Thank you, Dr. Tayback, for your remarks. 3103 03:03:16,752 --> 03:03:21,223 And yes, I think highlighting the contributions and the legacy of Dr. 3104 03:03:21,223 --> 03:03:25,861 Lindbergh in the NLM and all of our services and users to the NIH community 3105 03:03:26,628 --> 03:03:29,131 and beyond internationally across the federal government. 3106 03:03:29,164 --> 03:03:33,969 Appreciate your comments on all of those dimensions of Dr. 3107 03:03:34,036 --> 03:03:35,504 Lindbergh's legacy. 3108 03:03:35,504 --> 03:03:38,741 And with that, want to help us move on with our program. 3109 03:03:38,774 --> 03:03:39,708 So, Dr. 3110 03:03:39,708 --> 03:03:43,879 Reznick, let me turn things back over to you for the remainder of the afternoon. 3111 03:03:45,714 --> 03:03:46,915 Thank you very much, Jerry. 3112 03:03:46,915 --> 03:03:49,685 I certainly echo your thanks to Dr. Tayback and Dr. 3113 03:03:49,685 --> 03:03:51,520 Brennan for their remarks, 3114 03:03:51,520 --> 03:03:55,424 which certainly underscore the scientific and leadership legacy of Dr. 3115 03:03:55,424 --> 03:03:59,194 Lindbergh in the current and certainly the future work of our institution. 3116 03:03:59,795 --> 03:04:02,398 Before we begin the next part of our program, 3117 03:04:02,398 --> 03:04:04,333 I'd just like to remind everyone watching 3118 03:04:04,333 --> 03:04:07,870 that today's proceedings in their entirety are being recorded 3119 03:04:08,170 --> 03:04:12,441 and will be made available soon in the NIH Video Cast Archive. 3120 03:04:13,175 --> 03:04:16,578 This archived recording is significant because it is permanent. 3121 03:04:17,413 --> 03:04:20,382 So many more can appreciate today's programs 3122 03:04:20,382 --> 03:04:22,885 and the wonderful presentations that we've heard. 3123 03:04:22,885 --> 03:04:26,422 And I'll also add that this permanence is apropos the legacy of Dr. 3124 03:04:26,422 --> 03:04:29,224 Lindbergh itself, its own permanence, in fact, 3125 03:04:29,892 --> 03:04:32,528 indeed its influence on the lives of so many 3126 03:04:34,396 --> 03:04:36,131 in library circles, many of 3127 03:04:36,131 --> 03:04:40,235 whom we've heard today, and many more who are watching, of course . 3128 03:04:40,235 --> 03:04:43,705 So now it's my distinct pleasure to introduce my colleague, Dr. 3129 03:04:43,705 --> 03:04:47,042 Clement McDonald, who will offer a personal remembrance of Dr. 3130 03:04:47,042 --> 03:04:47,876 Lindbergh. 3131 03:04:48,077 --> 03:04:50,245 Dr. McDonald is the chief data 3132 03:04:50,612 --> 03:04:54,016 chief health data standards officer here at the National Library of Medicine. 3133 03:04:54,783 --> 03:04:58,520 And in this role, he coordinates standards, efforts across the NLM 3134 03:04:58,520 --> 03:05:04,093 and the NIH, including the fast health care interoperability resources or fire 3135 03:05:04,293 --> 03:05:08,630 interoperability standard and vocabularies specific to clinical care. 3136 03:05:09,565 --> 03:05:13,735 Dr. McDonald previously served a dozen years as director of the National Library 3137 03:05:13,735 --> 03:05:17,439 of Medicine's Lister Hill National Center for Biomedical Communications 3138 03:05:17,739 --> 03:05:20,876 and as scientific director of its intramural research program. 3139 03:05:22,077 --> 03:05:23,979 Dr. MacDonald's research 3140 03:05:23,979 --> 03:05:26,615 focuses on electronic medical health records. 3141 03:05:27,349 --> 03:05:30,719 EMR says their use in clinical care and research 3142 03:05:31,320 --> 03:05:34,056 and data standards needed to feed yamaha's 3143 03:05:34,223 --> 03:05:38,026 and epidemiological studies of clinical databases. 3144 03:05:38,427 --> 03:05:40,796 Welcome, Dr. McDonald. I'm going to turn things over to you. 3145 03:05:40,863 --> 03:05:41,697 Thank you for joining us. 3146 03:05:48,070 --> 03:05:49,571 Excuse me, Clem, you're on mute. 3147 03:05:49,571 --> 03:05:51,373 We're not hearing you and Dr. 3148 03:05:51,373 --> 03:05:53,942 Hell slides the rapture. 3149 03:05:53,942 --> 03:05:56,078 Okay. Yeah. 3150 03:05:56,078 --> 03:06:00,415 So I appreciate this chance to talk about my personal experience 3151 03:06:00,415 --> 03:06:03,852 with Don and reflections and the stories I hear about him. 3152 03:06:04,153 --> 03:06:07,122 So some people think of them as distinct, 3153 03:06:07,689 --> 03:06:10,025 as distant, and perhaps a bit stiff. 3154 03:06:10,392 --> 03:06:12,394 But actually, he was a fun guy. 3155 03:06:12,394 --> 03:06:14,796 You like the laugh. You liked it a lot. 3156 03:06:15,430 --> 03:06:20,202 He was a renaissance man with broad and eclectic interests. 3157 03:06:20,702 --> 03:06:22,337 He was an excellent photographer. 3158 03:06:22,337 --> 03:06:25,607 And he had his own darkroom, black and white and color. 3159 03:06:25,941 --> 03:06:27,476 He was a cowboy. 3160 03:06:27,476 --> 03:06:30,679 He and his children all had horses and rode them together. 3161 03:06:31,513 --> 03:06:35,951 He loved music, especially opera, and had a big collection of opera CDs. 3162 03:06:36,318 --> 03:06:37,419 He loved art. 3163 03:06:37,419 --> 03:06:42,391 I remember his interest in Turner's watercolors because the Indianapolis 3164 03:06:42,758 --> 03:06:46,361 Art Museum had one of the biggest US collections of Turner. 3165 03:06:46,828 --> 03:06:49,898 And he loved music, especially mezzanine. 3166 03:06:50,499 --> 03:06:53,302 So I would like to include also the heard. 3167 03:06:53,302 --> 03:06:57,206 This already is inclusion of medical record technology 3168 03:06:57,439 --> 03:06:59,741 as an important part of an album research. 3169 03:07:00,509 --> 03:07:04,313 It was part of his tool 2006 Strategic Plan, 3170 03:07:04,880 --> 03:07:08,150 and he believed breathing life into medical informatics 3171 03:07:08,450 --> 03:07:10,786 from the beginning of his tenure at the library. 3172 03:07:11,320 --> 03:07:15,157 So An Alarm was a major funder of medical research 3173 03:07:15,524 --> 03:07:19,261 until recent years, when urban institutes discovered it. 3174 03:07:19,895 --> 03:07:22,998 He fostered the creation of AMIA and was its first president. 3175 03:07:23,365 --> 03:07:25,734 And I was privileged to be as it is. Exactly. 3176 03:07:25,734 --> 03:07:28,070 And had a cabinet for two years. 3177 03:07:29,071 --> 03:07:31,106 I love to listen to him talk 3178 03:07:32,374 --> 03:07:33,976 extemporaneously. 3179 03:07:33,976 --> 03:07:39,448 His phrasing was polished, lively and clever just as it flowed out of his mouth. 3180 03:07:39,615 --> 03:07:45,520 As though I had written and had edited is also willing to say what he thought. 3181 03:07:45,687 --> 03:07:48,824 Tell it like it was a rare treat in Washington. 3182 03:07:49,591 --> 03:07:53,629 So after I joined it all and he and I would often meet 3183 03:07:53,629 --> 03:07:57,032 at the end of the day and toward the end of the meeting, he would say, 3184 03:07:57,032 --> 03:08:00,035 Hey, how about coming home to dinner with Mary and me? 3185 03:08:00,302 --> 03:08:04,139 That's a lot of what you can't really bring a guest home on such short notice. 3186 03:08:04,406 --> 03:08:05,874 What would Mary say? 3187 03:08:05,874 --> 03:08:10,045 And she always said, yes, I had many late 3188 03:08:10,078 --> 03:08:14,249 invitation dinners with him many, many times with Mary's cooking. 3189 03:08:14,549 --> 03:08:17,085 They were gustatory delights. 3190 03:08:17,085 --> 03:08:19,888 Some people saw Don and started tough and it could be. 3191 03:08:19,888 --> 03:08:23,225 There was also great fun. He loved to laugh. 3192 03:08:23,258 --> 03:08:26,495 So those meetings with me and Mary for a special treat, 3193 03:08:28,530 --> 03:08:29,464 he and Mary, I 3194 03:08:29,464 --> 03:08:33,168 really can involve the combined almost in everybody's mind 3195 03:08:33,402 --> 03:08:37,039 because they always work together and how they connected. 3196 03:08:37,439 --> 03:08:40,242 There's a readymade script for a romantic comedy. 3197 03:08:40,242 --> 03:08:40,909 I got this. 3198 03:08:40,909 --> 03:08:43,211 I had a long talk with Mary recently. 3199 03:08:43,712 --> 03:08:44,579 She's a she. 3200 03:08:44,579 --> 03:08:47,949 When she met him, she was working on a little baby 3201 03:08:48,283 --> 03:08:52,287 in the Vanderbilt pediatric treatment room at Columbia Hospital. 3202 03:08:53,055 --> 03:08:56,792 She and her team were unsuccessful in drawing blood 3203 03:08:56,792 --> 03:09:00,595 after two sticks, and as a matter of principle, 3204 03:09:00,962 --> 03:09:03,298 she would not stick a child more than twice. 3205 03:09:03,832 --> 03:09:08,136 So she sent a note to the lab saying, I will. 3206 03:09:08,236 --> 03:09:13,742 Unable to draw a blood sample down was a resume in clinical pathology at that time, 3207 03:09:14,309 --> 03:09:17,145 and he showed up shortly thereafter , 3208 03:09:17,145 --> 03:09:20,282 asking very arrogantly, No, those are her words. 3209 03:09:20,615 --> 03:09:22,017 Who wrote this note? 3210 03:09:22,017 --> 03:09:23,518 I did, she replied. 3211 03:09:23,518 --> 03:09:25,287 And he continued arrogantly. 3212 03:09:25,287 --> 03:09:26,722 What have you trained? 3213 03:09:26,722 --> 03:09:29,791 And she said, Simmons College, affiliated with Harvard. 3214 03:09:30,392 --> 03:09:32,594 And she asked, Where did you train? 3215 03:09:32,728 --> 03:09:34,129 He said, Amherst. 3216 03:09:34,129 --> 03:09:36,698 And then very shortly they brought it out. 3217 03:09:37,132 --> 03:09:40,035 Amherst has a football game with Williams in October. 3218 03:09:40,202 --> 03:09:41,903 Would you be my date? 3219 03:09:41,903 --> 03:09:45,574 She said, Well, I'm engaged to be married in December. 3220 03:09:45,574 --> 03:09:48,810 And he said explicitly, maybe another time. 3221 03:09:49,144 --> 03:09:53,348 However, he found out the next day and asked her again and she said okay. 3222 03:09:54,049 --> 03:09:56,318 After that he asked her on another day. 3223 03:09:56,818 --> 03:09:57,753 Can't go that day. 3224 03:09:57,753 --> 03:09:59,654 I have a prior appointment. 3225 03:09:59,654 --> 03:10:03,091 The appointment was to sit for her wedding to another guy. 3226 03:10:03,692 --> 03:10:05,827 Somehow they worked out another date. 3227 03:10:06,361 --> 03:10:09,631 She lived in Manhattan and the date was in New Jersey. 3228 03:10:09,931 --> 03:10:14,536 Coming back, he became very lost and ignored all of her admonitions 3229 03:10:14,770 --> 03:10:19,674 about how to get back to Washington Bridge on the way to Manhattan. 3230 03:10:19,875 --> 03:10:25,213 They circle for hours and finally found, despite his stubborn resistance 3231 03:10:25,213 --> 03:10:29,851 to her advice on the way that day, he asked her to marry him. 3232 03:10:30,285 --> 03:10:32,687 No mass gathered under Dan's Street. 3233 03:10:33,121 --> 03:10:34,322 She said yes. 3234 03:10:34,322 --> 03:10:37,859 I asked Mary, How could you decide to marry him after two days? 3235 03:10:38,293 --> 03:10:41,563 She said, We spent many hours together in New Jersey. 3236 03:10:42,597 --> 03:10:44,933 I also had another great privilege. 3237 03:10:44,933 --> 03:10:47,569 Mary called me over to Suburban Hospital to join 3238 03:10:47,736 --> 03:10:50,105 the immediate family for his last two days. 3239 03:10:50,839 --> 03:10:54,476 It was no longer fully conscious, but occasionally responding 3240 03:10:54,476 --> 03:10:58,346 with a moment or a grimace that suggested he understood something. 3241 03:10:58,914 --> 03:11:00,849 We held his hand at times. 3242 03:11:00,849 --> 03:11:04,453 Those two days with him and his immediate family, 3243 03:11:04,453 --> 03:11:07,722 their most precious moments and his last hours. 3244 03:11:07,722 --> 03:11:10,592 I got to kiss his forehead, squeeze his hand 3245 03:11:10,859 --> 03:11:14,229 and say good bye, old friend. 3246 03:11:14,229 --> 03:11:16,832 Thank you very much for being a chance to 3247 03:11:17,933 --> 03:11:20,936 present these stories to you. 3248 03:11:24,739 --> 03:11:26,875 Dr. MacDonald, thank you very, very much. 3249 03:11:27,042 --> 03:11:31,279 For pulling together those stories and reflections of Dr. 3250 03:11:31,279 --> 03:11:33,248 Lundberg and certainly Mary as well. 3251 03:11:33,248 --> 03:11:34,749 Thank you for sharing. 3252 03:11:35,717 --> 03:11:38,353 It's now my pleasure to introduce our next speaker, Dr. 3253 03:11:38,353 --> 03:11:42,157 Sally Howe, who's going to be joining us today by prerecorded video 3254 03:11:42,524 --> 03:11:43,859 to speak about Dr. 3255 03:11:43,859 --> 03:11:47,896 Lindbergh's high performance computing and communications leadership. As 3256 03:11:48,864 --> 03:11:50,432 Dr. Howe began her government 3257 03:11:50,432 --> 03:11:55,036 career in 1980 at the National Institute of Standards and Technology Nest, 3258 03:11:55,370 --> 03:11:59,074 where she worked in statistical computing and computational geometry. 3259 03:11:59,441 --> 03:12:03,011 And there she was, chief of the Scientific Computing Environments Division. 3260 03:12:03,678 --> 03:12:07,182 In 1992, she joined the newly established National 3261 03:12:07,182 --> 03:12:12,020 Coordinating Office for High Performance Computing and Communication, or PCC. 3262 03:12:12,654 --> 03:12:17,092 She worked there and at its center, the National Coordinating Office 3263 03:12:17,559 --> 03:12:22,230 for Networking and Information Technology R&D until 2007, 3264 03:12:22,230 --> 03:12:27,269 including as Associate Director from 2001 until 2007 . 3265 03:12:27,269 --> 03:12:28,203 From 2007. 3266 03:12:28,203 --> 03:12:32,040 Until her until her retirement in 2017, Dr. 3267 03:12:32,040 --> 03:12:34,142 Howe was at the National Library of Medicine 3268 03:12:34,142 --> 03:12:37,379 for the National Coordinating Office for HPC, have been located 3269 03:12:37,379 --> 03:12:41,016 since the mid 1990s and Elm. Dr. 3270 03:12:41,016 --> 03:12:44,185 Howe worked in the areas of health effects of climate change 3271 03:12:44,419 --> 03:12:46,888 and she built the print archive and finding aid 3272 03:12:47,188 --> 03:12:49,724 for the National Coordinating Office for PCC. 3273 03:12:50,292 --> 03:12:53,028 We certainly appreciate her pre-recording her presentation 3274 03:12:53,028 --> 03:12:54,896 as part of today's proceedings. 3275 03:12:54,896 --> 03:12:56,631 So I'm going to turn it over to Dr. Howe. 3276 03:13:02,137 --> 03:13:04,973 Hi. My name is Sally. How? 3277 03:13:05,340 --> 03:13:07,175 Thanks for inviting me. 3278 03:13:07,175 --> 03:13:11,713 My talk is about Don Lindbergh's high performance computing and communications 3279 03:13:12,013 --> 03:13:15,250 or HPC C Leadership and legacy. 3280 03:13:16,251 --> 03:13:20,855 Don Lindbergh led the HPC C program from 1992 3281 03:13:21,189 --> 03:13:24,292 when it was created until 1995. 3282 03:13:24,926 --> 03:13:27,529 I joined the new National Coordination 3283 03:13:27,529 --> 03:13:30,732 Office for HPC C in 1992 3284 03:13:31,366 --> 03:13:33,902 and stayed for 15 years. 3285 03:13:33,902 --> 03:13:38,373 I'll talk about events from the 1980s to the present. 3286 03:13:39,040 --> 03:13:40,675 Next slide. 3287 03:13:42,177 --> 03:13:43,745 This quote is from Walter 3288 03:13:43,745 --> 03:13:46,781 Isaacson's 2014 book, The Innovators. 3289 03:13:47,315 --> 03:13:51,319 It captures the impact of Don Lindbergh's HPC leadership. 3290 03:13:51,953 --> 03:13:54,022 It was a two step process 3291 03:13:55,390 --> 03:13:59,160 over the course of more than three decades, the federal government, 3292 03:13:59,527 --> 03:14:02,597 working with private industry and research universities, 3293 03:14:02,964 --> 03:14:08,770 designed and built a computing networking and information technology, research 3294 03:14:08,770 --> 03:14:12,240 and development or R&D program to help 3295 03:14:12,240 --> 03:14:15,076 federal science and engineering agencies. 3296 03:14:16,011 --> 03:14:20,815 Those efforts were formalized in the presidential HPC program. 3297 03:14:21,316 --> 03:14:23,551 Don Lindbergh was its first leader. 3298 03:14:24,019 --> 03:14:27,155 He laid the foundation and the framework for the program, 3299 03:14:27,455 --> 03:14:29,324 which continues to this day. 3300 03:14:30,458 --> 03:14:32,694 Walter Isaacson went on. 3301 03:14:32,694 --> 03:14:36,131 Then the government, through that infrastructure, open 3302 03:14:36,431 --> 03:14:39,701 to ordinary citizens and commercial enterprises. 3303 03:14:40,301 --> 03:14:42,937 This was the national information infrastructure 3304 03:14:43,004 --> 03:14:47,242 or and AI or Al Gore's information superhighway. 3305 03:14:48,276 --> 03:14:53,782 In 1994, the HPC program was asked to add R&D 3306 03:14:53,948 --> 03:14:57,619 for the I, Lindbergh and HPC. 3307 03:14:57,686 --> 03:14:59,788 He didn't miss a beat. 3308 03:14:59,788 --> 03:15:02,891 The HPC Plus and AI community 3309 03:15:03,258 --> 03:15:07,195 funded and conducted the R&D to make America's 3310 03:15:07,195 --> 03:15:10,331 digital revolution of Isaacson's title 3311 03:15:10,765 --> 03:15:13,735 The Extraordinary Success That It Is. 3312 03:15:14,502 --> 03:15:16,171 Next slide. 3313 03:15:17,639 --> 03:15:19,574 This story begins inside 3314 03:15:19,574 --> 03:15:22,610 eight federal science and engineering agencies. 3315 03:15:23,144 --> 03:15:25,880 Researchers say researchers and managers 3316 03:15:25,880 --> 03:15:28,717 in those agencies were making two discoveries. 3317 03:15:29,384 --> 03:15:34,556 Computational science, modeling and simulation was proving itself 3318 03:15:34,823 --> 03:15:37,992 to be the third leg of scientific inquiry, 3319 03:15:38,293 --> 03:15:41,296 alongside experimentation and theory. 3320 03:15:42,097 --> 03:15:46,534 In fact, computational science could do things that experimentation 3321 03:15:46,701 --> 03:15:51,272 could not do, such as modeling and simulation of phenomena 3322 03:15:51,406 --> 03:15:53,975 that were very big or very small, 3323 03:15:54,442 --> 03:15:57,912 very fast or very slow or very far away. 3324 03:15:58,713 --> 03:16:01,783 It could do modeling and simulation of phenomena 3325 03:16:01,983 --> 03:16:04,552 that were dangerous to health or safety 3326 03:16:04,819 --> 03:16:07,388 or were prohibitively expensive. 3327 03:16:08,256 --> 03:16:13,061 So computational science could help the agencies achieve their mission goals. 3328 03:16:14,529 --> 03:16:15,396 They were also 3329 03:16:15,396 --> 03:16:19,734 discovering that a supercomputer architecture could do both numeric 3330 03:16:19,768 --> 03:16:23,404 calculations and symbolic or text processing. 3331 03:16:23,872 --> 03:16:26,674 The agency needed both. 3332 03:16:26,674 --> 03:16:29,878 Those eight agencies were the Big Four, 3333 03:16:30,345 --> 03:16:34,883 the Defense Advanced Research Projects Agency, the Department of Energy, 3334 03:16:35,316 --> 03:16:38,153 the National Aeronautics and Space Administration, 3335 03:16:38,486 --> 03:16:41,156 and the National Science Foundation. 3336 03:16:41,156 --> 03:16:44,959 Plus the National Institute of Standards and Technology. 3337 03:16:45,126 --> 03:16:48,329 The National Oceanic and Atmospheric Administration, 3338 03:16:48,696 --> 03:16:53,902 the Environmental Protection Agency and the National Library of Medicine. 3339 03:16:54,903 --> 03:16:56,404 Next slide. 3340 03:16:58,206 --> 03:17:00,041 Given those discoveries, 3341 03:17:00,041 --> 03:17:05,480 the agencies found they had common needs to do computational science. 3342 03:17:05,480 --> 03:17:08,183 They needed general purpose supercomputers 3343 03:17:08,449 --> 03:17:11,686 for unclassified science and engineering R&D. 3344 03:17:12,453 --> 03:17:17,292 The agencies were funding R&D by manufacturers who were building 3345 03:17:17,292 --> 03:17:21,262 supercomputers that agencies and the private sector were buying. 3346 03:17:22,397 --> 03:17:24,599 They needed high speed networks to connect 3347 03:17:24,599 --> 03:17:27,435 supercomputers to the researchers who used them. 3348 03:17:28,036 --> 03:17:32,574 They were funding R&D by companies that were building those networks, 3349 03:17:32,841 --> 03:17:35,977 and the agencies and others were buying services. 3350 03:17:37,045 --> 03:17:38,179 The agencies also 3351 03:17:38,179 --> 03:17:41,416 required that their networks be interoperable. 3352 03:17:42,217 --> 03:17:45,486 All together, the agencies were funding and developing 3353 03:17:45,787 --> 03:17:48,590 the technologies underlying the Internet. 3354 03:17:50,525 --> 03:17:52,427 Those supercomputers and networks 3355 03:17:52,427 --> 03:17:55,296 would need to be ever faster and more capable. 3356 03:17:55,830 --> 03:18:00,902 That meant long term R&D, largely in universities and technology companies. 3357 03:18:01,636 --> 03:18:04,072 It would be expensive. 3358 03:18:04,072 --> 03:18:06,174 The agencies wanted to divide up the work 3359 03:18:06,608 --> 03:18:08,810 and have access to the results. 3360 03:18:10,278 --> 03:18:13,781 In those early days, few were thinking about ordinary 3361 03:18:13,815 --> 03:18:17,218 what ordinary citizens might need or want. 3362 03:18:18,186 --> 03:18:19,854 Next slide. 3363 03:18:24,525 --> 03:18:27,762 Under the umbrella of the Office of Science and Technology 3364 03:18:27,762 --> 03:18:32,600 Policy or OSTP in the Executive Office of the President. 3365 03:18:32,934 --> 03:18:36,604 The agencies laid out their case in a series of reports. 3366 03:18:37,171 --> 03:18:39,674 They recommended a balanced federal 3367 03:18:39,674 --> 03:18:42,510 R&D program in computer hardware, 3368 03:18:43,111 --> 03:18:47,048 software networks and education and training. 3369 03:18:48,116 --> 03:18:49,651 Next slide. 3370 03:18:51,686 --> 03:18:54,122 Their grand challenges, reports said. 3371 03:18:54,122 --> 03:18:58,159 Why grand challenges are fundamental problems in science 3372 03:18:58,159 --> 03:19:02,297 and engineering that have broad economic and scientific impact 3373 03:19:02,730 --> 03:19:05,199 and require high performance computing. 3374 03:19:06,234 --> 03:19:08,569 They spend climate and weather 3375 03:19:09,671 --> 03:19:12,140 machines like airplanes and cars. 3376 03:19:12,941 --> 03:19:16,811 The life sciences and general purpose tools 3377 03:19:16,811 --> 03:19:20,615 like visualization, imaging and virtual reality. 3378 03:19:22,450 --> 03:19:25,453 The visionary Don Lindbergh had written the book 3379 03:19:25,653 --> 03:19:29,691 The Computer and Medical Care in 1968. 3380 03:19:30,358 --> 03:19:33,361 He long knew that medicine and health care 3381 03:19:33,761 --> 03:19:36,597 needed powerful computers. 3382 03:19:36,597 --> 03:19:38,866 With the Global Change Research Act 3383 03:19:38,866 --> 03:19:41,269 becoming law in 1990, 3384 03:19:41,936 --> 03:19:46,107 Lindbergh observed that climate change was considered important 3385 03:19:46,474 --> 03:19:49,143 because it affected people. 3386 03:19:49,143 --> 03:19:52,580 He said he joined the next motor agency program 3387 03:19:52,847 --> 03:19:54,983 that also affected people. 3388 03:19:55,850 --> 03:19:58,453 That was IPCC. 3389 03:19:58,453 --> 03:19:59,988 Next slide. 3390 03:20:02,023 --> 03:20:03,725 What did Congress do? 3391 03:20:03,725 --> 03:20:07,495 It held hearings and funded R&D and procurements. 3392 03:20:09,063 --> 03:20:10,598 Senator Gore 3393 03:20:10,598 --> 03:20:13,234 and his colleagues in the House of Representatives 3394 03:20:13,668 --> 03:20:16,304 introduced high performance computing bills. 3395 03:20:17,005 --> 03:20:21,342 University and industry witnesses testified at hearings, 3396 03:20:21,709 --> 03:20:25,346 conveying support and offering good advice. 3397 03:20:26,047 --> 03:20:30,618 The HPC Act became law in December of 1991. 3398 03:20:32,286 --> 03:20:35,723 The EP said that the United States needed high performance 3399 03:20:35,723 --> 03:20:40,595 computing for national prosperity, national and economic security, 3400 03:20:41,262 --> 03:20:45,299 industrial production, engineering and scientific advancement. 3401 03:20:45,900 --> 03:20:48,236 That's still true today. 3402 03:20:48,236 --> 03:20:50,972 The act created a presidential program, 3403 03:20:51,406 --> 03:20:53,708 not the program led by an agency, 3404 03:20:54,175 --> 03:20:57,445 and was assigned responsibility to OSTP. 3405 03:20:58,679 --> 03:21:02,450 While informal planning and coordination had been fine, 3406 03:21:02,984 --> 03:21:06,220 a presidential program with growing requirements 3407 03:21:06,554 --> 03:21:11,259 and budgets and visibility warranted formal coordination. 3408 03:21:11,692 --> 03:21:14,429 That's where Don Lindbergh comes in. 3409 03:21:14,429 --> 03:21:16,631 The authorized appropriations 3410 03:21:16,631 --> 03:21:19,534 from sums otherwise authorized to be appropriated. 3411 03:21:20,068 --> 03:21:22,470 Funding was and still is 3412 03:21:22,737 --> 03:21:25,373 part of the regular budget process. 3413 03:21:25,773 --> 03:21:27,442 It wasn't a competition. 3414 03:21:28,743 --> 03:21:30,912 The law didn't give the program a name. 3415 03:21:31,412 --> 03:21:34,248 For many years it was the High Performance 3416 03:21:34,248 --> 03:21:36,384 Computing and Communications Program. 3417 03:21:37,351 --> 03:21:39,020 Next slide. 3418 03:21:40,655 --> 03:21:42,890 In the summer of 1992, 3419 03:21:43,124 --> 03:21:47,261 OSTP asked Don Lindbergh to lead a IPCC 3420 03:21:47,895 --> 03:21:51,833 that had two parts chairing the subcommittee, 3421 03:21:51,833 --> 03:21:56,204 which already existed and heading a new national coordination office. 3422 03:21:57,038 --> 03:21:59,507 Everyone was delighted. 3423 03:21:59,507 --> 03:22:03,611 He was the only HPC person who had both a national 3424 03:22:03,811 --> 03:22:06,714 and international reputation. 3425 03:22:06,714 --> 03:22:09,584 His selection signaled how important the government 3426 03:22:09,584 --> 03:22:13,921 thought both the program and the grand challenges were. 3427 03:22:14,989 --> 03:22:17,525 The agencies knew him and ILM, 3428 03:22:18,192 --> 03:22:21,462 and he could rely on the LIMS infrastructure 3429 03:22:21,929 --> 03:22:24,665 to get the CEO started quickly. 3430 03:22:25,566 --> 03:22:27,168 Next slide. 3431 03:22:28,503 --> 03:22:31,706 He set up a six person National Coordination Office. 3432 03:22:32,440 --> 03:22:35,776 Three of those people are in this picture, Dr. 3433 03:22:35,776 --> 03:22:40,381 Lindbergh's executive assistant, Pat Carson, and Charles Carlino, 3434 03:22:40,681 --> 03:22:44,285 who was the executive secretary of the chipset subcommittee. 3435 03:22:45,186 --> 03:22:48,189 The other three were a person and detail from there. 3436 03:22:48,256 --> 03:22:52,126 So an administrative assistant and myself. 3437 03:22:52,560 --> 03:22:54,562 Then on detail from this 3438 03:22:55,763 --> 03:22:57,265 next slide. 3439 03:22:59,000 --> 03:23:03,171 As we all know, Don Lindbergh was a curious 3440 03:23:03,171 --> 03:23:08,609 and voracious reader and a thinker across not just medicine and health care, 3441 03:23:08,809 --> 03:23:12,547 but also science and technology and the humanities. 3442 03:23:13,047 --> 03:23:15,983 He thought about how science and technology 3443 03:23:16,250 --> 03:23:18,953 could help people 3444 03:23:19,020 --> 03:23:21,422 before the HPC became law. 3445 03:23:21,822 --> 03:23:25,459 HPC people naturally associated themselves 3446 03:23:25,560 --> 03:23:29,764 primarily with their own agency or university or company. 3447 03:23:30,331 --> 03:23:33,568 They thought of themselves individually as hardware people 3448 03:23:33,834 --> 03:23:37,471 or software people or networking or applications. 3449 03:23:38,506 --> 03:23:42,743 Don Lindbergh helped them forge a new additional identity, 3450 03:23:43,311 --> 03:23:46,314 inviting them to his actions and his words 3451 03:23:46,647 --> 03:23:50,384 to be part of a broad HPC R&D community. 3452 03:23:51,519 --> 03:23:55,456 He did that by speaking at conferences and workshops on HPC 3453 03:23:55,656 --> 03:23:58,693 topics and visiting supercomputer centers. 3454 03:23:59,527 --> 03:24:02,630 He and the chipset met with supercomputer center directors, 3455 03:24:03,030 --> 03:24:07,835 leaders of software companies and leaders from the telecommunications industry. 3456 03:24:08,569 --> 03:24:10,738 He met with everyone who wanted to visit 3457 03:24:11,172 --> 03:24:14,442 and he talked to all of them about HPC. See? 3458 03:24:16,277 --> 03:24:18,779 In 1994, HPC 3459 03:24:19,113 --> 03:24:22,617 added R&D for the National Information Infrastructure 3460 03:24:23,284 --> 03:24:28,389 and AI R&D focus so focused on for applications areas 3461 03:24:28,889 --> 03:24:33,828 education, health care , manufacturing and digital libraries. 3462 03:24:34,428 --> 03:24:37,632 The HPC R&D community easily 3463 03:24:37,632 --> 03:24:41,035 expanded to include an AI R&D. 3464 03:24:42,870 --> 03:24:44,171 Donlin Berg remained 3465 03:24:44,171 --> 03:24:47,174 an Elm director while guiding PCC. 3466 03:24:47,608 --> 03:24:51,679 He spent mornings at his office on the mezzanine of an LMS 3467 03:24:51,679 --> 03:24:54,282 main building doing an elm work. 3468 03:24:55,049 --> 03:24:58,953 Then he spent afternoons at PCC National Coordination 3469 03:24:58,953 --> 03:25:01,622 Office doing PCC work. 3470 03:25:02,223 --> 03:25:04,292 The NCO was in D1, 3471 03:25:04,759 --> 03:25:08,162 the E4 basement of an Elms Leinster Hill 3472 03:25:08,162 --> 03:25:11,032 National Center for Biomedical Communications 3473 03:25:12,099 --> 03:25:16,203 and Elm was an early adopter of HPC technologies. 3474 03:25:16,804 --> 03:25:22,276 It moved key services to the Internet in early 1996 and offered 3475 03:25:22,343 --> 03:25:25,413 free public access to PubMed for 3476 03:25:25,413 --> 03:25:28,015 sports and retrieval of biomedical literature. 3477 03:25:28,649 --> 03:25:30,451 In 1997. 3478 03:25:30,451 --> 03:25:32,219 Its next fight. 3479 03:25:35,389 --> 03:25:37,425 In April 1993, 3480 03:25:37,525 --> 03:25:40,728 seven months after he became head of HP CC, 3481 03:25:41,228 --> 03:25:43,597 Don Lindbergh wrote his lessons learned. 3482 03:25:44,665 --> 03:25:47,535 He acknowledged his excellent, reliable 3483 03:25:47,535 --> 03:25:50,237 and self-motivated agency colleagues. 3484 03:25:51,405 --> 03:25:55,376 He introduced and welcomed every newcomer at their first tips. 3485 03:25:55,376 --> 03:25:58,779 That meeting kept up with their progress and asked 3486 03:25:58,779 --> 03:26:01,315 good questions to probe their views. 3487 03:26:02,149 --> 03:26:03,651 Next slide. 3488 03:26:05,953 --> 03:26:07,722 His HPC colleagues 3489 03:26:07,722 --> 03:26:13,260 had a surprising tolerance for the efforts required to adjust common goals 3490 03:26:13,561 --> 03:26:16,897 to satisfy the numerous agency mission requirements. 3491 03:26:17,531 --> 03:26:19,300 He made that easier. 3492 03:26:19,300 --> 03:26:24,405 The NCO started adding technical coordinators, subject matter professionals 3493 03:26:24,705 --> 03:26:27,775 who helped the agencies identify their shared 3494 03:26:27,775 --> 03:26:30,144 goals and document progress. 3495 03:26:30,878 --> 03:26:32,680 Next slide. 3496 03:26:34,815 --> 03:26:36,884 HPC needed 3497 03:26:36,884 --> 03:26:40,354 conscious application of ordinary management systems 3498 03:26:40,354 --> 03:26:43,691 and principles to the operation of the complex 3499 03:26:43,691 --> 03:26:45,860 HPC Project Project, 3500 03:26:46,727 --> 03:26:48,763 and it needed careful documentation 3501 03:26:49,029 --> 03:26:53,601 and formal dissemination of the results to agencies and the public. 3502 03:26:54,769 --> 03:26:56,170 To that end, the 3503 03:26:56,170 --> 03:26:58,806 NCO had full time technical writers 3504 03:26:59,173 --> 03:27:03,110 who drafted the annual supplements to the President's budget request 3505 03:27:03,411 --> 03:27:07,081 required by the law and drafted technical reports. 3506 03:27:08,182 --> 03:27:09,817 Next slide. 3507 03:27:11,786 --> 03:27:12,219 He wrote 3508 03:27:12,219 --> 03:27:16,791 that multi-agency budget cross cuts are worthwhile for projects 3509 03:27:16,791 --> 03:27:20,828 of clear national importance and cross-agency agency relevance. 3510 03:27:21,429 --> 03:27:23,697 Today there are only three. 3511 03:27:24,231 --> 03:27:28,602 Climate change, IPCC and nanotechnology. 3512 03:27:29,670 --> 03:27:31,472 Next slide. 3513 03:27:32,973 --> 03:27:36,377 This photo from the NCO for HP CC 3514 03:27:36,410 --> 03:27:40,080 Archive housed in NLM History of Medicine Division. 3515 03:27:40,581 --> 03:27:45,319 Looks like it was taken at the 1995 reception honoring Dr. 3516 03:27:45,319 --> 03:27:50,424 Lindbergh after he had stepped down as the chair and CEO director. 3517 03:27:50,991 --> 03:27:55,729 It reflects HPC sees several parts from left to right. 3518 03:27:56,030 --> 03:27:59,166 Our icon of inventing the internet 3519 03:27:59,166 --> 03:28:01,969 same and on the NLM Board of Regents 3520 03:28:02,436 --> 03:28:06,574 Tom Pike of NOA and Applications R&D Agency. 3521 03:28:07,107 --> 03:28:09,910 Norman Glick of the National Security Agency, 3522 03:28:10,177 --> 03:28:12,680 a computing systems R&D agency. 3523 03:28:12,947 --> 03:28:14,014 And Dr. Lindbergh. 3524 03:28:15,082 --> 03:28:16,917 Next slide. 3525 03:28:18,652 --> 03:28:19,520 Today. 3526 03:28:19,520 --> 03:28:22,456 PCC Is the networking and information 3527 03:28:22,456 --> 03:28:25,960 technology R&D or needed program. 3528 03:28:26,494 --> 03:28:28,662 It has 12 components. 3529 03:28:28,662 --> 03:28:33,133 The first six listed here trace their roots to the 1990s. 3530 03:28:33,534 --> 03:28:36,637 They include high capability computing, 3531 03:28:36,637 --> 03:28:40,374 infrastructure and applications and large scale networking. 3532 03:28:41,008 --> 03:28:43,043 The other six are newer. 3533 03:28:43,043 --> 03:28:48,048 They are R&D in large scale data artificial intelligence, 3534 03:28:48,449 --> 03:28:53,320 cybersecurity and privacy computing systems that help people 3535 03:28:54,188 --> 03:28:56,891 physical systems that have computers in them 3536 03:28:57,291 --> 03:29:00,961 and networks connected to them and robotics. 3537 03:29:02,296 --> 03:29:04,465 21 agencies participate. 3538 03:29:04,932 --> 03:29:08,302 The total budget is almost $8 billion, 3539 03:29:08,869 --> 03:29:12,206 and this is the largest at just over 2 billion. 3540 03:29:12,706 --> 03:29:16,544 NIH is number two at just under 2 billion. 3541 03:29:17,444 --> 03:29:20,381 24 NIH institutes and centers 3542 03:29:20,681 --> 03:29:23,684 plus NLM participate. 3543 03:29:23,684 --> 03:29:26,120 Sadly, NLM isn't 3544 03:29:26,120 --> 03:29:29,223 mentioned in the 2022 supplement. 3545 03:29:30,257 --> 03:29:31,892 Next slide. 3546 03:29:34,562 --> 03:29:35,696 But then supplement 3547 03:29:35,696 --> 03:29:39,900 notes that 30 years of PCC slash needed investments 3548 03:29:40,234 --> 03:29:44,972 underpinned our science and technology response to the pandemic. 3549 03:29:45,406 --> 03:29:46,440 They facilitated, facilitated 3550 03:29:47,708 --> 03:29:48,943 or enabled. 3551 03:29:48,943 --> 03:29:50,911 Rapid vaccine development. 3552 03:29:50,911 --> 03:29:53,347 Search for therapeutics and Cures. 3553 03:29:53,347 --> 03:29:54,949 Connectivity. 3554 03:29:54,949 --> 03:29:59,420 One thinks of the Internet, web browsers, search engines, smartphones 3555 03:29:59,620 --> 03:30:03,257 and video conferencing for many of us. 3556 03:30:03,824 --> 03:30:06,961 And access to supercomputers for COVID research 3557 03:30:08,028 --> 03:30:09,930 in early 2020. 3558 03:30:09,930 --> 03:30:13,467 Many, many HPC technologies needed 3559 03:30:13,567 --> 03:30:16,537 only to scale. 3560 03:30:16,537 --> 03:30:18,839 Without Donlin Works leadership, 3561 03:30:18,839 --> 03:30:22,977 HPC might have remained a technology R&D program 3562 03:30:23,410 --> 03:30:26,947 for the Federal Science and Engineering Engineering world. 3563 03:30:27,881 --> 03:30:30,751 With his leadership, a new broad 3564 03:30:31,018 --> 03:30:35,756 HPC C slash native community built and continues 3565 03:30:35,756 --> 03:30:38,826 to build the technologies underlying what 3566 03:30:38,859 --> 03:30:41,762 Walter Isaacson called a new economy. 3567 03:30:42,863 --> 03:30:44,665 Next slide. 3568 03:30:46,133 --> 03:30:48,168 HPC, CE technologies 3569 03:30:48,435 --> 03:30:50,938 and the knowledge and understanding they enable 3570 03:30:51,472 --> 03:30:54,842 now pervade every aspect of our lives. 3571 03:30:55,943 --> 03:30:59,346 In August 2022, just last month, 3572 03:30:59,980 --> 03:31:02,416 the Chips in Science Act became law. 3573 03:31:03,117 --> 03:31:08,555 It calls for OSTP to coordinate national scale technology, 3574 03:31:08,555 --> 03:31:13,427 R&D and transfer from federal agencies to the private sector. 3575 03:31:14,194 --> 03:31:18,298 The ACT identifies ten key technology focused areas 3576 03:31:18,866 --> 03:31:22,436 and five of which mention native topics. 3577 03:31:23,103 --> 03:31:27,074 Lindbergh's HPC See Now Named, could serve 3578 03:31:27,074 --> 03:31:31,178 as an excellent model for building their new community. 3579 03:31:32,613 --> 03:31:33,814 The End. 3580 03:31:33,814 --> 03:31:35,015 Thanks for watching. 3581 03:31:35,015 --> 03:31:36,316 Thanks very much to Dr. 3582 03:31:36,316 --> 03:31:37,951 Howe for her presentation. 3583 03:31:37,951 --> 03:31:41,655 And although she ends on a the end note, we all know 3584 03:31:41,655 --> 03:31:46,427 and as she mentioned 2 minutes earlier in her presentation, the story continues. 3585 03:31:46,427 --> 03:31:47,861 The leadership legacy of Dr. 3586 03:31:47,861 --> 03:31:53,367 Lindbergh remains squarely in place, along with now the leadership of Dr. 3587 03:31:53,367 --> 03:31:56,336 Brennan and future directors of the National Library of Medicine. 3588 03:31:56,670 --> 03:31:58,572 Thank you again, Dr. Howard. 3589 03:31:58,572 --> 03:32:02,042 Now we're going to proceed with the second panel of our program 3590 03:32:02,042 --> 03:32:06,313 entitled Lindbergh and the Evolution of the Library as Research Partner. 3591 03:32:07,314 --> 03:32:10,250 To this very end, it is my distinct pleasure to introduce 3592 03:32:10,250 --> 03:32:12,453 the chair of this second panel. 3593 03:32:12,453 --> 03:32:17,257 Teresa not serves as Associate Dean for the Virginia Commonwealth University 3594 03:32:17,257 --> 03:32:20,394 Libraries and Director of its Health Science Library. 3595 03:32:21,061 --> 03:32:24,164 Prior to joining Virginia Commonwealth University, she served 3596 03:32:24,331 --> 03:32:28,435 as the deputy director at the University of Maryland, Baltimore Health Sciences 3597 03:32:28,635 --> 03:32:31,839 and Human Services Library, and she held several positions 3598 03:32:31,839 --> 03:32:34,675 at the Texas Tech University Health Sciences Center 3599 03:32:34,842 --> 03:32:38,445 Library of the Health Sciences in Lubbock and in El Paso. 3600 03:32:39,213 --> 03:32:44,118 She was a 2526 National Library of Medicine Association 3601 03:32:44,118 --> 03:32:48,956 of Academic Health, Science Libraries and HHS Leadership Fellow. 3602 03:32:49,323 --> 03:32:54,762 And in 20 1718, she served as a mentor in the Leadership Development Program. 3603 03:32:55,629 --> 03:32:57,931 In 20 1617, she served 3604 03:32:57,931 --> 03:33:00,834 as President of the Medical Library Association, the MLA. 3605 03:33:01,268 --> 03:33:03,036 Theresa, not warm. Welcome to you. 3606 03:33:03,036 --> 03:33:04,972 Thank you for your time this afternoon. 3607 03:33:04,972 --> 03:33:06,607 I'm going to turn things over to you. Thank you. 3608 03:33:08,609 --> 03:33:10,844 Thank you for your kind introduction, Jeff. 3609 03:33:11,278 --> 03:33:12,513 Good afternoon. 3610 03:33:12,513 --> 03:33:13,380 I am pleased to welcome 3611 03:33:13,380 --> 03:33:16,450 you and all our distinguished panelists to the session on Lindbergh 3612 03:33:16,450 --> 03:33:19,219 and the evolution of the library as research partner. 3613 03:33:19,887 --> 03:33:23,123 As you've learned, Donald Abe Lindbergh was the visionary 3614 03:33:23,123 --> 03:33:26,627 leader of the National Library of Medicine for over 30 years. 3615 03:33:27,194 --> 03:33:30,330 He considered libraries of librarians key research partners. 3616 03:33:31,365 --> 03:33:32,132 Excuse me. 3617 03:33:32,132 --> 03:33:35,469 I was a fledgling health sciences librarian when Dr. 3618 03:33:35,469 --> 03:33:38,472 Lindbergh was appointed as the director of the National Library 3619 03:33:38,472 --> 03:33:40,674 of Medicine in 1984. 3620 03:33:42,042 --> 03:33:45,546 Dr. Charles Sargeant was my director at the time, and he had worked 3621 03:33:45,546 --> 03:33:49,082 closely with Lundberg, and they were both at the University of Missouri. 3622 03:33:49,483 --> 03:33:53,353 And Charlie was happy to share stories of his experience working with Lundberg. 3623 03:33:53,353 --> 03:33:54,454 And so. 3624 03:33:55,055 --> 03:33:57,591 Later, I had the privilege of attending the NLM 3625 03:33:57,591 --> 03:34:00,794 sponsored Woods Hole Biomedical Informatics Course, 3626 03:34:01,428 --> 03:34:04,398 an initiative that brought librarians, physicians, 3627 03:34:04,598 --> 03:34:08,235 health care providers informative sections together. 3628 03:34:08,669 --> 03:34:11,672 It was a transformative experience for many of us, and really 3629 03:34:11,672 --> 03:34:15,342 the first time I had the opportunity to interact directly with Dr. 3630 03:34:15,342 --> 03:34:16,410 Lindbergh. 3631 03:34:16,410 --> 03:34:19,780 He was visionary and inspiring and quite personable. 3632 03:34:20,614 --> 03:34:22,716 From my perspective, Dr. 3633 03:34:22,716 --> 03:34:26,587 Lindbergh initiated many programs that reshaped the work of health sciences, 3634 03:34:26,587 --> 03:34:29,756 librarians and researchers in the health sciences 3635 03:34:30,190 --> 03:34:34,962 while democratizing access to high quality health information and enhancing 3636 03:34:34,962 --> 03:34:38,298 clinical care through the application of biomedical informatics. 3637 03:34:39,233 --> 03:34:43,837 As we move forward, I would remind you that you can use the live feedback button 3638 03:34:43,837 --> 03:34:46,573 under your video window to send us questions, 3639 03:34:46,940 --> 03:34:47,241 and we'll 3640 03:34:47,241 --> 03:34:51,044 try to get to as many of your questions as possible after our panelists speak. 3641 03:34:52,679 --> 03:34:53,413 Today, our 3642 03:34:53,413 --> 03:34:56,850 panelists will share the current projects they are working on and how Dr. 3643 03:34:56,850 --> 03:34:59,319 Lindbergh's legacy echoes in their work. 3644 03:35:00,254 --> 03:35:03,190 Our first panel, Stephanie, is Christy Holmes. 3645 03:35:04,892 --> 03:35:08,228 Christy is the director of the Galtier Health Sciences Library 3646 03:35:08,228 --> 03:35:12,633 and Learning Center and Professor of Preventive Medicine in the Division 3647 03:35:12,633 --> 03:35:16,336 of Health and Biomedical Informatics at Northwestern University. 3648 03:35:16,637 --> 03:35:19,072 Feinberg School of Medicine in Chicago. 3649 03:35:20,240 --> 03:35:23,810 Christie served on the leadership team of the Northwestern University 3650 03:35:23,810 --> 03:35:27,047 Clinical and Translational Sciences Research Institute 3651 03:35:28,048 --> 03:35:28,415 and U. 3652 03:35:28,415 --> 03:35:32,986 States, where she directs evaluation and continuous improvement 3653 03:35:32,986 --> 03:35:36,556 for the Institute and several other programs and centers. 3654 03:35:37,190 --> 03:35:40,160 She also serves as the chief knowledge and excuse me, 3655 03:35:40,160 --> 03:35:44,231 the Chief of Knowledge Management and Northwestern's Institute 3656 03:35:44,231 --> 03:35:46,800 for Augmented Intelligence in Medicine 3657 03:35:47,301 --> 03:35:50,170 and directs the NL l am 3658 03:35:50,170 --> 03:35:53,740 the End and Health and National Evaluation Center. 3659 03:35:54,241 --> 03:35:57,511 Her work focuses on the discovery and equitable access 3660 03:35:57,511 --> 03:36:01,448 to knowledge through collaborative, computational and social action. 3661 03:36:02,149 --> 03:36:06,553 Today, Christie will speak on the Modern Library, found an article that Dr. 3662 03:36:06,553 --> 03:36:11,224 Lindbergh published in the Bulletin, the Medical Library Association, in 1996. 3663 03:36:11,692 --> 03:36:12,793 Christie, welcome. 3664 03:36:15,095 --> 03:36:15,529 Okay. 3665 03:36:15,529 --> 03:36:15,996 Great. 3666 03:36:15,996 --> 03:36:17,931 Thank you so much for that introduction. 3667 03:36:17,931 --> 03:36:20,534 Teresa, can you hear me? Okay? 3668 03:36:20,534 --> 03:36:22,336 Okay. Wonderful. Thank you. 3669 03:36:22,336 --> 03:36:25,005 I thank you all for the opportunity to join you today. 3670 03:36:25,038 --> 03:36:26,473 It is an absolute honor 3671 03:36:26,473 --> 03:36:30,377 to be part of this wonderful event that celebrates the life and legacy of Dr. 3672 03:36:30,377 --> 03:36:31,545 Lindbergh. 3673 03:36:31,545 --> 03:36:34,414 Before I begin my remarks, I'd like to take a moment to thank 3674 03:36:34,414 --> 03:36:38,585 the organizers, the National Library of Medicine, and the friends of the NLM. 3675 03:36:38,986 --> 03:36:41,221 Dr. Lindbergh's family and friends. 3676 03:36:41,321 --> 03:36:45,025 So many of my own collaborators and colleagues who have made profound 3677 03:36:45,025 --> 03:36:50,130 impact, impacts and influences on my own work are strong partners at Northwestern 3678 03:36:50,130 --> 03:36:52,132 University, Feinberg School of Medicine 3679 03:36:52,366 --> 03:36:56,303 and the dedicated and extremely talented team at Galtier Health Sciences 3680 03:36:56,303 --> 03:36:59,773 Library and Learning Center, who regularly make magic happen 3681 03:37:00,040 --> 03:37:03,643 through our resources, services and spaces, and whose work I will 3682 03:37:03,643 --> 03:37:06,113 briefly highlight a bit later in my remarks. 3683 03:37:06,747 --> 03:37:10,150 I also want to call attention to the design on some of my slides, 3684 03:37:10,150 --> 03:37:14,688 which reflects the design of the current strategic plan underway at Alnylam. 3685 03:37:15,088 --> 03:37:16,256 This active effort 3686 03:37:16,256 --> 03:37:19,960 builds on an incredible body of work at the National Library of Medicine, 3687 03:37:20,127 --> 03:37:23,530 accelerating biomedical discovery and data powered health. 3688 03:37:23,864 --> 03:37:28,201 It is indeed a bright future for libraries as research partners. 3689 03:37:33,707 --> 03:37:36,810 Dr. Lindbergh's impact is impossible to quantify 3690 03:37:37,077 --> 03:37:40,213 across biomedical informatics and library communities 3691 03:37:40,680 --> 03:37:45,018 through information standards, technology trends, a deep dedication 3692 03:37:45,018 --> 03:37:49,423 to interdisciplinary partnerships and thoughtful engagements to impact health. 3693 03:37:49,456 --> 03:37:52,192 His influence will be felt for years and years to come. 3694 03:37:52,759 --> 03:37:56,229 Perhaps the most remarkable is that much of his work was happening 3695 03:37:56,229 --> 03:37:59,433 during the relatively early days of the Internet, which Dr. 3696 03:37:59,433 --> 03:38:02,869 Lindbergh himself called an intellectual Wild West. 3697 03:38:03,570 --> 03:38:07,207 Today's foundational resources, such as those shown on the front page 3698 03:38:07,240 --> 03:38:11,078 of the National Library of Medicine website, which are shown on 3699 03:38:11,078 --> 03:38:15,582 the left like PubMed, ClinicalTrials.gov, Medline plus and more 3700 03:38:15,782 --> 03:38:19,653 were once new and unfamiliar, and as they were launched, 3701 03:38:19,653 --> 03:38:23,390 they offered access to medical information like never before. 3702 03:38:24,057 --> 03:38:26,760 A great example of that is shown here where we see Vice 3703 03:38:27,060 --> 03:38:31,231 President Al Gore with Suzanne McInerney, coauthor of Info Medicine. 3704 03:38:31,231 --> 03:38:34,234 David Lippman, who was the director of NCI at the time. 3705 03:38:34,601 --> 03:38:38,939 Harold Varmus, the director of NIH then, and Dr. 3706 03:38:38,939 --> 03:38:40,040 Lindbergh. 3707 03:38:40,040 --> 03:38:43,643 In the image, Vice President Gore is demonstrating a new system 3708 03:38:43,643 --> 03:38:47,714 developed by the NLM called PubMed, which simplified 3709 03:38:47,714 --> 03:38:52,686 searching for online medical information by researchers and the public alike. 3710 03:38:53,220 --> 03:38:56,623 The flexibility of PubMed and the ease of use prompted Gore 3711 03:38:56,623 --> 03:38:59,926 to make those remarkable comments we heard earlier in the video 3712 03:39:00,260 --> 03:39:01,761 in which the vice president said 3713 03:39:01,761 --> 03:39:04,831 making information like this freely available on the Web 3714 03:39:05,198 --> 03:39:09,269 maybe may do more to reform and improve the quality of health care 3715 03:39:09,269 --> 03:39:14,107 in the United States than anything else we have done in a long time. 3716 03:39:18,912 --> 03:39:19,479 I've thought a 3717 03:39:19,479 --> 03:39:22,149 lot about what to share during my remarks today. 3718 03:39:22,482 --> 03:39:26,953 Eventually, I came to the realization that I can likely never do a truly fitting 3719 03:39:26,987 --> 03:39:31,124 tribute to the legacy of Don Limburg and his lasting impact on libraries. 3720 03:39:31,124 --> 03:39:34,928 As as a research partner, I decided that perhaps I will just 3721 03:39:34,928 --> 03:39:38,465 contribute to the discussion with a few thoughts and experiences 3722 03:39:38,465 --> 03:39:42,335 that build upon the idea of libraries this research partners . 3723 03:39:42,335 --> 03:39:45,705 I'll also share the story of how I entered the world and found 3724 03:39:45,705 --> 03:39:49,009 a thoroughly invigorating professional home in libraries. 3725 03:39:49,342 --> 03:39:53,180 I cannot imagine a better place to be, and I am grateful to the champions 3726 03:39:53,180 --> 03:39:54,714 at NLM, such as Dr. 3727 03:39:54,714 --> 03:39:57,417 Lindbergh and Betsy Humphries and now Dr. 3728 03:39:57,417 --> 03:40:01,354 Brennan and so many others for their role in helping me find my way here. 3729 03:40:02,422 --> 03:40:04,024 Several years ago, I read Dr. 3730 03:40:04,024 --> 03:40:08,061 Lindbergh's lecture, The Modern Library Lost and found in which he present, 3731 03:40:08,061 --> 03:40:10,830 which he presented at the seventh International Congress 3732 03:40:10,830 --> 03:40:14,201 on medical librarianship in May of 1995. 3733 03:40:14,768 --> 03:40:18,338 There are a few passages I'd like to share with you today during my remarks. 3734 03:40:18,872 --> 03:40:22,776 First, he shares that the system of connections between computers 3735 03:40:22,776 --> 03:40:27,781 and their users has remade our world even more than the computers themselves. 3736 03:40:28,281 --> 03:40:29,616 He goes on to write. 3737 03:40:29,616 --> 03:40:30,984 Suffice it to say that 3738 03:40:30,984 --> 03:40:35,222 the spirit of voluntary cooperation and helpfulness within the library 3739 03:40:35,222 --> 03:40:39,025 and the medical communities permitted the work of NLM to be fruitful. 3740 03:40:39,693 --> 03:40:41,928 And here's the great section. 3741 03:40:41,962 --> 03:40:45,131 The Human Network, in other words, preceded 3742 03:40:45,131 --> 03:40:48,301 the electronic network, as it always must. 3743 03:40:48,301 --> 03:40:51,404 If useful services are to result. 3744 03:40:57,811 --> 03:40:59,446 Indeed, this human network 3745 03:40:59,446 --> 03:41:02,282 depicted as the puzzle pieces on the right of community 3746 03:41:02,282 --> 03:41:06,553 and capacity building, provides both a strong foundation, as well as momentum 3747 03:41:06,553 --> 03:41:10,357 for health sciences, libraries to partner, lead and champion . 3748 03:41:10,357 --> 03:41:14,127 Exciting efforts to translate and advance what we think of as a knowledge 3749 03:41:14,127 --> 03:41:17,330 network of data and resources in extraordinary ways. 3750 03:41:17,998 --> 03:41:21,501 This remarkable synergy between the human and knowledge networks 3751 03:41:21,501 --> 03:41:24,437 reminded me of a quote attributed to Aristotle, 3752 03:41:24,437 --> 03:41:27,540 where he communicates that the whole is something besides the part 3753 03:41:27,907 --> 03:41:31,444 in this case and the case of libraries, its research partners . 3754 03:41:31,444 --> 03:41:34,581 The whole is something much more impactful than the sum of the parts. 3755 03:41:34,581 --> 03:41:35,582 Indeed. 3756 03:41:41,855 --> 03:41:42,322 What? 3757 03:41:43,923 --> 03:41:45,358 I'm sorry. 3758 03:41:45,659 --> 03:41:47,727 Can we go back a couple of flights? 3759 03:42:02,409 --> 03:42:03,176 Okay. 3760 03:42:04,811 --> 03:42:06,446 As is the case for many of us 3761 03:42:06,446 --> 03:42:09,416 who have served in research roles in health sciences libraries. 3762 03:42:09,716 --> 03:42:12,652 My first major connection with the National Library of Medicine 3763 03:42:12,652 --> 03:42:13,920 was through training. 3764 03:42:13,920 --> 03:42:16,589 I joined Washington University's Becker Medical Library 3765 03:42:16,589 --> 03:42:19,626 as a bioinformatics test in the summer of 2006. 3766 03:42:19,959 --> 03:42:23,063 I just graduated with a biochemistry degree the year before, 3767 03:42:23,063 --> 03:42:27,000 and I was searching for something that would allow me to build programing 3768 03:42:27,000 --> 03:42:30,136 and connect with people in more of an infrastructure support role 3769 03:42:30,370 --> 03:42:33,506 rather than a discovery role that I might have as a postdoc. 3770 03:42:34,007 --> 03:42:36,543 I was able to quickly find training opportunities 3771 03:42:36,543 --> 03:42:39,879 at the National Library of Medicine, such as the Field Guide Workshops 3772 03:42:39,879 --> 03:42:42,882 and the CBI Advanced Workshop for Bioinformatics 3773 03:42:42,882 --> 03:42:46,619 Information Specialists, which is affectionately called Novice. 3774 03:42:46,920 --> 03:42:50,557 A five day intensive training program held at CDI, 3775 03:42:50,790 --> 03:42:53,560 which helped me get up and running to do my own workshops 3776 03:42:53,560 --> 03:42:56,863 and to be able to partner with researchers through consultation services. 3777 03:42:57,230 --> 03:43:00,867 I also found an incredibly supportive community of practice through a network 3778 03:43:00,867 --> 03:43:04,571 of bio information specialists at different libraries across the country 3779 03:43:04,871 --> 03:43:09,876 and through these novice leaders and an alum such as Renato Geer and a few 3780 03:43:10,243 --> 03:43:13,413 example papers of the work of this group are shown on the left. 3781 03:43:13,813 --> 03:43:17,317 For me, this is one of the most meaningful examples of the power of Dr. 3782 03:43:17,317 --> 03:43:20,086 Lindbergh's human network that NLM made possible. 3783 03:43:20,420 --> 03:43:23,089 Many of us have gone on to work together on various research 3784 03:43:23,089 --> 03:43:25,392 projects, outreach partnerships and more. 3785 03:43:26,259 --> 03:43:29,996 This focus on people continues today in a variety of ways and alarm. 3786 03:43:30,363 --> 03:43:34,901 For example, if we look at the Learn page today at NCBI, 3787 03:43:35,068 --> 03:43:38,471 we can see that it supports both end users and other workforce roles 3788 03:43:38,471 --> 03:43:41,207 who engage, use and support these resources. 3789 03:43:41,541 --> 03:43:45,512 A great example of this is the NCBI Virtual Outreach Event Series. 3790 03:43:45,779 --> 03:43:49,783 This series expanded online outreach to a worldwide audience of people 3791 03:43:49,783 --> 03:43:53,753 who use NCBI resources for biological and biomedical research, 3792 03:43:53,953 --> 03:43:57,090 science, education, clinical applications, and much more. 3793 03:43:57,457 --> 03:44:00,760 These virtual outreach events included a wide range of activities 3794 03:44:00,760 --> 03:44:04,964 such as interactive workshops, webinars and even codified. 3795 03:44:09,035 --> 03:44:10,136 Another great example 3796 03:44:10,136 --> 03:44:14,774 currently underway is the NIH Comparative Genomics Resource, or KDR, 3797 03:44:15,041 --> 03:44:15,909 a multi-year 3798 03:44:15,909 --> 03:44:19,979 National Library of Medicine project to maximize the impact of eukaryotic 3799 03:44:19,979 --> 03:44:24,651 research organisms and their genomic data resources to biomedical research. 3800 03:44:25,084 --> 03:44:29,522 The National Center for Biotechnology Information and as part of an alum, leads 3801 03:44:29,522 --> 03:44:31,191 both the development of this initiative 3802 03:44:31,191 --> 03:44:34,360 as well as the important work of engaging genomics communities. 3803 03:44:34,794 --> 03:44:38,198 Ultimately, the CCR project will facilitate reliable 3804 03:44:38,198 --> 03:44:41,501 comparative genomics analysis for eukaryotic organisms 3805 03:44:41,501 --> 03:44:43,770 in collaboration with the genomics community. 3806 03:44:44,637 --> 03:44:48,208 The CCR project intends to achieve several impacts that will benefit 3807 03:44:48,208 --> 03:44:51,711 research in the genomics community, which are listed here on the right. 3808 03:44:52,312 --> 03:44:53,847 Community Collaboration. 3809 03:44:53,847 --> 03:44:55,815 Again, that human network is critical. 3810 03:44:55,815 --> 03:44:59,419 The CCR feedback from the genomics community will inform 3811 03:44:59,419 --> 03:45:02,989 improvements made to and CVI data, tools and interfaces, 3812 03:45:03,289 --> 03:45:06,759 as well as help to guide new developments in these areas . 3813 03:45:06,759 --> 03:45:10,997 Moreover, KDR will enhance the NLM or and CDI health content 3814 03:45:11,531 --> 03:45:15,168 with community supplied content such that the sample metadata 3815 03:45:15,168 --> 03:45:19,105 and gene functional information and other types of resource information 3816 03:45:19,105 --> 03:45:22,842 like DAG to further empower scientific discovery. 3817 03:45:28,047 --> 03:45:30,850 My first meeting of Dr. 3818 03:45:30,850 --> 03:45:35,355 Limburg in person, as Teresa shared, was at the medical informatics 3819 03:45:35,355 --> 03:45:40,393 course in Woods Hole in 2007, another incredible human network program. 3820 03:45:40,760 --> 03:45:43,530 This course was launched in 1992 by Dr. 3821 03:45:43,530 --> 03:45:46,633 Limberg and Cathy Norton, who served as the director of the Marine 3822 03:45:46,633 --> 03:45:50,803 Biological Laboratory and the Woods Hole Oceanographic Institution Library 3823 03:45:50,803 --> 03:45:55,775 and Archives, who was a real information and technology trailblazer as well. 3824 03:45:56,175 --> 03:45:59,779 The course was designed to bring together medical doctors and librarians 3825 03:45:59,779 --> 03:46:04,150 who were in a position to be change agents in their institutions. 3826 03:46:07,320 --> 03:46:09,122 When I attended the course, I was now 3827 03:46:09,122 --> 03:46:12,959 one year into my job as a bioinformatics assistant, back her library. 3828 03:46:13,226 --> 03:46:16,129 I thoroughly enjoyed this training and consultation role on 3829 03:46:16,262 --> 03:46:20,099 campus building partnerships and programs for our research community. 3830 03:46:20,400 --> 03:46:23,069 But I was uncertain about this job long term. 3831 03:46:23,469 --> 03:46:26,506 While I was at the course, I had the chance to explore new ideas, 3832 03:46:26,506 --> 03:46:29,576 meet incredible people in the medical informatics community 3833 03:46:29,943 --> 03:46:31,411 who are shown here on this picture. 3834 03:46:31,411 --> 03:46:34,113 And I know there are a lot of familiar faces in this photo 3835 03:46:34,614 --> 03:46:37,917 and really think about my career and what might be possible. 3836 03:46:38,318 --> 03:46:39,719 During one chat with Dr. 3837 03:46:39,719 --> 03:46:42,689 Limberg, I had a chance to ask him about this. 3838 03:46:42,722 --> 03:46:45,959 I asked him if he thought I could make a career out of this, 3839 03:46:45,992 --> 03:46:50,463 and to be honest, I think I didn't really believe that a field of work 3840 03:46:50,463 --> 03:46:54,667 so interesting, supportive and fun could actually be a career for me. 3841 03:46:55,134 --> 03:46:56,002 His reply. 3842 03:46:57,136 --> 03:46:58,271 Why not this? 3843 03:46:58,271 --> 03:46:58,771 And why not? 3844 03:46:58,771 --> 03:47:00,873 You go for it and you won't regret it. 3845 03:47:01,140 --> 03:47:02,642 And I don't regret it. 3846 03:47:02,642 --> 03:47:05,211 After the medical informatics course, I crossed paths 3847 03:47:05,211 --> 03:47:08,514 with him at AMIA meetings and on campus at NLM through the Blair 3848 03:47:08,548 --> 03:47:12,685 Grant Review panel, and without fail he would ask me how I was doing, 3849 03:47:12,885 --> 03:47:16,389 what work I'd been up to, and how things were going in Missouri. 3850 03:47:16,756 --> 03:47:19,092 I appreciated his support and kindness. 3851 03:47:19,225 --> 03:47:23,029 Since that time, I've come to realize that everyone has a special Don 3852 03:47:23,029 --> 03:47:27,433 Limburg story that he was able to connect with so many in such a meaningful way. 3853 03:47:27,467 --> 03:47:29,669 It's a real testament to his legacy. 3854 03:47:32,071 --> 03:47:34,741 Looking back, my experience in the context of John's 3855 03:47:34,741 --> 03:47:37,744 human network of community and capacity building has set 3856 03:47:37,744 --> 03:47:42,048 a remarkably collaborative tone for so much of what I do today, both local 3857 03:47:42,048 --> 03:47:45,818 and national community and capacity building initiatives, catalyzing 3858 03:47:45,818 --> 03:47:49,656 new partnerships and projects, and helping me push against my own biases 3859 03:47:49,656 --> 03:47:52,458 and assumptions about data and methodologies in ways 3860 03:47:52,458 --> 03:47:56,129 that might not have been possible without this nurturing environment. 3861 03:47:56,763 --> 03:48:00,033 I also had the opportunity to think about putting data to work in new 3862 03:48:00,033 --> 03:48:03,336 and exciting ways not only for health care, research and education, 3863 03:48:03,336 --> 03:48:07,874 but also administrative workflows, knowledge dissemination and discovery 3864 03:48:07,874 --> 03:48:12,578 evaluation and continuous improvement and even understanding meaningful impact. 3865 03:48:12,812 --> 03:48:17,083 All of which has provided a strong foundation for our work at Northwestern. 3866 03:48:19,952 --> 03:48:23,423 The Cultural Scientist Librarian Learning Center, which I'll refer to as 3867 03:48:23,456 --> 03:48:26,726 Galtier, is a next generation fully integrated information 3868 03:48:26,726 --> 03:48:29,595 knowledge management hub for Feinberg School of Medicine. 3869 03:48:30,063 --> 03:48:33,733 Galtier provides dedicated support for the research, education and patient 3870 03:48:33,733 --> 03:48:37,303 care activities at the Feinberg School of Medicine in McCarter Medical Center. 3871 03:48:37,870 --> 03:48:41,474 Got Her is uniquely positioned as a unit within Northwestern 3872 03:48:41,474 --> 03:48:44,610 University Clinical and Translational Sciences Institute. 3873 03:48:44,610 --> 03:48:47,647 Are New Cats, the only relationship of its kind? 3874 03:48:47,914 --> 03:48:51,584 This relationship facilitates important synergies across research, 3875 03:48:51,584 --> 03:48:54,420 clinical and education priorities on campus. 3876 03:48:55,021 --> 03:48:59,292 We are actively involved in a wide range of research activities and partnerships 3877 03:48:59,292 --> 03:49:02,962 and cultures, such as an alum funded project with the Center 3878 03:49:02,962 --> 03:49:06,365 for Health Equity Transformation, which has catalyzed a partnership 3879 03:49:06,365 --> 03:49:10,670 with the Chicago Public Library, Chicago Department of Public Health and the Health 3880 03:49:10,670 --> 03:49:14,240 Sciences Libraries at the University of Chicago and the University of Illinois. 3881 03:49:14,240 --> 03:49:17,310 Chicago, a clinical informatics training program 3882 03:49:17,310 --> 03:49:21,681 with the Northwestern Medicine Enterprise Data Warehouse, a clinical information 3883 03:49:21,814 --> 03:49:25,518 program to support health care and a robust, systematic 3884 03:49:26,152 --> 03:49:28,821 review service across Feinberg School of Medicine, 3885 03:49:29,689 --> 03:49:32,091 as well as extensive partnerships and activities 3886 03:49:32,091 --> 03:49:35,728 with Northwestern's Institute for Augmented Intelligence in Medicine. 3887 03:49:36,929 --> 03:49:38,364 Beyond research activities, 3888 03:49:38,364 --> 03:49:41,634 we take our core library mission to heart every day. 3889 03:49:41,968 --> 03:49:43,803 This means a few specific things. 3890 03:49:43,803 --> 03:49:47,640 We intentionally focus our human network, including our community, community 3891 03:49:48,574 --> 03:49:51,511 of users and the culture library team. 3892 03:49:51,511 --> 03:49:55,481 We provide targeted and dependable services, resources and innovations, 3893 03:49:55,481 --> 03:49:59,485 and nurture inclusive action through our practices, collections and spaces. 3894 03:50:00,119 --> 03:50:03,723 We foster integrated partnerships and collaborative collaborative action. 3895 03:50:03,990 --> 03:50:06,926 We support professional development of our team, encouraging 3896 03:50:06,926 --> 03:50:09,595 and celebrating their professional growth and accomplishments. 3897 03:50:09,929 --> 03:50:13,332 And we advance our deep commitment to knowledge, equity and access 3898 03:50:13,332 --> 03:50:16,335 to make our library and collections welcome, accessible 3899 03:50:16,335 --> 03:50:18,237 and inclusive. 3900 03:50:20,873 --> 03:50:22,642 Our team has catalyzed enhancements 3901 03:50:22,642 --> 03:50:26,946 in library services and spaces to support strategic priorities and advancements 3902 03:50:26,946 --> 03:50:30,349 in information structure, aggregation, retrieval and application. 3903 03:50:31,184 --> 03:50:34,887 They are responsible for catalyzing remarkable enhancements in our clinical 3904 03:50:34,887 --> 03:50:38,524 support services, educational programing, special collections, 3905 03:50:38,825 --> 03:50:42,728 special projects, open science, research impact and so much more. 3906 03:50:43,229 --> 03:50:46,432 The blocks on the right highlight different departments at Alter Library, 3907 03:50:46,432 --> 03:50:47,967 which support an extensive range 3908 03:50:47,967 --> 03:50:51,571 of spaces, resources and services, both physical and virtual. 3909 03:50:52,138 --> 03:50:55,641 In addition to these departments, we also have two specialized cores 3910 03:50:55,641 --> 03:50:56,976 the Metrics and Impact Core 3911 03:50:56,976 --> 03:51:00,246 in the library's Department of Research, Assessment and Communications, 3912 03:51:00,513 --> 03:51:04,750 which supports evaluation, benchmarking and strategy needs across the enterprise 3913 03:51:05,084 --> 03:51:06,018 and the data lab. 3914 03:51:06,018 --> 03:51:09,021 A high tech data core for training, one on one consultations 3915 03:51:09,021 --> 03:51:11,858 and community building around informatics and data science. 3916 03:51:12,358 --> 03:51:15,261 The modern university library is not just a steward 3917 03:51:15,261 --> 03:51:18,164 of information, it is a partner in creating new knowledge. 3918 03:51:18,431 --> 03:51:21,634 Over the last several years, we've initiated a variety of programs 3919 03:51:21,634 --> 03:51:25,338 to align our library's priorities with our greater collaborative mission 3920 03:51:25,538 --> 03:51:29,876 and set a course for the library as a 21st century research partner. 3921 03:51:33,279 --> 03:51:35,982 To demonstrate the role of the library is a research partner. 3922 03:51:35,982 --> 03:51:39,819 I would like to highlight just one timely topic area to show how we leverage 3923 03:51:39,819 --> 03:51:43,656 the synergies possible through the human network of our user, community 3924 03:51:43,956 --> 03:51:47,593 and library team and that knowledge network of data and resources. 3925 03:51:48,060 --> 03:51:51,797 In this slide, we can see data sharing activities map to a few of our departments 3926 03:51:51,797 --> 03:51:53,733 in the library, further highlighting staff 3927 03:51:53,733 --> 03:51:57,136 library team expertize on this important research topic. 3928 03:51:57,837 --> 03:52:00,606 The culture team is a very collaborative one and works 3929 03:52:01,107 --> 03:52:04,010 often happens in cross-departmental collaborative working groups. 3930 03:52:04,644 --> 03:52:07,847 This is something we're working on now as a collaborative effort 3931 03:52:07,847 --> 03:52:12,151 to establish the resources and services, expertize and workflows needed to meet the 3932 03:52:12,151 --> 03:52:17,556 NIH data management and sharing policy, which goes into effect in January of 2023. 3933 03:52:18,224 --> 03:52:21,027 The Digital Systems Department provides expertize 3934 03:52:21,027 --> 03:52:24,730 for the creation, development, maintenance and support of technologies and culture. 3935 03:52:24,730 --> 03:52:29,001 Library accessibility is also advanced through the information systems 3936 03:52:29,001 --> 03:52:32,772 themselves to ensure that they meet accessibility standards and principles. 3937 03:52:33,239 --> 03:52:35,908 Digital Systems Houses The Data Lab, which includes 3938 03:52:35,908 --> 03:52:39,078 support for the entire research data management pipeline. 3939 03:52:39,478 --> 03:52:42,882 We are also enhancing our systems infrastructure as contributors and core 3940 03:52:42,882 --> 03:52:46,285 developer partners on the embedding our open source community 3941 03:52:46,285 --> 03:52:50,856 to build a turnkey next generation solution for digital repositories. 3942 03:52:51,624 --> 03:52:54,961 The Department's Data Lab provides consultation and training 3943 03:52:54,961 --> 03:52:56,562 for all stages of the research data 3944 03:52:56,562 --> 03:53:00,800 lifecycle and links the researchers with the university experts at cores and 3945 03:53:00,800 --> 03:53:04,904 other research facilities that can serve any complex needs that come in. 3946 03:53:06,105 --> 03:53:07,506 The Department of 3947 03:53:07,506 --> 03:53:11,477 Research, Assessments and Communication provides expertize in building metrics 3948 03:53:11,477 --> 03:53:15,648 and alternative metrics, information visualization for research, assessment 3949 03:53:15,915 --> 03:53:18,484 and advisory services for increasing the visibility 3950 03:53:18,484 --> 03:53:21,320 and accessibility of research in a digital environment. 3951 03:53:21,687 --> 03:53:24,190 Scholarly communications and digital scholarship, 3952 03:53:24,190 --> 03:53:28,060 including our repository, is a critical aspect of the preservation, 3953 03:53:28,294 --> 03:53:30,663 dissemination and re-use of research. 3954 03:53:31,697 --> 03:53:36,369 The Research and Information Services team shown in that light turquoise 3955 03:53:36,435 --> 03:53:41,073 block meets the educational, clinical and research needs of our campus. 3956 03:53:41,440 --> 03:53:44,510 Research and Information Services coordinates all reference 3957 03:53:44,510 --> 03:53:47,847 activities and culture as well as our Liaison Librarian program, 3958 03:53:47,847 --> 03:53:52,051 which pairs librarians with department centers, institutes and programs 3959 03:53:52,418 --> 03:53:57,323 to enhance communication, collaboration, and the effectiveness of our library 3960 03:53:57,590 --> 03:54:01,027 in supporting campus education, clinical and research needs. 3961 03:54:01,927 --> 03:54:04,330 The Collection, Management and Metadata Services 3962 03:54:04,330 --> 03:54:08,000 Team provides rapid and reliable access to resources. 3963 03:54:08,401 --> 03:54:12,038 The department's cataloging and metadata services are core to the way 3964 03:54:12,038 --> 03:54:15,775 we describe and make discoverable our resources and the care 3965 03:54:15,775 --> 03:54:21,047 we take to be aware of and address biases in our information systems and practices 3966 03:54:21,747 --> 03:54:24,617 not only in the past, but today as well. 3967 03:54:25,484 --> 03:54:27,987 Across these activities, we see the power of 3968 03:54:27,987 --> 03:54:31,023 integrated human and knowledge networks. 3969 03:54:34,627 --> 03:54:37,897 In listening to the comments of the earlier speakers and panelists, 3970 03:54:37,897 --> 03:54:41,567 it's clear that anything is possible when we focus our investments and time 3971 03:54:41,567 --> 03:54:46,472 and resources on a vibrant ecosystem that supports the evolution of resources 3972 03:54:46,472 --> 03:54:50,109 and data with the human community and capacity building component. 3973 03:54:50,609 --> 03:54:51,644 We see this in Dr. 3974 03:54:51,644 --> 03:54:54,146 Lindbergh's remarks at the end of this passage. 3975 03:54:54,647 --> 03:54:58,150 The modern library's evolution during the next ten years 3976 03:54:58,150 --> 03:55:00,286 do seem somewhat more clear. 3977 03:55:00,286 --> 03:55:03,689 More sophistication will be expected both of the user 3978 03:55:03,689 --> 03:55:07,293 of the information and of the librarian who arranges for it. 3979 03:55:07,660 --> 03:55:11,730 In this respect, the modern library will be ever more interesting. 3980 03:55:12,264 --> 03:55:16,669 It is critical that we keep an open mind and unfailing optimism about 3981 03:55:16,669 --> 03:55:20,172 what is possible when we work together to realize the vision that Dr. 3982 03:55:20,172 --> 03:55:23,409 Lindbergh had of the library as a research partner. 3983 03:55:26,345 --> 03:55:27,713 As we look to the future, we 3984 03:55:27,713 --> 03:55:31,851 will continue our keen focus on research, education and clinical priorities 3985 03:55:32,184 --> 03:55:35,921 and will grow in ways that reflect the evolution of our campus and mission. 3986 03:55:36,422 --> 03:55:40,526 Areas of effort will feature human and knowledge networks working in synergy 3987 03:55:40,526 --> 03:55:45,531 to produce new strategic partnerships and the evolution of our research services 3988 03:55:45,531 --> 03:55:49,802 and resources to harness this work to power innovation and discovery. 3989 03:55:50,402 --> 03:55:53,572 While various priorities and opportunities will emerge over time, 3990 03:55:53,572 --> 03:55:57,343 we will work to be nimble and continue to prioritize actions to support 3991 03:55:57,343 --> 03:56:01,447 the role of the library as an active, open and transformative 3992 03:56:01,447 --> 03:56:03,549 research partner. 3993 03:56:04,617 --> 03:56:06,452 I'd like to invite everyone. 3994 03:56:06,452 --> 03:56:10,556 There are a number of really amazing resources that have been made available 3995 03:56:10,556 --> 03:56:14,360 by the National Library of Medicine, and we're really just 3996 03:56:14,660 --> 03:56:19,231 such a pleasure to go back and reread in preparation for this. 3997 03:56:19,231 --> 03:56:21,400 And I wanted to include those here 3998 03:56:21,400 --> 03:56:25,237 and and I'd like to thank you for your time and attention. And 3999 03:56:26,205 --> 03:56:26,906 I'm excited 4000 03:56:26,906 --> 03:56:30,276 to hear the remarks from my fellow panelists. 4001 03:56:30,309 --> 03:56:31,443 Thank you. 4002 03:56:33,712 --> 03:56:35,181 Thank you, Christine. 4003 03:56:35,181 --> 03:56:38,984 One of the things that you talked about that really resonated with me is how 4004 03:56:39,318 --> 03:56:43,689 the human network that Lindbergh referenced lives on through those 4005 03:56:43,689 --> 03:56:47,193 speaking here today, those who are attending, as well as how 4006 03:56:47,526 --> 03:56:51,597 Lindbergh really leveraged the human network synergies to fill social stage 4007 03:56:51,597 --> 03:56:56,268 creation of interconnected systems to improve health across the world. 4008 03:56:56,769 --> 03:57:00,406 So with that, thank you so much for sharing your experience 4009 03:57:00,406 --> 03:57:02,274 at Northwestern. 4010 03:57:04,376 --> 03:57:07,179 Our second panelist this afternoon is Philip Morrow 4011 03:57:07,179 --> 03:57:11,650 Payne, PHC from the Washington University in Saint Louis. 4012 03:57:11,650 --> 03:57:15,721 Philip is the Janet and Bernard Becker, professor and director of the Institute 4013 03:57:15,721 --> 03:57:21,293 for Informatics or IQ at Washington University Saint Louis School of Medicine. 4014 03:57:21,594 --> 03:57:24,563 Philip serves as associate dean for health information 4015 03:57:24,563 --> 03:57:27,866 and Data Science and is the chief data scientist. 4016 03:57:28,400 --> 03:57:32,171 He is internationally recognized as a leader in the field of clinical 4017 03:57:32,171 --> 03:57:37,710 research, informatics and translational bioinformatics, as well as in the fields 4018 03:57:37,710 --> 03:57:41,580 of clinical research informatics and translational bioinformatics. 4019 03:57:42,214 --> 03:57:46,385 His research portfolio is actively supported by a combination of 4020 03:57:46,919 --> 03:57:50,556 in Katz and 11 NCI grants and contracts, 4021 03:57:50,556 --> 03:57:55,060 as well as a variety of awards from both nonprofit and philanthropic organizations. 4022 03:57:55,661 --> 03:57:57,429 Today, Philip is going to speak about 4023 03:57:57,429 --> 03:58:01,166 integrating informatics in the Health Sciences Library, creating 4024 03:58:01,166 --> 03:58:04,236 a digital hub for the contemporary academic health science. 4025 03:58:04,737 --> 03:58:06,372 Philip Great. 4026 03:58:06,372 --> 03:58:08,107 Thank you, Theresa, for the introduction. 4027 03:58:08,107 --> 03:58:12,077 And I have to admit, I'm a little daunted by the prospect of following Dr. 4028 03:58:12,077 --> 03:58:14,980 Holmes, who I consider to be a good friend and colleague. 4029 03:58:15,848 --> 03:58:18,250 So I will do my very best to continue 4030 03:58:18,851 --> 03:58:22,421 the sort of high bar that she set with her presentation. 4031 03:58:23,088 --> 03:58:25,691 So I'm really excited and honored to be here 4032 03:58:25,691 --> 03:58:28,093 today, and I appreciate the invitation. 4033 03:58:28,093 --> 03:58:30,863 Like many of the speakers at panelists today, almost 4034 03:58:30,863 --> 03:58:34,767 every aspect of my career can be traced back to the influence that Dr. 4035 03:58:34,767 --> 03:58:35,868 Weinberg had. 4036 03:58:35,868 --> 03:58:39,171 And I'll leave a few remarks about that towards the end of my presentation. 4037 03:58:39,171 --> 03:58:39,838 So don't worry. 4038 03:58:39,838 --> 03:58:44,043 If you haven't heard me speak about that, I will touch on that topic. 4039 03:58:44,476 --> 03:58:48,380 But what I do want to talk a bit about is the efforts that are underway here 4040 03:58:48,380 --> 03:58:53,185 at Washington University in Saint Louis to integrate our Health Sciences Library 4041 03:58:53,419 --> 03:58:56,655 with our broader data, information and knowledge enterprise 4042 03:58:56,655 --> 03:58:59,425 in support of the School of Medicine's multiple missions. 4043 03:58:59,925 --> 03:59:03,429 And you may note that I, unlike some of my fellow panelists, am 4044 03:59:03,429 --> 03:59:07,199 not really a traditional medical library professional. 4045 03:59:07,199 --> 03:59:10,869 In fact, I have trained and spent the bulk of my career as an implementation 4046 03:59:11,170 --> 03:59:14,039 and only recently stepped into a role where I took responsibility 4047 03:59:14,039 --> 03:59:16,542 for the strategic direction of the library. 4048 03:59:16,542 --> 03:59:19,778 So I think I'll bring a slightly different lens to this and hopefully one 4049 03:59:19,778 --> 03:59:23,515 that makes sense with the broader theme of today's sessions. 4050 03:59:25,351 --> 03:59:27,119 So I want to start. 4051 03:59:27,119 --> 03:59:29,621 Well, I've already missed one of my slides. 4052 03:59:29,621 --> 03:59:31,824 I want to start with a quote. 4053 03:59:31,824 --> 03:59:34,626 And many people have provided quotes today. 4054 03:59:34,626 --> 03:59:36,528 And I think in part, that is because Dr. 4055 03:59:36,528 --> 03:59:40,899 Lindbergh was so voluminous in his contributions to the knowledge base. 4056 03:59:41,467 --> 03:59:43,302 But this particular quote from Dr. 4057 03:59:43,302 --> 03:59:46,905 Lindbergh's swearing in ceremony as the director of the NLM 4058 03:59:46,905 --> 03:59:51,043 in 1984 was particularly prescient, given what I wanted to talk about, 4059 03:59:51,610 --> 03:59:57,116 because really the theme here in this quote is that the role of data, 4060 03:59:57,116 --> 04:00:02,087 information and knowledge in modern medicine was only going to increase, 4061 04:00:02,421 --> 04:00:03,789 and that as a result of that, 4062 04:00:03,789 --> 04:00:07,960 the fields of informatics and library science were inextricably 4063 04:00:07,960 --> 04:00:12,164 intermingled and central to the future success of the Academic Health Center. 4064 04:00:12,431 --> 04:00:14,666 And really, health and wellness more broadly. 4065 04:00:15,434 --> 04:00:18,504 And I think one of the true testaments to Dr. 4066 04:00:18,504 --> 04:00:21,640 Lindbergh's leadership is that he recognized this well before. 4067 04:00:21,640 --> 04:00:25,210 I think almost anyone else in our field, with the exception of a few 4068 04:00:25,744 --> 04:00:28,046 other key individuals who have participated today 4069 04:00:28,380 --> 04:00:31,984 and have also made remarks really fully understood. 4070 04:00:33,786 --> 04:00:36,121 So as I mentioned, I want to start by just saying a little bit 4071 04:00:36,121 --> 04:00:40,492 about the Becker Medical Library here at Washington University in Saint Louis. 4072 04:00:40,492 --> 04:00:41,226 And actually, Dr. 4073 04:00:41,226 --> 04:00:44,496 Holmes did a nice job of providing a little bit of a sneak preview of that, 4074 04:00:44,496 --> 04:00:48,233 given her prior affiliation with our organization. 4075 04:00:48,767 --> 04:00:51,603 But I think one of the things that's interesting about the Dr. 4076 04:00:51,603 --> 04:00:55,474 Library is that it really does have a long history 4077 04:00:55,474 --> 04:00:59,445 of working at this intersection of informatics and library science. 4078 04:01:00,112 --> 04:01:06,452 The library is very sort of senior in its lifespan 4079 04:01:06,452 --> 04:01:10,656 in that it was established in 1911 and actually is one of the oldest 4080 04:01:10,656 --> 04:01:13,459 and most comprehensive libraries west of the Mississippi. 4081 04:01:14,259 --> 04:01:16,094 For those of you that know me well as an individual 4082 04:01:16,094 --> 04:01:18,931 who grew up on the West Coast and then went to school on the East Coast, 4083 04:01:18,931 --> 04:01:23,335 I suddenly found myself as a midwesterner and therefore can make almost 4084 04:01:23,335 --> 04:01:27,739 any reference in sort of correlation to the location of the Mississippi River now. 4085 04:01:28,373 --> 04:01:30,442 But at the core of this 4086 04:01:30,943 --> 04:01:34,379 long history of bringing informatics and library science together 4087 04:01:34,713 --> 04:01:38,917 was a relationship that began in the early 1990s with the NCBI, 4088 04:01:39,384 --> 04:01:42,554 where the Becker Library was deeply engaged in the development 4089 04:01:42,554 --> 04:01:46,291 and dissemination of a number of critical tools and data resources 4090 04:01:46,291 --> 04:01:49,628 that tackled fundamental problems in the biomolecular sciences. 4091 04:01:50,095 --> 04:01:54,500 And it was actually because of that work at the intersection of Becker and NCBI 4092 04:01:54,867 --> 04:01:57,503 that a core information technology 4093 04:01:57,503 --> 04:02:00,906 and Bioinformatics Support Unit was created in 2000. 4094 04:02:01,440 --> 04:02:05,611 And the goal of creating this new unit was really to provide 4095 04:02:05,644 --> 04:02:09,381 a front door to critical resources that would enable this modern 4096 04:02:09,381 --> 04:02:13,051 knowledge enterprise in a research intensive academic health center . 4097 04:02:13,051 --> 04:02:16,321 And in particular, the group was quite focused on areas that you see enumerated 4098 04:02:16,321 --> 04:02:19,224 here, such as genomics, research, computing and knowledge management. 4099 04:02:19,558 --> 04:02:21,126 Not surprising for an institution 4100 04:02:21,126 --> 04:02:24,696 that also housed a large genome institute and a sizable clinical 4101 04:02:24,930 --> 04:02:28,200 as well as translational and basic science enterprise. 4102 04:02:28,767 --> 04:02:29,801 It was also interesting 4103 04:02:29,801 --> 04:02:32,638 that with the foundation, this group within the Becker Library, 4104 04:02:32,871 --> 04:02:34,139 there was a clear acknowledgment 4105 04:02:34,139 --> 04:02:37,175 of the fundamental interdisciplinary nature of this work, 4106 04:02:37,442 --> 04:02:41,113 in that there was a faculty advisory group that spanned both the preclinical 4107 04:02:41,113 --> 04:02:42,748 and clinical domains in the medical school 4108 04:02:42,748 --> 04:02:45,918 that came together to provide strategic guidance to this new unit. 4109 04:02:46,952 --> 04:02:48,687 And one of the important 4110 04:02:48,687 --> 04:02:50,789 aspects of the unit, when it was created 4111 04:02:50,789 --> 04:02:54,526 in 2000, was that it was meant not only to provide services, 4112 04:02:54,526 --> 04:02:58,130 but also to invest time and energy in workforce development. 4113 04:02:58,564 --> 04:03:02,100 It is an interesting sidebar, actually, that Washington University was also 4114 04:03:02,100 --> 04:03:04,703 one of the very first institutions to receive a training grant 4115 04:03:04,703 --> 04:03:07,539 from the National Library of Medicine when that program began, as well 4116 04:03:07,806 --> 04:03:11,543 under Marc Fritz's leadership at the time at the university. 4117 04:03:11,543 --> 04:03:14,580 And I think that speaks again to this commitment to workforce development 4118 04:03:14,580 --> 04:03:18,317 and the intersectionality of informatics and the library in that space. 4119 04:03:18,917 --> 04:03:22,387 And I won't read the other details here, although they emphasize that like everyone 4120 04:03:22,387 --> 04:03:26,291 in today's session, I had at least one embarrassing picture or magazine cover 4121 04:03:26,525 --> 04:03:29,428 showing people dressed in sort of late 4122 04:03:29,428 --> 04:03:32,331 nineties or early twenties apparel holding 4123 04:03:32,564 --> 04:03:36,468 shockingly large computers that were high tech at the time. 4124 04:03:36,768 --> 04:03:40,272 But nonetheless, there has been this very lengthy 4125 04:03:40,272 --> 04:03:43,108 and intentional approach to building bridges between scientists 4126 04:03:43,342 --> 04:03:46,511 and informatics and technology professionals that has been based 4127 04:03:46,511 --> 04:03:50,482 in the Becker Medical Library since the very beginning of such efforts. 4128 04:03:52,284 --> 04:03:53,852 And now I want to sort of 4129 04:03:53,852 --> 04:03:57,689 engage in just a little bit of time travel and fast forward to today in the role 4130 04:03:57,689 --> 04:03:58,890 that I'm in and sort of how 4131 04:03:58,890 --> 04:04:02,327 that's reflected in the evolving mission of the medical library. 4132 04:04:02,728 --> 04:04:05,063 And this is really the story of how we've created this new unit, 4133 04:04:05,063 --> 04:04:07,733 which we call the Office of Health Information and Data Science, 4134 04:04:07,733 --> 04:04:11,870 which I lead in my role as associate dean here at the School of Medicine. 4135 04:04:12,571 --> 04:04:16,508 And I won't bore you with the details, other than to point out in this timeline 4136 04:04:17,142 --> 04:04:20,612 that the development of the Office of Health Information and Data Science 4137 04:04:20,612 --> 04:04:24,950 has been relatively short in duration as compared to the lengthy history that Dr. 4138 04:04:24,950 --> 04:04:29,321 Library and actually dates back only to 2016 with the formation 4139 04:04:29,321 --> 04:04:33,325 of the Institute for Informatics or ITU at the university. 4140 04:04:33,625 --> 04:04:36,461 And now today we've really created an integrated academic 4141 04:04:36,461 --> 04:04:39,398 home for informatics, research, practice and education. 4142 04:04:39,665 --> 04:04:43,568 We brought that group together with our bio statistics and data science teams, 4143 04:04:43,568 --> 04:04:47,906 as well as research computing and data infrastructure and the Becker Library 4144 04:04:48,140 --> 04:04:51,777 in order to create an integrated unit that really spans the full spectrum. 4145 04:04:51,777 --> 04:04:54,980 Back to that theme, from data to information to knowledge. 4146 04:04:55,414 --> 04:04:57,549 And this has really been a major change 4147 04:04:57,816 --> 04:05:00,986 for our institution for many who know WashU. 4148 04:05:01,620 --> 04:05:06,191 We are, as I often affectionately use the phrase, pathologically decentralized 4149 04:05:06,191 --> 04:05:12,431 in that we enjoy building very robust silos of excellence across our enterprise. 4150 04:05:12,431 --> 04:05:16,635 And we've been very successful in driving critical advances in basic and clinical 4151 04:05:16,635 --> 04:05:19,838 and translational research for decades in that mode of operation. 4152 04:05:20,172 --> 04:05:23,141 Yet there was also a clear recognition by our leadership 4153 04:05:23,141 --> 04:05:25,877 that in these critical areas of data, information and knowledge, 4154 04:05:26,111 --> 04:05:29,114 we really needed something that was purposely built to be horizontal 4155 04:05:29,114 --> 04:05:32,384 and cross-cutting and really support all of our mission areas, 4156 04:05:32,384 --> 04:05:36,221 which is where this office becomes really the hub for that work. 4157 04:05:37,589 --> 04:05:40,092 And you can see here, our mission 4158 04:05:40,092 --> 04:05:43,028 very clearly is to bring those pieces together 4159 04:05:43,228 --> 04:05:47,599 and in fact, create the infrastructure, the workforce and the scientific 4160 04:05:48,066 --> 04:05:52,571 discoveries that really will drive precision medicine and our ability to 4161 04:05:52,571 --> 04:05:57,008 improve the quality of health and health care locally, regionally and nationally. 4162 04:05:57,309 --> 04:06:00,746 And certainly Saint Louis and the surrounding region is a microcosm 4163 04:06:00,746 --> 04:06:03,348 of the challenges that face the national health system here 4164 04:06:03,348 --> 04:06:07,486 in the United States, and thus is an ideal testbed for many of these initiatives. 4165 04:06:09,187 --> 04:06:12,357 This is sort of that the abridged version of what 4166 04:06:12,357 --> 04:06:14,693 this office means in sort of practical reality, 4167 04:06:14,693 --> 04:06:18,029 which is that it houses a informatics unit that spans the spectrum 4168 04:06:18,029 --> 04:06:21,266 from translational bioinformatics to clinical informatics to population 4169 04:06:21,266 --> 04:06:24,870 health, a rapidly growing biostatistics and data science 4170 04:06:25,103 --> 04:06:28,573 research unit, shared educational and workforce programs. 4171 04:06:28,907 --> 04:06:32,377 All of the fundamental structures and functions that make up the Becker 4172 04:06:32,611 --> 04:06:35,413 Medical Library, as well as all of the research, 4173 04:06:35,413 --> 04:06:36,782 computing and data infrastructure 4174 04:06:36,782 --> 04:06:40,619 that sits under what we call our Office of the Chief Research Information Officer. 4175 04:06:40,952 --> 04:06:44,589 And we see this as sort of the template for a next generation academic home 4176 04:06:44,589 --> 04:06:45,724 that again is 4177 04:06:45,791 --> 04:06:49,361 quite horizontal in its nature to achieve all the goals I've talked about. 4178 04:06:49,995 --> 04:06:53,231 And you can see a number of the research highlights here, but I would point out 4179 04:06:53,231 --> 04:06:55,734 that almost every one of these research domains, 4180 04:06:56,034 --> 04:06:59,504 which also involve practice in terms of services and practical tools, 4181 04:06:59,805 --> 04:07:03,642 have been in some way supported or enabled by the activities of the Becker 4182 04:07:03,642 --> 04:07:04,876 Medical Library. 4183 04:07:04,876 --> 04:07:08,046 So there's deep integration across all of our research teams, 4184 04:07:08,046 --> 04:07:10,715 as well as the services and training programs that we offer 4185 04:07:10,749 --> 04:07:13,785 to our medical school curriculum as a function of this tight 4186 04:07:13,785 --> 04:07:16,922 coupling of the Becker Medical Library and all the other units 4187 04:07:16,922 --> 04:07:18,123 that make up the office. 4188 04:07:20,525 --> 04:07:22,160 We'd also 4189 04:07:22,194 --> 04:07:24,596 be remiss if we didn't talk about educational programs, 4190 04:07:24,596 --> 04:07:26,331 because as much as we would like to believe 4191 04:07:26,331 --> 04:07:29,701 that we can recruit every single person to Saint Louis that we need in order 4192 04:07:29,701 --> 04:07:33,605 to tackle these large and complex problems, we simply cannot do that. 4193 04:07:33,905 --> 04:07:36,441 And so we're very committed to growing a workforce 4194 04:07:36,441 --> 04:07:39,211 locally that works at this, again, intersectional space. 4195 04:07:39,544 --> 04:07:42,280 And we do that in traditional ways that many of us are familiar with, 4196 04:07:42,280 --> 04:07:45,851 but also in equal measure in what we believe are quite innovative 4197 04:07:45,851 --> 04:07:49,421 ways, such as K through 12 outreach and engagement and a very, 4198 04:07:49,421 --> 04:07:53,792 very robust regional internship program that brings in trainees 4199 04:07:53,959 --> 04:07:57,629 who get experience in the Becker Library, in the Institute for Informatics 4200 04:07:57,629 --> 04:08:01,032 and in our Research Computing Services Group all at the same time. 4201 04:08:01,399 --> 04:08:04,202 And of course, all of the other components that you see enumerated here. 4202 04:08:04,436 --> 04:08:07,172 But the takeaway is we're very committed to building the pipeline 4203 04:08:07,172 --> 04:08:12,110 of future trainees and exposing them early and often to the fields of library 4204 04:08:12,110 --> 04:08:14,880 and information science, as well as informatics and data science 4205 04:08:15,080 --> 04:08:19,951 and training a workforce that can work in equal measure across all of those areas. 4206 04:08:21,786 --> 04:08:23,989 And that also leads to the services that we offer. 4207 04:08:23,989 --> 04:08:25,891 And I want to draw your attention 4208 04:08:25,891 --> 04:08:28,193 to the role of the medical library in that regard, 4209 04:08:28,193 --> 04:08:31,463 because one of the key roles and perhaps the most important role 4210 04:08:31,463 --> 04:08:34,466 is that our library serves today as a digital hub for our campus. 4211 04:08:34,766 --> 04:08:37,802 It's providing practical training in all of the tools 4212 04:08:37,802 --> 04:08:40,805 that our researchers need only to survive 4213 04:08:40,805 --> 04:08:44,309 but thrive in a modern, data intensive research environment. 4214 04:08:44,609 --> 04:08:45,644 And this is a critical role 4215 04:08:45,644 --> 04:08:49,047 that I think the library is uniquely suited to fill in, that their 4216 04:08:49,714 --> 04:08:54,119 sort of capacity as an impartial and central hub for the campus, 4217 04:08:54,119 --> 04:08:58,490 not connected to any particular disease domain or basic science domain, 4218 04:08:58,490 --> 04:09:01,293 but rather focused on these data, information and knowledge 4219 04:09:01,793 --> 04:09:05,330 related activities, makes the library a trusted partner for delivering 4220 04:09:05,330 --> 04:09:09,200 this type of training, as well as access to these services and capabilities. 4221 04:09:09,534 --> 04:09:11,336 And increasingly, what we've done is positioned 4222 04:09:11,336 --> 04:09:15,440 our library as the front door or onramp to all of our informatics data 4223 04:09:15,607 --> 04:09:16,942 and knowledge management services. 4224 04:09:16,942 --> 04:09:19,010 And I'll say a little bit more about that in a moment. 4225 04:09:20,245 --> 04:09:22,614 And so that really leads me to the final part of my remarks 4226 04:09:23,048 --> 04:09:26,017 this afternoon, which is really how are we innovating sort of 4227 04:09:26,017 --> 04:09:30,021 going from that history of the initial establishment of the Dr. 4228 04:09:30,021 --> 04:09:34,192 Library and its very early leadership in informatics to this new structure 4229 04:09:34,192 --> 04:09:36,528 with the Office of Health Information and Data Science 4230 04:09:36,828 --> 04:09:40,131 to sort of looking forward what comes next for our organization 4231 04:09:40,131 --> 04:09:43,435 with this structure and means of operating? 4232 04:09:44,102 --> 04:09:47,339 So first and foremost, when we talk about the future of the library, 4233 04:09:47,572 --> 04:09:51,443 we talk about it as a hub for what is increasingly, 4234 04:09:51,443 --> 04:09:55,180 if not essentially a digital knowledge enterprise that characterizes 4235 04:09:55,180 --> 04:09:58,750 all parts of our teaching and learning research and clinical missions here 4236 04:09:58,950 --> 04:10:02,487 at Washington University and with our partners at BJC health care. 4237 04:10:03,021 --> 04:10:05,991 And that means in addition to the collections and knowledge resources 4238 04:10:05,991 --> 04:10:09,027 that we provide today, we also are increasingly focused on 4239 04:10:09,027 --> 04:10:11,262 creating what we call centers of excellence. 4240 04:10:11,262 --> 04:10:14,165 Some of them are areas that might be familiar to many of you, 4241 04:10:14,165 --> 04:10:16,101 such as our Center for History in Medicine, 4242 04:10:16,101 --> 04:10:19,004 which, in addition to providing access to all of our archives 4243 04:10:19,004 --> 04:10:22,640 and other historical documents, serves as the official historian 4244 04:10:22,941 --> 04:10:26,011 of the medical school so that we can learn from the prior 4245 04:10:26,011 --> 04:10:29,147 history of the research and educational and service activities 4246 04:10:29,147 --> 04:10:32,517 of the lengthy history of this institution. 4247 04:10:33,084 --> 04:10:36,855 We also recently created a new Center for Health and Science Communication 4248 04:10:36,855 --> 04:10:40,025 with the explicit goal of helping to train our scientists 4249 04:10:40,025 --> 04:10:43,061 and practitioners to better communicate their work with the general public. 4250 04:10:43,328 --> 04:10:46,631 And I think we can all acknowledge that the trust gap between the general public 4251 04:10:46,831 --> 04:10:49,934 and academic medicine has never been greater than it is today. 4252 04:10:50,135 --> 04:10:53,038 And one of our key roles and responsibilities is to help address 4253 04:10:53,038 --> 04:10:56,241 that gap and bring those parties closer together with shared understanding. 4254 04:10:56,841 --> 04:10:59,978 And then, of course, in a way that's similar to some of our other peer 4255 04:10:59,978 --> 04:11:03,448 institutions, we have a deep investment in growing our evidence synthesis review 4256 04:11:03,448 --> 04:11:07,552 service to truly help our investigators navigate increasingly complex 4257 04:11:07,819 --> 04:11:10,989 knowledge resources as they pursue their research endeavors. 4258 04:11:11,723 --> 04:11:13,892 As already alluded to before, we've also established 4259 04:11:13,892 --> 04:11:16,895 the library is our onramp to informatics and data services. 4260 04:11:17,195 --> 04:11:19,998 And this is really about how do people come in and find those services? 4261 04:11:20,031 --> 04:11:23,001 Because by and large, our investigators, our trainees, 4262 04:11:23,001 --> 04:11:26,771 our practitioners don't necessarily know what services or capabilities they need. 4263 04:11:27,038 --> 04:11:28,173 And it's unreasonable 4264 04:11:28,173 --> 04:11:31,643 to expect that they would navigate the myriad of resources that are present. 4265 04:11:31,976 --> 04:11:33,912 What we really want to do is provide, and I think Dr. 4266 04:11:33,912 --> 04:11:36,214 Holmes referred to it earlier, is white glove service 4267 04:11:36,448 --> 04:11:39,451 where human experts help our investigators, our trainees 4268 04:11:39,451 --> 04:11:42,120 and our clinicians to navigate these myriad resources. 4269 04:11:42,654 --> 04:11:46,791 And importantly, again, we provide a number of emergent platforms 4270 04:11:46,791 --> 04:11:50,595 such as our expertize, profiling systems, and then our institutional data 4271 04:11:50,595 --> 04:11:51,329 repository, 4272 04:11:51,329 --> 04:11:55,266 which we've stood up in conjunction with our new data management services 4273 04:11:55,500 --> 04:11:58,803 to help our investigators navigate the new NIH data sharing policies 4274 04:11:58,803 --> 04:12:02,340 and embrace a culture of open science and sharing here at our campus. 4275 04:12:04,209 --> 04:12:04,742 When we think 4276 04:12:04,742 --> 04:12:06,811 about future directions for the library, 4277 04:12:07,912 --> 04:12:11,182 we are now increasingly focusing not just on the medical school, 4278 04:12:11,182 --> 04:12:12,650 but also the campus writ large. 4279 04:12:12,650 --> 04:12:16,387 And we've just launched a program to initiate a ten year 4280 04:12:16,387 --> 04:12:19,124 digital transformation program for the university, 4281 04:12:19,357 --> 04:12:22,260 which brings many of the lessons learned from the formation of the Institute 4282 04:12:22,260 --> 04:12:25,196 for Informatics and the other components to the rest of our campus. 4283 04:12:25,864 --> 04:12:28,766 We're also increasingly looking at how we can expand our digital collections, 4284 04:12:28,766 --> 04:12:33,238 and particularly those that are relevant to just in time, information and knowledge 4285 04:12:33,238 --> 04:12:36,407 needs at the point of care and expanding that to our entire health system. 4286 04:12:36,841 --> 04:12:40,278 So in conjunction with BJC Healthcare, we want to provide these just in time 4287 04:12:40,278 --> 04:12:43,915 knowledge resources to practitioners across all 14 hospitals 4288 04:12:43,915 --> 04:12:47,185 and a 300 mile catchment area, including both rural 4289 04:12:47,852 --> 04:12:50,922 and community hospitals and academic tertiary care centers, really 4290 04:12:50,922 --> 04:12:54,759 sort of democratizing access to these knowledge resources. 4291 04:12:55,293 --> 04:12:57,462 We're also using libraries of hope for navigating. 4292 04:12:57,462 --> 04:12:59,664 How do we provide new modalities of support 4293 04:12:59,664 --> 04:13:02,300 for all of these data, information and knowledge management needs? 4294 04:13:02,700 --> 04:13:04,369 Given the sort of evolving 4295 04:13:04,369 --> 04:13:07,772 nature of our hybrid workforce in this post-pandemic time period, 4296 04:13:08,139 --> 04:13:10,375 and then also providing new tools and resources 4297 04:13:10,375 --> 04:13:13,444 to increase utilization of public datasets and repositories 4298 04:13:13,444 --> 04:13:16,714 that are increasingly central to research and innovation endeavors. 4299 04:13:17,148 --> 04:13:18,249 And then finally, in a little bit 4300 04:13:18,249 --> 04:13:20,852 more sort of pragmatically, we're looking at the space 4301 04:13:20,852 --> 04:13:23,855 that physically makes up the home of the library and ascertaining 4302 04:13:23,855 --> 04:13:26,891 how does it truly become the hub for convening and team science 4303 04:13:26,891 --> 04:13:30,728 activities across our increasingly geographically distributed campus? 4304 04:13:32,530 --> 04:13:34,699 So I'll just end with a slightly embarrassing picture, but 4305 04:13:34,699 --> 04:13:39,537 one that I think is apropos of my comments about my own personal connection to Dr. 4306 04:13:39,537 --> 04:13:40,038 Lindbergh. 4307 04:13:40,038 --> 04:13:40,838 And this is a picture 4308 04:13:40,838 --> 04:13:44,609 actually from a location at the University of Missouri, Columbia. 4309 04:13:44,809 --> 04:13:48,680 Our key partner in both our TSA Cancer Center programs and located 4310 04:13:48,680 --> 04:13:53,151 just a little bit less than 2 hours from where I am today in Saint Louis. 4311 04:13:53,585 --> 04:13:57,055 And the first time I visited shortly after coming here to Saint Louis 4312 04:13:57,055 --> 04:14:00,825 six years ago, I went to Columbia and I had the opportunity 4313 04:14:00,825 --> 04:14:03,061 to see this display, which is in recognition of the 4314 04:14:03,361 --> 04:14:06,698 Donald Abe Lindbergh Award that is given each year 4315 04:14:06,864 --> 04:14:10,268 to excellent faculty in the health informatics program at Mizzou. 4316 04:14:11,002 --> 04:14:14,272 And it was sort of a prescient moment as I looked back upon 4317 04:14:14,272 --> 04:14:16,341 the impact he's had on my career. 4318 04:14:16,341 --> 04:14:18,576 And that impact has been multifold. 4319 04:14:19,210 --> 04:14:21,713 There are certainly a geographic and sort of 4320 04:14:22,880 --> 04:14:26,517 institutional affiliations that tied us together, including the fact that Dr. 4321 04:14:26,517 --> 04:14:29,988 Lindbergh was a Columbia alumni when he received his M.D.. 4322 04:14:29,988 --> 04:14:33,024 And I was fortunate to train in informatics in the Department 4323 04:14:33,024 --> 04:14:36,227 of Biomedical Informatics at the College of Physicians and Surgeons. 4324 04:14:36,761 --> 04:14:38,796 Certainly the connection here in Missouri, 4325 04:14:39,497 --> 04:14:42,967 I would not have had the opportunity to come into the field of informatics, 4326 04:14:42,967 --> 04:14:46,037 if not for the fellowship support that I received. 4327 04:14:46,037 --> 04:14:49,941 And I remember fondly the many convening events of the annual entries, including, 4328 04:14:50,141 --> 04:14:53,344 I think, and perhaps most importantly, many of the social events that Dr. 4329 04:14:53,344 --> 04:14:55,346 Lindbergh helped to organize, 4330 04:14:55,346 --> 04:14:57,915 even though we were all quite intimidated by him at the time. 4331 04:14:58,416 --> 04:15:02,220 And then when I sort of fast forward in my first academic leadership role 4332 04:15:02,220 --> 04:15:04,722 at the Ohio State University, when we were fortunate enough 4333 04:15:04,722 --> 04:15:09,227 to receive a T 15 training award during the final site visit, Dr. 4334 04:15:09,227 --> 04:15:10,161 Lindbergh, as well as Dr. 4335 04:15:10,161 --> 04:15:14,732 Korn, came to Ohio State to visit us and talk about the program they were planning. 4336 04:15:14,732 --> 04:15:19,837 And I always remember because Don had a very dry wit at times, 4337 04:15:20,538 --> 04:15:23,608 we showed him space that we had for our students 4338 04:15:23,608 --> 04:15:25,677 to engage in collaborative and team science. 4339 04:15:25,677 --> 04:15:28,279 And as we showed him the space, he looked at me and he said, 4340 04:15:28,579 --> 04:15:30,748 You just created that space just for this visit. Right? 4341 04:15:30,748 --> 04:15:32,884 And it was because he could smell the fresh paint in the room. 4342 04:15:33,051 --> 04:15:35,787 And that was entirely true. And he left it at that. 4343 04:15:35,787 --> 04:15:38,856 But I think that was apropos of his sense of humor. 4344 04:15:39,223 --> 04:15:42,560 And then I think perhaps most importantly to me, I had four years 4345 04:15:42,794 --> 04:15:45,763 of having the good fortune of serving on what at the time was the work, 4346 04:15:45,797 --> 04:15:49,133 the standing study section of the film. 4347 04:15:49,167 --> 04:15:49,934 Actually, Dr. 4348 04:15:49,934 --> 04:15:51,436 Holmes and I were on that committee together 4349 04:15:51,436 --> 04:15:54,672 for a period of time, and perhaps the best part of those meetings were what 4350 04:15:54,672 --> 04:15:58,976 I refer to as the family dinners with the study section, and Don and Mary, 4351 04:15:58,976 --> 04:16:02,413 where we really got to hear sort of his view of the history of the field. 4352 04:16:02,980 --> 04:16:06,951 And then lastly, I'll just share that most recently, I had the opportunity 4353 04:16:06,951 --> 04:16:09,987 to help lead a strategic planning process for the American College 4354 04:16:09,987 --> 04:16:12,990 of Medical Informatics, which included thinking about the history of that group, 4355 04:16:12,990 --> 04:16:15,993 which we've all heard about earlier today, and how it might evolve 4356 04:16:15,993 --> 04:16:16,994 to meet current needs. 4357 04:16:16,994 --> 04:16:19,197 And this is towards the end of his life. 4358 04:16:19,197 --> 04:16:23,401 And Don was so generous with providing his sort of historical insights 4359 04:16:23,401 --> 04:16:26,571 and knowledge as I navigated what was a very politically tenuous 4360 04:16:27,205 --> 04:16:29,841 process of sort of reshaping the future of me. 4361 04:16:29,841 --> 04:16:34,078 And I was immensely thankful for his willingness to share his time 4362 04:16:34,078 --> 04:16:34,612 and knowledge. 4363 04:16:34,612 --> 04:16:36,614 And I will always remember that very fondly 4364 04:16:36,614 --> 04:16:38,783 when I was doing that very critical work. 4365 04:16:38,783 --> 04:16:40,585 So I'll just say, like many of us in our field, 4366 04:16:40,585 --> 04:16:45,156 Don has been a giant in the field of informatics, hugely impactful 4367 04:16:45,323 --> 04:16:48,926 and has shaped my view of the world, which I hope what I shared with you today 4368 04:16:49,160 --> 04:16:52,630 is manifest in how we're bringing our informatics and library teams together. 4369 04:16:52,997 --> 04:16:57,001 And I'll just conclude by saying I think that this is consistent 4370 04:16:57,001 --> 04:17:00,004 with Don's vision for this intersectionality of informatics 4371 04:17:00,304 --> 04:17:03,274 and library science and medical libraries. 4372 04:17:03,274 --> 04:17:04,542 And I think it's only appropriate that 4373 04:17:04,542 --> 04:17:08,479 that would be happening here in the Show Me State where Don started his career. 4374 04:17:08,479 --> 04:17:10,281 So thank you again for the time. 4375 04:17:10,281 --> 04:17:14,085 And I will turn it over to our moderator and look forward to our 4376 04:17:14,085 --> 04:17:15,286 other panelists comments. 4377 04:17:16,954 --> 04:17:18,656 Thank you, Phillip. 4378 04:17:18,656 --> 04:17:22,960 I have reflected to you on how, in many ways, the whole 4379 04:17:23,461 --> 04:17:27,965 Don Lindbergh's journey in informatics really started in the Show Me site 4380 04:17:27,965 --> 04:17:30,735 at the University of Missouri and the deep connections 4381 04:17:30,735 --> 04:17:33,204 at the University of Washington in St Louis 4382 04:17:33,805 --> 04:17:36,507 and how that has propelled informatics forward. 4383 04:17:37,008 --> 04:17:40,344 Additionally, I think that Don's leadership 4384 04:17:40,344 --> 04:17:46,617 of the National Library of Medicine and how he encouraged the 4385 04:17:47,251 --> 04:17:50,822 organization to fund research in informatics 4386 04:17:50,822 --> 04:17:54,692 and in training programs I think is especially insightful. 4387 04:17:55,259 --> 04:17:57,962 And one of the things that I found especially meaningful 4388 04:17:57,962 --> 04:18:01,265 about what you're talking about is the libraries 4389 04:18:01,466 --> 04:18:04,702 and particularly librarians, because it's librarians who do the work 4390 04:18:06,504 --> 04:18:08,272 , really have the ability 4391 04:18:08,272 --> 04:18:13,978 to serve as this impartial and connected hub, bringing trusted partners together 4392 04:18:13,978 --> 04:18:17,348 across the university as being engaged in team 4393 04:18:17,348 --> 04:18:20,351 science and advance our research. 4394 04:18:20,751 --> 04:18:22,253 So thank you so much for. 4395 04:18:25,590 --> 04:18:27,592 I do have one more thought that I want to share. 4396 04:18:27,592 --> 04:18:32,530 I think that apparently we need to create a compendium of non Lindbergh quotes 4397 04:18:33,397 --> 04:18:36,834 that would inform future generations that might be welcomed by many. 4398 04:18:38,202 --> 04:18:40,571 Our next speaker is peace. 4399 04:18:40,571 --> 04:18:42,940 Awesome, Williamson. 4400 04:18:42,940 --> 04:18:45,843 She has her MLS and a master's degree in Science. 4401 04:18:46,277 --> 04:18:48,913 Peace is the Associate Director of the National Center 4402 04:18:48,913 --> 04:18:52,116 for Data Sciences for the Network of the National Library of Medicine 4403 04:18:52,583 --> 04:18:56,120 at the New York University Health Sciences Library. 4404 04:18:56,787 --> 04:19:00,091 Pieces Expertize includes data sciences, 4405 04:19:00,091 --> 04:19:04,095 scholarly communication and outreach and libraries. 4406 04:19:04,595 --> 04:19:07,231 In recognition of her research piece 4407 04:19:07,231 --> 04:19:12,937 received the 2021 Texas Women's University Hallmark Alumni Award, as 4408 04:19:12,937 --> 04:19:18,209 well as the Medical Library Association's 2020 ident George Eliot Prize. 4409 04:19:18,209 --> 04:19:22,680 For an article she coauthored, the Audie George Eliot Prize 4410 04:19:22,680 --> 04:19:26,984 recognizes the most effective article in furthering medical librarianship. 4411 04:19:27,952 --> 04:19:29,520 As an active educator. 4412 04:19:29,520 --> 04:19:34,458 Peace Teachers, Research Data Services and Libraries at San Jose State 4413 04:19:34,458 --> 04:19:39,163 University and Public Health Informatics at the University of Texas at Arlington. 4414 04:19:39,964 --> 04:19:44,502 Today, peaceful address, expanded expertize and emerging specialties. 4415 04:19:44,802 --> 04:19:47,905 Role of librarians embedded in each stage of research. 4416 04:19:48,039 --> 04:19:48,940 Peace. 4417 04:19:50,975 --> 04:19:53,978 Thank you so much, Teresa. 4418 04:20:00,952 --> 04:20:03,287 I don't know if I need to take control. 4419 04:20:04,221 --> 04:20:05,489 Okay, I have control. 4420 04:20:05,489 --> 04:20:06,791 Wonderful. 4421 04:20:07,191 --> 04:20:07,692 Okay. 4422 04:20:07,692 --> 04:20:12,630 Thank you so much for the invitation and for the opportunity to speak today. 4423 04:20:13,130 --> 04:20:15,800 I'm really excited to be part of this panel. 4424 04:20:16,233 --> 04:20:20,404 I think that it represents numerous perspectives 4425 04:20:20,404 --> 04:20:24,075 and really all of the roles that medical 4426 04:20:24,075 --> 04:20:27,244 libraries can touch and all of the fields. 4427 04:20:27,778 --> 04:20:28,980 Dr. Holmes and Dr. 4428 04:20:28,980 --> 04:20:32,583 Payne spoke from perspectives of Biochemistry and Informatics. 4429 04:20:33,751 --> 04:20:35,486 As someone who did not know Dr. 4430 04:20:35,486 --> 04:20:39,223 Lindbergh personally, I'm here to provide insight into how his vision 4431 04:20:39,223 --> 04:20:43,461 carries on into current and future developments in libraries. 4432 04:20:44,095 --> 04:20:45,963 This computational focus of Dr. 4433 04:20:45,963 --> 04:20:47,098 Lindbergh and now Dr. 4434 04:20:47,098 --> 04:20:52,203 Brennan came in advance of many of the clear examples of its need 4435 04:20:52,203 --> 04:20:56,474 and its impact, as evident during the COVID 19 pandemic and beyond. 4436 04:20:57,441 --> 04:20:58,576 I like to challenge us 4437 04:20:58,576 --> 04:21:02,380 in libraries to continue to investigate and engage in 4438 04:21:02,380 --> 04:21:06,784 metacognitive processes where we evaluate where our field is heading 4439 04:21:07,652 --> 04:21:10,021 with a focus during this presentation 4440 04:21:10,021 --> 04:21:13,224 on data librarianship. 4441 04:21:16,927 --> 04:21:20,197 Dr. Lindbergh created programs that changed fundamentally 4442 04:21:20,197 --> 04:21:23,801 the way that biomedical information is collected, shared and analyzed 4443 04:21:24,402 --> 04:21:27,805 through all of the computational changes he oversaw at the library. 4444 04:21:28,172 --> 04:21:33,177 He still valued primary resources and original documents and the stories 4445 04:21:33,177 --> 04:21:34,311 they told. 4446 04:21:35,413 --> 04:21:39,717 In an introduction, he wrote in Hidden Treasure in 2011, 4447 04:21:39,717 --> 04:21:44,255 he wrote that speedy computer access to information is truly wonderful. 4448 04:21:45,089 --> 04:21:47,792 Yet there are times, especially when we ask 4449 04:21:47,792 --> 04:21:51,896 why or how a discovery or a belief arose when we need to see 4450 04:21:51,896 --> 04:21:55,966 and hold the original intellectual work in context. 4451 04:21:56,400 --> 04:22:00,071 As a data librarian, I often emphasize the importance 4452 04:22:00,071 --> 04:22:05,342 of the domain of expertize in addition to the data literacy 4453 04:22:05,342 --> 04:22:08,879 that's necessary for understanding broad trends. 4454 04:22:09,113 --> 04:22:13,484 You cannot have one without the other, and it is incredibly important 4455 04:22:13,484 --> 04:22:16,554 to have that expertize partnered with the 4456 04:22:18,122 --> 04:22:21,859 interpretations that take place under Dr. 4457 04:22:21,859 --> 04:22:23,294 Lindberg's leadership. 4458 04:22:23,294 --> 04:22:26,597 In a limb, embrace the Internet, enabling the public 4459 04:22:26,597 --> 04:22:29,400 health providers and scientists to gain new 4460 04:22:29,633 --> 04:22:33,871 or improved access to medical literature via PubMed and PubMed. 4461 04:22:33,871 --> 04:22:39,376 Central ClinicalTrials.gov and Consumer Health Information on Medline plus. 4462 04:22:40,311 --> 04:22:42,747 He played an integral role in the establishment 4463 04:22:42,747 --> 04:22:45,716 of the National Center for Biotechnology and Information, 4464 04:22:46,317 --> 04:22:48,719 which we've talked about numerous times today. 4465 04:22:49,320 --> 04:22:53,124 But I'm going to talk about how that leads into the current roles 4466 04:22:53,124 --> 04:22:56,927 of data librarianship as we move forward in discovery. 4467 04:23:01,499 --> 04:23:02,099 My focus 4468 04:23:02,099 --> 04:23:06,003 today is mostly on the topic of open science. It's 4469 04:23:06,003 --> 04:23:09,507 something that I champion and something that I'm incredibly passionate about. 4470 04:23:09,840 --> 04:23:12,810 And I believe that a lot of the developments of Dr. 4471 04:23:12,810 --> 04:23:17,915 Limberg and the in Ilim have led toward the advancement of this aim. 4472 04:23:18,949 --> 04:23:20,017 Open science is the 4473 04:23:20,017 --> 04:23:22,987 natural way, a natural way of this movement. 4474 04:23:23,387 --> 04:23:26,924 And it focuses on transparency and accessibility. 4475 04:23:27,958 --> 04:23:31,529 Research aims, methods, materials and processes should be made 4476 04:23:31,529 --> 04:23:36,233 as openly available as possible, which include open licensing. 4477 04:23:37,067 --> 04:23:39,436 Open as defined by open knowledge. 4478 04:23:39,436 --> 04:23:42,339 And 2005 involves a standard which will 4479 04:23:42,606 --> 04:23:45,109 which allows for reuse and remixing. 4480 04:23:45,442 --> 04:23:49,013 However, in order for open science to occur, it involves 4481 04:23:49,013 --> 04:23:52,983 a combination of infrastructure, policies and guidelines, 4482 04:23:53,484 --> 04:23:58,322 incentives and tools in addition to resources, skills and effort. 4483 04:23:59,423 --> 04:24:03,594 Librarians are natural partners in this endeavor, as librarians 4484 04:24:03,594 --> 04:24:07,031 are leading the open movement alongside many other scholars and activists. 4485 04:24:07,565 --> 04:24:10,968 The open movement seeks to work toward solutions of many of the world's 4486 04:24:10,968 --> 04:24:14,171 most pressing problems in a spirit of transparency, 4487 04:24:14,171 --> 04:24:17,141 collaboration, re-use and free access. 4488 04:24:17,942 --> 04:24:20,878 It encompasses open science, open government, 4489 04:24:21,378 --> 04:24:25,449 open pedagogy, and much more participatory processes. 4490 04:24:25,883 --> 04:24:30,688 Sharing of knowledge and outputs and open source software are among its key tools. 4491 04:24:31,655 --> 04:24:34,625 The specific definition of open as applied to data, 4492 04:24:34,658 --> 04:24:38,395 knowledge and content is set out by the open definition. 4493 04:24:38,929 --> 04:24:43,200 And with these aims, many libraries are actively transforming 4494 04:24:43,267 --> 04:24:46,437 by increasing their capacity for supporting the open movement. 4495 04:24:47,304 --> 04:24:51,141 The librarian is active in the effort toward advancing open computing, 4496 04:24:51,642 --> 04:24:55,646 data driven biomedical research and open science through expertize 4497 04:24:55,646 --> 04:24:58,515 in information organization and information literacy. 4498 04:25:01,452 --> 04:25:03,520 Now some data to back up my claims. 4499 04:25:04,355 --> 04:25:07,725 Open is clearly something that's influential. 4500 04:25:07,725 --> 04:25:09,927 We all know this with the current pandemic. 4501 04:25:10,261 --> 04:25:14,498 But even prior to that, we saw evidence of that where open 4502 04:25:14,832 --> 04:25:18,402 openly published research had increased citations. 4503 04:25:19,169 --> 04:25:21,772 Increase of use not present on 4504 04:25:21,772 --> 04:25:24,808 this slide are also more accurate representation 4505 04:25:24,808 --> 04:25:28,078 and how it's being portrayed in news articles. 4506 04:25:29,046 --> 04:25:31,715 We also see that the field usage 4507 04:25:31,815 --> 04:25:36,120 as evident in the SNAP score is higher for research that is open. 4508 04:25:36,120 --> 04:25:39,790 And this is really kind of more obvious as you think about 4509 04:25:40,658 --> 04:25:45,329 when the entire article is made available and open and people are much more able 4510 04:25:45,329 --> 04:25:48,799 to understand what occurred and be able to replicate it. 4511 04:25:49,667 --> 04:25:54,038 In addition, we call it a movement because we are moving in that direction. 4512 04:25:54,038 --> 04:25:54,605 As of 4513 04:25:55,739 --> 04:25:57,875 2019, 4514 04:25:57,875 --> 04:26:02,146 25% of research being published has been published, open access 4515 04:26:02,146 --> 04:26:05,950 and all of the research that can possibly be study 4516 04:26:05,950 --> 04:26:09,186 using on paywall data. 4517 04:26:09,320 --> 04:26:11,722 So what is open mean and was involved? 4518 04:26:12,189 --> 04:26:13,791 Let's take a look. 4519 04:26:14,858 --> 04:26:18,028 Here is a very simplified 4520 04:26:18,028 --> 04:26:20,364 view of the research data lifecycle, 4521 04:26:21,432 --> 04:26:24,501 and we see how libraries are active partners here. 4522 04:26:25,302 --> 04:26:28,372 As previously mentioned, open science involves an investment 4523 04:26:28,372 --> 04:26:31,809 of resources, support and effort at multiple levels, 4524 04:26:32,276 --> 04:26:35,713 and they exist at each stage of this research data lifecycle. 4525 04:26:36,947 --> 04:26:40,184 In this picture, to simplify data lifecycle, you can see 4526 04:26:40,184 --> 04:26:44,355 planning, acquiring, structuring, analyzing and sharing data. 4527 04:26:45,222 --> 04:26:48,993 Libraries have developed services and built infrastructure at many, 4528 04:26:48,993 --> 04:26:51,462 if not all, stages of this process. 4529 04:26:52,997 --> 04:26:55,332 If we look at what 4530 04:26:55,332 --> 04:26:57,634 this process looked like traditionally, 4531 04:26:58,469 --> 04:27:01,472 it involved a great number of proprietary tools. 4532 04:27:02,239 --> 04:27:05,976 These are often commonly used for open publishing with a shift 4533 04:27:06,143 --> 04:27:08,278 in the end at that sharing stage. 4534 04:27:09,013 --> 04:27:12,149 However, many of these tools come at a significant cost 4535 04:27:12,149 --> 04:27:16,420 that are all cannot afford and work within tools and environments 4536 04:27:16,420 --> 04:27:20,491 such as utilizing proprietary file types and statistical software 4537 04:27:20,491 --> 04:27:23,594 that does not track the actions that are taken 4538 04:27:23,727 --> 04:27:26,497 and can advertently be inaccessible to others 4539 04:27:26,730 --> 04:27:30,067 and make reproducibility more difficult or impossible. 4540 04:27:31,235 --> 04:27:32,536 In 2005, Dr. 4541 04:27:32,536 --> 04:27:36,807 Lundberg and Betsy Humphreys wrote in the future, journals are still 4542 04:27:36,807 --> 04:27:40,110 an important vehicle for disseminating peer reviewed research results. 4543 04:27:40,611 --> 04:27:43,781 But many individual articles have electronic lives of their own. 4544 04:27:44,415 --> 04:27:47,751 Much scientific information is available free over the Internet. 4545 04:27:47,751 --> 04:27:50,387 Thanks in part to earlier efforts to make information 4546 04:27:50,788 --> 04:27:54,491 about clinical trials and government funded research available to the public. 4547 04:27:55,325 --> 04:27:56,326 So many sources. 4548 04:27:56,326 --> 04:28:01,231 Electronic information required paid licenses in this hand. 4549 04:28:01,231 --> 04:28:02,199 After he and Ms.. 4550 04:28:02,199 --> 04:28:06,236 Humphreys began to highlight efforts toward open resources 4551 04:28:06,470 --> 04:28:11,108 and digital libraries to inform resource researchers and the public. 4552 04:28:11,909 --> 04:28:14,178 As researchers shift to open science 4553 04:28:14,178 --> 04:28:18,315 methods, new processes and products are necessary 4554 04:28:18,315 --> 04:28:21,885 for transparency and accessibility at each stage. 4555 04:28:26,657 --> 04:28:29,059 Looking at this simplified model again 4556 04:28:29,359 --> 04:28:33,664 with some some examples are many of open 4557 04:28:33,664 --> 04:28:36,800 tools, software, file types, etc.. 4558 04:28:36,834 --> 04:28:38,135 At each stage 4559 04:28:38,135 --> 04:28:41,638 we can see there's a lot involved in the movement toward open science. 4560 04:28:43,006 --> 04:28:45,642 Unfortunately, the true integration of multimedia 4561 04:28:45,642 --> 04:28:50,681 information is still either not simple or cheap, says Dr. 4562 04:28:50,681 --> 04:28:51,582 Limberg. 4563 04:28:51,582 --> 04:28:54,518 Technology that supports ready online access 4564 04:28:54,518 --> 04:28:58,188 to full text, picture, sound, video, etc. 4565 04:28:58,188 --> 04:29:00,190 continue to evolve quickly. 4566 04:29:00,190 --> 04:29:03,827 And technology companies derive more income from selling services 4567 04:29:04,261 --> 04:29:07,631 than from selling hardware, which makes it less of a priority. 4568 04:29:09,233 --> 04:29:14,138 A library back in 2015, which was what he was looking at 4569 04:29:14,571 --> 04:29:18,575 as far as ten years in the future, continues to be the logical 4570 04:29:18,575 --> 04:29:22,212 entity to manage this complexity on behalf of the institution, 4571 04:29:22,479 --> 04:29:26,450 to make decisions about inevitable and substantial expenditures, 4572 04:29:26,850 --> 04:29:29,720 to adapt information services to new realities, 4573 04:29:30,020 --> 04:29:32,689 and to provide essential user training and support. 4574 04:29:33,624 --> 04:29:35,792 Again. This was something written by Dr. 4575 04:29:35,792 --> 04:29:39,329 Lindbergh in the New England Journal of Medicine in 2005. 4576 04:29:39,630 --> 04:29:43,200 And you can see that that rings extremely true as we 4577 04:29:43,200 --> 04:29:46,970 look at this model and open examples of each stage 4578 04:29:47,304 --> 04:29:51,508 and think about the entire environment of the open movement today. 4579 04:29:55,679 --> 04:29:56,680 As data have become 4580 04:29:56,680 --> 04:29:59,550 easier to collect, analyze and re, analyze, 4581 04:29:59,917 --> 04:30:04,288 store and share, and as processes toward open science become more complex, 4582 04:30:04,688 --> 04:30:08,725 there is a growing demand for data literacy skills, data technology 4583 04:30:08,959 --> 04:30:11,995 and infrastructure and process implementation and research. 4584 04:30:13,030 --> 04:30:15,966 Libraries, particularly research and medical libraries, 4585 04:30:15,966 --> 04:30:19,336 are expanding service services to support these practices, 4586 04:30:19,870 --> 04:30:23,707 particularly services for research, data curation and reuse. 4587 04:30:24,241 --> 04:30:28,579 In this context, I describe data curation as incompetent, encompassing, 4588 04:30:28,879 --> 04:30:32,816 managing data throughout research, and the process of making data fair 4589 04:30:33,116 --> 04:30:38,021 or findable, accessible, interoperable and reusable over the long term. 4590 04:30:38,989 --> 04:30:43,327 Libraries are now building open platforms like repositories and data portals, 4591 04:30:43,760 --> 04:30:47,030 teaching classes on use of open software, and more 4592 04:30:47,798 --> 04:30:51,668 librarians are partnering with larger resource providers to simplify 4593 04:30:51,868 --> 04:30:56,073 and make easier the process for their researchers and using their resources. 4594 04:30:56,540 --> 04:30:58,642 For example, I live in Texas. 4595 04:30:58,642 --> 04:31:00,877 We have the Texas Advanced Computing Center, 4596 04:31:01,144 --> 04:31:05,048 which has storage options, cloud computing and statistical services 4597 04:31:05,048 --> 04:31:08,518 in which research data librarians assist researchers in making use of. 4598 04:31:13,490 --> 04:31:14,157 Research Data 4599 04:31:14,157 --> 04:31:18,528 Services or RTX for short have become a critically important topic 4600 04:31:18,528 --> 04:31:23,100 for academic libraries, medical libraries and research libraries of all kinds. 4601 04:31:23,967 --> 04:31:28,338 With the average our one classified university employing a range between 0 4602 04:31:28,338 --> 04:31:32,709 to 10 librarians with an average of two data librarians per institution 4603 04:31:33,877 --> 04:31:38,048 assessing the data services being offered in RL member libraries. 4604 04:31:38,515 --> 04:31:42,586 Some researchers in 2018 placed them into the categories 4605 04:31:42,586 --> 04:31:46,356 of information, access, support, technical support 4606 04:31:46,356 --> 04:31:49,693 and personalized consultation console consultation. 4607 04:31:49,693 --> 04:31:53,430 Sorry, and these describe the acts of providing the information, 4608 04:31:53,864 --> 04:31:56,533 the technology and in-person assistance 4609 04:31:56,700 --> 04:31:58,702 to be able to work in this new landscape. 4610 04:31:59,670 --> 04:32:03,240 Many libraries have information placed online or in places 4611 04:32:03,240 --> 04:32:06,710 such as the data management planning tool or dump tool for short. 4612 04:32:07,311 --> 04:32:10,480 But they are limited and the consultation category 4613 04:32:10,814 --> 04:32:14,251 due to a number of factors which could include the number of them. 4614 04:32:14,518 --> 04:32:18,355 Again, mentioning that the average have two per institution. 4615 04:32:18,855 --> 04:32:22,993 Working with all of the researchers in one institution is quite an undertaking. 4616 04:32:24,094 --> 04:32:25,962 The the 4617 04:32:25,996 --> 04:32:28,732 financial aspects of the infrastructure and more. 4618 04:32:30,133 --> 04:32:33,170 In addition, the focus has been on the preparation 4619 04:32:33,470 --> 04:32:37,074 and the final curation of data, where fewer librarians provide 4620 04:32:37,074 --> 04:32:40,410 support for data, acquisition, processing and analysis. 4621 04:32:40,510 --> 04:32:43,213 However, that is shifting. 4622 04:32:46,817 --> 04:32:49,086 So I'll talk a little bit about each stage 4623 04:32:49,086 --> 04:32:53,490 and we'll circle back into kind of again looking at the future of libraries. 4624 04:32:54,224 --> 04:32:58,495 So thinking about the planning stage, in addition to data management planning, 4625 04:32:58,762 --> 04:33:02,099 librarians can advise on components of a good protocol 4626 04:33:02,332 --> 04:33:04,534 and assist with pre-registration. 4627 04:33:04,534 --> 04:33:08,605 We also work with colleagues across campuses to develop guidelines 4628 04:33:08,839 --> 04:33:11,341 and make resources and services more clear. 4629 04:33:12,209 --> 04:33:15,946 This includes working with research offices, I.T. 4630 04:33:15,946 --> 04:33:19,216 departments, information security, innovation 4631 04:33:19,216 --> 04:33:21,418 and commercialization offices, and more. 4632 04:33:22,319 --> 04:33:26,223 Together, we work to communicate across these offices to make requirements 4633 04:33:26,223 --> 04:33:30,460 clearer and more consistent to researchers while providing services 4634 04:33:30,460 --> 04:33:31,561 to support their work. 4635 04:33:32,796 --> 04:33:35,766 Librarians are collaborators with specialized skills. 4636 04:33:36,199 --> 04:33:40,604 We are able to help researchers across this lifecycle from reviewing 4637 04:33:40,604 --> 04:33:44,307 data management plans to assisting with data sharing and publishing. 4638 04:33:45,075 --> 04:33:48,845 We do this by helping researchers one on one during consultations 4639 04:33:49,112 --> 04:33:51,848 and by holding workshops where we teach data different 4640 04:33:51,882 --> 04:33:54,684 different data analysis and visualization tools. 4641 04:33:55,585 --> 04:33:59,389 Depending on expertize, librarians can provide guidance on best practices 4642 04:33:59,389 --> 04:34:02,392 for designing data collection tools, particularly surveys 4643 04:34:02,993 --> 04:34:06,163 to have well-structured data at the completion of their collection. 4644 04:34:07,030 --> 04:34:10,901 And as I mentioned, we've provided significant amount of training 4645 04:34:10,901 --> 04:34:15,906 on software programs and other tools for data collection for secondary data. 4646 04:34:15,906 --> 04:34:17,441 Librarians have awareness 4647 04:34:17,441 --> 04:34:21,111 or the ability to find data sources that may be useful for research. 4648 04:34:21,578 --> 04:34:24,448 And we assess researchers in the process of submitting requests 4649 04:34:24,881 --> 04:34:28,919 for applications to data service data sources, including projects. 4650 04:34:29,853 --> 04:34:34,558 And data that you may be familiar with through your local health department. 4651 04:34:35,158 --> 04:34:37,994 Other data sources like the Inmarsat data and so on. 4652 04:34:42,265 --> 04:34:45,202 Some libraries also 4653 04:34:45,202 --> 04:34:48,772 kind of exist within the center of the data lifecycle, 4654 04:34:49,005 --> 04:34:52,909 including working to help researchers and structuring their data 4655 04:34:53,076 --> 04:34:54,644 and analyzing them. 4656 04:34:54,644 --> 04:34:58,748 I mentioned the idea of creating workshops, 4657 04:34:58,748 --> 04:35:03,687 online tutorials and tools and helping people one on one, consultations 4658 04:35:03,987 --> 04:35:09,559 with data structuring, database design, and also working with analog 4659 04:35:09,593 --> 04:35:12,696 analytical software and research methods. 4660 04:35:22,472 --> 04:35:23,974 Two decades ago, Dr. 4661 04:35:23,974 --> 04:35:28,979 Lundberg stated, If I read and memorized two medical journal articles 4662 04:35:28,979 --> 04:35:32,616 every night by the end of the year, I'd be 400 years behind. 4663 04:35:34,050 --> 04:35:35,719 Adam Marcus stated in Dr. 4664 04:35:35,719 --> 04:35:40,457 Lindbergh's obituary in The Lancet, This was a statement from two decades ago. 4665 04:35:40,490 --> 04:35:44,694 So imagine how wide that gap is now that millions of articles 4666 04:35:44,995 --> 04:35:46,329 are published each year. 4667 04:35:46,329 --> 04:35:49,833 And we saw this ramp up even further with the COVID 19 pandemic. 4668 04:35:51,268 --> 04:35:54,137 His career focused on applying the power of computers 4669 04:35:54,137 --> 04:35:57,440 to medical research, discovery and information access. 4670 04:35:58,608 --> 04:36:00,310 As a researcher. 4671 04:36:00,310 --> 04:36:01,912 He led the development of A.I. 4672 04:36:01,912 --> 04:36:08,285 systems, and he wrote that the flood of patient specific data generated 4673 04:36:08,285 --> 04:36:13,356 by large scale prospective normal cohort students presents special problems. 4674 04:36:14,257 --> 04:36:17,761 And I don't want to skip over the problems that are involved 4675 04:36:17,761 --> 04:36:21,097 in a lot of these processes and the amount of commitment 4676 04:36:21,097 --> 04:36:23,833 that it takes to be successful in moving toward this movement. 4677 04:36:26,503 --> 04:36:27,804 Not pictured, are they? 4678 04:36:27,804 --> 04:36:30,740 Numerous in alarm products and data sets? 4679 04:36:31,608 --> 04:36:34,244 I only had so much room in that life 4680 04:36:34,244 --> 04:36:37,414 cycle picture, but a lot of it all. 4681 04:36:37,814 --> 04:36:41,551 Work focuses on metadata such as the Unified Medical Language 4682 04:36:41,551 --> 04:36:46,890 System, Daily Med Committee plus and and and so on. 4683 04:36:47,490 --> 04:36:51,561 Before the UML, databases lacked common terminology, 4684 04:36:51,795 --> 04:36:55,065 and these systems have numerous uses for information sharing, 4685 04:36:55,465 --> 04:36:58,168 compilation of evidence and interoperability. 4686 04:36:59,002 --> 04:37:02,305 This is a key area of leadership coming out of the SPL 4687 04:37:02,672 --> 04:37:05,775 as librarians can and are helping usher researchers 4688 04:37:05,775 --> 04:37:10,246 path standalone data sets toward fair data and interoperability. 4689 04:37:15,418 --> 04:37:17,721 Hopefully the taxes on take small in the slide. 4690 04:37:17,721 --> 04:37:19,389 But I also wanted to point out 4691 04:37:19,389 --> 04:37:22,959 some other areas of support that libraries are offering. 4692 04:37:23,259 --> 04:37:26,596 I think these will only grow and intensify 4693 04:37:26,596 --> 04:37:31,301 with all of the memos and policies that are currently coming out. 4694 04:37:32,002 --> 04:37:36,106 But some of these include helping researchers find where to publish. 4695 04:37:37,140 --> 04:37:41,011 Funding article processing charges for open access 4696 04:37:41,811 --> 04:37:45,615 initiatives with the idea that funding you on the front end 4697 04:37:45,615 --> 04:37:49,686 with a one time charge to make your article permanently public 4698 04:37:50,186 --> 04:37:55,191 where you're saving that library the funds of continuous subscriptions 4699 04:37:55,191 --> 04:37:57,560 in order to maintain access to those articles. 4700 04:37:58,795 --> 04:38:01,831 Assisting with copyright and helping researchers 4701 04:38:01,831 --> 04:38:07,470 navigate their copyright agreements to possibly 4702 04:38:07,771 --> 04:38:10,907 have their articles open as open as possible, 4703 04:38:11,041 --> 04:38:13,209 not just their articles, but also their data sets, 4704 04:38:13,643 --> 04:38:16,413 and then assessing the research impact on the back end. 4705 04:38:18,848 --> 04:38:19,983 I don't want to forget to 4706 04:38:19,983 --> 04:38:23,086 point out that librarians are researchers as well. 4707 04:38:23,820 --> 04:38:27,891 We have a number of domains, specific expertize, 4708 04:38:27,991 --> 04:38:29,426 particularly in medical libraries. 4709 04:38:29,426 --> 04:38:34,497 Many of us have, as Teresa mentioned, I have a kind of public health 4710 04:38:34,497 --> 04:38:37,667 background and others have backgrounds in biology, 4711 04:38:38,601 --> 04:38:41,004 chemistry and so on. 4712 04:38:41,004 --> 04:38:43,139 We also have our initial focus, 4713 04:38:43,139 --> 04:38:46,643 which is around information literacy and information access, 4714 04:38:47,343 --> 04:38:50,346 information organization and now scholarly communication 4715 04:38:50,346 --> 04:38:52,749 as that field grows. 4716 04:38:55,685 --> 04:38:56,619 With all of this. 4717 04:38:56,619 --> 04:39:01,391 I hope this helps you look forward toward where libraries are going, 4718 04:39:01,524 --> 04:39:05,695 opportunities for libraries, and the legacy that Dr. 4719 04:39:05,695 --> 04:39:08,631 Lindbergh has set by focusing on computers 4720 04:39:08,932 --> 04:39:11,234 in medicine and in librarianship. 4721 04:39:12,202 --> 04:39:16,139 You can also see this legacy, carry on with it in a lab and continued 4722 04:39:16,139 --> 04:39:20,243 R&D with Litecoin Common Data Elements 4723 04:39:20,510 --> 04:39:23,713 and Advances in Medical Research, Description and access. 4724 04:39:24,547 --> 04:39:27,083 Again, thank you so much for having me 4725 04:39:27,083 --> 04:39:30,153 as a speaker and I look forward to your question. 4726 04:39:32,922 --> 04:39:33,356 Thank you. 4727 04:39:33,356 --> 04:39:34,624 Peace. That was excellent. 4728 04:39:34,624 --> 04:39:36,793 And I really appreciate that. 4729 04:39:36,793 --> 04:39:41,264 And in listening to what you said and I see some common themes from science, 4730 04:39:41,264 --> 04:39:44,901 data science, team science, collaboration, 4731 04:39:45,335 --> 04:39:48,104 open access through science 4732 04:39:49,038 --> 04:39:51,975 solving problems, how librarians can serve 4733 04:39:51,975 --> 04:39:56,045 as a partner in the research enterprise. 4734 04:39:56,613 --> 04:40:02,318 And from everything I knew about Don Lindberg, this really reflected 4735 04:40:02,318 --> 04:40:05,455 his vision of the future, where librarians are collaborators 4736 04:40:05,455 --> 04:40:07,924 and connectors and the research. 4737 04:40:08,892 --> 04:40:10,794 Ecosystem. 4738 04:40:10,794 --> 04:40:14,464 Before we move on to other questions, I do have a question for piece, 4739 04:40:15,031 --> 04:40:17,567 which is with the new. 4740 04:40:18,601 --> 04:40:20,904 Announcement of the White House 4741 04:40:20,904 --> 04:40:23,306 Office of Science Technology Policy. 4742 04:40:24,741 --> 04:40:29,012 Last week that the embargo is going to be removed 4743 04:40:29,012 --> 04:40:32,448 and that there's going to be a focus on sharing of data. 4744 04:40:32,816 --> 04:40:35,919 How do you foresee librarians working in that space, 4745 04:40:36,586 --> 04:40:39,155 or how will it change the practice of librarianship? 4746 04:40:40,957 --> 04:40:42,859 Yeah, that's a great question. 4747 04:40:42,859 --> 04:40:44,894 Thank you for asking. 4748 04:40:44,894 --> 04:40:47,630 For those who are unfamiliar, 4749 04:40:47,630 --> 04:40:51,067 the White House just released a new memo 4750 04:40:51,067 --> 04:40:55,972 which include included basically four large changes 4751 04:40:55,972 --> 04:40:58,308 to the previous memo 4752 04:40:59,142 --> 04:41:01,578 and that there are no more embargoes. 4753 04:41:02,011 --> 04:41:05,448 So any research that's being published 4754 04:41:05,448 --> 04:41:08,251 from federally funded agencies 4755 04:41:09,219 --> 04:41:13,089 must be made immediately available by deposit in 4756 04:41:14,357 --> 04:41:16,492 acceptable repositories. 4757 04:41:16,492 --> 04:41:19,963 And that includes not only the article itself or the 4758 04:41:20,663 --> 04:41:25,201 the publication itself, but also the underlying data 4759 04:41:25,401 --> 04:41:29,672 as well as the metadata describing kind of the researcher 4760 04:41:29,672 --> 04:41:33,610 and just making some of that research process transparent. 4761 04:41:34,911 --> 04:41:40,283 In addition to that, all federal funding agencies must now adopt these policies 4762 04:41:40,283 --> 04:41:44,721 when the previous memo was only to the largest agencies. 4763 04:41:44,721 --> 04:41:49,993 So that includes agencies like any age, which was not originally included. 4764 04:41:50,693 --> 04:41:54,631 This promotes equity and access to research. 4765 04:41:54,864 --> 04:42:00,670 It increases trust in the research that's being participated in. 4766 04:42:00,904 --> 04:42:01,838 And it makes sense. 4767 04:42:01,838 --> 04:42:05,475 Taxpayers are funding this research 4768 04:42:05,475 --> 04:42:08,511 and that research should be made available for any use. 4769 04:42:09,012 --> 04:42:13,983 We also saw the importance of this, of course, as I mentioned, numerous time 4770 04:42:14,384 --> 04:42:19,155 and public health side I have too is during the COVID 19 pandemic 4771 04:42:19,155 --> 04:42:24,027 where the access to information allowed for the speedy 4772 04:42:24,894 --> 04:42:28,498 creation of things like vaccines and understanding of 4773 04:42:29,499 --> 04:42:31,701 this virus. 4774 04:42:32,902 --> 04:42:36,005 So what is the role of medical libraries in all of this? 4775 04:42:36,039 --> 04:42:37,607 Well, I'll be honest. 4776 04:42:37,607 --> 04:42:41,077 I'm already hearing from medical libraries in terms of what this means, 4777 04:42:41,778 --> 04:42:46,316 not only this new post up memo, but the NIH policy 4778 04:42:46,316 --> 04:42:49,819 that is coming into place in January 4779 04:42:50,586 --> 04:42:53,623 as these policies and memos 4780 04:42:53,990 --> 04:42:57,727 work toward motivating researchers toward openness. 4781 04:42:58,094 --> 04:43:00,730 They are looking to their libraries to support them 4782 04:43:00,730 --> 04:43:03,333 as they engaged in the changes necessary 4783 04:43:04,400 --> 04:43:06,202 to be able to foster that. 4784 04:43:06,202 --> 04:43:09,806 Not only the researchers, but I mentioned that in my presentation, 4785 04:43:10,073 --> 04:43:12,875 also the institution as a whole. 4786 04:43:13,643 --> 04:43:16,145 I worked when I was a data librarian 4787 04:43:16,412 --> 04:43:19,882 with a number of nonacademic units 4788 04:43:20,249 --> 04:43:25,288 to create policies within the institution that aligned with these federal 4789 04:43:26,055 --> 04:43:31,394 federal policies and memos to also create infrastructure that made it easier 4790 04:43:31,594 --> 04:43:35,465 and to look at the software and tools that we have available 4791 04:43:35,665 --> 04:43:39,502 and how can we make them as seamless as possible 4792 04:43:39,669 --> 04:43:43,706 and as focused on reproducibility and openness as possible 4793 04:43:44,440 --> 04:43:48,745 in order to do that, that it can be things like teaching how to make use of 4794 04:43:49,779 --> 04:43:52,582 tools that allow for reproducibility, 4795 04:43:52,582 --> 04:43:54,650 saving an open file type, 4796 04:43:54,650 --> 04:43:59,122 and depositing in these repositories that are being recommended 4797 04:43:59,455 --> 04:44:01,991 by recommended federally. 4798 04:44:02,425 --> 04:44:05,094 So I think there are a lot of opportunities for libraries 4799 04:44:05,094 --> 04:44:07,997 and it's a matter of getting engaged in this process 4800 04:44:08,231 --> 04:44:10,600 and also looking at the leadership coming out of the alnylam. 4801 04:44:11,667 --> 04:44:13,903 Thank you. Peace. That was excellent. 4802 04:44:13,903 --> 04:44:16,072 So we do have a question for the panel. 4803 04:44:16,672 --> 04:44:20,943 Then I would actually ask each of you to answer that, which is what 4804 04:44:20,943 --> 04:44:25,181 other frontiers and opportunities do you see for your institution? 4805 04:44:25,515 --> 04:44:28,251 So we'll go back to the order that we started, 4806 04:44:28,251 --> 04:44:31,421 which is Christy Holmes from Northwestern first. 4807 04:44:33,189 --> 04:44:34,457 Sure. Thank you. 4808 04:44:34,457 --> 04:44:38,027 So for me, I mean, I think your sky's the limit. 4809 04:44:38,061 --> 04:44:42,999 It's been a remarkable day to hear about all of the ways that 4810 04:44:44,801 --> 04:44:47,670 that we see intersections between 4811 04:44:48,771 --> 04:44:50,873 data and informatics 4812 04:44:50,873 --> 04:44:54,610 and research activities and the people that not only 4813 04:44:55,945 --> 04:45:00,183 do this work, but the people who benefit from it as well. 4814 04:45:00,216 --> 04:45:04,720 So the thing that's making, I think me most excited these days 4815 04:45:05,088 --> 04:45:10,893 is the role that libraries can play in equitable access to research. 4816 04:45:11,194 --> 04:45:17,500 So taking advantage of not just technology but social strategies, you know, 4817 04:45:17,533 --> 04:45:22,805 working with people, engaging in railways, partnering with communities, 4818 04:45:23,473 --> 04:45:27,343 community led research activities so that we're really making 4819 04:45:27,343 --> 04:45:31,914 the most of these incredible investments by American taxpayers 4820 04:45:32,648 --> 04:45:35,485 so that it's not of perhaps 4821 04:45:35,751 --> 04:45:38,621 as technologically 4822 04:45:40,423 --> 04:45:42,625 strong of an area. 4823 04:45:42,625 --> 04:45:46,062 I don't see a lot of, you know, huge 4824 04:45:46,062 --> 04:45:49,332 work to build technology or 4825 04:45:50,032 --> 04:45:52,435 data standards necessarily. 4826 04:45:52,435 --> 04:45:56,172 But I do think that it's something that requires intentional action. 4827 04:45:56,472 --> 04:46:00,309 So it's something that everyone agrees is a worthwhile activity, 4828 04:46:00,309 --> 04:46:02,578 but it's really hard to be intentional about it. 4829 04:46:02,612 --> 04:46:06,716 And so that's something I've been thinking a lot about these days, and 4830 04:46:08,184 --> 04:46:11,921 I'm really excited about the work that libraries are playing 4831 04:46:11,954 --> 04:46:16,025 to help to advance this this work and in many different areas. 4832 04:46:16,626 --> 04:46:19,495 Right. Thank you, Christine. Philip. 4833 04:46:19,495 --> 04:46:19,996 Yeah. 4834 04:46:19,996 --> 04:46:24,433 So I, I will give three concrete examples that I think actually are just emblematic 4835 04:46:24,433 --> 04:46:25,935 of some bigger themes. 4836 04:46:25,935 --> 04:46:29,138 So I think you heard all three of us talk about in different ways 4837 04:46:29,138 --> 04:46:33,109 the critical issue of communications and in particular 4838 04:46:33,109 --> 04:46:37,380 how we equip our various constituencies in our academic health centers 4839 04:46:37,380 --> 04:46:42,151 to more effectively communicate with the broader public. 4840 04:46:42,451 --> 04:46:46,522 And I think that's a unique role that the libraries and our institutions 4841 04:46:46,822 --> 04:46:51,794 can fill, certainly at our institution and an area where we really want to lead, 4842 04:46:51,794 --> 04:46:53,663 because we believe that the trust gap 4843 04:46:53,663 --> 04:46:58,100 between our communities and our researchers and practitioners 4844 04:46:58,100 --> 04:47:03,139 is an impediment to achieving sort of critical goals around access , 4845 04:47:03,139 --> 04:47:07,677 affordability, equity and improved overall population level health. 4846 04:47:07,677 --> 04:47:09,111 And it starts with being able to communicate 4847 04:47:09,111 --> 04:47:12,782 and get people to sort of understand and have a sort 4848 04:47:12,782 --> 04:47:16,352 of shared framework for the current state of the art in health and health care. 4849 04:47:17,386 --> 04:47:19,121 So that's one big area. 4850 04:47:19,121 --> 04:47:23,859 I think the second area and I alluded to this is how do we better help 4851 04:47:23,859 --> 04:47:27,463 our investigators specifically in the research arena, navigate 4852 04:47:27,463 --> 04:47:30,533 the myriad of large public data resources that are available? 4853 04:47:30,866 --> 04:47:33,436 And at the risk of sounding like I'm making an editorial comment, 4854 04:47:33,436 --> 04:47:37,740 I'll say that, you know, the natural tendency of funders and researchers 4855 04:47:37,740 --> 04:47:40,743 alike, when given the opportunity, is to create yet another data set. 4856 04:47:41,677 --> 04:47:46,315 And the question is, you know, are we fully leveraging the very expensive 4857 04:47:46,315 --> 04:47:49,885 and very sort of voluminous data sets 4858 04:47:49,885 --> 04:47:53,222 we've already created before we create yet another data set? 4859 04:47:53,656 --> 04:47:55,992 And I think that begins with helping people, people 4860 04:47:56,459 --> 04:47:59,095 to understand and discover what resources are there, 4861 04:47:59,262 --> 04:48:03,065 how we can augment what they may be doing at a laboratory or clinical research 4862 04:48:03,065 --> 04:48:06,402 or population health level, and then bring those pieces together. 4863 04:48:06,402 --> 04:48:08,971 And again, I think it's a unique role that the library can fill. 4864 04:48:09,639 --> 04:48:13,009 And then the third, which is much more aspirational for us, is that, 4865 04:48:13,309 --> 04:48:15,011 you know, we have a very large health system 4866 04:48:15,011 --> 04:48:18,481 and we all know that, you know, health systems are increasingly aggregating 4867 04:48:19,148 --> 04:48:22,318 and creating larger and larger networks of both ambulatory 4868 04:48:22,318 --> 04:48:24,153 and inpatient facilities. 4869 04:48:24,153 --> 04:48:28,057 And we have really just this incredibly diverse 4870 04:48:28,057 --> 04:48:31,160 workforce of individuals at all of our facilities 4871 04:48:31,160 --> 04:48:34,897 that need access to just in time contextual information sources. 4872 04:48:35,398 --> 04:48:39,402 And we believe that those individuals will benefit greatly from the expertize 4873 04:48:39,402 --> 04:48:43,072 and capabilities that a medical library brings to the table in terms of delivering 4874 04:48:43,072 --> 04:48:46,842 the right information and the right time, place and format and of note. 4875 04:48:46,842 --> 04:48:50,613 That's a critical intersection of informatics and library science. 4876 04:48:50,946 --> 04:48:52,448 And so we're really focused right now. 4877 04:48:52,448 --> 04:48:55,685 Like I mentioned earlier, we've got 14 hospitals over a 300 mile 4878 04:48:55,685 --> 04:48:59,055 catchment area and they're not all tertiary care, academic health centers. 4879 04:48:59,055 --> 04:49:03,426 In fact, that is the minority of sort of the beds and employees in our system. 4880 04:49:03,759 --> 04:49:04,527 And so the question is, 4881 04:49:04,527 --> 04:49:06,962 how do we extend the reach of our medical library 4882 04:49:06,962 --> 04:49:09,065 to meet the information needs of those individuals 4883 04:49:09,065 --> 04:49:12,702 where we can see direct impact on not only education and workforce 4884 04:49:12,702 --> 04:49:16,339 development, but patient outcomes and quality and safety and value of care. 4885 04:49:16,339 --> 04:49:20,042 So those are sort of three big themes that we're particularly focused on in terms 4886 04:49:20,042 --> 04:49:23,412 of sort of frontiers and opportunities that we really want to pursue. 4887 04:49:24,580 --> 04:49:25,848 Thank you, Philip. 4888 04:49:25,848 --> 04:49:27,149 So peace. 4889 04:49:27,149 --> 04:49:29,318 The question is to you as well. 4890 04:49:29,318 --> 04:49:33,923 And I don't know whether you want to put on your internal Center 4891 04:49:33,923 --> 04:49:37,493 for National Center for Data Services or one of your other hats. 4892 04:49:37,526 --> 04:49:40,596 So, again, what other frontiers and opportunities 4893 04:49:40,596 --> 04:49:42,798 do you see for your institution? 4894 04:49:42,798 --> 04:49:44,767 Like an institution? 4895 04:49:45,034 --> 04:49:47,303 Yeah, just thinking generically. 4896 04:49:48,104 --> 04:49:52,041 I think just to add to something that Philip said 4897 04:49:52,641 --> 04:49:57,980 about kind of always wanting to create another data set is the idea 4898 04:49:57,980 --> 04:50:02,284 of the massive amount of information that is currently existing. 4899 04:50:02,618 --> 04:50:06,222 And kind of going back to what we know about human subjects research 4900 04:50:06,222 --> 04:50:09,925 and the idea of respect for persons and thinking about 4901 04:50:10,526 --> 04:50:14,196 honoring people's participation in our research, 4902 04:50:14,196 --> 04:50:17,333 whether it's a survey or something a lot more involved 4903 04:50:18,334 --> 04:50:21,737 or even just making use of their our data. 4904 04:50:22,705 --> 04:50:25,374 This is something that we need to remember. 4905 04:50:25,374 --> 04:50:28,711 And I think that also drives 4906 04:50:28,711 --> 04:50:32,381 our aim toward the open movement of rather 4907 04:50:32,381 --> 04:50:37,052 than kind of recreating every time we're making use of what already exists . 4908 04:50:37,052 --> 04:50:39,388 And I think libraries can help drive that. 4909 04:50:39,922 --> 04:50:43,893 In addition, I think that there is so much to develop 4910 04:50:43,893 --> 04:50:49,398 in terms of linked data and interoperability making use of. 4911 04:50:49,432 --> 04:50:51,534 There is some talk about machine readable 4912 04:50:52,935 --> 04:50:55,871 data in the new oh step memo, 4913 04:50:55,871 --> 04:50:59,708 but you know, just thinking about more than kind of. 4914 04:51:00,743 --> 04:51:05,948 Static datasets and how we can build infrastructure for that future. 4915 04:51:06,882 --> 04:51:10,486 I also think that there is a push pull between 4916 04:51:11,187 --> 04:51:16,025 participant and patient privacy and confidentiality of their information 4917 04:51:16,258 --> 04:51:19,562 and scientific advancement and how to respect that, particularly 4918 04:51:19,562 --> 04:51:23,065 as we think about marginalized communities and 4919 04:51:24,066 --> 04:51:26,402 who is involved in the research and who is involved 4920 04:51:26,402 --> 04:51:31,073 and kind of as the researcher and as the patient and participants, 4921 04:51:31,106 --> 04:51:35,344 I think that libraries have a lot to to develop 4922 04:51:35,344 --> 04:51:39,448 and to explore in terms of moving this forward in a 4923 04:51:39,882 --> 04:51:43,552 in a way for discovery, but also in a way that respects persons. 4924 04:51:45,888 --> 04:51:46,689 Great. 4925 04:51:46,722 --> 04:51:50,993 So the other question that's come in from the audience is Dr. 4926 04:51:50,993 --> 04:51:53,996 Payne explained one focus of his institution, among 4927 04:51:54,196 --> 04:51:56,899 others, is to be the history of medicine. 4928 04:51:57,500 --> 04:52:01,003 Can you please describe how this focus fits with and contributes 4929 04:52:01,003 --> 04:52:05,975 to the contemporary mission of Washington University St Louis? 4930 04:52:06,709 --> 04:52:08,344 Yes, sir. It's a great question. 4931 04:52:08,344 --> 04:52:12,047 I would begin by saying I'm a little bit of a history nerd, so 4932 04:52:12,348 --> 04:52:15,951 fundamentally, I'm always excited about our Center for History 4933 04:52:15,951 --> 04:52:20,322 in Medicine and the archives collections and the other activities of that group. 4934 04:52:20,789 --> 04:52:24,193 But I would start by saying, you know, we recently went through a process 4935 04:52:24,193 --> 04:52:26,962 of refreshing our medical school curriculum, 4936 04:52:27,396 --> 04:52:31,400 and we really found that there were three essential themes that weren't reflected 4937 04:52:31,400 --> 04:52:35,337 in our current curriculum that we wanted to embrace with that refresh. 4938 04:52:36,138 --> 04:52:39,542 One was really preparing our providers 4939 04:52:39,842 --> 04:52:42,611 to be more humanistic and more able 4940 04:52:42,611 --> 04:52:45,681 to serve as advocates for the patients and communities that they serve. 4941 04:52:46,148 --> 04:52:49,184 The second was to incorporate public health competencies 4942 04:52:49,184 --> 04:52:52,121 into sort of the core competencies of practitioners. 4943 04:52:52,454 --> 04:52:54,723 And the third, quite, I guess, 4944 04:52:55,791 --> 04:52:56,759 sort of 4945 04:52:57,159 --> 04:53:00,029 constructively for us was to incorporate digital health 4946 04:53:00,029 --> 04:53:03,566 and informatics and data science as sort of another core competency. 4947 04:53:04,199 --> 04:53:06,869 But from our perspective, you know, being able to prepare 4948 04:53:06,902 --> 04:53:10,706 future practitioners that sort of embrace the humanistic side of medicine 4949 04:53:11,040 --> 04:53:13,976 and that are able to advocate for the communities that we serve , begins 4950 04:53:13,976 --> 04:53:15,778 with understanding the history 4951 04:53:15,778 --> 04:53:18,914 of how those individuals and communities had been served in the past, 4952 04:53:18,914 --> 04:53:20,916 and that history is both positive and negative. 4953 04:53:21,283 --> 04:53:23,485 And our Center for History Medicine both provides 4954 04:53:23,485 --> 04:53:27,856 sort of the tangible artifacts and the expertize to help people navigate 4955 04:53:27,856 --> 04:53:31,160 in sort of a given domain so that all of those knowledge resources, 4956 04:53:31,460 --> 04:53:34,730 but also , as I mentioned earlier, serves as the official historian 4957 04:53:34,730 --> 04:53:38,300 of our medical school to speak to sort of the role that we've played. 4958 04:53:38,300 --> 04:53:42,204 Again, you know, both positive and negative, because I think we all have 4959 04:53:42,204 --> 04:53:45,541 sort of, you know, dimensions of the histories of our institutions 4960 04:53:46,208 --> 04:53:47,242 that we look back at. 4961 04:53:47,242 --> 04:53:51,113 And in a current historical context, you know, requires some deeper analysis 4962 04:53:51,113 --> 04:53:52,281 and understanding. 4963 04:53:52,281 --> 04:53:54,650 And so that is a central role of that center. 4964 04:53:54,650 --> 04:53:57,753 And we also want to support both trainees and faculty 4965 04:53:57,753 --> 04:54:00,889 that want to make the history of medicine part of their scholarly endeavors, 4966 04:54:01,423 --> 04:54:04,259 again, reflecting that humanistic angle of the field. 4967 04:54:04,593 --> 04:54:07,596 So when you put it all together, you know, the value of histories 4968 04:54:07,630 --> 04:54:10,466 is the history nerd in me is being able to learn from prior 4969 04:54:11,266 --> 04:54:14,903 sort of positive and negative lessons and then transpose 4970 04:54:14,903 --> 04:54:17,473 and understand that in a current and contemporary context. 4971 04:54:17,473 --> 04:54:20,242 And that's exactly what our center does on a daily basis. 4972 04:54:21,143 --> 04:54:24,713 And it also is a sidebar has the the distinction 4973 04:54:24,713 --> 04:54:27,950 of being very poppy for the fact that there are a couple Nobel medals there 4974 04:54:27,950 --> 04:54:29,952 that on occasion you can go and actually hold. 4975 04:54:29,985 --> 04:54:33,822 So if you are so inclined and you're in Saint Louis, we can arrange that as well. 4976 04:54:34,690 --> 04:54:35,991 That's awesome. 4977 04:54:35,991 --> 04:54:39,795 So peace or Christi, do you have any thoughts on that as well? 4978 04:54:41,597 --> 04:54:42,264 I think, too. 4979 04:54:42,264 --> 04:54:46,235 And so actually we have a number of really important 4980 04:54:46,235 --> 04:54:49,672 partnerships that flow through our special collections. 4981 04:54:49,905 --> 04:54:53,575 It allows us to be able to ask questions and investigate topics 4982 04:54:53,575 --> 04:54:57,112 in a much more nuanced and I think engaging way 4983 04:54:57,112 --> 04:55:01,984 than simply a report or a discussion topic. 4984 04:55:01,984 --> 04:55:05,054 And so one resource. 4985 04:55:05,254 --> 04:55:06,822 The National Library of Medicine 4986 04:55:06,822 --> 04:55:09,825 that I'd like to highlight is the exhibition program, 4987 04:55:10,092 --> 04:55:13,696 and that's been a really tremendous opportunity for us to be able 4988 04:55:13,696 --> 04:55:18,834 to catalyze conversations on our campus across a wide variety of topics. 4989 04:55:19,101 --> 04:55:21,336 And so this exhibition program, 4990 04:55:22,304 --> 04:55:24,807 it's really fantastic. 4991 04:55:24,807 --> 04:55:28,444 There are resources that travel around the country 4992 04:55:28,444 --> 04:55:31,513 that are banners and other kinds of exhibit materials, 4993 04:55:31,747 --> 04:55:36,118 and you're able to set it up in a way in your space, whatever that is, 4994 04:55:36,719 --> 04:55:41,356 that provides a weight for the attendee 4995 04:55:41,356 --> 04:55:45,160 or for our patrons to be able to look at this content in new ways. 4996 04:55:45,461 --> 04:55:48,263 And then we supplement that 4997 04:55:48,263 --> 04:55:51,266 with materials from our special collections 4998 04:55:51,266 --> 04:55:54,369 that may look at that topic from a historical perspective. 4999 04:55:55,037 --> 04:55:57,539 We also then use it as an opportunity 5000 04:55:57,539 --> 04:56:01,910 to catalyze conversations that perhaps 5001 04:56:02,444 --> 04:56:07,082 may be related to the topic in the in the exhibit . 5002 04:56:07,082 --> 04:56:10,986 And so it provides a really I think 5003 04:56:12,154 --> 04:56:14,656 it's a 5004 04:56:15,157 --> 04:56:19,628 setting, an environment to ask difficult questions to 5005 04:56:20,496 --> 04:56:23,932 to perhaps ask ourselves how we're contributing 5006 04:56:23,932 --> 04:56:28,437 to some of these topics or conversations, how are we advancing 5007 04:56:28,437 --> 04:56:33,175 what's happening on our own campus and in our community in meaningful ways? 5008 04:56:33,175 --> 04:56:35,511 And it's been a great catalyst for networking, too. 5009 04:56:35,511 --> 04:56:39,381 We have a number of conversations and partnerships that have started 5010 04:56:39,982 --> 04:56:44,186 as a result of conversations that have started from those activities in the past. 5011 04:56:44,186 --> 04:56:48,524 So we're delighted that this program has started again 5012 04:56:48,524 --> 04:56:52,628 from the National Library of Medicine, and we'll look forward to hopefully 5013 04:56:52,628 --> 04:56:55,430 being able to bring one of those exhibits to Northwestern. 5014 04:56:56,431 --> 04:56:57,266 Thank you for hosting. 5015 04:56:57,266 --> 04:57:00,435 And I can echo what you're saying, because when we bring those exhibits 5016 04:57:00,435 --> 04:57:05,641 and we do programing around that, that allows us to contextualize 5017 04:57:06,074 --> 04:57:10,245 the history of medicine in Richmond, Virginia and across the country 5018 04:57:10,746 --> 04:57:14,149 as a unique learning opportunity for many of our users. 5019 04:57:14,716 --> 04:57:17,152 So with that, I would like to thank the panel 5020 04:57:17,152 --> 04:57:19,154 for sharing their knowledge and experience. 5021 04:57:19,721 --> 04:57:23,325 I very much appreciate your contributions to the session 5022 04:57:23,325 --> 04:57:27,095 this afternoon, and I am going to turn things back over to Jeff. 5023 04:57:30,432 --> 04:57:32,000 Thank you very much, Theresa, 5024 04:57:32,000 --> 04:57:36,505 and to all of our panelists, outstanding presentations and a great Q&A. 5025 04:57:37,039 --> 04:57:41,476 Really appreciate your time and your engagement with us on this wonderful day. 5026 04:57:42,110 --> 04:57:45,280 And we are going to take another break or 15 minutes. 5027 04:57:45,280 --> 04:57:49,084 Our proceedings will pick up around 5 minutes to the hour. 5028 04:57:49,351 --> 04:57:53,522 So please come back and join us for our last two presentations of the day. 5029 04:57:53,722 --> 04:57:55,290 Thank you very much. 5030 04:58:11,673 --> 04:58:16,411 Welcome back to the 2022 Lindbergh King Lecture and Scientific Symposium. 5031 04:58:16,578 --> 04:58:17,813 My name is Jeff Reznick. 5032 04:58:17,813 --> 04:58:19,882 I'm chief of the NLM History Medicine Division. 5033 04:58:19,882 --> 04:58:22,885 And it's been my distinct privilege this afternoon, 5034 04:58:23,218 --> 04:58:25,354 all day to moderate our proceedings. 5035 04:58:26,021 --> 04:58:29,157 For those of you who are just joining, please use the live feedback button 5036 04:58:29,157 --> 04:58:32,261 under your video stream to send questions or comments. 5037 04:58:32,995 --> 04:58:34,563 We're going to continue with our program. 5038 04:58:34,563 --> 04:58:37,866 And in so doing, it's my great pleasure to introduce Betsy 5039 04:58:37,866 --> 04:58:40,969 Humphreys, who is with us, to offer her reflections on Dr. 5040 04:58:40,969 --> 04:58:43,538 Lindbergh's leadership and scientific legacy. 5041 04:58:44,006 --> 04:58:47,276 Betsy, retired as deputy director of the National Library of Medicine 5042 04:58:47,276 --> 04:58:51,480 in 2017 after serving in that position for 12 years. 5043 04:58:52,047 --> 04:58:56,184 Throughout her 44 years at the helm, she took on many responsibilities, 5044 04:58:56,184 --> 04:58:59,988 including serving as acting director, where she was responsible 5045 04:58:59,988 --> 04:59:03,759 for all of the library's activities, ranging from program development 5046 04:59:03,759 --> 04:59:06,028 to evaluation to policy formulation. 5047 04:59:06,795 --> 04:59:10,766 Betsy contributed to the development of the NIH and HHS policies 5048 04:59:10,766 --> 04:59:14,970 on health information technology, public access to research results, 5049 04:59:15,304 --> 04:59:18,173 and clinical trial registration and results reporting. 5050 04:59:19,041 --> 04:59:22,444 Her earliest accomplishments at the NLM included automation 5051 04:59:22,444 --> 04:59:26,682 of internal operations, leadership of intelligence, library operations, 5052 04:59:26,682 --> 04:59:28,951 division, where I work, and direction 5053 04:59:28,951 --> 04:59:32,120 of the Unified Medical Language System, UML Large project. 5054 04:59:32,754 --> 04:59:36,658 And very notably, Betsy recently co-edited a very important book 5055 04:59:36,658 --> 04:59:39,661 entitled Transforming Biomedical Informatics 5056 04:59:39,828 --> 04:59:43,498 and Health Information Access, Donn Lindbergh and the U.S. 5057 04:59:43,532 --> 04:59:47,002 National Library of Medicine, published this year by iOS Press. 5058 04:59:47,402 --> 04:59:48,971 Welcome back to the great to see you. 5059 04:59:48,971 --> 04:59:50,839 And I'm going to turn things over to you. Thank you. 5060 04:59:58,447 --> 05:00:00,349 Oh. Okay. 5061 05:00:02,317 --> 05:00:04,019 Thank you, Jeff. 5062 05:00:04,019 --> 05:00:07,322 This has been a great symposium, a really interesting day, of course. 5063 05:00:07,522 --> 05:00:09,624 I love hearing about 5064 05:00:10,826 --> 05:00:16,131 the wonderful things that people have done with data and services. 5065 05:00:16,431 --> 05:00:21,937 I enjoyed seeing people who were helped early in their career 5066 05:00:21,937 --> 05:00:24,806 by training opportunities that NLM provided. 5067 05:00:25,340 --> 05:00:29,811 And so it's a great treat for me to listen 5068 05:00:29,811 --> 05:00:33,181 to people, many of whom are my long term friends and colleagues. 5069 05:00:33,181 --> 05:00:35,350 So I've enjoyed it a great deal. 5070 05:00:35,350 --> 05:00:39,788 I think the Dawn would have approved of a program that began 5071 05:00:39,788 --> 05:00:45,027 with a focus on patients and included so many stellar people who were benefit 5072 05:00:45,227 --> 05:00:49,898 have benefited from MLM support services and training programs. 5073 05:00:50,565 --> 05:00:54,703 It would also have resonated to the recent comments 5074 05:00:54,703 --> 05:00:58,507 about needless creation of new datasets, respecting research 5075 05:00:58,507 --> 05:01:02,210 participants contributions by enabling re-use of their data 5076 05:01:02,511 --> 05:01:06,481 and the value of history and and of anyone 5077 05:01:06,581 --> 05:01:11,019 traveling exhibition program, which is really part of his legacy. 5078 05:01:11,420 --> 05:01:13,422 He was a tremendous. 5079 05:01:15,924 --> 05:01:16,324 He was a 5080 05:01:16,324 --> 05:01:20,529 tremendous contributor to an Olympic history of medicine programs 5081 05:01:20,529 --> 05:01:25,400 along multiple dimensions, including really 5082 05:01:25,600 --> 05:01:31,640 integrating the onsite exhibition program and really pushing traveling exhibitions. 5083 05:01:31,640 --> 05:01:35,477 So he'd be glad to hear that people are still using them 5084 05:01:35,477 --> 05:01:36,845 and enjoying them. 5085 05:01:38,980 --> 05:01:41,616 Having listened to everyone's comments 5086 05:01:41,850 --> 05:01:45,787 about Dawn's outstanding qualities as a leader and a person, 5087 05:01:46,421 --> 05:01:50,192 you know that I was beyond fortunate to have worked directly with him 5088 05:01:50,192 --> 05:01:53,662 for all of his 30 plus years at the National Library of Medicine, 5089 05:01:54,196 --> 05:01:57,099 and to have had the advantage of him 5090 05:01:57,432 --> 05:02:02,637 as a mentor, a great boss and a good friend. 5091 05:02:03,004 --> 05:02:05,240 And because of the latter, also 5092 05:02:06,308 --> 05:02:08,710 because of all these roles, really also 5093 05:02:09,377 --> 05:02:12,781 becoming a great friend of Mary Lindbergh 5094 05:02:12,781 --> 05:02:15,851 and knowing his family. 5095 05:02:15,851 --> 05:02:19,254 I think that it's obvious 5096 05:02:19,788 --> 05:02:23,358 that Don was a great boss. 5097 05:02:23,692 --> 05:02:25,627 He gave 5098 05:02:26,595 --> 05:02:28,663 people who worked for him, 5099 05:02:28,663 --> 05:02:32,000 myself and others, challenging opportunities. 5100 05:02:33,168 --> 05:02:35,170 Resources. 5101 05:02:35,170 --> 05:02:37,706 Lots of running room. 5102 05:02:37,739 --> 05:02:39,040 Good advice. 5103 05:02:39,040 --> 05:02:42,077 Back up when things get sticky and 5104 05:02:42,444 --> 05:02:45,647 and plenty of limelight. 5105 05:02:45,814 --> 05:02:48,250 Don started many things. 5106 05:02:48,250 --> 05:02:51,186 And if you came along later, 5107 05:02:51,186 --> 05:02:53,221 five years later, ten years later, 15 5108 05:02:53,221 --> 05:02:56,758 years later, you might have said, well, what did he have to do with this? 5109 05:02:56,758 --> 05:02:59,161 I, I see. 5110 05:02:59,161 --> 05:03:02,531 You know, Alexis, Betsy, I see David Lippman or whomever. 5111 05:03:03,031 --> 05:03:05,934 And it's because that he got things started. 5112 05:03:06,101 --> 05:03:10,438 He delegated and he gave a lot of freedom. 5113 05:03:10,639 --> 05:03:15,177 And he didn't need to be the front person for the things that he turned over. 5114 05:03:16,244 --> 05:03:19,314 He was very interesting in what he spent. 5115 05:03:19,314 --> 05:03:21,683 His personal time are very 5116 05:03:23,485 --> 05:03:24,486 judicious. 5117 05:03:24,486 --> 05:03:28,156 He had a particular. 5118 05:03:28,156 --> 05:03:29,357 View of looking 5119 05:03:29,357 --> 05:03:32,727 at each activity and seeing whether 5120 05:03:33,328 --> 05:03:38,533 the direct participation of the director of the National Library of Medicine 5121 05:03:38,934 --> 05:03:41,469 could make a difference. 5122 05:03:42,304 --> 05:03:45,840 And in a lot of areas, that involved 5123 05:03:46,508 --> 05:03:49,678 making underserved populations 5124 05:03:50,078 --> 05:03:52,547 realize that no one was serious 5125 05:03:52,747 --> 05:03:57,452 about working with them and helping them, or encouraging 5126 05:03:58,553 --> 05:04:01,856 leading lights in the fields who were headed to retirement 5127 05:04:01,856 --> 05:04:04,859 to deposit papers where they would be taken care of. 5128 05:04:05,527 --> 05:04:08,163 And in coming up 5129 05:04:08,163 --> 05:04:14,002 with great ideas about how technology could be used in a particular program, 5130 05:04:14,002 --> 05:04:17,172 he would be passing off great ideas and focusing on some of them. 5131 05:04:17,572 --> 05:04:20,275 So that was another aspect 5132 05:04:20,275 --> 05:04:23,144 of his great leadership. 5133 05:04:23,912 --> 05:04:25,513 Like. Dr.. 5134 05:04:25,513 --> 05:04:29,117 Carney this morning, I'm going to start by reminding you 5135 05:04:30,619 --> 05:04:33,221 about 1984. 5136 05:04:33,221 --> 05:04:35,290 In that year, 5137 05:04:35,290 --> 05:04:40,262 train searchers, primarily librarians, conducted less than 3 million 5138 05:04:40,262 --> 05:04:43,798 searches of an album database and paid their fair share 5139 05:04:44,232 --> 05:04:48,236 of the commercial telecommunications costs to reach into one's computer system. 5140 05:04:49,437 --> 05:04:52,140 They searched Medline and other bibliographic 5141 05:04:54,242 --> 05:04:55,610 the source chemical 5142 05:04:55,610 --> 05:04:57,979 toxicological and cancer databases. 5143 05:04:58,647 --> 05:05:04,019 The Libraries Network managed by NLM, the library network managed by NLM 5144 05:05:04,152 --> 05:05:08,890 probably filled about nearly 2 million requests for full text journal articles. 5145 05:05:09,190 --> 05:05:11,192 Although it would be a few years before Dr. 5146 05:05:11,192 --> 05:05:13,295 Klein could actually count them. 5147 05:05:13,295 --> 05:05:16,531 In 1984, all the index citations 5148 05:05:16,531 --> 05:05:20,135 and abstracts were key de novo for the Medline database. 5149 05:05:20,902 --> 05:05:24,272 Some of the data in the factual databases were received on magnetic 5150 05:05:24,306 --> 05:05:28,710 magnetic tape from other federal agencies and organizations, 5151 05:05:29,577 --> 05:05:31,846 including the Chem Abstracts Service actually, 5152 05:05:32,414 --> 05:05:36,017 and NLM licensed Medline to other US online 5153 05:05:36,251 --> 05:05:39,554 database providers and had formal agreements with the Pan American Health 5154 05:05:39,554 --> 05:05:43,391 Organization and the governments of 13 countries to facilitate, facilitate 5155 05:05:44,492 --> 05:05:46,995 access to Medline outside the US. 5156 05:05:48,129 --> 05:05:50,231 By 1984. 5157 05:05:50,231 --> 05:05:54,202 Standards like this with very heavy use. 5158 05:05:59,607 --> 05:06:03,778 Now imagine that you are very familiar 5159 05:06:03,778 --> 05:06:05,780 with that picture, Beetle, and you know all about it. 5160 05:06:06,815 --> 05:06:09,984 But just before dawn, Lindbergh arrives as director, 5161 05:06:09,984 --> 05:06:14,489 you are kidnaped by aliens and taken to another galaxy. 5162 05:06:15,023 --> 05:06:19,327 31 years later, they decide to punish you by returning you to Earth. 5163 05:06:20,362 --> 05:06:23,064 Knowing the NLM of 1984 5164 05:06:23,231 --> 05:06:26,634 and being apprized of the general tremendous expansion 5165 05:06:26,634 --> 05:06:29,838 in world worldwide, access to advanced computing devices and the Internet. 5166 05:06:30,872 --> 05:06:35,610 What would would strike you as most of the most surprising 5167 05:06:35,610 --> 05:06:39,047 aspects of intelligence services in 2015? 5168 05:06:40,081 --> 05:06:44,953 I think it would be what was entirely new and had no precursor. 5169 05:06:45,186 --> 05:06:47,655 In 1984, 5170 05:06:47,655 --> 05:06:50,492 my comments are going to center on 5171 05:06:50,492 --> 05:06:54,529 how expansion of intelligence scope from 1984 5172 05:06:54,529 --> 05:06:59,401 to 2015 occurred and the role of Don Lindbergh in making it happen. 5173 05:07:01,603 --> 05:07:02,704 Excuse me, Betsy. 5174 05:07:02,704 --> 05:07:05,473 Yeah. Hi. Pardon me. It's Jeff. 5175 05:07:05,974 --> 05:07:08,309 We're not seeing your slides advance. 5176 05:07:08,309 --> 05:07:11,212 And you do have control. Yes, but that's. 5177 05:07:11,212 --> 05:07:15,483 That's that's because it's not ready to be advanced yet. 5178 05:07:16,084 --> 05:07:18,019 Fair enough. All right. 5179 05:07:18,019 --> 05:07:18,553 Sorry. We just. 5180 05:07:18,553 --> 05:07:23,591 I failed 1 to 1 in presentation by having so much to say 5181 05:07:23,591 --> 05:07:26,861 about before I advance my slides, at any rate. 5182 05:07:27,495 --> 05:07:28,029 Thank you. 5183 05:07:28,363 --> 05:07:31,065 At the time Don retired in 2015, 5184 05:07:31,599 --> 05:07:36,304 I first encountered Stuart Kaufman's ideas about the adjacent possible 5185 05:07:36,571 --> 05:07:39,207 and their application to institutional innovation. 5186 05:07:40,041 --> 05:07:43,478 Kaufman theorized an additional contributor to evolution, 5187 05:07:44,279 --> 05:07:46,581 quote, It may be the case 5188 05:07:46,581 --> 05:07:49,050 that biospheres on average 5189 05:07:49,651 --> 05:07:52,420 keep expanding into the adjacent possible. 5190 05:07:53,021 --> 05:07:57,592 By doing so, they increase the diversity of what can happen next. 5191 05:07:58,526 --> 05:08:03,465 This is a good metaphor for expansion of Alan's programs, services and influence. 5192 05:08:03,798 --> 05:08:07,368 If you have a broad view of what's adjacent 5193 05:08:07,368 --> 05:08:11,506 and what's possible, as Don Wennberg clearly did. 5194 05:08:18,079 --> 05:08:20,782 Well, now I am trying to advance them. 5195 05:08:24,285 --> 05:08:25,253 There we go. 5196 05:08:26,421 --> 05:08:30,391 So I want to. 5197 05:08:35,163 --> 05:08:37,065 Talk about 5198 05:08:37,966 --> 05:08:42,570 why Don Lindberg came out and 5199 05:08:44,806 --> 05:08:48,610 he came with a purpose. 5200 05:08:49,844 --> 05:08:52,947 He in turn, he he looked 5201 05:08:53,581 --> 05:08:56,551 at the opportunity of an alliance directorship. 5202 05:08:57,652 --> 05:09:01,823 And realized that NLM was in a position 5203 05:09:02,624 --> 05:09:07,128 to really accelerate the applications of advanced 5204 05:09:07,128 --> 05:09:09,497 computing and communications to patient care 5205 05:09:10,298 --> 05:09:12,567 and biomedical research. 5206 05:09:12,567 --> 05:09:16,070 And he thought that he was a person 5207 05:09:16,838 --> 05:09:19,807 who could really make this happen. 5208 05:09:21,276 --> 05:09:25,113 He was attracted by the existing 5209 05:09:25,346 --> 05:09:27,348 and Elim Foundation 5210 05:09:28,283 --> 05:09:30,752 that he could build upon. 5211 05:09:30,985 --> 05:09:33,521 The mission he loved 5212 05:09:33,521 --> 05:09:37,125 and frequently quoted is. And. 5213 05:09:38,560 --> 05:09:43,464 He was aware and because of his previous experience 5214 05:09:43,464 --> 05:09:46,467 at NLM, which involved 5215 05:09:47,869 --> 05:09:50,672 serving on the board of scientific counselors for the Lister 5216 05:09:50,672 --> 05:09:54,976 Hill Center and also serving on the block, which we've heard 5217 05:09:56,411 --> 05:09:57,412 discussed by previous 5218 05:09:57,412 --> 05:09:59,414 speakers, the grant review committee. 5219 05:10:00,782 --> 05:10:02,984 He knew that 5220 05:10:02,984 --> 05:10:07,121 NLM had a really multidisciplinary staff 5221 05:10:07,755 --> 05:10:09,023 with. 5222 05:10:10,592 --> 05:10:15,930 And multidisciplinary programs that covered the gamut 5223 05:10:16,364 --> 05:10:21,803 the services, the educational program, research and grants. 5224 05:10:22,036 --> 05:10:24,205 So this was a broad way. 5225 05:10:24,205 --> 05:10:28,276 Many different ways he could influence what he wanted to have happen here, 5226 05:10:28,943 --> 05:10:32,246 which is the application of computers to health 5227 05:10:32,280 --> 05:10:36,117 care and biomedicine . 5228 05:10:36,117 --> 05:10:41,422 He was proud of the services that ILM already had. 5229 05:10:41,889 --> 05:10:43,224 They were excellent. 5230 05:10:43,224 --> 05:10:48,196 They were regularly updated, and for 1984, they were very 5231 05:10:49,230 --> 05:10:51,099 frequently used. 5232 05:10:52,033 --> 05:10:56,537 And he was very enthusiastic 5233 05:10:56,904 --> 05:11:00,174 about the NLM network. 5234 05:11:01,242 --> 05:11:04,445 Because of his experience. 5235 05:11:05,580 --> 05:11:07,715 As someone in institutions 5236 05:11:07,715 --> 05:11:10,251 to work members of the network. 5237 05:11:11,052 --> 05:11:13,621 He was very admiring of the 5238 05:11:15,623 --> 05:11:17,892 capabilities of medical librarians. 5239 05:11:18,826 --> 05:11:23,131 One can sort of understand why one of the medical librarians 5240 05:11:23,131 --> 05:11:26,534 that he was very familiar with was Estelle BROADMAN, 5241 05:11:26,868 --> 05:11:33,574 who was director at WashU and a real pioneer in library automation. 5242 05:11:35,643 --> 05:11:40,214 He. I first spent 5243 05:11:40,214 --> 05:11:43,251 time with him when it came by giving him a tour. 5244 05:11:44,719 --> 05:11:48,990 Somebody asked him if he would like to see 5245 05:11:49,657 --> 05:11:51,959 the current state 5246 05:11:52,026 --> 05:11:56,998 of automated systems that were used to build and alarms databases, 5247 05:11:57,398 --> 05:12:01,169 and they were among the systems that we were in the midst 5248 05:12:01,169 --> 05:12:04,605 when he arrived of redeveloping and trying to improve. 5249 05:12:05,139 --> 05:12:07,341 And he responded. 5250 05:12:07,341 --> 05:12:09,310 Nothing would please me more. 5251 05:12:09,310 --> 05:12:12,346 And I was given the role of giving him the tour. 5252 05:12:13,414 --> 05:12:17,552 I immediately discovered some things that 5253 05:12:19,087 --> 05:12:21,089 you all know, too. If you knew Don. 5254 05:12:21,089 --> 05:12:23,424 He was interested in everything. 5255 05:12:23,424 --> 05:12:25,927 He was fascinated 5256 05:12:25,927 --> 05:12:28,262 at looking at the online indexing system. 5257 05:12:29,330 --> 05:12:31,599 Of which he was very complimentary 5258 05:12:31,599 --> 05:12:33,267 and he asked 5259 05:12:34,168 --> 05:12:37,205 questions that I thought that I realized later 5260 05:12:37,405 --> 05:12:42,143 were questions to desire to find out whether the users of the system 5261 05:12:42,143 --> 05:12:45,980 had participated in designing it and whether it had been developed 5262 05:12:45,980 --> 05:12:47,648 in an innovative way. 5263 05:12:47,648 --> 05:12:50,918 Because as far as he was concerned, that was the only way to develop 5264 05:12:51,486 --> 05:12:54,822 a good and useful system. 5265 05:12:55,823 --> 05:12:56,557 ED of 5266 05:12:56,557 --> 05:12:59,961 when the users and then make the improvements based on real use. 5267 05:12:59,961 --> 05:13:03,765 One of his famous quotes is systems that get used to get better. 5268 05:13:04,832 --> 05:13:07,769 So he was very interested in that, but he was also interested 5269 05:13:07,769 --> 05:13:10,972 in the fact that the Cataloger who was showing him the catalog system 5270 05:13:11,873 --> 05:13:14,942 was working part time at home. 5271 05:13:15,643 --> 05:13:20,915 This was in 1984 and NLM was the first was doing an experiment. 5272 05:13:20,915 --> 05:13:25,119 We were the New Age experiment about flexi placed, you know, working at home 5273 05:13:25,119 --> 05:13:26,654 some days or whatever. 5274 05:13:26,654 --> 05:13:29,657 So he was fascinated by that and he was perfectly delighted 5275 05:13:29,657 --> 05:13:32,660 that NLM had been in the forefront of that 5276 05:13:32,660 --> 05:13:35,930 as we were actually in the forefront of a lot of things. 5277 05:13:36,397 --> 05:13:41,068 So I learned about a lot about him on that trip, on that tour, 5278 05:13:41,269 --> 05:13:45,406 and he immediately asked me as he asked everyone 5279 05:13:45,640 --> 05:13:49,076 when he was thinking about something and he met somebody new and he wanted 5280 05:13:49,076 --> 05:13:52,046 some, you know, he just would ask, well, what do you think about this idea? 5281 05:13:52,180 --> 05:13:55,283 So he asked me, what did I think about the UI M.S., 5282 05:13:56,083 --> 05:14:00,121 his idea, which was very sort of inchoate at the time. 5283 05:14:02,023 --> 05:14:03,691 But I said, well, we 5284 05:14:03,691 --> 05:14:07,595 have a little minor project that sort of is in line with that. 5285 05:14:07,595 --> 05:14:08,763 And you said, Oh, what was that? 5286 05:14:08,763 --> 05:14:11,199 And I said, Well, we have a project to map 5287 05:14:12,400 --> 05:14:15,570 the medical parts of the Library of Congress 5288 05:14:15,570 --> 05:14:19,173 subject headings to the medical subject headings, which is the 5289 05:14:19,340 --> 05:14:23,511 we used it in a room and he immediately said, This is music to my ears. 5290 05:14:24,045 --> 05:14:27,949 It was not long after that that I was on the M.S. 5291 05:14:27,949 --> 05:14:30,384 team, but. 5292 05:14:33,354 --> 05:14:35,790 He arrived with visionary ideas. 5293 05:14:40,795 --> 05:14:43,731 Moving ahead on them. 5294 05:14:46,734 --> 05:14:47,401 Was going 5295 05:14:47,401 --> 05:14:51,372 to obviously require a substantial increase in an arms budget. 5296 05:14:51,772 --> 05:14:54,542 And the list of his initial priorities 5297 05:14:54,542 --> 05:14:57,311 he brought really reflected this. 5298 05:14:57,545 --> 05:15:01,215 You see them here along with cryptic notes on early progress, 5299 05:15:01,215 --> 05:15:04,585 which went ahead pretty quickly, as you can see. The. 5300 05:15:05,820 --> 05:15:15,296 The health community, 5301 05:15:15,830 --> 05:15:19,300 the health care community for as far as he was concerned, the general public 5302 05:15:19,500 --> 05:15:20,268 and the Congress 5303 05:15:20,268 --> 05:15:23,471 needed to become more aware of and eliminates programs and services. 5304 05:15:23,971 --> 05:15:28,242 The Board of Regents was all on this page already, so they really supported this. 5305 05:15:28,509 --> 05:15:33,314 And in a very fortunate coincidence, an alum was to celebrate 5306 05:15:33,314 --> 05:15:36,484 its 150th anniversary in 1986. 5307 05:15:37,418 --> 05:15:41,956 Dorn saw this as ample justification for special events and expanded publicity 5308 05:15:41,956 --> 05:15:45,493 much more than an Olympics in planning, I should say, before he arrived, 5309 05:15:45,893 --> 05:15:49,864 and much of it was sponsored 5310 05:15:49,964 --> 05:15:54,869 by the newly established friends of an alum, which he was 5311 05:15:55,903 --> 05:15:59,106 no enthusiastic about that. 5312 05:15:59,106 --> 05:16:03,144 That new organization, which also I think 5313 05:16:03,144 --> 05:16:06,280 was created in 1986. 5314 05:16:06,280 --> 05:16:10,084 Now, to make an important difference in justifying increased resources, 5315 05:16:10,718 --> 05:16:13,554 the library needed a long range plan with compelling goals. 5316 05:16:13,721 --> 05:16:15,623 You've heard a lot about it and you've seen it. 5317 05:16:17,325 --> 05:16:18,759 The board was in complete agreement 5318 05:16:18,759 --> 05:16:22,096 with this priority of Don's as well. And. 5319 05:16:24,732 --> 05:16:29,704 Dawn was absolutely clear that the plan should reflect the ideas 5320 05:16:29,704 --> 05:16:32,540 of a very broad, multidisciplinary, 5321 05:16:32,807 --> 05:16:36,811 narrow range of NLM. 5322 05:16:38,279 --> 05:16:40,715 Current and potential users, partners 5323 05:16:40,715 --> 05:16:42,450 and stakeholders. 5324 05:16:44,585 --> 05:16:45,553 As it happened, 5325 05:16:45,553 --> 05:16:49,824 about 200 people participated in the five panels that contributed 5326 05:16:49,824 --> 05:16:53,794 to the development of the long range plan for 1986 to 2006. 5327 05:16:54,261 --> 05:16:56,530 A number of them 5328 05:16:56,864 --> 05:17:01,202 were from many different disciplines were part of Dawn's 5329 05:17:01,202 --> 05:17:05,239 existing personal network to refer back to remarks in the last panel. 5330 05:17:06,273 --> 05:17:08,509 Donald West King was one of these. 5331 05:17:10,011 --> 05:17:11,712 Like Donald King, many 5332 05:17:11,712 --> 05:17:15,483 participants became strong advocates and allies 5333 05:17:15,483 --> 05:17:18,119 for involvement for the plan and ran around, 5334 05:17:19,920 --> 05:17:21,956 as you heard, heard before, 5335 05:17:21,956 --> 05:17:24,025 seeking and listening 5336 05:17:24,759 --> 05:17:28,262 to ideas and opinions from a wide spectrum of sources 5337 05:17:28,529 --> 05:17:33,234 and enlisting them as allies was a hallmark of Don's leadership. 5338 05:17:34,168 --> 05:17:37,071 To quote him, No one has a lock on good ideas. 5339 05:17:37,304 --> 05:17:39,040 They come from everywhere. 5340 05:17:39,040 --> 05:17:42,810 The great idea to establish and CPI it. 5341 05:17:42,810 --> 05:17:47,748 An alarm arose in the panel planning panel on factual data, 5342 05:17:48,349 --> 05:17:52,019 which included one future and two former Nobel Prize winners. 5343 05:17:53,354 --> 05:17:55,423 One at least Josh Lautenberg, 5344 05:17:55,423 --> 05:17:58,659 was a long term colleague of of Dawn. 5345 05:17:59,894 --> 05:18:02,463 The overall 1986 plan 5346 05:18:02,463 --> 05:18:05,633 raised some topics as requiring more focused plans. 5347 05:18:06,167 --> 05:18:08,936 Dawn considered two of them to be especially important. 5348 05:18:09,970 --> 05:18:13,607 The specially focused outreach panel chaired by Mike DeBakey, 5349 05:18:13,607 --> 05:18:18,913 another previous colleague of Don's, advocated expanding the mission 5350 05:18:18,913 --> 05:18:22,149 and funding of the Library Network to promote online services to health 5351 05:18:22,149 --> 05:18:25,419 professionals not affiliated with institutions and medical work 5352 05:18:26,554 --> 05:18:29,557 that had medical libraries in 1999. 5353 05:18:29,757 --> 05:18:33,461 In 1990, Don made outreach to expand the use 5354 05:18:33,461 --> 05:18:37,264 of all alum programs and services and alum wide priority. 5355 05:18:37,264 --> 05:18:40,468 And it was one that was highest priority for him 5356 05:18:40,935 --> 05:18:44,105 till the day he left the National Library of Medicine. 5357 05:18:45,806 --> 05:18:48,008 Also in 1990, a special planning 5358 05:18:48,008 --> 05:18:51,946 panel on electric electronic imaging chaired by Dr. 5359 05:18:51,946 --> 05:18:55,983 King, I should say, endorsed the production of the visible human datasets. 5360 05:18:56,884 --> 05:18:59,120 And provided a blueprint for the project 5361 05:18:59,120 --> 05:19:02,957 in 1990, Don believed in the importance of imagery 5362 05:19:02,957 --> 05:19:06,060 in understanding biomedical concepts and data. 5363 05:19:08,662 --> 05:19:09,663 To Don. 5364 05:19:09,663 --> 05:19:12,833 The increasing availability of personal computers in offices 5365 05:19:12,833 --> 05:19:17,438 and homes was a golden opportunity to expand and alarms directly as a group, 5366 05:19:17,638 --> 05:19:20,741 to use this group to help professionals 5367 05:19:20,975 --> 05:19:24,945 by providing an affordable way to search Medline to answer clinical questions. 5368 05:19:25,346 --> 05:19:27,348 He was particularly, again, particularly 5369 05:19:27,448 --> 05:19:29,383 concerned about physicians practicing 5370 05:19:29,383 --> 05:19:32,153 outside of institutions with medical library services. 5371 05:19:32,987 --> 05:19:38,492 Less obviously pneumonia, less resources he envisioned would be the first in a line 5372 05:19:38,492 --> 05:19:43,697 products designed expressly for system developers and informatics researchers. 5373 05:19:44,031 --> 05:19:49,370 In 1984, the problem they were designed to address, namely the differences 5374 05:19:49,370 --> 05:19:52,506 in terminologies and codes used in disparate electronic 5375 05:19:52,840 --> 05:19:55,576 biomedical databases, 5376 05:19:55,576 --> 05:19:59,013 was a problem that Dawn saw, 5377 05:19:59,280 --> 05:20:02,049 but very few others did. 5378 05:20:02,049 --> 05:20:07,154 And then, in response to recent reductions in anyone's extramural budget 5379 05:20:07,521 --> 05:20:11,725 not unrelated to acrimonious interactions with publishers in the information 5380 05:20:11,725 --> 05:20:16,864 industry, Dodd's initial priorities included the grant budget 5381 05:20:17,031 --> 05:20:21,835 improving increasing it and improving relations with publishers and 5382 05:20:23,103 --> 05:20:25,573 the information industry. 5383 05:20:26,407 --> 05:20:29,476 There were many heroes in the best start to Don's tenure 5384 05:20:29,476 --> 05:20:33,414 at NLM, including great advisors, strong advocates, etc. 5385 05:20:33,414 --> 05:20:34,949 supporters in the Congress 5386 05:20:34,949 --> 05:20:38,419 and terrific on staff, both existing and newly recruited. 5387 05:20:38,719 --> 05:20:40,888 But Don's visionary ideas. 5388 05:20:41,055 --> 05:20:43,290 Ability to inspire. And. 5389 05:20:44,391 --> 05:20:46,293 Action and newly 5390 05:20:46,293 --> 05:20:49,196 and uncanny judgment were essential. 5391 05:20:49,597 --> 05:20:53,167 Throughout his career, Don made inspired decisions about what to do 5392 05:20:53,167 --> 05:20:54,501 and when to do it. 5393 05:20:54,501 --> 05:20:57,538 A shining example was his 5394 05:20:57,538 --> 05:21:00,774 decision to aggressively 5395 05:21:01,008 --> 05:21:05,613 pursue the establishment of NCI as the highest priority 5396 05:21:05,646 --> 05:21:08,616 coming out of the 1986 long range plan. 5397 05:21:10,150 --> 05:21:12,753 I should add that Don 5398 05:21:12,753 --> 05:21:17,591 also made great decisions about what not to do in that category. 5399 05:21:17,591 --> 05:21:21,996 His first and best was refusing Ken Smith's offer to step aside as 5400 05:21:22,830 --> 05:21:24,632 deputy director. 5401 05:21:25,332 --> 05:21:29,136 The establishment of an CPI 5402 05:21:29,203 --> 05:21:32,773 at an ELM in 1988, with the function shown here, 5403 05:21:33,040 --> 05:21:37,745 an initial budget of 8 million had a tremendous positive impact 5404 05:21:37,745 --> 05:21:41,548 on biomedical science and on the scope and effect of integration of mental health 5405 05:21:41,582 --> 05:21:44,051 services, as you heard from many speakers. 5406 05:21:44,585 --> 05:21:49,590 It made sense, as stated by the planning panel because, quote. 5407 05:21:50,724 --> 05:21:51,959 At the time. 5408 05:21:51,959 --> 05:21:55,296 The problems of scientific research in molecular biology 5409 05:21:55,296 --> 05:21:58,332 are increasingly problems of information science. 5410 05:21:59,199 --> 05:22:01,101 I think they still are. 5411 05:22:01,101 --> 05:22:03,971 However, the establishment 5412 05:22:03,971 --> 05:22:06,674 at NLM was by no means inevitable. 5413 05:22:07,408 --> 05:22:10,210 I am sure that the advocacy 5414 05:22:10,511 --> 05:22:14,948 of Josh Lederberg, Alan Maxim, another Nobel 5415 05:22:14,948 --> 05:22:18,085 Prize winner, and Richard Roberts, who would become one, 5416 05:22:19,186 --> 05:22:21,155 was extremely helpful 5417 05:22:21,155 --> 05:22:27,161 in overcoming the skepticism in the scientific community 5418 05:22:27,161 --> 05:22:31,398 that a library was a reasonable home for this responsibility. 5419 05:22:31,799 --> 05:22:36,103 And of course, in addition to bringing the scientific community 5420 05:22:36,103 --> 05:22:38,572 on board, Congress had to understand the need for it. 5421 05:22:40,174 --> 05:22:43,077 You could see, Don, immediately, immediately 5422 05:22:44,311 --> 05:22:46,847 into recruited Dan 5423 05:22:46,847 --> 05:22:50,617 Macy's, who was an NCI branch chief, who had served on the panel 5424 05:22:50,784 --> 05:22:55,522 that made the recommendation as director of the Lister Hill Center to help 5425 05:22:55,522 --> 05:22:59,893 NLM scientific visibility and credibility in biotechnology information. 5426 05:23:00,427 --> 05:23:04,098 And he was ably assisted by Denis Benson, who was already working in 5427 05:23:04,098 --> 05:23:05,366 Lister Hill at that time. 5428 05:23:06,500 --> 05:23:08,335 Parallel efforts, 5429 05:23:08,335 --> 05:23:11,572 which involved another NLM employee, Frances 5430 05:23:11,572 --> 05:23:13,874 Humphrey, Howard Hubert Humphrey sister. 5431 05:23:15,642 --> 05:23:19,646 The succeeded in educating Claude Pepper on the importance 5432 05:23:19,646 --> 05:23:23,717 of creating the center in the short window be cut 5433 05:23:23,717 --> 05:23:27,521 before the expected 1000 5434 05:23:27,788 --> 05:23:29,490 fold increase 5435 05:23:29,490 --> 05:23:31,525 in molecular biology data became. 5436 05:23:33,193 --> 05:23:34,995 By the time. 5437 05:23:35,696 --> 05:23:39,400 By the time Congress acted to establish NCB 5438 05:23:39,400 --> 05:23:43,337 in November 1988, Alnylam had a higher profile. 5439 05:23:43,637 --> 05:23:48,509 An initial set of microbiology research tools and was adding sequence 5440 05:23:48,509 --> 05:23:54,815 data tags to Medline citations, the latter being Don's Idea and 5441 05:23:55,816 --> 05:23:58,118 instruction to the indexing operation. 5442 05:23:59,486 --> 05:24:01,255 Dawn quickly hired 5443 05:24:01,255 --> 05:24:05,225 Dave David Litman to lead the new center once the law was passed, 5444 05:24:06,160 --> 05:24:09,730 and Jim Astill actually arrived in England shortly before. 5445 05:24:09,730 --> 05:24:10,464 David. 5446 05:24:10,464 --> 05:24:12,933 And of course, as I said, Dennis was already in place 5447 05:24:13,801 --> 05:24:16,236 and CBI was up and running 5448 05:24:16,236 --> 05:24:21,341 in 1989, early in 1989, and designated to assume 5449 05:24:21,475 --> 05:24:26,079 full responsibility for Gene Bank in 1982. 5450 05:24:33,120 --> 05:24:34,588 In the 1990s. 5451 05:24:34,588 --> 05:24:38,392 And Sally gave us insights to this and you heard from other people as well. 5452 05:24:38,992 --> 05:24:42,696 NLM embraced the Internet and the web browser and reinvented 5453 05:24:42,696 --> 05:24:44,431 all of its services. 5454 05:24:44,431 --> 05:24:48,035 It was this was not an easy thing to do. 5455 05:24:48,969 --> 05:24:50,304 It was inevitable. 5456 05:24:50,304 --> 05:24:54,741 As soon as the web browser appeared, every other interface was obsolete. 5457 05:24:54,741 --> 05:24:59,046 And issues and problems that you had been struggling with in the past like 5458 05:25:00,247 --> 05:25:03,083 nothing was really platform independent and designing 5459 05:25:03,083 --> 05:25:06,620 products to be loaded on machines as we were with grateful meant 5460 05:25:06,954 --> 05:25:09,890 and having to have a mac version of the PC version. So 5461 05:25:11,692 --> 05:25:16,330 the web browser was nirvana for service developers, 5462 05:25:16,897 --> 05:25:20,934 but we had a lot of services, so they all had to migrate and we had to 5463 05:25:22,536 --> 05:25:23,637 deal with. 5464 05:25:25,506 --> 05:25:28,075 Something that is not common today. 5465 05:25:28,275 --> 05:25:32,846 We had to make sure that all our existing users could make a had 5466 05:25:32,846 --> 05:25:36,450 an Internet connection and be had a Web capable workstation. 5467 05:25:36,717 --> 05:25:39,987 Now, of course, we're used to the fact that the. 5468 05:25:40,988 --> 05:25:44,958 Users having new devices means that the system developers 5469 05:25:45,192 --> 05:25:48,996 have to develop new services, not that you have to ensure that people 5470 05:25:48,996 --> 05:25:52,432 have the right equipment to use your service. 5471 05:25:53,967 --> 05:25:58,739 This change obviously enabled the things 5472 05:25:58,739 --> 05:26:02,943 that have made a huge impact on the world. 5473 05:26:03,977 --> 05:26:06,680 It enabled us to, 5474 05:26:06,680 --> 05:26:09,082 first off, and one of the earliest things 5475 05:26:09,683 --> 05:26:12,786 was to really make our historical resources 5476 05:26:13,053 --> 05:26:16,723 beautiful, gorgeous special collections, 5477 05:26:17,090 --> 05:26:20,627 pictures, movies, etc., accessible 5478 05:26:21,295 --> 05:26:24,731 to remote users in ways they never were before. 5479 05:26:24,865 --> 05:26:28,702 And this was something that was actually a big, high priority for Don. 5480 05:26:28,702 --> 05:26:29,870 As I said, he loved 5481 05:26:31,805 --> 05:26:34,374 the he loved 5482 05:26:34,775 --> 05:26:37,311 the historical collections. 5483 05:26:38,312 --> 05:26:42,983 The biggest thing I don't have to go over was except to tell you 5484 05:26:43,417 --> 05:26:48,221 that it was important to orchestrate. 5485 05:26:49,222 --> 05:26:51,725 The. Announcement 5486 05:26:51,892 --> 05:26:55,462 of the free med line in such a way 5487 05:26:55,896 --> 05:26:59,232 that there would not be any blowback from. 5488 05:27:00,867 --> 05:27:04,671 Others in the information industry about unfair competition 5489 05:27:04,671 --> 05:27:07,240 for the private sector and this, that and the other thing. 5490 05:27:07,841 --> 05:27:10,410 So consequently, 5491 05:27:10,410 --> 05:27:13,347 as Don said, I figured I was pretty bulletproof. 5492 05:27:13,380 --> 05:27:17,718 I was up there on the on the stage with Harold Varmus, 5493 05:27:18,118 --> 05:27:22,823 with the vice president and with Senators Harkin and Specter. 5494 05:27:23,724 --> 05:27:26,860 So he figured that 5495 05:27:26,860 --> 05:27:30,197 he was not going to get any blowback and he really didn't, 5496 05:27:30,197 --> 05:27:32,966 although this was a seismic and. 5497 05:27:35,002 --> 05:27:38,138 Upset in the access to information. 5498 05:27:38,538 --> 05:27:41,274 And of course once we saw 5499 05:27:41,675 --> 05:27:46,113 how the public was searching Medline the issue of. 5500 05:27:47,314 --> 05:27:50,217 But is Medline really going to be helpful to them 5501 05:27:50,217 --> 05:27:55,422 for many of their issues, which is gaining an understanding of basic concepts 5502 05:27:55,422 --> 05:27:59,426 and getting something that is not written and specialist few 5503 05:28:00,927 --> 05:28:02,729 people in library operations. 5504 05:28:02,729 --> 05:28:05,599 My predecessor, Alison Cogliano, 5505 05:28:06,500 --> 05:28:08,535 saw this one coming, so 5506 05:28:10,137 --> 05:28:12,806 a group was already put together to 5507 05:28:13,840 --> 05:28:16,476 develop a prototype of what became Medline. 5508 05:28:16,476 --> 05:28:20,380 Plus, as soon as we saw that the as Don saw 5509 05:28:20,380 --> 05:28:23,583 the level of public use of Medline. 5510 05:28:23,984 --> 05:28:25,619 This seemed like the next step. 5511 05:28:25,619 --> 05:28:29,523 And he was delighted because he would have always liked to serve the direct 5512 05:28:30,657 --> 05:28:31,558 the public. 5513 05:28:31,558 --> 05:28:35,962 But before the internet and the web browser, he didn't have a way 5514 05:28:36,263 --> 05:28:38,732 of delivering services that would be useful to people. 5515 05:28:44,771 --> 05:28:49,576 This is a very high level explanation which you already know. 5516 05:28:49,576 --> 05:28:52,579 And I'm not going to run through this about the fact 5517 05:28:52,579 --> 05:28:56,616 that by 2015 life was totally different. 5518 05:28:57,250 --> 05:29:00,854 And the time he retired, everything had expanded. 5519 05:29:00,854 --> 05:29:02,189 You've heard about it before. 5520 05:29:03,356 --> 05:29:04,925 You didn't hear so much. 5521 05:29:04,925 --> 05:29:10,030 But the active outreach program that NLM had was enormous. 5522 05:29:10,030 --> 05:29:15,102 The national the network of libraries had doubled in size because it now included 5523 05:29:15,669 --> 05:29:19,573 public libraries, community information centers and other partners, 5524 05:29:19,573 --> 05:29:25,779 as well as health sciences libraries, to help people understand 5525 05:29:25,779 --> 05:29:31,585 what was available to them for it and to actually become aware of it. 5526 05:29:32,452 --> 05:29:35,388 People don't use things if they don't know about them. 5527 05:29:35,789 --> 05:29:38,391 Many people say, Oh, you just discovered on the web. 5528 05:29:39,025 --> 05:29:41,461 Maybe a little harder now with so much stuff on the web. 5529 05:29:41,962 --> 05:29:45,265 Not as hard then, but a lot of people didn't at that time, 5530 05:29:45,332 --> 05:29:48,401 you know, didn't necessarily know why they should be on the web 5531 05:29:48,401 --> 05:29:50,570 or why they should be looking for it 5532 05:29:51,004 --> 05:29:52,773 and where they should go for health information. 5533 05:29:52,773 --> 05:29:54,541 So the outreach was really important. 5534 05:29:55,809 --> 05:29:56,877 And of course, 5535 05:29:56,877 --> 05:29:59,479 Medline began the avalanche 5536 05:30:00,280 --> 05:30:02,582 in terms of free data 5537 05:30:03,650 --> 05:30:05,018 available. 5538 05:30:05,185 --> 05:30:07,287 And there were. 5539 05:30:09,022 --> 05:30:13,527 Many more channels of access to data application 5540 05:30:13,527 --> 05:30:18,431 programing interfaces, download sites, integration of data across systems. 5541 05:30:18,431 --> 05:30:21,935 This is all made possible by these technological advances 5542 05:30:21,935 --> 05:30:25,872 that you all know about as well as I do. And. 5543 05:30:27,274 --> 05:30:31,244 NLM also worked on organizational arrangements and public policy 5544 05:30:32,279 --> 05:30:35,182 and trained more people that could contribute 5545 05:30:35,182 --> 05:30:37,751 to all of this, as we heard from some of them already today. 5546 05:30:38,451 --> 05:30:42,889 It was the interaction of all of these things, working on all of them. 5547 05:30:43,190 --> 05:30:47,527 They actually cemented and expanded them around 5548 05:30:47,761 --> 05:30:51,031 influence. So. 5549 05:30:52,632 --> 05:30:56,203 In this next set of slides I'm showing you are old slides. 5550 05:30:56,236 --> 05:30:58,772 This is what life looked like in 2015, 5551 05:30:59,472 --> 05:31:03,777 and you can see that a tremendous amount 5552 05:31:04,044 --> 05:31:08,248 had happened and much more has happened since and will still go on. 5553 05:31:08,515 --> 05:31:11,852 It's very interesting if you look at this little place 5554 05:31:11,852 --> 05:31:15,789 where it says PubMed citations back to 1940s 5555 05:31:16,156 --> 05:31:19,726 to the present, back to 1940s was also done. 5556 05:31:19,926 --> 05:31:23,496 But he initiated the project to go back from the sixties, 5557 05:31:23,496 --> 05:31:26,733 which is really where our automated data had started in 5558 05:31:27,200 --> 05:31:30,170 and convert the indexing 5559 05:31:31,204 --> 05:31:34,441 pre sixties indexing. 5560 05:31:34,441 --> 05:31:37,577 And of course the fast connections 5561 05:31:38,011 --> 05:31:43,283 were the payoff from the addition of data to analyze services. 5562 05:31:43,583 --> 05:31:46,953 What we just saw in terms of access to the literature 5563 05:31:46,953 --> 05:31:51,191 was huge and valuable and maybe our greatest contribution or is. 5564 05:31:51,625 --> 05:31:56,463 But on the other hand, you if you look back to 1984, it's in a straight line. 5565 05:31:56,463 --> 05:31:58,465 From there, it really is. 5566 05:31:58,798 --> 05:32:02,669 It's just doing it better with the with the technology that's available. 5567 05:32:03,904 --> 05:32:05,839 The creation of NCB 5568 05:32:05,839 --> 05:32:11,077 was a total different thing for album and it had huge benefits, 5569 05:32:11,311 --> 05:32:13,880 including the tight integration 5570 05:32:14,180 --> 05:32:17,884 and access mechanisms for all of these kinds of data. 5571 05:32:18,318 --> 05:32:21,421 I, you know, we could wonder whether this would have happened 5572 05:32:21,721 --> 05:32:25,091 if then CPI had been created somewhere else. 5573 05:32:25,592 --> 05:32:29,729 It probably wouldn't have had it happened as quickly or as smoothly. 5574 05:32:30,630 --> 05:32:32,065 Maybe it wouldn't have happened at all. 5575 05:32:32,065 --> 05:32:33,500 I don't know. But it's a huge 5576 05:32:34,868 --> 05:32:38,071 it's a huge legacy of that one decision. 5577 05:32:38,438 --> 05:32:41,408 Now, it's interesting to look at clinicaltrials.gov, 5578 05:32:41,942 --> 05:32:46,947 because the origin of clinicaltrials.gov was not a decision by anyone. 5579 05:32:47,380 --> 05:32:49,182 By John Lindbergh. 5580 05:32:49,182 --> 05:32:51,851 It followed the following sequence of events 5581 05:32:52,252 --> 05:32:55,855 in 1988, and ILM asked the staff what we could do 5582 05:32:56,122 --> 05:33:00,560 to serve AIDS researchers and patients better. 5583 05:33:01,795 --> 05:33:04,698 They said the top one would be to create AIDS baseline, 5584 05:33:05,432 --> 05:33:09,502 a focused, bibliographic database of AIDS information. 5585 05:33:10,036 --> 05:33:12,672 We did that in 19. 5586 05:33:13,707 --> 05:33:16,042 At the end of 1988, 5587 05:33:16,042 --> 05:33:19,579 in the same legislation that created NCI, 5588 05:33:19,879 --> 05:33:24,384 there was a requirement to build new AIDS resources for the community. 5589 05:33:25,118 --> 05:33:26,653 AIDS drugs. 5590 05:33:26,653 --> 05:33:28,922 AIDS trials. So. 5591 05:33:32,225 --> 05:33:34,027 I h everybody 5592 05:33:34,027 --> 05:33:38,064 looked at that requirement, which was HHS was all involved and everything too. 5593 05:33:38,064 --> 05:33:38,832 And they said, well, 5594 05:33:38,832 --> 05:33:41,801 and all of a sudden it's line and they have all this other database, 5595 05:33:42,302 --> 05:33:44,304 they should build the AIDS trials database. 5596 05:33:44,838 --> 05:33:45,605 So we did that. 5597 05:33:46,639 --> 05:33:48,608 So fast forward 5598 05:33:48,608 --> 05:33:51,911 in 1988, 98 for check in 5599 05:33:52,012 --> 05:33:55,081 1997 the. 5600 05:33:59,119 --> 05:34:03,690 The. Congress says builds clinical trials. 5601 05:34:03,690 --> 05:34:04,758 Soccer. 5602 05:34:05,458 --> 05:34:07,861 And Harold Varmus. 5603 05:34:10,263 --> 05:34:12,799 Who has this assignment? 5604 05:34:12,899 --> 05:34:14,100 Looks around. 5605 05:34:14,100 --> 05:34:15,668 Some progress is being made. 5606 05:34:15,668 --> 05:34:18,204 People are talking about it, but nothing is happening. 5607 05:34:18,405 --> 05:34:21,775 And in 1998, he sends Don Lindbergh an e-mail 5608 05:34:22,275 --> 05:34:27,047 and he said, Don, I want anyone to take this over to do this. 5609 05:34:27,447 --> 05:34:29,315 And you have the experience. 5610 05:34:29,315 --> 05:34:31,017 You've done well with AIDS trials. 5611 05:34:31,017 --> 05:34:34,654 So you take this on and please get back to me 5612 05:34:34,888 --> 05:34:38,058 immediately and tell me who on your staff is going to be in charge of this. 5613 05:34:38,525 --> 05:34:41,528 And Don shortly responded, Alex and Chris. 5614 05:34:42,362 --> 05:34:45,231 So then you end up 5615 05:34:45,231 --> 05:34:49,135 with the situation of alum as clinicaltrials.gov. 5616 05:34:49,135 --> 05:34:50,403 And as you see here, 5617 05:34:50,403 --> 05:34:54,307 we go down there, and ten years later, there's now a new requirement. 5618 05:34:55,842 --> 05:34:56,609 I think what's 5619 05:34:56,609 --> 05:35:01,014 interesting here and what our returned person 5620 05:35:01,014 --> 05:35:05,418 from the other galaxy would also find remarkable 5621 05:35:06,119 --> 05:35:09,456 was the extent to which NLM databases 5622 05:35:10,190 --> 05:35:13,359 and services were tied into 5623 05:35:14,761 --> 05:35:17,964 requirements for the research community. 5624 05:35:19,265 --> 05:35:21,034 Where in fact, 5625 05:35:21,034 --> 05:35:23,736 people had to use our services 5626 05:35:24,137 --> 05:35:27,941 because of what was. 5627 05:35:31,377 --> 05:35:32,345 Had been laid down 5628 05:35:32,345 --> 05:35:34,881 by legislation, public policy, and what have you. 5629 05:35:36,916 --> 05:35:39,819 This was a major change. 5630 05:35:39,819 --> 05:35:44,657 And then you get to an honest vocabulary portfolio. 5631 05:35:44,691 --> 05:35:49,095 I could give you a very long list of things that were acquired 5632 05:35:49,095 --> 05:35:50,497 as a result of this. 5633 05:35:50,497 --> 05:35:55,602 How this happened, it, Don, was essential 5634 05:35:55,668 --> 05:35:59,272 to this ending up being an initial priority. 5635 05:35:59,506 --> 05:36:03,143 And not only was it essential for him to get this 5636 05:36:03,176 --> 05:36:06,212 started in the direction for us to move ahead on this. 5637 05:36:06,746 --> 05:36:11,084 It was actually essential that he stayed as long as he did, 5638 05:36:11,918 --> 05:36:14,854 because this was also 5639 05:36:14,854 --> 05:36:20,360 quite a distance adjacent possible when we started, and it required 5640 05:36:20,793 --> 05:36:26,032 steady support and interest in this direction for this to happen 5641 05:36:29,035 --> 05:36:30,303 . I think. 5642 05:36:30,837 --> 05:36:32,939 That it is the data. 5643 05:36:34,841 --> 05:36:37,677 The NCB is genomic data. 5644 05:36:39,112 --> 05:36:42,849 The clinical trials, data and analytics 5645 05:36:43,249 --> 05:36:46,586 for in the standardization of electronic health data. 5646 05:36:46,853 --> 05:36:49,589 It is those things. 5647 05:36:49,589 --> 05:36:50,790 Which. 5648 05:36:51,491 --> 05:36:55,395 Are different in kind from what was going on 5649 05:36:55,395 --> 05:37:00,633 at the National Library of Medicine in 1984 and an alarm 5650 05:37:01,267 --> 05:37:04,771 that certainly Don Wennberg had a lot to do 5651 05:37:05,038 --> 05:37:07,106 with all of those directions. 5652 05:37:08,208 --> 05:37:10,310 But in fact 5653 05:37:10,310 --> 05:37:12,512 he would have been delighted and alone. 5654 05:37:13,446 --> 05:37:17,083 There is a connection between ANL and services direct used all the time 5655 05:37:18,051 --> 05:37:20,119 between Medline Plus and others, 5656 05:37:20,153 --> 05:37:23,289 and it is enabled by all of that work and standards. 5657 05:37:24,891 --> 05:37:26,559 But in the end, 5658 05:37:26,559 --> 05:37:30,830 what Don was really interested in was helping people. 5659 05:37:31,464 --> 05:37:33,900 And he focused 5660 05:37:34,100 --> 05:37:37,403 a lot of his own personal time on. 5661 05:37:39,772 --> 05:37:41,140 Trying to make 5662 05:37:41,140 --> 05:37:45,478 services and information more accessible, more usable, 5663 05:37:45,912 --> 05:37:50,350 and more useful to the whole community. And. 5664 05:37:51,351 --> 05:37:53,620 Trying to get more people 5665 05:37:53,620 --> 05:37:56,289 in that community into the business 5666 05:37:56,623 --> 05:38:00,059 of working on information systems and information delivery. 5667 05:38:00,460 --> 05:38:05,064 So I think that that is really a great part of this legacy. 5668 05:38:05,798 --> 05:38:06,699 Thank you. 5669 05:38:11,604 --> 05:38:14,207 Betsy, thank you very much. 5670 05:38:14,207 --> 05:38:18,511 We've received a number of comments during the course of your presentation 5671 05:38:18,511 --> 05:38:21,514 and one of them rings especially. 5672 05:38:22,849 --> 05:38:23,416 True. 5673 05:38:23,416 --> 05:38:26,419 And I'd like to just share and it's a quotation 5674 05:38:26,419 --> 05:38:29,155 that's been attributed widely to a variety of people 5675 05:38:29,422 --> 05:38:33,226 over the past several decades, but it applies here and I want to share it. 5676 05:38:33,226 --> 05:38:35,295 And then a follow on thought. 5677 05:38:35,295 --> 05:38:36,796 The comment is the Dr. 5678 05:38:36,796 --> 05:38:40,166 Lindbergh and his leadership of the National Library of Medicine 5679 05:38:40,800 --> 05:38:44,637 embraced the idea that the only way to predict the future is to invent it. 5680 05:38:45,805 --> 05:38:46,939 And I'd like to. 5681 05:38:46,939 --> 05:38:51,477 With respect to your your comments and those of earlier presenters say 5682 05:38:51,744 --> 05:38:54,914 we can extend that, saying the only way to predict 5683 05:38:54,914 --> 05:38:58,885 the future is to invent it, which is what he did, and to plan for it 5684 05:38:59,218 --> 05:39:02,355 with a distinctive appreciation of the past, combined 5685 05:39:02,355 --> 05:39:05,458 with embracing experiences and challenges and opportunities. 5686 05:39:05,458 --> 05:39:08,361 And to your very point at the end of your presentation, 5687 05:39:08,528 --> 05:39:13,232 being supportive of people all along the way colleagues, peers, students, 5688 05:39:14,067 --> 05:39:16,969 all who can contribute to the to the public service mission. 5689 05:39:16,969 --> 05:39:20,273 So thank you for allowing me to reflect in that way. 5690 05:39:20,273 --> 05:39:22,675 And thank you very much for your your presentation. 5691 05:39:24,010 --> 05:39:25,211 It's good to see you. 5692 05:39:25,445 --> 05:39:26,579 See you too. 5693 05:39:27,146 --> 05:39:28,114 Likewise. 5694 05:39:28,681 --> 05:39:32,452 So for our closing remarks this afternoon on this great day, 5695 05:39:32,618 --> 05:39:36,723 so many great presentations, we have a distinct honor before us. 5696 05:39:37,690 --> 05:39:39,759 It is my 5697 05:39:39,759 --> 05:39:43,796 pleasure to introduce Christopher Lindbergh. 5698 05:39:44,731 --> 05:39:49,569 Christopher Lindbergh is the grandson of Dr. 5699 05:39:49,569 --> 05:39:50,470 Lindbergh. 5700 05:39:50,870 --> 05:39:55,074 He is currently a senior at Portland State University in Portland, Oregon. 5701 05:39:55,074 --> 05:39:57,210 So he's joining us, obviously, from the West Coast. 5702 05:39:58,044 --> 05:40:00,847 His interest in photography and the outdoors 5703 05:40:01,247 --> 05:40:03,383 echo those of his grandfather. 5704 05:40:03,383 --> 05:40:05,952 In fact, as I understand it from Mrs. 5705 05:40:05,952 --> 05:40:07,553 Lindbergh, when Dr. 5706 05:40:07,553 --> 05:40:11,924 Lindbergh loaned Christopher his camera during a visit to Plymouth, Massachusetts, 5707 05:40:12,225 --> 05:40:15,528 when Christopher was about two and a half years old, Dr. 5708 05:40:15,528 --> 05:40:15,895 and Mrs. 5709 05:40:15,895 --> 05:40:18,798 Lindbergh were astounded at his excellent eye, 5710 05:40:19,065 --> 05:40:23,202 and they could see that Christopher had immediately taken to photography. 5711 05:40:23,803 --> 05:40:27,640 Indeed, he has grown to become what I understand, to be an avid photographer. 5712 05:40:28,040 --> 05:40:31,277 So it's therefore very apropos for Christopher 5713 05:40:31,277 --> 05:40:36,115 to close our proceedings today to help us see even further how his grandfather 5714 05:40:36,115 --> 05:40:40,820 exorcized his own eye to lead the world's largest biomedical library. 5715 05:40:41,087 --> 05:40:43,156 And in so doing, as we know, 5716 05:40:43,156 --> 05:40:46,859 leave a remarkable legacy of service to science and society. 5717 05:40:47,360 --> 05:40:49,829 Christopher, a warm welcome to you from all of us 5718 05:40:49,962 --> 05:40:51,998 at the National Library Medicine, the NIH. 5719 05:40:52,832 --> 05:40:54,200 And thank you for joining us today. 5720 05:40:54,200 --> 05:40:55,902 I'm going to turn it over to you. Thank you. 5721 05:40:57,904 --> 05:41:00,940 Thank you, Jeff, for those kind introductory words. 5722 05:41:00,940 --> 05:41:03,810 It's so great to see so many of you. 5723 05:41:03,810 --> 05:41:06,679 Betsy Can Smith, Claire McDonald's. 5724 05:41:07,480 --> 05:41:10,483 Jeff I like to take this opportunity to thank you personally 5725 05:41:10,483 --> 05:41:14,220 for all your hard and tireless work the last few years, putting this together 5726 05:41:14,220 --> 05:41:17,323 and making sure that we were able to finally get it done. 5727 05:41:17,323 --> 05:41:21,160 And I'd also like to extend that to the media team today 5728 05:41:21,160 --> 05:41:23,196 for making sure everything is done so smoothly. 5729 05:41:26,499 --> 05:41:29,035 Yes, as I say, this is no small feat. 5730 05:41:29,035 --> 05:41:30,603 I would have loved to have seen all of you 5731 05:41:30,603 --> 05:41:32,772 in person back at the library, of course, but 5732 05:41:34,640 --> 05:41:36,309 health risks demand . 5733 05:41:36,309 --> 05:41:39,011 Otherwise, we convene remotely. 5734 05:41:39,011 --> 05:41:42,381 Despite my initial disappointment at not being able to see you all, 5735 05:41:42,648 --> 05:41:43,916 I realized that again. 5736 05:41:43,916 --> 05:41:47,887 Like all of you, I agree 100% that my grandfather would have loved 5737 05:41:47,887 --> 05:41:52,692 the fact that this was still happening remotely and had an avenue to, 5738 05:41:53,259 --> 05:41:56,529 you know, collect, connect globally and make sure that this was 5739 05:41:57,964 --> 05:42:00,666 a nice. 5740 05:42:00,666 --> 05:42:03,736 Pathway for information to be exchanged and for all of us 5741 05:42:03,736 --> 05:42:06,506 to get together again after being apart for so long. 5742 05:42:09,642 --> 05:42:11,711 That was one of his main goals in his career 5743 05:42:11,711 --> 05:42:16,215 was to make public communication and make certain information 5744 05:42:16,349 --> 05:42:20,052 available to the public, as is perfectly exemplified 5745 05:42:20,052 --> 05:42:24,557 by his efforts with Medline and Medline, plus all those things. 5746 05:42:25,391 --> 05:42:28,694 He was someone who truly wanted to help people like feel and to further 5747 05:42:28,694 --> 05:42:30,563 the betterment of mankind, genuinely. 5748 05:42:30,563 --> 05:42:34,433 And there are many people like that throughout history who do as good 5749 05:42:34,433 --> 05:42:38,738 a job as he did and as are and are, 5750 05:42:38,771 --> 05:42:42,708 as in in close proximity to us as they do them. 5751 05:42:43,776 --> 05:42:47,480 He saw into the future of medicine and knew that the storage and transfer 5752 05:42:47,480 --> 05:42:48,881 and application of information 5753 05:42:48,881 --> 05:42:51,851 was going to change and knew that computers were part of the answer. 5754 05:42:52,752 --> 05:42:55,988 In a chapter of the recent book that Betsy 5755 05:42:55,988 --> 05:42:59,592 and Robert Logan have put together and put so much work into. 5756 05:43:00,660 --> 05:43:02,028 There's an excerpt that he says 5757 05:43:02,028 --> 05:43:05,231 Journals on the shelf will become too remote for immediate decisions. 5758 05:43:05,231 --> 05:43:08,568 And I think he was he was spot on and saw that coming a mile away 5759 05:43:09,101 --> 05:43:13,940 and that he assumed that computers would soon be potentially essential. 5760 05:43:14,473 --> 05:43:17,977 And I think by, you know, our our remote convening today, 5761 05:43:17,977 --> 05:43:20,479 he was on to something. 5762 05:43:21,147 --> 05:43:23,516 He loved his time at the library as as 5763 05:43:23,516 --> 05:43:25,785 I did as well the short time that I was there. 5764 05:43:27,553 --> 05:43:30,189 And it was truly the passion that fulfilled his life. 5765 05:43:31,157 --> 05:43:36,429 I was privileged to see this process firsthand from behind the scenes 5766 05:43:36,429 --> 05:43:39,732 as my time spent with him at the house was matched 5767 05:43:39,732 --> 05:43:42,201 in my early years to the time spent in the office. 5768 05:43:43,836 --> 05:43:46,005 He was the same person in and out of the office. 5769 05:43:46,005 --> 05:43:48,040 We all knew the same person. 5770 05:43:48,040 --> 05:43:51,577 Always cool, calm, collected from door to door. 5771 05:43:51,577 --> 05:43:51,978 He moved. 5772 05:43:51,978 --> 05:43:56,015 He loved every minute there, and I truly don't believe he ever had a bad day 5773 05:43:56,682 --> 05:43:59,318 in office or in his time at the library. 5774 05:44:00,886 --> 05:44:03,489 As I watched parts of the library grow and change, 5775 05:44:03,489 --> 05:44:07,159 the library seemed to watch right back as I grew up and 5776 05:44:08,194 --> 05:44:10,963 got to know everybody and they got to know me and see me 5777 05:44:10,963 --> 05:44:12,898 grow up and go through my processes. 5778 05:44:12,898 --> 05:44:17,436 And I was for a while an annual fixture in the mezzanine 5779 05:44:17,536 --> 05:44:21,107 every summer, which in itself was a great pleasure. 5780 05:44:21,140 --> 05:44:24,110 And I look back as 5781 05:44:24,110 --> 05:44:25,745 some of the greatest times 5782 05:44:25,745 --> 05:44:29,281 that I will ever get to experience. 5783 05:44:29,482 --> 05:44:32,718 These are, of course, among core memories of my childhood, 5784 05:44:32,918 --> 05:44:36,155 as are as are the people who were at the library at the time 5785 05:44:37,456 --> 05:44:41,661 previously mentioned Betsy Clam so many more 5786 05:44:41,661 --> 05:44:45,898 that I that I would love to mention and personally thank and extend gratitude 5787 05:44:46,899 --> 05:44:49,301 for for all the all of the time and 5788 05:44:50,169 --> 05:44:53,139 and kind energy that they have given me over the years. 5789 05:44:57,443 --> 05:45:00,579 I believe that I saw the library in its golden years, 5790 05:45:00,646 --> 05:45:02,782 both because of my grandfather's influence 5791 05:45:02,782 --> 05:45:06,852 and, as previously mentioned, the people who worked with him at the time 5792 05:45:06,852 --> 05:45:11,323 who he had handpicked and trusted and personally believed in. 5793 05:45:11,957 --> 05:45:16,762 And these are the part of the part of what made the team so special. 5794 05:45:16,762 --> 05:45:20,199 These people are part of what made the process and his time there so special. 5795 05:45:20,766 --> 05:45:25,037 The group of doers and accomplished years that followed and supported him. 5796 05:45:25,104 --> 05:45:27,640 And that he supported and followed right back. 5797 05:45:30,643 --> 05:45:32,011 Again, people like Betsy 5798 05:45:32,011 --> 05:45:34,847 Humphrey and Robert Logan are. 5799 05:45:36,582 --> 05:45:39,885 On our end and incredibly 5800 05:45:41,087 --> 05:45:44,290 special to the Lindbergh family and will forever 5801 05:45:44,290 --> 05:45:48,260 be held in the highest regards in our hearts and in 5802 05:45:48,260 --> 05:45:50,129 have put in so much fantastic 5803 05:45:50,129 --> 05:45:54,533 work into the book the last few years and making sure that we all can properly 5804 05:45:56,435 --> 05:45:56,902 remember 5805 05:45:56,902 --> 05:45:58,971 him and remember ourselves with him. 5806 05:46:00,039 --> 05:46:02,308 And the EP 5807 05:46:02,341 --> 05:46:07,780 and the organization of events and exhibits throughout the years 5808 05:46:07,780 --> 05:46:11,951 made the library a place that was enjoyed as well as respected. 5809 05:46:12,218 --> 05:46:17,490 And I think that was, again, one of his one of his driving goals for the library, 5810 05:46:18,758 --> 05:46:21,894 not just to be an intellectual powerhouse, 5811 05:46:21,894 --> 05:46:27,500 but to be a place that was inviting to everyone and made people want to learn 5812 05:46:27,500 --> 05:46:30,636 and want to come and explore and investigate. 5813 05:46:32,838 --> 05:46:34,039 And, you know, 5814 05:46:34,039 --> 05:46:37,476 things like the murder rooms and and the costume parties. 5815 05:46:37,476 --> 05:46:42,181 And, you know, when when David Nash had the Frankenstein mask on, you know, 5816 05:46:42,181 --> 05:46:45,384 these are all things that were just so fantastic and so great that 5817 05:46:45,951 --> 05:46:49,722 wouldn't have happened otherwise, I feel like. 5818 05:46:50,189 --> 05:46:52,391 And this was how he conducted himself, 5819 05:46:53,058 --> 05:46:55,594 a combination of well-rounded comedy, 5820 05:46:55,594 --> 05:47:00,633 as has been previously stated and constant commanding respect 5821 05:47:00,666 --> 05:47:07,139 not of people, but of the situation and how he handled handled things. 5822 05:47:08,707 --> 05:47:09,775 These also seem to be 5823 05:47:09,775 --> 05:47:12,044 recurring things in our adventures. 5824 05:47:12,778 --> 05:47:16,615 For example, 4th of July, one year at the Government Printing Office, 5825 05:47:16,615 --> 05:47:22,054 followed by several hours of lost driving in the city or boat 5826 05:47:22,054 --> 05:47:26,659 trips up the Potomac for the weekend, complete with towing up rock. 5827 05:47:26,659 --> 05:47:30,362 We one time we towed up a rock that was so big it took four people 5828 05:47:30,362 --> 05:47:33,132 and three different watercraft, two on wedge from the anchor. 5829 05:47:33,766 --> 05:47:37,403 And, you know, seemed seemingly. 5830 05:47:37,403 --> 05:47:39,638 Random elements of hilarity 5831 05:47:40,339 --> 05:47:42,808 that were seemed only 5832 05:47:42,808 --> 05:47:45,978 to to two part to perfect for the scenario, 5833 05:47:46,145 --> 05:47:48,914 you know, two to perfect. 5834 05:47:50,082 --> 05:47:51,317 So even an absurd 5835 05:47:51,317 --> 05:47:54,720 situation is just always had command of the situation. 5836 05:47:55,287 --> 05:47:58,023 And I saw how far this reach was 5837 05:47:58,023 --> 05:48:02,361 and how far his respect followed him on numerous trips that we took together. 5838 05:48:03,596 --> 05:48:06,532 One such trip to Alaska for the Native Voices. 5839 05:48:06,532 --> 05:48:09,468 When I was, I think, one of our favorite trips we ever took, 5840 05:48:10,102 --> 05:48:11,704 and I had never been there before. 5841 05:48:11,704 --> 05:48:12,404 My grandfather 5842 05:48:12,404 --> 05:48:16,275 was finishing up the work on that exhibit, Native Voices, whose traveling 5843 05:48:16,275 --> 05:48:20,079 adaptation would reach over 20 venues across the country in the following years. 5844 05:48:21,447 --> 05:48:25,150 Here we were met by Ted Mala, who facilitated our numerous bookings 5845 05:48:25,150 --> 05:48:30,756 and appointments and is one another of many, many people that I was able to meet 5846 05:48:31,190 --> 05:48:36,228 and be around and learn from and have been lucky to call my friend 5847 05:48:36,829 --> 05:48:38,230 ever since. 5848 05:48:40,499 --> 05:48:43,235 The hospitality and accommodation was second to none. 5849 05:48:43,235 --> 05:48:48,340 And I had experiences, like I said, that I may never have again that were so rich. 5850 05:48:48,340 --> 05:48:49,642 And these range from 5851 05:48:50,609 --> 05:48:53,312 salmon fishing in the rain to long nights 5852 05:48:53,579 --> 05:48:56,882 talking, you know, over several rounds of drinks with whoever was there. 5853 05:48:56,882 --> 05:49:02,655 And they were the kinds of conversations that had no destination or direction. 5854 05:49:03,389 --> 05:49:07,259 And I think sometimes these are the richest forms of conversation. 5855 05:49:07,960 --> 05:49:13,232 And it was rare that you would have a conversation with my grandfather 5856 05:49:13,232 --> 05:49:15,734 and not have learned something that you didn't know before. 5857 05:49:17,036 --> 05:49:19,538 And my relationship with him was similar in nature. 5858 05:49:19,538 --> 05:49:23,575 And I always had a tremendous respect for him, which came from the usual 5859 05:49:23,575 --> 05:49:26,912 familial, familial structure, but also in 5860 05:49:26,912 --> 05:49:29,181 his inherent way of commanding the room. 5861 05:49:29,982 --> 05:49:32,217 And there is never a lack of conversation. 5862 05:49:32,217 --> 05:49:33,385 And rare was the occasion, 5863 05:49:33,385 --> 05:49:36,188 like I say, where you would walk away not having learned something. 5864 05:49:37,056 --> 05:49:40,426 He had piles of books cresting the armrests on both sides 5865 05:49:40,793 --> 05:49:43,762 of two separate armchairs in two different rooms of the house. 5866 05:49:44,630 --> 05:49:48,033 And he had just had an ever growing intellect and thirst for knowledge. 5867 05:49:48,267 --> 05:49:53,072 This gave him the ability to entertain a conversation with anyone about anything 5868 05:49:53,706 --> 05:49:56,508 in a way that made them feel included without 5869 05:49:57,242 --> 05:50:01,180 looming an intellect or making you feel less than or uninformed. 5870 05:50:02,314 --> 05:50:05,150 I never felt condescended to or spoken down to, 5871 05:50:05,284 --> 05:50:09,321 which as I grew older, I came to realize was a true testament to his character 5872 05:50:09,321 --> 05:50:11,991 and himself as a person and all people. 5873 05:50:13,192 --> 05:50:16,662 Consistency and understanding were cornerstones of our relationship. 5874 05:50:17,429 --> 05:50:19,898 Some of his hobbies became mine and my endeavors 5875 05:50:19,898 --> 05:50:23,168 were always a priority and were treated as such and vice versa. 5876 05:50:23,936 --> 05:50:27,706 We both shared a love for cinema and film that stemmed from photography 5877 05:50:28,374 --> 05:50:33,212 and grew into something we learned we just loved doing together. 5878 05:50:34,246 --> 05:50:37,016 One Christmas, I remember we were all staying up for the New Year's, 5879 05:50:37,016 --> 05:50:40,652 for the ball drop, and we were channel surfing waiting to pass the time. 5880 05:50:41,720 --> 05:50:44,289 And until this time, my grandfather had never waste, 5881 05:50:44,356 --> 05:50:46,291 you know, wasted time with television. 5882 05:50:46,291 --> 05:50:49,194 And he saw it as just that, a waste of time for the most part. 5883 05:50:49,828 --> 05:50:52,464 And that night, though, we stumbled 5884 05:50:52,464 --> 05:50:56,835 upon Turner Classic movies, and this was a soft spot 5885 05:50:56,835 --> 05:51:00,406 my grandfather didn't know he had, and he was instantly hooked. 5886 05:51:00,406 --> 05:51:03,976 And if you're not familiar, it's just old, older movies 5887 05:51:03,976 --> 05:51:07,513 from anywhere from like the 50, 6070s, eighties, 5888 05:51:08,047 --> 05:51:12,518 you know, spaghetti westerns and things like that, and James Cagney movies. And 5889 05:51:13,552 --> 05:51:14,420 he's here. 5890 05:51:14,420 --> 05:51:16,088 He loved it. Right, right from the jump. 5891 05:51:16,088 --> 05:51:17,556 So we watched the nineties. 5892 05:51:17,556 --> 05:51:22,461 The first film that we found was the 1966 adaptation of Fahrenheit 451, 5893 05:51:23,295 --> 05:51:25,998 followed by a couple of Cary Grant movies. 5894 05:51:26,565 --> 05:51:30,769 And we became so infatuated with the films that we missed the ball, 5895 05:51:30,769 --> 05:51:33,972 drop the whole event and watched until about four in the morning, 5896 05:51:34,773 --> 05:51:35,574 which was shocking. 5897 05:51:35,574 --> 05:51:38,043 It was absolutely unheard of. 5898 05:51:38,110 --> 05:51:40,813 After the end of each film, I would go to turn off the TV, 5899 05:51:40,813 --> 05:51:42,514 and before I could reach it, he would say, Well, 5900 05:51:42,514 --> 05:51:45,017 hold on now, hold on, see what else there is. 5901 05:51:45,584 --> 05:51:47,653 And we would slide right into the next movie, 5902 05:51:47,653 --> 05:51:49,121 and then we would get right through that one. 5903 05:51:49,121 --> 05:51:51,290 And it just went on and on and on. Analysis. 5904 05:51:51,290 --> 05:51:53,492 I feel his first introduction to television 5905 05:51:54,293 --> 05:51:59,364 and you know, after that he like he loved the Westerns, the John Wayne's 5906 05:51:59,364 --> 05:52:02,367 and all those great things whenever, whenever he had the chance. 5907 05:52:02,367 --> 05:52:08,140 But it was never a form of entertainment that he stuck it out or would seek out. 5908 05:52:10,309 --> 05:52:10,876 That being 5909 05:52:10,876 --> 05:52:13,645 said, this has become one of our favorite things to do together. 5910 05:52:14,213 --> 05:52:15,714 Our love of photography helped me 5911 05:52:15,714 --> 05:52:18,350 grow a passion and practice that has become a business. 5912 05:52:19,751 --> 05:52:23,388 As you can see, I'm in a partially finished studio 5913 05:52:23,388 --> 05:52:25,791 for green screens and media production, 5914 05:52:27,893 --> 05:52:31,063 and I have been running a multimedia production business 5915 05:52:31,063 --> 05:52:34,466 for about the past year and hope to scale into a successful brand. 5916 05:52:34,967 --> 05:52:38,370 After the practices of my grandfather and his photography, 5917 05:52:39,271 --> 05:52:43,775 in addition to myself, Rob Logan and I have joined forces in attempts 5918 05:52:43,775 --> 05:52:45,144 to digitize and preserve 5919 05:52:45,144 --> 05:52:49,548 that vast collection of photography, which includes prints and digital copies 5920 05:52:49,815 --> 05:52:52,951 and amassed images from my grandfather's extensive travels. 5921 05:52:53,652 --> 05:52:55,787 These will ideally be the next installments 5922 05:52:55,787 --> 05:52:58,790 in the Lindbergh legacy and will hopefully be available 5923 05:52:59,258 --> 05:53:02,995 on the Internet as these recordings will be in the next year or two. 5924 05:53:04,963 --> 05:53:07,499 He shared these experiences with my father before me 5925 05:53:07,499 --> 05:53:09,868 and I hope to share with my family in the future. 5926 05:53:10,602 --> 05:53:12,871 Looking back, the things that stand out as core 5927 05:53:12,871 --> 05:53:15,841 memories are seemingly simple in nature. 5928 05:53:16,008 --> 05:53:18,010 But the older I get, I see them differently 5929 05:53:18,010 --> 05:53:20,012 and with a more refined understanding. 5930 05:53:20,812 --> 05:53:24,883 For example, the fact that my grandfather taught me how to swim in the backyard 5931 05:53:24,883 --> 05:53:27,986 pool of the house in Maryland, which I'm sure many of you are familiar 5932 05:53:29,188 --> 05:53:29,922 as a child. 5933 05:53:29,922 --> 05:53:32,090 These are some of the best days in your life. 5934 05:53:32,591 --> 05:53:35,027 Sunshine Pool Toys. 5935 05:53:35,027 --> 05:53:37,429 Visiting the grandparents for the summer. 5936 05:53:37,429 --> 05:53:39,464 It's all sublime. 5937 05:53:39,464 --> 05:53:41,500 This is how I remember this memory for years. 5938 05:53:41,500 --> 05:53:42,834 But now, with the prospect 5939 05:53:42,834 --> 05:53:47,172 of planning family for myself, I have a whole new level of respect 5940 05:53:47,172 --> 05:53:51,443 for my grandfather and what he was able to accomplish in that moment. 5941 05:53:51,476 --> 05:53:54,780 What was a simple afternoon of poolside fun to a child 5942 05:53:55,180 --> 05:53:59,117 was the result of years of hard work, accomplishment and commitment. 5943 05:53:59,551 --> 05:54:03,188 And the satisfaction of teaching your grandchild to swim in your own pool 5944 05:54:03,589 --> 05:54:08,894 alongside your beautiful house is a whole a whole worldly accomplishment in itself. 5945 05:54:10,662 --> 05:54:11,330 Accomplishment 5946 05:54:11,330 --> 05:54:13,365 was simply second nature to my grandfather. 5947 05:54:14,333 --> 05:54:17,669 His effortless control is something I look up to to this day 5948 05:54:17,669 --> 05:54:19,871 and try to restore in myself. 5949 05:54:19,871 --> 05:54:22,341 He managed to master so many facets of his life 5950 05:54:22,374 --> 05:54:25,410 in so many areas that it seemed daunting by comparison, 5951 05:54:26,345 --> 05:54:29,581 but he wouldn't see them as such and would simply advise you to do your best 5952 05:54:29,915 --> 05:54:31,650 and to do what's right. 5953 05:54:31,650 --> 05:54:33,986 And oftentimes they are one in the same. 5954 05:54:37,823 --> 05:54:40,325 Somehow some parts of me found it 5955 05:54:41,059 --> 05:54:45,864 somewhat difficult to organize this collection of words, mostly because 5956 05:54:46,632 --> 05:54:50,602 it seems stems from wanting to accurately and appropriately represent him 5957 05:54:50,836 --> 05:54:55,374 and remember him, as everyone here has done today, in so many beautiful words. 5958 05:54:56,675 --> 05:54:59,011 But it's really the finality of this event. 5959 05:55:00,312 --> 05:55:04,516 And although this is the final ceremony, I remind myself that it is 5960 05:55:04,516 --> 05:55:07,653 far from the last memory of the legacy best left behind. 5961 05:55:08,654 --> 05:55:10,422 The National Library of Medicine is forever 5962 05:55:10,422 --> 05:55:13,525 changed and influenced for the better, as is the world. 5963 05:55:14,359 --> 05:55:17,896 I extend a tremendous thanks to my grandfather for being the driving force 5964 05:55:18,497 --> 05:55:21,066 for our family and our surroundings. 5965 05:55:22,901 --> 05:55:26,471 And with that, I offer my closing statements and I thank you guys 5966 05:55:26,471 --> 05:55:29,708 all once again for being here, for organizing 5967 05:55:29,708 --> 05:55:31,977 such amazing tributes. 5968 05:55:32,711 --> 05:55:35,981 And I hope to see you as many of you soon as I can. 5969 05:55:37,716 --> 05:55:39,051 Thank you very much. 5970 05:55:41,620 --> 05:55:43,655 Christopher, thank you very, very much. 5971 05:55:44,589 --> 05:55:47,392 Your reputation, as I understand it, 5972 05:55:47,592 --> 05:55:50,028 from your grandmother as a photographer has 5973 05:55:51,963 --> 05:55:53,965 is incredibly, wonderfully obvious. 5974 05:55:54,066 --> 05:55:57,669 Your keen eye and keen ability with words 5975 05:55:58,170 --> 05:56:01,239 is fantastic. And. 5976 05:56:01,740 --> 05:56:03,775 I share your thoughts 5977 05:56:04,142 --> 05:56:07,312 respectfully, and I appreciate them both professionally. 5978 05:56:07,546 --> 05:56:08,513 Having known Dr. 5979 05:56:08,513 --> 05:56:12,551 Lindbergh myself for 7 to 8 years, maybe a decade, 5980 05:56:13,185 --> 05:56:16,888 but also personally, if I may so publicly say 5981 05:56:17,923 --> 05:56:18,957 the beautiful way in which 5982 05:56:18,957 --> 05:56:21,526 you articulated your memories of your grandfather is 5983 05:56:22,761 --> 05:56:24,629 unique to you 5984 05:56:24,763 --> 05:56:25,964 , unique to your memories. 5985 05:56:25,964 --> 05:56:27,933 But it's universal at the same time. 5986 05:56:27,933 --> 05:56:29,868 And I thank you 5987 05:56:29,868 --> 05:56:34,406 both professionally and personally for their wonderful, wonderful remarks. 5988 05:56:34,539 --> 05:56:38,110 And very respectfully, of course, 5989 05:56:38,110 --> 05:56:40,812 and with your remarks, I want to thank you very, 5990 05:56:40,812 --> 05:56:44,783 very much for your time and our communication for today. 5991 05:56:45,016 --> 05:56:47,786 And I look forward to our own the crossing again soon 5992 05:56:48,086 --> 05:56:49,654 and know that we're here to support you. 5993 05:56:49,654 --> 05:56:52,324 And we wish you all the best in your studies 5994 05:56:52,391 --> 05:56:55,927 and certainly in your business and on your own path in life. 5995 05:56:55,927 --> 05:56:59,831 Influenced so wonderfully by your grandfather and his leadership 5996 05:57:00,465 --> 05:57:03,869 of the National Library, Medicine and Science and society 5997 05:57:03,869 --> 05:57:06,805 and all that we've learned today from these wonderful proceedings. 5998 05:57:07,105 --> 05:57:08,140 Thank you very much. 5999 05:57:08,140 --> 05:57:10,675 And you really likewise, Jeff. 6000 05:57:10,675 --> 05:57:13,044 Thank you so much. Thank you. Welcome. 6001 05:57:14,012 --> 05:57:16,014 So with your remarks, Christopher, 6002 05:57:16,481 --> 05:57:19,017 and all of the wonderful contributions today, we're going 6003 05:57:19,017 --> 05:57:22,220 to conclude this special and outstanding program 6004 05:57:22,220 --> 05:57:26,057 that we've had the experience of of watching and being a part of today 6005 05:57:26,792 --> 05:57:29,060 on behalf of the entire National Library Medicine, 6006 05:57:29,060 --> 05:57:31,096 which I've had the great privilege of representing today. 6007 05:57:31,596 --> 05:57:35,200 Thanks to everyone for their contributions, and especially, 6008 05:57:35,200 --> 05:57:36,935 of course, to our keynote presenter, Dr. 6009 05:57:36,935 --> 05:57:41,673 Isaac, for his enlightening and thought provoking presentation. 6010 05:57:42,841 --> 05:57:46,144 Thanks again to the friends of the National Library Medicine, the NLM, 6011 05:57:46,211 --> 05:57:50,115 for their co-sponsorship of this event and for being such wonderful friends 6012 05:57:50,115 --> 05:57:50,816 of the NAL 6013 05:57:50,816 --> 05:57:54,453 and the world's largest biomedical library located on the campus of the NIH. 6014 05:57:55,053 --> 05:57:58,390 I'd also like to thank, along with all of you who are watching 6015 05:57:58,390 --> 05:58:02,627 and all who contributed today our outstanding and Elm communications 6016 05:58:02,627 --> 05:58:06,131 and media teams for their time and their outstanding talent and our 6017 05:58:06,465 --> 05:58:10,936 mutual support for such a long time to realize this wonderful event. 6018 05:58:10,969 --> 05:58:13,071 Each and every one of you on these fantastic. 6019 05:58:13,071 --> 05:58:14,739 It's been a pleasure working with you. 6020 05:58:14,739 --> 05:58:17,676 And this program is a testimony to Dr. 6021 05:58:17,676 --> 05:58:20,011 Lindbergh's leadership and scientific legacy. 6022 05:58:20,011 --> 05:58:23,882 And it's also a testimony to our teamwork and representation of the world's 6023 05:58:23,882 --> 05:58:26,885 largest biomedical library to the global public. 6024 05:58:27,519 --> 05:58:30,589 And, of course, thanks to all of you for tuning in near 6025 05:58:30,589 --> 05:58:34,392 and far for our watching our program today. 6026 05:58:34,493 --> 05:58:36,962 The archive proceedings will be available soon. 6027 05:58:36,962 --> 05:58:40,398 As I and others have mentioned, they will be available permanently 6028 05:58:40,398 --> 05:58:43,368 and freely to anyone in the world with Internet access, 6029 05:58:43,802 --> 05:58:46,104 and it will be in the Nature Video Cast Archive. 6030 05:58:46,371 --> 05:58:49,875 And for everyone who registered for the program, you'll receive word 6031 05:58:50,141 --> 05:58:53,445 when those proceedings are freely and permanently available. 6032 05:58:54,012 --> 05:58:57,282 Thanks once more, my colleagues and I appreciate your tuning in 6033 05:58:57,282 --> 05:58:59,751 and we look forward to keeping in touch. Thank you.