>>GOOD MORNING.
THANK YOU FOR JOINING US.
I'M HOWARD CHANG, A CO-CHAIR OF
THE WORKING GROUP.
WE'RE EXCITED TO HAVE A BROAD
HOST OF GUESTS TO INFORM THE
ADVISORY COMMITTEE TO THE
DIRECTOR'S WORKING GROUP ON THE
UPCOMING REPORT ON CATALYZING
DEVELOPMENT AND USE OF NOVEL
ALTERNATIVE METHODS, NAMs. ,
THIS WILL INFORM HOW NIH INVESTS
MOVING FORWARD.
NEXT SLIDE PLEASE.
ACHIEVEING SCIENTIFIC
BREAKTHROUGH REQUIRES CONTINUOUS
DEVELOPMENT VALIDATION AND
ADOPTION OF TECHNOLOGIES AND
TECHNIQUES.
ANIMAL RESEARCH CONTINUES TO BE
NECESSARY FOR UNDERSTANDING
HUMAN DISEASE AND DEVELOPMENT OF
TREATMENTS, WE'VE SEEN THAT
SO-CALLED NOVEL ALTERNATIVE
METHODS, NAMs, HOLD TREMENDOUS
PROMISE FOR INCREASING TOOLS
AVAILABLE TO ACCOMPLISH NIH'S
MISSION TO ADVANCE HUMAN.
ADDITIONALLY, THEY OPEN THE
DOORS FOR NEW SCIENTIFIC
APPROACHING INCLUDING
COMPLEMENTARY AND SOMETIMES
ABILITY TO ANSWER NEW SETS OF
QUESTIONS FROM THOSE BEST SUITED
FOR ANIMAL-BASED APPROACHES.
THEREFORE WHILE TRADITIONAL
ANIMAL MODELS CONTINUE TO BE
VITAL TO ADVANCE SCIENTIFIC
KNOWLEDGE, DIFFERENT MODELS
OFFER UNIQUE STRENGTHS THAT WHEN
UTILIZED CORRECTLY OR IN
COMBINATION CAN EXPAND
RESEARCHERS TOOLBOXS OR ANSWER
PREVIOUSLY NOT ANSWERABLE
BIOMEDICAL RESEARCH QUESTIONS.
AT A TIME WHEN TECHNOLOGIES ARE
CHANGING IT'S IMPORTANT TO
CONSIDER HOW TO SUPPORT GROWTH
AND MAXIMIZE THE VALUE IN
EQUITABLE AND ACCESSIBLE WAY.
NEXT PLEASE.
WHILE THERE'S A BROAD AND
DIVERSE SET OF TOOLS AND
TECHNIQUES THAT COULD FALL UNDER
THE UMBRELLA OF NOVEL
ALTERNATIVE METHODS, FOR THE
PURPOSE OF OUR WORKING GROUP
WE'LL NARROW THE SCOPE TO THE
RAPIDLY CHANGING TECHNIQUES
COMPLEMENTARY TO TRADITIONAL
ANIMAL MODELS.
IN PARTICULAR, OUR WORKING GROUP
HAS FOCUSED ON IN CHEMICAL, IN
VITRO USING CELL TECHNIQUES .
WE SAW A FEW QUESTIONS FROM
REGISTRANTS ABOUT RESEARCH USING
INVERTEBRATES SUCH AS DROSOPHILA
OR THE FRUIT FLY.
RESEARCH CONTINUES TO ADVANCE
BIOMEDICAL INVESTIGATION AND
HAVE LED TO 14 PRIZES TO DATE.
NIH VALUES OUR INVESTMENT BUT
COULD HAVE HAD MULTIPLE
WORKSHOPS ON THAT TOPIC ALONE.
NEXT SLIDE PLEASE.
TO IDENTIFY AND ADVISE PRIORITY
AREAS IN THE BEST WAYS WHICH NIH
CAN SUPPORT AND PROMOTE NOVEL
ALTERNATIVE METHODS, DR. LARRY
TABAK, NIH ACTING DIRECTOR, GAVE
MYSELF AND DR. LYRIC JORGENSON
THE HONOR OF CO-CHAIRING THIS
COMMITTEE TO THE WORKING GROUP
ON CATALYZING DEVELOPMENT AND
USE OF NOVEL ALTERNATIVE METHODS
TO ADVANCE BIOMEDICAL RESEARCH.
WE CONVENED A GROUP OF EXPERTS
FROM DIVERSE BACKGROUNDS,
SECTORS, FIELDS, INCLUDING
INDUSTRY, ACADEMIA AND SISTER
AGENCIES LISTED HERE.
NEXT PLEASE.
IN JANUARY OF 2023 DR. TABAK
CHARGED A WORKING GROUP TO
ASSESS LANDSCAPE OF ALTERNATIVE
METHODS IN BIOMEDICAL INCLUDING
CHALLENGES AND OPPORTUNITIES OF
DIFFERENT METHODS IN DIFFERENT
APPLICATIONS.
THIS ANALYSIS WILL HELP THE
WORKING GROUP IDENTIFY HIGH
PRIORITY AREAS FOR NIH
INVESTMENT TO CATAPULT PROGRESS
IN UNDERSTANDING BIOMEDICAL
PROCESSES AND ENHANCED
CAPABILITIES TO FORM BIOMEDICAL
RESEARCH.
TO ACCOMPLISH THIS THE WORKING
GROUP IS CONSULTING WITH EXPERTS
IN THE COMMUNITY DURING THIS
REGULAR MEETINGS AND PROVIDE
UPDATE TO OUR PROGRESS TO THE
ACD JUST THIS PAST JUNE.
WE'RE SET TO PROVIDE
RECOMMENDATIONS IN A REPORT TO
THE ACD AT THE END OF THE YEAR.
NEXT PLEASE.
TO ENSURE WE HEAR FROM VOICES OF
EVERYONE WE PUBLISH A REQUEST
FOR INFORMATION, RFI, ON JUNE 12
TO INVITE PUBLIC FEEDBACK TO
CONFIRM THE WORKING GROUP'S
RECOMMENDATIONS.
THE RFI WAS ORIGINALLY SET TO
CLOSE THE WEEK OF AUGUST 16,
HOWEVER TO ALLOW MORE TIME FOR
RESPONSE FOLLOWING THIS MEETING
THE DEADLINE WAS EXTENDED TO
SEPTEMBER 5.
WE ENCOURAGE EVERYONE TO SHARE
THOUGHTS TO HELP INFORM AND
SHAPE OUR FINAL REPORT.
SO FAR WE'VE RECEIVED THOUGHTFUL
FEEDBACK TO ADD NICELY TO THE
CONVERSATIONS THE WORKING GROUP
HAS BEEN HAVING.
WE'RE HEARING ABOUT DATA, BENCH
MARKING, THE IMPORTANCE OF
CROSS-DISCIPLINARY
COLLABORATION, ALL COMMENTS WILL
BE POSTED.
NEXT PLEASE.
SO THE WORKING GROUP DISCUSSION
TODAY A KEY THEME EMERGED, THE
POWER OF INTERDISCIPLINARY
WORK, TRANSLATING KNOWLEDGE INTO
PRODUCTS OR PRACTICES RELYING ON
BRINGING TOGETHER DISCIPLINES,
TECHNOLOGY, DATA.
COLLABORATION DRIVES INNOVATION,
AND TEAMS OF PEOPLE FROM
DIFFERENT DISCIPLINES AND
BACKGROUNDS CAN CREATE
OUT-OF-THE-BOX SOLUTIONS.
EACH SECTOR HAS A POTENTIAL ROLE
TO PLAY.
BY INTEGRATING EARLY IN
TECHNOLOGY CONCEPTION
RESEARCHERS CAN DEVELOP NAMs
THAT PROVIDE HIGH QUALITY
FINDINGS REPRODUCEIBLE FINDINGS.
TODAY'S MEETING WE HOPE TO LEARN
MORE ABOUT A THE COMMUNITY
THOUGHTS ON OVERCOMING BARRIERS
AND DRIVE FORWARD PROGRESS IN
NAMs DEVELOPMENT AND USE
THROUGH DIVERSE TEAMS.
NEXT PLEASE.
SO WITH THAT, THOSE GOALS IN
MIND, WE HAVE AN EXCITING AGENDA
MODERATEED BY OUR WORKING GROUP
MEMBERS.
WE'LL HAVE TWO SESSIONS, FROM
9:15 TO 10:30 OPPORTUNITIES AND
CHALLENGES FOR NAMs BY DR.
NANCY LANE, THEN CROSS-SECTOR
APPROACHES FOR DRIVING NAMs
USE, MODERATEED BY DR. DAN
TAGLE, FOLLOWED BY QUESTIONS.
WE'LL HAVE THREE PANEL SESSIONS
1-2 P.M., THEN LEVERAGING
DATASETS MODERATEED BY DR.
NOVAKAVIC.
3:30 TO 4:30 EQUITABLE
DEPLOYMENT OF ROBUST AND
RELIABLE NAMs INTO PRACTICE
MODERATEED BY DR. TONY BAINES.
REGISTRANTS ARE INVITED TO
PROVIDE QUESTIONS, AND WE'RE
HAPPY TO SHARE WITH MODERATORS
TO CHOOSE FROM.
NEXT SLIDE PLEASE.
BEFORE WE START THE FIRST
SESSION I THANK THE WORKING
GROUP MEMBERS, SPEAKERS AND ALL
OF YOU FOR PARTICIPATING IN THIS
MEETING, VIEWPOINTS ARE CRITICAL
FOR MAKING A CYCLE WHEREBY
RESEARCH CONDUCTED WITH NAMs
INFORM WORK IN OTHER MODELS
WHICH INFORMS HUMAN HEALTH IN
THE FORM OF BIOMEDICAL DATA THAT
FURTHER IMPROVES MODELS USED IN
RESEARCH AND INVESTIGATORS CAN
UTILIZE -- COMBINE TOOLS IN A
BEST WAYS TO ANSWER THEIR
ULTIMATE QUESTIONS TO UNDERSTAND
AND IMPROVE HUMAN HEALTH.
SO THANK YOU, EVERYBODY.
THE FIRST SESSION MODERATEED BY
WORKING GROUP MEMBER DR. NANCY
LANE NCY LANE WILL GET US
STARTED.
I'LL HAND IT OVER TO DR. LANE
PLEASE.
>>GOOD MORNING.
I'M DR. NANCY LANE FROM THE
UNIVERSITY OF CALIFORNIA AT
DAVIS, AND THIS MORNING WE'RE
GOING TO TALK ABOUT THE
OPPORTUNITIES AND CHALLENGES OF
NOVEL ALTERNATIVE METHODS IN
BIOMEDICAL RESEARCH.
NEXT SLIDE PLEASE.
, THIS SESSION WILL FOCUS ON
SUCCESSFUL DEPLOYMENT OF NAMs
WHETHER FOR CONDUCTING BASIC
RESEARCH, UNCOVERING DISEASE
MECHANISMS OR TRANSLATING
KNOWLEDGE INTO PRODUCTS OR
PRACTICE, RELIES HEAVILY ON
BRINGING TOGETHER DISCIPLINES,
TECHNOLOGIES, AND DATA.
THIS SESSION WILL FOCUS ON
RESEARCH AREAS FOR WHICH NAMs
HAVE BEEN IMPACTFUL TO IDENTIFY
BEST PRACTICES FOR LEVERAGING
THESE APPROACHES.
NOW, WE HAVE FOUR OUTSTANDING
PRESENTERS THIS MORNING.
OUR FIRST ONE WILL BE DR. NATHAN
PRICE WHO IS AT THE THORNE
HEALTH TECH AND ON LEAVE FROM
THE INSTITUTE OF SYSTEMS
BIOLOGY.
HE IS EXPERT ON PRECISION HEALTH
AND WILL SHARE WITH US SOME
NOVEL WORK THEY ARE DOING THERE.
ALSO HAVE THOMAS HARTUNG FROM
JOHNS HOPKINS UNIVERSITY, AND HE
IS AN INTERNATIONAL EXPERT ON
TRANSLATIONAL/PRODUCT
DEVELOPMENT.
NICOLE KLEINSTREUER, DIRECTOR OF
NATIONAL TOXICITY PROGRAM
INTERAGENCY CENTER FOR
EVALUATION OF ALTERNATIVE
TOXICOLOGYIC METHODS AND ADJUNCT
ASSOCIATE PROFESSOR AT THE YALE
SCHOOL OF PUBLIC HEALTH.
HER RESEARCH FOCUSS ON
BIOLOGICAL SYSTEMS AND
SUSCEPTIBLEIBILITY TO
PERTURBATIONS.
AND THEN CHIRAG PATEL FROM
HARVARD MEDICAL SCHOOL,
INFORMATICS, DISSECTING
DIFFERENCES THROUGH DATA SOURCES
THAT CAPTURE THE COMPREHENSIVE
CLINICAL EXPERIENCE.
SO WE'RE HONORED TO HAVE BOTH --
ALL OF THEM TODAY.
NOW, ALL OUR SPEAKERS WILL GIVE
A SHORT 10-MINUTE PRESENTATION,
AND AFTERWARDS WE'LL SPEND TIME
AS A PANEL DISCUSSING SOME
PERTINENT QUESTIONS WHICH I WILL
SHOW YOU AFTER OUR SPEAKERS GIVE
THEIR PRESENTATIONS.
SO THE FIRST ONE TODAY WILL BE
NATHAN PRICE.
WELCOME, DR. PRICE.
>>WELL, GOOD MORNING, EVERYONE.
IT'S A PLEASURE TO BE HERE, I'M
LOOKING FORWARD TO AN INTRIGUING
DAY.
TODAY I'M GOING TO TALK ABOUT IN
PARTICULAR DIGITAL TWINS AND
ALTERNATIVE CLINICAL TRIAL
DESIGNS.
SO, THE WAY I'M COMING INTO THIS
HAS BEEN A REAL INTEREST OVER
THE LAST DECADE OR SO ON WAYS
THAT WE APPROACH NOT ONLY LATE
STAGE DISEASE BUT THINKING MORE
ABOUT EARLY DETECTION AND WAYS
THAT WE CAN LEVERAGE A LOT MORE
DENSE DATA STARTING FROM THE
PERIOD OF WELLNESS MOVEING INTO
LATER AREAS.
MOST INTRIGUEING IS NON-ACUTE
TOXINS OVER THE COURSE OF
DECADES, THEY WON'T GIVE US A
DISEASE TOMORROW BUT DO
EVENTUALLY AS WELL AS POSITIVE
SIDE WE'RE TRYING TO AIM FOR
PREVENTION, INCREASING HEALTH
SPAN, THINGS OF THIS NATURE,
INTERVENTIONS MAY TAKE A PERIOD
OF TIME, HOW DO WE THINK ABOUT
THAT DIFFERENTLY, WE WROTE A
BOOK ON THIS A FEW MONTHS AGO
WITH LEROY HOOD.
I'LL TALK ABOUT ALZHEIMER'S
DISEASE, ONE OF THE GREAT
CHALLENGES WE HAVE.
TREATMENT IS INCREDIBLY
DIFFICULT, BUT AIMING AT
PREVENTION IS A MUCH EASIER
CHALLENGE.
THIS IS FOR OBVIOUS REASONS.
ONCE YOUR NEURONS HAVE DIED AND
YOU LOST A TON OF SYNAPSES TRY
TO REGROW THOSE WITH A SMALL
MOLECULE IS VERY CHALLENGING
ENDEAVOR, MAYBE FANCIFUL.
PREVENTION IS MUCH SIMPLER.
I DID WRITE ABOUT THIS IN THE
L.A. TIMES A MONTH AGO.
ALSO, "THE LANCET" CAME OUT WITH
RECOMMENDATIONS IN 2020 AROUND A
BUNCH OF DIFFERENT FACTORS
MODIFIABLE, SO THINGS YOU CAN
MODIFY TO CHANGE YOUR RISK OF
ALZHEIMER'S DISEASE OVER TIME.
I'LL POINT AT THIS BECAUSE I'M
VERY MUCH IN FAVOR OF THE
RECOMMENDATIONS PUT OUT.
I THINK THEY LEFT SOME THINGS
OUT THAT SHOULD HAVE BEEN
INCLUDED OR THAT WE COULD AT
LEAST ARGUE SHOULD BE INCLUDED,
AN EXAMPLE WITH DIGITAL TWINS
AND ALTERNATIVE CLINICAL TRIALS
ABOUT WHY I THINK THAT IS AND
WHAT WE CAN DO ABOUT IT.
SO, TO JUMP IN, I'M GOING TO
GIVE AN EXAMPLE OF A DIGITAL
TWIN MODEL WE SPENT THE LAST
THREE YEARS DEVELOPING, WHICH IS
A MODEL OF HOW THE BRAIN
MAINTAINS HEALTH.
HIS AN ODE-BASED MODEL WITH A
BAYESIAN OVERLAY, I WON'T HAVE
TIME TO GO INTO DETAIL.
THIS LEVERAGES DATA FROM A
THOUSAND PAPERS THAT ARE IN THE
LITERATURE, SO THIS WOULD
INCLUDE KINETIC BINDING RATES
AND FEEDBACK LOOP CYCLES AND SO
FORTH
WHAT THIS HAS DONE FOR ME HAS
GIVEN ME A DIFFERENT VIEW OF
WHAT I THINK IS DRIVING
ALZHEIMER'S.
WE CAN TALK ABOUT THAT
SEPARATELY.
FOR THE PURPOSES OF TODAY, WHAT
THIS MODEL REPRESENTS OR ANY
DIGITAL TWIN MODEL SINCE WE'RE
TALKING GENERALLY TODAY IS A
COMPLEX TESTABLE HIGH POTENTIAL
HYPOTHESIS HOW YOU MAINTAIN
HEALTH, LAYER ON INFORMATION,
HOW DISEASE INITIATES,
PROGRESSES, KILLS, THINKING
ABOUT CLINICAL TRIALS IN A
DIFFERENT WAY WHEN WE HAVE THIS
KIND OF CAPABILITY.
I'M LEAVING OUT A LOT BUT I'VE
GOT TO GO QUICKLY TODAY
WHAT THIS LET US DO IS DIGITAL
TWIN SIMULATION.
THIS IS ON A PER-PATIENT BASIS
SO I'LL GIVE AN EXAMPLE.
IN THIS CASE WE WOULD BE LOOKING
AT AN INDIVIDUAL, HAPPENS TO BE
A MAN AGE 50, TWO COPIES OF THE
APOE4 GENE, A NUMBER OF
MEASUREMENTS OUT OF THE BLOOD OR
COGNITIVE ASSESSMENTS, DIFFERENT
RISK FACTORS AT PLAY.
WE USE THIS IN A WAY TO MODEL
THE UNCERTAINTY THAT'S THERE AND
WE CAN BUILD A PROBABILISTIC
FUTURE OF WHAT WE WOULD EXPECT
TO BE THE AGE OF DIAGNOSIS FOR
SOMEONE GIVEN THESE
MEASUREMENTS.
WE WOULD EXPECT THE MOST LIKELY
AGE OF DIAGNOSIS TO BE 61, WE
BELIEVE THERE WOULD BE A 99%
PROBABILITY THIS INDIVIDUAL
WITHOUT CHANGES WOULD HAVE
DEMENTIA BY AGE 68 BASEED ON
THIS SIMULATION OF BRAIN
PHYSIOLOGY.
WE ALSO ARE GOING THROUGH A
NUMBER OF POTENTIAL
INTERVENTIONS, THINGS THEY COULD
DO TO HAVE AN EFFECT.
WHAT YOU'LL NOTICE IF YOU LOOK
FROM THE BOTTOM IS -- THIS IS
ALL GEARED TOWARDS NATURAL
PRODUCTS OR LIFESTYLE
INTERVENTIONS, YOU CAN DO THIS
FOR DRUGS, THERE'S A FASCINATING
STORY AROUND STATINS THAT I
DON'T HAVE TIME TO GET INTO.
BASICALLY WHAT YOU'LL SEE FROM
THE BOTTOM IS AT AN INDIVIDUAL
LEVEL MOST THINGS SHOW NO
EFFECT.
IF YOU LOOK UP HERE AT THE ALL,
I'M USING ALL FOR BREVITY'S
SAKE, WE CALCULATE ALL POSSIBLE
COMBINATIONS, THERE EXIST AS
COMBINATION TO EXPECT A DELAY IN
ONSET OF ALZHEIMER'S FOR 6 YEARS
IN THIS PERSON.
TO GET A SENSE HOW MUCH THIS
CHANGES PERSON TO PERSON I'LL
SHOW THIS JUST A VIDEO TO CYCLE
THROUGH, THIS WILL GIVE VERY
BRIEFLY -- I KNOW WE'RE ZIPING
THROUGH A LOT OF STUFF HERE, BUT
BASICALLY WHAT THIS GIVES IS A
SENSE FOR HOW DIFFERENT IT IS
PERSON TO PERSON, HOW CAN YOU DO
PERSONALIZEED RECOMMENDATIONS
AND SO FORTH.
ONE INTERESTING THING OF THESE
MODELS IS THAT YOU CAN DO IT FOR
PERSONALIZEED RECOMMENDATIONS,
ALSO SIMULATE ENTIRE POPULATIONS
ANNUAL EXPECTATIONS ACROSS
POPULATIONS FOR INTERVENTION
STANDINGS OF STRATEGY AND
SIMULATES COGNITION OVER COURSE
OF LIFE.
YOU CAN ASK QUESTIONS WHAT CAN
YOU DO EVEN IF YOUR EFFECT TAKES
A WHILE TO MANIFEST.
THAT'S WHAT I WANT TO TALK ABOUT
TODAY.
SO IN TERMS OF DATA, TO GIVE A
BRIEF OVERVIEW, THESE ARE ALL
GENETIC AND KNOWN HAZARD RATES
IN THE LITERATURE THAT WE HAVE
DATA ON FOR WHEN PEOPLE GET
ALZHEIMER'S DIAGNOSIS.
WHAT WE DID FROM THIS
FUNDAMENTAL MECHANISM IS
SIMULATE 10 MILLION DIGITAL
TWINS, HOW WELL DOES THAT
REPRESENT THE POPULATION WE'RE
AIMING FOR?
SO WHEN WE DO THAT, THESE ARE
THE PREDICTIONs THAT COME OUT.
WHAT YOU'LL SEE IS THAT YOU'RE
ABLE TO THROUGH A COMMON COMPLEX
HYPOTHESIS LEVERAGING A HUGE
AMOUNT OF MOLECULAR DATA AS WELL
AS 30 CLINICAL TRIALS AND
RESEARCH STUDIES, THAT YOU CAN
GET GOOD EXPLANATORY POWER FOR
AGES WHICH YOU SEE PEOPLE GET
DIAGNOSED WITH DEMENTIA, AND
FACTORS THAT RELATE TO THAT.
I'M GOING TO TALK ABOUT THAT
HERE IN JUST A MOMENT.
SO WHAT DOES THIS MEAN FOR NOVEL
ALTERNATIVE METHODS, THE SUBJECT
WE'RE HERE TO TALK ABOUT TODAY?
WHAT I WANT TO FOCUS ON IS THE
WAY DIGITAL TWINS ENABLE
PERSONALIZEED EVIDENCE-BASED
MEDICINE.
THIS ENTAILS THINKING ABOUT HOW
DO WE GENERATE VERY GOOD HIGH
QUALITY DATA USING DIGITAL TWINS
WHERE WE'RE INTERVENING IN
PERSONALIZED WAYS WITH DIFFERENT
INDIVIDUALS.
I'M GOING TO GIVE AN EXAMPLE,
COMMON COMPOUND, VITAMIN D,
BASIC THAT EVERYONE KNOWS ABOUT.
ONE OF THE REASONS I BRING IT UP
IS IF YOU LOOK AT OBSERVATIONAL
DATA, HAVING LOW VITAMIN D IS
ASSOCIATED WITH A VERY HIGH
INCREASED RISK FOR ALZHEIMER'S
DISEASE, HAZARD RATIO IS .23,
YOU'RE ONLY 23% AS LIKELY TO
HAVE ALZHEIMER'S.
CAUSATION VERSUS CORRELATION, SO
THERE HAVE BEEN A SET OF
RANDOMIZED CLINICAL TRIALS DONE
ON VITAMIN D, AND THOSE TRIALS
ARE NOT COME OUT STRONGLY, WE'VE
SEEN THIS STORY MANY TIMES.
THE QUESTION IS WE THROW THIS
AWAY, WE DO NOT INCLUDE VITAMIN
D IN THE RECOMMENDATIONS IN "
THE LANCET" FOR 2024
ALZHEIMER'S, DESPITE THE FACT
THE APPARENT EFFECT WOULD BE ONE
OF THE LARGEST THAT'S KNOWN.
ONE OF THE THINGS CAN YOU DO
WITH DIGITAL TWINS IS SIMULATE
IN DETAIL CLINICAL TRIALS AROUND
A GIVEN MECHANISM, THE WAY YOU
DO THAT IS BECAUSE YOU CAN
ACTUALLY ENROLL PEOPLE OF
EXACTLY THE AGES THAT COME INTO
THE TRIAL AND SIMULATE EFFECTS
FOR THE MECHANISM AT EXACTLY THE
LEVEL THAT YOU BELIEVE IT'S AT
AND THAT YOU HAVE FROM THE
LITERATURE AND ASK THE SIMPLE
QUESTION WHAT WE EXPECT TO SEE A
POSITIVE RESULT?
AND SO CONDENSING DOWN A HUGE
AMOUNT OF WORK HERE WHAT YOU CAN
DO IS LOOK AT THEN THE PREDICTED
DIFFERENCE IN -- THIS IS A
COGNITIVE TEST, MMSE, THAT YOU
WOULD EXPECT, HOW LONG WOULD YOU
HAVE TO FOLLOW PEOPLE OF A
DIFFERENT AGE TO SEE A SIDE?
IF YOU PLOT THE CLINICAL TRIALS
DONE, THE REASONS WE DON'T
INCLUDE VITAMIN D IN
RECOMMENDATIONS FOR THE DELAY OF
ALZHEIMER'S, THEY ALL APPEAR
HERE.
IN OTHER WORDS, IF WE SIMULATE
THE MECHANISM WE FIGURED OUT BY
PUTTING THIS MODEL TOGETHER THAT
MECHANISMS IN THE LITERATURE,
BASICALLY THAT VITAMIN D
CONTROLS NOISE OVER TIME WITH
THE CHOLESTEROL TRAFFICKING IN
THE BRAIN, WHEN WE PUT THAT IN
THE DIGITAL TWINS THE LOWERING
OF THE VARIABILITY WILL GIVE
THOSE -- THOSE PEOPLE WILL GET
ALZHEIMER'S AT 25% THE RATE.
THIS IS THROWN AWAY IN THE
COMMUNITY BECAUSE OF THIS
CLINICAL TRIAL DESIGN.
OBSERVED TRIALS ARE LONG ENOUGH
TO SEE THE EFFECT.
THE ARGUMENT IS THAT WE MAY BE
OVERTHROWING AWAY INFORMATION
BECAUSE OF THE WAY CLINICAL
TRIALS ARE SET UP.
SO, THE CURRENT PARADIGM WE ALL
KNOW.
I'M RUNNING OUT OF TIME.
NOVEL ALTERNATIVE METHOD HERE
YOU STILL RUN A BLINDED
RANDOMIZED CLINICAL TRIAL BUT
NOW YOU'LL TEST A DIGITAL TWIN
MODEL, PERSONALIZED MULTI-FACTOR
RECOMMENDATION.
THE DIFFERENCE IS ONE OF THE
REASONS YOU DON'T SEE EFFECT IN
SHORT TERM WITH A SINGLE
COMPOUND ALMOST EVERYONE IS A
NON-RESPONDER BECAUSE YOU'RE
HOPEING FOR RANDOM CHANCE TO
TELL YOU FOR THE VITAMIN D OR
WHATEVER TO BE THE FINAL PIECE
OF THE PUZZLE.
IF YOU DO MULTI-FACTORIAL
DIGITAL TWIN-BASED SIMULATION
YOU THEN TAKE MEASUREMENTS,
APPLY THE MODEL, GIVE A
DIFFERENT INTERVENTION FOR EVERY
PERSON, HIGHER EFFECT SIZE, YOU
NEED LOWER N, MOST PARTICIPANTS
BECOME RESPONDERS BECAUSE YOU'RE
DOING A COMBINATION THAT'S
PERSONALIZEED TO THEM.
YOU END UP WITH SOMETHING MUCH
MORE ECONOMICALLY VIABLE AND YOU
GET A DIFFERENT PATH INTO THIS
CAUSATION VERSUS CORRELATION
ISSUE.
WE CAN THINK DIFFERENTLY ABOUT
CLINICAL TRIALS, TO GET TO A
PLACE WE CAN DO MUCH MORE WITH
PREVENTIVE FROM STANDPOINT OF
THINGS LIKE THE SIMPLE VITAMIN D
CASE THAT MIGHT BE PREVENTIVE AS
WELL AS LOOKING AT TOXICOLOGY
OVER THE COURSE OF TIME.
WITH THAT I WILL END.
THANK YOU.
[APPLAUSE]
>>WHAT A TREAT FOR BEING ON
TIME.
DO WE HAVE TIME FOR A QUESTION
OR TWO OR DO WE NEED TO MOVE?
DOES ANYBODY FROM THE ROOM OR
ONLINE HAVE ANY QUESTIONS, ONE
OR TWO WE CAN TAKE FOR DR.
PRICE?
>>JUST SO I'M CLEAR WITH THE
DIGITAL TWIN MOD EL WHAT I'M
SEEING FROM THE PRESENTATION ONE
OF THE KEY ATTRIBUTES HAVE YOU
DECREASED VARIABILITY, AND
THAT'S OBVIOUSLY SOMETHING
THAT'S DESIRED.
BUT, AGAIN, SHOWING THAT YOU
DECREASE VARIABILITY THROUGH A
MODEL THAT SIMULATES THE EXACT
SAME PERSON IS DIFFERENT FROM
HAVING POPULATION VARIABILITY
BUILT INTO THE ASSESSMENT.
SO I'M JUST TO GET A HANDLE ON
THAT.
>>LET ME CLARIFY THAT.
>>OKAY.
>>SO I'M NOT TALKING ABOUT
DECREASING VARIABILITY IN
SIMULATION OF A PERSON.
THERE'S MASSIVE INTERPERSONAL
VARIABILITY.
WHEN WE SIMULATE THE TWINS WE'RE
SIMULATEING ALL KINDS OF
DIVERSITY ENSURES IN GENETICS,
PERSONAL BEHAVIOR, NUTRITION,
ALL KINDS OF THINGS, A HUGE
AMOUNT OF VARIABILITY IS BUILT
IN.
THE THING WHICH WAS TOO MUCH
DETAIL WAS THE MECHANISM WE USE
FOR VITAMIN D.
FOR THE PURPOSE OF THIS
AUDIENCE, THAT'S WHEN I SAID
DECREASED VARIABILITY, THAT'S
WHAT I WAS REFERRING TO, TOO
MUCH DETAIL TO PUT IN.
THE POINT THERE IS JUST THAT IN
THE DIGITAL TWIN MODEL BECAUSE
WE KNOW, WE HAVE A MECHANISM FOR
WHAT VITAMIN D DOES OVER THE
COURSE OF TIME AND CAN SIMULATE
EFFECT OVER DECADES, EFFECT ON
NEURONAL DEATH, VERY SMALL IN
ACCRUING.
YOU CAN IDENTIFY THAT THAT
MECHANISM IS EFFICIENT TO
EXPLAIN THE INCREDIBLE OBSERVED
HAZARD RATIO IN A WAY THAT'S
PLAUSIBLE.
AND SO FOR MY MONEY FOR EXAMPLE
I WOULD SAY THE EVIDENCE BEHIND
LIKE VITAMIN D THAT SHOULD BE IN
THE RECOMMENDATIONS, TO ME IT'S
STRONG ENOUGH THAT I WOULD
INCLUDE IT, UNLESS LIKE A
WELL-POWERED CLINICAL TRIAL SAID
NOT TO.
THE ONES DONE SO FAR AS I SHOWED
WHEN YOU SIMULATE THOSE CLINICAL
TRIALS IT SHOWS THAT YOU WOULD
EXPECT TO SEE EXACTLY WHAT WAS
SEEN BECAUSE THOSE THINGS ONLY
FOLLOWED PEOPLE FOR SIX MONTHS,
THREE YEARS AT THE MAX.
AND THE THREE-YEAR FOLLOW-UP WAS
DONE IN FAIRLY YOUNG PEOPLE.
FOR EFFECT THEY WERE MEASUREING
IT'S BASICALLY AN UNDERPOWERED
ARGUMENT THAT THEY DON'T HAVE
ANY CHANCE OF SEEING THIS SUBTLE
EFFECT OVER THAT SMALL AMOUNT OF
TIME EVEN THOUGH THE AGGREGATE
IS VERY LARGE.
IT GIVES A DIFFERENT PARADIGM
THINK HOW LONG YOU GO ABOUT A
CLINICAL TRIAL BY MOVING AWAY
FROM THIS, HEY, WE'RE TESTING
ONE COMPOUND TO WE'RE TESTING
COMBINATIONS OF THINGS TOGETHER.
SO THAT YOU -- I MEAN AT THE
CENTERPIECE, IF YOU'RE RUNNING A
TRIAL WHERE 2% OF PEOPLE ARE
RESPONDERS YOU NEED A LARGE N.
IF YOU RUN A TRIAL WHERE 70% ARE
RESPONDERS YOU CAN GET IT WITH A
SMALLER N, FROM PERSONALIZATION
IN DOING IT DIFFERENTLY.
>>THANK YOU.
AS EACH SPEAKER, PLEASE IDENTIFY
YOURSELF.
WE'RE JUST GETTING INTO THIS,
IT'S OKAY.
YES, WE'RE GOOD.
>>DOES THAT WORK?
>>YES.
>>ARNOLD FROM UCSF.
CURIOUS ABOUT MODEL FOR YOUR
DIGITAL TWIN, NOTION
COMBINATORIAL FACTORS MIGHT HAVE
OVERLAPING MECHANISMS THAT MAY
NOT BE ADDITIVE.
HOW DO YOU DISENTANGLE THAT?
>>WHEN YOU BUILD A MODEL YOU
HAVE REGULATORY FEEDBACK LOOPS,
S CURVE, THIS ISN'T LIKE A
LINEAR EQUATION MODEL.
IT REPRESENTS MECHANISM.
YOU CAN GET VERY NON-LINEAR
EFFECTS, THAT'S WHAT'S
SIMULATEED.
WE CAN GO THROUGH AND WHEN WE DO
THE PERSONALIZED RECOMMENDATIONS
CAN LOOK AT THE THINGS THAT ARE
ADDITIVE OR SUPER OR SUBADDITIVE
AND CAN YOU EVALUATE THAT.
YEAH, THAT'S ALL BUILT INTO JUST
DOING IT AS A COMPLEX MODEL.
>>I'M NOT SURE HOW YOU CAN DO
THAT.
>>IF HAVE YOU AN ODE MODEL
THERE'S NO REASON TO THINK THAT
WOULD BE LINEAR.
IT'S NOT A LINEAR MODEL.
THERE WOULD BE THRESHOLD
EFFECTS.
THERE WOULD BE HYSTERESIS IN
SOME CASES.
THERE WOULD BE, YEAH, NO
EXPECTATION -- IT'S NOT A LINEAR
MODEL SO THERE'S NO EXPECTATION
IT WOULD BE ADDITIVE.
>>BUT IS IT SOMEHOW VALIDATED
EMPIRICALLY, THESE COMBINATIONS
THAT ARE NOT ADDITIVE?
>>YOU'RE RUNNING A -- YOU'RE
BUILDING A MODEL, SO YOU'RE
TAKING A THOUSAND PAPERS I
MENTIONED, YOU'RE BUILDING A
MECHANISM.
AND SO FOR THE VITAMIN D
EXAMPLE, VITAMIN D BINDS TO A
VITAMIN D RECEPTOR, HAS A ROLE
IN THE REGULATION OF
CHOLESTEROL, IN CHOLESTEROL
TRANSPORT PATHWAY.
THAT BECOMES LESS NOISY OVER
TIME.
YOU'RE SIMULATEING THE EFFECT --
IT'S COMPLICATED.
YOU'RE SUMMING ABILITY FOR
NEURONS TO MAINTAIN POSITIVE
ENERGY BALANCE, SO THAT
CHOLESTEROL TURNS OUT TO BE VERY
IMPORTANT FOR THAT.
THIS IS BECAUSE IT TURNS OUT YOU
WANT TO KEEP CONCENTRATION OF
CHOLESTEROL LOW IN ASTROCYTES TO
KEEP GENERATION OF NEURONS HIGH
IN LOW OXIDATEIVE CONDITIONS, A
LOT TO WALK THROUGH WHAT THAT
IS.
BASICALLY WHAT YOU DO BY
SOLVEING THAT EQUATION AND
SIMULATEING DECADES OF A
PERSON'S LIFE, THOSE TIMES WHEN
YOU GET THAT HIGH AMOUNT OF
VARIABILITY AND REGULATION AT A
CERTAIN PROBABILITY RATE CAUSES
ENOUGH OF A PROBLEM THAT AN
EXTRA NEURON WILL DIE.
NOT VERY OFTEN BUT IT HAPPENS A
LITTLE BIT.
AS DO YOU A SIMULATION OVER THE
COURSE OF TIME, YOU FIND THAT
EXTRA AMOUNT OF NEURONAL DEPTH
AS IT ADDS UP CHANGES THE
DIAGNOSTIC RATE AT DIFFERENT
AGES FOR ALZHEIMER'S DISEASE.
WHAT WE FIND IS THAT MECHANISM
WHEN SIMULATED QUANTITATIVELY
GIVES US BACK PLAUSIBLEY ABOUT
THE RATE THAT IS OBSERVEED IN
LITERATURE.
IT'S A COMPLEX -- IT'S A COMPLEX
STYLE MODEL THAT INCLUDES ALL OF
THOSE KIND OF THINGS IN IT.
>>I APPRECIATE THAT QUESTION
BECAUSE IT DOES TALK ABOUT THE
COMPLEXITIES OF MANY THINGS
WE'RE GOING TO TALK ABOUT TODAY.
>>WONDERFUL TO HEAR ABOUT THIS.
A COUPLE QUESTIONS.
CLEARLY YOU MENTIONED
NON-LINEAR, IT'S MICRO TO
SYSTEMS LEVEL, SO YOU NEED
EMPIRICAL DATA AT SOME POINT TO
HAVE STARTED FROM THE
(INDISCERNIBLE).
>>YEAH, YEAH.
>>INDIVIDUAL STUDIES ARE NOT
SCALING THE WHOLE DATASET.
THEY MAY BE JUST DOING THE
MOLECULAR STUFF, SOMEBODY ELSE
MIGHT BE DOING SYSTEMS LEVEL
STUFF.
HOW DO YOU SEE SOME KIND OF A
VALIDATION OF THIS PATHWAY,
DEVELOPING THIS COMPLEX --
>>OKAY, NATHAN, SHORT ANSWER.
>>THIS IS ONE OF THE THINGS I
THINK THAT DIGITAL TWIN MODELING
IS POWERFUL FOR BECAUSE THE
DISCIPLINE IS WHAT YOU'RE
TALKING ABOUT.
YOU HAVE ALL THE DATA ACROSS
DIFFERENT SCALES, ONE OF THE
OTHER BEAUTIFUL THINGS ABOUT IT,
YOU CAN TAKE DIFFERENT CLINICAL
TRIALS AND FIT THEM INTO
DIFFERENT PIECES OF THE MODEL.
SOME ARE LIKE LONG OBSERVATIONAL
TRIALS OVER MANY YEARS.
SOME ARE ACUTE INTERVENTIONS FOR
A SHORT PERIOD OF TIME.
YOU FIT THOSE IN THE SIMULATIONS
IN DIFFERENT WAYS.
YOU HAVE TO COMPARE MOLECULAR
DATA THAT YOU HAVE, AND WHEN YOU
PUT THAT TOGETHER YOU MAKE
PREDICTIONS AT THE POPULATION
LEVEL.
THAT'S ALL THE EMPIRICAL DATA WE
HAVE TO GO TO.
SO THE SLIDES I SHOWED, FOR
EXAMPLE, AT THE AGE AT WHICH ALL
THE PEOPLE WITH APOE2 22, OR 3,
3 OR 4-4 GETS ALZHEIMER'S.
WHAT YOU DO IS SEGMENT SOME OF
THAT OUT.
SOME IS USED FOR CALIBRATION,
OTHER IS USED FOR PREDICTION.
YOU HAVE TO ITERATE.
IT IS A COMPLEX PROCESS.
>>SOUNDS WE'LL HAVE SOME GOOD
DISCUSSION TODAY.
I NEED TO MOVE ON AND I NOW
WELCOME THOMAS HARTUNG FROM
JOHNS HOPKINS UNIVERSITY TO TALK
ABOUT TRANSLATIONAL PRODUCT
DEVELOPMENT IN MICROPHYSIOLOGIC
SYSTEMS.
THANK YOU.
>>THANK YOU VERY MUCH.
IN THE INTEREST OF TIME I'LL
SKIP CONFLICT OF INTEREST
ACKNOWLEDGMENT AND SO ON BECAUSE
I THINK IN 10 MINUTES CANNOT
ASSUME ANY POSSIBLE OF CONFLICT
OF INTEREST GETTING ALTERNATIVE
METHODS MOVING FORWARD.
WE'RE HERE ON A TOPIC WHERE WE
ARE VERY MUCH WITH SOCIETAL
NEEDS.
MAJORITY OF CITIZENS IS
INCREASINGLY OBJECTING TO ANIMAL
TESTING.
NUMBERS HERE 70 TO 80% IF IT IS
ABOUT COSMETIC TESTING.
THE CONSEQUENCE IN BOTH SIDES OF
THE ATLANTIC INCREASINGLY
LEGISLATION PRODUCED IS IMPETUS
TO REPLACE ANIMAL TESTING.
AT THE SAME TIME WE IDENTIFIED
NEED FOR BIOMEDICINE.
SIMPLY SAID, WE'RE NOT
70-KILOGRAM RATS.
THAT SUMMARIZES A LOT OF THE
PROBLEMS SO WE NEED HUMAN
MODELS.
A LOT OF THE WORK ON WHAT WE NOW
CALL NEW APPROACH METHODS,
ALTERNATIVE METHODS HAVE BEEN
DONE TRADITIONAL, USING 10% OF
ANIMALS ACCORDING TO EUROPEAN
DATA HAVE TO ASSUME NUMBERS ARE
NOT MUCH DIFFERENT, MUCH WORK
BEING DONE IN TOXICOLOGY.
WE HAVE DIRECT COMPARISON
BECAUSE WE WANT TO REPLACE
ANIMAL EXPERIMENT, WHILE OTHER
AREAS OF BIOMEDICINE HAVE
BROUGHT ALLS -- BROAD USE OF IN
VITRO, NATURAL GROWTH, OFTEN
DON'T REFER AS ALTERNATIVE.
IF YOU TAKE TOXICOLOGY AS A TEST
CASE, TOXICOLOGY SHOULD BE THE
BEST POSSIBLE ANIMAL
EXPERIMENTS, FOR MANY REASONS.
IT IS DONE UNDER HIGH QUALITY
STANDARDS, DONE WITH HIGH DOSES,
YOU DON'T NEED A DISEASE MODEL.
THESE ARE YOUNG HEALTHY ANIMALS
HIGHLY STANDARDIZED.
THIS IS A STUDY WE DID ON 2800
CHEMICALS, AROUND 100 REPEAT
STUDIES, 81% REPRODUCE ON
AVERAGE, IDENTIFICATION OF TOXIC
SUBSTANCES, THE PURPOSE, WAS
ACHIEVED IN 69% OF THESE.
THAT'S THE SENSITIVITY OF THESE
METHODS.
THIS ALONE SHOULD OPEN BROADLY
FOR NEW APPROACH METHODS,
DEMONSTRATING THAT WE HAVE
REPRODUCIBILITY ISSUES IN THESE
THINGS.
AND IF YOU GO FOR THE MORE
COMPLEX TOXICITIES WE DON'T HAVE
THE TRUTH BUT CAN COMPARE, FOR
EXAMPLE, MICE AND RATS, RATS AND
RABBITS.
WE SEE ONLY 60% INTERSPECIES
CORRESPONDENCE BETWEEN DIFFERENT
ANIMAL SPECIES IF YOU DO THINGS
LIKE CANCER OR REPRODUCTIVE
TOXICITY, REPEAT THOSE.
TO BE CLEAR CELL CULTURES ARE NO
BETTER BECAUSE THEY ARE MORE
ETHICAL.
WE HAVE SIMILAR PROBLEMS HERE,
ABOUT 25% OF CELL LINES USED IN
ACADEMIC RESEARCH APPEAR TO BE
MISIDENTIFIED, NOT THE RIGHT
SPECIES, NOT THE RIGHT ORGAN,
NOT THE RIGHT SEX.
10 TO 25% OF CELLS ARE
MYCOPLASMA ISSUE EFFECTED, 25%
OF GENOME LOST, OTHER PARTS HAVE
BEEN MULTIPLIED USING TUMOR CELL
LINES.
I DON'T HAVE THE TIME TO TALK
ABOUT CULTURE ARTIFACTS.
I'M HAPPY TO PRODUCE MY SLIDES,
PROVIDE MY SLIDES, I WANT TO GET
MANY THINGS ON THE RECORD HERE.
NOW IT'S NOT MOVING FORWARD.
OKAY.
WE HAVE A GAME CHANGEER IN CELL
CULTURE AT LEAST WITH STEM CELLS
AND BIOENGINEERING
MICROPHYSIOLOGIC SYSTEMS, TRYING
TO NOT JUST KEEP CELL ALIVE AND
INTERROGATE FUNCTIONALITY BUT
PRODUCING ARCHITECTURE AND
FUNCTIONALITY OF THESE SYSTEMS.
AND THIS HAS BEEN COVERED IN A
NUMBER OF OUR WORKSHOPS WHERE WE
BROUGHT TOGETHER OPINION
LEADERS, OVER THE LAST 10 YEARS,
DEMONSTRATING THIS EVOLUTION AND
OPPORTUNITIES FOR TECHNOLOGYIC
DEVELOPMENT FOR SCIENCE AND
BUSINESS.
AS A RESULT OF THE SECOND OF THE
WORKSHOPS THIS PAPER IN
"SCIENCE" WAS PUBLISHED WHICH IS
A MORE READABLE SUMMARIZED
VERSION WHERE WE SPECIFICALLY
FOCUS ON SYSTEMS FOR DRUG
DEVELOPMENT, DRIVING THIS AREA.
AS A RESULT OF THIS SECOND
WORKSHOP WE WERE ABLE TO START A
SERIES OF WORLD SUMMITS ON
MICROPHYSIOLOGIC SYSTEMS, YOU
SEE HERE SUZIE FITZPATRICK AND
DON INGBER, THE STRONG
ENGAGEMENT OF FDA IS CRITICAL
FOR PROGRESS IN MICROPHYSIOLOGIC
SYSTEMS, SO IS THE MASSIVE
SUPPORT BY THE NCATS FOR THIS
CONFERENCE SERIES.
LAST YEAR IN NEW ORLEANS 52
ORGANIZATIONS TEAMED UP WITH US
AND WE HAD 665 REGISTRANTS, 65
COMING FROM THE FDA
DEMONSTRATING ENORMOUS INTEREST.
THIS YEAR IN JUNE WE CARRIED OUT
THE SECOND OF THESE WORLD
SUMMITS.
WE HAD TO STOP ADVERTISEMENT IN
FEBRUARY BECAUSE WE REACHED OUR
CAP OF 1,300 ATTENDANCE, WAITING
LIST, DEMONSTRATING NORMAL
GROWTH TRAJECTORY OF THESE
EVENTS.
THESE ARE THE HOSTS OF LAST
YEAR, AND WE'RE GOING NOW TO
SEATTLE, WE'LL MEET MIDDLE OF
JUNE NEXT YEAR FOR THE THIRD
WORLD SUMMIT.
ONE IMPORTANT ASPECT WE CREATED
THIS SEWED, IF YOU'RE INTERESTED
TO JOIN THIS RAPIDLY GROWING
COMMUNITY PLEASE SIGN UP.
IT'S ALL ABOUT QUALITY OF THESE
SYSTEMS, IF YOU WANT TO REPLACE
CREDIBLEY TRADITIONAL TEST
METHODS.
ONE ASPECT IS WE DEVELOPED OVER
THE LAST 8 YEARS GUIDEANCE
TISSUE CULTURE PRACTICE, WE'RE
ABOUT TO PUBLISH A DRAFT WHICH
INCLUDES THESE AND THINKING HOW
TO MOVE TO VALIDATION OF THESE
SYSTEMS CRITICAL FOR REGULATORY
USE.
OUR OWN WORK LED BY LENA
SMIRNOVA AND MY TEAM AROUND
BRAIN ORGANOIDS.
I USE THIS TO ILLUSTRATE THE
BROAD VARIETY OF APPLICATIONS.
THESE ARE STANDARDIZED HUMAN 3D
SYSTEMS BASED ON INDUCED
PLURIPOTENT STEM CELLS.
THESE PERFECTLY ROUND BALLS ARE
VERY WELL STANDARDIZE, PRODUCE
1200 IN ONE SIX WELL PLATE, NOT
REALLY COSTLY EXERCISE TO
PRODUCE SUCH THINGS.
THEY CAN BE DONE BY DIFFERENT
GENETIC BACKGROUNDS, IN DISEASE
PHENOTYPES, YOU CAN INTRODUCE
CRISPR/Cas RISK GENES, REPAIR
GENES YOU'RE INTERESTED IN, ALSO
MODIFY WITH REPORTER GENES, FOR
EXAMPLE, LIKE DEVELOPMENT LINES
OF DIFFERENT CELL TYPES.
THEY INCLUDE NOT ONLY VARIOUS
NEURONS BUT ALSO GLIOCELLS,
OLIGODENDROCYTES, ASTROCYTES, IN
THE MEANTIME PROTOCOLS BRING
THEM TO PHYSIOLOGICAL ALMOST
50%, ADD GLIAL CELLS TO MAKE
IMMUNOCOMPETENT.
MODELS FOR INFECTION, PUBLISHED
IN THESE MODELS SHOWING
APPLICABLE TO A BROAD VARIETY OF
DISEASE CASES.
GENE ENVIRONMENT STUDIES ALLOWED
US TO SHOW THE FIRST RISK PAIR
FOR AUTISM, AND NOW A STUDY WITH
175,000 CHILDREN LOOKING FOR
GENE/ENVIRONMENT INTERACTION.
FUNCTIONAL ENDPOINTS ALLOW MORE
MEANINGFUL THINGS THAN TESTING
FOR CYTOTOXICITY TO CERTAIN CELL
TYPES.
IMPRESSIVELY LATELY BY TACKLEING
THE CHALLENGE OF STUDYING MEMORY
AND LEARNING IN THESE SYSTEMS,
ORGANOID INTELLIGENCE, O.I.
YOU MAY HAVE HEARD LAST NOVEMBER
ABOUT THE NEURON CULTURES AND
SIMILAR TYPE OF ARTIFICIAL
ENVIRONMENTS AT THE MOMENT BEING
USED IN OUR O.I. RESEARCH
COMMUNITY, IN ORDER TO
DEMONSTRATE NOT ONLY SHORT TERM
BUT ALSO LONG TERM LEARNING
EFFECTS CAN BE LEARN.
THIS IS A PAPER FROM A YEAR AGO
DEVELOPING AN EEG SHOWING
TECHNOLOGICAL OPPORTUNITIES
MOVING THIS TOWARDS MEANINGFUL
ENDPOINTS.
ORGANOID INTELLIGENCE WAS
PRESENTED IN FEBRUARY, WE HAD
600 PRESS HITS, THE FIRST
WORKSHOP, AND THIS IS MOVING
FORWARD NOW THE NATIONAL SCIENCE
FOUNDATION IS GOING TO ANNOUNCE
FUNDING FOR THIS.
IN GENERAL, A.I. IS AT THE
MOMENT THE PARTNER FOR MANY OF
THESE DEVELOPMENTS BECAUSE OF
ITS TREMENDOUS SYNERGY OF DATA
PRODUCTION, COMPUTING POWER, AND
THE NEW A.I. ALGORITHMS.
I DON'T NEED TO TELL YOU HOW
MUCH DISRUPTION AT THE MOMENT IS
TAKING PLACE IN OUR LIVES
BECAUSE OF A.I.
IT'S THE END OF THE WORLD AS WE
KNOW IT, AND I FEEL FINE, MY
PERSONAL SUMMARY FOR THIS.
ALREADY IN 2018 SIMPLE FORMS OF
A.I. ALLOWED US TO SHOW LARGE
NUMBERS OF PREDICTIONS COULD BE
DONE WITH PRECISION BETTER THAN
RESPECTIVE ANIMAL TEST
REPRODUCIBILITY, IN THE MEANTIME
WE'VE SHOWN THIS IS ALSO IN PART
APPLICABLE TO HUMAN DATA AND
WE'RE SUMMING UP FOR CANCER OR
REPRODUCTIVE PREDICTIONS, REALLY
AN OPPORTUNITY FOR PREDICTING
ANIMAL TESTING.
IT IS ALSO POSSIBILITY NOW TO
MOVE THESE METHODS INTO OTHER
AREAS.
FOR EXAMPLE, TO FRONT LOAD TOX,
WHY ONLY AT THE END OF PRODUCT
DEVELOPMENT, GREEN TECHNOLOGY,
AND ALEX MAARTENS WROTE THE
FIRST TEXT BOOK.
WE'VE HAD A WORKSHOP, CALLING
FOR HUMAN EXPOSE HOME PROJECT.
THIS PROJECT IS ACTUALLY
SUGGESTED TO GIVE MORE RELEVANCE
TO EXPOSURE AND EMBRACE THESE
NEW TECHNOLOGIES, A.I., MPS,
OTHERS, INTEGRATE EVIDENCES.
THE EXPOSOME IS COMPLEMENTARY
HUMAN GENOME PROJECT TO CATALOG
THIS EVEN MORE IMPACTFUL PART OF
HUMAN DISEASE ETIOLOGY.
THIS IS PART ALSO OF THE
EXPOSOMEICS APPROACHES, THIS IS
A PAPER SUMMARIZING SOME OF
THESE IDEAS, ALSO HERE AGAIN
A.I. EMERGED AS THE NATURAL
PARTNER, WHAT WE CALL EXPOSOME
INTELLIGENCE.
THE CHALLENGE IS FROM MY POINT
OF VIEW AT THE MOMENT FIRST OF
ALL TO COMBINE THESE VARIOUS NEW
METHODOLOGIES, DATA INTEGRATION,
SYSTEMATIC REVIEW, RISK
ASSESSMENT, STRATEGY USING
DIFFERENT APPROACHES.
AGAIN A PAPER HERE ON INTEGRATED
STRATEGY, IN VITRO, IN VITRO, IN
SILICO COMBINED I CALL IT.
AN INTERESTING ASPECT IS
EVIDENCE-BASED MEDICINE IS
GUIDING US TOWARDS
EVIDENCE-BASED APPROACHES ALSO
IN THE PRE-CLINICAL SCIENCES.
THE EVIDENCE-BASED TOXICOLOGY
MOVEMENT IS ONE WE HAVE BEEN
PARTICULARLY PUSHING OVER THE
LAST 20 YEARS ALMOST.
AND YOU SEE HERE THE ENORMOUS
UPTICK THE SYSTEM REVIEWS WHICH
WE OBSERVED WHILE PROMOTING
THESE TYPE OF EFFECTS.
SO, IN SHORT, SUMMARIZING UP, I
THINK OUR TRADITIONAL WAY OF
DOING BIOMEDICAL RESEARCH WHICH
IS BASED ON MOVING THROUGH
HYPOTHESIS TO CAUSATION AND
PROOF AT THE MOMENT IS BEING
COMPLEMENTED BY TWO VERY
IMPORTANT APPROACHES.
ONE IS EVIDENCE-BASED
APPROACHES, WHICH IS THE
IDENTIFYING THE MOST RELEVANT
STUDIES AND DATA, THE BEST
HUMANS CAN DO.
AND MACHINE LEARNING, WHICH IS
TRYING TO GO THROUGH BIG DATA
AND COMING TO EVIDENCE IN A
DIFFERENT WAY OF EVIDENCE
INTEGRATION.
WITH THIS, I WOULD LIKE TO
CLOSE.
I SHOWED YOU A.I.,
MICROPHYSIOLOGICAL SYSTEMS,
GREEN TECHNOLOGY, INTEGRATED
TESTING, EVIDENCE-BASED
APPROACHES AS EMERGING
TECHNOLOGYS TO SUBSTITUTE FOR
ANIMAL TESTING.
THE SMART WAY FORWARD WILL BE
OPEN ACCESS PUBLISHING, FAIR
ACCESSIBLE DATA, EXPLAINABLE
A.I., MECHANISTIC VALIDATION AND
THE HUMAN EXPOSOME PROJECT.
THANKS A LOT.
[APPLAUSE]
>>WE'RE GOING TO HOLD QUESTIONS
FOR DR. HARTUNG TILL THE BREAK
SO THAT WE CAN HEAR FROM OUR
OTHER SPEAKERS AND SPEND SOME
TIME AS A PANEL DISCUSSING SOME
OF OUR LARGE QUESTIONS.
I'D LIKE TO INTRODUCE NICOLE
KLEINSTREUER, FROM THE U.S. NIH,
WHO IS GOING TO TALK ABOUT THE
REGULATORY PROCESSES, EVALUATION
OF ALTERNATIVE TOXICOLOGYIC
METHODS.
NICOLE COMES VIRTUALLY TODAY.
WELCOME, NICOLE.
>>THANK YOU, NANCY.
THANK YOU, LYRIC AND HOWARD AND
ALL OF THE WORK GROUP MEMBERS
FOR THE OPPORTUNITY.
I'M VERY SAD NOT TO BE THERE
WITH YOU IN PERSON.
BUT I'M SURE YOU ARE ALL NOT SAD
TO SHARE THE COVID THAT I
CURRENTLY HAVE RIGHT NOW.
SO I'M GOING TO JUMP RIGHT INTO
THIS.
SO, I THINK MANY OF YOU MIGHT BE
FAMILIAR WITH NICEATM AND
ICCVAM, HOW WE CAN BRIDGE
EFFORTS WE'VE PUT FORTH IN
TOXICOLOGY TO THE SPACE AND
BIOMEDICAL RESEARCH.
WE'RE THE U.S. FEDERAL RESOURCE
FOR ALTERNATIVES TO ANIMAL
TESTING, NICEATM HOUSED WITHIN
NIEHS PROVIDES SCIENTIFIC AND
OPERATIONAL SUPPORT TO A
CONGRESSIONALLY MANDATED
COMMITTEE OF 17 U.S. FEDERAL
AGENCIES, YOU CAN SEE THEM ON
THE SCREEN HERE.
EVENLY DIVIDED BETWEEN
REGULATORY AND RESEARCH
AGENCIES.
THESE ARE ALL AGENCIES THAT
REQUIRE OR CONSIDER CHEMICAL
SAFETY DATA, ARE INTERESTED IN
MOVEING TO HUMAN RELEVANT
TESTING APPROACHES.
AND WE DEVELOP DATASETS, MODELS,
NAMs THAT REALLY FOLLOW THIS
CYCLICAL PROCESS THAT YOU SEE ON
THE SLIDE.
ITERATIVE APPROACH, ALONG THIS
CONTINUUM OF USING BIG DATA,
PREDICTIVE MODELS WITH THE GOAL
OF GENERATING HUMAN RELEVANT
INSIGHTS INTO DISEASE PROCESSS
THAT SUPPORT EFFECTIVE
ENVIRONMENTAL HEALTH RESEARCH
AND PROTECT SENSITIVE AND
SUSCEPTIBLE POPULATIONS.
I'M GOING TO TALK AT A HIGH
LEVEL ABOUT THE CONCEPTS OF
VALIDATION AND HOW THEY ARE
EVOLVING.
FIVE YEARS AGO, WE PUBLISHED A
STRATEGIC ROADMAP THAT
REPRESENTS A CONSENSUS ACROSS
THESE 17 AGENCIES, AND DESCRIBES
THREE FUNDAMENTAL PROCESSES THAT
ARE REALLY CRITICAL TO ENSURING
NAMs ARE BEING DEVELOPED THAT
ARE FIRST TAILORED TO MEET
REGULATORY NEEDS, SO HELPING END
USERS GUIDE DEVELOPMENT OF
NAMs, THAT USE EFFICIENT AND
FLEXIBLE APPROACHES TO ESTABLISH
CONFIDENCE IN NEW METHODS, TO
ENSURE ULTIMATELY THESE NEW
METHODS WILL BE ADOPTED AND PUT
IN USE BY REGULATED INDUSTRY AND
FEDERAL AGENCIES.
SO, THE ROADMAP IS AVAILABLE
ONLINE.
IT'S ALSO PAIRED WITH
IMPLEMENTATION PLANS THAT ARE
TRACKED AND PUBLICLY REPORTED.
I ENCOURAGE YOU TO LOOK AT THOSE
DOCUMENTS.
ONE THING THAT BECAME APPARENT
DURING THE DEVELOPMENT OF THE
ROADMAP IS THERE'S REALLY NO
SUCH THING AS A
ONE-SIZE-FITS-ALL APPROACH TO
VALIDATION.
HERE IS ONE EXAMPLE OF TWO
DIFFERENT ICCVAM REGULATORY
AGENCIES, THE BIGGEST PLAYERS IN
THE REGULATORY SPACE, FDA AND
EPA, AND HOW MANY DIFFERENT
CENTERS AND OFFICES THERE ARE IN
EACH OF THOSE AGENCIES.
YOU HAVE EVERYTHING RANGING FROM
SMALL MOLECULE DRUGS TO DEVICES
TO FOOD ADDITIVES TO
ENVIRONMENTAL CHEMICALS LIKE
INDUSTRIAL CHEMICALS OR
PESTICIDES, AND EACH OF THESE
OFFICES AND CENTERS HAVE THEIR
OWN DEDICATED NEEDS AND
REGULATORY DECISION FRAMEWORKS
THAT NEED TO BE CONSIDERED WHEN
DEVELOPING NEW APPROACH
METHODOLOGIES TO ASSESS THE
CHEMISTRIES THEY CARE ABOUT.
AS A FOLLOW-UP TO THE U.S.
STRATEGIC ROADMAP, ICCVAM HAS
BEEN WORKING HARD OVER THE LAST
COUPLE YEARS ON A NEW REPORT,
VALIDATION, QUALIFY INDICATION
AND LEAGUEER TO ACCEPTANCE,
CURRENTLY OPEN FOR PUBLIC
COMMENT.
YOU CAN ACCESS THROUGH THE QR
CODE.
HERE I'M SUMMARIZING SOME OF THE
KEY CONCEPTS TO CONSIDER DURING
THE DEVELOPMENT AND
IMPLEMENTATION OF FLEXIBLE FIT
FOR PURPOSE VALIDATION STRATEGY
FOR NAMs.
THOSE COVER THINGS LIKE THE
CONTEXT OF USE, SO WHAT
REGULATORY STATUTE DATA ARE
INTENDED TO COMPLY WITH, WHETHER
IT'S MEANT TO BE USED FOR
SCREENING AND PRIORITIZATION OR
HAZARD IDENTIFICATION OR
QUANTITATIVE RISK ASSESSMENT.
BIOLOGICAL RELEVANCE, POSSIBLY
THE MOST IMPORTANT OF THE KEY
CONCEPTS, MAKING SURE THAT THE
TEST SYSTEM THAT'S BEING
DEVELOPED IS REALLY REPLICATEING
PHYSIOLOGY, BIOLOGY INTENDED,
HAS HUMAN RELEVANCE.
THE TECHNICAL CHARACTERIZEATION
OF METHODS, WE'LL HEAR MORE FROM
ELIJAH PETERSON.
DATA INTEGRITY AND INFORMATION
TRANSPARENCY, AND INDEPENDENT
REVIEW.
I'M GOING TO FOCUS ON IN
PARTICULAR THIS CONCEPT OF
BIOLOGICAL AND MECHANISTIC
RELEVANCE AND HOW THAT REALLY IS
CRUCIAL TO SUPPORT REGULATORY
TRANSLATION AND APPLICATION.
THESE CONCEPTS MAY SEEM
INTUITIVE BUT REPRESENT A
FUNDAMENTAL SHIFT HOW WE'VE BEEN
THINKING ABOUT VALIDATION AND
ESTABLISHING SCIENTIFIC
CONFIDENCE IN NAMs.
SO WE'RE MOVING BEYOND AN
EXCLUSIVE RELYANCE ON COMPARING
TO EXISTING HISTORICAL REFERENCE
ANIMAL DATA, AT BEST A SURROGATE
FOR HUMAN RESPONSE, OPENING THE
DOOR TO THE POSSIBILITY THAT
METHODS THAT ARE BASED ON HUMAN
BIOLOGY MAY NOT ALWAYS AGREE
WITH THE ANIMAL TEST BECAUSE
THEY ARE IN FACT DOING A BETTER
JOB OF REPRESENTING THE HUMAN
RESPONSE.
AND SO IN THE VALIDATION WORK
GROUP REPORT WE HAVE MULTIPLE
EXAMPLES OF HOW USING HUMAN
BIOLOGICAL AND MECHANISTIC
RELEVANCE AS THE ANCHOR HAS BEEN
SUCCESSFUL AND THESE COVER
ENDOCRINE DISRUPTION,
DEVELOPMENTAL NEUROTOX,
RESPIRATORY IRRITATION.
I'M GOING TO FOCUS ON SKIN
SENSITIZEATION AS THE EXEMPLAR
OF HUMAN BIOLOGY-BASED STRATEGY
THAT GAINED ACCEPTANCE.
SO, THE ORGANIZATION FOR
ECONOMIC COOPERATION AND
DEVELOPMENT PUBLISHED GUIDEANCE
DOCUMENTS ON ADVERSE OUTCOME
FRAMEWORK, AN ORGANIZATIONAL
STRUCTURE TO BREAK DOWN HOW
EXOGENOUS INFLUENCES LIKE
CHEMICAL EXPOSURE INTERACT ON
MOLECULAR LEVEL RESULTING IN
CASCADE, RESULTING IN ADVERSITY
ON A POPULATION LEVEL.
THIS IS A HELPFUL FRAMEWORK TO
DEVELOP TESTING STRATEGY TO
PROVIDE COVERAGE AS IN THE CASE
OF SKIN SENSITIZEATION, SO HERE
YOU HAVE THE AOP FOR SKIN
SENSITIZEATION STARTING WITH THE
FIRST MOLECULAR INITIATING EVENT
BINDING TO SKIN PROTEINS,
ACTIVATING INFLAMMATORY
PROCESSES, KERATINOCYTES, T CELL
PROLIFERATION, ULTIMATELY THIS
ADVERSE OUTCOME OF INFLAMMATION.
AND A NUMBER OF DIFFERENT TEST
METHODS, MANY APPEAR IN OECD
TEST GUIDELINES MAPPED TO KEY
EVENTS RANGEING FROM IN SILICO
COMPUTATIONAL PREDICTIONS TO IN
CHEMICO CELL FREE REACTIVITY
ASSAYS TO IN VITRO CELL-BASED
METHODS TO IN VIVO TESTS THAT
MEASURE THE APICAL OR SUBAPICAL
ENDPOINTS.
WHAT'S UNDERSTOOD HERE IS THAT
THE INDIVIDUAL NAMs THAT
MEASURE EACH OF THOSE KEY EVENTS
MAY NOT BE ABLE TO BE USED ON
THEIR OWN TO DETERMINE SKIN
SENSITIZEATION HAZARD, BUT IF
YOU COMBINE THEM IN DEFINED
APPROACHES, THEN YOU ENSURE
SUFFICIENT COVERAGE OF BIOLOGY
AND MECHANISM THAT YOU CAN
ACTUALLY RELIABLY PREDICT THAT
ADVERSE OUTCOME.
SO TO MAKE A LONG STORY VERY
SHORT, NUMBER OF YEARS AND
DECADES ESTABLISHED CONFIDENCE
IN THESE DEFINED APPROACHS THAT
COMBINE THESE HUMAN
BIOLOGY-BASED TEST METHODS IN
VARIOUS COMBINATIONS, AND IN
THIS CASE WE HAD HUMAN REFERENCE
DATA TO COMPARE TO.
AND SO THIS IS A REALLY LANDMARK
INTERNATIONALLY HARMONIZED TEST
GUIDELINE ADOPTED WHO YEARS AGO
THAT SHOWS WHEN YOU HAVE TESTING
STRATEGY THAT COMBINE THESE IN
VITRO AND IN SILICO AND IN
CHEMICO METHODS, YOU OUTPERFORM
THE ANIMAL TEST WHEN COMPARED TO
HUMAN REFERENCE DATA.
AND WHILE THERE ARE MULTIPLE
METHODS AVAILABLE THAT COVER
EACH KEY EVENT MANY REQUIRE
SPECIALIZEED INSTRUMENTATION AND
MIGHT BE LOWER THROUGHPUT SO
WE'RE ALWAYS TRYING TO INCREASE
ACCESSIBILITY, ENCOURAGE BROADER
UPTAKE.
ONE EXAMPLE OF HOW WE'RE
APPLYING KEY CONCEPTS IN THE
VALIDATION WORK GROUP REPORT IS
NICEATM PARTNERED WITH THE FDA
AND CPSC AND NIST TO APPLY THESE
HIGHER THROUGHPUT PROTOCOLS SO
THIS IS AGAIN AN ASSAY THAT
MEASURES PROTEIN REACTIVITY,
INITIAL EVENT, ALSO ENDPOINT
APPLICABLE TO IMMUNOLOGICAL
CASCADES, THE RESULT OF THE
VALIDATION STUDY WILL BE
SUBMITTED TO THE OECD LATER THIS
YEAR.
IN NAM APPLICATION IN REGULATORY
DECISION MAKING IT'S FAIR TO
SARASOTA THE U.S. IS LEAD --
FAIR TO SAY THE U.S. IS LEADING
THE CHARGE GOING FURTHER THAN
OECD GUIDELINES WORKING TO APPLY
ARTIFICIAL INTELLIGENCE AND
MACHINE LEARNING-BASED MODELS
LIKE ARTIFICIAL NEURAL NETWORKS
TO INTEGRATE NAM DATA AND DERIVE
POINTS OF DEPARTURE FOR RISK
ASSESSMENT, THIS IS RECENT WHERE
THE EPA NOTED IN VITRO AND IN
CHEMICO STUDIES PROVIDE
INFORMATION THAT'S MORE
RELIABLE, REPRODUCEIBLE, HUMAN
RELEVANT THAN EXISTING ANIMAL
TESTS, THIS IS THE FIRST USE OF
SUCH INFORMATION IN REGULATORY
RISK ASSESSMENT.
AND OUR GROUP IS TAKING THIS A
STEP FURTHER, APPLYING BAYESIAN
PROBABLYABLEISTIC MODELS TO
CONSIDER VARIABILITY ACROSS
POPULATIONS, USED TO FACILITATE
DECISIONS ON CONSUMER SAFETY
USING BAYESIAN STATISTICS TO
INFER THIS HUMAN RELEVANT METRIC
OF POTENCY ACROSS A POPULATION.
WE'VE PARTNERED WITH UNILEVER TO
EXPAND THIS DATABASE AND MAKE
THIS MODEL OPEN SOURCE.
THIS IS ALSO ON THE OECD WORK
PLAN FOR INCLUSION IN THE
DEFINED APPROACH GUIDELINES.
I'LL FINISH AND DRAW YOUR
ATTENTION TO A REPORT THAT LOOKS
AT USE OF ANIMALS ACROSS BOTH
BASIC RESEARCH AND REGULATORY
APPLICATIONS.
I THINK IT'S CRITICAL THAT THE
ACD WORKING GROUP TURNED THE
FOCUS TO NAMs AND BIOMEDICAL
RESEARCH WHERE THE VAST MAJORITY
ARE USED BUT THERE'S A FALSE
DISTINCTION BETWEEN TOXICOLOGY
AND BIOMEDICAL RESEARCH, AND
THERE'S SO MUCH THESE FIELDS CAN
LEARN FROM EACH OTHER AND BY
BRIDGING OUR APPROACHES BECAUSE
ULTIMATELY EFFECTIVE REGULATORY
DECISION MAKING ACTUALLY RELIES
UPON EFFECTIVE RESEARCH TO
DEVELOP METHODS THAT CAN ANSWER
CRITICAL QUESTIONS ABOUT HUMAN
HEALTH AND THE ENVIRONMENT.
AND NAMs ARE FUNDAMENTAL TO
THIS UNDERSTANDING, SO I'M VERY
EXCITED TO SEE ENGAGEMENT OF
BIOMEDICAL RESEARCH COMMUNITY SO
WE CAN CONTINUE TO DEVELOP
SUCCESSFUL NAMs ULTIMATELY
TRANSLATED INTO REGULATORY USE.
I'LL STOP THERE AND THANK MY
AMAZING GROUP AND POINT YOU TO
SEVERAL OTHER RESOURCES ONLINE.
>>THANK YOU, NICOLE, VERY MUCH.
[APPLAUSE]
AND WE'LL GIVE YOU A FEW MINUTES
OFF AND WE'LL COME BACK TO YOU
FOR THE PANEL.
OKAY.
NEXT WE'LL HEAR FROM CHIRAG
PATEL, WHO FOCUSS ON
INTER-INDIVIDUAL DIFFERENCES
THROUGH INTEGRATED DATA SOURCES
THAT CAPTURE CLINICAL
EXPERIENCE.
>>THANK YOU FOR HAVING ME.
IT'S A PLEASURE AND HONOR TO BE
HERE AMONGST SUCH A FANTASTIC
PANEL AND TO LEARN ABOUT HOW TO
INTEGRATE NAMs INTO SOMETHING
YOU ALREADY SAW THIS MORNING.
FOR THOSE HERE, AS YOU WALKED UP
THE STAIRS TO WILSON HALL
THERE'S AN ADVERTISEMENT, IF YOU
WILL, FOR THE "ALL OF US" STUDY
WHICH IS ALLOWING US TO ACCRUE
DATA AT AN UNPRECEDENTED SCALE
FOR US TO DO THESE SORT OF
EXPERIMENTS.
MY QUESTION TODAY IS HOW DO WE
INTEGRATE BIOBANK SAMPLES INTO
THE WORLD OF NAMs?
FOR U.S., INFORMATICS, IT'S BEEN
POSSIBLE TO ESTABLISH NEW
EXPOSURES.
EXAMPLES FROM LIFE LINES IN THE
NETHERLANDS, U.K. BIOBANK
UNPRECEDENTED OUTPUT, AND NOW
THE "ALL OF US" STUDIES.
THEY ARE OBSERVATIONAL,
NON-RANDOMIZED, CONVENIENT,
OFTEN PEOPLE SELF-SELECT FOR
THESE STUDIES, AND THEY ARE
SINGLE COHORT.
HOW DO WE USE DATA ACROSS THE
DIFFERENT MODALITYS TO GET
CAUSEALITY?
THE SPEAKERS, WE CAN JUMP IN AND
START TO LEVERAGE THESE DATA AT
SCALE TO DO DISCOVERY.
WE HAVE BIOSAMPLES TO DO
MEASUREMENTS, AND WHERE
INDIVIDUALS LIVE TO GET ANOTHER
SENSE OF DIGITAL BIOMARKER OF
THEIR EXPOSURES.
I'LL TALK ABOUT LEARNINGS FROM
SOME PAPERS THAT WE'VE
PUBLISHED, BUT FIRST TO IDENTIFY
GENETIC BASIC OF VARIATION THE
BIOBANK HAS BEEN HUGE ADVANCE
FOR US.
IN A FEW YEARS SINCE THE BIOBANK
ERA STARTED, ALMOST DOUBLING OF
NUMBER OF PUBLICATIONS, THESE
ARE ESSENTIALLY A WELCOME
ADDITION TO THE OLD CANDIDATE
GENE ERA OF THE PAST, SCALED FOR
DISCOVERY, REPRODUCEIBLE,
NEGLIGIBLE FOUNDING, ZERO
REVERSE CAUSEALITY.
THE CHALLENGES TO ADDRESS NOW
HOW TO ADDRESS VARIATION COMING
FROM MULTIPLE ANCESTRY GROUPS,
MULTIPLE RACE GROUPS, AND HOW TO
USE THIS IN A TRANSLATIONAL
CAPACITY TO GET TO PREDICTION.
SO FAR IN MY OPINION THERE'S
LITTLE PREDICTION CAPABILITY.
SO WE NEED TO START INTEGRATING
DATA ACROSS THE GENOME AND
EXPOSOME WHICH IS THE SYSTEMATIC
EXPOSURES ACROSS DOMAINS AND
MODALITYS WHICH DR. HARTUNG
TALKED ABOUT.
HERE IS AN ESSAY TO SUGGEST WE
NEED A WAY OF TAXONOMIZING
EXPOSURES, ESSENTIALLY TO PUT
THESE TOGETHER IN A SINGLE
DATASET TO START ANALYZING
SYSTEMATICALLY AND
CONCEPTUALIZEING HOW EACH FACTOR
PLAYS A ROLE.
AND IF THE ENVIRONMENT OR
EXPOSOME IS CAUSAL WE NEED WAYS
OF MEASUREING OUTPUT, CONNECTING
THAT TO CLINICAL OUTCOMES.
EXPOSOME IS CAUSAL THEY MUST
INDUCE BIOLOGICAL RESPONSE, WE
MUST BE ABLE TO MEASURE, MY
HYPOTHESIS WE COULD DO THIS WITH
BIOBANK SAMPLES.
CHANGES IN OMICS RESPONSE AS WAS
IN THIS PAPER.
THE KEY QUESTION IN DOING
EXPOSOMEIC RESEARCH IS HOW MUCH
VARIATION CAN WE ATTRIBUTE TO
EXPOSOME IN DISEASE, A SENSE OF
POWER AND SPACE WE NEED TO
EXPLORE.
IF YOU COULD THINK OF PHENOTYPIC
VARIATION AS A PIE, VARIATION
DUE TO GENETICS, SHARED
ENVIRONMENT, INTERACTION, WHAT
EXPLAINS WHAT?
BUILDING THE PREDICTIVE MODEL
AND SCALING UP TO DO EXPOSOME
WIDE ASSOCIATION STUDIES, WHAT
FACTORINGS ARE ASSOCIATED, HOW
DO THEY ADD UP IN AGGREGATE AND
FIGURE OUT THE RIGHT MODEL.
FOR EXAMPLE, IN GENETICS WE HAVE
THE GENOTYPE AS MODALITY BY
WHICH WE'RE TESTING, WHAT IS
EXPOSOME ARCHITECTURE, MULTIPLE
FACTORS OF SMALL EFFECTS OR FEW
FACTORS WITH LARGE EFFECTS SUCH
AS SMOKING OR COPD.
WE PUT TOGETHER A LARGE TWINS
DATASET USING SAMPLES, IN NATURE
GENETICS, ESTIMATED SHARED
EXPOSE UP ON, NON-SHARED
EXPOSOME.
WE CONCLUDED THERE'S A LOT OF
VARIATION YET TO BE EXPLAINED,
THAT CANNOT BE EXPLAINED BY
GENETICS OR SHARED ENVIRONMENT
SO WHERE IS THIS VARIATION?
THIS IS WHERE THE EXPOSOME-WIDE
ASSOCIATION IDEA COULD COME INTO
PLAY.
THE DIFFICULTY IN BIOBANK
SAMPLES, THERE'S A HUGE
OPPORTUNITY PULMONARY --
OPPORTUNITY BUT WE NEED TO
INTEGRATE ACROSS MODALITYS,
GEOSPATIAL MARKERS, HOW TO
MEASURE INFORMATION SUCH AS AIR
POLLUTION, HAVE TO DEAL WITH
SELF-REPORTED QUESTIONNAIRES AND
BEHAVIORAL TYPES OF INFORMATION
SUCH AS RECALLS, UNTARGETED MASS
SPECTROMETRY, UNDERSTANDING
BLACK MATTER IF YOU WILL AND
FIGURING OUT HOW TO ANNOTATE
THOSE MARKERS COMING OUT OF
THOSE MODALITYS, THE NEXT STEP
FOR US, AND SENSOR-BASED
BEHAVIORAL INFORMATION.
THINK ABOUT THIS INFORMATION
THAT INFLUENCES THE EXPOSOME HOW
TO WE PUT THIS TOGETHER TO
UNDERSTAND THE ROLE OF THE
EXPOSOME WRIT LARGE ON
PHENOTYPE.
HERE IS A PAPER WE PUBLISHED IN
JAMA A LONG TIME AGO SHOWING
EXTENT OF COMPLEXITY DEALING
WITH MULTIPLE EXPOSURES.
IF YOU TAKE, FOR EXAMPLE,
METABOLITE OF NICOTINE, ASK THE
QUESTION ACROSS A REPRESENTED
SAMPLE WHAT IS CORRELATED,
ACROSS THE BOARD OTHER
POLLUTANTS, STRONGLY CORRELATED.
YOU CAN DO THIS EXERCISE ACROSS
EXPOSURES AND SEE UNLIKE
GENETICS WORLD YOU HAVE DENSE
CORRELATION TO DEAL WITH WHEN
ANALYZING WRIT LARGE.
IF YOU LOOK AT LITERATURE FOR
INDIVIDUALS WHO HAVE DONE
DOMAIN-WIDE OR EXPOSOME-WIDE
ASSOCIATION STUDIES, UNLIKE IN
GENETICS WORLD YOU HAVE DIVERSE
ASSOCIATION SIZE, NATHAN WAS
GETTING TO THAT EARLIER TODAY,
IN CLINICAL PHENOTYPE.
YOU HAVE EVERYTHING FROM ODDS
RATIOS THAT RANGE FROM .9 TO
1.3, FOR EXAMPLE, FOR DEPTH BUT
ON THE OTHER SIDE EXPLAINING
LIPID LEVELS OR CHOLESTEROL, DUE
TO HIGH RISK FOR CARDIOVASCULAR
DISEASE, R SQUARED, CHIPPING
AWAY.
SO WAYS TO DEAL WITH CORRELATION
AND HETEROGENEITY OF THESE
EXPOSURES, WE'VE TRIED TO
DEVELOP ALL EXPOSURE RISK
SCORES, SO WE TOOK TOGETHER THE
BEHAVIORS THAT COULD BE
CORRELATED WITH EXPOSURES, PUT
THEM TOGETHER IN THE SCORE,
ATTEMPTED TO VALIDATE THEM IN
THE U.K. BIOBANK.
OTHERS VALIDATED OTHER COHORTS
SUCH AS THE PEGS COHORT, AN
NIH-FUNDED COHORT.
THE KEY TAKEAWAY IS EXPOSURES
PLAY A ROLE, IT'S COMPLEMENTARY
TO CLINICAL RISK SCORE, THE WAY
WE NEED TO THINK ABOUT
VALIDATEING THESE SCORES.
IT'S NOT IS IT BETTER, WHAT
WE'RE CAPTIVATEED BY ARTIFICIAL
INTELLIGENCE, BUT DOES IT ADD TO
ANYTHING WHEN WE'RE TALKING
ABOUT A DECISION TO BE MADE AT
THE BEDSIDE.
TO DO THIS WE USED THE
CLASSIFICATION INDEX, ASKING THE
QUESTION IF YOU HAVE A CLINICAL
RISK SCORE, FOR EXAMPLE, FOR
DIABETES, LOOKING AT FAMILY
HISTORY, LIPIDS, GLUCOSE, BLOOD
PRESSURE, DO THESE NEW MEASURES
SUCH AS POLYGENIC RISK SCORE,
EXPOSURE SCORE WHICH SEEMS TO BE
VALID IN RECLASSIFYING
INDIVIDUALS.
IF YOU'RE ABLE TO DEPLOY THIS
EARLY SUCH AS, FOR EXAMPLE,
DIGITAL TOOL, HOW DO YOU GET
PEOPLE TO COME TO THE DOCTOR TO
GET DIAGNOSED?
SO THAT'S ONE POTENTIAL UTILITY
FOR POPULATION SCREENING IS TRY
TO GET TO UNDIAGNOSED CASES.
SO WHAT WE'RE DEALING WITH THE
ENVIRONMENT, HUGE MODALITY OF
THE EXPOSOME, THINGS THAT NEED
TO BE DONE IN TERMS OF DECISION
MAKING AT THE FEDERAL OR PUBLIC
POLICY LEVEL, EVEN THE
INDIVIDUAL LEVEL, WE'RE USING
THIS BRADFORD HILL CRITERION, IS
IT RELEVANT IN THIS ERA, AND WE
GET A SENSE THAT SOME OF THESE
NEED TO BE REFRESHED, STRENGTH
OF ASSOCIATION, MANY EXPOSURES I
SAY WITH THE EXEMPTION OF THINGS
LIKE SMOKING OR CERTAIN
LIFESTYLES HELD IN AGGREGATE
HAVE SMALL RISK.
HAVE YOU HETEROGENEITY, SOME
LARGE, SOME SMALL.
CONSISTENCY OF ASSOCIATION WE
COULD TRIANGULATE TO ASSESS
CONSISTENCY.
AFTER THAT, IT'S REALLY OUT
THERE IN TERMS OF WHETHER
BRADFORD HILL OR RELEVANT OR WE
NEED TO IMPROVE.
FOR EXAMPLE, BIOLOGICAL
GRADIENT, PLAUSIBILITY.
MUNAFOO AND SMITH, AS THE PANELS
WERE TALKING EARLY, TRYING TO
MOVE BEYOND REPRODUCIBILITY BUT
ALSO THINKING ABOUT TESTING
UNDER DIFFERENT ASSUMPTION.
SO WHEN LOOKING AT SMOKING
CAUSING AN OUTCOME, YOU MIGHT
LOOK AT THIS CORRELATION,
EPIDEMIOLOGIC STUDY, ALSO LOOK
AT INSTRUMENTAL VARIABLE
ANALYSES YOU COULD BE DOING IN
ECONOMICS BASED STUDY LIKE
SMOKING TAX ACE.
TO-- TAXATION.
USING GENETIC INTER-INDIVIDUAL
VARIATION AS A RANDOMIZED
TRIAL.
YOU TAKE GENOTYPES, RANDOMIZED
AT BIRTH, AND LOOK AT THOSE AS
YOUR INSTRUMENT BY WHICH YOU
LOOK AT EXPOSURE AND CAUSEALITY,
GENE-ENVIRONMENT, TAKE GENETIC
VARIANTS AS PROXY FOR EXPOSURES,
CORRELATE WITH OUTCOMES.
IN CONCLUSION, GUIDING
QUESTIONS, WE NEED REAL WORLD
SURVEILLANCE
WHAT ARE THE IMPORTANT EXPOSURES
WE SHOULD BE PAYING ATTENTION
TO AND HOW DO THEY CORRELATE?
THAT GUIDES OUR QUESTIONS TO ASK
NEXT.
ALSO WITH THESE BIOBANK SCALE
ANALYSES COMES WITH BUGS AND
FEATURES, I HOPE I ILLUSTRATED,
WITH HIGH-THROUGHPUT
EPIDEMIOLOGY OUR CURRENT
HUERISTICS ARE APPLICABLE?
CAN WE MAKE A STATEMENT ABOUT
BIOLOGY INFLUENCED BY EXPOSURES
USEING NEW OMICS TYPE OF
READOUTS?
AND ARE THESE MULTIPLE OMIC
READOUTS RELEVANT.
I THANK MY COLLABORATORS AND MY
GROUP AND OUR FUNDING.
HAPPY TO TAKE QUESTIONS WITH THE
ESTEEMED PANEL.
THANK YOU.
[APPLAUSE]
>>THANK YOU ALL VERY MUCH.
THAT'S REALLY QUITE A NICE
OVERVIEW AS TO WHERE WE ARE AND
WHAT TOOLS ARE AVAILABLE TO US
TO START THINKING ABOUT.
SO LET ME START OUT.
WE'VE GOT ABOUT 15 MINUTES TO
HAVE JUST -- JUST DISCUSS THINGS
AS A PANEL.
LET ME ASK NICOLE, ARE THERE
LESSONS LEARNED IN TERMS OF
TECHNOLOGICAL READINESS, CHOICE
OF HYPOTHESIS TO APPLY TO THE
SYSTEM THAT WOULD BE SCALEABLE
TO OTHER NAMs EFFORTS FOCUSED
ON SUSCEPTIBILITY?
>>I SHORT ANSWER IS YES.
THERE'S A NUMBER OF LESSONS
LEARNED PARTICULARLY STARTING
WITH HUMAN BIOLOGY BASED
FRAMEWORK TO DEVELOPING NAMs
THAT COVER THE KEY ASPECTS OF
MOLECULAR CELLULAR AND TISSUE
LEVEL EVENTS THAT CONTRIBUTE TO
ADVERSE OUTCOMES.
AND I THINK THERE'S A TREMENDOUS
AMOUNT OF POTENTIAL IN THE FIELD
OF NAMs TO REPRESENT HUMAN
VARIABILITY AND SUSCEPTIBILITY
ACROSS POPULATIONS IN A WAY THAT
ISN'T SCALEABLE OR FEASIBLE TO
DO WITH IN VIVO TRADITIONAL
MAMMALIAN MODELS.
I THINK THERE'S A LOT OF
EXCITING WORK THAT'S ONGOING,
USING THINGS LIKE
PATIENT-DERIVED INDUCED
PLURIPOTENT STEM CELL MODELS,
MICROPHYSIOLOGIC SYSTEMS,
INTEGRATING TESTING STRATEGY.
SO THERE'S A LOT OF WORK
UNDERWAY, THERE'S A LOT OF WORK
THAT NEEDS TO BE DONE.
THIS REPRESENTS A REAL
OPPORTUNITY FOR NIH TO STEP IN
AND REALLY PROVIDE AN INFLUX OF
RESOURCE IN THIS SPACE TO
SUPPORT FURTHER DEVELOPMENT OF
THOSE APPROACHES.
>>OTHER PANELISTS, WHAT DO YOU
THINK?
LET'S SEE, GO TO THE MIDDLE ONE
I THINK.
>>OKAY.
NICOLE SAID IT.
THERE'S NO WAY OF REPLICATEING
HUMAN DIVERSITY IN ANIMALS, BUT
THERE'S TONS OF OPPORTUNITIES
WITH PATIENT-DERIVED GENETIC
BACKGROUND TO STEM CELLS iPSC,
THAT'S THE WAY FORWARD, VERY FEW
OTHER OPPORTUNITIES.
>>YEAH, THAT'S AN EXCITING
PIECE OF THE FIELD.
CHIRAG, HOW WOULD YOU START THIS
PROCESS?
WHAT DO YOU THINK?
>>I THINK THAT AS I WAS SAYING
EARLIER THAT HAVING A WAY OF
ASSESSING THESE INDIVIDUALS AT
BIOBANK SCALE, THAT'S THE FIRST
STEP.
THEN ALSO HAVING STEPS IN PLACE
TO POTENTIALLY RECALL
PARTICIPANTS BY WHICH WE CAN DO
THESE EXPERIMENTS THAT WE'RE
TALKING ABOUT.
SO ALL OF A SUDDEN WE HAVE ALL
THIS INFORMATION THAT WE'VE
COLLECTED ON PARTICIPANTS ON THE
POPULATION LEVEL, AND NOW WE
HAVE A MECHANISM BY WHICH WE CAN
RECALL INDIVIDUALS BACK TO DO
FURTHER TESTING, EVALUATE SOME
TECHNOLOGIES WE TALKED ABOUT.
>>AND THEN TRANSLATE THOSE
FACTORS INTO THE LABORATORY TO
THE iPS AND WORK FROM THERE.
>>EXACTLY.
>>EXCELLENT.
NATE?
>>SO, I THINK IT'S BEEN SAID
WELL.
I THINK, YEAH, ABILITY TO FOLLOW
PEOPLE FOR MUCH LONGER PERIODS
OF TIME IS RADICALLY BETTER
BECAUSE OF TECHNOLOGY.
AND SO THAT ABILITY TO COME BACK
TO HAVE MORE INPUT, I THINK JUST
LETTING -- THINKING ABOUT HOW WE
HARNESS MORE OF A LOT OF THE
PEOPLE INFORMATION PEOPLE ARE
GETING NOW WITH WEARABLES AND
DEVICES.
THERE'S A LOT OF INTEREST
BECAUSE IT OPENS SO MANY ASPECTS
OF LONG-TERM EFFECTS ON HEALTH
THAT YOU JUST ARE INVISIBLE FOR
THE LONGEST TIME, DON'T HAVE TO
BE TOTALLY INVISIBLE ANYMORE.
>>MEASURE IT, WE GET MORE DATA.
GOOD, GOOD.
WE'VE ALSO COVERED OUR SECOND
QUESTION BUT I'M GOING TO ASK
THOMAS, HOW DID INTEGRATION OF
TECHNOLOGIES STANDARDS
DISCIPLINES DATA ET CETERA
ADVANCE YOUR PROJECTS, WERE
THERE CHALLENGES AND HOW DID YOU
OVERCOME THEM?
WE HAVE TO, IF YOU WILL, WRITE A
MANUAL AT SOME POINT ON HOW TO
DO THIS, WHAT YOU'VE DONE.
>>YOU NEED COMMUNICATION
BETWEEN DATA SCIENTISTS,
INFORMATICIANS, ENGINEERS,
BIOLOGYISTS, CLINICIANS, ALL
STILL TALKING DIFFERENT WAYS.
IF YOU SAW THE VARIANTS FROM
NON-ANIMAL TO NOVEL APPROACH,
NEW APPROACH, AND WHATEVER, THIS
IS ILLUSTRATING THAT WE DON'T
HAVE A STANDARD.
THERE'S NOT MANY PEOPLE WHO CAN
BRIDGE BETWEEN THESE MANY AREAS.
AND THIS IS ON A BIG CHALLENGE
THAT WE HAVE TO GENERATE.
>>HOW HAVE YOU STARTED TO WORK
ON THAT?
>>FIRST IN MY OWN LIFE I DID
STUDY BIOCHEMISTRY, MEDICINE,
MATHEMATICS INFORMATICS, SPREAD
MYSELF THINLY AND BROADLY TO
PRODUCE THESE TYPE OF STUDENTS.
AT THE MOMENT THE FIELD IS
EXPOSEING, KNOWLEDGE IN LIFE
SCIENCE DOUBLING EVERY TWO TO
THREE YEARS NOW.
WE'RE TENDING TO PRODUCE HIGHER
SPECIALIZEED PEOPLE WHO KNOW
MORE ABOUT ESSENTIALLY NOTHING.
>>BUT, THOMAS, WE CAN'T CLONE
YOU.
>>NO, NO.
>>TALK TO ME ABOUT THE TEAM
THAT YOU NEED TO BUILD TO BE
ABLE TO ADVANCE THIS TECHNOLOGY?
>>ATTRACT MANY PEOPLE,
DISCIPLINES, START HAVING THEM
TALK THROUGH WORKSHOPS, WORKING
GROUPS, OUTREACH.
WE NEED TO ASSEMBLE THESE PEOPLE
AND OFTEN THIS IS ABOUT SHARING
THE FUNDAMENTALS, DEVELOPING
ONTOLOGYS, DEVELOPING SO
VOCABULARYS.
THROUGH A.I. A LOT OF THINGS ARE
ACCESSIBLE, TRANSLATABLE, TONS
OF DOCUMENTS WHICH MAKE US DRAWN
INFORMATION IN RECENT YEARS
SUDDENLY BEING CONDENSED IN
PRETTY GOOD FORM AND WE HAVE
ACCESS THEM MORE EASILY.
I'M VERY OPTIMISTIC ABOUT
TRANSFORMATIVE CHARACTER OF
HANDING INFORMATION THROUGH A.I.
BUT NEED TO LEARN HOW TO WORK
WITH THIS ALSO.
>>GOOD.
THANK YOU, THANK YOU.
CHIRAG, MUST HAVE SIMILAR
CHALLENGES?
YOU ALL HAVE SIMILAR CHALLENGES.
>>YEAH, I REALLY THINK, TO
REITERATE WHAT DR. HARTUNG SAID,
THE KEY IS TRAINING AND GETTING
OUR STUDENTS EXPOSED TO THESE
NEW TOOLS THAT SEEM TO HAVE BUGS
AND FEATURES SUCH AS ADVANCES IN
A.I.
AND GETTING THEM AT THE BEDSIDE
SOONER.
SO AT OUR INSTITUTE WE HAVE THIS
FANTASTIC Ph.D. PROGRAM WHERE
STUDENTS NEED TO PAY -- GO TO
THE HOSPITAL AND BE AT BEDSIDE,
I THINK THAT'S VERY IMPORTANT.
THE SECOND THING ARE THE DATA.
I THINK THAT BRINGS STUDENTS AND
COLLABORATORS TOGETHER
NATURALLY.
I THINK EVEN IN THE NEW AGE OF
CLOUD COMPUTING AND A.I. WE HAVE
DATA SILOS WE NEED TO BREAK.
THE VERY SIMPLE THINGS LIKE
GETTING CLINICAL TRIAL DATA OUT
AND PUBLICLY AVAILABLE NOW ARE
VERY, VERY IMPORTANT.
>>VERY GOOD POINT.
>>I BELIEVE NICOLE HAS A HAND
UP.
NICOLE ALSO HAS HER HAND UP.
>>NICOLE, SORRY.
>>NO WORRIES.
CHIRAG SAID WHAT I WAS GOING TO
SAY BY I'LL EXPAND AND ADD MY
TWO CENTS AS A FOUNDATIONAL
STRUCTURE THAT'S REALLY
ESSENTIAL TO BE ABLE TO BUILD
INTEGRATED SYSTEMS MODELS THAT
BRING IN IN VITRO, IN SILICO, IN
CHEMICO APPROACHES THAT ARE
PARTNERED WITH A.I. THAT CAN
SUBSUME ALL OF THAT DATA AND
GENERATE TESTABLE HYPOTHESES TO
FEED IN AND BE FED BACK INTO
ITERATIVELY IMPROVEING A.I.
MODELS SO INVESTING IN DATA
INFRASTRUCTURE IN A WAY THAT
PRODUCES BOTH UNSTRUCTURED AND
STRUCTURED WELL-ANNOTATEED
DATASETS THAT CREATE THAT
ECOSYSTEM IS GOING TO BE
FUNDAMENTAL TO SUPPORTING THE
DEVELOPMENT OF MORE EFFECTIVE
MODELS.
>>THANK YOU FOR THAT COMMENT.
COHORTS LIKE THE U.K. BIOBANK
THAT HAVE GENETICS HAVE BEEN
WONDERFUL.
HOWEVER A LOT OF TRIALS THAT
HAVE BEEN DONE UP UNTIL RECENTLY
WE'VE NOT BEEN ABLE TO GET THAT
DATA AND THERE'S A LOT OF GOOD
DATA MINING IN THAT AND
HOPEFULLY THAT CAN BE BROUGHT
TOGETHER WITH ALL THE
DE-IDENTIFICATION THAT'S DONE
NOW.
HOPEFULLY WE CAN GET SOME OF
THAT VERY IMPORTANT DATA ALSO.
THANK YOU.
THE LAST QUESTION IN THE LAST
FEW MINUTES WE HAVE IS, NATHAN,
I DIDN'T FORGET YOU.
WHAT KIND OF INFRASTRUCTURE,
PHYSICAL OR INTELLECTUAL, IS
NEEDED TO REPLICATE SUCCESS AND
ADDRESS THE CHALLENGES, THE
INFRASTRUCTURE?
>>YEAH, THERE'S A LOT OF
DIFFERENT THINGS WE NEED ON
INFRASTRUCTURE.
ONE IS -- IF WE'RE TRYING TO USE
A.I. BROADLY ACROSS, AND
COMPUTATIONAL METHODS, PARTLY
WHAT'S NECESSARY THERE IS SOME
SORT OF STRUCTURE SO WE HAVE
MORE INTEROPERABILITY AMONGST
THESE THINGS, THAT COMES DOWN TO
STANDARDS.
THAT BECOMES CHALLENGING BECAUSE
YOU DON'T WANT TO STIFLE
INNOVATION OF DIFFERENT GROUPS
AND SO FORTH BUT DEFINING WHAT
THE BOUNDARY CONDITIONS ARE IN
TERMS OF TALKING, WE'VE DONE
THIS IN SOME MODELING
COMMUNITIES I'VE BEEN IN OVER
TIME DECIDING STANDARDS.
A LOT OF THESE GROUPS GET PUT
TOGETHER.
I THINK THAT'S ONE PIECE.
SECOND OBVIOUSLY ON ALL THE
APPROACHES THAT WE'RE LOOKING AT
FOR THESE NON-ALTERNATIVE
METHODS REALLY HAVING PLACES
THAT YOU CAN GO TO FOR
REPRESENTING THOSE MECHANISMS, I
THINK WE NEED AN INITIATIVE
AROUND THESE STYLE DIGITAL TWINS
AROUND MANY AREAS, I'M NOT A
HUGE PROPONENT FOR THE FULL
VIRTUAL HUMAN, WHICH IS
SURPRISING BECAUSE I LOVE
AUDACIOUS THINGS.
YOU CAN'T HAVE ALL THAT DENSELY
DOUBLEED, NOT YET, BUT
STRATIFYING INTO PIECES DENSELY
COUPLED AND LOOSE COUPLING IS
NECESSARY AT LEAST FOR CURRENT
FRAMEWORKS.
ONE OTHER THING I'LL SAY AND LET
THE OTHERS JUMP IN, IN TERMS OF
ALSO INFRASTRUCTURE FOR JUST
UNDERSTANDING EACH OTHER ACROSS
DOMAINS, BUT ALSO OUT INTO THE
PUBLIC AND TO, YOU KNOW, THE
PEOPLE THAT FUND US AND SO
FORTH, ONE OF THE AREAS THAT'S
INCREDIBLY EXCITING IS WITH THE
LARGE LANGUAGE MODELS WE'RE
FAMILIAR WITH, A FRAMING TO THE
PUBLIC I THINK WOULD BE
INCREDIBLY USEFUL BECAUSE I
THINK THERE'S A VERY STRONG
ARGUMENT THAT A LOT OF THE
OUTPUT OF SCIENCE THAT PEOPLE
PAID, SOCIETY PAYS BILLIONS OF
DOLLARS FOR NOT ACCESSIBLE.
IT'S BEHIND PAY WALLS, WE'VE
MADE STRIDES AGAINST THAT OVER
THE LAST SEVERAL YEARS.
BUT EVEN STILL IF IT'S IN A
PAPER THEY CAN'T UNDERSTAND AND
HAS A BIG TROUBLE AT MANIFESTING
IN THE PUBLIC DISCOURSE, AND FOR
PEOPLE TO UTILIZE A LOT OF THIS
STUFF WE'VE DONE, AND SO ONE OF
THE OTHER THINGS I WANT TO POINT
OUT IS THAT THE LARGE LANGUAGE
MODELS ESPECIALLY WITH
INVESTMENT IN INFRASTRUCTURE
THAT ALLOWS THAT TO BE HIGH
QUALITY ACCESSIBLE IN A WAY
PEOPLE CAN GET ACCESS TO, IT'S
NOW POSSIBLE FOR, YOU KNOW, A
THIRD GREAT STUDENT TO ASK A
QUESTION INTO THE SCIENTIFIC
LITERATURE AND GET AN ANSWER
EXPLAINED BACK IN A LANGUAGE SHE
CAN UNDERSTAND.
SO I THINK THAT HELPS BOTH IN
TERMS OF MULTI-DISCIPLINEARITY
TO GET ANSWERS TO QUESTIONS.
I'VE HAD STUDENTS ASK
STATISTICAL QUESTIONS HOW DO I
DO THIS, WHY SHOULD I DO THAT,
THE ABILITY TO EXPLAIN BACK IS
INCREDIBLE BUT I WANTED TO PUT
IN THE PLUG FOR OUR
RESPONSIBILITY BACK TO THE
PUBLIC.
IT'S PROBABLY THE FIRST TIME
THEY HAVE BEEN ABLE TO HAVE
ROBUST ACCESS TO A REAL DEPTH OF
INFORMATION WE'RE PRESENTING.
THAT'S A HUGE OPPORTUNITY FOR
THE BIOMEDICAL COMMUNITY.
>>OKAY.
>>I JUST WANTED TO ADD ONE
POINT QUICKLY, IT'S NOT ONLY
ABOUT DATA ACCESSIBILITY.
IT'S ALSO ABOUT SCIENTIFIC
KNOWLEDGE.
IT'S ABOUT OPEN ACCESS
PUBLISHING IN THE MACHINE
READABLE FORMAT.
THIS IS SOMETHING WHICH WOULD
REALLY SUIT THE NIH ALSO TO
FOSTER THIS.
>>IF I MAY ADD ONE ADDITIONAL
POINT.
I AGREE WITH EVERYTHING SAID BUT
THERE'S A REAL OPPORTUNITY THAT
HASN'T BEEN CAPITALIZEED ON
EFFECTIVELY YET, TO APPLY
FEDERATED DATA SHARING AND MODEL
BUILDING APPROACHES SO I THINK
THE REALITY OF THE SITUATION IS
THAT THERE IS QUITE A LOT OF
PROPRIETARY DATA THAT, YOU KNOW,
OUT OF NECESSITY, OUT OF
INTELLECTUAL PROPERTY, WILL
CONTINUE TO REMAIN PRIVATE BUT
THERE'S ENCRYPTION TECHNOLOGIES
USED AND FEDERATED MODEL
BUILDING APPROACHES WHERE
MODELS ARE SHARED, IMPROVED
INTERNALLY, DATA CAN REMAIN
PROPRIETARY BUT THAT MODEL GETS
SHARED EXTERNALLY SO I THINK
THERE'S A REAL OPPORTUNITY THERE
TO BUILD CONSORTIUMS, THAT NIH
CAN PLAY A BIG ROLE IN.
>>VERY GOOD POINTS, HOW WE CAN
WORK TOGETHER TO MOVE THE
NEEDLE.
I WANT TO THANK ALL OF MY
PANELISTS FOR STARTING US OFF
THIS MORNING AND REALLY WORKING
AND DESCRIBING THE OPPORTUNITIES
AND CHALLENGES FOR NAMs IN
BIOMEDICAL RESEARCH.
THANK YOU ALL.
AND FOR ALL YOUR HARD WORK AND
FOR THIS VERY EXCITING TIME.
THANK YOU, THANK YOU.
[APPLAUSE]
>>THANK YOU, NANCY, FOR
MODERATEING.
WE'LL TAKE A 15-MINUTE BREAK.
>>WELCOME BACK.
I WANT TO INTRODUCE OUR SECOND
SESSION, WITH DR. DAN TAGLE, HOW
DIFFERENT SECTORS CAN WORK
TOGETHER CATALYZING USE OF
NAMs.
WE DON'T HAVE AN INDUSTRY
PRESENTER BUT SPECIAL THANKS TO
DR. MYRTLE DAVIS, PARTICIPATING
TO PROVIDE HER INDUSTRY
PERSPECTIVE.
I'LL HAND IT OVER TO DR. TAGLE
TO CHAIR THE NEXT SESSION
PLEASE.
>>ALL RIGHT.
THANK YOU, DR. THANK.
GOOD MORNING, EVERYONE.
GOOD MORNING TO THE SPEAKERS,
MODERATORS AND MEMBERS OF THE
WORKING GROUP ON NAMs.
WE'RE AT WILSON HALL AT THE NIH,
AND I THINK WELCOME ALSO TO THE
MORE THAN 500 REGISTRANTS WHO
ARE TUNING IN VIRTUALLY.
A PLEASANT GOOD MORNING TO ALL.
I'M DAN TAGLE AT NCATS AT THE
NIH.
ALSO THE EX OFFICIO MEMBER OF
THE ACD WORKING GROUP ON NAMs.
SESSION 2 IS CROSS-SECTOR
APPROACHES FOR DRIVING NAMs
USE AND DEVELOPMENT.
FOUR SECTORS ARE REPRESENTED,
BIOMEDICAL RESEARCH ENTERPRISE
AND ROLES IN CATALYZING
DEVELOPMENT AND USE OF NAMs.
THIS SESSION FOCUSS ON THE
UNIQUE AND COMPLEMENTARY EFFORTS
UNDERWAY REPRESENTED IN EACH
SECTOR AND SEEKS TO IDENTIFY
SYNERGYS AND NEEDS FOR
COLLABORATION.
WE HAVE THE PRIVILEGE THIS
MORNING TO WELCOME FOUR PANEL
MEMBERS, EACH PRESENTING A KEY
STAKEHOLDER IN DEVELOPMENT AN
ADAPTION OF NAMs.
FIRST DR. ALEX CARLISLE,
FOUNDER, CHAIRMAN, CEO OF THE
NATIONAL ALLIANCE AGAINST
DISPARITIES IN PATIENT HEALTH,
NADPH, A NON-PROFIT HEALTH
RESEARCH ORGANIZATION APPLYING
SCIENTIFIC RESEARCH AND
TECHNOLOGY, COMMUNITY EDUCATION,
OUTREACH AND ADVOCACY TO REDUCE
HEALTH DISPARITIES AND IMPROVE
PUBLIC HEALTH OUTCOMES FOR OUR
NATION.
DR. CARLISLE HAS OVER 30 YEARS
OF EXPERIENCE IN HEALTH CARE,
BIOMEDICAL RESEARCH, B.A. IN
BIOLOGY FROM FISK UNIVERSITY,
DOCTORATE IN BIOCHEMISTRY FROM
HOWARD UNIVERSITY, POSTDOCTORAL
TRAINING AT NCI AS PART OF THE
CANCER GENOME ANATOMY PROJECT
AND WORKED ON PARKINSON'S
DISEASE AT NINDS.
HE HAS LED RESEARCH EFFORTS AT
SEVERAL TOP ACADEMIC MEDICAL
CENTERS INCLUDING FOX CHASE
CANCER CENTER, CHILDREN'S
HOSPITAL OF PHILADELPHIA AND
ENOVA FAIRFAX HOSPITAL.
>>GOOD DAY.
THANK YOU FOR HAVING ME HERE.
TEN YEARS AGO, MY PRESENTATION
WOULD HAVE PROBABLY LOOKED A LOT
LIKE MOST OF THE PRESENTATIONS
THAT WE'VE SEEN TODAY.
BUT TODAY I'M ACTUALLY GOING TO
FOCUS ON ANOTHER CRITICAL ASPECT
TO REALLY GETTING THE NOVEL
TECHNOLOGIES, NOVEL ALTERNATIVE
METHODS DEVELOPED TO ENSURE
BROAD EFFICACY, USAGE, AND
ETHICAL AND EQUITABLE FASHION.
SO I'M GOING TO JUST TAKE A FEW
SLIDES TO TALK ABOUT SOME
FUNDAMENTAL POINTS THAT I THINK
ACTUALLY HAVE BEEN TOUCHED ON A
LITTLE BIT TODAY AND I WAS
PLEASED TO HEAR SOME OF THE
COMMENTS FROM SOME PREVIOUSLY
PANELISTS WHO TALKED ABOUT THE
NEED FOR ENSURING ACCESS AND
TRANSLATION.
I'M CERTAINLY GOING TO HIGHLIGHT
THAT AGAIN.
YOU'LL GET A BREAK HERE, NOT AN
OVERLY TECHNICAL PRESENTATION
HERE BUT, AGAIN, THE POINT IS TO
REALLY HIGHLIGHT SOME VERY
CRITICAL FUNDAMENTAL ELEMENTS
THAT NEED TO BE CONSIDERED IN
THE DEVELOPMENT OF ANY
TECHNOLOGY TO MAKE SURE, AGAIN,
THAT TECHNOLOGY IS EQUITABLE AND
ETHICAL.
AS MENTIONED EARLIER I SPENT
TIME AT NIH WITH NCI, NINDS,
PART OF THE CANCER GENOME
AANATOMY PROJECT, REALLY THE
BEGINNING OF BIG DATA
GENERATION, CREATING HIGH
CONTENT, HIGH-THROUGHPUT GENOMIC
INTERROGATION PLATFORMS WHICH
LED TO TRANSLATION OR GENERATION
OF A LOT OF DATA, AND HELPING
DEVELOP EARLY BIOINFORMATIC
ANALYSES PACKAGE FOR THAT, AS
YOU CAN IMAGINE WITH THE
GENERATION OF THAT DATA, THERE
CAME REAL COMPUTATIONAL
CHALLENGES IN TERMS OF HOW TO
STORE THAT DATA, MORE
IMPORTANTLY ANALYZE IT, WORKING
WITH PETER AT CIT TO HELP
DEVELOP SCANS AND OTHER THINGS.
I SPENT TIME AT NORTHROP GRUMMON
AS WELL.
ONE OF THE LESSONS LEARNED THAT
WE TYPICALLY APPROACH TECHNOLOGY
GENERATION OR DEVELOPMENT FROM A
TOP-DOWN PERSPECTIVE, RIGHT?
AND IT MAKES SENSE.
SUBJECT MATTER EXPERTS, YOU
KNOW, WE HAVE THE MINDSET, HEY,
WE HAVE SCIENCE, UNDERSTAND
TECHNOLOGY, WE'RE THE BEST
QUALIFIED OR EQUIPPED TO DESIGN
AND DEVELOP TECHNOLOGY.
HOWEVER, WHAT HAPPENS IS TAKING
THAT APPROACH YOU GET VERY
NUANCED, THINGS THAT COME OUT OF
IT REQUIRE EXPERTISE IN TERMS OF
BEING ABLE TO UNDERSTAND AND
NAVIGATE THAT.
SO WHAT YOU SEE RIGHT HERE
REALLY IS DOCUMENTATION OF THE
FIRST NATURE PUBLICATION FROM
2021 WHICH DOCUMENTS IN THE
ACADEMIC SPACE, YOU KNOW, FROM
WHAT WOULD BE CONSIDERED SOME
WELL-RESOURCEED INSTITUTIONS AND
SCIENTISTS THAT ARE THERE ARE
REAL CHALLENGES TO BEING ABLE TO
USE SOME OF THE TECHNOLOGY
THAT'S BEEN DEVELOPED.
I THINK I HEARD A COMMENT FROM
THE PREVIOUS SPEAKER, PUBLIC
KNOWLEDGE, RIGHT?
TREMENDOUS AMOUNTS OF INVESTMENT
TO CREATE THESE RESOURCES,
INFRASTRUCTURE, DATA RESOURCES,
AND SHOULD NOT BE IVORY PALACE.
THIS IS TECHNOLOGY THAT SHOULD
HAVE BROAD ACCESS AND
APPLICABILITY, USEABILITY, FOR
NOT ONLY RESEARCH COMMUNITY BUT
BROADER COMMUNITY AS WELL.
WE'RE SEEING A LOT OF THIS COME
THROUGH COMMISSION REPORTS,
WHICH ARE REALLY STATEING THAT
WE HAVE A RESPONSIBILITY TO MAKE
SURE THAT THIS WORK, MUCH OF IT
WHICH IS GENERATED FROM PATIENT
SAMPLES OR DATA, TO BE ABLE TO
TRANSLATE THAT VALUE BACK TO
THAT COMMUNITY.
THAT NEEDS TO BE FACTORED INTO
ANY TECHNOLOGY BEING DEVELOPED.
THE SECOND WAY IS MAKING SURE
THE TECHNOLOGY BEING DEVELOPED
IS WELL INFORMED AND, AGAIN, IS
ROBUST IN ITS ABILITY TO MAKE
SURE THAT IT'S GOING TO BE
ETHICAL AND EQUITABLE.
ONE OF THE WAYS THAT YOU DO
THAT, IT'S A SIMPLE CONCEPT,
AGAIN I THINK -- AND I'VE BEEN
THERE, YOU KNOW, AS SUBJECT
MATTER EXPERTS, YOU KNOW, WHEN
WE'RE AMONGST OURSELVES IT'S
DIFFICULT TO BRING THAT PURVIEW
TO THE TABLE.
AND SO HAVING HUMAN DESIGN
EXPERTS OR TEAMS SKILLED AND
UNDERSTAND IMPORTANCE OF
ENGAGING WITH THE END USER,
CUSTOMER, THAT'S A VERY CRITICAL
COMPONENT TO THIS.
SO, AGAIN, THIS IS SOMETHING
THAT WE NEED TO STAY COGNIZANT
OF AND MAKE SURE AS WE'RE
DEVELOPING TECHNOLOGIES THAT
WE'RE ACTUALLY INCLUDING THE
FOLKS THESE TECHNOLOGIES ARE
INTENDED TO BENEFIT OR TO BE
USED BY.
SO, ONE OF THE THINGS THAT WE
DO, IT'S A BIG PART OF WHAT WE
DO.
OUR ROLE, OUR MISSION IS REALLY
TO MAKE SURE AS THESE ADVANCES
IN SCIENCE AND TECHNOLOGY TAKE
PLACE, THAT WE ARE OCCUPYING
SPACE TO HELP TRANSLATE AND MAKE
SURE IN ITS APPLICATION IT'S
SERVING COMMUNITIES GENERALLY
MARGINALIZEED, UNDERRESOURCED
AND DON'T BENEFIT.
AND SO A BIG PART OF OUR DOING
THAT WORK IS WORKING WITH
ORGANIZATIONS LIKE THE ROBERT
WOOD JOHNSON FOUNDATION
PCORI, CDC, NIH AND OTHERS TO
MAKE SURE THAT QUALITATIVE
COMPONENT, WE'VE HEARD ABOUT THE
QUANTITATIVE SCIENCE TODAY, BUT
THERE IS REALLY A FUNDAMENTAL
EQUAL AT THAT TIME --
QUALITATIVE COMPONENT WE NEED TO
CONSIDER.
WHAT WE FOUND BY PARTICIPATING
IN STAKEHOLDER COMMUNITY EFFORTS
IS THAT FOLKS MAKE THE MISTAKE
THEY ARE DOING IT AND GETTING IT
AND DON'T REALLY TAKE THE TIME
TO MAKE THE INVESTMENT TO DO
THAT RIGHT.
YOU KNOW, AGAIN, WE'RE SEEING
THIS WITH PHARMACEUTICAL
COMPANIES AND OTHER TECHNOLOGY
COMPANIES WHERE, AGAIN, THEY ARE
JUST NOT TAKING THAT TIME TO
INVEST IN THE COMMUNITY AND DO
DEEP QUALITATIVE.
HERE IS THE WORK WE'VE DONE,
RWJ, PLEASE FEEL FREE TO TAKE A
LOOK.
THROUGH THESE CONVENEINGS, WE DO
DEEP QUALITATIVE WORK AND
UNDERSTAND FUNDAMENTALLY WHAT
VIEWS ARE ABOUT TECHNOLOGY, WHAT
THE BARRIERS AND FACILITATORS
MIGHT BE WITHIN THOSE
COMMUNITIES IN TERMS OF
INTERACTING WITH TECHNOLOGY, AND
TRYING TO REALLY ASSESS WHAT
THAT VALUE PROPOSITION IS TO
UNDERSTAND, AGAIN, POTENTIAL FOR
HARM, POTENTIAL FOR GOOD, SO WE
CAN COME UP WITH GUIDING
PRINCIPLES TO MAKE SURE
TECHNOLOGY IS GOING TO BE
APPLIED THE RIGHT WAY.
SO YOU MIGHT HAVE NOTICED IN THE
INTRODUCTORY SLIDE THAT IN
ADDITION TO BEING THE CHAIR AND
CEO OF NADPH, GIVEN MY ACADEMIC
BACKGROUND, I'M ALSO THE LEAD
MPI ON AIM AHEAD DATA
INFRASTRUCTURE CORE.
SO THIS IS AN INITIATIVE THAT
REALLY IS IN LINE WITH OUR
NATIONAL STRATEGY WHICH IS ABOUT
TRYING TO ACCELERATE AROUND
INNOVATION AND TYPES OF
TECHNOLOGY WE HAVE HEARD ABOUT
TODAY.
IT'S NO SECRET THE U.S. IS
CERTAINLY LOSING SOME OF ITS
COMPETITIVE ADVANTAGE IN TERMS
OF TECHNOLOGY INNOVATION, AND SO
WE'RE SEEING TREMENDOUS
INVESTMENT ALSO, A NUMBER OF
INITIATIVES ON WAYS TO RESTORE
THAT, RECLAIM THAT.
ONE OF THE THINGS THAT HAS
REALLY COME OUT OF A NUMBER OF
THINK TANKS AND NATIONAL
ACADEMYS BEING ONE OF THOSE IS
WE NEED TO DO A BETTER JOB
INVESTING IN UNDERREPRESENTED
COMMUNITIES.
THERE'S A WEALTH OF TALENT IN
THESE COMMUNITIES, AND IN ORDER
TO GET THE INNOVATION, WE NEED
THAT DIVERSITY OF THOUGHT.
IT'S GREAT A LOT OF INNOVATION
COMES FROM THE HARVARDS AND
STANFORDs OF THE WORLD BUT WE
ALSO NEED THEM TO COME FROM THE
HOWARDS, MOREHOUSES, AND OTHER
PLACES.
AIM AHEAD IS ONE OF THOSE
INITIATIVES FOR DEVELOPING AND
APPLYING ARTIFICIAL INTELLIGENCE
IN THOSE COMMUNITIES.
I'M HAPPY TO BE PART OF THAT
INITIATIVE, THAT PROGRAM, TO
LEAD INFRASTRUCTURE CORE WHERE,
YOU KNOW, MUCH OF WHAT I SAID
EARLIER, THAT'S THE APPROACH
WE'RE USING IN OUR APPROACH TO
HELP BUILD THIS CAPACITY AND
THOSE INSTITUTIONS.
WHAT THAT MEANS IS HEY WE'RE NOT
JUST GOING TO INTRODUCE EXISTING
TECHNOLOGY AT CURRENT STATE IT
IS BUT HAVE TAKEN THE FIRST YEAR
OR TWO OF THE PROGRAM TO ENGAGE
ACROSS THE ENTIRETY OF THE
STAKEHOLDER COMMUNITY TO
UNDERSTAND WHAT IS YOUR BASIC
CAPACITY AS IT EXISTS RIGHT NOW?
WHAT DO YOU WANT DO WITH THE
TECHNOLOGY?
WE MAKE ASSUMPTIONS THIS GREAT
TECHNOLOGY IS DESIRED, OF VALUE,
BUT WE HAVEN'T TAKEN THE TIME TO
EVALUATE AND INTERACT WITH
COMMUNITIES TO SEE IF THAT'S
ACTUALLY THE CASE.
THAT'S ONE OF THE THINGS, I'M
PROUD TO SAY WE FOCUSED ON.
A LOT OF THAT HAS CENTERED
AROUND ETHICS AND EQUITY, SO
WE'RE APPLYING LESSONS LEARNED
FROM WORKING WITH ORGANIZATIONS,
COLLABORATEING WITH GREAT
INSTITUTIONS.
A COLLEAGUE AT VANDERBILT,
AGAIN, BRINGING OUR COLLECTIVE
EXPERTISE IN THE SPACE TO REALLY
ENGAGE COMMUNITIES AND COME
FORTH WITH A SET OF PRINCIPLES
TO GUIDE DEVELOPMENT OF THIS
TECHNOLOGY.
SO, ONE OF THE OTHER THINGS
THAT'S REALLY IMPORTANT IS,
AGAIN, A SIMPLE CONCEPT, ONE
THAT I'M NOT ASHAMED TO SAY I
OVERLOOKED FROM MY CAREER, MUCH
OF MY ACADEMIC CAREER, IT WASN'T
UNTIL I GOT TO NORTHROP GRUMMON,
HEAD OF PRECISION MEDICINE
BUSINESS UNIT, ASPIRATIONAL UNIT
WITHIN NORTHROP GRUMMAN.
I CAME TO THIS PLACES LIKE THIS
TO SPEAK, IMMEDIATELY WHAT ARE
YOU DOING HERE?
YOU'RE BUILDING BOMBS AND
MISSILES, NOTHING TO DO WITH
LIFE, YOU KNOW, WHY ARE YOU
HERE?
HERE I AM AN ACADEMIC SCIENTIST,
TRYING TO LEAD THIS GROUP OF
SOFTWARE DEVELOPERS AND
ENGINEERS, HEY GUY, YOU'VE BEEN
ANALYZING ELECTRONIC AND ALL
THESE OTHER SIGNALS BUT I WANT
YOU TO UNDERSTAND BIOLOGIC
SIGNALS, HEY, THIS IS THE LEGACY
CAPABILITY, CAN BE APPLIED TO DO
GOOD HERE.
SO UNFORTUNATELY NORTHROP DIDN'T
ONE TO GO THE FULL DISTANCE TO
MAKE THOSE INVESTMENTS DESPITE
GETTING PROOF OF CONCEPTS WITHIN
NCI ACTUALLY, SO WE DEVELOPED
PREDICTIVE ONTOLOGY PLATFORM
THAT WORKED WELL, NCI ASKED US
TO PUT SOMEBODY IN THE
LABORATORY FOR A YEAR TO
CUSTOMIZE THAT AND IT WOULD HAVE
TAKEN ONE FTE, BUT THAT'S
ANOTHER STORY.
BUT HERE, WHAT I WANTED TO POINT
OUT IS THE ENTIRETY OF THE
DEVELOPMENT LIFE CYCLE, RIGHT?
AND SO THIS IS BACK TO THE POINT
THAT I MADE EARLIER IN TERMS OF
REALLY BEING VERY SINCERE, VERY
AUTHENTIC AND GENUINE, AND
ABILITY AND WILLINGNESS TO
ENGAGE, YOU KNOW, THE BROADER
COMMUNITY BECAUSE IT'S NOT A
SIMPLE ONE-OFF.
YOU HAVE TO BE EMBED AND INCLUDE
THEM.
IN ADDITION WE HAVE TO BE
WILLING TO TAKE OURSELVES OUT OF
THE EQUATION.
ONE OF THE THINGS THAT I CAN
TELL YOU FROM DOING THIS WORK
FOR THE LAST DECADE IS A POWER
DYNAMIC, YOU CAN PUT US IN A
ROOM BUT INEVITABLY WHAT
HAPPENS, THEY WILL ACQUIESCE AND
YOU MAY HAVE ONE OR TWO THAT ARE
A BIT BOISTEROUS AND WILL DO SO
IN A VERY NARROW FASHION, BUT WE
TAKE OVER THE ROOM, SO WE'RE
MISSING THE OPPORTUNITY TO
REALLY CAPTURE THAT CRITICAL
INPUT.
AND THAT WAS POINT I WAS MAKING
EARLIER.
A SIMPLE CONCEPT IF YOU'RE GOING
TO BUILD SOMETHING FOR SOMEBODY
TO USE, WHETHER TRYING TO SELL
IT OR WHATEVER, WHY DON'T YOU
ASK THEM WHAT IS IT YOU WANT TO
USE THIS FOR?
IS THIS OF VALUE, RIGHT?
IN ACADEMIA I THINK WE MISS THE
MARK ON THAT.
WE GET IT ON THE TECHNOLOGY SIDE
IN TERMS OF INDUSTRY SO THERE'S
A LOT OF INVESTMENT IN PRODUCT
DEVELOPMENT AND CONSUMER
PSYCHOLOGY AND THINGS LIKE THAT.
ENGAGING WITH PERSONS WITH LIVED
EXPERIENCE, THIS IS A VERY
POWERFUL MODEL, PWLE MODEL, THAT
WE EMPLOY AT NADPH.
WHO IS GOING TO KNOW BETTER THAN
THE FOLKS WITH THAT DISEASE OR
CONDITION, SO WE HAVE TO ENGAGE
THEM AND IT HAS TO BE
C ONTINUOUSNESS, CONTINUITY OF
THE LIFE CYCLE.
THIS IS DEMONSTRATING THE WORK
FLOW.
WE HAVE A ROBUST CONCIERGE
SERVICE.
I CAN TELL YOU BECAUSE WE'RE
JUST GETTING FRESH OFF WORKING
WITH FOLKS, IT TAKES A LOT OF
TIME.
I CAN'T TELL YOU THE MAN AND
WOMAN HOURS WE PUT INTO
HAND-HOLDING STAKEHOLDERS
THROUGH EVERY COMPONENT OF THIS.
I'VE HAD SOFTWARE DEVELOPERS,
CLOUD ARCHITECTS, ON CALLS WITH
STAKEHOLDERS TO MAKE SURE HEY,
DO YOU UNDERSTAND THIS DATA,
RIGHT?
LET US HELP YOU REFINE YOUR
QUESTION, REFINE YOUR HYPOTHESIS
BECAUSE THE WAY YOU HAVE IT
FORMULATED NOW YOU'RE NOT SET UP
TO ANSWER THAT QUESTION, RIGHT?
SO THIS IS WHAT WE'RE
ENCOUNTERING AT AIM AHEAD.
IT TAKES A LOT OF INVESTMENT TO
DO THAT.
THE REALITY IS NOT MANY FOLKS
ARE ALWAYS WILLING TO DO THAT.
WE WANT TO GET TO THE GOOD
STUFF.
I JUST WANTED TO POINT THAT OUT
AND MAKE SURE THAT'S SOMETHING
WE STAY COGNIZANT OF.
AND THEN FINALLY ON MY LAST
SLIDE, NO GROUP IS HOMOGENOUS.
THERE'S TREMENDOUS AMOUNT OF
HETEROGENEITY.
ONE OF THE THINGS WE LEARNED IN
WORKING WITH THIS STAKEHOLDER
COMMUNITY IS THAT TREMENDOUS
STRATIFICATION, WE'VE PUT
INVESTMENT INTO DEVELOPING
SELF-ASSESSMENT TOOL, SO THEY
WERE ABLE TO GO IN AND ANSWER
SOME BASIC QUESTIONS, THESE
QUESTIONS, AGAIN, WERE INFORMED
BY ALL OF THAT HARD WORK I
TALKED ABOUT.
SO WE'RE TALKING ABOUT SURVEYS,
INTERVIEWS, AND CONVENEINGS TO
GET AT WHAT THE THEMES ARE,
TIMES OF QUESTIONS WE NEED TO
ASK.
SO IN DOING THAT WE CAME ONE A
MATURITY MODEL, GO IN, ASK BASIC
QUESTIONS ABOUT ARTIFICIAL
INTELLIGENCE CAPACITY, AND FROM
THAT WE'RE ABLE TO GIVE THEM A
SCORE.
WITH THAT SCORE IT ALLOWS US TO
STAGE APPROPRIATELY RESOURCES
THEY NEED TO MATURE FROM CURRENT
STATE TO SOME DESIRED FUTURE
STATE.
AGAIN, THIS IS A RESULT OF THAT
ENGAGEMENT AND THE TAKEHOME
MESSAGE FROM THAT IS THAT, HEY,
YOU ALL MIGHT BE HBCUs OR
HISPANIC-SERVING INSTITUTIONS,
BUT GUESS WHAT, YOUR NEEDS COULD
BE DIFFERENT, RIGHT?
SO HOW WE DEVELOP THINGS, YOU
HAVE TO TAKE INTO CONSIDERATION.
IT'S NO DIFFERENT THAN WE LOOK
AT DEMOGRAPHIC SUBPOPULATIONS
FROM CLINICAL PERSPECTIVE.
HISPANIC COMMUNITIES, A GREAT
EXAMPLE WHERE WE'RE SEEING
TREMENDOUS STATIFICATION AND
DIVERSITY IN THE COMMUNITY.
SO WE CAN'T TREAT A PARTICULAR
DEMOGRAPHIC GROUP AS A
HOMOGENOUS MONOLITHTIC GROUP.
WE NEED TO BE COGNIZANT OF THAT.
I THINK THAT'S ALL I WANTED TO
COVER TODAY.
AGAIN, THANK YOU VERY MUCH.
[APPLAUSE]
>>THANK YOU, DR. CARLISLE.
NEXT PRESENTER IS DR. ELIJAH
PETERSEN, AT THE U.S. NATIONAL
INSTITUTE OF STANDARDS AND
TECHNOLOGY, RESEARCH FOCUSES OF
IN VITRO ASSAYS, INTERLABORATORY
AGREEMENT OF THE ASSAY RESULTS,
A B.S. AND M.S. IN CIVIL
ENGINEERING, B.A. IN PSYCHOLOGY
FROM CASE CASE WESTERN RESERVE
UNIVERSITY AND Ph.D. FROM
UNIVERSITY OF MICHIGAN,
RECIPIENT OF FULBRIGHT
SCHOLARSHIP FOR POSTDOCTORAL
RESEARCH AT A UNIVERSITY IN
FINLAND.
>>THANK YOU FOR THIS
OPPORTUNITY TO SHARE A BIT ABOUT
A GREAT INTERAGENCY EFFORT IN
THE LAST FEW YEARS.
I'LL FOCUS MORE FOCUSED ON A
TOPIC UNDERPINNING DATA GOING TO
DIFFERENT MODELS AND A.I. AND SO
FORTH EVERYONE HAS BEEN TALKING
ABOUT.
THE QUESTION IS HOW CAN WE GET
THOSE GOOD QUALITY DATA GOING IN
SO WHEN COMPUTATION MODELS ARE
YIELDING RESULTS WE'RE
EXPECTING.
THIS EFFORT IN PARTICULAR, I'LL
BE TALKING ABOUT TODAY FROM THE
MULTI-GOVERNMENT AGENCY EFFORT,
YOU CAN SEE NICOLE WAS A MEMBER,
JOHN GORDON FROM THE CPSC, EMILY
REINKE FROM DoD.
THERE'S APPROACH METHODS,
THOUSAND CAN WE HAVE GREATER
MEASUREMENT ASSURANCE IN THEM?
IT'S A COMPLICATED QUESTION BUT
WE CAME OUT WITH HELPFUL IDEAS.
ONE OF THE VALUABLE THINGS ABOUT
THIS GROUP, ALSO IN VALIDATION
WORK GROUP NICOLE DISCUSSED
EARLIER, PEOPLE FROM DIFFERENT
AGENCIES BRING DIFFERENT
VIEWPOINTS AND EXPERTISE.
FOR US AT NIST WE'RE ALSO
FOCUSED ON TECHNICAL QUALITY,
HOW TO UNDERSTAND UNCERTAINTY
AND SOME OF THOSE NUANCES.
CPSC IS A REGULATORY AGENCY,
JOHN HAD EXPERIENCE IN INDUSTRY
TO DEVELOP ASSAYS.
A BROAD RANGE OF EXPERTISE, SOME
PEOPLE UNDERSTAND MEASUREMENT
QUALITY.
OTHER PEOPLE ARE PERFORMING
LABS, PERSPECTIVE OF WHAT WOULD
IT BE LIKE TO BE A TECHNICIAN
DOING IT MORE FREQUENTLY, OTHER
PEOPLE HAVE PERSPECTIVE HOW TO
BRING ASSAYS TO FRUITION AS A
STANDARD.
IN THIS PARTICULAR PROJECT TO
YIELD THIS REPRODUCE NAMs,
LIKE IF YOU'RE BUILDING A CAR
THERE'S BASIC QUALITY TOOLS AND
APPROACHES YOU CAN USE TO GET
THE SAME THING EVERY TIME.
WE PUT THESE IN USE AND ONCE YOU
GET THESE RESULTS FROM
CONCEPTUAL AND EXPERIMENTAL
ANALYSES, YOU CAN BUILT
STATISTICAL MODELS AND HAVE
RESPONSE AND ALSO CONFIDENCE
ABOUT WHETHER THERE MIGHT BE A
FALSE POSITIVE OR FALSE NEGATIVE
RESULT.
IT SHOULD BE POINTED OUT THERE
MAY BE TRADEOFFS.
FOR SOME ASSAYS YOU MAY NOT NEED
AS MANY CONTROLS, IF IT'S A
FIRST SCREENING FOR EXAMPLE, IF
YOU'RE TRYING TO HAVE SOMETHING
WITH SIMILAR RESULT TO IMPORTANT
IN VIVO TEST RESULT YOU MAY NEED
MORE CONTROLS WHICH COULD
INCREASE COST OR DECREASE
THROUGHPUT.
I'M GOING TO TALK ABOUT
INCREASING CONTROLS BUT IN THE
CONSENSUS PROCESS THERE MAY BE
CHOICE OF, WELL, DO WE REALLY
NEED THAT?
IF WE DIDN'T HAVE THAT, WE CAN
DO THIS OR THAT BETTER,
DIFFERENT CRITERIA.
SO THIS IS THE GENERAL FRAMEWORK
HERE.
THE KEY QUESTION, WHEN DO YOU
TAKE AN ASSAY THROUGH THIS
PROCESS?
ONE OF THE KEY QUESTIONS AT THE
BEGINNING IS THERE BIOLOGICAL
RELEVANCE, THIS GETS INTO THINGS
NICOLE WAS TALKING ABOUT EARLIER
WITH VALIDATION WORK GROUP,
PILLARS FOR LOOKING AT IS THIS
NAMs SOMETHING THAT COULD FILL
FULL A KEY TESTING NEED.
THERE'S ALSO A CAPACITY TO -- IF
YOU PUT EFFORT IN, COULDN'T YOU
GET THE QUALITY TO BE AT
SUFFICIENTLY HIGH LEVEL, FOR
SOME MAYBE YOU DON'T HAVE THE --
MAYBE TECHNOLOGY HASN'T BEEN
DEVELOPED ENOUGH OR THERE'S SOME
OTHER FACTORS, EVEN IF YOU PUT
EFFORT IN YOU MAY NEVER GET TO
THE LEVEL YOU HOPED FOR IT TO BE
FOR FULFILLING KEY TESTING
NEEDS.
THEN ONCE YOU HAVE AN ASSAY THAT
YOU THINK WILL MEET CRITERIA,
YOU FIND AT THE END IT DOESN'T
BUT AT THE BEGINNING YOU THINK
YOU HAVE A GOOD ASSAY, THEN YOU
FIRST APPLY CONCEPTUAL TOOLS
I'LL DESCRIBE ON THE NEXT FEW
SLIDES, SOURCES OF VARIABILITY,
INTENDED CONTROL MEASUREMENTS,
MOVE TO WITHIN LABORATORY
TESTING WHERE YOU'RE GETTING
HANDS DIRTY AND YOU THINK THESE
ARE KEY THINGS BUT MAYBE THEY
ARE NOT.
MAYBE THERE'S SOMETHING YOU
HADN'T THOUGHT ABOUT THAT YOU
UNCOVER LATER, OH, YOU NEED TO
KEEP AN EYE ON THAT.
THAT BUILDING TOGETHER INTO A
STATISTICAL MODEL.
YOU MAY OR MAY NOT NEED
TRANSFERABILITY OR INTERLAB
TESTING, WHATEVER YOUR OUTPUT IS
AS STAND ORDER.
NICOLE SAID NO ONE-SIZE-FITS-ALL
MODEL.
SOME CASES MAY NEED THIS, OTHER
CASES YOU MAY NOT.
THAT'S CONTEXT SPECIFIC.
ON THE RIGHT SIDE YOU'LL SEE
DOTTED LINES.
THAT SUGGESTS THIS ISN'T JUST A
LINEAR PROCESS.
ONE, TWO, THREE, FOUR.
OFTEN MAY BE THAT YOU GET
INFORMATION FROM LATER STEP THAT
CAUSES YOU TO REINTERPRET WHAT
YOU DO AT EARLIER STEP.
WE HAD A CASE WITH INTERLAB
TESTING, HAD IT SET, GO BACK TO
CONCEPTAL ANALYSIS, OH, WE
DIDN'T THINK WAS KEY TO MEASURE
BUT WE SHOULD MEASURE THAT.
YOU NEED TO DO ANOTHER ROUND TO
ADD CONFIDENCE, AT THE END HAVE
A ROBUST METHOD MEETING YOUR
NEED.
I'LL GIVE SPECIFIC EXAMPLES WHAT
TOOLS COULD LOOK LIKE IN
PROCESS.
THIS IS A FISH BONE DIAGRAM.
YOU HAVE A SENSE OF THINGS I
NEED TO WATCH OUT FOR, GETTING
THINGS FROM YOU KNOW TO BE TRUE
TO DIFFERENT PEOPLE CAN DISCUSS
OR OTHER PEOPLE HAD DIFFERENT
EXPERIENCE.
EACH LINE IS KEY SOURCE OF
UNCERTAINTY, WITH SUBRANGES OFF
EACH.
THIS COULD -- IF I UNDERSTAND
THESE, THE IDEA YOU HAVE A GOOD
HANDLE.
IF YOU HAD A GOOD UNDERSTANDING
WHERE THE KEY SOURCE WAS,
ANOTHER ASSAY COULD USE THAT,
LIKE A LEGO SET, NOT LIKE YOU
NEED TO REDO THIS.
THERE'S ITERATIVE THINGS TO
BUILD ON EACH OTHER.
IT GETS EASIER WITH TIME AND YOU
HAVE MORE EXPERIENCE.
ANOTHER KEY THING THAT WE
RECOMMEND IS CONCEPTUAL TOOL,
FLOWCHART, WHAT ARE THE KEY
STEPS?
DO I HAVE A CONTROL MEASUREMENT
THAT COVERS EACH STEP?
IF YOU DON'T HAVE A CONTROL
MEASUREMENT THAT'S MONITORING,
THAT MAY GO HAYWIRE, YOU'RE
WONDERING WHAT HAPPENED
AFTERWARDS.
IT COULD BE SOME CONTROL
MEASUREMENT COULD COVER MULTIPLE
STEPS OR CONTROL MEASUREMENTS
COULD COVER SINGLE STEP.
KEY THING INSIGHT INTO EVERY
STEP TO MAKE SURE IT'S WORKING
AS YOU'RE EXPECTING.
THIS COULD INFLUENCE YOUR PLATE
DESIGN, I DON'T NEED TO GET INTO
SPECIFICS.
THIS IS FROM THE SCREENING ASSAY
NICOLE TALKED ABOUT EARLIER.
WE'RE LOOKING AT WELLS FOR
INTERFERENCE, WELLS FOR NEGATIVE
CONTROL, POSITIVE CONTROL,
SOLVENT SYSTEM.
WE CAN ALSO LOOK AT HOW
PIPETTEING IS GOING, IN COME UP
2 ONE SINGLE STEP, AND THEN ON
COLUMNS 2-9 IN ROW A WE CAN SEE
IS THERE A GRADIENT, IT SHOULD
BE A-9 IS THE SAME AS COLUMN 2
BUT SOMETIMES IT'S NOT.
WE FOUND AN EXAMPLE, DEGRADATION
OF PROBE AMONG PIPETTEING STEPS
WHICH WE DIDN'T THINK THAT WAS
THE CASE BEFOREHAND.
NOTHING IN THE LITERATURE
SUGGESTED THAT WOULD HAPPEN.
SO THE KEY THING HERE IS YOU'RE
ENCODING QUALITY INTO THE ASSAY
SO SOMEONE ELSE IS USING IT,
THEY DON'T NEED TO THINK IS
EVERYTHING COVERED, HOW DO I
HAVE CONFIDENCE, EVERYTHING IS
ALREADY THERE.
THEY NEED TO RUN IT AND FROM THE
DIFFERENT OUTPUTS CAN
UNDERSTAND, DIAGNOSTIC CRITERIA
FOR HOW THE ASSAY IS GOING.
THIS IS AN EXAMPLE, YOU CAN GET
CONTROL CHARTING RESULTS FOR
SOME CONTROL MEASUREMENT HOW
IT'S WORKING.
THESE ARE THREE EXAMPLES OF
THINGS NOT GOING WELL.
THIS IS HAPPENING, GO BACK AND
LOOK AT SOMETHING, SOMETHING'S
NOT WORKING.
PART A YOU'RE SEEING THE MEAN IS
DECREASING ACROSS TIME.
FOR B YOU'RE SEEING THE
VARIABILITY IS INCREASING ACROSS
TIME, BIGGER ERROR BARS.
FOR C THERE'S A STEP CHANGE,
MAYBE YOU CHANGED AGENTS, YOUR
AGENT IS CHANGING IN WAYS YOU
DIDN'T EXPECT.
BY MONITORING YOU CAN HAVE
CONFIDENCE ACROSS TIME THINGS
ARE WORKING WELL AT LEAST WITHIN
YOUR LABORATORY.
ANOTHER POWERFUL TOOL SCATTER
PLOTS, YOU WANT ALL THE CONTROL
MEASUREMENTS BE INDEPENDENT,
THAT'S WHERE YOU HAVE IN PART A
ON THE Y-AXIS THAT'S THE MEAN
OD, AND ON THE X-AXIS IS OUR
CONTROL CADMIUM SULFATE, NO
RELATIONSHIP BETWEEN NUMBER OF
CELLS AND CADMIUM SULFATE
RESULTS AS LONG AS YOU'RE ABOVE
1.5 OR SO.
IF YOU LOOK AT PART B HERE YOU
CAN SEE NUMBER OF CELLS REALLY
INFLUENCES YOUR RESULTS.
YOU COULD THINK THINGS ARE
DIFFERENT BUT IT'S JUST A
FUNCTION HOW YOU PERFORMED THE
ASSAY ONE TIME AND HOW MANY
CELLS ARE THERE.
SPECIFICATION THING ABOVE 1.5 OR
1.4, OTHERWISE YOU CAN'T TRUST
YOUR RESULTS IN THE SAME WAY AS
YOU'RE EXPECTING.
HISTOGRAMS ARE IMPORTANT, NOT
ASSUME THEY ARE GAUSSIAN.
THIS IS FROM A COMET ASSAY,
CLEARLY NOT A GOOD GAUSSIAN
DISTRIBUTION.
I THINK THIS IS EXAMPLE OF WHAT
GOVERNMENT AGENCIES CAN DO,
WHERE WE PUT IN FOUNDATIONAL
PIECES THAT OTHER PEOPLE CAN
BUILD UPON AND SUPPORT
INNOVATION TO THRIVE IN
DIFFERENT AREAS, SO MANY NAMs,
SO MUCH COMPLEXITY, TO HAVE
CONFIDENCE WE THOUGHT IT WOULD
BE HELPFUL TO HAVE STEPS TO
IMPROVE CONFIDENCE.
HOPEFULLY THIS COULD SUPPORT
STANDARDIZEATION AND BROADER
ADOPTION OF NAMs.
THANK YOU FOR YOUR TIME.
[APPLAUSE]
>>THANK YOU, DR. PETERSEN.
NEXT SPEAKER AND PANEL MEMBER
DR. YVETTE SEGER, DIRECTOR OF
SCIENCE POLICY, DEPUTY DIRECTOR
OF OFFICE OF PUBLIC AFFAIRS,
DIRECTOR OF STRATEGIC SCIENTIFIC
PROGRAM ADVANCEMENT, AND MEMBER
OF THE BOARD OF DIRECTORS FOR
CENTER FOR OPEN SCIENCE AT THE
FEDERATION OF AMERICAN SOCIETIES
FOR EXPERIMENTAL BIOLOGY, FASEB,
WHICH HAS BEEN AROUND SINCE
1912, FEDERATION OF SCIENTIFIC
SOCIETIES THAT ADVANCES HEALTH
AND WELL-BEING BY PROMOTING
RESEARCH AND EDUCATION IN
BIOLOGICAL AND BIOMEDICAL
SCIENCES THROUGH COLLABORATIVE
ADVOCACY AND SERVICE TO
SOCIETIES AND MEMBERS.
FASEB IS THE LARGEST BIOLOGIC
COALITION AND POLICY VOICE,
BIOLOGICAL AND BIOMEDICAL
RESEARCHERS.
DR. SEGER HOLDS A B.A. IN
ZOOLOGY, ALSO IN POLITICS AND
GOVERNMENT FROM OHIO WESLEY AN
UNIVERSITY, RECEIVED Ph.D. IN
GENETICS FROM STONY BROOK
UNIVERSITY, PRIOR TO JOINING
FASEB WAS A A FELLOW AT
NATIONAL ACADEMYS, SENIOR POLICY
ANALYST AT NIH AND SENIOR
ANALYST AT DISCOVERY LOGIC.
>>THANK YOU.
I'M SORRY YOU HAVE TO READ MY
BIO.
IT'S A PLEASURE TO BE HERE.
I'M GOING TO LIFT THINGS UP A
LITTLE BIT TO A DIFFERENT LEVEL
BECAUSE WE'RE TALKING ABOUT
STAKEHOLDER ENGAGEMENT HERE AND
SO THERE'S NO SCIENCE IN THIS
PRESENTATION BUT I WILL BE
TALKING A LOT ABOUT SCIENTISTS.
SO AS YOU HEARD IN THE
INTRODUCTION, I'M REPRESENTING
THE FEDERATION OF AMERICAN
SOCIETIES FOR EXPERIMENT
BIOLOGY, 26 SOCIETIES, 110,000
SCIENTIST.
THERE SEEMS TO BE AN ARTIFICIAL
FIRE WALL BETWEEN TOXICOLOGY
TESTING AND BIOMEDICAL RESEARCH
AS DR. KLEINSTREUER SAID.
I'VE GOT 110,000 RESEARCHERS, WE
DON'T REPRESENT ALL SOCIETIES IN
BIOLOGY AND BIOMEDICAL RESEARCH.
AS YOU CAN SEE BY LOOKING AT THE
LOGOS WE REPRESENT THE BREADTH
OF BIOLOGY AND BIOMEDICAL
RESEARCH, MOST OF OUR
RESEARCHERS ARE ENGAGED IN BASIC
RESEARCH BUT WE DO HAVE SOME
SOCIETIES THAT START TO BRIDGE
THE CLINICAL RESEARCH, AND ONE
THING THAT YOU SHOULD KNOW ABOUT
SCIENTIFIC SOCIETIES THAT'S VERY
IMPORTANT IS THAT REQUEST FOR
INFORMATION ARE LOVE LANGUAGE.
ANYTIME YOU WANT TO ENGAGE
STAKEHOLDERS, ISSUE A REQUEST
FOR INFORMATION BECAUSE YOU WILL
HEAR THROUGHOUT MY PRESENTATION
WHAT WE LIKE TO DO IS WE LIKE TO
SHARE OUR THOUGHTS.
WE LIKE TO USE OUR SCIENTISTS TO
COME TOGETHER FOR A CONSENSUS
OPINION, NATION -- ANYTHING
ISSUED BY FASEB IS NOT ME
WRITING SOMETHING BUT BRINGING
TOGETHER A REPRESENTATION OF OUR
MEMBER SCIENTISTS USUALLY ABOUT
ONE TO TEN PERCENT TO COME
TOGETHER IN TERMS OF WHAT
COMMENTS ARE GOING TO BE IN
RESPONSE TO REQUEST FOR
INFORMATION.
AND SO RELYING ON REQUEST FOR
INFORMATION FASEB SUBMITTED
COMMENTS.
THANK YOU FOR ENGAGING US IN
THAT MANNER AND ALSO EXTENDING
THE DEADLINE TO ALLOW OTHERS WHO
MIGHT HAVE NOT HAD ALL THE
RESOURCES THAT MY TEAM HAD TO
PULL THIS TOGETHER.
AND SO LOOKING AT SOME OF THE
STRENGTHS AND ECHOES WHAT WE HAD
IN OUR COMMENTS, WHAT ARE THE
STRENGTHS IN ADVANCING NAMs?
SO SUCCESSFUL ADVANCEMENTS
DEPENDS ON ITERATIVE APPROACH TO
INFORM DECISION MAKING.
WE HEARD THIS IN THE FIRST
PANEL, OTHER PANELISTS HERE,
ECHOED IN OUR COMMENTS.
SOME POTENTIAL BARRIERS, YOU
HAVE STRENGTHS BUT YOU ALSO HAVE
THE BARRIERS.
CHALLENGES TO ADVANCING NAMs
INCLUDE LACK OF FUNDING
MECHANISMS TO FACILITATE
CHARACTERIZEATION OF NOVEL
TECHNOLOGIES AND LACK OF
MECHANISMS TO FOSTER
COLLABORATION BETWEEN ANIMAL
RESEARCHERS AND NAMs
DEVELOPERS.
I WANT TO HONE IN ON THE FIRST
PART OF WHAT WE FOCUSED ON IS,
AGAIN, THINK OF MY CONSTITUENTS.
THEY ARE UNIVERSITY-BASED
RESEARCHERS, FOR THE MOST PART.
THEY ARE GOING TO ENGAGE IN
RESEARCH FOR WHICH THEY HAVE
FUNDING.
AND SO I THINK THROUGHOUT THE
WORKING GROUP DELIBERATIONS,
THIS IS SOMETHING REALLY
IMPORTANT TO KEEP IN MIND IS
THAT RESEARCHERS AREN'T
NECESSARILY RETICENT TO PURSUE
THIS LINE OF RESEARCH, IT'S MORE
THAT THERE IS A NEED TO HAVE THE
FINANCIAL SUPPORT TO PURSUE IT.
SO WHETHER THAT COMES FROM NIH
DIRECTLY OR THROUGH PARTNERSHIP,
THIS IS SOMETHING THAT YOU WILL
HEAR OVER AND OVER AGAIN FROM
FASEB CONSTITUENTS BEING A KEY
BARRIER, IF YOU UNLOCK THAT GATE
YOU WILL HAVE A LOT MORE
INTEREST TO PURSUE THE
DEVELOPMENT OF NAMs.
SOME OF THE BEST PRACTICES YOU
HEARD THROUGHOUT THE
PRESENTATION IN THE FIRST PANEL,
EVEN MY CO-PANELIST, THERE'S A
LOT OF EXISTING RESOURCES BUT
WITH LENS OF BIOMEDICAL
RESEARCHERS FASEB REPRESENTS AND
I DON'T THINK WE'RE UNIQUE IN
SCIENTIFIC SOCIETIES, THEY ARE
USEFUL BUT THERE'S LIMITED
COMMUNITY AWARENESS.
SO IN THE TOXICOLOGY FIELD,
THERE'S A LOT OF AWARENESS BUT
MAKING THAT BRIDGE TO THE BASIC
BIOMEDICAL RESEARCH COMMUNITY
ISN'T ALWAYS THERE.
YOU HAVE TO HAVE SOMEBODY THAT'S
LOOKING FOR IT.
SIMILARLY THESE RESOURCES STILL
HAVE GAPS THAT THEY DO NOT
DIRECTLY ADDRESS RIGOR AND
REPRODUCIBILITY CHALLENGES
ASSOCIATED WITH NAMs.
AGAIN, WE'RE WITH A COMMUNITY
LOOKING SPECIFICALLY TO
TRANSITION FROM ANIMAL MODELS TO
ADOPTING NAMs AND THEIR
CONCERNS ABOUT UNDERSTANDING
RIGOR AND REPRODUCIBILITY.
THOSE ARE HIGHLIGHTS FROM OUR
RFI COMMENTS FOR THOSE WHO
HAVEN'T SEEN THEM YET, THEY ARE
POSTED ON THE FASEB WEBSITE AND
THE WORKING GROUP WILL RECEIVE A
COPY AS WELL.
SO WHY I'M HERE, HOW CAN
SCIENTIFIC SOCIETIES HELP?
ONE OF THE THINGS THAT WE'RE
VERY GOOD AT, ESPECIALLY I WOULD
SAY FASEB EXCELS AT BECAUSE WE
REMEMBER AT ANY GIVEN TIME WE'VE
REPRESENTED 25 TO 35 SCIENTIFIC
SOCIETIES, SOME COME, SOME GO,
BUT WE REPRESENT A LOT OF
SOCIETIES, WE'RE GOOD AT
CONVENING.
JUST LIKE THIS WORKING GROUP HAS
CONVENED ALL OF YOU HERE, THIS
IS WHAT FASEB HAS TO DO AS PART
OF ITS GOVERNANCE STRUCTURE TO
HAVE STATEMENTS THAT REPRESENT
ALL THE SOCIETIES.
SO SOME THINGS THAT WE DO I
WOULD SAY PRETTY WELL IS THAT WE
ORGANIZE AND PARTICIPATE IN
STAKEHOLDER MEETINGS.
SO, YOU KNOW, JUST EVEN WITHIN
OUR OWN MEMBERSHIP BUT ALSO
EXPANDING WE LIKE TO ENGAGE THE
COMMUNITY, FOSTER DIALOGUE,
INCREASE COORDINATION BETWEEN
STAKEHOLDERS.
WE'LL HAVE CLOSED DOOR FASEB
FAMILY MEETINGS, SO THAT WE CAN
TALK ABOUT WHAT'S REALLY
BOTHERING US, AND THEN A LOT OF
TIMES WE'LL HAVE PUBLIC FORA, IN
THE FORM OF VIRTUAL MEETINGS,
SOMETIMES WE OPEN THE DOORS TO
BROADER STAKEHOLDERS TO
PARTICIPATE IN OUR CONVENING.
ANOTHER THING RELATED TO THAT WE
HAVE A DEEP NETWORK OF
SCIENTISTS EAGER TO VOLUNTEER
FOR EFFORTS THAT ADVANCE
SCIENCE.
OUR VOLUNTEERS THAT WORK WITH
FASEB AMAZE ME.
THEY ARE SO PASSIONATE ABOUT THE
WORK THEY DO MAKING SURE THAT
RESEARCHERS HAVE RESOURCES THAT
ARE AVAILABLE TO THEM, SO AGAIN
I REPRESENT 110,000 SCIENTISTS,
AND MAJORITY OF THEM WHEN CALLED
TO SERVE, WILL SERVE.
AND THEY ARE EAGER TO SHARE
THEIR INPUT.
ANOTHER THING THAT FASEB DOES
REALLY WELL OR SCIENTIFIC
SOCIETIES GENERALLY IS
AMPLIFYING COMMUNICATIONS OF
RESOURCE OPPORTUNITIES AND
COLLABORATIVE PARTNERSHIPS.
YOU CAN JUST SAY AMPLIFYING
COMMUNICATION.
ONE OF THE THINGS THAT OUR
MEMBERS RELY UPON IS THEY DON'T
DO WHAT MY TEAM DOES.
IT MIGHT BE ODD BUT I LOVE TO
READ THE FEDERAL REGISTER, THE
NIH GUIDE.
THAT'S NOT EVERYONE'S CUP OF TEA
BUT IT IS THE START OF MY DAY.
SO WE CAN HELP.
YES, THERE ARE COMMUNICATIONS
COMING OUT OF NIH ABOUT THIS
WORKING GROUP, THE BLOG, THEY
MIGHT TAKE LONGER.
WE HAVE MORE FLEXIBILITY TO GO
OUT AND START COMMUNICATING.
HEY, DID YOU KNOW A WORKING
GROUP THAT IS A REQUEST FOR
INFORMATION?
NEXT, HEY THAT RFI, DID YOU MISS
THAT DEADLINE?
IT WAS EXTENDED TO SEPTEMBER 5
SO YOU STILL HAVE THE
OPPORTUNITY.
DON'T UNDERESTIMATE THE ABILITY
OF THAT TELEPHONE GAME THAT
SCIENTIFIC SOCIETIES CAN PROVIDE
BECAUSE SOMETIMES AS MANY
CHANNELS AS THE FEDERAL AGENCIES
CAN HAVE OUT THERE, SOMETIMES
THEY WANT TO HEAR FROM THEIR
PEERS.
THEY DON'T THINK IT'S PERTINENT
UNTIL THEY HEAR IT FROM THEIR
PEERS.
WE CAN DO THAT RAISING
AWARENESS.
SO HIGHLIGHTING THE
OPPORTUNITIES WE ALSO HAVE
ACTIVE ENGAGEMENT OF EARLY
CAREER RESEARCHERS, SO, YOU
KNOW, HAVING ACCESS NOT ONLY TO
ESTABLISHED INVESTIGATORS WHO
CAN HELP TURN THE TIDE ON
CERTAIN ASPECTS OR TOPICS EARLY
CAREER RESEARCHERS ARE ALWAYS
LOOKING TO SCIENTIFIC SOCIETIES
FOR WAYS TO ENGAGE AND EXPAND
THEIR INVOLVEMENT.
SO JUST TO REITERATE, IT'S
CONVENING WEBINARS, DIGITAL
MEETINGS, IN-PERSON MEETINGS,
CONVENEINGS, BRINGING
STAKEHOLDERS TOGETHER THROUGH
GOVERNANCE PROCESS OR MEETINGS
WE CONVENE ON BEHALF OF THE
OPPORTUNITY.
EVEN SOCIETIES THAT ARE NOT
MEMBERS OF FASEB LOOK TO PARTNER
WITH US BECAUSE WE'RE ALL DOING
ONE IMPORTANT THING, AMPLIFYING
THE VOICE OF SCIENTISTS.
AT THE END OF THE DAY THAT'S
WHAT'S MOST IMPORTANT TO US.
WE'VE HEARD A LOT ABOUT
DEVELOPING GUIDEANCE.
WHENEVER I'M GIVING A
POLICY-ORIENTED TALK ABOUT WHO
DRIVES POLICY DEVELOPMENT,
SCIENTIFIC SOCIETIES ARE A BIG
PLAYER IN THAT GAME AS WELL.
SOMETIMES WE WILL TAKE AN ISSUE
THAT WE THINK IS IMPORTANT TO
OUR CONSTITUENTS AND WE WILL
WRITE A REPORT AND
RECOMMENDATIONS WITH ALL THE
DIFFERENT STAKEHOLDERS, ACADEMIC
INSTITUTIONS, FEDERAL AGENCIES,
AND SO THOSE BECOME CONSENSUS
DOCUMENTS OUT OF OUR PROCESS AS
WELL.
AND GETTING BACK TO BRIDGEING
THE COMMUNICATIONS, NOT ONLY
WITH SCIENTISTS, WHICH IS A
STRENGTH, BUT GETTING BACK TO
WHAT OTHER PANELISTS HAVE SAID
IS WE DO HAVE A AGREEMENT TO
COMMUNICATE WITH THE PUBLIC.
SO, AGAIN, WE'VE SEEN SOME
REALLY NICE BOILED DOWN
TECHNICAL BUT STILL TECHNICAL
TALKS, EVEN JUST TODAY, AND
SOMETIMES YOU JUST NEED A FACT
SHEET TO GET THE INFORMATION OUT
THERE.
YOU NEED TO SIMPLIFY SO THE
PUBLIC UNDERSTANDS, SOMEONE WHO
ISN'T WORKING IN YOUR SPECIFIC
DISCIPLINE CAN UNDERSTAND IT.
SO WE HAVE EXAMPLES OF
FACTSHEETS, THESE ARE ANOTHER
BREAD AND BUTTER WHEN WE'RE NOT
READING THE FEDERAL REGISTER OR
NIH GUIDE, WE'RE MAKING A FACT
SHEET.
HOW TO COMMUNICATE IN THE
SIMPLEST TERMS SO WE GET
SCIENTISTS AND MEMBERS OF THE
PUBLIC EXCITED ABOUT THIS.
THOSE ARE MY HIGH LEVEL
COMMENTS.
I'M LOOKING FORWARD TO
DISCUSSION.
I WANTED TO GIVE SOME
ACKNOWLEDGMENT TO MY TEAM, NAOMI
IS MY ASSOCIATE DIRECTOR FOR
SCIENCE POLICY AND OUR ANIMALS
IN RESEARCH COMMITTEE WITH
NAOMI'S GUIDEANCE, THIS GROUP
HELPS COME UP WITH INITIAL
DOCUMENTATION FOR RESPONSE.
SO I LOOK FORWARD TO THE
CONVERSATION.
THANK YOU.
[APPLAUSE]
>>THANK YOU, DR. SEGER.
AS DR. CHANG MENTIONED, OUR
CO-CHAIR, OUR INDUSTRY
REPRESENTATIVE FELL THROUGH BUT
DR. MYRTLE DAVIS WAS GRACIOUS
ENOUGH TO STEP IN AND ENTER THAT
ROLE.
SO DR. MYRTLE IS A MEMBER OF THE
ACD WORKING GROUPS ON NAMs.
DR. DAVIS IS IS FROM BMS, A
GLOBAL COMPANY TO DELIVER
INNOVATEIVE MEDICINES TO HELP
PATIENTS PREVAIL OVER SERIOUS
DISEASES.
REACHED A BACHELOR'S DEGREE IN
CHEMISTRY, DOCTOR OF VETERINARY
MEDICINE FROM TUSKEGEE
UNIVERSITY, Ph.D. IN
TOXICOLOGY FROM UNIVERSITY OF
ILLINOIS, POSTDOCTORAL TRAINING
IN TOXICOLOGY, PATHOLOGY,
UNIVERSITY OF MARYLAND, WHERE
SHE WAS ALSO ASSOCIATE PROFESSOR
IN DEPARTMENT OF PATHOLOGY.
PRIOR TO JOINING BMS WAS AT NCI
AND ELI LILLY, PRESIDENT OF THE
SOCIETY OF TOXICOLOGY IN 2021.
DR. DAVIS DOESN'T HAVE ANY
FORMAL PRESENTATION BUT WAS
WONDERING IF YOU HAVE SOME
REMARKS YOU WANT TO KICK US OFF?
>>SURE.
IT'S A PLEASURE TO STEP IN.
I'M RELUCTANT TO SAY I REPRESENT
THE ENTIRE PHARMACEUTICAL
INDUSTRY TODAY BUT WHAT I WILL
DO IS PROVIDE SOME PERSPECTIVE
THAT I THINK MY COLLEAGUES WHO
ARE ALL WORKING IN THE SAME WAY
TO PROVIDE SAFE AND EFFECTIVE
MEDICINES TO PATIENTS ON A DAILY
BASIS, WHAT WE THINK ABOUT
INTERFACE WAS WHAT THIS GROUP IS
THINKING ABOUT WITH REGARD TO
NEW APPROACHES AND METHODS.
SO, ONE THING THAT HAS BEEN
REALLY FRUITFUL WITH REGARD TO
THE CONVERSATIONS BEING
INCLUSIVE OF INDUSTRY PARTNERS
SUCH AS PHARMA IS THAT WE'RE
STARTING TO LEARN MORE ABOUT
EACH OTHER AND WHAT TYPES OF
SCIENTIFIC QUESTIONS WE ALL HAVE
WITH REGARD TO WHAT WE DO.
I KNOW WHEN WE FIRST STARTED OUT
DISCUSSING NEW APPROACH METHODS
THERE WERE LOTS OF ASSUMPTION
ABOUT OUR FOCUS ON REGULATORY
EXPECTATIONS, AND I WILL SAY AS
A LEADER IN THE DISCOVERY SPACE
THERE ARE SO MANY MORE QUESTIONS
THAT WE HAVE, QUITE FRANKLY WE
CAN -- WOULD LOVE TO ANSWER WITH
MANY DIFFERENT APPROACHES, AND
THE EXCITEMENT THAT WE ALL SHARE
WITH REGARD TO ANY NEW METHOD IS
THE ABILITY TO SEE HOW IT WOULD
HELP US TO ANSWER QUESTIONS THAT
WE CAN'T ANSWER CURRENTLY, OR
QUITE FRANKLY THAT WE'RE JUST
CURIOUS ABOUT.
THAT SCIENTIFIC CURIOSITY AND
NEED IS NOT ENDEMIC TO THE
ACADEMIC COMMUNITY, NOR IS IT
ENDEMIC TO THE GOVERNMENT
COMMUNITY.
IT'S ALSO PART OF OUR COMMUNITY.
AND FOR THAT REASON WE HAVE A
LOT IN COMMON.
THE OTHER THING WE HAVE IN
COMMON IS AN EXPECTATION TO ONLY
USE ANIMALS WHEN ABSOLUTELY
NECESSARY.
THIS IS SOMETHING THAT WE HAVE
TO CONTINUE TO REPEAT BECAUSE,
AGAIN, PEOPLE HAVE SOME IDEAS
ABOUT REGULATORY EXPECTATIONS
DRIVING A NEED TO USE ANIMALS IN
RESEARCH.
AND I WILL OBVIOUSLY SPEAK A
LITTLE BIT FOR MY COLLEAGUES AT
FDA AND SAYING THERE'S NEVER
BEEN ANY TYPE OF REGULATORY
REQUIREMENT FOR USE OF ANIMALS
IN OUR WORK.
WE USE THE BEST SYSTEMS
NECESSARY TO ANSWER THE
QUESTIONS THAT HELP US TO
UNDERSTAND HUMAN RISK, AND TRY
TO PUT INTO PERSPECTIVE HOW WE
MIGHT ADMINISTER MOLECULES TO
PATIENTS SAFELY.
IF THAT IS AN ALTERNATIVE THAT
DOES NOT INCLUDE ANIMALS THAT
WOULD BE ABSOLUTELY WONDERFUL.
WHAT I HEARD FROM FOLKS ON THIS
PANEL, ALSO NICOLE AND OTHERS,
HOW THAT'S BEEN VALIDATED WELL
ENOUGH TO BE CONFIDENT IN DATA
IT PRODUCES.
AT THE END OF THE DAY I THINK AS
SCIENTISTS ALL OF US WANT TO BE
CONFIDENT IN DATA SO WHEN WE
DRAW CONCLUSIONS WE CAN DRAW
THEM WITH CONFIDENCE KNOWING THE
SYSTEM WE USE WAS APPROPRIATE
AND VALID FOR THE QUESTION WE
ASKED.
SO WITH THAT, I THINK WE HAVE SO
MUCH IN COMMON, I'M LOOKING
FORWARD TO THE QUESTIONS.
DAN ALWAYS HAS CHALLENGING
QUESTIONS SO I'M ASSUMING WE'LL
HEAR SOME OF THOSE TODAY.
AGAIN, THANK YOU FOR
REPURPOSEING ME FOR THIS ROLE AS
WELL AS THE ROLE ON THE COUNCIL.
>>THANK YOU, DR. DAVIS.
[APPLAUSE]
TO START US OFF, CERTAINLY WE'VE
HEARD A LOT FROM OUR PANEL
MEMBERS ABOUT THEIR VARIOUS
STRENGTHS.
COULD YOU REEMPHASIZE WHAT YOUR
VARIOUS ORGANIZATIONS OR SECTORS
HAVE IN TERMS OF STRENGTH IN
ADVANCING NAMs AND THEN ALSO
ELABORATE IN TERMS OF WHAT TYPES
OF CROSS-SECTOR COLLABORATIONS
ARE NEEDED TO HAVE THE GREATEST
IMPACT IF WE ARE TO ACHIEVE
SOMETHING MEANINGFUL AND
IMPACTFUL IN RELATIVELY SHORTER
PERIOD OF TIME.
DR. CARLISLE, CAN YOU KICK US
OFF?
>>THANK YOU.
AND THEN FOR THOSE KEEPING
SCORE, THERE'S AN L MISSING,
CARLISLE, L BETWEEN THE S AND E.
I THINK -- FOR OUR ORGANIZATION,
WE'RE GOOD AT A LOT OF THINGS
BUT TWO THINGS WE'RE STRONG AT,
THAT BALANCE EACH OTHER OUT, ONE
I TALKED ABOUT EARLIER IS
QUALITATIVE RESEARCH.
WE HAVE A WORLD CLASS
QUALITATIVE RESEARCH DIVISION,
FOLKS MADE A TREMENDOUS AMOUNT
OF INVESTMENT.
RWJF, I'D LIKE TO ACKNOWLEDGE
THEM AND THEIR INVESTMENT IN US,
OPERATIONALLY, BASED ON THE WORK
WE'VE DONE, IN SUPPORT OF
INITIATIVES THEY HAVE, AN THEN
OTHERS.
I'D LIKE TO ALSO JUST
ACKNOWLEDGE DR. RACHEL HENDRICKS
STIRUPS, WE DO THAT REALLY WELL.
IN TERMS OF TAKING THIS MODEL,
PERSONS WITH LIVED EXPERIENCE
MODEL, AND TAKING THE RIGHT
APPROACHES TO ENGAGE COMMUNITIES
IN A VERY TRUSTED SINCERE MANNER
TO UNDERSTAND HOW TECHNOLOGY
IMPACTS THEM AND WORKING WITH
THEM TO MAXIMIZE THE VALUE
PROPOSITION THAT SCIENCE AND
TECHNOLOGY CAN HAVE IN THOSE
COMMUNITIES.
ON THE OTHER SIDE, I'M JUST
COMING FROM A -- JUST EXPLAINING
THIS TO PCORI REVIEW TEAM, WE'VE
GOT THIS DICHOTOMY BECAUSE WE'RE
STRONG ON QUANTITATIVE SIDE,
BUILDING TECHNOLOGY.
I WAS FORTUNATE TO BRING LEAD
TECHNOLOGYISTS HAVE ME FROM
NORTHROP GRUMMON ONCE THE HEALTH
DIVISION WAS SOLD AND FOLKS
MOVED AROUND A BIT.
WE'RE GOOD AT BUILDING THAT.
AIM AHEAD, WE'VE GOT A
CLOUD-BASED INFRASTRUCTURE FOR
DATA ANALYTICS, COMMUNITY
ENGAGEMENT, DISSEMINATEING DATA
RESOURCES.
WE'RE GOOD AT A.I. AND DOING
THAT STUFF.
WHAT WE SAY, HOWEVER, IS THAT IT
CAN'T BE FOR THE SAKE OF THE
TECHNOLOGY AND A.I.
WE HAVE TO MAKE SURE THAT WE'RE
HITTING THE RIGHT VALUE.
ONE OF THE THINGS THAT I THINK
HAS CERTAINLY BEEN IMPLICIT IN
ALL THE PRESENTATIONS BUT I
DON'T THINK WE'VE REALLY
PUNCTUATED ON THAT, MY COLLEAGUE
HERE CAN UNDERSTAND, WE'RE
TALKING ABOUT LEVERAGING DATA
INFORMATION, YOU KNOW, RESOURCES
THAT ARE LARGELY BEING DERIVED
FROM, AGAIN, PEOPLE.
SO IT'S IMPORTANT TO MAKE SURE
THAT WHETHER IT BE IN EFFORTS TO
DIVERSIFY CLINICAL TRIALS,
RIGHT, YOU KNOW, INCREASE
REPRESENTATION OF DATA, THAT IN
OUR QUEST TO DO THAT, AND I
THINK AGAIN IT'S VERY TIMELY,
THE WHOLE SITUATION WITH
HENRIETTA LACKS IS, AGAIN, NOT
AS THOUGH THERE IS A MALICIOUS
INTENT, BECAUSE I THINK FOR ALL
OF US, RIGHT, AGAIN THE MORAL
COMPULSION IS THERE.
BUT IT'S DIFFICULT SOMETIMES TO
BE FULLY COGNIZANT THAT, HEY,
AND I KNOW THIS, AGAIN I'VE BEEN
A CANCER BIOLOGIST FOR MUCH OF
MY CAREER, AND WE WEAR THAT
BADGE OF HONOR, FIGHTING THE
GOOD FIGHT, RIGHT?
SO WE FEEL LIKE, HEY, IF WE'RE
IN A LABORATORY TRYING TO CURE
CANCER, WHATEVER WE'RE DOING IS
GOOD AND SORT OF IMPLICIT IS
TRUST.
AGAIN, WE HAVE TO TAKE THOSE
THINGS INTO CONSIDERATION.
AND SO AS WE, YOU KNOW, WHETHER
IT'S DIGITAL TWINS, AGAIN A.I.,
ALL OF THESE THINGS, THE
UNDERLYING RESOURCE OR DRIVER IS
DATA.
WE HAVE TO BE VERY CAREFUL
AROUND THAT IN TERMS OF THE
POLICIES AROUND THAT TO MAKE
SURE THAT WE ARE ENSURING THAT
THE RIGHT ETHICS AND EQUITY IS
IN THAT.
IN ADDITION TO SOMETHING ELSE WE
HAVEN'T TALKED ABOUT IS HUGE,
HUGE, COMMODITIZATION.
HENRIETTA LACKS'S EXAMPLE,
BIOLOGY SAMPLE WAS A COMMODITY.
WE SHOULD BE RESPECTFUL AS WE
EXTRACT AND THINK ABOUT, AGAIN,
WHAT THE PROPER INCENTIVES ARE.
YOU KNOW, COMPENSATION
MECHANISMS.
IT WAS ALWAYS SOMETHING WE
DIDN'T WANT TO TALK ABOUT,
DISCUSSION WE WERE RETICENT TO
HAVE, PARTICULARLY IN THE
ACADEMIC COMMUNITY, BUT, AGAIN,
WE'RE BEGINNING TO BROACH THAT.
IT'S REALLY IMPORTANT.
THOSE ARE THE TWO THINGS OUR
ORGANIZATION IS STRONG.
AS FAR AS ADVANCING, OBVIOUSLY,
YOU KNOW, THE ARRAY OF DATA
MODALITYS, WE REALLY WANT TO
POSITION OURSELVES TO CAPTURE
EVERY TYPE OF DATA THERE IS AND
MODEL AROUND THAT, BE VERY
ROBUST ABOUT THE DATA.
I THINK WHAT'S GOING TO BE VERY
CRITICAL, AND WE'VE HEARD
THROUGH CONVERSATIONS, GETTING
TO THE RIGHT METRICS SO ROBUST
METRICS, WE START TALKING ABOUT
EXPOSURES, ENVIRONMENT, I THINK
ABOUT SOMETHING, A CONCEPT IN
TERMS OF GENERATIONAL.
IMPACT ON GENOMES, THINGS
TRANSMITTED, WHAT'S THE
BIOLOGICAL IMPACT OF STRESS?
WE HAVEN'T ARRIVED THEY ROBUST
METRICS QUANTITATIVELY TO DO
THAT SO I THINK BETTER METRICS
BUT STANDARDIZEATION IS CRITICAL
AS WE EXPAND AROUND THESE
MODALITYS OF DATA.
>>DR. PETERSEN, DO YOU HAVE
ANYTHING TO ADD?
>>SURE.
TO REITERATE A BIT FROM WHAT I
WAS SAYING FOR MY PRESENTATION,
I THINK IN THE GOVERNMENT SPACE
THERE'S SOME REAL ADVANTAGES,
THAT WE CAN BE A CONVENEER IN
THE PRE-COMPETITIVE SPACE, WE
DON'T HAVE A LOSSER -- HORSE IN
THE RACE, WHICH TECHNOLOGY IS
GOING TO BE MOST COMPETITIVE AT
THE END, BUILDING INFRASTRUCTURE
THROUGH EFFORTS SUCH AS WHAT I
DISCUSSED IN TERMS OF VALIDATION
WORK GROUP, THAT REPORT THAT'S
OUT NOW, THERE'S REALLY -- WE
CAN HELP BUILD A FOUNDATION TO
SUPPORT EVERYONE.
AS A CONVENEER WE CAN BRING
TOGETHER DISPARATE GROUPS,
SOMETHING THAT'S BEEN VERY
INTERESTING, YOU COULD HAVE
INDUSTRY, ACADEMIC, NON-PROFIT
AND SO FORTH FOR DIFFERENT
EFFORTS, MUCH LIKE WE'RE DOING
TODAY.
GOVERNMENT-SUPPORTED EFFORT.
THE THIRD THING I'LL SAY THAT AT
LEAST THE CURRENT STRUCTURE,
THERE'S NOT AS MUCH SUPPORT AT
THE MOMENT FOR TAKING SOME OF
THOSE INTO BECOMING STANDARDS,
SO A LOT OF GOVERNMENT
SCIENTISTS, FOR MY AGENCY
STANDARDS, OMISSIONS, WE DO THAT
CARRYING FROM THE INNOVATION TO
THE -- YOU KNOW,
STANDARDIZEATION AND HAVE THAT
BE READY AND GO THROUGH NUANCES
AND WHAT CAN BE A PAINFUL
PROCESS.
>>DR. SEGER?
>>THINKING ABOUT SCIENTIFIC
SOCIETIES SPECIFICALLY,
OBVIOUSLY WE BRING TOGETHER THE
SCIENTISTS BUT IT'S CONVENING
AND CONSENSUS SO THINKING ABOUT
THE NEED FOR GUIDELINES,
STANDARDS, WE LOVE TO BE PART OF
THOSE CONVERSATIONS.
WE HAVE THE GOVERNANCE
STRUCTURES TO SUPPORT THAT,
BRINGING TO FEDERAL AGENCIES
WHAT WILL BE ADAPTED BY THE
BROADER COMMUNITY IS SOMETHING
WE'RE REALLY STRONG AT DOING,
AND CERTAINLY LIKE TO BE LEANED
UPON.
I FORGET WHO BROUGHT IT UP, NO
ONE LIKES TOP-DOWN.
AND ONE OF THE THINGS IS IF YOU
GET THINGS TO BUBBLE UP AND THE
COMMUNITY AGREES AS THEY ARE
MOVING FORWARD YOU'RE MORE
LIKELY TO HAVE THE ADOPTION,
MORE LIKELY TO HAVE A LOT OF
ENERGY AND POSITIVE ACTIVITY
TOWARDS THAT GOAL, DEVELOPING
NAMs.
>>DR. DAVIS?
>>IF WE'RE DOING WHAT WE SHOULD
BE DOING WELL, WITHIN THE
PHARMACEUTICAL INDUSTRY, WE
TRULY APPRECIATE THE NEED TO
UNDERSTAND BASIC DISEASE
MECHANISMS WELL.
IT'S FINE TO HAVE INSIGHT,
RESULTED IN A WONDERFUL
PUBLICATION OF SORTS.
BUT TO REPRODUCE THAT AND TO
DEFINE IT AS TRULY CAUSAL OR
IMPORTANT TO THE DISEASE IS
WHERE THE RUBBER MEETS THE ROAD.
AND IF WE GO DOWN THAT ROAD
WITHOUT AN APPRECIATION FOR
MECHANISM WE'LL END UP WITH
MOLECULES THAT DON'T FUNCTION AS
WELL AS WE WOULD LIKE.
WE'VE WASTEED A LOT OF TIME,
EFFORT, AND MONEY IN TESTING
THESE THINGS SO SCIENTIFIC RIGOR
NEEDED IN THE SCIENTIFIC
COMMUNITY TO UNDERSTAND DISEASE
MECHANISMS, I CAN EXPAND TO SAY
TOXICOLOGY AS WELL,
UNDERSTANDING MECHANISMS OF
TOXICITY.
THIS IS GOLD.
I MEAN, WE'RE TALKING ABOUT
INVESTING IN TECHNOLOGY, WHICH
IS GREAT.
BUT I DON'T THINK THAT, YOU
KNOW, WE SHOULD JUST FOCUS
MAINLY ON TECHNOLOGY BUT AN
UNDER PINNING OF BASIC
MECHANISTIC UNDERSTAND, I HEARD
NICOLE SAY THAT WAS THE BASIS OF
ALL HER MODEL.
I HEARD A FOCUS ON KNOWING WHAT
VITAMIN D IS DOING FOR
CHOLESTEROL WHICH RESULTED IN A
MODEL FOCUS.
AGAIN, ASSOCIATIONS WITH GREAT
BUT WE NEED THAT BASIC
UNDERSTANDING AND THAT
INVESTMENT.
I THINK FOR PHARMA WE UNDERSTAND
THAT MORE INFORMATION, THE MORE
INFORMATION WE HAVE ON
MECHANISM, THE MORE WE CAN DO.
WE ALSO UNDERSTAND THE
APPRECIATION FOR SPEED.
SO THE SECOND THING WE DO WELL
IS WE MOVE THAT, WE HAVE TO FOR
LOTS OF REASONS.
AND WE UNDERSTAND THAT YOU CAN
MAKE DECISIONS ABOUT WHAT YOU
CAN AND CANNOT DO BASED ON LACK
OF ABSOLUTE UNDERSTANDING.
THAT'S SOMETHING WE DO VERY
WELL.
WE DON'T NECESSARILY HAVE THE
LUXURY OF WAITING FOR EVERY
SINGLE DATA POINT TO BE
UNDERSTOOD BEFORE WE MAKE
DECISIONS, AND WE HAVE TO MAKE
DECISIONS BASED ON INFORMATION
THAT WE HAVE AND RIGOR BY WHICH
IT WAS GENERATED.
TO YOUR POINT, ALEX, WE CONNECT
WITH PATIENTS.
WE UNDERSTAND WHAT PATIENTS ARE
GOING THROUGH.
EVERY PHARMA HAS THE EQUIVALENT
OF A PATIENT WEEK, PEOPLE COME
IN AND TALK WITH YOU ABOUT WHAT
THEY ARE EXPERIENCING.
MY DRIVER EVERY DAY AS A
TOXICOLOGYIST UNDERSTANDING MY
GOAL IS TO DECREASE THE END OF
THAT COMMERCIAL.
I DON'T WANT TO HEAR SIDE
EFFECTS OF THE END.
I'D LIKE THEM TO NOT BE THERE.
WHEN I HEAR A PATIENT SAY I'M
TAKING YOUR DRUG AND I FEEL
BETTER THAN I DID BEFORE, NOT
WORSE, THAT'S WHAT SHOWS WE'RE
DOING OUR JOB WELL.
SO I THINK THAT CONNECTIVITY
WITH THE PATIENT, CONNECTIVITY
WITH MECHANISTIC UNDERSTANDING,
CONNECTION WITH SPEED AND
DECISION MAKING IS SOMETHING WE
DO WELL.
>>WE HEARD ABOUT LACK OF
MECHANISMS, PERHAPS BARRIERS TO
MAKE COLLABORATIONS HAPPEN.
CAN YOU IDENTIFY OTHER BARRIERS
THAT POTENTIALLY EXIST WITH AN
INTERDISCIPLINARY AND
CROSS-SECTOR COLLABORATIONS,
WHAT ADDITIONAL INCENTIVES MIGHT
TAKE PLACE OTHER THAN LACK OF
FUNDING?
OR BESIDES.
>>THAT'S MY TYPICAL ANSWER.
NO, I THINK IT'S HAVING ACCESS
TO THE RIGHT PARTNERSHIPS,
KNOWING HOW TO PARTNER WITH
INDUSTRY, HAVING THE TECHNOLOGY
THAT'S AVAILABLE TOO.
I THINK THE INTEREST IS ALWAYS
THERE.
MONEY IS ALWAYS A LIMITING
FACTOR BUT HOW DO I DO THIS
RIGHT?
IN THE FIRST PANEL THERE WAS
DISCUSSION OF BUILDING THE RIGHT
TEAMS, SO YOU'RE NOT GOING TO
BUILD THE RIGHT TEAM JUST OUT OF
ACADEMIC MEDICINE.
IT'S GOING TO REQUIRE ADDITIONAL
RESOURCES, THOSE WHO ARE
FAMILIAR WITH HOW INDUSTRY
PROCESSES WORK, SPEED, THINKING
MORE PROJECT MANAGEMENT.
SO, YOU KNOW, THINKING ABOUT
SCIENCE MORE HOLEISTICALLY
INSTEAD OF MECHANISTICALLY WOULD
BE WHAT I WOULD ADD ULD ADD TO
THAT COMMENTARY.
>>THERE ARE TREMENDOUS
PRESSURES WE FACE IN ACADEMIA,
INDUSTRY, AROUND INTELLECTUAL
PROPERTY, THE NEED TO PUBLISH,
IN MY OPINION ARE BARRIERS OR
IMPEDIMENTS TO COLLABORATION,
AND CERTAINLY, YOU KNOW, AGAIN,
DATA INTEROPERABILITY.
I'LL NEVER FORGET DURING THE
CANCER MOONSHOT INITIATIVE BEING
AT ASCO WITH VICE PRESIDENT
BIDEN ADMONISHING SCIENTISTS,
YOU HAVE TO DO A BETTER JOB
LIBERATEING AND SHARING DATA.
WE FELT THAT GESTALT.
WHEN YOU GO HOME TO YOUR
INSTITUTIONS YOU'RE FACED WITH
PRESSURES OF THINGS YOU HAVE TO
DO TO COMPETE.
SO REALLY COMING TOGETHER
COLLECTIVELY TO FIND THE RIGHT
PRE-COMPETITIVE MODELS THAT
ENABLE US TO COLLABORATE AND
SHARE WITHOUT VACATING OR, YOU
KNOW, AGAIN, SORT OF LOSING HOLD
OF THINGS THAT YOU REALLY NEED
THAT ARE THE ACADEMIC OR
INDUSTRIAL SORT OF, YOU KNOW,
LIFE BLOOD FOR INDUSTRY.
I THINK THAT'S IMPORTANT.
>>OTHERS CARE TO ADD TO THOSE?
>>SURE.
I THINK ONE THING WE'RE TRYING
TO ADDRESS THROUGH VALIDATION
WORK GROUP, HOW DO YOU VALIDATE
NAMs, AND UPDATING GUIDEANCE
THAT WAS LAST, I DON'T KNOW, IS
IT 25 YEARS OLD, SOME DINOSAUR,
IT'S BEEN HERE FOR AGES.
I THINK THAT'S ONE THING AS A
NEW GOVERNMENT-WIDE TO REMOVE
BARRIER.
I CAN'T SPEAK FOR OTHER
AGENCIES.
IF YOU LOOK AT THE ICCVAM
MEETINGS, HERE IS WHAT WE NEED,
SOME CONSIDERATIONS WE HAVE TO
USE THIS FOR SOME DECISION
MAKING.
I WOULD SAY A BIT OF NIST BIAS
HERE BUT I THINK THERE'S MORE
KNOWN FOR INNOVATION, OFTEN IT'S
NOT AS APPRECIATED TO UNDERSTAND
ASSAYS WELL OR TO UNDERSTAND
WHAT CAN GO WRONG AS WE PUBLISH
EXCITING FINDINGS AND MOVE ON.
THE GAP WE'RE TRYING TO FULFILL
BETWEEN INNOVATION AND THEN
APPLYING FOR A COMPANY MAKING
DECISION OR REGULATORY DECISION
OR SOME OF THAT.
THERE'S A WINDOW THAT IS --
THERE COULD BE MORE SUPPORT FOR.
>>ALL RIGHT.
APPRECIATE THE THOUGHT ON HAVING
TO BALANCE THAT.
I THINK GOING BACK TO YOU, DR.
PETERSEN, YOU MENTIONED A NUMBER
OF COLLABORATIONS ACROSS VARIOUS
FEDERAL AGENCIES.
DID YOU FIND ANY BEST PRACTICES
FOR SHARING INFORMATION ACROSS
THOSE DIFFERENT ORGANIZATIONS OR
SECTORS THAT WOULD HELP DRIVE
NAMs DEVELOPMENT, ESPECIALLY
IN TERMS OF APPLICATION TO HUMAN
OR MAKING IT MORE HUMAN
RELEVANT?
>>ONE OF THE BEST PRACTICES IN
GENERAL THERE'S A LOT OF WORK
WITH ICCVAM TRYING TO HAVE
TRANSPARENCY.
THERE'S ALL THESE ASSAYS.
WHAT ARE REGULATORS WANTING AND
NEEDING?
YOU WOULD NOT BELIEVE HOW MANY
CALLS OR HOURS.
YOU NEED ECOTOXICITY, OR
SENSITIZEATION, WHAT DO YOU
NEED?
THERE'S DOCUMENTS, PEOPLE
OUTSIDE THE AGENCIES CAN
UNDERSTAND WHAT'S HAPPENING,
SOMETIMES MULTIPLE WAYS FROM
OUTSIDE YOU WOULD HAVE NO IDEA
IT'S BEING DONE THAT WAY.
IN TERMS OF -- THAT WOULD BE ONE
BEST PRACTICE.
WE TALKED ABOUT REACHING OUT TO
PATIENTS, UNDERSTANDING THEM,
BUT THERE'S ALSO A LOT OF
UNDERSTANDING EACH OTHER,
DIFFERENT AGENCIES, NICOLE HAD A
PRESENTATION ABOUT CENTERS, EPA,
NEEDS, REALLY THE DIALOGUE
BETWEEN UNDERSTANDING WHAT
AGENCIES ARE NEEDING, WHAT THEY
ARE DOING, EVEN WITHIN THE
GOVERNMENT.
ALSO THERE COULD BE INTERESTING
PERSPECTIVES FROM INDUSTRY,
ACADEMIA THAT COMPLEMENT.
OH, YEAH, WE ALSO WANT THIS, FOR
OUR OWN DECISION MAKING, IF WE
HAD CONFIDENCE IN IT, IT COULD
BENEFIT US.
I THINK DISCUSSIONS AND
TRANSPARENCY AND PROMOTING THAT
GOES A LONG WAY.
>>THANK YOU.
DR. SEGER, WHEN YOU WORKED WITH
VARIOUS SOCIETIES, IS THERE
SOMETHING THAT YOU APPLY IN
TERMS OF BEST WAY TO APPROACH
THEM?
>>IT'S A GOOD QUESTION.
IT REALLY IS FIGURING OUT WHAT
ARE THE BIGGEST PAIN POINTS, IF
THERE ARE SOLUTIONS TO ADDRESS
THOSE, NOT SWEAT THE SMALL
STUFF.
YOU KNOW, IT SOUNDS SIMPLE BUT
WHAT ARE THE BIG THINGS THAT OUR
GROUP NEEDS TO TACKLE, WHAT
RESOURCES NEED TO BE THERE AND
FOCUS ON THOSE.
AND STICK TO OUR STRENGTHS.
SO A LOT OF TIMES THINKING ABOUT
RFIS WE DON'T RESPOND TO EVERY
QUESTION IF THEY ARE NOT
APPLICABLE OR WE DON'T HAVE THE
EXPERTISE, WE DON'T HAVE IT BUT
YOU MIGHT WANT TO LOOK AT THIS
OTHER GROUP.
THAT'S A LEVEL OF HUMILITY THE
COMMUNITY NEEDS TO HAVE, JUST
THINKING ABOUT I DON'T HAVE ALL
THE PIECES TO THIS NAMs PUZZLE
BUT I'VE GOT TO WORK WITH
EVERYONE ON THIS PANEL TO FIGURE
OUT WHAT WE'RE GOING TO AGREE
UPON, YOU KNOW, WE MIGHT BE
SAYING THE SAME THING IN A
DIFFERENT LANGUAGE, SO
STANDARDIZEING IS HELPFUL.
WE HAVE TO STANDARDIZE ACROSS
MEMBER SOCIETIES, WE FALL INTO
JARGON, SOMETHING WE WATCH FOR.
>>IN THE REMAINING FOUR MINUTES
CAN YOU SPEAK TO WHAT YOUR
ORGANIZATION IS DOING TO ADVANCE
TRAINING NEXT GENERATION
SCIENTISTS.
WE'LL START WITH DR. SEGER.
>>SO MANY QUESTIONS.
NO, SO, YEAH, I MEAN TRAINING
THE NEXT GENERATION IS VERY
IMPORTANT TO ALL SCIENTIFIC
SOCIETIES.
WE RECOGNIZE WE'RE THE STANDARD
BEARERS FOR DISCIPLINES SO
RECOGNIZING AND BUILDING
RESOURCES FOR INTERDISCIPLINARY
RESEARCH, RECOGNIZING A LOT OF
OUR SENIOR LEADERSHIP, THAT THE
SCIENTIFIC COMMUNITY, THE WAY
SCIENCE IS DONE IS A LOT
DIFFERENT FROM WHEN THEY WERE
GRAD STUDENTS OR POSTDOCS, SO
PARTNERS CREATEIVELY, THINKING
HOW WE USE CONFERENCES TO BE THE
BEST PLACE TO BRING TOGETHER
DIFFERENT STAKEHOLDERS, AND ALSO
A LOT OF OUR SOCIETIES ARE
THINKING HOW DO THEY -- I ASK
FOR FUNDING BUT SOME SOCIETIES
WILL GIVE THE FUNDING OR WILL
OFFER COURSES AND WORKSHOPS,
THOSE OPPORTUNITIES TO DEVELOP
SKILLS, RECOGNIZING THAT IT'S
NOT EVERYONE GOING TO P.I.,
ACADEMIC P.I. SCHOOL, THAT WE
HAVE TO DEVELOP MORE SKILLS
BEYOND.
>>THE LAST POINT WAS POIGNANT.
WE'VE BEEN LOOKING TO DEVELOP
STRONG RELATIONSHIPS AT THE
COMMUNITY COLLEGE LEVEL, AND
WORK WITH SOME OF THOSE LIKE
NORTHERN VIRGINIA COMMUNITY
COLLEGE, IN ADDITION TO SOME OF
THE OTHER UNDERRESOURCE
INSTITUTIONS, ACADEMIC
INSTITUTIONS, WORKING THROUGH
INTERNSHIP PROGRAMS, BRINGING
THEM ON FULL-YEAR COOPERATIVE
PROGRAMS, WAYS TO TIE THAT WORK
INTO ACTUAL CREDIT SO THEY CAN
HELP ADVANCE THROUGH THEIR
ACADEMIC PROGRAMS, SO THAT'S
ESSENTIALLY THE WAYS WE'RE GOING
ABOUT DOING THAT.
MOST OF THE FOCUS BASED ON HOW
WE'RE BUILT IS, AGAIN, AROUND
THE DATA SCIENCE PIECE.
WE DO HAVE A VERY STRONG
ACADEMIC FACULTY, ADPH, WE'VE
GOT SOMEBODY HERE FROM ISB, ROB
MOREOWITZ IS A FACULTY MEMBER AT
ISB SO WE'RE PROUD ABOUT THAT.
SO MOST OF OUR WORK IS VIRTUAL
IN SILICO.
WE DID HAVE CARD CARRYING NADPH
IN SOME TOP MEDICAL CENTERS IN
THE COUNTRY SO WE'RE LOOKING AT
WAYS TO ALSO -- THAT'S A
CRITICAL PIECE.
WE NEED TO BE COGNIZANT, MUCH OF
THE STUFF WE'RE TALKING ABOUT
HERE, VIRTUAL OR DIGITAL, THE
CHALLENGE TO MAKE SURE WE
FUNCTIONALLY VALIDATE THOSE
THINGS, AGAIN USING NOVEL
ALTERNATIVE METHODS AND OTHERS
TO DO THAT.
SO WE HAVE THOSE RELATIONSHIPS
AS WELL.
>>THANK YOU.
DR. DAVIS?
>>YES, SO ONE OF THE JOYS THAT
WE ALL EXPERIENCE IN THE SUMMER
IS HAVING TONS OF SUMMER INTERNS
AT BRISTOL MYERS SQUIBB, WHO
COME IN, NOT JUST TO WATCH.
WE HAVE RIGOROUS REVIEW OF
PROPOSALS FROM SCIENTISTS EVERY
YEAR, THEY WILL HAVE AN ACTUAL
PROJECT THAT CAN RESULT IN
DEEPER UNDERSTANDING OF A NEW
METHOD, OR BETTER YET,
UNDERSTANDING HOW TO TEST WITH
RIGOR AND HYPOTHESIS AND GET THE
ANSWERS THAT MATTER.
THE OTHER THING WE DID WITH
BRISTOL-MYERS SQUIBB, WE
PARTNERED WITH THE SOCIETY OF
TOXICOLOGY TO FUND A STUDENT
AWARD.
WE FOUND EVEN WITHIN THE SOCIETY
OF TOXICOLOGY THERE WAS LOTS OF
FUNDING FOR UNDERGRADUATES BUT A
REAL GAP WITH REGARD TO GRADUATE
STUDENTS.
AND THE ONE THING THAT MADE OUR
AWARD A LITTLE DIFFERENT IS THAT
WE REALLY WANTED TO IDENTIFY
FACULTY MEMBERS WE COULD
SUPPORT.
MONEY DOES NOT GO TO GRADUATE
STUDENT.
IT GOES TO FACULTY MEMBER SO
RESEARCH PROGRAM BY WHICH THE
STUDENT IS MATRICULATING TO
Ph.D. IS SUPPORTED THROUGH THE
FUNDS BMS PROVIDES.
WE DO NOT MAKE STIPULATION
RESEARCH HAD TO BE RELEVANT TO
BMS, JUST RIGOROUS WITH REGARD
TO HYPOTHESIS TESTING.
THAT'S SOMETHING WE PUT OUR
MONEY WHERE OUR MOUTHS WERE ON
THAT ONE.
AND, AGAIN, PARTNERING WITH
ACADEMIC INSTITUTIONS IN GENERAL
JUST TO TRY TO FIND HOW WE HELP
STUDENTS UNDERSTAND WHAT WE CAN
DO, LOTS WANT US TO TALK ABOUT
JOBS BUT WE QUICKLY TURN THE
CONVERSATION TO WHAT IS YOUR
RESEARCH AND HOW ARE YOU EXCITED
ABOUT SCIENCE.
SO THAT'S SOMETHING WE DID.
>>THANK YOU.
>>WE HAVE INTERNSHIP PROGRAMS
AT NIST.
ANOTHER THING WE DO TO GIVE
TALKS AT PLACES PEOPLE ASK US.
I COULD TALK ABOUT QUALITY ALL
DAY LONG, PEOPLE ARE INTERESTED
HOW THIS IS WITH NAMs, PLEASE
REACH OUT, I'M HAPPY TO DISCUSS
FURTHER IN DIFFERENT VENUES.
>>I THINK WE'RE AT THE TOP OF
THE HOUR.
SO LET'S THANK OUR PANEL MEMBERS
FOR THE ACTIVITY SESSION.
[APPLAUSE]
I BELIEVE WE HAVE A LUNCH BREAK.
>>THANKS, EVERYONE.
WE'LL BE BACK AT 1:00.
>>OKAY, WELCOME BACK,EVERYBODY.
FOR THE AFTERNOON SESSION, WE'RE
BRINGING LEADERS IN THEIR FIELDS
TO CONVERSATION ABOUT HIGH
PRIORITY NEEDS THAT CROSS
DISCIPLINES, TECHNIQUES,
SECTORS.
WE'LL START THE WORKING GROUP
WITH MEMBER SZCZEPAN BARAN.
DR. BARAN, THE FLOOR IS YOURS.
>>THANK YOU SO MUCH FOR HAVING
US PARTICIPATE IN THIS SESSION.
AGAIN, THE TITLE IS DEVELOPING
INTEGRATED AND MULTI-SYSTEM
MODELS.
SO MY NAME IS DR. BARAN, AT
VERISIM LIFE, BEFORE THAT AT
NOVARTIS HEADING UP EMERGING
TECHNOLOGIES FOR ALMOST A
DECADE.
TO SET THE STAGE FOR THIS
SESSION, WE'RE GOING TO TALK
ABOUT HOW WE CAN INTEGRATE
VARIOUS TECHNOLOGIES, VARIOUS
NAMs TOGETHER FOR THE MORE
POWERFUL IMPACT ON DRUG
DISCOVERY AND DEVELOPMENT, BUT
ALSO WE WANT TO LOOK AT OTHER
INDUSTRIES AS WELL, BROUGHT UP
EARLIER, HOW SILOED WE ARE.
SO HERE ALSO WHEN WE'RE GOING TO
BE TALKING ABOUT THE QUESTIONS
THAT WE HAVE, WE'RE GOING TO TRY
TO ADDRESS IT FROM HOW CAN WE
LEARN FROM VARIOUS INDUSTRIES,
NOT JUST PHARMACEUTICAL BUT ALSO
HYDROCHEMICAL, ENVIRONMENTAL,
AND OTHERS.
THERE'S DEFINITELY A NEED FOR
THAT.
AGAIN, I THINK THE ADDITIVE
ASPECT LIKE IN SILICO, IN VITRO
AND IN VIVO, THE CALL TALKED
ABOUT SKIN SENSITIZEATION ASSAY,
BROUGHT TOGETHER TO TOGETHER TO
DEVELOP OECD GUIDELINE.
TODAY THE QUESTIONS ARE FROM
THAT PERSPECTIVE.
ALSO TODAY I'M NOT GOING TO
INTRODUCE EACH PANELIST HERE.
I'LL ASK THEM TO INTRODUCE SO
I'M NOT JUST READING FROM A
PAGE.
I'M GOING TO KICK OFF TO GRACA
TO KICK OFF WITH AN
INTRODUCTION.
>>THANK YOU.
GOOD AFTERNOON.
I'M GRACA ALMEIDA-PORADA,
PROFESSOR OF REGENERATIVE
MEDICINE AT WAKE FOREST
INSTITUTE FOR REGENERATIVE
MEDICINE.
I'D LIKE TO THANK NIH AND THE
ORGANIZERS FOR INVITING ME TO
PARTICIPATE IN THIS SYMPOSIUM.
I'M VERY HAPPY TO BE HERE
BECAUSE I THINK THERE'S HIGH
PRIORITY NEED TO DEVELOP AND
VALIDATE MULTI-SYSTEM APPROACHES
THAT RELIABLY REPRODUCE HUMAN
BIOLOGY.
THE FOCUS OF MY RESEARCH IS TO
DEVELOP CELL AND GENE THERAPY
PLATFORMS TO TREAT PATIENTS WITH
DISORDERS, TO THAT END I USE
ANIMAL MODELS, I USE IN SILICO
AND I USE IN VITRO MODELS.
SO, TO GIVE YOU A LITTLE BIT OF
AN IDEA HOW I'VE USED THESE
TECHNOLOGIES, OF COURSE I'M NOT
GOING TO TALK ABOUT THE IN VIVO
MODELS BECAUSE IT'S NOT WHAT
WE'RE HERE FOR, BUT USING IN
SILICO MODELS AND COOPERATING
WITH EXPERTS IN THE FIELD OF
MOLECULAR DYNAMIC SIMULATIONS WE
HAVE BEEN ABLE TO INSERT
MUTATION IN THE -- THE SAME
MUTATION THAT OCCURS IN SICKLE
CELL PATIENTS IN SILICO, IN
SHEEP, AND PREDICT THAT MUTATION
WOULD CAUSE WHAT OCCURS IN HUMAN
PATIENTS.
FROM THAT DATA WE COLLABORATED
WITH OTHER INVESTIGATORS,
EXPERTS AT MAKING MODELS, AND
THROUGH CRISPR/Cas TECHNOLOGY
THEY WERE ABLE TO ACTUALLY
CREATE AN ANIMAL MODEL OF SICKLE
CELL DISEASE.
MOVING INTO INTEGRATED
MULTI-ORGANS ON A CHIP, WE USE
THESE SYSTEMS WITH ORGANOIDS TO
ADDRESS ASPECTS OF GENE THERAPY,
CURRENTLY FOCUSED IN STUDYING
AAV GENE THERAPY USING DIFFERENT
SEROTYPES, AND SO USE THESE
MULTI-SYSTEM ORGANOIDS TO
PREDICT TOXICITY AND EFFICACY,
AND WE HAVE -- BECAUSE WE ARE
DOING THESE IN VITRO MODELS AND
IN VIVO MODELS, WE HOPE WE CAN
COMPARE THE RESULTS THAT WE'RE
GETTING WITH OUR IN VITRO MODELS
USING THE MULTI-SYSTEM
APPROACHES TO WHAT WE'RE GETTING
INTO OUR IN VIVO MODELS AND
COMPARE TO WHAT PATIENTS OR
WHAT'S BEEN REPORTED IN CLINICAL
TRIALS USING AAV.
SO, SO FAR WE'VE GOTTEN VERY
INTERESTING DATA, AND ALSO
ANOTHER ASPECT THAT WE ARE
ADDRESSING IS TO TEST THE OTHERS
THAT ASTRONAUTS MAY -- OR
STRESSORS THAT ASTRONAUTS MAY
ENCOUNTER WHILE IN DEEP SPACE.
SO, WE USE THESE ORGANOIDS TO
NOT ONLY ADDRESS PROBLEMS THAT
THEY CAN ENCOUNTER SUCH AS
RADIATION, VLCs, THAT CAN BE
HARMFUL FOR THE ASTRONAUTS AND
DEVELOP COUNTERMEASURES USING
ORGANOIDS OR MULTI-SYSTEM
ORGANOIDS SO THAT WE CAN FIND
THOSE COUNTERMEASURES AND USE
THEM TO PREVENT THOSE HAZARDS IN
THE FUTURE FOR THOSE DOING SPACE
TRAVEL.
I THINK THAT IDEALLY WITH THE
SYMPOSIUM WE CAN FIND COMMON
GROUND AND MOVE FORWARD TO
DEVELOP THESE TECHNOLOGIES THAT
I THINK WILL BE PRICELESS IN
TERMS OF FINDING BETTER
SOLUTIONS FOR THE PATIENTS AND
HAVING BETTER ANSWERS THAN THOSE
THAT WE FIND NOW USING JUST
ANIMAL MODELS.
THANK YOU.
>>THANK YOU, GRACA.
DO WE HAVE FOLKS ONLINE?
BLANCA, CAN WE PASS TO YOU FOR
INTRODUCTION?
>>HI.
CAN YOU HEAR ME?
>>YES, WE CAN.
>>THANK YOU.
WELL, I'M BLANCA RODRIGUEZ, I'M
A PROFESSOR OF COMPUTATIONAL
MEDICINE, UNIVERSITY OF OXFORD.
OUR SPECIALTY IN MY TEAM IS
DEVELOPMENT OF COMPUTATIONAL
METHODS FOR UNDERSTANDING
HEARTS, WE FOCUS SPECIFICALLY ON
THE HEART OWN THOUGH WE'VE MADE
SOME WORK ALSO IN OTHER ORGANS.
OUR MAIN GOAL IS TO DEVELOP THE
TWO PARADIGMS OF IN SILICO
TRIALS, DEVELOPMENT OF NEW
THERAPIES, HUMAN-BASED MODEL AND
SIMULATION BASED TECHNOLOGY, AND
OTHER COMPUTATIONAL APPROACHES
TO MIMIC WHAT IS DONE IN
CLINICAL TRIALS BUT USING
SIMULATIONS.
WE INTERACT QUITE A BIT WITH
EXPERIMENTALISTS AND CLINICIANS
THAT GATHER DATA THAT ARE
COMPLEMENTARY TO OUR APPROACHES
SO WE USE EXPERIMENTAL AND
CLINICAL DATA TO BUILD OUR
VIRTUAL ORGANS AND VALIDATE
RESULT OF OUR SIMULATIONS SO
CREDIBILITY OF MODELING AND
SIMULATIONS FOR THEIR UPTAKE,
NOT ONLY IN ACADEMIA BUT ALSO IN
INDUSTRY AND REGULATORY
SETTINGS.
WE COLLABORATE QUITE A BIT WITH
INDUSTRY AND WE HAVE BEEN
WORKING ALSO IN THE REPLACEMENT
OF ANIMAL EXPERIMENTS IN THIS
CONTEXT USING HUMAN-BASED
MODELS.
THE INTERNATIONAL PRIZE FOR
STUDIES IN A HAVE POTENTIAL TO
REPLACE ANIMALS, AND I HAVE ALSO
COLLABORATED IN DEVELOPING THE
FRAMEWORK, THE CONCEPTUAL
FRAMEWORK FOR REGULATORY USE OF
THESE TECHNOLOGIES BOTH WITH THE
FDA AND THE EUROPEAN AGENCY.
THANK YOU.
>>GREAT.
THANKS, BLANCA.
IF YOU'RE NOT AWARE, YOUR VIDEO
IS NOT SHOWING UP, IF YOU WANT
TO TRY TO ADDRESS THAT WHILE WE
GO THROUGH INTRODUCTIONs, THAT
WOULD BE FANTASTIC.
ROSEER?
>>THANK YOU FOR THE INVITATION.
SORRY I CANNOT JOIN IN PERSON,
BUT IT'S A PLEASURE TO BE HERE.
I AM ROSER VINTO, GROUP LEADER
IN CAMBRIDGE IN THE U.K., WITH
TEAM INTEREST IS IN THE
DEVELOPMENT, REGENERATION AND
FUNCTION OF CAUSAL LYMPHOID
TISSUES, USING QUANTITATIVE
TOOLS, SO WE USE, DEVELOP,
DIFFERENT STATE OF TECHNOLOGIES,
GENOMICS, BIOINFORMATICS AND
ALSO GENETIC EDITING AND
BIOENGINEERING TOOLS.
SO, WE HAVE BEEN USING NAMs
SINCE WE STARTED THE TEAM.
I WILL FOCUS ON OUR WORK IN THE
UTERUS BECAUSE IT IS ONE OF THE
MOST STUDIES TISSUES.
WE HAVE BENEFIT A LOT FROM THE
NAMs.
IT IS FASCINATING TISSUE BECAUSE
IT REGENERATES MORE THAN 400
TIMES IN WOMEN'S LIFETIME, IT'S
A PERFECT REGENERATION, WITHOUT
THE SCARRING, INVOLVES IN A LOT
OF DISEASES INCLUDING PROBLEMS
WITH MENSTRUAL CYCLE,
ENDOMETRIOSIS WHICH AFFECT MORE
THAN 30% OF WOMEN WORLDWIDE.
AND THIS IS QUITE DIFFERENT IN
MOUSE.
WE HAD TO USE NAMs ALSO FOR
THIS REASON.
BASICALLY THE WAY WE'VE GONE
THROUGH IT FIRST FOCUSING ON IN
VIVO DATA, MAKING IN SILICO
MODELS, AND FOR THESE WHAT WE'VE
BEEN DOING IS TO TAKE
MEASUREMENTS OF INDIVIDUALS
ACROSS THE MENSTRUAL CYCLE AND
THESE MEASUREMENTS INCLUDED
TRANSCRIPTOME, EPIGENOME,
BIOINFORMATICS AND MACHINE
LEARNING TO INTEGRATE THE DATA
AND BUILD A MODEL.
HERE WE HAVE ALSO BEEN BUILDING
BIOINFORMATIC TOOLS, INCLUDING
USING ALL THESE MULTI-MODAL
INFORMATION TO STUDY CELL-CELL
COMMUNICATION.
A MAIN INTEREST, LIKE GOOGLE
MAPS OF TISSUE, IN THIS CASE
UTERUS, HAS BEEN TO BENCHMARK
AND ALSO IMPROVE THE CURRENT IN
VITRO MODELS AND IN PARTICULAR
ORGANOIDS, AND FOR THIS WE HAVE
BEEN TAKING THE SINGLE CELL
MEASUREMENTS IN IN VITRO MODELS
AND THEN USE AND DEVELOP
BIOINFORMATICS TO COMPARE IN
VITRO MODELS, IN VIVO YOU HAVE
INHIBITION IN REGENERATION, BY
ADDING INHIBITOR MOLECULE IN THE
ORGANOIDS WE COULD IMPROVE THEM,
AND WE'RE ALSO NOW DOING ON
THESE ALSO SIMILAR COMPARISONS
TO ALSO UNDERSTAND HOW WELL THE
DISEASE IS RECAPITULATED IN
VITRO, OR SPECIFIC PERTURBATION
WILL BE RECAPITULATED, I FOCUS
ON THE WORK IN THE UTERUS, ALSO
STRONG INTEREST IN IMMUNE SIDE,
SIMILAR APPROACH OF IN VITRO/IN
VIVO APPROACH.
THANK YOU.
>>THANK YOU.
TERRY?
>>IT'S A PLEASURE TO BE HERE
AND HAVE THE OPPORTUNITY TO
CONTRIBUTE A LITTLE BIT TO THIS
NOBLE EFFORT.
I'M CURRENTLY SERVING AS THE
HEAD INVESTIGATIVE TOXICOLOGY AT
ABBVIE, ESSENTIALLY WORK CLOSELY
WITH DISCOVERY BUILDING FIT FOR
PURPOSE, WE DO IN VITRO ASSAYS,
WE HELP TO ESTABLISH A COMPLEX
IN VITRO MODELS GROUP WITH
EXPERTISE IN CHARACTERIZING
MODELS, WE BUILT OUR OWN MODELS
IN MANY CASES BUT PREFER WITH
THE TIME WE HAVE AND RESOURCES
IT'S MUCH MORE EFFICIENT TO
CONTRACT OR BRING THAT
TECHNOLOGY IN, THAT WOULD BE THE
MOST PREFERRED.
BUT THROUGH THIS PROCESS WE'VE
GAINED A LOT OF EXPERIENCE IN
WHAT IT TAKES TO BUILD AND
MAINTAIN THESE MODELS.
WHAT SOME STRENGTHS AND
WEAKNESSES ARE.
IT'S BEEN REALLY VALUABLE.
I ALSO HAD THE OPPORTUNITY
RELATED TO THIS TO SERVE AS THE
CHAIR FOR THE IQMPS AFFILIATE IN
THE PAST, QUITE REWARDING,
HELPED ME TO UNDERSTAND A
BROADER INDUSTRY PERSPECTIVE
REALLY FROM PHARMACEUTICAL
COMPANIES AS TO HOW THEY ARE
APPLYING NAMs IN THEIR SAFETY
ASSESSMENTS, CHALLENGES THEY ARE
FACING.
I'M PROUD OF WHAT THE GROUP IS
DOING, NO LONGER WORKING CLOSELY
WITH THEM BUT I THINK THEIR
TALLY IS UP TO 15 PUBLICATIONS
SINCE 2018, 2019.
UNPRECEDENTED ENGAGEMENT IN
INDUSTRY REGARDING A NEW
TECHNOLOGY.
ANOTHER MAJOR EFFORT I'VE
UNDERTAKEN AT ABBVIE,
ESTABLISHED A COMPUTATIONAL
TOXICOLOGY GROUP.
I'M A TOXICOLOGYIST BY TRAINING
BUT I HAVE MACHINE EXPERTS IN
THE GROUP, THIS IS REALLY
OPENING OUR EYES TO THE NEED FOR
DATA AND STRUCTURE OF DATA WHICH
IS CRITICAL TO APPLYING ANY
ADVANCED ANALYTICS.
I THINK THIS HAS GIVEN ME A
BROAD EXPOSURE TO NAMs.
I'M FORTUNATE TO BE THERE
APPLYING THEM, TO SOLVE
PROBLEMS, TO HELP PRIORITIZE AND
HOPEFULLY PROGRESS THE SAFEST
COMPOUNDS FORWARD.
>>THANKS FOR SHARING YOUR
KNOWLEDGE.
NOW THE FUN PART, THE QUESTIONS.
TERRY, WE'LL START WITH YOU.
WHAT BARRIERS ARE THERE TO THE
USE OF HYBRID MODELS?
BY HYBRID I MEAN AGAIN COMBINING
IN SILICO, IN VITRO, IN VIVO,
AND WHAT ARE CHALLENGES AND
INCENTIVES NEEDED TO OVERCOME
THE SPECIFIC CHALLENGES?
>>CHALLENGES ARE SIGNIFICANT IN
SOME CASES.
THERE ARE LOTS OF DIFFERENT
KINDS OF DATA, YOU JUST WENT
OVER THERE .
A LOT OF IN VITRO DATA IS
CONSISTENTLY KEPT.
MOST COMPANIES, AND THERE'S
INSTITUTIONS, PUBLIC DATABASES
THAT HAVE THAT INFORMATION.
HOPEFULLY THOSE CAN BE LINKED TO
MOLECULES OF INTEREST, LIKE
PHARMACEUTICALS OR IN SOME CASES
COULD BE CHEMICALS.
WE WANTED TO BRING THE CHEMICAL
INDUSTRY IN AS WELL.
SO HAVING THE RIGHT DATA IN THE
RIGHT FORMAT IS CRITICAL.
WE'RE LACKING I THINK
SIGNIFICANTLY IN SOME CASES IN
HAVING THE RIGHT DATABASES.
WE HAVE A LOT, BUT I THINK
THAT'S A GREAT PLACE FOR FUTURE
INVESTMENT.
ALSO LEARNED QUITE A BIT ABOUT
IN VIVO DATA, GETTING
TRANSLATION PIECE, YOU KNOW.
CLINICAL DATA IS IN A GOOD STATE
I WOULD SAY, YOU KNOW, AS FAR AS
ITS CONDITION.
IT USES CONSISTENT TERMS, MEDRA
TERMS ARE APPLIED.
PRE-CLINICAL DATA ON THE OTHER
HAND IS DIFFERENT.
PHARMACEUTICAL COMPANIES HAVE
LARGE DATABASES OF PRE-CLINICAL
DATA THEY HAVE GENERATED OVER
TIME.
THERE'S A LOT OF EXTRA STRUGGLES
TO TRY TO USE THAT DATA, TERMS
ARE DIFFERENT.
PATHOLOGISTS MAY NOT USE THE
SAME TERM TO DESCRIBE LESIONSS.
TRANSLATING FROM PRE-CLINICAL TO
CLINICAL IS QUITE DIFFERENT
BECAUSE THE DATA THEMSELVES ARE
VERY DIFFERENT.
, YOU KNOW, PRE-CLINICAL DATA IS
ESSENTIALLY HISTOLOGY, RIGHT?
WHEREAS CLINICALLY YOU HAVE
HISTOPATHOLOGY -- EXCUSE ME,
CLINICAL PATHOLOGY IS CONSISTENT
BUT YOU WOULDN'T HAVE HISTOLOGY
DATA.
YOU'D HAVE GENERALLY SYMPTOMS OR
OTHER TYPES OF TERMS DESCRIBING
A PATIENT'S CONDITION THAT
REALLY AREN'T APPLICABLE TO
ANIMALS.
YOU CAN'T GET INFORMATION ABOUT
NAUSEA FROM ANIMALS, FOR
EXAMPLE, RIGHT?
SO THERE ARE SOME CHALLENGES
THERE IN DOING THAT.
BUT I THINK EFFORTS IN THAT AREA
WOULD REALLY BEAR SOME FRUIT IN
CONSISTENTLY BEING ABLE TO, YOU
KNOW, LINK TERMS THAT MIGHT BE
ASSOCIATED WITH EACH OTHER.
THOSE ARE SOME OF THE MAIN
BARRIERS I SEE THERE.
SO INCENTIVES WOULD BE
OPPORTUNITIES TO SHARE DATA.
IF THERE WERE WAYS TO DO THAT,
AUTONOMOUSLY, ANONYMOUSLY,
EXCUSE ME, IF THERE WERE
OPPORTUNITIES TO SHARE DATA,
THAT WERE APPROPRIATE, THAT
WOULD BE GREAT.
SOMEONE EARLIER MENTIONED
FEDERATED DATABASES.
THAT WOULD REALLY HELP TO
PROGRESS INTEGRATED MODELS.
AND THEN, YOU KNOW, YOU COULD
HAVE THE CONNECTION BETWEEN IN
VITRO TO PRE-CLINICAL OR EVEN
CLINICAL.
I THINK MANY OF THE IN VITRO
SYSTEMS ARE ACTUALLY HUMAN
BASED.
SO, MIGHT ACTUALLY MAKE THE MOST
SENSE TO TRY TO CONNECT THE IN
VITRO, THE COMPLEX MODELS TO THE
HUMAN DATA.
>>THANKS, TERRY.
BLANCA?
>>CAN YOU SEE ME NOW?
I DON'T KNOW WHAT HAPPENED WITH
MY CAMERA BEFORE.
FOR ME, THE MAIN BARRIERS ARE
TWO DIFFERENT TYPES.
THE FIRST ONE IS RELATED TO
MANAGEMENT AND HOW MUCH
MANAGEMENT IS WILLING TO INVEST
TO UPTAKE THESE NEW
TECHNOLOGIES.
AND THAT COMES FROM MANAGEMENT
BUY-IN, COMES FROM TWO MAIN
ASPECTS, IN MY OPINION.
THE FIRST ONE IS HAVING CLEAR
BENEFITS, DEFINING WHAT ARE THE
BENEFITS OF USING NEW
APPROACHES, WHETHER THEY ARE
ECONOMICS OR BASED ON HEALTH
ECONOMICS OR BASED ON ANY OTHER
BENEFITS, ETHICAL, FOR EXAMPLE.
AND THE OTHER ONE IS TRUST.
AND TRUST IN THESE TECHNOLOGIES
IS A BIG TOPIC AS WELL, REALLY
IMPORTANT TO GET MANAGEMENT
SUPPORT.
IT COMES FROM -- AT LEAST TWO
DIFFERENT THINGS.
ONE IS EVIDENCE, SCIENTIFIC
EVIDENCE OF THE VALIDITY OR
CREDIBILITY OF METHODOLOGIES,
BUT ALSO THERE'S SOMETHING MORE
EMOTIONAL ABOUT IT.
IT'S HOW PEOPLE RELATE TO THESE
TECHNOLOGIES.
IN MY EXPERIENCE, A LOT OF
SKEPTICISM IS JUST IGNORANCE
ABOUT WHAT THE NEW TECHNOLOGIES
CAN BRING.
SO THAT'S THE FIRST SET OF
BARRIERS THAT I HAVE EXPERIENCED
IN TERMS OF GETTING MANAGEMENT
SUPPORT, TO GET THE RIGHT SORT
OF FINANCIAL SUPPORT, TO
IMPLEMENT THESE TECHNOLOGIES, AT
LEAST EXPLORE THESE
TECHNOLOGIES.
OTHER BEARERS ARE OPERATION --
OTHER BARRIERS ARE OPERATIONAL,
WHETHER DATA ARE QUALITY,
QUANTITY TO CONSTRUCT THE NEW
METHODOLOGIES AND VALIDATE THEM,
BUT ALSO IN TERMS OF OPERATIONAL
BARRIERS, WHETHER THE TEAM HAS
THE RIGHT EXPERTISE AND TRAINING
TO WORK TOGETHER WITH THE
APPROACHES.
SO INTERDISCIPLINARY, THERE'S
NOT A SINGLE PERSON ABLE TO
CONTROL OR HANDLE OR UNDERSTAND
ALL THE ASPECTS OF HYBRID
SYSTEMS SO THIS IS ABOUT TEAMS
WORKING TOGETHER.
AND AGAIN, LEADERSHIP NEEDS TO
BE ABLE TO UNDERSTAND THE
COMPLEMENTARYITY OF THE
APPROACHES, AND THIS IS ANOTHER
SOURCE OF POTENTIAL BARRIERS
THERE.
SO THOSE ARE MY TWO CENTS.
>>THANKS, BLANCA.
WHAT ARE SOME INCENTIVES THAT
YOU THINK YOU WOULD BE ABLE TO
ADDRESS THOSE BARRIERS WITH?
>>WELL, I MEAN, A LOT OF -- SO
WHETHER YOU'RE TALKING DIGITAL
HEALTH, THE BARRIERS ARE VERY
SIMILAR.
SO THERE NEEDS TO BE INCENTIVE
THAT COMES VERY OFTEN FROM
EITHER GOVERNMENT OR REGULATORY
AGENCIES, PEOPLE WHO HAVE THE
POWER TO REALLY PUT THE CARROT
IF NOT SOMETHING ELSE IN FRONT
OF PEOPLE TO CHANGE.
SO CHANGE TAKES A LOT OF ENERGY.
AND THE INCENTIVES NEED TO BE
VERY, VERY CLEAR.
FOR EXAMPLE, WHEN IN 2013 THE
FDA ANNOUNCEED THEY WERE GOING
TO BE CONSIDERING HUMAN-BASED
METHODOLOGIES RATHER THAN
CLINICAL TRIALS, OR CLINICAL
STUDIES IN HEALTHY VOLUNTEERS,
THAT WAS A HUGE INCENTIVE.
IF THE FDA SAYS WE'LL BE USING
THE NEW METHODS, WE'LL BE
ACCEPTING THEM IN SUBMISSIONS,
OR EVEN WORSE WHAT HAPPENED
WITH -- OR EVEN BETTER, SORRY,
WHAT HAPPENED IN CHEMICAL
TOXICITY WHEN ANIMAL METHODS
HAVE BEEN BANED. BANED --
BANNED.
THAT'S VERY POWERFUL.
WITHOUT THAT INCENTIVE, THE
CHANGE IS GOING TO BE VERY SLOW
AND OFTEN SKEPTICISM IS JUST AN
EXCUSE FOR CHANGE BECAUSE CHANGE
TAKES ENERGY AND RESOURCES, AND
THERE NEEDS TO BE A VERY CLEAR
REASON TO DO IT.
AND SO I THINK GOVERNMENT AND
REGULATORY AGENCIES HOLD THE
POWER FOR A LOT OF THIS.
>>THANKS, BLANCA.
ROSER?
>>YES, BUILDING ON THIS, I WAS
ALSO THINKING ABOUT QUANTITATIVE
MEASUREMENTS THAT WE'RE SAYING,
AND I THINK IT'S A PROBLEM ALSO
WITH THE DATABASES, ONE OF THE
ISSUES AS WELL IS IT'S KIND OF
EASY TO GET FUNDING FOR THINGS
THAT ARE NEW BUT NOT THAT MUCH
FOR MAINTAINING SOMETHING THAT
IS ALREADY THERE.
THAT SOMETIMES CREATES A
PROBLEM, KIND OF MAINTAINING
SOMETHING AND THEN USE THAT
DATA.
YEAH, I WOULD ALSO SAY THAT
ANOTHER BARRIER WILL BE STARTING
ALSO LINKING TO THE FIDELITY
WILL BE TO VALIDATE, TO MAKE A
GOOD FUNCTIONAL VALIDATION, WHAT
IS FUNCTIONAL, WHAT IS A
REFERENCE, AND I GUESS THERE ARE
A LOT OF OPPORTUNITIES HERE NOW
THAT WE CAN MAKE ALL THESE
MEASUREMENTS BOTH IN VIVO AND IN
VITRO, TO START CONVINCING THE
AGENCIES THAT MAYBE THERE'S NOT
A MODEL THAT IS RIGHT BUT IS
RIGHT FOR THIS PURPOSE.
AND SO I THINK THERE'S A LOT OF
OPPORTUNITIES ON THAT, YEAH, I
WILL ECHO THE OTHER WORDS THAT
MY COLLEAGUES HAVE SAID ABOUT
STANDARDIZEING STANDARDIZING
MEASUREMENTS AS WELL.
>>WHAT ARE LIMITING FACTORS TO
MAKING HYBRID MODELS MOST USEFUL
FOR STUDYING HUMAN CONDITIONS,
DEPLOYING FIRST-IN-HUMAN
ADVANCES?
THINKING ABOUT THE LIMITING
FACTORS, IF YOU COULD ALSO
ADDRESS HOW CAN WE ADDRESS THOSE
LIMITING FACTORS AND IF YOU HAVE
SOME SPECIFIC EXAMPLES THAT
WOULD BE HELPFUL.
GRACA, MAYBE WE CAN KICK OFF
WITH YOU.
>>SURE, THANK YOU.
SO, I BELIEVE THERE'S TWO
PATHWAYS FOR THESE HYBRID
MODELS.
ONE IS DISCOVERY AND INNOVATION,
THE OTHER IS QUALIFICATION THAT
CAN THEN USE IN -- FOR THE FDA.
I THINK WE CANNOT DISREGARD ONE
OR THE OTHER.
WE HAVE TO CONTINUE TO INNOVATE
IN ORDER TO FEED, TO
QUALIFICATION AND VALIDATION OF
THOSE SYSTEMS, SO THAT WE CAN
TAKE THEM TO THE CLINIC.
SO I THINK WE STILL HAVE A LOT
OF LIMITING FACTORS BECAUSE THEY
COME FROM THE MULTI-SYSTEMS
ITSELF, EITHER BIOLOGICAL
COMPONENTS OR A.I. COMPONENTS OR
THE OTHER COMPONENTS THAT WE
WANT TO ADD TO THOSE
MULTI-SYSTEM APPROACHES.
I THINK ONE THING THAT IS
MISSING IS TALKING BETWEEN
PEOPLE THAT A.I. OR MACHINE
LEARNING OR EVEN REGULATORS FROM
THE BEGINNING TO KNOW WHAT IS
THAT THEY NEED FROM THOSE
NAMs.
THAT'S BEEN ADDRESSED TO A
CERTAIN WAY THAT THE FDA HAS
TAKEN LEAD AND SO HAS THE EPA
BUT WE NEED MORE, WE NEED A
BROADER INTEREST AND MORE
TALKING BETWEEN THE DIFFERENT
PEOPLE THAT ARE CONTRIBUTING TO
THOSE NAMs.
AND THE TRUTH IS THAT THOSE OF
US LIKE ME, BIOLOGY, WE DON'T
SPEAK THE SAME LANGUAGE AS
PEOPLE IN BIOINFORMATICS OR A.I.
WE NEED TO UNDERSTAND THE
LANGUAGE TO BE PRODUCTIVE
TOGETHER.
SO STARTING WITH TEAMS FROM THE
BEGINNING, I THINK THAT'S
ESSENTIAL.
FOR INSTANCE IN TERMS OF THE
MULTI-ORGAN ON A CHIP
TECHNOLOGIES, WE ARE
PROGRESSING, AND I BELIEVE THAT
THIS IS THE WAY TO GO.
THEN YOU ASSOCIATE MACHINE
LEARNING OR BIOINFORMATICS, WHAT
WE CAN AGAINST SENSORS THAT CAN
IN REAL TIME MEASURE WHAT'S
HAPPENING INTO THOSE SYSTEMS.
BUT FOR INSTANCE I SEE THE MORE
I USE THESE SYSTEMS AND MORE I
SAY WE'RE GETTING ACTUALLY A
GOOD RESPONSE, I THINK THERE'S
ALSO A NEED TO DEVELOP BETTER
SYSTEMS.
FOR INSTANCE, THOSE ORGANOIDS OR
THOSE ISSUES, WHAT DO THEY
REPRODUCE?
DO WE MAKE THEM FROM iPS
CELLS?
iPS CELLS IF WE DRIVE THEM
THROUGH DIFFERENCE SOURCES DO
THEY RETAIN CHARACTERISTICS OF
VARIETY OF DONORS IN TERMS OF
ETHNICITY BECAUSE EACH TIME YOU
CULTURE CELLS IN VITRO THINGS
CHANGE.
IF YOU USE PRIMARY CELLS, WHERE
DO THE PRIMARY CELLS COME FROM?
WE'RE HAVING DIFFICULTIES
FINDING SOURCES OF PRIMARY
CELLS, TO MAKE ORGANOIDS DO YOU
USE FROM SINGLE DONOR OR
MULTIPLE DONORS?
SO FAR THEY ARE WORKING WELL
FROM MULTIPLE DONORS BUT WOULD
WE GET BETTER RESPONSES IF WE
WERE USING FOR INSTANCE ORGANOID
IN WHICH WE HAVE KUPFFER CELLS
AND HEPATOCYTES FROM THE SAME
DONOR, PRIMARY CELLS, SO WE CAN
TEST DRUGS OR TEST GENE THERAPY
OR TEST WHATEVER WE WANT TO
TEST.
IF YOU WANT TO USE THESE SYSTEMS
WITH DIFFERENT ORGANS, A BRAIN
ORGANOID OR YOU HAVE LUNG
ORGANOID, OR LUNG TISSUE, HOW
ARE YOU USING JUST THE SAME
DONOR OR CAN YOU USE DIFFERENT
DONORS?
FOR INSTANCE, IF AN AGENCY COULD
COLLECT THESE TISSUES AND
PROVIDE THEM TO THE
INVESTIGATORS SO THAT WE
ACTUALLY COULD MATCH TISSUES
FROM THE SAME DONOR WOULD BE
VERY USEFUL.
WE HAVE DEVELOPED UNIVERSAL
MEDIA SO WE CAN HAVE MULTIPLE
ORGANOIDS AND HAVE THEM GROW FOR
CONSIDERABLE NUMBER OF TIME
USING THE SAME MEDIA.
BECAUSE IF THE ORGANOIDS NEED
DIFFERENT MEDIA, THEN YOU CAN'T
USE THEM IN CONJUNCTION.
BUT STILL IF YOU ARE USING TOX
OR TOX STUDIES YOU'RE
APPROACHING PLASMA, HOW DO WE
ADDRESS THAT, HOW CAN WE GIVE
SOMETHING THAT IS ON FLOW, THE
PLASMA COMPONENT OF THE
INDIVIDUAL.
FOR INSTANCE, EXTRACELLULAR
MATRIX COMPOSITIONS, ARE WE
MIMICKING MECHANICAL FORCES THAT
EXIST IN THE ORGANOIDS,
VASCULARIZATION, MOST OF THESE
ORGANOIDS, THEY ARE GIVING VERY
GOOD RESULTS AND WE'RE GETTING
PROMISING RESULTS BUT WOULD BE
BETTER TO HAVE THE CORRECT
VASCULARIZATION IN THESE TISSUES
BECAUSE EACH CELL IS DIFFERENT
IN EACH DIFFERENT TISSUE.
WE NEED TO THINK ABOUT THE
PROBLEMS.
WE NEED THE IMMUNE SYSTEM GOING
INTO THESE MULTI-SYSTEM
ORGANOIDS SO THAT WE CAN ADDRESS
TOXICITY AND IMMUNE RESPONSES.
THERE'S A NEED FOR INNOVATION IN
THE BIOLOGICAL SYSTEMS.
THERE'S WITHIN THESE SINGLE
ORGANOIDS WE MAY HAVE RESOURCES
THAT WE CAN USE FOR
QUALIFICATION AND VALIDATION FOR
END USER, SO TRANSLATE THOSE TO
THE CLINIC IN A SHORT PERIOD OF
TIME.
AT THE SAME TIME WE COULD
BENEFIT FROM MACHINE LEARNING,
A.I., AND OF COURSE
BIOINFORMATICS AND GENOMIC
ANALYSIS, THE OMICS ANALYSIS OF
THESE ORGANOIDS, ALL TOGETHER TO
GET A BIG PICTURE OF WHAT'S
HAPPEN AND MAKE THE DATA THAT
WE'RE GETTING MORE USEFUL AND
MORE COMPLETE.
>>SO THANKS, GRACA.
TO FOLLOW UP, AT WAKE FOREST
HAVE YOU STANDARDIZED WHAT KIND
OF METADATA IS BEING COLLECTED
WITH, FOR EXAMPLE, ORGANOID
EXPERIMENTS, AND SECOND PART OF
THE QUESTION, IS THERE DATABASE
AT WAKE FOREST WHERE ALL OF THAT
DATA IS COMING IN, STILL SILOED
LIKE RESEARCHER OR THERAPEUTIC
AREA?
>>I BELIEVE WE'RE THROWING
EXACTLY TO GET THE DATA, ALL
TOGETHER, AND WORKING
COLLECTIVELY TO COLLECT ALL THAT
DATA.
AND FROM WHAT I HEAR, SOMETIMES
IT'S CHALLENGING.
>>THANK YOU.
TERRY?
>>YEAH, I'M JEALOUS OF THAT.
I WISH WE HAD CONSISTENT DATA
COLLECTION.
ALL THE MODELS WE USE ARE SO
DIFFERENT THAT MAKES IT A REAL
CHALLENGE TO HAVE ENOUGH DATA TO
APPLY ANALYTICS.
ONE THING YOU SAID THAT STRUCK A
CHORD WAS CELL SOURCES.
SOMEONE MENTIONED 25% OF CELL
TYPES WERE MISIDENTIFIED, AND
PART OF THE CHARACTERIZEATION
PROCESS WE GO THROUGH WHEN WE
BRING CELLS IN AND CHARACTERIZE
IN VITRO MODELS, WE DO APPLY
NEXT GEN SEQUENCING TO THOSE
CELL TYPES.
WE FOUND THE SAME, YOU KNOW,
FAIR NUMBER OF THOSE ARE THE
WRONG CELL OR THE WRONG SPECIES.
AND SO HAVING A QUALITY SOURCE
OR SOURCE OF VERIFIED CELL TYPES
WOULD BE FANTASTIC STEP FORWARD
I THINK.
I ALSO REALLY WOULD LIKE TO
REPEAT THE COMMENT ABOUT
UNIVERSAL MEDIA, THAT'S A
CHALLENGE, YOU KNOW, WHEN YOU'RE
GOING TO GET INTO MULTI-ORGAN
SYSTEMS THAT ARE CONNECTED, I
THINK ONE THING THAT'S ALSO
SOMETIMES CONSIDERED AND CAN BE
A LITTLE BIT OF A CHALLENGE
THERE IS SIZE, RIGHT?
AT THIS POINT THEY ARE ALL
ESSENTIALLY THE SAME SIZE.
THAT'S NOT EXACTLY HOW THAT IS
PHYSIOLOGICALLY OR ANATOMICALLY
I GUESS I SHOULD SAY.
SO THAT NEEDS TO BE CONSIDERED
ALSO.
BUT ALL OF THIS REALLY, YOU
KNOW, HELPS THE CONFIDENCE PART.
AND I'D SAY THAT THAT'S THE
BIGGEST -- MAYBE ONE OF THE
BIGGEST BARRIERS, HAVING
CONFIDENCE TO MAKE DECISIONS ON
THE DATA.
WE SEE IN VITRO TO IN VIVO
TRANSLATION DIFFERENCES, OR
CHALLENGES, ALL THE TIME.
AND SO WE HAVE TO KNOW THAT
THESE SYSTEMS, THESE IN VITRO
SYSTEMS, TRANSLATE BETTER.
THAT TAKES SOME TIME TO DEVELOP,
BUT, YOU KNOW, I THINK
UNDERSTANDING THE SYSTEM BETTER,
HAVING GOOD SOURCE OF CELLS,
GOOD VALIDATION, THOSE THINGS
WILL HELP CONSIDERABLY, BUT THE
HIGHEST BARRIER REALLY IS
CONFIDENCE, I THINK, TO CONVINCE
AT LEAST IN MY -- FROM MY
PERSPECTIVE WHERE I SIT
CONVINCING PEOPLE TO MAKE
DECISIONS REGARDING PATIENT
SAFETY ON AN IN VITRO MODEL IS
TOUGH.
SO WE NEED CORROBORATEING
EVIDENCE, SOME WAY TO BUILD UP
THAT CONFIDENCE SO WE CAN DO
THAT.
>>SO MAYBE I CAN PUSH YOU.
CAN YOU GIVE US AN EXAMPLE OF,
YOU KNOW, HOW -- WHAT DO YOU
MEAN BY CONFIDENCE?
IN YOUR SITUATION, SOMETHING
MADE THAT DIFFERENCE AND MADE
YOUR LEADERSHIP TO ENGAGE WITH
THAT?
>>YEAH, IF YOU HAVE A SAFETY
SIGNAL IN ANIMALS, YOU KNOW, AND
HAVE OTHER MATERIAL THAT'S GOING
TO STOP, RIGHT?
YOU SWITCH TO NEW MATERIALS.
BUT IF YOU HAD SOME
CORROBORATEING EVIDENCE, YOU
KNOW, LET'S SAY YOU HAD SOME OF
THESE COMPLEX MODELS
REPRESENTING THAT SPECIES,
REPRODUCE THE RESULT, HUMAN
MODELS SHOWED A DIFFERENT RESULT
THAT WOULD PROVIDE CONFIDENCE
THAT YOU HAD WHAT YOU NEEDED TO
REPRODUCE EFFECT, YOU SAW
SOMETHING DIFFERENT, THEN YOU
COULD INVEST SOME RESOURCE INTO
SHOWING THAT SOMEHOW WITH SOME
EXTENDED INVESTIGATEIVE STUDIES
POTENTIALLY.
>>THANK YOU.
BLANCA?
>>I WANTED TO TOUCH ON OTHER
ASPECTS.
IF WE HAD DONE EVERYTHING THAT
GRACA AND TERRY WERE TALKING
ABOUT, IF WE HAVE A REALLY GOOD
SYSTEM, THAT IS CREDIBLE, WHERE
WE SHOW EVIDENCE OF CREDIBILITY
AND BEYOND WHAT HAS BEEN
ACCOMPLISHED WITH ANIMAL
STUDIES, FOR EXAMPLE, AND WE
WOULD STILL HAVE ISSUES WITH
UPTAKE OF THESE METHODOLOGIES,
EVEN WITH EVIDENCE BACKING US
UP.
AND ONE OF THE BIG PROBLEMS I
THINK IS THE ESTABLISHING -- SO
A LOT OF THE METHODS THAT HAVE
DEVELOPED IN ACADEMIA AND ARE
DEVELOPED IN THAT WAY DIE IN THE
VALLEY OF DEATH, RIGHT?
SO THEY DON'T REALLY FOLLOW
THROUGH TO WHAT'S IMPACTED, THEY
ARE NOT IMPLEMENTED IN
INDUSTRIAL SETTINGS, DON'T
REPLACE ANIMAL EXPERIMENTS.
AND ONE OF THE BIG PROBLEMS IS
THAT THE CYCLE OF THE WORK IS
VERY LONG.
SO YOU NEED TEN YEARS OF
VALIDATION STUDIES OF DIFFERENT
TYPES OF STUDIES AND DIFFERENT
TYPE OF WORK THAT REQUIRE MANY,
MANY YEARS TO PROGRESS THESE NEW
METHODOLOGIES TOWARDS IMPACT.
AND USUALLY THE FUNDING CYCLES
ARE SHORTER THAN WHAT IS
REQUIRED.
SO, HAVING LONGER FOR FUNDING
RESOURCES FOR FUNDING
METHODOLOGIES THAT PROGRESS
METHODOLOGY FROM DEVELOPMENT TO
THE VALIDATION, TO THE
IMPLEMENTATION, IS VERY
IMPORTANT.
EVEN FOR STARTUPS, THE
IMPLEMENTATION OF THE
METHODOLOGY IS -- REQUIRES
RESOURCES THAT ARE NOT EASILY
OBTAINABLE.
SO, THINKING THROUGH WHAT IS
REQUIRED TO ACHIEVE IMPACT,
BEYOND INNOVATION, BEYOND
CREDIBILITY, BEYOND THE
DEVELOPMENT AND HOW THEY WOULD
BE IMPLEMENTED TO DELIVER ACT IS
VERY IMPORTANT, THERE AREN'T
THAT MANY FUNDING TEAMS THAT
ALLOW TO SUPPORT THAT PROCESS,
EVEN FOR STARTUPS.
SO, I THINK THAT'S REALLY,
REALLY IMPORTANT.
AND THE OTHER ONE IS IN THAT
CYCLE, QUALIFICATION OF THE NEW
METHODOLOGIES CAN BE IMPORTANT,
ESPECIALLY FOR CLINICAL USE,
PROBABLY MORE THAN FOR INDUSTRY.
BUT THAT'S DEBATABLE.
AND WHETHER OR NOT THE AGENCIES
THAT PROVIDE THIS QUALIFICATION
HAVE ENOUGH RESOURCES, ENOUGH
EXPERTISE FOR HYBRID SYSTEMS IS
DEBATABLE AS WELL.
SO, I'VE HEARD THAT SOME
AGENCIES ARE NOT WELL STAFFED,
AND THAT'S ONE OF THE LIMITING
FACTORS IN THE QUALIFICATION OF
NEW METHODOLOGIES.
SO REALLY THINKING ABOUT HOW THE
REGULATORY AGENCIES CAN BE
PROPERLY RESOURCED AGENCIES SO
AGE LIST THAT DEAL WITH HYBRID
ARE WELL RESOURCED IN TERMS OF
PEOPLE, NUMBERS, ALSO EXPERTISE
IS VERY IMPORTANT.
I DO THINK THOSE WHO ASPECTS ARE
REALLY IMPORTANT, VERY LONG
CYCLES INVOLVED IN THE
IMPLEMENTATION OF NOVEL
METHODOLOGIES BEYOND THEIR
DEVELOPMENT, AND WELL RESOURCED
QUALIFICATIONS THAT HAVE
APPROPRIATE TRAINING, ESPECIALLY
TALKING HYBRID SYSTEMS THAT
INVOLVE COMPUTATIONAL AND
EXPERIMENTAL METHODS FOR
CLINICAL IMPACT, IT'S QUITE A
BIG INTERDISCIPLINARY ASK.
THANKS.
>>THANKS.
ROSER, WOULD YOU LIKE TO ADD
ANYTHING?
>>YES, I WANTED TO ADD TWO
THINGS.
MAYBE FIRST I THINK IT'S
IMPORTANT THAT WE
QUANTITATEIVELY SERVE THE
FIDELITY OF THE MODELS, ALSO
AGAIN BUILDING ON THE FACT WE
NEED TO COME TOGETHER AS A
MULTI-DISCIPLINARY TEAM TO ALSO
ESTABLISH STANDARDS OF WHAT WE
CONSIDER GOOD PARAMETERS TO
COMPARE THE DATA, AND, AGAIN,
MAKING SURE THEY ARE
QUANTITATIVE.
IT'S IMPORTANT TO MOVE THE
FIELD, AND I THINK IT'S A
BARRIER AT THE MOMENT.
AND THAT ALSO INVOLVES WHEN WE
VALIDATE SOMETHING, WE ARE NOT
THEY ARE CHERRY-PICKING BUT
MAKING SURE WE HAVE A BROAD
VALIDATION OF THE SYSTEM AND,
AGAIN, FOR THESE, IT'S IMPORTANT
WHAT WE WERE DISCUSSING AS A
TEAM, WE NEED MULTI-DISCIPLINARY
TEAM OF PEOPLE COMING TOGETHER
AND BRINGING IDEAS, HAVE
QUANTITATIVE MEASURES LOOKS
LIKE.
I THINK THE OTHER THING THAT IS
LIMITATION IS SIMPLICITY OF THE
MODELS, WHICH OF COURSE IS AN
ADVANTAGE BECAUSE YOU CAN LOOK
FOR INDIVIDUAL ASPECTS, SEPARATE
THEM, STUDY THEM
MECHANICISTICALLY BUT AT THE
SAME TIME IT'S A LIMITATION
BECAUSE, FOR EXAMPLE, WE HAVE
IMMUNE CELLS, VASCULATURE ON
TISSUES, A LOT OF THESE MODELS
DO NOT HAVE THEM, AND THE SAME
WHEN WE DO IN SILICO MODELING,
IT'S VERY SNAPSHOT, WE DON'T
HAVE FULL RECAPITULATION OF
DYNAMIC MEASUREMENT, AND I DO
FEEL WE NEED TO INVEST ON MAKING
ALL THESE MODELS MORE COMPLEX SO
THEY DO RECAPITULATE THE HUMAN
PHYSIOLOGY AND THE OTHER THING
WILL ALSO BE TO MAKE THEM FOR
ADAPTABLE FOR STUDYING LONG-TERM
RESPONSES WHICH WE ARE WORSE AT
PREDICTING I THINK.
THANK YOU.
>>ONE OF THE THINGS, BRING
DIFFERENT STAKEHOLDERS INTO
THAT, INTO THE CONVERSATION, THE
SUBJECT MATTER EXPERTS.
I GUESS THAT MAKES ME THINK
ABOUT COMPUTATIONAL TEAM THAT
YOU GUYS STARTED
TERRY, COMMENT ON HOW WAS THE
TEAM BUILT AND DOES THE TEAM,
FOR EXAMPLE, NOW ENGAGE WITH
SOME OF THE FOLKS FROM THAT
SYSTEM YOU HAVE?
>>THAT WAS FORMED TO LEVERAGE
HISTORIC DATA INITIALLY.
SO IT TURNED OUT TO BE A MUCH
BIGGER CHALLENGE TO MAKE THAT
DATA USABLE.
MAKE IT -- PUT IT IN A FORMAT
THAT COULD BE CONNECTED TO OTHER
DATA, AND THEN USED WITH
ANALYTICS FOR SOME REASONS I
TALKED ABOUT.
BUT IT'S ACTUALLY HAD A REALLY
BIG IMPACT ALREADY.
WE DON'T YET HAVE ENOUGH DATA
FROM THE MICROPHYSIOLOGICAL
SYSTEMS TO ADD, AND I WOULD JUST
ADD THOUGH THAT I GUESS WE
TALKED A LITTLE BIT ABOUT THE
BAR FOR CONFIDENCE.
THOSE SYSTEMS ARE BEING APPLIED
NOW.
I DON'T WANT TO MAKE IT SOUND
LIKE THEY ARE NOT BEING USED.
THEY ARE BEING APPLIED, IN
SPECIFIC CASES, WHERE THEY HAVE
BEEN QUALIFIED AND DO PROVIDE
GREAT INFORMATION.
WE'VE USED MULTIPLE ORGAN ON A
CHIP TO ANSWER QUESTIONS, OR
ORGANS ON CHIPS TO ANSWER
QUESTIONS.
BUT IF YOU'RE TALKING ABOUT, YOU
KNOW, THE HIGHER GOAL OF
REPLACING ANIMALS, THAT'S A MUCH
DIFFERENT BAR.
THAT'S WHERE THAT CONFIDENCE
FACTOR REALLY MATTERS.
THERE'S STILL SOME THINGS TO DO.
BUT FOR THAT REASON WE DON'T
HAVE ENOUGH DATA REALLY TO APPLY
A LOT.
WE'RE GETTING THERE WITH THINGS
LIKE SPHEROIDS RAPIDLY.
THOSE MODELS ARE ALSO EXCELLENT.
YOU SEE SOME WORK DONE, REPORTED
BY GENENTECH OR ASTRAZENECA,
GREAT SUCCESS IN PREDICTING
ORGAN TOXICITIES USING
SPHEROIDS.
SO THERE'S A LOT MORE THAT CAN
BE DONE, A LOT OF COMPANIES ARE
WORKING HARD TO GET THERE, WITH
REALLY ADVANCED SYSTEMS WE DON'T
HAVE ENOUGH DATA YET SO WE'RE
WORKING TOWARDS THAT BUT ONE OF
THE ADVANTAGES AND DISADVANTAGES
WITH THOSE SYSTEMS IS THEY LIVE
A LONG TIME, THEY HAVE A LOT OF
VIABILITY, BUT IT ALSO TAKES
LONGER TO GENERATE DATA BECAUSE
EXPERIMENTS ARE MUCH LONGER.
SO I THINK WE'LL GET THERE BUT
THAT'S WHERE WE ARE RIGHT NOW.
>>SO GRACA, FOR YOU AT WAKE
FOREST, SO LIKE FOR
PHYSIOLOGICAL AND IN VITRO
SYSTEMS, WE FOUND OUT THAT YOU
GOT TO QUALIFY OR VALIDATE
WHATEVER TERMINOLOGY YOU WANT TO
USE FOR SPECIFIC CONTEXT OF USE.
FOR THE IN SILICO TOOLS YOU'RE
USING AT WAKE FOREST DO YOU SEE
IT'S THE SAME THING THAT YOU
HAVE TO QUALIFY FOR A SPECIFIC
QUESTIONS, CONTEXT OF USE OR CAN
YOU GENERALIZE MORE?
>>WE GENERALIZE A LITTLE BIT
MORE, RIGHT?
WE ARE INNOVATION AND DISCOVERY,
ALTHOUGH TERRY SAID THESE
SYSTEMS ARE BEING USED IN THE
CLINIC, BUT I THINK IN ACADEMIA
WE REACH OUT TO COLLABORATORS
AND START THE PROCESS OF -- I
DON'T DO IN SILICO MOLECULAR
DYNAMIC SIMULATIONS, I DON'T
KNOW HOW TO DO IT, SO I REACH
OUT TO A COLLABORATOR AND
TOGETHER HE UNDERSTANDS MY
LANGUAGE, I UNDERSTAND HIS
LANGUAGE, AND WE PUT A PROJECT
TOGETHER TO SOLVE QUESTIONS.
SO AT LEAST ON MY PART, BECAUSE
I CANNOT SPEAK ON THE INSTITUTE
ITSELF, BUT WE TRY TO
COLLABORATE WITH PEOPLE FROM
DIFFERENT BACKGROUNDS SO THAT WE
CAN SEE IF THAT PIECE OF
INFORMATION OTHERWISE.
BUT I THINK THERE'S A TREND TO
TRY TO -- ESPECIALLY WITH THE
MULTI-SYSTEMS TO STANDARDIZE TO
GET IT THE NEXT LEVEL.
ONE THING I WOULD LIKE TO
REITERATE, YOU KNOW, ANY
CLINICAL PRODUCT, IT TAKES 10 OR
15 YEARS TO GO FROM BENCH TO
CLINIC.
SO I KNOW THESE MULTI-SYSTEMS
HAVE BEEN BUILT AND USED FOR A
WHILE, BUT WE CANNOT EXPECT THAT
WE'RE GOING TO GET ALL THE
RESULTS TOMORROW.
THESE ARE LONG-TERM INVESTMENTS,
AND THEY ARE FOR THE BEST BUT
MEETINGS LIKE THIS ARE IMPORTANT
SO WE CAN PUT ALL THIS TOGETHER
SO WE KNOW, INTERACT WITH
PEOPLE, TO OTHER TYPES OF
SCIENCE SO WE CAN INTEGRATE
THOSE.
SO THAT WE CAN SPEAK --
>>THANK YOU SO MUCH.
BLANCA?
>>I JUST WANTED TO COMMENT ON
THE ISSUE OF QUALIFICATION OF IN
SILICO METHODS.
AND SO THE REQUEST IS TO QUALIFY
THEM FOR VERY SPECIFIC CONTEXT
OF USE.
AND THAT CREATES SOME PROBLEMS
BECAUSE THE -- SO IN SILICO
METHODS ARE UPDATED QUITE
QUICKLY, ESPECIALLY IF YOU HAVE
MORE DATA, AND IT POSES A BIT OF
A PROBLEM, IF THE QUALIFICATION
SLOWS DOWN THE PROCESS AND IT'S
VERY EXPENSIVE, FOR VERY
SPECIFIC CONTEXT OF USE.
IT NEEDS TO BE DONE EVERY TIME
THE METHOD IS UPDATED, FOR
CERTAIN APPLICATIONS.
SO IT CREATES A BIT OF DIFFERENT
SCENARIO TO THE IN VITRO
SYSTEMS.
AND IT NEEDS TO BE VERY DYNAMIC,
I WOULD THINK, PROBABLY
INCORPORATE THOSE SECOND OR
THIRD GENERATION ALGORITHMS IN
THE PROCESS.
CERTAINLY MODELING AND
SIMULATION POSES A PROBLEM
BECAUSE THE QUALIFICATIONS CAN
TAKE MUCH LONGER THAN THE UPDATE
OF THE MODEL.
SO, IT'S A DIFFERENCE BETWEEN IN
SILICO AND INDIVIDUAL SYSTEM,
ONE THAT NEEDS TO BE TAKEN IN
CONSIDERATION IN THE
QUALIFICATION.
>>GREAT.
THANK YOU SO MUCH.
AND SO WE HAVE ABOUT EIGHT
MINUTES LEFT OR SO.
I DID WANT TO THROW OUT A THIRD
QUESTION HERE BECAUSE AS OTHERS
HAVE SAID RIGHT NOW WE'RE NOT
READY TO REPLACE OUR TRADITIONAL
MODELS, AT LEAST NOT YET.
SO, WHAT ARE THE CHALLENGES OF
INTEGRATING NAMs WITH OUR
TRADITIONAL METHODOLOGIES
ALONGSIDE THEM?
AND HOW CAN WE ADDRESS THOSE
CHALLENGES?
WITH THAT, MAYBE ROSER, WE CAN
START WITH YOU.
>>YEAH, SURE.
I WAS THINKING OF CHALLENGES.
ONE WILL BE TRADITIONALLY WE'VE
NOT DONE THAT MANY SYSTEMATIC OR
STANDARDIZED QUANTITATIVE
MEASUREMENTS, AND ON ONE HAND
THAT'S SOMETHING THAT WILL NEED
TO BE CHANGED, IN MY VIEW, AND
LOOKING FOR WAYS TO HARMONIZE
THESE METADATA OR THESE -- ALL
THESE MEASUREMENTS, THAT WE
HAVE, AND, AGAIN, I THINK
HARMONIZEATION OF ALL THE
METADATA COLLECTED WILL BE BIG
STEPS, THEN WE CAN INCORPORATE
THEM IN OUR IN SILICO MODELS,
AND LIKEWISE ADAPTING IN SILICO
MODELS TO TAKE INTO ACCOUNT THAT
DATA, THAT IS NOT QUANTITATE
QUANTITATIVE AS OTHER
MEASUREMENTS, WE CAN BE DOING
NOW IN MORE ADVANCED NAMs
TECHNOLOGIES.
I GUESS THE OTHER THING WILL BE
KIND OF TRANSLATION BETWEEN MICE
AND HUMANS, A LOT OF WORK, WHEN
USED IN MICE, AND THERE I THINK
AGAIN WE CAN TAKE ADVANTAGE OF
COMPUTATIONAL TOOLS TO MAKE THIS
TRANSLATION OR TRANSITION, WE
KNOW THIS IS DIFFERENT BETWEEN
HUMAN AND MICE, THEN WE CAN TAKE
INTO CONSIDERATION IN OUR MODEL
TO TRANSLATE A RESULT, BUT
OBVIOUSLY THAT WILL BE A
CHALLENGE.
THE OTHER I THINK IT WILL ALSO
BE THE FACT THAT WE NEED TO
ADAPT ALSO THE NAMs FOR
RECAPITULATEING MORE LONG-TERM
RESPONSES SINCE I WAS MENTIONING
BEFORE, WHICH CAN BE DONE IN
MORE TRADITIONAL SYSTEMS WITH A
LOT OF CURRENT MODELS WILL NOT
TAKE INTO ACCOUNT MORE LONG-TERM
RESPONSES WHICH ARE REQUIRED,
ANYWAYS, AND I THINK THOSE ARE
KIND OF THREE CHALLENGES THAT I
HAVE THOUGHT ABOUT AND OF COURSE
IN ITS COMPLEXITY.
>>GREAT.
THANKS.
BLANCA, JUMPING TO YOU, IN 90
SECONDS IF YOU CAN ANSWER THAT
QUESTION.
>>I WOULD SAY THAT THINKING
ABOUT IMPLEMENTATION FROM THE
OUTSET, AND CONTEXT OF USE OF
THE METHODOLOGY FROM THE OUTSET,
ENGAGING WITH PEOPLE WHO WILL BE
USING THE METHODOLOGY FOR THE
DECISION MAKING FROM THE
BEGINNING AND MAYBE A BROAD
RANGE OF THEM FROM THE BEGINNING
OF THE DEVELOPMENT IS QUITE
USEFUL.
AND WOULD ENABLE A BROADER
IMPACT OF THE METHODOLOGY.
>>GREAT.
THANKS, BLANCA.
GRACA?
>>I AGREE WITH ROSER AND
BLANCA, I WOULD LIKE TO ADD THAT
AS FAR AS ACADEMIA, SOMEONE SAID
THIS MORNING THAT WE GET FUNDED
AND WE CAN WORK ON A PROJECT
WHILE WE ARE FUNDING, RIGHT?
IF THE PANELS THAT ARE
EVALUATING THE APPLICATIONS THAT
WE WRITE DON'T HAVE CONFIDENCE
IN THOSE MODELS, THEN WE ARE NOT
GOING TO BE ABLE TO WORK.
SO, EVEN FOR THOSE THAT ARE
USING MULTI-SYSTEMS, THEY MAY
NOT GET THE FUNDS THAT THEY NEED
TO BRING IT TO MORE TRADITIONAL
BIOMEDICAL -- TO INTEGRATE WITH
MORE TRADITIONAL BIOMEDICAL
RESEARCH APPROACHES.
ONE THING THAT I WOULD ALSO LIKE
TO SAY IS LONGEVITY OF THE
SYSTEMS, AT LEAST BIOLOGICAL
SYSTEMS WITH MULTI-SYSTEM
APPROACHES THAT MANY PEOPLE THAT
WORK WITH ANIMAL MODELS SAY,
WELL, WE HAVE THREE MONTHS, WE
HAVE A YEAR, AND WE'RE NOT THERE
YET WITH THIS TYPE OF -- I THINK
THAT ALSO CREATES DIFFICULT
INTEGRATION IN WHAT OUR CONCEPTS
ARE OF RESEARCH OR WHAT WE WANT
TO GET FROM A SPECIFIC -- IN
TERMS OF LONGEVITY AND EFFECT.
I THINK THERE'S INTEGRATION IS
POSSIBLE AND I THINK EVERYONE IS
EITHER -- WE NEED 12 APPROACH
TEAMS THAT UNDERSTAND THESE
SYSTEMS AND CAN GET THIS AND
WORK LONG TERM, APPROACH WITH
COMPANIES, WITH ACADEMIA AND SO
FORTH.
I DON'T KNOW WHAT THE BEST
APPROACH WOULD BE BUT SOMETHING
THAT ALLOWS US TO WORK LONG TIME
TO GET THESE DATA TO TRANSLATE,
WHAT WE KNOW RIGHT NOW FROM
ANIMAL MODELS AND FROM RESEARCH
THAT IS MORE TRADITIONAL.
>>GREAT.
THANK YOU.
TERRY.
>>YEAH, I THINK ONE THING WE
HAVEN'T REALLY TALKED ABOUT IN
THIS DISCUSSION THAT MIGHT BE
PERTINENT HERE IN INTEGRATING
NAMs MORE FULLY INTO THE
PROCESS IS, YOU KNOW, ONE OF THE
THINGS THE IQMPS HAS TALKED
ABOUT SINCE 2014 I THINK AT
LEAST OFF AND ON SOME IS THE
NEED FOR ANIMAL CELL-BASED
MODELS AS WELL TO HELP MAKE THE
COMPARISON, UNDERSTAND
TRANSLATION.
I THINK EFFORTS HAVE FOCUSED ON
HUMANS, RIGHTLY SO.
BUT THAT'S SOMETHING TO CONSIDER
DOWN THE ROAD THAT MAY ACTUALLY
HELP AT LEAST IN THE AREA OF
SAFETY.
I'M NOT SURE, I THINK THAT'S THE
MAIN AREA IT WOULD HELP, HAVING
COUNTERPART MODELS.
I ALSO THINK ONE INTERESTING
THING I'VE BEEN SEEING OVER TIME
IS MORE AND MORE NEW BIOLOGIC
PLATFORM DRUGS COMING INTO
PIPELINES, AND AS THEY COME THEY
ARE VERY DIFFERENT FROM
TRADITIONAL SMALL MOLECULE DRUGS
WHETHER WE HAVE REALLY NEEDED TO
LOOK FOR INTEGRATED RESPONSES,
MUCH MORE SELECTIVE, AND THIS
REALLY I THINK WILL NATURALLY
HELP US TO DRIFT MORE TO NAMs
USE.
MAYBE NOT ONLY ADVANCED MODELS
BUT MORE IN VITRO SYSTEMS TO
ASSESS SAFETY OVER TIME.
>>THANK YOU SO MUCH.
AND SO WE HAVE A MINUTE AND A
HALF LEFT.
I'M GOING TO QUICKLY IN TEN
SECONDS, IF YOU HAD A MAGIC WAND
AN UNLIMITED FUNDING WHAT CHANGE
WOULD YOU MAKE HAPPEN.
ROSER, WE'LL START WITH YOU.
YOU'RE MUTED.
>>SORRY.
I THINK ONE OF THE IMPORTANT
THINGS TO INCREASE COMPLEXITY
FOR ME OF THE NAMs, THAT'S
SOMETHING I WILL INVEST IN.
>>BLANCA?
>>LONGER FUNDING CYCLES.
IMPLEMENTATION.
>>GRACA?
>>I WOULD GET A TEAM OF PEOPLE
FROM DIFFERENT SECTORS TOGETHER,
INCLUDING AGENCIES FROM THE
GOVERNMENT, FROM COMPANIES,
ACADEMIA, AND WOULD DEVELOP
THESE SYSTEMS SIDE BY SIDE WITH
THE DIFFERENT TECHNOLOGIES
TALKING TOGETHER, AND OF COURSE
THE BIOLOGY HAS TO BE IMPROVED
BUT IN PARALLEL WITH BIG TEAMS
MOVING THE FIELD FORWARD, EVEN
IF IT'S NOT TO GET A CLINICAL
RESPONSE OR TO A CLINICAL POINT
RIGHT NOW.
BUT FIRST TO UNDERSTAND HOW WE
CAN BENEFIT FROM ALL THE SOURCES
THAT WE HAVE TO GET SOMETHING,
THAT THEN CAN BE MEANINGFUL IN
THE FUTURE.
>>TERRY?
>>I WOULD LIKE TO SEE LARGE
BLINDED OR ANONYMOUS DATABASES,
YOU KNOW, COMPILED THAT REALLY
INCREASE THE POWER OF THE NEW
ADVANCED ANALYTICS WHERE PEOPLE
COULD SHARE INFORMATION, AT
LEAST THE PRE-COMPETITIVE
INFORMATION, AND I THINK SAFETY
IS ONE OF THOSE AREAS WHERE --
IT'S PRE-COMPETITIVE, AND I
THINK THAT WOULD HELP ADVANCE
THINGS.
I'VE SEEN A LOT OF IMPACT, YOU
KNOW, IN THE COMPUTATIONAL AREA,
I THINK IN SILICO IS REALLY A
GREAT AREA TO FOCUS.
>>THANK YOU ARE SO MUCH.
I WOULD LIKE TO THANK ALL FOUR
OF YOU FOR PARTICIPATING IN THIS
PANEL.
I KNOW THE COMMITTEE IS
DEFINITELY GOING TO END UP
UTILIZING INFORMATION YOU SHARED
AND EXPERTISE YOU SHARED PULLING
INTO OUR REPORT WHICH IS COMING
OUT LATER THIS YEAR.
AGAIN, THANK YOU SO MUCH FOR
YOUR TIME.
[APPLAUSE]
>>THANK YOU.
BYE-BYE.
WELCOME BACK.
OUR WORKING GROUP MEMBER, DR.
NOVAKOVIC WILL LEAD THIS
SESSION.
PLEASE TAKE IT AWAY.
>>THANK YOU, HOWARD.
GOOD AFTERNOON FROM ME TOO.
I'M GORDANA, PROFESSOR AT
COLUMBIA UNIVERSITY, AND MY LAB
IS INTERESTED IN ENGINEERING
HUMAN TISSUES FOR MEDICAL
IMPACT.
A LARGE PART OF THIS EFFORT IS
THE DEVELOPMENT OF ORGANS ON A
CHIP AND THEIR UTILIZEATION IN
MODELING DISEASE, INJURY, AND
THERAPEUTIC MODALITYS IN A
PATIENT-SPECIFIC FASHION.
SO, I WOULD LIKE TO WELCOME YOU
TO PANEL 4, WHICH IS ABOUT
LEVERAGING DIVERSE DATASETS FOR
MAXIMAL USE FOR NAMs.
WE'RE ASSEMBLED AN OUTSTANDING
GROUP OF FIVE PANELISTS, TO
PROVIDE PERSPECTIVE ON VARIOUS
ASPECTS OF THIS TOPIC.
EACH PANELIST WILL MAKE
INTRODUCTORY REMARKS WITHIN
ABOUT FIVE MINUTES, AND THEN
WE'LL FOLLOW BY 30 MINUTES OF
DISCUSSION.
I'M GRATEFUL TO THE ORGANIZERS
FOR PUTTING TOGETHER THIS
IMPORTANT AND TIMELY WORKSHOP.
ALSO FOR INVITING US TO BE PART
OF IT.
AS YOU SEE HERE ON THE SCREEN,
STARTING FROM THE LEFT, OUR
FIRST PANELIST IS IVAN RUSYN,
PROFESSOR OF VETERINARY MEDICINE
AND PHARMACOLOGY AT TEXAS A & M
AND INVESTIGATOR USING
MICROPHYSIOLOGICAL SYSTEMS FOR
DRUG TESTING.
IVAN WILL SPEAK ABOUT DATA
ANALYSIS APPROACHES TO ESTABLISH
ROBUSTNESS AND REPRODUCIBILITY
OF NAMs.
THE NEXT PANELIST IS DONNA
MENDRICK, WITH THE FDA,
ASSOCIATE DIRECTOR OF REGULATORY
ACTIVITIES, IN THE OFFICE OF THE
CENTER DIRECTOR.
DONNA WILL SPEAK ABOUT THE
APPROACHES TO BUILDING
CONFIDENCE INTO NAMs.
THE THIRD PANELIST IS ANN ERIC
GOURMELON, JOINING FROM PARIS,
FRANCE, PRINCIPAL ADMINISTRATOR
IN TEST GUIDELINES PROGRAM AT
OECD.
AND SHE WILL SPEAK TO US ABOUT
BUILDING MINIMUM CONSENSUS
DATABASES AND DATA TESTING
METHODS.
AFTER ANNE WE'LL HAVE JAMES ZOU,
STANFORD UNIVERSITY WHERE HE'S
AN ASSISTANT PROFESSOR OF
BIOMEDICAL DATA SCIENCE, AND
HE'S ALSO THE FACULTY DIRECTOR
OF THE UNIVERSITY-WIDE STANFORD
DATA HEALTH HUB.
HE'S EXPERTISE IN ARTIFICIAL
INTELLIGENCE, HE WILL SPEAK
ABOUT THE ARTIFICIAL
INTELLIGENCE METHODS THAT ARE
ENABLING IN SILICO NAMs.
AND OUR LAST PANELIST IS JOHN
BURKE.
JOHN IS THE CO-FOUNDER,
PRESIDENT, CEO OF APPLIED
BIOMATH, TWO DECADES OF
EXPERIENCE IN MATHEMATICAL
MODELING IN LIFE SCIENCES, AND
IN BIOLOGY, AND ALSO IN
PHARMACEUTICAL AND BIOLOGY
RESEARCH.
JOHN WILL SPEAK ON INTEGRATING
DISPARATE TYPES OF DATA AND THIS
WILL BE A GREAT TRANSITION INTO
DISCUSSION PART OF OUR PANEL.
NOW LET US MOVE TO IVAN RUSYN'S
REMARKS.
I THINK YOU CAN REMOVE THIS
SLIDE NOW SO PEOPLE CAN SEE
PARTICIPANTS.
>>THANK YOU, GORDANA FOR THE
KIND INTRODUCTION AND TO MEMBERS
OF THE PANEL FOR HAVING US AND
THIS IMPORTANT WORKSHOP.
AS WAS MENTIONED, MY LABORATORY
HAS BEEN INVOLVED IN A VARIETY
OF LARGE AND SMALL AND
CONSORTIUM-BASED EXPERIMENTS
WHERE NEW APPROACH METHODS HAVE
BEEN TESTED IN A VARIETY OF
CONTEXTS, AND MORE RECENTLY
PERHAPS MORE RELEVANT TO THIS
PARTICULAR MEETING IS MY LAB'S
EXPERTISE IN TESTING TISSUE
CHIPS ON MICROPHYSIOLOGIC
SYSTEMS ORIGINALLY WITH FUNDING
FROM DAN TAGLE'S SHOP FROM NCATS
AND FOR THE LAST FOUR YEARS AS A
CONSORTIUM OF PHARMACEUTICAL
COMPANIES, GOVERNMENT AGENCIES,
TRADE ASSOCIATION, AND ALSO A
CONSUMER GOODS COMPANY.
AND WHAT WE'VE BEEN DOING FOR
THE LAST 3 1/2 YEARS AS PART OF
THE THIS CONSORTIUM IS DEFINING
WHAT SHOULD BE TESTED EVERY YEAR
AND WHICH MODELS SHOULD BE
TESTED, ALSO HOW THE DATA SHOULD
BE COLLECTED AND SHARED.
THE RESULT OF THAT HAS BEEN ON
AVERAGE EVERY YEAR 2,000 TISSUE
CHIPS AND A LARGER NUMBER OF IN
VITRO 96 OR 384 WELL PLATE
MODELS.
FROM THE VERY BEGINNING OF MY
TIME IN TOXICOLOGY, ESPECIALLY
IN WORKING ON IN VITRO METHODS,
AND HOW THEY COMPARE TO HUMAN
TOXICOLOGY OR ANIMAL MODELS, THE
TRANSPARENCY OF THE DATA AND
SHARING OF THE DATA HAS BEEN
MOST IMPORTANT COMPONENT TO US.
THIS IS NOT A NEW PROBLEM, SOME
OF THE ORIGINAL ADVOCATES FOR
REPLACEMENT OF ANIMALS HAVE
BEENED A ROW INDICATING AS
EARLY -- ADVOCATING 200 YEARS
AGO, FULL AND DETAILED
PUBLICATION OF THE RESULTS IS
KEY TO ESTABLISHING CONFIDENCE
IN THESE MODELS.
I AGREE WITH NCATS ORIGINAL IDEA
OF FUNDING A DATABASE TO HOUSE
TISSUE CHIP DATA, QUIPING NOT
ENOUGH DATA TO HOUSE, DAN TAGLE
AND COLLEAGUES PERSEVERED AND
FUNDED A DATABASE CENTER AND
ACTUALLY THAT'S BEEN PROVEN
TREMENDOUSLY USEFUL, BECAUSE NOT
ONLY WE BUT ALSO OTHERS HAVE
BEEN PUTTING DATA IN THERE, AND
I LOOKED AT THE NUMBERS A YEAR
AGO, AND DATA FROM OUR CENTER
WAS 85% OF ALL OF THE DATA IN
DATABASE AT THAT TIME.
AND I ASKED MY COLLEAGUES AT THE
DATABASE TO PULL THE DATA LAST
WEEK AND I'M NOW GLAD TO SEE
WE'RE ONLY ABOUT 35% BECAUSE
NCATS HAS BEEN ENCOURAGING
GRANTEES TO DEPOSIT INFORMATION,
AND IT'S NOT JUST SIMPLY ANY
INFORMATION BUT IT'S HIGHLY
STRUCTURED INFORMATION, AND THE
STRUCTUREDNESS OF THAT
INFORMATION REALLY IS THE DOOR
TO THE FUTURE ANALYSIS USING ANY
TYPES OF MACHINE LEARNING OR
A.I. APPROACHES.
NOW, JUST TO CONCLUDE, I THINK
HOPEFULLY WHAT WE'RE GOING TO
TALK ABOUT TODAY IS WHETHER OR
NOT NAMs REALLY ARE A SOURCE
OF BIG ENOUGH DATA FOR US TO
REALLY BRING THEM INTO THE
CONTEXT OF LARGE SCALE MODELING
OR NOT.
I'M NOT YET SURE THAT TRULY
COMPLEX NAMs HAVE PROVIDED A
LOT OF INFORMATION BECAUSE IN
THE DATABASE RIGHT NOW THERE'S
ABOUT 450,000 DATA POINTS, FROM,
YOU KNOW, DOZENS OF TISSUE CHIP
CENTERS.
THAT DOESN'T INCLUDE MICROARRAYS
OR RNAseq BUT IT'S REALLY
BIOCHEMICAL ASSAYS OR OTHER
TIMES OF ASSAYS THAT WE'RE
PHENOTYPEING THESE MODELS ON.
IN MY OPINION WE NEED MORE DATA,
WE ALSO NEED TO REALLY WORK WITH
THE DEVELOPERS TO MAKE SURE THEY
UNDERSTAND WHY THEY ARE
DEVELOPING CERTAIN MODELS
BECAUSE WE CAN HAVE A LOT OF
DATA BUT WE NEED TO HAVE THE
RIGHT KIND OF DATA FOR THESE
ANALYSES.
WITH THAT I'LL YIELD THE FLOOR
TO MY COLLEAGUES, AND LOOKING
FOR FORWARD TO THE DISCUSSION.
>>TERRIFIC.
THANK YOU SO MUCH.
DONNA, YOU WILL BE NEXT PLEASE.
>>OKAY.
THANK YOU VERY MUCH.
THANK YOU FOR THE INVITATION.
I WANT TO START BY SAYING A
DISCLAIMER THAT I'M SPEAKING FOR
MYSELF, NOT THE FDA.
ALONG WITH SUZIE FITZPATRICK WE
CHAIR THE ALTERNATIVE METHODS
WORKING GROUP, I HOPE YOU'LL
SEARCH GOOGLE FDA ALTERNATIVES
YOU'LL PULL UP THE WEBSITE.
WE TALK ABOUT THE WORK, HAVE
EXAMPLES OF PEER-REVIEWED
PUBLICATIONS, SOME
PRESENTATIONS, WE'RE TRYING TO
INCREASE TRANSPARENCY BECAUSE
THE FDA IS WORKING HARD ON
NAMs.
WE HAVE A LOT OF PEOPLE WORKING
ON IN SILICO MODELING, ALMOST
EVERY CENTER HAS VARIOUS NAMs,
WE'RE DOING A LOT OF WORK AND
CAN'T SEEM TO GET THAT MESSAGE
OUT VERY WELL.
SO PLEASE LOOK AT THAT WEBSITE.
I HAVE A VERY ECLECTIC
BACKGROUND IN ACADEMIC
BIOTECHNOLOGY, EXPERIENCE IN IN
VITRO AND IN VIVO AND IN SILICO
MODELS.
I TENDS TO UNDERSTAND POSITIVE
AND NEGATIVES OF BOTH, I KNOW
IT'S OBVIOUS BUT I WANT TO MAKE
SURE WE NEED TO APPROACH
(INDISCERNIBLE) ONE THING THAT
BOTHERS ME IN VITRO SYSTEMS
PEOPLE USE TOXIC MOLECULES BUT
NEGATIVE CONTROL IS MEDIA.
THAT IS NOT CORRECT.
YOU NEED NEGATIVE -- USUALLY
COMPOUNDS DON'T CAUSE TOXICITY
YOU'RE LOOKING AT BECAUSE
OTHERWISE YOU'RE SHORT-SHIFTING
YOURSELF.
WE NEED MULTIPLE DONORS, YOU
KNOW, IT CAN BE HARD TO FIND
SOME CELLS THAT WORK IN AN MPS
SYSTEM, YOU MIGHT BE STUCK WITH
ONE OR TWO DONORS, MY CONCERN
ARE YOU REALLY LOOKING AT ONE
PERSON'S RESPONSE VERSUS
MULTIPLE PEOPLE, AND YOU WOULD
NEVER DO AN ANIMAL STUDY WITH
ONE ANIMAL.
WE NEED MULTIPLE DONORS TO
REFLECT ETHNICITYS, THAT CAN BE
DIFFICULT BECAUSE SOMETIMES, WE
NEED TO GO IN THAT DIRECTION.
YOU SEE WITH IN SILICO
APPROACHES WE NEED THE BEST
TRAINING AND TEST AVAILABLE,
HIGH QUALITY DATA, BUT
PARTICULARLY IT'S IMPORTANT HOW
YOU TRAIN AND TEST YOUR MODEL.
YOU DON'T WANT TO OVERFIT AND
OVERPROMISE.
PEOPLE ASK ABOUT STANDARDS.
STANDARDS ARE IMPORTANT BUT IT'S
ALWAYS A BALANCING ACT.
IF YOU PUT THEM IN PLACE TOO
SOON, YOU STIFLE INNOVATION.
IF YOU DON'T PUT SOMETHING IN
PLACE AT THE RIGHT TIME PEOPLE
CAN'T OPERATE.
SO IT'S ALWAYS A QUESTION WHEN
DO YOU SET STANDARDS.
INTEGRATING NAMs CAN BE
DIFFICULT.
AT THE END OF THE DAY IT WON'T
BE ONE MPS SYSTEMS, IT WILL BE
MULTIPLE, HOW YOU INTEGRATE THAT
DATA AND HOW YOU -- WITH FIRE
WALLS, FDA, IT CAN BE DIFFICULT
TO BRING DATA IN, ET CETERA, FOR
VARIOUS REASONS.
WHOLE DATA EXCHANGE CAN BE
PROBLEMATIC.
USERS DO NOT LIKE BLACK BOXINGS.
WITH A.I. MODELS, WHAT DATA, HOW
DID YOU TRAIN, WHAT WAS YOUR
ACCURACY?
SAME WITH IN VITRO SYSTEMS.
WE PROVIDED AS MUCH DATA AS YOU
CAN, YOU NEED TO BUILD
CONFIDENCE.
AND PEOPLE ARE HARD WIRED NOT TO
ACCEPT CHANGE.
I THINK SCIENTISTS ARE SUPPOSED
TO BE MORE OPEN BUT WE'RE
PEOPLE, IT'S THE SAME WITH US.
YOU HAVE TO WIN HEARTS AND
MINDS.
AS TERRY MENTIONED EARLIER ONE
OF THE THINGS WE HEATHER FROM
VARIOUS PHARMACEUTICAL
COMPANIES, IN THE RAD SYSTEM YOU
HAVE A LOT OF IN VIVO DATA, AN
IDEA OF TIMING, DOSE, RESPONSES,
HISTOPATHOLOGY, IN HUMAN EVEN IF
HAVE YOU ADVERSE EVENT, IN A
CLINIC, YOU RARELY DO A BIOPSY
SO YOU DON'T UNDERSTAND A LOT OF
WHAT DAMAGE IT CAUSED.
SO PEOPLE THINK YOU CAN JUST GO
FROM HUMAN MPS TO HUMAN IN VIVO
BUT A LOT OF PEOPLE ARE
EXPRESSING THE FACT THEY ARE NOT
GOING TO HAVE CONFIDENCE IF THEY
CAN'T COMPLETE THE PARALLELOGRAM
AND LOOK AT CONCORDANCE BETWEEN
RATS AND IN VIVO AND IN VITRO.
ANIMAL MSS ARE NEEDED, THE
CHALLENGE IS NO ONE IS FUNDING
ANIMAL VERSION, WE NEED TO FIND
SOME WAY TO FUND ANIMAL VERSIONS
TO SERVE PURPOSES BUT HELP BUILD
CONFIDENCE IN HUMAN MPS IF
YOU'RE GOING TO MAKE THAT
CONCORDANCE.
AGAIN, I DON'T THINK IT HAS TO
BE DONE FOR EVERY SCENARIO BUT
YOU NEED SOME DATA N HUMAN
DELIVER WITH A HUMAN MPS, FOR
EXAMPLE, SHOW ALL TYPES YOU SEE
IN THE CLINIC.
I'VE BEEN INVOLVED IN DISRUPTIVE
TECHNOLOGY FOR MANY YEARS.
WHAT I CONTINUALLY SEE IS PEOPLE
OVERSELL.
AND I KNOW WHY YOU OVERSELL AT
THE BEGINNING TRYING TO BUILD
P.R. AND GET FUNDING BUT THAT
COMES BACK AND STOPS THE WHOLE
FIELD, NOTHING IS 100% PERFECT
AND WILL SOLVE ALL THE NEEDS,
PEOPLE GET DISENFRANCHISED WITH
YOUR APPROACH AND IT CAN TAKE
DECADES TO COME BACK OUT.
WE NEED TO FIND WAYS TO
UNDERSELL AND OVERDELIVER, THE
ONLY WAY WE'RE MOVING FORWARD.
I'LL END WITH THAT.
>>OKAY.
THANKS SO MUCH, DONNA.
IT WAS GREAT.
ANNE, YOU WOULD BE NEXT.
>>HELLO.
GOOD AFTERNOON, I GUESS.
I'M ANNE GOURMELON, I COME FROM
THE SLIGHTLY DIFFERENT CONTEXT
OF WORK WHERE AT OECD WE DEAL
WITH SETTING STANDARDS FOR
TESTING -- WELL, METHODOLOGIES
TO TEST AND ASSESS CHEMICALS.
AND MOSTLY BY CHEMICALS WE MEAN
PESTICIDES, INDUSTRIAL
CHEMICALS, NANOMATERIALS,
COSMETICS, BUT NOT NECESSARILY
PHARMACEUTICAL DRUGS.
AND THIS COMES WITH THE
CHALLENGE OF HAVING LIMITED DATA
TO BUILD THOSE STANDARDS, AND TO
REACH REGULATORY ACCEPTANCE OF
THE METHODS.
SO REALLY HAVE TWO POINTS.
ONE OF THE CHALLENGES I SEE IN
THE CASE OF NAMs FOR CHEMICAL
SAFETY TESTING AS I SAID IS THE
LACK OF OR LIMITED DATA
AVAILABLE, ESPECIALLY FROM
HUMAN, WHICH IS THE TARGET
SPECIES, RIGHT?
AND THEREFORE THERE'S REALLY A
STRONG NEED TO BUILD CONSENSUS
DATABASES TOGETHER THAT CAN BE
AUGMENTED AS EXPERIENCE IS
GAINED AND ALTERNATIVE DATA IS
GENERATED.
BUT STRUCTURED DATABASES THAT
WOULD IDEALLY ALSO ENCOMPASS
PREPARATORY DATA, WE'VE HEARD
EARLIER TODAY FROM NICOLE AND
FROM OTHERS, I THINK TERRY WAS
MENTIONING ALSO ENCRYPTION OF
DATA, OR WAYS TO PROTECT THE
INTELLECTUAL PROPERTY OF THOSE
WHO HAVE GENERATED THOSE DATA OF
COURSE, BUT IT'S REALLY
IMPORTANT TO HAVE CONSENSUS
DATABASES THAT ALL OPERATORS CAN
USE TO PUT THEM ON ALMOST EQUAL
FOOTING BECAUSE THEN WHEN
PUTTING THEM ON EQUAL FOOTING
YOU ALSO INCREASE THE
COMPETITION AMONG THEM, WITH THE
VIEW TO HAVE, YOU KNOW, THE BEST
AVAILABLE METHODOLOGIES AMONG
ALL THOSE EMERGING TECHNOLOGIES,
AND IT'S PRETTY IMPORTANT TO
HAVE THESE CONSENSUS DATABASES.
WE HAVE SEEN, FOR INSTANCE,
NICOLE AND OTHERS WERE
MENTIONING THIS MORNING THE WORK
THAT HAS BEEN DONE ON SKIN
SENSITIZATION, AND PEOPLE THAT
NICOLE MAY KNOW VERY WELL THAT
PRIOR TO DIVING INTO
INTEGRATION OF NAMs, THE
DIFFERENT IN VITRO, IN CHEMICO,
IN SILICO METHODS TO MAKE SENSE
OF THEM FOR SPECIFIC USE
CONTEXT, IT HAS BEEN ESSENTIAL
TO COME TO SOME AGREEMENT WITH
THE REGULATORS ON CONSENSUS
DATABASE OF SUFFICIENT NUMBER OF
CHEMICALS INCLUDING THE
NEGATIVES.
IT'S VERY DIFFICULT TO FIND AND
FIND NEGATIVE DATA, TRULY
NEGATIVE DATA, AND VERY OFTEN
DATABASES WILL BE SKEWED TOWARDS
POSITIVE CHEMICALS, AND WE KNOW
VERY WELL THAT FOR MODELS TO
BE -- MODELS, METHODS, TO BE
TRUSTED, THEY HAVE TO EQUALLY
PREDICT A RANGE OF POSSIBLE
RESPONSES AND NOT ONLY THE --
YOU KNOW, THE POSITIVE OR THE
STRONGEST ACTIVE SUBSTANCES.
SO, THAT WAS ONE OF MY POINTS.
THE OTHER ONE, YEAH, AND ALSO
THE DATABASES NEED TO BE PUBLIC,
OF COURSE.
ANOTHER POINT I WANTED TO MAKE
IS THAT IN -- ESPECIALLY IN
CHEMICAL SAFETY TESTING,
REGULATORY PURPOSES, WE NEED TO
BE A LITTLE BIT BETTER AT
UNDERSTANDING, UNDERSTANDING AND
USING IN A COMPREHENSIVE MANNER
DIVERSITY OF MATHEMATICAL
APPROACHES, STATISTICAL
APPROACHES, THAT HELP US, I
WOULD SAY, FILL THE GAP OF THESE
LIMITED DATA AVAILABLE, SO BY
DOING SIMULATIONS, THERE ARE ALL
KINDS OF APPROACHES,
BOOTSTRAPING, CROSS-VALIDATION,
A LOT OF DIFFERENT METHODS FOR
DIFFERENT PURPOSES, OF COURSE,
BUT THEY REALLY HELP IN THE CASE
OF LIMITED DATASETS, ESPECIALLY
WHEN DATASETS FOR TRAINING AND
FOR TEST -- FOR METHOD
VALIDATION ARE A BIT OVERLAPING.
IT'S REALLY IMPORTANT TO BE ABLE
TO USE OTHER APPROACHES AND TO
GUIDE REGULATORS TO MAKE THEM
UNDERSTAND, SO TO SPEND A LOT OF
TIME WITH THEM, TRAINING THEM,
MAKING THEM UNDERSTAND WHAT ALL
THESE MATHEMATICAL APPROACHES
ARE ABOUT, AND RECENTLY AT AN
OECD MEETING OF THE CHEMICALS
AND BIOTECHNOLOGY COMMITTEE,
EARLY JULY, FOR THE FIRST TIME
MEMBER COUNTRIES HAVE SAID THAT
THEY REALLY NEED -- THEY SEE
A.I. A ONE OF THESE BIG DATA,
BIG TECHNOLOGY WHERE THEY DON'T
HAVE CAPACITY AT NATIONAL LEVEL
TO REALLY APPROACH A.I., AND
HAVE THE CONFIDENCE NEEDED TO
UPTAKE A.I. AS, YOU KNOW, A
METHOD OR TECHNOLOGY TO
INTEGRATE ALL DATA AVAILABLE, SO
I THINK IT'S REALLY CRITICAL TO
ADDRESS THESE NEEDS.
IT'S ABOUT DATA, LEVERAGING
DIVERSE DATASETS FOR MAXIMALLY
USED NAMs, RIGHT?
THAT'S THE THEME OF OUR SESSION.
THESE WERE MY TWO KEY MESSAGES.
MIND THE TECHNOLOGICAL GAP.
>>THANKS SO MUCH, ANNE.
JAMES, YOU'RE NEXT.
>>GREAT.
THANK YOU VERY MUCH TO THE
ORGANIZERS AND EXCITED TO BE
ABLE TO PARTICIPATE.
I'LL BE TALKING ABOUT A.I.
ENABLEED IN SILICO APPROACHES,
IN SILICO DATA, AS RESOURCE FOR
NAM.
AND A.I. HAS BEEN -- ESPECIALLY
GENERATIVE MAKING ADVANCES
RECENTLY.
YOU'VE BEEN USING CHAT GPT AND
LANGUAGE MODELS.
WE'RE IN AN INTERESTING TIME
WHERE A.I. APPROACHES CAN BE
USED TO GENERATE IN SILICO DATA
FOR BIOMEDICAL RESEARCH
ESPECIALLY IN SETTINGS WHERE
EXPERIMENTS ARE NOT FEASIBLE OR
JUST TOO EXPENSIVE TO PERFORM.
IN SILICO APPROACHES CAN HELP US
GENERATE SOME INITIAL
PRELIMINARY INSIGHTS.
I WANT TO ILLUSTRATE BY GIVING
THREE QUICK EXAMPLES TO MAKE IT
CONCRETE OF HOW GENERATIVE A.I.
CAN HELP US APPROACH NAM.
FIRST EXAMPLE USING PROTEIN
LANGUAGE MODELS, APPROACH FOR IN
SILICO DATA FOR VARIANT
INTERPRETATION.
THERE'S BEEN EXCITING
DEVELOPMENT BASED ON TRAINING
LARGE LANGUAGE MODELS, PROTEIN
IMMUNOASSAY DATA, TO PREDICT
PROTEIN STRUCTURE, ALPHA FOLD IS
ONE EXAMPLE, BECOMING A POWERFUL
RESOURCE FOR IN SILICO VARIANT
INTERPRETATION, BASICALLY ONE
THING PEOPLE CAN DO NOW IS LOOK
AT IF YOU HAVE A PARTICULAR
CODING MUTATION YOU CAN
INTRODUCE THAT IN IN SILICO INTO
PROTEIN SEQUENCE, HOW DOES THAT
AFFECT THE LANGUAGE MODELS, TO
ASSESS ALL THE POSSIBLE CODING
MUTATIONS TO ANNOTATE FUNCTIONAL
VARIATIONS.
WE STILL NEED TO VALIDATE THIS
USING DATA FROM THE SCAN BUT
IT'S A POWERFUL RESOURCE FOR THE
COMMUNITY.
SECOND EXAMPLE IS USING
GENERATIVE A.I. MODELS TO
GENERATE SYNTHETIC DATA, MAYBE
BECAUSE IT'S TOO EXPENSIVE.
ONE EXAMPLE IS ONE AREA WE'VE
BEEN EXPLORING RECENTLY TO
BASICALLY USE A.I. TO
COMPUTATIONAL GENERATE SPATIAL
TRANSCRIPTOMICS AND POET QUOTEIC
DATA FROM WIDELY AVAILABLE
HISTOLOGY IMAGES, ROUTINELY
COLLECTED C OLLECTED IN CLINICAL
WORKFLOWS.
THAT PROVIDES RICHER INFORMATION
BEYOND WHAT PEOPLE CAN NORMALLY
OBTAIN.
THIRD IS USING SYNTHETIC DATA
FOR CLINICAL TRIALS, ESPECIALLY
BY COMBINING A.I. WITH LARGE
SCALE DATA FROM ELECTRONIC
HEALTH RECORDS.
THIS IS ALSO A REALLY EXCITING
AREA OF A.I.-BASED IN SILICO
APPROACHES, SO ONE AREA PEOPLE
ARE USING THIS TO HELP US
UNDERSTAND EFFECTS OF DIFFERENT
OFF-LABEL USAGES, DRUGS APPROVED
FOR ONE INDICATION BUT USED
OFF-LABEL IN OTHER INDICATIONS
TO -- INSTEAD OF RUNNING A
CLINICAL TRIAL TO TEST OFF-LABEL
USAGES WHICH CAN BE VERY
EXPENSIVE PEOPLE CAN JUST LOOK
AT REAL WORLD DATA FROM THE
CHART,
[AUDIO DISTORTION]
BASEED ON CONTROL ARMS.
IT GIVES A FAST WAY TO PROVIDE
INSIGHT INTO EFFICACY AND SAFETY
OF THESE OFF-LABEL USAGES.
SIMILAR PEOPLE ARE USING A.I. TO
GENERATE SYNTHETIC CONTROL ARMS
THAT CAN THEN BE HELPED TO
AUGMENT CONTROL ARMS OF THEIR
ACTUAL CLINICAL TRIALS.
I THINK GOING FORWARD THERE'S
ALSO A LOT OF POTENTIAL
OPPORTUNITIES FOR USING THINGS
LIKE CHATGPT TO HELP US ORGANIZE
AND INDEX COMPLEX BIOMEDICAL
DATA, ESPECIALLY FOR NAMs.
DATABASES, IT'S HARDER TO WORK
WITH DIFFERENT DATABASES FROM
DIFFERENT SOURCES, AND LANGUAGE
MODELS CAN BE A WAY TO PROVIDE
MORE NATURAL LANGUAGE
INTERFACES, HOW TO HELP OTHER
RESEARCHERS ACCESS AND TO WORK
WITH THESE DIVERSE NAMs
RESOURCES.
>>THANK YOU, JAMES.
JOHN, YOU'RE NEXT AND LAST
BEFORE WE SWITCH TO QUESTIONS.
>>THANK YOU VERY MUCH.
I ALSO WOULD LIKE TO THANK THE
ORGANIZERS FOR INVITEING ME TO
CONTRIBUTE.
THIS IS A VERY EXCITING
OPPORTUNITY FOR US AS A SOCIETY
AND SCIENCE.
SO THANK YOU.
I'D LIKE TO START BY SAYING THAT
I'M PRETTY PASSIONATE ABOUT
USING SYSTEMS MODELING, FRANKLY
HELPING PATIENTS, IT'S EXCITING
TO USE MATHEMATICS AND
SIMULATION, WHETHER YOU'RE A
PHYSICIST, BIOLOGIST, COMPUTER
SCIENTIST, TO HELP PATIENTS
DESIGN BETTER THERAPYS OR STOP
THERAPYS THAT SHOULD NOT WORK,
SAVING TIME AND MONEY.
I LIKE TO COMPARE THIS TO PRETTY
MUCH ANY OTHER KIND OF
ENGINEERING IN OTHER FIELDS,
WHETHER COMPUTER ENGINEER,
ARTICLE ENGINEER, CHEMICAL
ENGINEER, WHERE YOU WORK ON THE
INTERFACE OF HUMANITY AND
PRODUCTS AND TRYING TO MAKE
THINGS BETTER, OPTIMIZATION,
WE'RE DOING THE VERY SAME THING
HERE USING SYSTEMS APPROACHES.
TO BE CLEAR A LOT OF HYBRID
APPROACHES, WHEN I SAY SYSTEMS I
MEAN ORDER DIFFERENTIAL
EQUATIONS, SOMETIMES HYBRID
APPROACHES, SYSTEMS OF
DIFFERENTIAL EQUATIONS WITH
MACHINE LEARNING, WHICH I HOPE
I'LL HAVE TIME TO GET INTO.
BUT WE FOCUS ON THIS, TO YOUR
POINT, WHERE NOBODY LIKES BLACK
BOXES.
IF YOU TAKE STANDARD PK PT
MODELING, THERE'S A LOT KNOWN,
WE NEED THAT, WHEN I TALK ABOUT
SYSTEMS MODELING EVERYONE IN
THEIR MIND HAS A PICTURE HOW A
DISEASE WORKS.
BIOLOGY IS COMPLEX.
WE HAVE A PICTURE OF HOW THERAPY
WORKS, WHETHER IT'S A
TETRAVALENT BINDER, YOU'RE DOING
THIS BECAUSE YOU WANT TO GO TO A
CERTAIN TISSUE, SPARE OTHERS, OR
A GENE THERAPY OF SOME KIND.
THIS IS A REASON WHY.
AND THEN TYPICALLY AT LEAST WHEN
I'M DOING THESE SYSTEMS MODELING
APPROACHES YOU CONVERT THESE
PICTURES INTO A SYSTEM OF
BIOCHEMICAL EQUATIONS BECAUSE
THEY MEAN SOMETHING.
THEY ARE TRANSPARENT.
THEY ARE CLEAR.
THIS ARROW MEANS THIS IS A K ON
AND K OFF BETWEEN LIGAND AND
RECEPTOR, I WANT TO TARGET A
DRUG TO MANAGE THAT SO IT'S AN
ENGINEERING APPROACH USING MATH
AND COMPUTER SCIENCE FOR
SIMULATION.
THAT'S WHAT I MEAN BY SYSTEMS
APPROACHES, WHERE NOW THIS
MATHEMATICAL MODEL CAN ACT AS A
CENTRAL REPOSITORY OF DATA, WE
HAVE HYPOTHESES, AND WE CAN
INCLUDE MORE THAN ONE HIGH
POTENTIAL APPROACHES 'TIS AND
MODEL -- ONE HYPOTHESIS AND
MODEL IT.
IF YOU HAVE MORE THAN ONE IN
VITRO ASSAY, IF YOU HAVE AN IN
VITRO ASSAY, A COMPETITOR,
CLINICAL DATA YOU'RE USING TO
INFORM YOUR SYSTEM, WELL, THIS
ONE MODEL YOU'D LIKE TO BELIEVE
WILL RECAPITULATE A LOT, I WON'T
SAY ALL, BUT A LOT OF THIS DATA
BUT HELPS YOU FIND OUT WHERE
YOUR UNDERSTANDING IS BROKEN.
OH, I CAN'T RECAPITULATE THIS,
WHAT AM I MISSING?
MAYBE I'M OVERSIMPLIFYING.
WE WORK WITH PHARMA AND BIOTECH,
WE HAVE TO WORK ON PROJECT
TIMELINES WITH DATA THAT'S
AVAILABLE.
WE HAVE TO INFORM VERY IMPORTANT
DECISIONS.
WE HAVE TO USE THE RIGHT SIZE
MODEL AT THE RIGHT TIME.
IT'S DIFFERENT RETURN OF
INVESTMENT.
THIS IS WHERE FOR EXAMPLE THE
NEW TARGET STAGE, YOU MIGHT
HAVE -- IN YOU'RE A BIOTECH, TEN
TARGETS YOU'RE GOING AFTER, ON
PAPER THEY ALL LOOK EQUALLY
EFFICACIOUS, BIOLOGY IS COMPLEX,
RIGHT?
SO IT'S IMPORTANT TO HAVE THE
BIOLOGY COMPLEXITY, ALSO
MECHANISM OF ACTION OF THERAPY,
YOU GOT YOUR MONEY FROM A VC
BECAUSE HAVE YOU EXCITING IP
HERE AND YOU WANT IT TO WORK.
WELL, NOW USING DYNAMIC SYSTEMS
APPROACH CAN YOU DO LITERALLY
MILLIONS OF PK/PD SIMULATIONS,
CELL TYPE ONE LOW TO HIGH, K ON
K OFF, ET CETERA, ALL OF THESE
PARAMETERS.
AND SO THESE TEN TARGETS YOU
MIGHT FIND THREE YOU'RE LIKE,
YOU KNOW, FOR A MAJORITY OF
PARAMETERS THIS LOOKS FEASIBLE.
I CAN MAKE A DRUG FOR IT.
I'M NOT TALKING ABOUT EFFICACY.
I'M TALKING ABOUT TARGET
COVERAGE, DEVELOPABILITY.
THERE MIGHT BE ANOTHER SET
WHERE, MAN, I NEED A TIGHT
BINDER, A REALLY LONG HALF-LIFE,
PUTTING THOSE TOGETHER TAKES
MORE TIME, COSTS MORE MONEY,
MAYBE MORE SENSITIVE PARAMETERS.
IN REALITY WE DON'T HAVE THE
SAME NUMBER OF T CELLS, B CELLS,
SITE PER CELL.
WE ALL HAVE VARIABILITY EVEN IF
WE'RE ALL HEALTHY.
WITH PATIENT POPULATIONS, THOSE
DISTRIBUTIONS OF PARAMETER
NUMBERS, SITES, NUMBER OF CELL,
ARE DIFFERENT WITH INDICATIONS,
SUBINDICATIONS, ACROSS
INDICATIONS, EVEN IF THEY ARE
THE SAME.
NOW YOU MIGHT SAY SO MY
GOODNESS, THESE NEXT THREE OR
FOUR THERE'S SEVEN SENSITIVE
MODEL PARAMETERS, MAYBE IN THE
FIRST THREE THERE'S ONLY ONE OR
TWO.
THE ONES WITH FEWER SENSITIVE
MODEL PARAMETERS MEANS I HAVE
FEWER EXPERIMENTS, FEWER -- LESS
UNCERTAINTY, MAYBE THEY ARE
EASIER TO DEVELOP BUT THERE'S A
MODEL THAT SAYS, WELL, I MIGHT
HAVE TO CREATE A DRUG I DON'T
HAVE THE TECHNOLOGY WHERE EVERY
PARAMETER IS UNCERTAIN, DOESN'T
MEAN YOU DON'T WORK ON THEM.
MAYBE YOU HAVE TO GET MORE
MONEY, CHANGE THE TPP, A
SYSTEMATIC WAY TO ARGUE AND
UNDERSTAND THIS DATA
HOLISTICALLY.
THEN AS THE PROGRAM CONTINUES IF
YOU WANT TO BE FAST IN THE FIRST
PROGRAM, YOU GOT TO BE FAST,
HELPING MAKE DECISIONS.
NOW YOU MIGHT HAVE TO ADD MORE
BIOLOGICAL COMPLEXITY BECAUSE
NOW YOU'RE THINKING ABOUT
REGENERATION, THINKING ABOUT
THERAPEUTIC INDEX.
SAY FOR INSTANCE YOU'RE MAKING A
GENE THERAPY OR A MULTI-SPECIFIC
IMMUNE CELL CANCER CELL
INHIBITOR, THINKING ABOUT
SOMETHING IN I AND I,
BALANCINGING THE TREG KEY
EFFECTOR RATIO TO RATIO AND
FEEDBACK OF CYTOKINES,
DEPENDENTING ON CONTEXT OF
CYTOKINE SYNTHESIS, FEEDBACK
STRENGTH, THE NUMBERS OF TREG F
EFFECTOR CELLS WILL IMPACT
EFFICACY AND SAFETY.
YOU WANT TO THINK WHAT DRUG
PARAMETERS WILL MAKE THIS SAFE
AND EFFICACIOUS BECAUSE ONCE
YOU'RE IN THE CLINIC IT'S A
FOREGONE CONCLUSION, RIGHT?
IT'S HARD TO CHANGE THERAPEUTIC
INDEXES, MAY BE TOO LATE.
THIS IS WHERE DOING THIS
CONSTANT FORWARD AND BACKWARD
TRANSLATION TO FIGURE OUT WHAT
IS OPTIMAL IN THE CLINIC, WHAT
IS THE PRE-CLINICAL EXPERIMENT
LOOKING LIKE, WHEN YOU HAVE
BIPHASIC CURVE, IT'S IMPORTANT,
ARE YOU PUTTING TOO MUCH DRUGN
LOSING EFFICACY, THIS COULD HELP
AT PRE-CLINICAL STAGE AND THEN
FIGURING OUT IN THE CLINIC WHERE
THE POTENTIAL UNCERTAINTY IS,
AND INFLECTION POINTS ARE FOR
MULTIPLE SIMULATED PATIENTS, FOR
EFFICACY AND SAFETY, SO WHEN YOU
BACK TRANSLATE THESE ARE THE
PRE-CLINICAL EXPERIMENTS YOU
HOPE TO DO, SOMETIMES YOU CAN'T,
BUT THIS IS WHERE MODELING CAN
HELP US BECAUSE YOU'RE NOT
REGENERATING HYPOTHESES AND
RISKY THIS IS, I THINK THIS IS
WHY THE FDA LIKES THESE
APPROACHES, BECAUSE IT ALLOWS
THE WHAT IFs.
WHAT IF MY TARGET EXPRESSION IS
TEN-FOLD HIGHER, IF MY SYNTHESIS
RATE IS HIGHER, MORE CRITICAL
FOR THEMES.
THERAPIES.
IN VITRO ASSAYS ARE IMPORTANT,
IN ANIMAL MODELS, YES, THERE'S A
LOT OF HIGH HYPOTHESES WE MAY
NOT UNDERSTAND BUT THEY ARE
ALIVE.
THERE'S A LOT OF REASONS TO STAY
AWAY FROM THEM BUT THE
COMPLEXITY IS WHAT MAKES THINGS
DIFFICULT AND THIS IS WHERE
SYSTEMS MODELING HELPS OUT, THIS
IS PRECISELY THE FUTURE OF
NAMs WHERE I CAN PUT IN THE
RIGHT BIOLOGY TO GENERATE THE
RIGHT DATA UNDER THE RIGHT
CONTEXT WITH THE RIGHT SYSTEMS
AND DYNAMICS AND TIME POINTS,
AND AS THESE SYSTEMS GET MORE
AND MORE COMPLEX THE
COMBINATORICS ARE EXPENSIVE.
THESE ARE THE TWO TO CHANGE,
IT'S MOST INFORMATIVE ON BEING A
SUCCESSFUL BEST IN CLASS DRUG IN
THE CLINIC.
YOU DID THIS AT NAMs,
BACKWARDS AND FORWARD.
IT DOES HELP, LIKE ANY
ENGINEERING DOES, DOES TAKE
TIME, I DO HAVE HAZARDS.
ONE IS THERE'S NO SUCH THING AS
MATH MAGIC.
YOU STILL HAVE TO DO THE WORK,
GENERATE DATA, MAKE DIFFICULT
DECISIONS WITH INCOMPLETE DATA
AND KNOWLEDGE.
NAMs CAN HELP BUT WON'T SOLVE
ALL YOUR PROBLEMS.
THERE'S A LOT OF DATA OUT THERE.
WE NEED THE RIGHT DATA, NEED TO
UNDERSTAND IT, MAKE SURE WE
UNDERSTAND THE CONTEXT, AND LIKE
MATH MODELS DATA DOESN'T APPLY
TO ALL ISSUES.
THIS MATH MODEL MIGHT ANSWER
CERTAIN QUESTIONS, DOESN'T
ANSWER ALL QUESTIONS.
I THINK THAT'S REALLY ALL I WANT
TO START OFF WITH.
THANK YOU.
>>OKAY.
THANK YOU, JOHN.
THANK YOU ALL.
SO COULD YOU PLEASE PUT UP THE
SECOND SLIDE WHICH IS THE SLIDE
WITH THE QUESTIONS SO WE CAN
LOOK INTO THEM WHILE WE'RE
HAVING DISCUSSION.
THE NEXT ONE.
PERFECT.
THANK YOU.
OOPS, OKAY.
OKAY.
SO, GREAT POINTS.
AND MAYBE WE CAN START WITH A
QUESTION ONE.
IT IS ABOUT THE DATA, MODELS,
AND THOUGHTS, EXPERIMENTAL AND
ANALYTICAL, THAT WOULD
EFFECTIVELY DRIVE NAM RESEARCH,
TECHNOLOGY DEVELOPMENT AND
TRANSLATION.
I WONDER, DONNA, IF YOU WOULD
REFLECT A LITTLE BIT ON MODELS
THAT YOU THINK WOULD BE
PARTICULARLY EFFECTIVE, OR EVEN
JUST GIVE AN EXAMPLE OF WHAT IS
IN YOUR OPINION MOST EFFECTIVE
APPROACH.
>>I'D LIKE TO FOCUS ON THREE
THINGS, I WILL KEEP IT BRIEF.
FUNDING, UNDERSTANDING THE
CURRENT STATE OF THE ART, AND
HOW WE CAN LEAD TO ADOPTION.
ACADEMIC LABS NEED FUNDING.
WHAT A LOT OF PEOPLE DON'T THINK
ABOUT IS A LOT OF COMPANIES ARE
DEVELOPING PLATFORMS ARE SMALL
COMPANIES, THEY NEED FUNDING.
AND FOR DISRUPTIVE TECHNOLOGY TO
BE ACCEPTED, MENTIONED EARLIER,
CAN TAKE A DECADE OR MORE.
SOME COMPANIES MAY FOLD IF THEY
CAN'T STAY IN BUSINESS LONG
ENOUGH.
I DON'T HAVE THE ANSWER BUT IT'S
SOMETHING TO THINK ABOUT.
WE COULD SPEND TIME WORKING ON A
PARTICULAR PLATFORM, THE COMPANY
GOES UNDER.
IT'S IMPORTANT TO UNDERSTAND THE
STATE OF THE ART.
IF YOU'RE TRYING TO REPLACE OR
AUGMENT AND ANIMAL TEST, HIGHEST
BAR, IT'S IMPORTANT TO
UNDERSTAND STRENGTH AND WEAKNESS
OF CURRENT ANIMAL APPROACH AND
ANY ALTERNATIVE APPROACH.
SOME PEOPLE THINK ANIMALS
PROVIDE NO VALUE, THAT'S
INCORRECT.
SOME PEOPLE THINK, OH, HUMAN
CELLS IN VITRO SOLVES
EVERYTHING.
THAT'S NOT CORRECT EITHER.
AGAIN, YOU'RE WORKING WITH
GENERALLY ONE PERSON, ONE
PERSON'S CELLS, YOU DON'T HAVE
ALL THE DIFFERENT CLINICAL
PARAMETERS GOING ON.
A LOT OF MPSs HAVE ONE CELL
TYPE.
YOU CAN GET MISLED BY THE
TERMINOLOGY.
YOU HAVE TO UNDERSTAND WHAT
VALUE THEY ARE PROVIDING.
YOU HAVE TO UNDERSTAND
LANDSCAPE.
NO ONE IS GOING TO ACCEPT
ALTERNATIVE THAT DOESN'T PROVIDE
AT LEAST DATA PROVIDED BY ANIMAL
STUDY.
YOU NEED A CERTAIN LEVEL OF
CONFIDENCE THAT ALTERNATIVE WILL
HAVE THE SAME -- AT LEAST THE
SAME ACCURACY AS MAIN.
AS THE ANIMAL MODEL MAL MODEL.
I'VE TALKED ABOUT MPS TRYING TO
BUILD AN ANIMAL VERSION TO BUILD
CONFIDENCE.
THE OTHER THING IS I FIND OUT
FROM PHARMACEUTICAL COMPANIES
SOME PROVIDERS ARE APPROACHING
THEM SAYING DON'T WORRY, WE'LL
QUALIFY ALL OUR PLATFORMS.
AND THEY ARE SAYING, YOU DON'T
HAVE TO DO THAT.
YOU KNOW, IF YOU'RE USING IT IN
EARLY STAGE SCREENING, YOU DON'T
HAVE TO HAVE AN FDA-QUALIFIED
PLATFORM, IF YOU'RE USING FOR
DECISION MAKING, YOU MAY NOT
HAVE TO HAVE THAT FOR EFFICACY
EITHER.
COMPANIES THINK THEY WILL GET A
FREE PASS IF THEY QUALIFY,
THAT'S NOT THE ROAD TO GO DOWN,
WON'T GET THEM WHERE THEY THINK
THEY ARE.
IN ANY NEW APPROACH TALK TO THE
END USERS.
ONE THING THAT'S IMPORTANT IN
THE MPS FIELD FDA HAS BEEN
INVOLVED EARLY ON.
WHATEVER THE END USER, WHETHER
CLINICIAN, REGULATORY CENTER,
TALK UP FRONT AND UNDERSTAND
WHAT THEY NEED TO GET THERE.
I WILL STOP ARE THAT.
>>YEAH, THANK YOU, DONNA.
THIS IS GREAT.
THIS TIES BACK TO YOUR AND OTHER
PEOPLE'S REMARKS.
I WONDER, JAMES, IF YOU COULD
EXPAND ABOUT ANALYTICAL
APPROACHES BECAUSE A.I. WAS
MENTIONED MULTIPLE TIMES, NOT
ONLY IN THIS SECTION, AND THEN
ONE OF THE QUESTIONS THAT WAS
BROUGHT UP IS LIKE WHAT SHOULD
BE DONE IN TERMS OF APPROACH,
INFRASTRUCTURE STANDARDIZEATION
TO HAVE A BROADER ADOPTION OF
A.I. METHODS.
YOU GAVE EXAMPLES FOR IN SILICO
BUT THE ISSUE IS MUCH BROADER
THAN WE TALKED ABOUT NAMs.
>>THE THING THAT WOULD MAKE THE
BIGGEST DIFFERENCE IF WE COULD
TIE THE A.I. BASED IN SILICO
APPROACH WAS VERY TARGETED
EXPERIMENTAL VALIDATIONS AND
FOLLOW-UPS, SO I THINK THAT'S
OFTEN THE BIGGEST GAP IN
ADOPTING A.I. ACROSS MANY
DIFFERENT APPLICATIONS.
FOR EXAMPLE, I GIVE THE EXAMPLE,
ALPHA FOLD AND PROTEIN LANGUAGE
MODELS IN SILICO INTERPRETATION,
THAT COULD BE DONE IN SILICO
QUICKLY FOR MANY MILLIONS OF
MUTATIONS, BUT OFTEN THE BIGGEST
GAP IS WE DON'T KNOW FOR WHICH
OF THOSE PREDICTIONS, WHICH OF
THESE MUTATIONS THIS A.I.
PREDICTION IS RELIABLE AND WHICH
MUTATIONS PREDICTIONS ARE LESS
RELIABLE.
IT'S OFTEN THE BIGGEST CHALLENGE
WITH USING A.I. MODELS.
TO ASSESS THAT THEN IDEALLY WE
WANT TO HAVE SOME MORE TARGETED
SMALLER SCALE BUT EXPERIMENTAL
FOLLOW-UPS TO TEST TO ASSESS
VALIDITY.
I THINK BEING ABLE TO CLOSE THAT
GAP, ITERATIVE LOOP WHERE A.I.
WILL MAKE PREDICTIONS, AND THEN
SUGGEST AND RECOMMEND, DESIGN
EXPERIMENTS AND HAVE THE
EXPERIMENTAL FOLLOW-UPS TO
VALIDATE HOPEFULLY IN A RAPID
MANNER, THAT WOULD BE USEFUL IN
ADOPTION OF A.I. METHODS.
>>THANK YOU, JAMES.
LET'S MOVE TO QUESTION 2, IF WE
HAVE TIME REMAINING WE CAN
ALWAYS GO BACK.
SO, THIS IS ABOUT HOW CAN WE
BEST MAINTAIN CONFIDENCE IN THE
DATA?
SO MAYBE IVAN CAN YOU START AND
EXPAND ON POINTS YOU DR. MADE.
>>YES, THANK YOU, GORDANA.
THIS REALLY IS A QUESTION THAT
IS MULTI-DIMENSIONAL, BUT IT'S
NOT TOO LARGE FOR IT NOT TO HAVE
A SOLUTION, AND IN THIS REGARD,
I'D LIKE ACD PANEL TO TAKE A
LOOK AT THE RECENT NATIONAL
ACADEMY REPORT, BUILDING
CONFIDENCE
AND JUST CAME OUT IN JULY,
PROVIDES SOLUTIONS, WHETHER OR
NOT ANIMAL OR CLINICAL DATA IS
THE RIGHT BENCHMARK.
ONE OF THE SOLUTIONS THAT IS
OFFERED IN THAT REPORT IS
ACTUALLY TRYING TO BRING THE
DEVELOPERS OF TECHNOLOGY AND
USERS OF TECHNOLOGY, USERS BEING
REGULATORY AND COMPANIES WHO MAY
WISH TO USE THESE METHODS IN
THEIR OWN WORK, THROUGH REALLY
ALIGNING THE TARGET HUMAN
POPULATION WITH THE TEST METHODS
EXPECTATIONS IN WHEN KNOWN AS
SYSTEMATIC REVIEW, POPULATION
EXPOSURE COMPARATOR AND OUTCOME
STATEMENTS, WE'RE THINKING ABOUT
THE HUMAN POPULATION AND OUTCOME
OF PARTICULAR DISEASE, BUT IT IS
POSSIBLE TO ALIGN MULTIPLE NEW
APPROACH METHODS TO TEST METHOD
PICO TO MAKE THE DEVELOPERS
THINK BEFORE THEY ACTUALLY COME
UP WITH THE SOLUTION OR
POTENTIALLY WHAT THEY THINK IS A
SOLUTION, TRYING TO UNDERSTAND
WHAT IS THE POPULATION THEY ARE
ATTEMPTING TO MODEL AND WHETHER
IT'S A PARTICULAR DISEASE
POPULATION OR TOMORROW HUMAN
POPULATION, HOW THEY ACTUALLY GO
INTO DO EXPOSURES, IS IT
POSSIBLE TO TRANSLATE WHAT'S
HAPPENING IN HUMANS, AND WHAT
THAT I OF MAY CAUSE DISEASE, HOW
THE DRUG WILL BE DELIVERED IN
THAT MODEL SYSTEM, WHAT IS THE
COMPARATOR?
DONNA SAID DON'T JUST USE MEDIA
AS YOUR VEHICLE.
HAVE APPROPRIATE
POSITIVE/NEGATIVE CONTROLS IN
THE SYSTEM AND THE OUTCOME BE
TRANSPARENT ARE YOU MODELING THE
WHOLE DISEASE OR JUST PART OF
THE DISEASE OR ONLY PART OF THE
TISSUE.
SO I THINK CONFIDENCE WILL START
PRIMARILY FROM EVERYONE ALIGNING
ON THE REASONS FOR WHY WE HAVE
THIS PARTICULAR METHOD, AND WHAT
THAT METHOD CAN DELIVER WITHOUT
OVERSELLING, AND THE DATA, THE
STANDARD OPERATING PROCEDURES
AND OTHER THINGS WILL IN SOME
WAYS ARE ALMOST SECONDARY TO
JUST HAVING THE UNDERLYING
PURPOSE FOR WHY THAT TEST
EXISTS, AND WHAT THAT TEST IS
MEANT TO REPLACE OR DELIVER.
SO, WE AND OUR COLLEAGUES HAVE
BEEN TRYING TO APPLY THIS IN THE
WAY IN WHICH WE'RE TESTING
VARIOUS IN VITRO SYSTEMS, AND I
CAN TELL YOU FROM EXPERIENCE IT
MAKES IT MUCH EASIER TO
COMMUNICATE TO FUTURE
PERSPECTIVE USERS CONFIDENCE
RATHER THAN TECHNICAL DETAILS OF
THE MODEL.
>>TERRIFIC.
ANNE, ARE THERE ANY COMMENTS YOU
WOULD LIKE TO ADD, LIKE FROM THE
PERSPECTIVE OF DATABASES THAT
YOU DISCUSSED, AND ALSO FROM THE
PERSPECTIVE OF COLLABORATEIVE
EFFORTS, ALL THIS IS HAPPENING
IN DIVERSE COLLABORATEIVE TEAMS,
TRAINING IS HAPPENING IN DIVERSE
AND COLLABORATEIVE TEAMS,
THERE'S COLLABORATIVE TEAMS,
THERE'S THIS HUGE COMPLEXITY.
WHAT ARE IMPORTANT THINGS TO
BUILD INTO CONFIDENCE INTO THE
DATA WE HAVE HAVING AND
COLLECTING.
>>THANK YOU.
I WOULD AGREE WITH EVERYTHING
THAT IVAN SAID.
I WOULD ADD MAYBE A COUPLE OF
THE REMARKS, IVAN MENTIONED
TRANSPARENCY, AND I THINK IT'S
QUITE CRITICAL THAT AT LEAST A
CERTAIN DEGREE OF TRANSPARENCY
IS AVAILABLE TO THE USERS,
EITHER UPON REQUEST IN REVIEW
PANELS OR UP FRONT, AS MINIMUM
REQUIRED LEVEL OF TRANSPARENCY
FOR THE USERS TO HAVE AN
UNDERSTANDING, HAVE
ACCESSIBILITY TO THE SPECIFIC
TECHNOLOGY THAT IS PROPOSED, SO
THAT THEY CAN ADOPT IT.
AND UNDERSTAND HOW IT CAN BE
USED OR USEFUL IN THEIR SPECIFIC
CONTEXT OF USE, AND SO I WOULD
SAY, YEAH, TRANSPARENCY TO A
CERTAIN DEGREE, EITHER UP FRONT
OR UPON REQUEST IS REALLY
CRITICAL.
THEN I WOULD SAY ALSO, YEAH,
HAVING -- SETTING UP PEER REVIEW
PANELS, OF PEOPLE WHO HAVE
SUFFICIENT UNDERSTANDING OF THE
SPECIFIC TECHNOLOGY, TO ASK
QUESTIONS, PEER REVIEWERS NEED
TO BE SUPPORTED BY REGULATORS,
BY THE FUTURE USERS, OF THE
TECHNOLOGY SO THAT CONCLUSIONS
OF PEER REVIEW PANEL CAN BE
TRUSTED AND FOR WHAT IT IS AND
FOR WHAT THE TECHNOLOGY, WHAT
THE CLAIMS ARE OF A PARTICULAR
APPROACH, NEW APPROACH METHODS.
AND IN TERMS OF SOLUTIONS ALSO I
WAS THINKING WHAT ROLE MAYBE
SCIENTIFIC SOCIETIES, WE HEARD
EARLIER TODAY THE ROLE OF
SCIENTIFIC SOCIETIES, I WAS
THINKING THEY ARE AT REALY AN
INTERSECT BETWEEN RESEARCHERS, I
WOULD SAY A COMMUNITY OF
RESEARCHERS, RIGHT?
THERE IS REALLY COLLECTIVE
INTELLIGENCE AND KNOWLEDGE IN
SCIENTIFIC SOCIETIES, AND I
THINK ONE ROLE IS THEY COULD
PLAY IS TO FACILITATE ACCESS TO
NEW TECHNOLOGIES, TO NAMs, FOR
THE USERS DEVELOPING, YOU KNOW,
TRAINING, EDUCATIONAL MATERIAL,
AND I THINK ALL OF THESE
TOGETHER WOULD HELP MAINTAIN
CONFIDENCE IN THE METHODOLOGIES,
TECHNOLOGIES, AND ULTIMATELY THE
DATA GENERATED.
>>THAT'S GREAT.
THANK YOU.
SO, LET'S TURN TO QUESTION 3,
REALLY THE MOST COMPREHENSIVE
AND SOMEHOW INTEGRATING ALSO
SOME ASPECTS OF THE FIRST TWO.
WHAT APPROACH DO WE RECOMMEND
FOR MAINTAINING, SHARING,
INTEGRATING NAM DATA.
SO, JOHN, IF YOU WOULD START
PLEASE.
JOHN BURKE?
>>YES, IT'S A DOOZY.
I'M GOING TO TRY TO STAY CALM.
FIRST AND FOREMOST WE HAVE TO
HAVE TRUST IN THE SYSTEM.
AND THERE HAS TO BE
TRANSPARENCY.
AND THIS IS OBVIOUS, RIGHT?
WE HAVE TO TRUST THE DATA, IT'S
HIGH QUALITY DATA, WE HAVE THE
RIGHT CONTROLS.
BUT WHEN YOU GET DOWN INTO THE
DATA MANAGEMENT, NOT ONLY DO WE
HAVE TO SAVE THE DATA, BUT I
THINK WE HAVE TO HAVE TECHNOLOGY
TO UNDERSTAND THE MACRO
CONSTANTS OR MACRO DATA, LIKE
WHY DID I CHOOSE TO SET MY MODEL
ARE MENTAL HEALTH OR NEURONAL
TISSUE, ENDOMETRIOSIS, WHATEVER
SYSTEM I'M WORKING ON, THIS IS
THE FUTURE, IT'S VERY, VERY
COMPLEX, THERE'S A LOT OF
POSITIVE AND NEGATIVE FEEDBACK
SYSTEMS.
WHY DID I SET UP TO HAVE THIS
MANY CELLS, THERE HAS TO BE A
REASON.
SCIENTIST WHO MAY NOT BE
MATHEMATICIAN OR ENGINEER OR
BIOLOGIST OR PROTEIN ENGINEER,
OR MEDICINAL CHEMIST, WE LOOK AT
THINGS DIFFERENTLY.
I CAN POKE INTO THIS DATA AND
SAY THIS CAME FROM THIS PIECE OF
LITERATURE, THIS CAME FROM THIS
CERTAIN DATA.
I CHOSE THIS PATHWAY IN ESSENCE
BECAUSE THIS IS A VERY ITERATIVE
APPROACH, WHERE MAYBE RIGHT FROM
THE GET-GO THERE WAS A LARGE
MACHINE LEARNING ANALYSIS ON A
CORPUS OF DATA THAT SAID THESE
FIVE PATHWAYS ARE THE MOST
IMPORTANT PATHWAYS FOR MY
INDICATION.
AND THESE ARE THE TEN REASONS
WHY, THE TEN PIECES OF DATA THAT
I THINK ARE MOST IMPORTANT.
BUT THEN THE NEXT STEP IS WE
CONVERT THIS SYSTEMATICALLY INTO
A SYSTEM OF ORDINARY
DIFFERENTIAL EQUATIONS.
BECAUSE IT'S NON-LINEAR SOME
PARAMETERS I CAN CHANGE, IT
WON'T CHANGE THE PK/PD TOO MUCH,
PATIENT VARIABILITY.
SOME PARAMETERS, IF I CHANGE A
WEE BIT IT COULD GO BONKERS,
BECAUSE OF SENSITIVITY,
ANALYSIS, POTENTIAL VARIABILITY.
YOU HAVE TO UNDERSTAND DIGGING
DOWN INTO DATA WHY DECISIONS
WERE MADE, RIGHT?
NOW YOU DO THE EXPERIMENT WITH
NAMs, THAT'S PART OF THE DATA
BECAUSE IT'S MORE BIOLOGY, MORE
INTERACTIONS, MORE COMPLEXITY,
BUT WE SYSTEMATICALLY FIGURE OUT
WHAT WE'RE GOING TO CHANGE
BECAUSE WE DON'T HAVE THIS IN
TIME AND MONEY, HOW IS THIS
INTEGRATED WITH STANDARD IN
VITRO ASSAYS, ANIMAL MODELS, TO
ENTER GET FROM ANY KIND OF
SCIENTIFIC BACKGROUND TO START
HAVE SCIENTIFIC DISCUSSIONS WITH
TEAMMATES, NOW WE CAN LOOK AT A
PICTURE OF THIS IS HOW WE THINK
THE DISEASE WORKS, THIS IS WHERE
THE MODEL ISN'T WORKING.
I WOULD DO EXPERIMENTS AROUND
THIS.
THIS IS WHERE IT'S WORKING VERY
WELL.
THIS IS GREAT.
THIS PART I TRUST.
THIS DATA I DON'T TRUST.
SO IT ENABLES A REAL SYSTEMATIC
DISCUSSION THAT'S ALWAYS BASED
ON THE COMPLEXITY OF BIOLOGY AT
THE RIGHT TIME.
I ALSO LIKE WHAT WAS BROUGHT UP,
THE CUSTOMER IS ALWAYS VERY
IMPORTANT.
I KNOW THAT MIGHT SOUND GROSS,
BUT IF YOU'RE WORKING, FOR
EXAMPLE, WHETHER YOU'RE INSIDE
LARGE PHARMA OR IN A BIOTECH,
THERE'S OFTEN DISCUSSIONS ON
KILLING PROJECTS OR NOT, IT'S
HARD TO KILL A PROJECT.
IF YOU CAN WORK WITH THE CSO OR
VP OR HEAD OF DISCOVERY, AND TO
USE THIS LOGICALLY TO JUSTIFY
KILLING A PROGRAM THAT'S
ACTUALLY VERY GOOD, RIGHT?
NOW WE'RE NOT LOSING
OPPORTUNITY, TIME, MONEY,
BECAUSE THESE PROGRAMS TAKE 15
YEARS TO SEE PATIENTS, WE ONLY
HAVE SO MUCH TIME OR MONEY AND
HOW CAN WE USE THIS NAMs DATA
ITERATIVELY TO MAYBE DESIGN THE
TPP OR LEAD GENERATION STRATEGY
OR HOW TO PRIORITIZE EXPERIMENTS
SO WHEN WE GET TO IND WE HAVE
THE MOST INFORMATIVE DATA, SO WE
CAN MAKE OUR BEST FIRST TUMOR
DOSE PREDICTION, MAYBE TO SAVE
TIME, A DOSE OR TWO IN THE
CLINIC, BETTER FOR PATIENTS,
BETTER FOR THE COMPANY.
MAYBE IT'S BEST IN CLASS.
MAYBE THERE'S A WAY YOU CAN DO
SOMETHING IN SILICO TO SAY THIS
IS GOING TO BE THIS DRUG, WHAT'S
COMING OUT IN FIVE YEARS, IMPACT
DECISION MAKERS.
THIS IS GOING TO BE WORTH A $20
MILLION PHASE I OR PHASE II
STUDY BUT YOU WANT TO MAKE SURE
YOU HAVE THE RIGHT DATA TO
REDUCE LATE STAGE, YOU KNOW,
CLINICAL FAILURE RATE.
HOPEFULLY IT'S FIRST IN CLASS,
BEST IN CLASS, WE HAVE THAT
RIGHT DATA.
SO IT'S -- TO RECOMMEND
MANAGING, SHARING, INTEGRATING,
YEAH, WE NEED GOOD SCIENCE BUT
HAVE TO IDENTIFY THE QUESTIONS
THAT REALLY MATTER I THINK.
>>OKAY.
THAT'S GREAT.
WE DO HAVE A FEW MORE MINUTES,
EVEN I WAS WONDERING IF YOU CAN
ADD YOUR PERSPECTIVE, SAME
QUESTION, IVAN.
>>SIX OR SEVEN YEARS AGO I WAS
SKEPTICAL WHETHER COMPLEX NEW
APPROACH METHODS,
MICROPHYSIOLOGIC SYSTEMS WOULD
DELIVER ENOUGH DATA BUT ALSO
THERE HAS BEEN A GREAT SUPPORT
FROM THE FIELD OF ENVIRONMENTAL
TOXICOLOGY TO LARGE SCALE DATA
COLLECTION PROGRAMS THAT ARE A
PARTNERSHIP OF NIEHS, NCATS,
EPA, TOX CAST, TOX21 PROGRAMS.
THE DASHBOARD BUILT, INTEGRATED
CHEMICAL ENVIRONMENTS HOUSED IN
DR. KLEINSTREUER'S OFFICE OR EPA
TOX CAST DASHBOARD, THEY ARE
TREMENDOUS REPOSITORYS OF
SYSTEMATICALLY COLLECTED AND
PARSED AND OUT AND DEPOSITED
INFORMATION THAT STARTS FROM
QUALITY OF THE CHEMICAL THAT
WENT INTO THOSE TESTS TO THE
ACTUAL CONDITIONS, TO THE
OUTCOMES, TO ACTUALLY THEN
LINKAGE TO ANIMAL RESULTS
BECAUSE AGAIN EPA AND OTHERS
HAVE DONE WONDERFUL JOB OF
PUTTING ANIMAL STUDIES TOGETHER.
THE GREAT THING IS A LOT OF THAT
INFORMATION IS PUBLIC, WAS
MENTIONED A LOT OF PHARMA DATA
IS NOT PUBLIC, PRE OR POST
COMPETITIVE SPACE, GOING TO HELP
US INTERPRET INFORMATION BUT WE
ALL NEED TO BE OPEN ABOUT
DELIVERING ALL OF OUR
INFORMATION, IN MORE THAN JUST
EXCEL SPREADSHEETS, AS
SUPPLEMENTAL DATA TO
PUBLICATIONS.
MICROPHYSIOLOGICAL
SYSTEMS/DATABASE AT NCATS, A
GREAT EXAMPLE OF HOW THAT CAN BE
DONE.
I'M A BRIG PROPONENT OF
DATABASES WITH PERSONAL
COMMITMENT FROM RESEARCHERS TO
DELIVER THAT INFORMATION.
AND TAKE THE TIME TO ACTUALLY
PUT IT IN BECAUSE IT'S A
THANKLESS JOB TO ACTUALLY PUT IT
IN.
IT'S MORE INTERESTING TO
ACTUALLY DO THE EXPERIMENTS.
>>I THINK THIS IS A TERRIFIC
DISCUSSION.
I WOULD LIKE TO PROPOSE WE HAVE
LIKE THREE MINUTES REMAINING,
CAN EACH OF YOU MAKE ONE
SENTENCE STATEMENT ABOUT
SOMETHING YOU WOULD LIKE TO
HAPPEN OVER THE NEXT YEAR OR SO
THAT WOULD REALLY MOVE THE
NEEDLE IN THE RIGHT DIRECTION,
THAT WE TRY TO DEFINE TODAY.
SO, LET'S SAY START WITH YOU,
DONNA, JUST AN EXAMPLE, I MEAN
DOESN'T HAVE TO BE
COMPREHENSIVE, WHAT WOULD YOU
LIKE TO SEE HAPPENING SOON IN
THIS SPACE?
>>I WOULD LIKE TO SEE MEETINGS
LIKE THIS WHERE WE TALK OPENLY
ABOUT NAMs, ALSO THE GOOD NEWS
AND BAD NEWS.
AGAIN, PEOPLE PUBLISHING
NEGATIVE FINDINGS, TO UNDERSTAND
HOW SYSTEMS ARE OPERATING WE
NEED TO TALK ABOUT BOTH SIDES.
>>TERRIFIC.
ANNE?
>>I WOULD SAY THAT I'D LIKE TO
SEE MORE CONSENSUS DATABASES OF
CURATEED HIGHLY STRUCTURED DATA
MADE PUBLICLY AVAILABLE FOR MORE
ADVERSE EFFECTS, ADVERSE HEALTH
EFFECTS, SO THAT IT'S AVAILABLE
TO ALL POTENTIAL METHOD
DEVELOPERS.
>>SUPER.
JAMES?
>>I THINK IT WOULD BE HELPFUL
TO HAVE MORE RESOURCES AND MORE
EFFORTS IN CREATING TARGETED
VALIDATION DATA FOR A.I.
>>OKAY.
IVAN?
>>I'D LIKE THE NAM DEVELOPERS
TO REALLY THINK HARD AND LONG
ABOUT THEIR HAMMERS BEFORE THEY
BUILD THEM, TO UNDERSTAND WHERE
THE NAILS ARE, AND TO GIVE KUDOS
TO OUR COLLEAGUES AT THE FDA.
THEY HAVE PUBLISHED RECENTLY A
COUPLE PAPERS WHERE THEY ARE
VERY, VERY SPECIFIC ABOUT WHAT
PROBLEMS THEY HAVE AND WHAT
SOLUTIONS THEY ARE LOOKING FOR.
SO I THINK WE HAVE TO START FROM
THE PROBLEMS, AND DEFINE THEM,
AND THEN BUILD SOLUTIONS FOR
THEM RATHER THAN OFFER SOLUTIONS
AND SEE IF THERE ARE ANY
PROBLEMS.
>>GREAT.
JOHN?
SUPER BRIEFLY.
>>YES, BRIEFLY.
MORE VACATION TIME.
NO, I THINK I WOULD -- IT'S NOT
GOING TO HAPPEN OVER THE NEXT
YEAR OR TWO BUT I THINK IT WOULD
HAPPEN IN VALID BENCHMARKING,
TRUSTING THIS ANALYSIS, IF WE
HAD NAMs SYSTEMS AROUND
RELEVANT ANIMAL MODELS AND
DIFFERENT HUMAN INDICATIONS,
THAT WOULD ENABLE BACKWARDS AND
FORWARDS TRANSLATION, AND
UNDERSTAND WHAT THESE ASSAYS MAY
LOOK LIKE FOR LEAD SELECTION AND
THEN TRANSLATING INTO THE HUMAN,
IT'S DIFFICULT.
YOU HAVE TO TRUST THESE ANIMAL
MODELS.
>>THESE ARE TERRIFIC
RECOMMENDATIONS.
THANK YOU FOR THE SESSIONS.
AND WE'RE FINISHING AT 3:15
>>GOOD AFTERNOON, WELCOME BACK
TO OUR LAST SESSION.
OUR WORKING GROUP LEADER MEMBER,
WORKING GROUP MEMBER DR. TONY
BAINES, WILL MODERATE.
DR. BAINES, TAKE IT AWAY.
>>THANK YOU, HOWARD.
I WANT TO SAY GOOD AFTERNOON,
GOOD MORNING, GOOD NIGHT,
DEPENDING WHERE YOU ARE.
AGAIN, I'M TONY BAINES,
ASSOCIATE PROFESSOR AT NORTH
CAROLINA CENTRAL UNIVERSITY IN
DURHAM, NORTH CAROLINA.
I'M ALSO ADJUNCT ASSOCIATE
PROFESSOR IN PHARMACOLOGY, ALSO
TOXICOLOGY ENVIRONMENTAL
MEDICINE AT UNC-CHAPEL HILL,
VERY HAPPY TO BE HERE.
I WANT TO FIRST THANK THE NIH
FOR HOSTING THIS CONVERSATION.
IT'S A VERY IMPORTANT
CONVERSATION TALKING ABOUT
BIOMEDICAL RESEARCH WE'VE HEARD
THROUGHOUT THIS WHOLE DAY.
I'M HONORED TO BE ON THE
ADVISORY COMMITTEE FOR THE
DIRECTOR AS RELATES TO NAMs.
I'M ON A PANEL OF VERY SMART AND
INTELLIGENT AND PASSIONATE
FOLKS, SO I'M HONORED TO WORK
WITH EVERYBODY ON THE COMMITTEE.
I WANT TO THANK EVERYBODY HERE,
PHYSICALLY IN THE WILSON ROOM,
AS WELL AS THOSE OUT VIRTUALLY.
I APPRECIATE YOU HANGING OUT
WITH US, IF YOU'VE BEEN HERE ALL
DAY THANK YOU.
IF YOU'RE JUST JOINING US,
WELCOME, WELCOME.
WE WANT TO TRY TO HAVE A VERY
FRUITFUL AND ENGAGING
CONVERSATION ABOUT THIS VERY
IMPORTANT TOPIC CALLED EQUITABLY
DEPLOYING ROBUST AND RELIABLE
NAMs INTO PRACTICE.
SO WHEN I THINK ABOUT THAT
TITLE, I KIND OF BREAK IT UP
INTO KEY WORDS.
FIRST THING IS NAMs INTO
PRACTICE.
I THINK ABOUT APPLICATION.
AT THE END OF THE DAY, GREAT
CONVERSATIONS, GREAT PANELS,
DISCUSSION ON A LOT OF THE
CREATION AND DEVELOPMENT THEORY
BUT HOW DO WE PUT THIS IN
PRACTICE, LEAVE HERE AND MAKE
SURE THIS IS NOT JUST ANOTHER
SESSION THAT WE'VE HAD, ANOTHER
GREAT SESSION, BUT HOW CAN WE
MAKE SURE IT DOES PRACTICE WITH
NAMs, THE KEY WORDS.
ANOTHER SET OF KEY WORDS I THINK
ABOUT, ROBUST AND RELIABLE.
THAT MAKES ME THINK ABOUT
VALIDATION, HOW DO WE MAKE
MODELS, WITH ANY MODELS, I
REMEMBER BEING TRAINED AS A GRAD
STUDENT, THERE'S NO PERFECT
MODEL.
THERE'S BENEFITS AND LIMITATIONS
WITH EVERY MODEL.
HOW DO WE MAKE SURE THEY ARE
VALIDATED TO WHERE WE HAVE
CONFIDENCE USING THEM.
LASTLY I THINK ABOUT EQUITABLE.
EQUITABLEY USING THESE RELIABLE
MODELS, THINKING ABOUT
ACCESSIBILITY, AVAILABILITY,
USAGE FOR ALL AND TO ALL.
SO THOSE ARE THE KEY POINTS THAT
I THINK ABOUT FROM THAT TITLE.
SO I'M VERY HAPPY TO HAVE THIS
VERY DISTINGUISHED PANEL THAT WE
HAVE HERE, AS WELL AS VIRTUAL,
GLAD NICHOLAS COULD JOIN US
VIRTUAL.
I'M GOING TO BRIEFLY INTRODUCE
EVERYBODY, THEY ARE DO A BETTER
JOB INTRODUCEING THEMSELVES.
I'LL LET THEM INTRODUCE
THEMSELVES, YOU KNOW, IN MORE
DEPTH.
ALSO GIVE INITIAL THOUGHTS WHEN
THEY THINK ABOUT OUR TITLE THAT
WE'VE BEEN LABELED WITH IN TERMS
OF EQUITABLY DEPLOYING REBUST
AND RELIABLE NAMs INTO
PRACTICE.
THANKS TO OUR INTERPRETER FOR
BEING HER.
FIRST JESSE CARDER, USDA, U.S.
DEPARTMENT OF AGRICULTURE, AND
IN ANIMAL WELFARE AND
INFORMATION CENTER, SHE HAS MANY
YEARS OF EXPERIENCE AS RELATES
TO RELATES TO ANIMAL HANDLING,
BEHAVIOR, WELFARE, WE HAVE MEGAN
LA FOLLETTE, THREE Rs
COLLABORATE A ACTIVE, MAKING
SURE ANIMALS ARE CONSIDERING
WITH REDUCING, REPLACING,
REFINING.
MICHAEL MOORE IS A PROFESSOR AND
CHAIR AT TULANE UNIVERSITY,
DEPARTMENT OF BIOMEDICAL
ENGINEERING, HE ALSO IS I THINK
A SCIENTIST, CHIEF SCIENTIFIC
OFFICER OF A COMPANY, CRO CALLED
AXOSIM FOCUSED ON
NEURODISCOVERY, LOOK FORWARD TO
HEARING WHAT HE'S DOING.
WE HAVE MANU PLATT, DIRECTOR OF
BIOMEDICAL ENGINEERING.
BEFORE HERE HE WAS AT GEORGIA
TECH, WHERE I KNEW HIM,
DEPARTMENT OF BIOMEDICAL
ENGINEERING, HE WORKS ON HIV AND
SICKLE CELL ANEMIA, STROKE AND
CARDIOVASCULAR DISEASES.
HAPPY FOR HIM TO BE HERE, ALSO
HERE AT NIH AS ASSOCIATE
DIRECTOR FOR SCIENTIFIC
DIVERSITY, EQUITY, AND
INCLUSION.
LAST BUT NOT LEAST NICHOLAS
TATONETTI, WHO IS VIRTUAL, AND
HE'S AT COLUMBIA UNIVERSITY,
CHIEF OFFICER FOR CAMPUS DATA
SCIENCE AT CAMPUS CENTER AT
COLUMBIA, INVOLVED IN SYSTEMS
POLLING, DRUG SAFETY, DRUG
SURVEILLANCE, ET CETERA.
I'M HAPPY HE'S HERE, AS WELL.
AGAIN, I THANK ALL THE PANELISTS
FOR TAKING TIME OUT.
I KNOW EVERYBODY IS BUSY, TAKING
TIME OUT OF YOUR BUSY SCHEDULE
TO HAVE A CONVERSATION, I WANT
THIS TO BE A CONVERSATION
RELATEED TO OUR TOPIC.
HOW ABOUT WE GET STARTED.
HOW ABOUT WE START WITH MANU IN
TERMS OF A LITTLE BIT MORE
INTRODUCTION OF YOURSELF, MAKE
SURE FOLKS KNOW WHO YOU ARE AND
JUST INITIAL THOUGHTS, BRIEF
INITIAL THOUGHTS ABOUT OUR TOPIC
IN TERMS OF EQUITABLE ROBUST AND
RELIABLE NAMs PRACTICE, NAMs
INTO PRACTICE.
>>SOUNDS GOOD.
THANKS FOR HAVING ME.
THANKS TO THE WORKING GROUP FOR
HAVING US WITH THIS
CONVERSATION.
I LEARNED QUITE A BIT TODAY.
GREAT TO TUNE IN ALL DAY AND
THEN COMMENT AT THE END, SO MY
THOUGHTS CONTINUE TO GROW
THROUGHOUT THE DAY, I'M SURE AS
THE OTHER PANELISTS DID.
I DID MY UNDERGRADUATE AT
MOREHOUSE COLLEGE.
I THINK ABOUT EQUITY AND ACCESS
TO RESEARCH, RESEARCH PLATFORMS,
OVER THE COURSE OF MY CAREER AS
MENTIONED IN THE INTRODUCTION
OUR WORK FOCUSED ON RACIAL
HEALTH DISPARITIES, SICKLE CELL
IS A MAJOR FOCUS, PREDOMINANTLY
AFFECTS AFRICAN AMERICANS, I
USED TO WORK WITH HIV AND
CARDIOVASCULAR DISEASE WHICH
TOOK ME TO LOW-INCOME COUNTRIES,
WE DID A LOT OF WORK IN SOUTH
AFRICA, ETHIOPIA.
I COME TO BIOMEDICAL ENGINEERING
FROM THE BIOLOGY SIDE BUT
STARTED TO APPRECIATE WHAT
ENGINEERS CAN BRING, MAKING
THINGS SIMPLER, FASTER, CHEAPER
TO MOVE TECHNOLOGY, DIAGNOSTICS,
HEALTH CARE.
ONE OF THE BIG FINDINGS THAT
I'LL BRING UP ABOUT NAMs, WHEN
MY LAB BEGAN TO WORK IN SOUTH
AFRICA WE HAVE IDEAS AND
TECHNOLOGY THAT WORKED REALLY
WELL HERE IN THE UNITED STATES
AND CAMPUS AT GEORGIA TECH AND
WHEN WE WOULD GO OVERSEAS THE
SCIENCE WOULD WORK BUT OTHER
SMALL THINGS WOULD MAKE IT MORE
CHALLENGING TO IMPLEMENT OVER
THERE.
I WORK WITH MY COLLABORATORS WHO
WOULD TALK ABOUT DIFFICULTIES IN
A RURAL CLINIC OR SOMEWHERE
ELSE, YOU WANT TO IMPLEMENT
TECHNOLOGY OR MAKE IT AVAILABLE
TO MORE, IT BEGAN TO TRAIN MY
STUDENTS AND ME ON HOW WE NEED
TO THINK ABOUT THINGS, WORKING
IN SIMPLER FASTER WAYS, IN A
VARIETY OF CONDITIONS, WHAT IF
ELECTRICITY IS NOT ON ALL NIGHT,
WHAT IF FREEZERS ARE NOT
RELIABLE, AND MAKING SCIENCE
ACCESSIBLE TO ALL NOT JUST
WEALTHIER COUNTRIES.
THERE'S SOMETHING ABOUT
DEVELOPING UNDER THESE
ENVIRONMENTS BUT WE SHOULD BE
THINKING ON THE GROUND FLOOR
EARLIER ABOUT HOW TO TRANSLATE
THAT TO OTHER GROUPS AND OTHER
PEOPLE.
AS PART OF MY NEW JOB WITH THE
NIH CENTER, HOUSEED IN NIBIB,
OTHERS ARE DEVELOPING
TECHNOLOGIES THESE ARE SOME
THINGS WE ENCOURAGE PEOPLE TO
BEGIN TO THINK ABOUT AND LOOKING
FORWARD TO CONTINUING THOSE
CONVERSATIONS.
>>THANKS.
MICHAEL IS NEXT.
>>YEAH, THANKS.
AS TONY MENTIONED EARLIER, I'M A
PROFESSOR AND CHAIR IN
BIOMEDICAL ENGINEERING
DEPARTMENT, TULANE UNIVERSITY IN
NEW ORLEANS.
I JUMPED AT THE CHANCE TO COME
TO WASHINGTON, D.C. WHERE IT'S
ONLY 93 DEGREES TODAY.
[LAUGHTER]
JUST A BEAUTIFUL DAY OUTSIDE,
ALMOST FREE OF HUMIDITY COMING
FROM WHERE I'M COMING FROM.
AND SO I STARTED A COMPANY VERY
EARLY ACTUALLY IN THE
DEVELOPMENT OF THIS TECHNOLOGY
THAT WE SPUN OUT OF MY LAB WHICH
WAS PERIPHERAL NERVE
MICROPHYSIOLOGICAL SYSTEMS.
ONE REASON WE WERE ABLE TO
COMMERCIALIZE TECHNOLOGY WHEN IT
WAS YOUNG THERE WASN'T ANYTHING
ELSE OUT THERE FOR
PHARMACEUTICAL COMPANIES LOOKING
TO TEST.
MOSTLY THEY TEST ONCOLOGY DRUGS
ON OUR TISSUE.
AND PERIPHERAL NEUROPATHY IS A
VERY KNOWN SIDE EFFECT OF CANCER
DRUGS, CHEMOTHERAPEUTICS, WE GOT
EARLY ADOPTERS BEFORE IT WAS
COMMERCIALLY READY, IN A
COMMERCIAL SETTING BECAUSE THERE
WAS NOTHING ELSE THERE.
SOME LESSONS THAT I WAS FORCED
TO LEARN HAVING ONE FOOT IN
ACADEMIA AND ONE FOOT IN THE
COMMERCIAL SECTOR, ALSO SOMEBODY
MENTIONED EARLIER IN ONE OF THE
EARLIER PANELS HAVING THE
CONTEXT OF USE IN MIND DURING
THE DEVELOPMENT PROCESS, WE WERE
FORCED TO DO THAT BECAUSE WE
STARTED THIS COMPANY SO EARLY.
AND SO THESE KIND OF THINGS HAVE
GIVEN ME A PERSPECTIVE IN THE
TENSIONS THAT THERE ARE BETWEEN
LET'S SAY ACADEMIA AND
COMMERCIAL SECTOR, INCENTIVE
STRUCTURES ARE DIFFERENT,
PRIORITIES ARE DIFFERENT.
AND ALSO, YOU KNOW, ACADEMIA AND
COMMERCIAL SECTOR, BETWEEN WHAT
COMPANIES WANT VERSUS WHAT YOU
AS TECHNOLOGY DEVELOPMENT PERSON
WANTS TO ACHIEVE THERE'S A
TENSION BETWEEN THOSE THINGS.
THERE'S A TENSION BETWEEN SORT
OF REGULATORY FRAMEWORK OF
THINGS AND SCIENTIFIC FRAMEWORK,
SO LIVING BETWEEN THESE TENSIONS
IS I THINK SOMETHING THAT MORE
OF US NEED TO DO.
IT'S VERY TRICKY THOUGH.
THAT'S ONE OF THE THINGS WE'LL
BRING UP TODAY.
THERE'S A TENSION BETWEEN THE
BIOLOGICAL NECESSITYS AND
ENGINEERING DEVELOPMENT, AND SO
AGAIN JUST LIVING BETWEEN THESE
WORDS THAT OFTEN DON'T
COMMUNICATE HAS FORCED ME TO
LEARN HARD LESSONS, HOPEFULLY
SOME OF THOSE WE'LL TALK ABOUT
TODAY.
THANKS.
>>THANK, MICHAEL.
MEGAN, HOW ABOUT YOU GOING NEXT,
AND AFTER MEGAN WE'LL HAVE
NICHOLAS.
>>AWESOME.
THANK YOU FOR HAVING ME.
I'M EXECUTIVE DIRECTOR AT THE
THREE Rs COLLABORATIVE.
I COME FROM DENVER, COLORADO, SO
I DIDN'T REALLY COME HERE FOR
THE WEATHER.
BUT CERTAINLY IT'S BEEN REALLY
INSPIRING TO SEE THE SCIENTIFIC
EXPERTISE AND COLLABORATION AND
JUST ALL OF THE DIVERSE OPINIONS
HERE.
REALLY WHAT MY NON-PROFIT DOES
IS ABOUT ADVANCING BETTER
SCIENCE FOR BOTH PEOPLE AND
ANIMALS, THAT SCIENCE PIECE IS
REALLY AT THE FOREFRONT, AND
THAT'S OUR GOAL.
AND CERTAINLY NAMs ARE A
CRITICAL PART OF THE THREE Rs,
WE WANT TO WORK TO ACCELERATE
THEIR DEPLOYMENT INTO EVERYDAY
PRACTICE.
MY BACKGROUND IS THAT I HAVE A
Ph.D. IN RESEARCH ANIMAL
WELFARE AND BEHAVIOR, BUT I
ACTUALLY SPECIFICALLY FOCUS ON
THE IDEA OF IMPLEMENTATION,
PUTTING THE THREE Rs INTO
PRACTICE.
CAN WE FIND THREE Rs
TECHNIQUES THAT ARE
EVIDENCE-BASED, DO PEOPLE USE
THEM?
NOT ALWAYS.
HOW DO WE UNDERSTAND WHY THEY DO
OR DO NOT USE THEM AND THEN
ACCELERATE THE IMPLEMENTATION BY
DIRECTLY ADDRESSING THOSE
BARRIERS.
AND IT'S BEEN REALLY EXCITING
NOW WITH THE THREE Rs
COLLABORATIVE TO EXPAND MY WORK
AND MY Ph.D. TO ALL SORTS OF
PARTICULAR TOPICS AND WE'VE GOT
SEVEN PARTICULAR TOPICS AT THE
COLLABORATIVE, ONE OF THEM IS
FOCUSED ON MICROPHYSIOLOGIC
SYSTEMS.
WE LEAD AN INITIATIVE COMPOSED
OF COMMERCIAL TECHNOLOGY
PROVIDERS BECAUSE WE DO SEE IN
TERMS OF PUTTING NAMs INTO
PRACTICE THEY HAVE A LOT OF
EXPERTISE, THEY HAVE A LOT OF
MORE DEVELOPMENT OF THESE
SYSTEMS, AND WE'RE ABOUT TO
LAUNCH AN ARTIFICIAL
INTELLIGENCE INITIATIVE AS WELL,
SO THAT'S MY BACKGROUND.
AND THEN, YOU KNOW, THINKING
ABOUT, YOU KNOW, OUR PANEL
SESSION TODAY, PUTTING NAMs
INTO PRACTICE, WE REALLY SEE A
COUPLE DIFFERENT THINGS THAT ARE
NEEDED.
SO AS MANY OF THE OTHER SESSIONS
HAVE TALKED ABOUT IS THAT
INVESTMENT INTO THE INDEPENDENT
CHARACTERIZEATION AND
VALIDATION, AND I WILL JUST PUT
IN A PLUG ESPECIALLY FOR
COMMERCIALLY AVAILABLE SYSTEMS
BECAUSE IF WE THINK ABOUT THE
FASTEST WAYS TO GET THINGS INTO
PRACTICE NOT EVERYBODY GOING TO
BE AN EXPERT ON THESE.
IF WE CAN TRAIN PEOPLE TO BE
EXPERTS AND THEN INCREASE OUR
ACCESS TO THOSE EXPERTS, WE CAN
INCREASE NAMs IN PRACTICE.
AND THE SECOND THING THAT I'D
LIKE TO EMPHASIZE IS KIND OF THE
TYPE OF WORK WE DO AT THE
COLLABORATIVE WHERE WE'RE REALLY
THINKING ABOUT, YOU KNOW, LIKE
MY NON-PROFIT, OTHER SCIENTIFIC
SOCIETIES WHERE WE'RE SPANNING
ACROSS THE INDUSTRY, WE WORK IN
ACADEMIA, WE WORK WITH
PHARMACEUTICALS, WORK WITH
BIOTECHNOLOGIES, AND WE'RE
THINKING ABOUT SCIENCE-BASED,
EVIDENCE-BASED SCIENCE
COMMUNICATION AND DISSEMINATION.
AND THAT INVOLVES UNDERSTANDING
WHERE WE ARE AT THE STATUS QUO,
AND THEN WORKING ON REALLY
CAREFULLY CRAFTED MESSAGING
THAT'S LOOKING AT WHY PEOPLE
CHANGE.
I THINK I REALLY LIKED WHAT
DONNA SAID, DONNA MENDRICK SAID
EARLIER, SCIENTISTS ARE PEOPLE.
CHANGE IS HARD.
AND I SOMETIMES WORRY IN THIS
FIELD THAT IF ALL WE'RE DOING
WITH NAMs ARE IF OUR PRIMARY
FOCUS IS PUTTING DOWN ANIMAL
RESEARCH, SO THAT WE LIFT UP
NAMs, THAT'S -- WE'RE
ALIENATEING THE PEOPLE WHOSE
HEARTS AND MINDS WE'RE TRYING TO
CHANGE.
AND SO WHAT WE DO AT THE
COLLABORATIVE IS REALLY WORK TO
HAVE BALANCEED MESSAGING,
EVIDENCE-BASED MESSAGING THAT'S
CHAMPIONING EARLY ADOPTERS,
TALKING ABOUT SUCCESSS,
CHALLENGES, ET CETERA, THAT'S
LOOKING AT THE EVIDENCE BASE,
TALKING ABOUT -- THERE MIGHT BE
EVIDENCE FOR THIS, MIGHT NOT BE
EVIDENCE FOR THAT.
INCREASING CONFIDENCE BY
TRAINING AND REALLY HAVING THIS
INFORMATION IN A WAY THAT PEOPLE
CAN UNDERSTAND, BUT THAT IS
APPROACHABLE.
SO THAT PEOPLE DON'T IMMEDIATELY
THEIR COGNITIVE BIAS TURNS ON,
COGNITIVE DISSONANCE, AND THEY
FEEL ATTACKED.
IF WE WANT THESE TO BE
WIDESPREAD WE NEED TO BE CAREFUL
ABOUT COMMUNICATIONS AND OUR
MESSAGING.
>>THANK YOU.
NEXT, NICHOLAS?
>>YES, THANK YOU.
SO SORRY I CAN'T BE THERE TODAY.
SOUNDS LIKE IT'S BEEN A GREAT
DISCUSSION.
AND I'VE ACTUALLY RECENTLY MOVED
FROM COLUMBIA, FROM NEW YORK TO
LOS ANGELES, WHERE I'M NOW THE
ASSOCIATE PROFESSOR AND VICE
CHAIR OF COMPUTATIONAL
BIOMEDICAL HERE, AND IN L.A. THE
HURRICANE HAS PASSED, AND IT IS
ACTUALLY QUITE A BEAUTIFUL DAY.
SO, WITH THAT IN MIND, I'D LIKE
TO JUST GIVE YOU A LITTLE BIT OF
BACKGROUND ON ME, AND THEN HOW I
VIEW NAMs AND THEIR POTENTIAL.
MY EXPERTISE IS IN THE USE OF
OBSERVATIONAL REAL WORLD DATA
FOR DRUG SAFETY AND DRUG
TOXICITY STUDIES.
FIGURING OUT HOW TO LEVERAGE THE
POWER OF BILLIONS OF DATA POINTS
THAT WE COLLECT EVERY DAY AND
EVERY YEAR IN HOSPITALS ACROSS
THE COUNTRY TO ADDRESS ISSUES OF
UNEXPECTED ADVERSE DRUG
REACTIONS, DRUG-DRUG
INTERACTIONS, HOW THOSE ARE
DISTRIBUTEED LARGELY INEQUITABLY
ACROSS DIFFERENT DEMOGRAPHIC
POPULATIONS.
I THINK THESE DATA REPRESENT
HUGE POTENTIAL TO ADDRESS
INEQUITIES IN HEALTH CARE,
ESPECIALLY AS RELATED TO DRUG
EFFECTS, AND COULD HAVE REALLY
SIGNIFICANT EFFECTS AT REDUCING
RELYANCE ON ANIMAL SYSTEMS.
ONE OF THE THINGS WE PRACTICE IN
MY LAB IS WHAT WE CALL REVERSE
TRANSLATIONAL MEDICINE WHICH IS
WE USE PATIENT DATA, HUMAN DATA,
TO MAKE DISCOVERIES, TO GENERATE
HYPOTHESES BY TRAINING LARGE
SCALE DATA MINING AND ARTIFICIAL
INTELLIGENCE ALGORITHMS, AND
THEN WE VALIDATE THOSE IN VERY
SIMPLE MODEL SYSTEMS OFTEN IN
VITRO.
OR USING DIFFERENT TYPES OF
ORGANOIDS OR MORE ADVANCED
THINGS THAT PEOPLE HAVE BEEN
COMING OUT WITH.
WHAT THIS ALLOWS US TO DO IS TO
DISCOVER A PARTICULAR EFFECT OF
A DRUG IN POPULATION THAT
MATTERS AND TO DO IT IN
DIFFERENT SUBPOPULATIONS SO WE
KNOW WHAT THE DIFFERENCE IS.
WE KNOW THEY ARE CLINICALLY
SIGNIFICANT BECAUSE WE
DISCOVERED THEM IN HUMANS.
AND THEN WE TACK ON A SIMPLE
EXPERIMENT AND AT THE END TO
PROVE CAUSEALITY, THE ONE THING
THAT THESE OBSERVATIONAL STUDIES
REALLY CAN'T ACHIEVE IS
ESTABLISHING CAUSEALITY BUT WITH
SIMPLE PROSPECTIVE EXPERIMENT
YOU CAN.
THIS REVERSE TRANSLATIONAL LOOP
IS ALTERNATIVE WAY TO GENERATE
EVIDENCE THAT WE CAN USE AND
MAKES EVERYTHING A LITTLE BIT
FASTER AND A LITTLE BIT EASIER.
OF COURSE THERE ARE SOME
LIMITATIONS TOO.
BUT THE ADVANTAGES ARE THAT WE
GET TO LOOK AT HOW DRUGS ARE
USED IN THE POPULATION THAT THEY
ARE ACTUALLY USED IN WITH ALL
THE MESSYNESS INVOLVED,
COMORBIDITYS, OTHER DRUGS THAT
PATIENTS ARE TAKING.
AND THE DIFFERENCE IS IN
DEMOGRAPHICS BETWEEN WAYS DRUGS
ARE USED AND HOW THEY MAY HAVE
BEEN STUDIED IN CLINICAL TRIALS.
I'M LOOKING FORWARD TO A VIBRANT
DISCUSSION TODAY.
>>THANK YOU, NICHOLAS.
YOU'RE LEARNING ABOUT NAMs AND
THE WEATHER AS WELL.
LAST BUT NOT LEAST, JESSIE.
>>HI, EVERYONE.
I WANT TO THANK THE WORKSHOP FOR
INVITEING ME TO COME SPEAK.
WE'LL HAD A PRODUCTIVE
CONVERSATION, AND I'M THANKFUL
TO PARTAKE.
I'M ONE OF MAYBE THE LOCAL,
LUCKY ONES, I'M LOCAL TO THE
AREA SO I'M USED TO THIS WHAT I
WAS CONSIDERING HOT AND HUMID
WEATHER BUT THANKFUL I'M NOT IN
NEW ORLEANS.
LIKE TONY SAID, I'M FROM THE
UNITED STATES DEPARTMENT OF
AGRICULTURE, SPECIFICALLY WITH
THE ANIMAL WELFARE INFORMATION
CENTER, AWIC, MIXED UP WITH THE
REGULATING ARM, ANIMAL PLANT
HEALTH INFECTION AS MUCH AS --
HEALTH INSPECTION SERVICE.
A LOT OF WORK IS TO PROVIDE
INFORMATION ON THE CARE AND USE
OF ANIMALS, SPECIFICALLY
RESEARCH ANIMALS.
AND SO IN MORE SPECIFICALLY, WE
PROVIDE INFORMATION ON WHAT THE
REGULATIONS ARE IN THE ANIMAL
WELFARE ACT AS PERTAIN TO
ANIMALS IN RESEARCH AND ALSO
HELP P.I.s OR SCIENTISTS FIND
THAT INFORMATION IN THE
LITERATURE BECAUSE INFORMATION
ON NAMs AND ANIMAL USE
ALTERNATIVES WHILE IT MIGHT SEEM
LIKE IT'S COMMON SENSE AND EASY
TO FIND, IT'S NOT ALWAYS THE
CASE BECAUSE IT'S NOT EXPLICITLY
WRITTEN ABOUT IN THE LITERATURE.
SO WHILE WE DON'T CONDUCT
RESEARCH ON NAMs OR ANY
SPECIFIC AREA OF SCIENCE, WE
KNOW A LOT A LITTLE BIT ABOUT A
LOT OF NAMs AND THOSE TYPES OF
TECHNOLOGIES AND MODELS BECAUSE
WE'RE CONSTANTLY LOOKING THROUGH
LITERATURE, PROVIDING
INFORMATION TO P. P.I.s
CONSIDERING USING NAMs AND
SYNTHESIZEING TO SEE IF IT'S THE
RIGHT FIT FOR THEIR RESEARCH.
I'M EXCITED TO BE ON THIS PANEL
IN PARTICULAR BECAUSE I THINK IT
GETS US PAST SOME OF THE MORE
GENERAL AND OBVIOUS
CONVERSATIONS ON BARRIERS TO
IMPLEMENTATION OF NAMs WHERE
WE GET THE APPLICATION PROCESS
LIKE TONY MENTIONED, SO HOW CAN
WE MAKE THEM EQUITABLE, HOW CAN
WE MAKE THEM AFFORD AND AND
ACCESSIBLE TO EVERYONE.
I WAS THINKING HOW CAN WE MAKE
THESE ACCESSIBLE TO BIG NAME
UNIVERSITIES WITH FUNDING,
HARVARD OR M.I.T., BUT MANU
MENTIONED A GOOD POINT, MAKE
THEM ACCESSIBLE EVEN OUTSIDE THE
COUNTRY, TO OTHER AREAS OR
COUNTRIES THAT DON'T HAVE
RESOURCES OR WEALTH THAT THE
UNITED STATES MIGHT HAVE.
I'M EXCITED TO TALK ABOUT SOME
OF THESE APPLICATIONS AND
BARRIERS, AND LOOKING FORWARD TO
PROLIFIC DISCUSSION.
THANKS.
>>I WANT TO THANK PANELISTS FOR
THE INTRODUCTION, INITIAL
THOUGHTS ABOUT OUR TOPIC.
I FORGOT TO MENTION MY TRAINING
IS IN PHARMACOLOGY AND
TOXICOLOGY, PHARMACOLOGYIST,
TOXICOLOGIST BY TRAINING, STUDY
PANCREATIC CANCER, MORE
SPECIFICALLY I'M INTERESTED IN
TRYING TO VALIDATE NOVEL DRUG
TARGETS, IN THE TARGETED THERAPY
SPACE OF PANCREATIC CANCER, I'VE
USED ANIMAL MODELS, IN VITRO
MODELS, SPHEROIDS, DEFINITELY
APPRECIATE THIS CONVERSATION
WE'RE HAVING.
AS YOU CAN SEE WE HAVE A
TALENTED PANEL SO I'M LOOKING
FORWARD TO HAVING FUN AS
MODERATOR, ASKING QUESTIONS.
WHOEVER WANTS TO GRAB IT, FEEL
FREE.
MEGAN SAID SOMETHING THAT MADE
ME CHANGE UP MY ORDER OF
QUESTIONING.
HOW ABOUT WE START WITH THIS
QUESTION FIRST.
WHICH I THINK IS A VERY VALID
QUESTION.
WHEN WE TALK ABOUT NAMs, WE
GET INTO THE SPACE WHERE THEY
ARE REPLACING ANIMAL RESEARCH,
CAN WE DO IT, PEOPLE GET
UNCOMFORTABLE.
I WOULD LOVE TO HEAR PEOPLE'S
THOUGHTS CAN WE BE COMFORTABLE
IN TERMS OF BIOMEDICAL RESEARCH
BEING BIOMEDICAL RESEARCHERS OR
IN THAT SPACE CAN WE BE
COMFORTABLE TALKING ABOUT ANIMAL
RESEARCH IN NAMs, CURIOUS TO
HEAR PEOPLE'S THOUGHTS, ARE WE
TRYING TO REPLACE, SUPPLEMENT,
COMPLEMENT?
PEOPLE'S FEELINGS ABOUT THAT AND
HOW CAN WE BE COMFORTABLE, BE
COMFORTABLE WITH BOTH OF THOSE
THINGS HAPPENING MAYBE AT ONCE.
>>I CAN START ON THIS TOPIC,
IT'S ONE MY ORGANIZATION DEALS
WITH A LOT.
WE SPAN THREE RS, REFINEMENT
SUCH AS REFINED MOUSE HANDLING
TO NPS AND ARTIFICIAL
INTELLIGENCE INITIATIVES SO
WE'RE CERTAINLY EXPERTS AT
BALANCING THAT USE.
WHAT WE -- WHAT OUR MESSAGING
IS, WHAT WE TALK ABOUT, IT'S
ABOUT THE BEST SCIENCE, BEST
MODEL FOR THE PARTICULAR
QUESTION, OR PARTICULAR CONTEXT
OF USE.
THERE MAY BE PARTICULAR CONTEXT
OF USE OR PARTICULAR QUESTIONS,
OR IF WE THINK ABOUT -- OFTEN I
TALK TO PEOPLE, YOU THINK ABOUT
THE ENTIRE SCIENTIFIC PIPELINE,
RIGHT NOW, YOU KNOW, IF WE'RE
THINKING ABOUT DRUG DEVELOPMENT,
YOU'RE GOING TO NEED TO USE AN
ANIMAL MODEL -- AN ANIMAL AT
SOME POINT.
CAN YOU USE A NAM EARLIER IN THE
DRUG DEVELOPMENT PIPELINE WHERE
YOU'RE LOOKING AT DISCOVERY,
LEAD OPTIMIZATION, RULING
CERTAIN COMPOUNDS OUT OR
DETERMINING THIS ONE IS BETTER
IN THIS PARTICULAR ANIMAL
SPECIES, THIS PARTICULAR ANIMAL
MODEL FOR A PARTICULAR REASON,
MAYBE YOU'RE USING IT THERE.
WE ALSO CERTAINLY HAVE
COMMERCIAL PROVIDERS THAT ARE
DOING PERSONALIZED MEDICINE THAT
ARE ACTUALLY TAKING TISSUES FROM
PATIENTS, DOING WORK NOT DONE IN
ANIMAL MODELS.
THERE'S ALSO PLACES IN THE
RESEARCH WHERE THERE'S NOT GOOD
ANIMAL MODELS, NOT A MODEL THAT
TRANSLATES.
WE MIGHT NOT BE REPLACING THE
ANIMALS BECAUSE THERE'S NOT
ANIMALS USED IN THAT SENSE BUT
IT DOESN'T MEAN IT'S NOT
WORTHWHILE.
NAMs ARE GREAT FOR THE
SCIENCE, GREAT WHEN THEY REPLACE
AT LEAST A PORTION OF THE
ANIMALS OR REDUCE THEIR NUMBERS
BY, YOU KNOW, ESTABLISHING THE
FIRST DOSE TO PUT INTO ANIMALS.
YOU CAN DO REDUCTION, REDUCE
THAT STUDY DESIGN, REFINEMENT BY
SEEING THESE ARE THE TOXICITIES
WE EXPECT.
COMPLEMENTARY, SUPPLEMENTAL.
I THINK FOR THE FASTEST
PROGRESS, TALKING ABOUT THEM IN
COMBINATION IS GOING TO GET MORE
PEOPLE TO USE THEM SOONER
BECAUSE, AGAIN, I THINK THAT
RELATIONSHIP BUILDING AND
BALANCED MESSAGEING IS REALLY
IMPORTANT.
>>PHYSIOLOGY WAS THE BEST
BIOLOGY CLASS I EVER TOOK.
THE WAY IT SHOWED ALL THE
DIFFERENCE SYSTEMS.
>>AND THE TOUGHEST.
PRETTY TOUGH.
>>AND ALSO HAD ENGINEERING
ELEMENTS TOO, QUITE FANTASTIC.
SEEING ALL THOSE ORGAN SYSTEMS
CONNECTED CHANGED THE WAY YOU
COULD THINK ABOUT HITTING ONE
TARGET OR NOT.
AND SO I THINK THAT'S WHY I
THINK THAT ANIMAL MODELS DO
SERVE A PLACE BECAUSE ALL OF
PHYSIOLOGY IS HARD TO
RECAPITULATE AND CAPTURE.
WHAT IS THE ACTUAL QUESTION ONE
IS ASKING, WHAT DATA DOES ONE
NEED TO GET FROM THAT?
I'VE BEEN A PART OF NSF
OFFICERS, I'VE SEEN IT FROM, YOU
KNOW, MIX A MATRIX, PUT CELLS
ON, TO COMPLICATEED DESIGN.
WHAT DO YOU NEED TO GET THE
ANSWER TO THE QUESTION?
ANIMAL MODELS CAN CHANGE, THE
BEST ANIMAL MODEL CAN CHANGE,
WE'VE BEEN ON STUDY SECTION,
WATCHED THAT WAVE MOVE, IF
YOU'VE BEEN WORKING ON THE OLD
ANIMAL MODEL WHAT HAPPENS TO THE
REST OF YOUR WORK WHEN YOU WANT
TO PUBLISH OR GET IT MOVED
FORWARD?
I WONDER HOW THAT'S GOING TO
LOOK WITH NAMs.
WHAT BECOMES THE STANDARD NAM
AND IS IT ACCESSIBLE TO EVERYONE
TO GET THE TYPE OF DATA THAT
WILL GET THEM THE GRANT,
PUBLICATION, OUTSIDE OF THE DATA
THEY NEED TO HELP PATIENTS AND
FOR THEIR COMPANY.
SO I THINK AS LONG AS WE TAKE A
MEASURED APPROACH AND PHASING
ONE OUT, SETTING UP STANDARDS
AND GUIDELINES IN THE FIELDS, WE
COULD THINK ABOUT IT IN THE
EQUITABLE SENSE AND NOT JUST
KNOCK PEOPLE OUT OF THE BOX.
>>APPRECIATE THAT.
ANY OTHER THOUGHTS?
COOL.
NICHOLAS, RAISE YOUR HAND.
WE SEE YOU, IF YOU WANT TO SPEAK
UP JUST RAISE YOUR HAND.
NEXT QUESTION, WE'VE HEARD THIS
IN OTHER PACKAGE SESSIONS ABOUT
THE DIFFERENT PLAYERS THAT ARE
AT THE TABLE WHEN IT COMES TO
NAMs, WE TALK ABOUT
BIOLOGISTS, ENGINEERS, COMPUTER
SCIENTISTS, MATHEMATICIANS, A
WHOLE BUNCH OF FOLKS.
WANTED TO ASK THOUGHTS FROM
PANELISTS, DO YOU SEE EXPERTISE
GAPS WITH NAMs?
DO YOU SEE NAMs BEING LIKE
SLOWED DOWN BECAUSE WE JUST
DON'T HAVE EVERYBODY AT THE
TABLE THAT NEEDS TO BE AT THE
TABLE TO PUSH THIS TECHNOLOGY
ALONG.
CURIOUS TO HEAR PEOPLE'S
THOUGHTS, ARE THERE EXPERTISE
GAPS, YOU KNOW, THAT'S NEEDED
AND WHAT DO YOU SUGGEST WE DO TO
HELP FILL THOSE GAPS?
>>YEAH, I CAN START ON THIS.
I DO STILL THINK THERE'S SOME
EXPERTISE GAPS IN TERMS OF WHEN
WE'RE DEVELOPING THESE
TECHNOLOGIES.
I THINK A LOT OF THE DEVELOPERS
ARE ENGINEERS AND THAT'S WHERE
THEIR BACKGROUND AND FOCUS IS,
AND MAYBE THOSE CONVERSATIONS
AREN'T HAD WITH THE P.I.s AND
BIOLOGISTS AND EXPERTS IN
SCIENTIFIC COMMUNITY.
THERE NEEDS TO BE BETTER WORKING
GROUPS AND CONVERSATIONS THERE.
AS WELL AS INVOLVING OTHER
STAKEHOLDERS, LIKE THE
REGULATORS AS WELL AS ACADEMIA
AND INDUSTRY, AND EVERYONE WHO
IS GOING TO HAVE A BUY-IN OR
SOME SAY OR APPLICATION IN USING
NAMs.
I THINK INDUSTRY OR THE
COMPANIES THAT ARE DEVELOPING
THESE NAMs CAN GET SO FOCUSED
AND DEVELOPING A PRODUCT, BUT
THEY SOMETIMES DON'T ALWAYS
REMEMBER THE INTENDED USE OF THE
METHOD OR TECHNOLOGY, WHEN THEY
ARE DEVELOPING, AND I THINK
THAT'S WHERE DONNA MENTIONED,
YOU KNOW, WE GET INTO
OVERPROMISING ON THESE NAMs.
THAT GETS US NOWHERE.
THE RELIABILITY AND TRUST ISN'T
THERE WHEN THE P.I.s SEE IT IN
THAT SCOPE.
I THINK THERE'S BARRIERS, WE
WANT TO MAKE SURE ALL PARTIES
ARE INVOLVED IN CONVERSATIONS
DEVELOPING THESE.
>>I'LL ADD.
THIS IS A VERY ACUTE -- IN MY
EXPERIENCE, I'VE TRIED MANY
TIMES TO REACH OUT TO
NEUROSCIENTISTS COLLABORATORS,
AND I THINK I COME TO THEM WITH
A LOT OF EXCITEMENT.
HEY, WE BUILT THIS MODEL,
WOULDN'T IT BE GREAT TO USE IT
FOR WHATEVER IT IS YOU'RE
WORKING ON, THEIR EYES GLOSS
OVER.
THEY JUST GO, YEAH, YEAH, THAT
WOULD PROBABLY BE GOOD AND
NOTHING HAPPENS.
I THINK THERE'S -- THIS IS A
REAL CHALLENGE, I THINK.
THERE'S-- THIS IS A TWO-WAY
STREET.
ON ONE HAND YOU HAVE SOME
BIOLOGISTS WHO SOMETIMES THEIR
WHOLE CAREER WAS BUILT ON A
CERTAIN MODEL, CERTAIN ANIMAL
MODEL, HOW ARE YOU GOING TO ASK
THEM TO TRY SOMETHING WITH STEM
CELLS, WIRES AND TUBES COMING
OUT OF IT, I DON'T KNOW WHERE
I'M GOING TO START.
THE REASON IT'S A TWO-WAY STREET
YOU HAVE BIOLOGISTS WHO LOOK AT
NAMs AS ENGINEERING PROJECTS,
YOU KNOW, DATA SCIENCE, THEY
DON'T KNOW ANYTHING, IT'S
ENGINEERING, THEY DON'T KNOW
ABOUT WIRES, CABLES, TUBES.
I THINK BIOLOGISTS ARE VERY
SMART PEOPLE.
I'M AN ENGINEER.
>>WE APPRECIATE THAT.
>>YEAH, YEAH.
I'M AN ENGINEER SO I CAN SAY
THIS, I'M BEING SERIOUS.
I DON'T THINK I'M SMART ENOUGH
TO BE A MOLECULAR BIOLOGIST.
WHAT ENGINEERS HAVE TO DEVELOP,
SOMETIMES ENGINEERS NEED TO BE
TAKEN DOWN A PEG WITH EGOS,
EVERYBODY KNOWS THAT.
ONE OF THE THINGS THAT I THINK
WE ENGINEERS NEED TO REALIZE, IF
YOU DON'T MAKE SOMETHING EASY TO
USE NOBODY WILL USE IT.
IF YOU DON'T MAKE SOMETHING
THAT'S SO EASY TO USE THAT IT'S
A KIT, YOU OPEN THE WRAPPER, PUT
IT ON THE PLATE, IT ROCKS, WHO
IS GOING TO USE IT AND LEARN HOW
TO, YOU KNOW, PLUG IN TUBES,
WIRES, THINGS LIKE THAT.
SO THAT'S SOMETHING THAT
ENGINEERS NEED TO THINK MORE
ABOUT.
THAT'S WHAT MAKES - STEVE JOBS,
WHEN APPLE WAS GETTING GOING,
WHAT MADEED SUCCESSFUL.
WHEN THE MacINTOSH CAME OUT,
BEFORE THAT YOU HAD TO TYPE
CODE, I'M A NERD BUT MOST KIDS
AND MOST GROWNUPS IN THE 1980s
DIDN'T LIKE TO TYPE CODE.
SO VERY FEW PEOPLE USED
COMPUTERS AT HOME AND THE
MacINTOSH COMES OUT, NOW WE
VULNERABILITY A -- NOW WE HAVE
COMPUTERS IN OUR POCKET.
ENGINEERS NEED TO THINK IN THOSE
TERMS.
IF YOU WANT PEOPLE TO USE THE
THING YOU'RE DEVELOPING, YOU'VE
GOT TO DO TWO THINGS, MAKE IT
USEFUL, PRACTICAL, EASY TO USE,
AND THE OTHER THING THAT IS
IMPORTANT, WE HAVE TO STOP
DEVELOPING AT SOME POINT.
THIS IS A REALLY DIFFICULT THING
FOR ENGINEERS TO DO BECAUSE
WE'RE ALWAYS LIKE TRYING TO --
YOU KNOW, I'M GUILTY.
I GET INTERESTED IN THE NEXT
TOOL.
I WANT TO BUILD THE NEXT HAMMER,
BEFORE THE FIRST HAMMER IS BEING
DEMONSTRATED AND IN USE BY
PEOPLE WHO WANT TO USE I'M
DEVELOPING THE NEXT HAMMER, OR
MAYBE THE WRENCH.
IT'S A CRITICAL CHALLENGE.
I DON'T KNOW HOW TO CHANGE THAT
CULTURE.
I GUESS I HAVE TWO IDEAS BUT
I'VE BEEN TALKING A LOT SO I'LL
TRY TO BE REAL QUICK.
ONE IDEA IS FUNDING AGENCIES CAN
GET CREATIVE WITH
INCENTIVIZEING, NIBIB PUT FORTH
GRANT MECHANISMS SPECIFICALLY TO
HAVE ENGINEERS WORK WITH
BIOLOGISTS, ENGINEERS AND
PHYSICISTS, MATHEMATICIANS
WORKING WITH BIOLOGISTS, MAYBE
MORE WOULD BE HELPFUL.
THERE'S A NEW ASSISTANT
PROFESSOR AT TULANE UNIVERSITY,
NOT IN MY DEPARTMENT, AT ANOTHER
DEPARTMENT, I WON'T MENTION HER
NAME, I DIDN'T TELL HER I WAS
TALKING ABOUT HER, SHE'S A
BIOLOGIST, CARD-CARRYING WORKS
WITH MOUSE KNOCKOUTS AND
EVERYTHING.
SHE DID A POSTDOC IN A
BIOMEDICAL ENGINEERING LAB TO
LEARN HOW TO USE
MICROPHYSIOLOGIC SYSTEMS TO
APPLY THOSE TO HER RESEARCH, TO
HER BASIC RESEARCH.
I THINK TRAINING MECHANISMS LIKE
THIS COULD BE POWERFUL, AND THIS
COULD BE DONE I DON'T KNOW IF
IT'S EARLY, GRADUATE LEVEL,
MAYBE POSTDOC IS MORE
APPROPRIATE BUT YOU COULD
SPECIFICALLY TARGET BIOLOGISTS
WHO WANT TO DO BASIC BIOLOGY AND
YOU COULD GIVE THEM TRAINING
OPPORTUNITIES TO GET TRAINING IN
MACHINE LEARNING, TO GET
TRAINING IN DATA SCIENCE,
TRAINING IN STATISTICS, TRAINING
IN MICROPHYSIOLOGIC SYSTEMS,
THAT WOULD BE ONE WAY FUNDING
AGENCIES CAN INCENTIVIZE THINGS
LIKE THAT.
>>NICHOLAS, DO YOU WANT TO
CHIME IN?
>>YEAH, THAT WAS SPOT ON.
IN OUR EXPERIENCE IN TRANSLATING
A.I. MODELS WE FACE A LOT OF THE
SAME ISSUES.
THEY ARE NOT WIRES STICKING OUT
BUT THEY ARE CONFUSING, AND THEY
REQUIRE A LOT OF EXPERTISE TO
USE.
AND IT REALLY -- I LOVE WHAT YOU
SAID, YOU HAVE TO MAKE IT EASY,
THAT'S 100 100% TRUE.
IT HAS TO PASS THE SNIFF TEST.
IF YOU HAND SOMEBODY A MODEL
SYSTEM, WHETHER A.I. OR IN A
DISH WITH WIRES, NEEDS TO
PRODUCE RESULTS THAT MAKE SENSE
AT FIRST PASS OR PEOPLE WILL
DISMISS THAT QUICKLY.
YOU HAVE TO MEET THEM WHERE THEY
ARE USING METHODS THEY LIKE TO
USE, SEEING THE RESULTS THEY
LIKE TO SEE, TO BUILD THAT TYPE
OF TRUST IN THESE NEW TYPE OF
MODELS.
>>YEAH, I THINK NOT ONLY MAKING
IT EASY FOR END USERS IS HUGE
BUT LIKE MICHAEL SAID GETTING
TRAINING, HOW CAN WE INCENTIVIZE
USE OF NAMs, AND ONE WORKING
GROUP THAT I'M ON ICCVAM,
CONSIDERATION OF ALTERNATIVE
METHODS, ONE OF OUR CHARGES IS
TO IDENTIFY INCENTIVES TO
UTILIZE NAMs, AND ONE OUTLET
WE'RE ENCOURAGING IS GETTING
LARGER FUNDING AGENCIES TO PUT
MONEY TOWARDS SPECIFICALLY NOT
ONLY DEVELOPING NAMs BUT
VALIDATEING THEM OR MONEY HAVING
SOMEONE TRAIN ON HOW TO USE
THESE.
LIKE MICHAEL SAID, IT'S THE CART
BEFORE THE HORSE WHERE WE KEEP
DEVELOPING BEFORE WE HAVE
CONFIDENCE AND A NAME THAT'S
DEVELOPER ESTABLISHED.
HOW CAN WE IDENTIFY OR PUT
TOGETHER TRAINING OPPORTUNITIES
FOR GRAD OPPORTUNITIES OR
POSTDOCS OR EVEN THE YOUNGER
P.I.s AND SCIENTISTS TO CHANGE
THAT MINDSET AND GET THEM
COMFORTABLE USING THESE
DIFFERENT NAMs.
SOME DOES FALL ON THE FUNDING
AGENCIES, BECAUSE MONEY TALKS.
>>SO KEEPING THAT IN THE
FOREFRONT ABOUT THE CHANGING OF
TRAINING, WHAT ARE YOUR THOUGHTS
ABOUT IMPACTING VARIOUS TRAINEES
AT THE UNDERGRAD LEVEL, GRAD
LEVEL, POSTDOC LEVEL, BECAUSE
YOU JUST THINK, I'M BEING REAL,
A LOT OF P.I.s, SCIENTISTS,
ENGINEERS, WHATEVER, AS THEY GET
MORE MATURE, THE CHANGE IS GOING
TO BECOME LESS IN TERMS OF THEM
BEING WILLING TO LEARN NEW
THINGS SOMETIMES.
THE IDEA I SOMETIMES THINK ABOUT
MIGHT NEED TO IMPACT UPCOMING
GENERATION, CURIOUS TO HEAR
PEOPLE'S THOUGHTS ABOUT HOW CAN
WE IMPLEMENT NAMs AND TRAINING
OF THE NEXT GENERATION OF
ENGINEERS, BIOLOGISTS, COMPUTER
SCIENTISTS, ALL THOSE FOLKS.
>>NOT TO PLUG MY FORMER
INSTITUTION BUT GEORGIA TECH
DEPARTMENT OF ENGINEERING, I WAS
IN THE SECOND CLASS, TO AGE
MYSELF, MENTION WAS TO TAKE LIFE
SCIENTIST STUDENTS, TRADITIONAL
ENGINEERS, IN CLASS TOGETHER,
MAKE THEM INTEGRATE, BROUGHT IN
ANTHROPOLOGY PERSON WHO WATCHS
PEOPLE TO STUDY US AND THE
CURRICULUM TO MAKE SURE THAT THE
MONKEYS FROM THIS SIDE WERE
HANGING OUT WITH THE MONKEYS
FROM THIS SIDE AND PLAYING NICE,
LEARNING IN CLASS TOGETHER.
SO THAT HAS LED TO SUCCESS.
I KNOW AT M.I.T. ENGINEERING
DEPARTMENT THEY TAKE THAT MODEL.
WE PUT LABELS ON SCIENTISTS,
BIOLOGY BIOLOGIST, ENGINEER.
YOU HAVE TO FOLLOW THAT, GET A
DEGREE.
BUT WHEN I CAME INTO BIOMEDICAL
ENGINEERING FROM BIOLOGY I
THOUGHT WE WERE ALL SCIENTISTS.
I WAS CORRECTED IN THE LAB.
MY SECOND YEAR.
SOMEONE SAID, OH, YOU'RE A
SCIENTIST, WELL, I'M AN
ENGINEER.
I REALIZE ENGINEERS MAKE MORE
MONEY, I'M AN ENGINEER TOO.
IF WE HAVE ARTIFICIAL BOXES A
BIOLOGIST CAN'T LEARN TO
ENGINEER NAMs, THEY THINK
THAT'S OVER THERE, I WILL NEVER
GO OVER THERE BUT IF AN ENGINEER
SAYS I CAN'T TALK TO THAT
BIOCHEMIST BECAUSE I'M NOT GOING
TO LEARN THE PATHWAYS THEY HAVE
LEARNED WHEN I THINK ALL OF
THESE INDIVIDUALS AS WE'VE SAID
HAD SMART PEOPLE AND SO WITH US
LEARNING THE RIGHT LANGUAGE TO
COMMUNICATE ACROSS OUR BARRIERS
THAT'S WHEN YOU CAN BRING THE
WHOLE TEAM TOGETHER.
I THINK IF ENGINEERS DEPARTMENTS
ARE WILLING TO TAKE IN LIFE
SCIENCES STUDENTS WHO GOT A
BACHELORS IN LIFE SCIENCE BUT
HAVE SOME QUANTITATIVE SKILLS
THEY CAN BE THERE AND BIOLOGY IS
MOVING QUANTITATIVE EVEN AS A
BIOLOGY CURRICULUM AND SO
PROGRAMS ARE HAVING THEM TAKE
COMPUTER SCIENCE AND HEAVYER
MATH.
THAT'S HOW WE START TO GET
EVERYBODY LEARNING WITH A FOCUS
BUT ABLE TO TRANSLATE FOR EACH
OTHER.
AND THEN THE BARRIERS ARE DOWN
FOR THE FUTURE GENERATION, JUST
AS OLD HANDS HAVE TO ADAPT.
>>DO YOU CALL YOURSELF A
SCIENTIST OR ENGINEER?
>>WHEN I'M ON A PLANE AND
SOMEONE ASKS, I'M A SCIENTIST.
AND THEN AS OTHER PEOPLE ASK ME,
I SAY BIOMEDICAL ENGINEER.
>>OKAY.
BACK AND FORTH, GOTCHA.
ANY OTHER THOUGHTS BEFORE I MOVE
ON?
>>I'LL ADD SINCE I'M IN
EDUCATION INSTITUTION, I TEACH
NEURAL MICROENGINEERING,
RESTRICTED TO A CERTAIN NUMBER
OF ENGINEERING GRADUATE
STUDENTS, OPEN TO A CERTAIN
NUMBER OF NEUROSCIENCE GRADUATE
STUDENTS.
I WAS SHOCKED THE FIRST TIMING I
OFFERED THAT COURSE THAT NO
NEUROSCIENTISTS SIGNED UP FOR
IT.
I WAS SCRATCHING MY HEAD.
AND I REALIZED THAT THE COURSE
DESCRIPTION WAS TALKING ABOUT
THIS ENGINEERING TOOLS, SO I
MADE TWO COURSE DESCRIPTIONS FOR
THE TWO LISTINGS, I HAD NO
PREREQUISITES.
I WAS ABLE TO GET STUDENTS TO
SIGN UP.
THEN IT WAS BEAUTIFUL ACTUALLY
BECAUSE WE HAVE BIOMEDICAL
ENGINEERS AND NEUROSCIENTISTS IN
THIS CLASS, THEY WOULD READ
PAPERS AND THEY WOULD GIVE
LECTURES TO EACH OTHER, THEN
THEY WOULD MIX THEM UP,
NEUROSCIENCE AND ENGINEERS, AND
WOULD TEACH EACH OTHER DIFFERENT
CONCEPTS RELATED TO THE FIELD.
AND IT WOULD BE AMAZING TO SEE
EYES OPEN, NEUROSCIENCE GRAD
STUDENTS I REMEMBER ONE TIME ONE
OF THE STUDENTS SAID, I GAVE
THIS ASSIGNMENT, THEY HAD TO
DESIGN SYSTEM TO ADDRESS
HYPOTHESIS, ONE NEUROSCIENTISTS
SAID, OH, YOU CAN BUILD
SOMETHING?
LIKE IT WAS JUST -- I THINK THAT
WAS REALLY EYE OPENING FOR THAT
STUDENT BECAUSE BEFORE THAT
ENGINEERING WAS TAKING MATH AND
STUFF.
ENGINEERING IS ABOUT DESIGN AND
ANALYSIS, AND MATH IS IN THE
BACKGROUND.
MOST OF US KNOW THIS IN
ENGINEERING BUT I DON'T EVER
COMMUNICATE IT THAT WAY.
I THINK THIS ACCESSIBILITY,
MAKING PEOPLE UNDERSTAND THAT
WORKING TOGETHER JUST REQUIRES
YOU TO BE ABLE TO COMMUNICATE, A
LOT REALLY IS JUST
COMMUNICATION.
>>ONE MORE THING OUT THERE TOO.
YOU SAID SOMETHING GREAT.
I THINK ABOUT NAMs,
MATHEMATICAL MODEL.
WHEN I STARTED GRADUATE SCHOOL
THAT'S WHAT I WAS MOST RESISTANT
TO APPRECIATEING THAT YOU COULD
APPLY MATH TO BIOLOGICAL SYSTEMS
THAT WE DID NOT HAVE ALL THE
ANSWERS TO.
I THINK THAT'S ANOTHER TRAINING
OPPORTUNITY FOR THE
UNDERGRADUATE BIOLOGIC
CURRICULUM TO GET TO UNDERSTAND
HOW PREDICTED MATH MODELING
DOESN'T TELL YOU ALL THE THE
ANSWERS BUT FOR ME, IT WILL SAVE
YOU SOME EXPERIMENTS, IT CAN
TELL YOU THE REALM OF WHAT MAY
BE POSSIBLE, WHAT'S NOT.
SOME MAJORS STOP AT CALC 1.
>>FOR TRAINING THE NEXT
GENERATION, TO SWITCH
METHODOLOGIES, ONE THING WE'RE
WORKING ON AT THREE Rs,
CREATING ACCESSIBLE VIRTUAL
SELF--BASED ONLINE TRAINING
MODULE THAT PUTS THREE Rs IN
PRACTICE, ONE FOR EACH R, IN
REPLACEMENT SECTION GOING INTO
THINGS LIKE MPS, IN SILICO, HIGH
LEVEL BUT AT LEAST GETTING, AND
OUR DREAM WOULD BE THAT
EVERYBODY WHO IS AN ANIMAL
RESEARCHER, WHO IS GOING INTO
THE LAB, WOULD IDEAL I --
IDEALLY HAVE TO TAKE THIS, NOT
TOO INTENSIVE BUT GETS SOME
LEVEL OF EXPOSURE, A WAY THEY
CAN UNDERSTAND TO START THINKING
ABOUT IT BECAUSE, AGAIN,
EVERYBODY HERE HAS AT LEAST A
PRETTY DECENT GRASP, ON THE
CONCEPTS, SO MANY PEOPLE HEARDED
WORD ORGAN ON A CHIP, HAVE NO
IDEA WHAT IT MEANS, DON'T KNOW
HOW TO APPLY, AREN'T AWARE OF
THE VALIDATION EFFORTS THAT
HAPPENED, SUCCESS STORIES.
HIGH LEVEL WOULD SPARK THINKING
MAYBE I CAN USE THIS TO
SUPPLEMENT, REPLACE.
IN THIS WORLD POST-COVID, THE
VIRTUAL EDUCATION HAVING
WELL-DESIGNED ONLINE TRAINING
MODULES CAN BE REALLY ACCESSIBLE
AND IF WE'RE THINKING ABOUT
EQUITY THAT IS GOING TO BE A
REAL HUGE WIN FOR NAMs, FOR
ALL SORTS OF DIFFERENT THINGS.
>>MEGAN AND I WILL TALKING
EARLIER, THERE'S NOT
CENTRALIZEED TRAININGS AVAILABLE
THAT FOCUS ON NAMs OR ANIMAL
USE ALTERNATIVES, FOR AN
UPCOMING SCIENTIST WHAT ARE
REQUIRED TRAININGS?
ALAF HAS ONE, WHAT ELSE DO THEY
HAVE TO TAKE TO GAIN EXPOSURE TO
THESE TOPICS?
I THINK IT'S VERY EASY FOR NEW
SCIENTISTS TO BECOME SILOED AT
THEIR OWN UNIVERSITY, RESOURCES
ONLY AVAILABLE THERE.
AND SO, AGAIN, LIKE STANFORD,
HARVARD, M.I.T. OTHER NAMES WITH
RESOURCES OR TECHNOLOGIES
AVAILABLE IS GREAT, BUT HOW CAN
WE SPREAD THE WORD AND GET
PEOPLE INTERESTED FROM THE EARLY
STAGES AND MORE EQUALLY.
I THINK HONEING IN ON FORMALIZED
TRAININGS WOULD BE A GOOD INTRO.
>>ANOTHER QUESTION, SO IN TERMS
OF NAMs AS IT RELATES TO, YOU
KNOW, CAN WE USE THIS, IS THERE
ANYBODY ON THE PANEL THAT CAN
TALK SPECIFICALLY ABOUT EXAMPLES
OF NAMs THAT HAVE BEEN
VALIDATED?
WE HEARD EARLIER TODAY ABOUT
FROM NICOLE ABOUT HOW SKIN
SENSITIVITY ASSAY SEEMED TO BE
GREAT, GOTTEN FDA APPROVAL FOR
THAT SPACE IN TERMS OF SKIN
ALLERGIES AND STUFF.
HELPING HOPEFULLY TO DETERMINE
TOXICITY.
ARE THERE ANY OTHER EXAMPLES
THAT WE CAN GIVE THE VIRTUAL
AUDIENCE OF NAMs VALIDATED OR
CLOSE TO VALIDATION THAT YOU
KNEW HAVE BEEN WORKING, IF
ANYBODY CAN TALK ABOUT THAT REAL
QUICK, THAT WOULD BE GREAT, JUST
TO SHARE SOME OF THAT.
WE SAID SKIN EARLIER.
ANY OTHER EXAMPLES OR CURRENTLY
DOING?
YOU MENTIONED NERVE ON A CHIP,
MICHAEL.
ANY THOUGHTS ABOUT THAT?
>>YEAH, IN VITRO SECTOR QUITE A
BIT OF SUCCESS WITH LIVER
MODELS, KIDNEY MODELS, SOME
FIRST ONES.
AND WHEN I SAY SUCCESS I THINK
WHAT I MEAN IS MULTIPLE CELL
TYPES, CELLS FROM MULTIPLE
DONORS SHOWING SOME BIOLOGICAL
VARIABILITY WHICH YOU EXPECT BUT
ALSO SHOWING THE SAME KIND OF
ESPECIALLY IN THE TOXICITY
FIELD, WHERE WE FIRST STARTED
DOING ALL THIS, SHOWING
TOXICITIES THAT YOU WOULD
EXPECT.
AT THIS POINT HUNDREDS OF DRUGS
HAVE BEEN PUT THROUGH THOSE
MODELS IN ORDER TO VALIDATE
THEM.
SEEM MORE MATURE MODELS LIKE
LIVER.
HUNDREDS OF DRUGS HAVE BEEN
TESTED, AND WE'RE STARTING TO
SEE THE DIFFERENCES WHEN YOU
POOL CELLS FROM DIFFERENT
DONORS, VERSUS WHEN YOU KEEP THE
CELLS SEPARATE AND YOU TREAT
THEM LIKE THEY ARE DIFFERENT
PEOPLE, YOU CAN SEE THE
VARIABILITY.
I THINK THE NERVOUS SYSTEMS HAS
A LONG WAY TO GO FRANKLY BEFORE
WE'RE AT A POINT LIKE THAT.
THAT'S ONE OF THE DIFFICULT
CHALLENGES IS TO BE HONEST JUST
HAVING ACCESS TO HIGH QUALITY
CELLS.
I MEAN IN THE IN VITRO SECTOR,
LET'S BE HONEST, WE CAN BUILD
WHATEVER YOU WANT TO BUILD, BUT
CELLS DO THE WORK.
SO IF YOU DON'T HAVE A HIGH
QUALITY CELL SOURCE YOU WON'T GO
ANYWHERE.
IN THE NERVOUS SYSTEM THERE'S
BEEN A LOT OF WORK DONE IN THE
BRAIN BUT PEOPLE AND COMPANIES,
IN THE PERIPHERAL NERVE WHERE I
SPEND MY TIME THERE'S BEEN VERY
LITTLE DONE, SO THERE'S
LITERALLY LIKE ONE -- I WORK
WITH SENSORY NEURONS, THERE'S
BEEN ONE DONOR THAT CAME, THAT'S
BEEN REALLY, REALLY WELL
CHARACTERIZED, TWO OR THREE
CELLS LINES, BUT THAT'S IT.
TWO OR THREE CELL LINES REALLY
WELL VALIDATED, REALLY WELL
CHARACTERIZED.
AND SO SOMEBODY MENTIONED
EARLIER IMAGINE DOING A CLINICAL
TRIAL WITH THREE PEOPLE.
AND SO THAT'S AN ENORMOUS
CHALLENGE.
LIKE I SAID IN THE CELL CULTURE
FIELD THERE'S BEEN A LOT MORE
ADVANCE IN OTHER AREAS.
YOU MENTIONED SKIN EARLIER.
LIVER AND KIDNEY IN PARTICULAR.
FOR THE IN VITRO WORLD WE HAVE A
LONG WAY TO GO BEFORE THIS --
THERE'S ENOUGH CELL TYPES, IT'S
NOT ONLY CELL TYPES, THAT'S VERY
IMPORTANT TOO BUT YOU HAVE TO
HAVE ENOUGH DONORS, LIKE CELL
LINES THAT HAVE BEEN TAKEN FROM
DIFFERENT DONORS, IF THEY ARE
PRIMARILY CELLS, THAT'S GOING TO
BE A SIGNIFICANT CHALLENGE AND I
THINK GETTING BACK TO THE
REPRODUCIBILITY, THE
RELIABILITY, HAVING PEOPLE BE
ABLE TO TRUST THESE MODEL
SYSTEMS, WE'RE GOING TO HAVE TO
DEMONSTRATE VALIDATION IS VERY
IMPORTANT.
IT'S HARD TO GET R01s TO
VALIDATE SOMETHING THAT'S
ALREADY BEEN DEVELOPED.
AND ONE OF THE REASONS FOR THAT
IS REVIEWERS HAVE TO -- I'VE
REVIEWED MANY GRANTS.
WE HAVE TO REVIEW INNOVATION.
IF SOMEBODY COMES ALONG, WELL,
WE'VE DEVELOPED THIS
MICROPHYSIOLOGIC SYSTEMS,
PUBLISHED SEVEN OR EIGHT PAPERS,
NOW WE NEED TO VALIDATE IT,
THAT'S NOT INNOVATIVE.
AS A REVIEWER YOU GIVE THAT A
BAD SCORE BECAUSE IT'S NOT
INNOVATIVE.
THAT'S REALLY TOUGH BECAUSE
VALIDATION IS EXTREMELY
IMPORTANT IN ORDER FOR THESE TO
BECOME USEFUL.
THAT'S ONE OF THOSE TENSIONS
BETWEEN ACADEMIA AND COMMERCIAL
SECTOR WHERE THE INCENTIVE
STRUCTURES AND PRIORITIES ARE
EXTREMELY DIFFERENT AND THESE
ARE THINGS THAT WE HAVE TO
ADDRESS.
>>SO -- GO FOR IT.
>>SO, I DON'T HAVE A TON OF
EXPERIENCE WITH MODELS AVAILABLE
NOW ON THE ENGINEERING SIDE BUT
WANT TO TALK ABOUT A.I.-BASED
MODELS THAT COULD EXIST.
MEGAN, I'D LOVE TO HEAR YOUR
THOUGHTS.
THERE'S POTENTIAL FOR A.I.
MODELS TO EVENTUALLY STAND IN AS
NAMs AS WELL.
NOW, THE DISTANCE BETWEEN WHERE
WE ARE NOW AND WHERE THEY WILL
BE, DEFINITELY NOT AVAILABLE
NOW, IT WILL BE A WHILE, BUT YOU
CAN IMAGINE AN A.I. SYSTEMS
COULD HAVE COMPLEXITY, COULD
HAVE BEHAVIORS, AND COULD
REPRESENT THE DIVERSITY THAT WAS
REQUIRED TO BE A GOOD NAM, EVEN
THE REPRODUCIBILITY AND RIGOR.
NOW, GETTING THERE IS GOING TO
BE A BIG CHALLENGE, GOING TO BE
ABOUT GETTING CLEVER ABOUT HOW
TO USE DATA, HAVING THE RIGHT
DATASETS AVAILABLE TO TRAIN
THOSE A.I. ALGORITHMS ON, SO
SUCCESSS THAT WE'VE SEEN FROM
TRANSFORMER MODELS AND LARGE
LANGUAGE MODELS IS THAT WE NEED
TO GIVE COMPLEXITY, BUILD
GENERAL KNOWLEDGE A.I., WHILE WE
GIGED A TRIAL OF THREE PEOPLE IS
RIDICULOUS IN THE FUTURE THAT
MIGHT NOT BE.
IT USED TO BE RIDICULOUS TO
TRAIN MACHINE LEARNING WITH A
FEW EXAMPLES AND NOW ROUTINE.
IT'S AN EXCITING OPPORTUNITY TO
THINK ABOUT WAYS WE COULD REDUCE
OR REPLACE A LOT OF POTENTIAL
ANIMAL MODELS.
>>I'M ACTUALLY GOING TO TAKE
THE QUESTION AND MODIFY IT A
LITTLE BIT.
YOU ASKED ABOUT EXAMPLES OF
NAMs THAT ARE VALIDATED.
ONE THING THAT I AND WE AT THE
THREE Rs COLLABORATIVE FOCUS
ON IS NOT GETTING OVERLY FOCUSED
ON THIS VALIDATION OR
QUALIFICATION PIECE.
CERTAINLY IF WE WANT TO HAVE
REALLY WIDESPREAD USE ESPECIALLY
IN THE SAFETY SPACE, THAT'S
REALLY IMPORTANT BUT THERE'S A
LOT OF WAYS TO USE NAMs RIGHT
NOW WHERE NAMs ARE USED
PHARMACEUTICAL COMPANIES AND
OTHERS TO MAKE DECISIONS HELPING
REPLACE ANIMALS EVEN THOUGH THE
SYSTEM IS NOT QUALIFIED PER SE,
AND FDA IS ACCEPTING THIS DATA
NOW, THEY HAD IN THE PAST,
BEFORE THE FDA MODERNIZATION
ACT, WE KNOW THEY HAVE USED IT
TO EXPAND LABEL EXPANSION FOR
EFFICACY, WE KNOW MPS DATA IS
BEING INCLUDED IN IND
SUBMISSIONS, SO THIS IS EXAMPLES
OF NAMs, YEAH, WHETHER LIVER,
WHETHER, YOU KNOW, CYSTIC
FIBROSIS, SEVERAL EXAMPLES OF
NAMs BEING USED.
YOU KNOW, WE HAVE TO HAVE THAT
CONFIDENCE IN THEM AND USE THEM
FOR DECISION MAKING.
SO THAT'S MY FLIP ON THE
QUESTION, IS THAT YOU DON'T HAVE
TO VALIDATE NECESSARILY.
YOU DON'T HAVE TO QUALIFY.
SOMETIMES, YOU KNOW, WE'RE
PUSHING FOR MORE DEVELOPMENT,
OUR MODELS ARE INCREASING,
GETTING MORE COMPLEX, SO BY THE
TIME WE QUALIFY THIS MODEL, IS
THE MODEL NOW HERE AND SO THEN
ALL THAT TIME WE SPENT ON THE
QUALIFICATION REALLY THIS IS A
BETTER MODEL, AND SO WE NEED
THAT FLEXIBILITY, CERTAINLY NEED
STANDARDIZATION, THAT
VALIDATION, IN SAFETY SPACE AND
TOXICOLOGY SPACE IS IMPORTANT,
ESPECIALLY FOR EFFICACY, THERE'S
MORE FLEXIBILITY THERE, THE
BIOLOGICS.
WE'VE HAD SOME OF OUR PHARMA
PARTNERS TODAY TALK ABOUT THEIR
WAYS THEY ARE USING NAMs RIGHT
NOW.
I THINK THERE'S WAYS TO USE THEM
QUITE WELL.
BUT THERE DOES OF COURSE NEED TO
BE EXPANSION, NEED TO BE
VALIDATION, CHARACTERIZEATION,
THOSE ARE IMPORTANT.
BUT DON'T LET THE IMPORTANCE OF
THAT MAKE YOU LOSE SIGHT OF THE
WAYS YOU CAN SUCCESSFULLY USE
THEM NOW.
>>YOU MAKE THE CASE THAT MORE
OF A GRAY AREA.
>>YEAH, WELL --
>>NOW IT'S BLACK AND WHITE.
>>YES, AND THAT I THINK USING
THE NAMs IN THIS EARLIER DRUG
DISCOVERY LEAD OPTIMIZATION
PIECE BUILDS CONFIDENCE TO MOVE
TOWARDS VALIDATION AND
CHARACTERIZEATION SO USING IT
HERE IS GREAT.
WE CAN REPLACE A LOT OF ANIMALS
IN DRUG DISCOVERY AND BASIC
RESEARCH AND NOT USE ASSAYS
FORMERLY QUALIFIED OR VALIDATED,
WE DON'T NEED THAT FOR THE
POERPGS -- PORTION OF THE
BIOMEDICAL FIELD.
DON'T OVERLOOK THE IMPORTANCE OF
NAMs IN THESE FIELDS
>>THE PIECE I STILL THINK OF
THE PROMISE OF NAMs,
PERSONALIZED MEDICINE,
N-of-1, WHICH, YOU KNOW, I
THINK THAT RECREATING ARM, ONE
OF THE THINGS I STUDY, SICKLE
CELL DISEASE, BONE MARROW
TRANSPLANTS WILL BE THE
FUNCTIONAL CURE, WHETHER GENOME
EDITED OR NOT, WHICH WILL HAVE
GvHD, TRANSPLANT DOCTORS DO
THE BEST WITH MATCHING BUT IS
THERE A NAM THAT WOULD TAKE
CELLS AND GIVE YOU THAT ANSWER
FASTER BEFORE YOU ACTUALLY PUT
THAT INTO THE PATIENT.
I THINK THERE'S SEVERAL OTHER
WAYS THAT THE N-of-1, BECAUSE
IF YOU DO THIS FOR A LARGE NONE
OF POPULATIONS, THAT'S GREAT,
BUT FIT DOESN'T WORK FOR ME,
DON'T CARE WHO ELSE IT WORKS
FOR.
THERE'S A LOT OF POTENTIAL THAT
MAY NOT BE AGAIN FULLY VALIDATED
SYSTEM BUT RECREATING SPECIFIC
QUESTIONS WE CAN TAKE PATIENT
CELLS AND APPLY AND GET ANSWER
ANSWER, THAT'S A WIN.
>>WE HAVE A COMMERCIAL MEMBER
ON OUR INITIATIVE THAT IS DOING
THAT SUCCESSFULLY RIGHT NOW,
THAT IS TAKING TUMOR CELLS FROM
PATIENTS, TESTING DIFFERENT DRUG
MODALITYS ON THEM, DETERMINING
WHICH CANCER DRUG IS BEST FOR
THAT PATIENT, AND EXTENDING
THEIR SURVIVAL TIME BY LIKE
SEVEN MONTHS, BY A LONG TIME
THAT MATTERS TO PEOPLE.
AND SO, YOU KNOW, THAT IS
CERTAINLY A SUCCESS FOR THOSE
PEOPLE, FOR THOSE INDIVIDUALS,
IF WE'RE THINKING ABOUT EQUITY,
MAYBE THAT I DON'T KNOW HOW MANY
PEOPLE CAN AFFORD TO HAVE THAT
PRECISION MEDICINE RIGHT NOW BUT
MAYBE THERE'S A WAY TO EXPAND
THAT.
AND I CERTAINLY THINK THAT THAT,
YEAH, THE N-of-1, THERE'S
SUCCESS OF THAT RIGHT NOW BEING
USED IN THE CLINIC.
>>OKAY, OKAY.
ACTUALLY KIND OF JUST REAL QUICK
QUESTION THAT GOES WITH WHAT WE
WERE TALKING ABOUT, DO YOU
CONSIDER 3D CELL CULTURE TO BE
THE GOLD STANDARD FOR
ALTERNATIVES TO ANIMAL MODELS AT
THIS TIME?
DO YOU CONSIDER 3D CELL CULTURE
TO BE THE GOLD STANDARD FOR
ANIMAL MODELS AT THIS TIME,
CURIOUS YOUR THOUGHTS ON THAT.
>>I'LL SAY IT RIGHT NOW.
I DON'T BUILD MICROPHYSIOLOGIC
SYSTEMS, I'VE WORKED WITH
PEOPLE HAVE THAT.
THERE'S BEEN GREAT TISSUE
ENGINEERS MODELS THAT ALLOW
PATIENT DERIVED CELLS TO BE USED
WITH CERTAIN CELL LINES.
>>ORGANOIDS AND STUFF.
>>RIGHT.
IF IT'S ALL BEEN
PRE-CHARACTERIZED, IF WE TALK
ABOUT RIGOR AND REPRODUCIBILITY
DESPITE PATIENT TO PATIENT
VARIABILITY THEY STILL DO SOME
NICE THINGS.
I DON'T KNOW IF THOSE ARE USED
TO MAKE CLINICAL DECISIONS BUT
USED TO HELP IDENTIFY TARGETS
AND SIGNALING PATHWAYS TO
DISRUPT.
I'M STILL A FAN OF THOSE,
ALTHOUGH I HAVE MY ANIMAL MODELS
AND MY OTHER THINGS BUT I THINK
THEY WILL STILL TELL ME QUITE A
LOT OF INFORMATION.
YOU CAN VISUALIZE, SEE IT, WATCH
THEM MOVE, A LOT YOU CAN LEARN,
SKIN OF THE ANIMAL, DEEP INTO --
YOU CAN'T QUITE GET TO.
>>OKAY, COOL.
THERE'S BEEN A BIG PUSH RECENTLY
BY NIH TO MAKE SURE THAT FOR NOW
CLINICAL TRIALS ARE MORE DIVERSE
THAN THEY USED TO BE, AND ALSO
WHEN IT COMES TO CELL LINES
MAJORITY OF CELL LINES FROM YOUR
APPEARANCE AND NOT MORE DIVERSE,
SO THOSE MANDATES TO MAKE THINGS
BETTER HAVE COME OUT RECENTLY.
WHAT CAN WE DO TO MAKE SURE WE
DON'T HAVE THIS CONVERSATION
YEARS LATER WHERE A MANDATE HAS
TO MAKE SURE NAMs ARE MORE
ETHNICALLY DIVERSE, WHAT HAS TO
HAPPEN TO MAKE SURE WE DON'T
HAVE THE SAME AROUND-THE-CIRCLE
CONVERSATION AGAIN, OH,
HOMOGENOUS, YOU KNOW, WE GOT TO
MAKE CHANGES.
>>I DON'T MEAN TO TALK TOO MUCH
BUT ONE THING THAT CAME UP
RECENTLY WAS COVID, YOU KEPT
SEEING ON THE NEWS, CAN'T FIND
PEOPLE TO PARTICIPATE IN
CLINICAL TRIALS.
I WAS CONVINCING MY FAMILY TO
SIGN UP BUT NO ONE CONTACTED
THEM.
I HAD THE TARGET AUDIENCE, I WAS
NOT CONTACTED EITHER.
I'VE BEEN IN OTHER CONVERSATIONS
WITH GEORGIA CANCER COALITION,
THERE WERE A LARGE NUMBER OF
PATIENTS, BLACK PATIENTS,
WILLING TO PARENTS PATE --
PARTICIPATE BUT CLINICIANS WERE
NOT ASKING THEM.
I WORK WITH SICKLE CELL, MOSTLY
BLACK, ALL HAVE BEEN IN CLINICAL
TRIALS, THAT'S THE TARGET
POPULATION.
OTHER GROUPS STARTED TO STATE
THIS.
CLINICAL TRAINING HAS TO BE
ABOUT ASKING ALL YOUR PATIENTS,
NOT BEING AFRAID, BARRIERS TO
CONVERSATIONS WITH PATIENTS FROM
UNDERSERVED GROUPS.
SOME ARE SCARED, THAT MAY BE A
MYTH BUT IF THE DOCTOR EXPLAINS
THE RISK, SEEMS LIKE THE NEWEST
BEST GREATEST THING IF EXPLAINED
THAT WAY, A LOT OF PEOPLE,
FAMILY MEMBERS WOULD TRY THINGS
BUT ARE NOT OFFERED.
THE CONVERSATION HAS TO GET DOWN
TO PATIENT, CLINIC, OFFICE, ARE
YOU HAVING THAT CONVERSATION TO
INTRODUCE THEM TO THE TRIAL.
>>I'LL SPEAK BRIEFLY TO THIS.
I THINK THERE IS A REAL
OPPORTUNITY HERE TO LEARN FROM
SOME OF THE SHORTCOMINGS WITH
ANIMAL MODELS AND CLINICAL
TRIALS, WITH OTHER FIELDS, TRY
TO BUILD IN SOME EQUITY AND SOME
OF THESE BEST PRACTICES IN FROM
THE GET-GO, WHETHER IT'S
REPORTING STANDARDS, WHETHER
IT'S THIS BIOLOGICALLY RELEVANT
VARIABILITY, I DO THINK LIKE
WHAT MICHAEL SAID, CELL
SOURCEING IS AN ISSUE.
I THINK IT'S AN ISSUE WITHOUT
THE EQUITY PIECE IN THERE.
SO I, TO BE HONEST, I DON'T KNOW
WHAT THE SOLUTION IS TO THAT BUT
HAVING SOME INVESTMENT ON THAT
CELL SOURCEING, THAT TAKES
EQUITY, THAT TAKES DIVERSITY OF
THE HUMAN POPULATION, INTO
ACCOUNT, AND ALSO I THINK THE
OTHER THING TO ADDRESS IS A LOT
OF US SCIENTISTS, I'M NOT AN
ENGINEER, ALTHOUGH MAYBE I
SHOULD HAVE PAID ATTENTION TO
THAT PAYMENT STRUCTURE IN GRAD
SCHOOL.
[LAUGHTER]
BUT I THINK SOME OF US IN
SCIENCE, YOU KNOW, YOU'RE
DRILLED IN PRETTY EARLY THAT
VARIABILITY IS BAD, THAT YOU'RE
TRYING TO MINIMIZE VARIABILITY,
AS MUCH AS POSSIBLE, SIGNAL TO
NOISE RATIO, THESE ARE IMPORTANT
CONCEPTS BUT I THINK WE NEED TO
START EARLY IN OUR TRAINING TO
THINK ABOUT THAT VARIABILITY
BEING PURPOSEFUL AND SOME
VARIABILITY IS TRUE AND WHERE --
CAN WE SOMEHOW GET THAT ENTIRE
TRAINING MODULE EARLIER FOR ALL
RESEARCHERS, ANIMAL RESEARCHERS
INCLUDED BASS THERE'S ISSUES
WITH NOT HAVING PURPOSEFUL
VARIABILITY, ALSO FOR IN VITRO,
ARTIFICIAL INTELLIGENCE, I'M
STILL LEARNING ABOUT THAT FIELD,
SO MAYBE NICHOLAS CAN TELL US
ABOUT THAT.
>>I MEAN, I CAN JUST AGREE WITH
THESE COMMENTS, THEY ARE
FANTASTIC.
I THINK THE IMPORTANT THING IS
BUILDING IN THESE -- MEASUREING
INEQUITIES WHEN WE CAN.
SO TO THE EXTENT THAT THESE
MODELS ARE EVEN NOW VALIDATED OR
EVALUATEED AGAINST DIFFERENT
EQUITY TRANSLATIONAL EQUITY
BASICALLY DO THEY TRANSLATE THE
SAME FOR DIFFERENT POPULATIONS
IS JUST THE FIRST STEP.
IF WE CAN'T MEASURE AND DON'T
HAVE METHODS TO MEASURE, NOW
THERE'S A BIG LITERATURE,
BECAUSE OF HOW SCARY AND
POWERFUL A.I. CAN BE THERE'S A
VERY LARGE LITERATURE ABOUT HOW
THEY CAN BE APPLIED AND
EVALUATED EQUITABLY OR WHERE
BIASES CAN BE IDENTIFIED, THAT
COULD TRANSLATE HERE.
THERE'S A LOT OF LITERATURE AND
RESOURCES, THAT'S ALWAYS THE
FIRST STEP, JUST MEASUREING.
>>I'LL PUT A FINE POINT ON WHAT
NICHOLAS SAID BY SAYING THAT IT
WOULD BE VERY, VERY EXPENSIVE TO
HAVE CELL LINES THAT
REPRESENTATIVE, YOU KNOW,
HUMANITY, THE SPECTRUM OF
HUMANITY.
THAT'S WHERE I THINK ARTIFICIAL
INTELLIGENCE, THE DIGITAL TWINS
BROUGHT UP EARLIER COULD HELP US
OUT BECAUSE WE MIGHT BE ABLE TO
SPOT CHECK THE -- WELL, TWO
WAYS.
YOU COULD SPOT CHECK THE
ARTIFICIAL INTELLIGENCE MODELS
BY TESTING, YOU KNOW, IN
PARALLEL WITH A FEW CELL LINES,
YOU MIGHT BE ABLE TO AUGMENT
WHAT YOU CAN DO WITH CELL LINES
BY SIMULATION SO I THINK THOSE
TWO COULD GO HAND IN HAND
BECAUSE IF YOU NEEDED TO HAVE A
THOUSAND CELL LINES FOR A SINGLE
CONTEXT OF USE, I THINK IT'S
PROHIBITIVELY EXPENSIVE TO
QUALIFY THAT NUMBER OF CELL
LINES.
I THINK THIS IS WHERE WE JUST
HAVE TO TURN TO MODELING AND
SIMULATION.
>>SPEAKING AS A FORMER GRAD
STUDENT, YOU UNDERSTAND.
SO WE'RE SLOWLY WRAPPING UP.
I WANT TO TACKLE THIS QUESTION.
WE'VE SAID A LOT THAT TALKS TO
OUR FELLOW SCIENTISTS,
ENGINEERS, BUT IT'S IMPORTANT TO
CONNECT WITH PUBLIC AS WELL.
I WOULD LIKE TO ASK THE QUESTION
HOW DO YOU HOPE TO ENGAGE THE
PUBLIC IN CONSIDERING AND
UNDERSTANDING ROAD MAP AHEAD TO
NAMs AND KEY OPPORTUNITIES FOR
PUBLIC EDUCATION TO ADVANCE THE
FIELD.
WE'VE BEEN TALKING TO FELLOW
COLLEAGUES IN THE SCIENCE AND
ENGINEERING FIELD BUT IN TERMS
OF THE PUBLIC HOW DO YOU ENGAGE
THE PUBLIC TO HELP THEM CONSIDER
IMPORTANCE IN USAGE OF NAMs,
WHAT DOES THAT LOOK LIKE AND
WHAT CAN BE DONE AS RELATES TO
PUBLIC EDUCATION IN GENERAL?
FOR ANYBODY.
>>I CAN START OFF.
I HAVE A COUPLE IDEAS FLOATING
AROUND.
DEALING WITH THE PUBLIC IN
PARTICULAR IT'S IMPORTANT TO BE
TRANSPARENT, AS TRANSPARENT AS
POSSIBLE ABOUT NAMs AND
LIMITATIONS AND REALLY EDUCATING
THEM ON WHY, MY PERSONAL UPON,
NOT THE USDA, WHY WE'RE NOT IN A
PARTICULAR PLACE TO, YOU KNOW,
NOT USE ANY ANIMALS IN RESEARCH.
I PERSONALLY DON'T THINK WE'RE
THERE YET AND THINK EDUCATION IS
KEY.
FROM AN OUTSIDER, PUBLIC AND
SOCIETY THINK IT'S EASY, WHY ARE
WE USING ANIMALS WHEN IT'S 21ST
CENTURY AND WE HAVE TECHNOLOGY.
WE'RE NOT COMMUNICATING OUR
GO-TO IS BECOME CLOSED OFF AND
NOT SAY THE WRONG THING.
WORKSHOPS AND SYMPOSIA LIKE
THIS, FORMING THE LINE OF
COMMUNICATION IS HUGE.
SOCIETY HAS A LOT OF SAY IN
FUTURE REGULATIONS AND POLICIES,
AND I THINK WE'RE BETTER OFF
GETTING AHEAD AND EDUCATING UP
FRONT VERSUS WAITING FOR THE
BACKLASH.
>>YES, I THINK CONVERSATION
WITH THE PUBLIC IS FANTASTIC.
I THINK SCIENTIFIC DEMOS,
ESPECIALLY WITH YOUNG PEOPLE
ALWAYS HELPS.
I THINK THE COMPUTATION MODELING
AND A.I. PART OF NAMs IS GOING
TO SCARE THE GENERAL PUBLIC.
A.I. HAS ALREADY BEGUN TO SCARE
THE GENERAL PUBLIC.
AND WHEN I THINK THERE'S A
CONCERN IF YOU CAN APPLY THAT TO
MY OWN HEALTH, YOU KNOW, I HAVE
A FAMILY FULL OF CONSPIRACY
THINKERS, I ALREADY KNOW WHERE
THEY WOULD GO WITH THAT
CONVERSATION.
AND SO I THINK IT HAS TO BE --
SOME CONVERSATION WE'VE HAD
HERE, WHAT ARE PROS AND
BENEFITS, AND THEN WHAT ARE SOME
LIMITATIONS AND WHY DO WE THINK
IT'S A PLACE THAT CAN BE
HELPFUL.
I THINK WHEN YOU START TALKING
ABOUT COST, THE CONVERSATION WE
CANNOT SIMULATE A THOUSAND TYPES
OF HUMANS IN A LAB, IT'S
EXPENSIVE, BUT A COMPUTER CAN,
PEOPLE DIDN'T GET HARMED IN
THOSE STUDIES SO THIS IS
ETHICAL.
I THINK IT'S GOING TO BE A
DIFFERENT EXPLANATION FOR
DIFFERENT AUDIENCES.
I THINK THE SCIENTISTS MUST BE
AWARE THERE MUST BE MULTIPLE
AUDIENCES IN THE ROOM, SOME PRO
A I, SOME AGAINST IT, SOME
SAYING KILL THE ANIMALS IN THE
GOATS TO MAKE ME BETTER.
SLIDE ABOUT HUMANS NOT A MON HE
-- MONOLITH, WE NEED TO HAVE
RESPONSES, BECAUSE WE'LL CUT OUT
ONE WHOLE SIDE OF THE AUDIENCE.
>>THAT WAS BEAUTIFULLY SAID,
WOULD JUST ADD ONE OF THE WAYS
WE ADDRESS THIS IS BY MAKING
SURE THAT IT'S A CONVERSATION.
WE'RE NOT OUT -- WE NEED TO
EDUCATE BUT BE EDUCATED BY THE
COMMUNITY AS WELL.
SO WE HAVE THESE COMMUNITY
ADVISORY BOARDS THAT WE HAVE
THAT GUIDE US IN RESEARCH AND
TRIALS, WE CONTINUALLY GO BACK
TO THEM AND THESE GROUPS.
SOME ARE FOCUSED ON PARTICULAR
DEMOGRAPHIC GROUPS, WE HAVE
LGBTQ PANELS, FOR EXAMPLE, THAT
WE GO BACK TO DO, A LOT OF
RESEARCH WITH.
THEY ADVISE US ON THE WORK THAT
WE'RE DOING.
AND SO JUST MAKING SURE THAT
THERE IS A WAY TO COMMUNICATE
BACK AND THAT WE ENGAGE IN
CONVERSATIONS IS REALLY
IMPORTANT.
>>I'LL JUST POP IN REAL QUICK
ECHOES WHAT JESSIE SAID, IT'S
REALLY IMPORTANT THAT WHEN WE'RE
EDUCATING THE PUBLIC WE NEED TO
REMEMBER THAT OUR FELLOW
SCIENTISTS SEE THAT
COMMUNICATION AS WELL.
AND SO SOMETIMES, AGAIN, I THINK
THERE IS SOME OF THIS
OVERPROMISING OR TRYING TO SWAY
PUBLIC OPINION AGAINST ANIMAL
RESEARCH SO THAT WE CHANGE THE
POLICY TO KIND OF PUSH, AND
WHILE CERTAINLY THERE MAY BE
MERITS AND COUNTER CULTURES, ET
CETERA, I THINK THAT CAN
SOMETIMES AGAIN ALIENATE THE
SCIENTISTS TRYING TO HAVE MORE
ENGAGEMENT IN NAMs.
THAT BALANCEED COMMUNICATION,
ALSO TRAINING MORE SCIENTISTS IN
SCIENCE COMMUNICATION GENERALLY
IS A SKILL THAT OFTEN GETS
OVERLOOKED IN SO MANY GRADUATE
PROGRAMS.
SOME SCIENTISTS STRUGGLE TO
COMMUNICATE TO FELLOW
SCIENTISTS, OR IN AN ADJACENT
FIELD, LET ALONE THE PUBLIC.
THERE COULD BE A LOT MORE
TRAINING BUT ALSO ENGAGING IN
EXPERTS, WE DON'T ALL HAVE TO BE
AN EXPERT IN EVERYTHING.
SOME PEOPLE ARE, YOU KNOW, MAY
BE MORE ATTUNED TO EDUCATION, TO
TRAINING, SOME NOT.
SO I THINK RELYING ON THE
EXPERTISE OF OTHERS TO TRANSLATE
KIND OF COMPLEX IDEAS TO THE
PUBLIC TO OTHER STAKEHOLDERS IN
A WAY THAT IS UNDERSTANDABLE,
TRANSPARENT, ALSO JUST HONEST
AND REALISTIC.
>>OKAY, OKAY.
THANK YOU.
SO AWESOME PANEL.
WE HAVE LESS THAN TEN MINUTES.
WE DON'T HAVE TO STAY THE ENTIRE
TIME.
I KNOW PEOPLE HAVE BEEN HERE ALL
DAY, THEY ARE GETTING TIRED.
IF YOU CAN JUST EACH OF YOU GIVE
YOUR LASTING THOUGHTS, BRIEFLY,
LASTING THOUGHTS THAT YOU WANT
TO LEAVE WITH THE VIRTUAL
AUDIENCE AND AUDIENCE IN THE
ROOM AS RELATED TO OUR TOPIC, I
WOULD APPRECIATE IT.
LASTING THOUGHTS, A COUPLE
SENTENCES WHAT YOU THINK ARE
TAKEAWAYS THAT WE WANT FOLKS TO
REMEMBER AS THIS DAY ENDS.
HOW ABOUT WE START BACK ON THIS
END, WITH JESSIE.
>>SURE.
TO START OUT I THINK SOMETHING I
WANT TO LEAVE THE AUDIENCE WITH
IS THAT WE'RE DOING GREAT WORK
IN THE DEVELOPMENT OF NAMs AND
HAVING THESE TYPES OF WORKSHOPS
AND SYMPOSIA TO TALK ABOUT
NAMs, BARRIERS, INCENTIVES.
HOW CAN WE APPLY AND MAKE CHANGE
ON THE GROUND LEVEL?
HOW CAN WE INCENTIVIZE NAMs?
SHOULD FUNDING AGENCIES INVEST
IN NAMs, BECAUSE MONEY TALKS
AND THAT'S GETS P.I.S, MORE
SEASONED ONES, TO MAKE THE
CHANGE.
WE TALK ABOUT TRAININGS, GETTING
EXPOSURE AND EDUCATION, WHO ARE
THE ONES THAT CAN MAKE THAT
CHANGE, MAYBE THREE Rs OR
AWIC.
THESE CONVERSATIONS AND
WORKSHOPS MOVE THE NEEDLE IN
THAT DIRECTION.
>>SO MY TAKEAWAY IS THAT I'D
LIKE TO LEAVE THE AUDIENCE,
FIRST OF ALL, POWER OF
COLLABORATION, WE'RE ALL DOING
IT TODAY, IT'S WHAT MY
ORGANIZATION IS ABOUT.
I THINK THAT GETTING INTO ROOMS
LIKE THIS, TALKING TO EACH
OTHER, LEARNING FROM EACH OTHER,
HAVING THESE OPEN CONVERSATIONS
IS TRULY REALLY IMPORTANT.
ALSO, YOU KNOW, WE ALSO
SUBMITTED TO THE RFI, OUR TWO
CORE MESSAGES, FIRST LIKE OTHER
PANELISTS HAVE SAID, INVESTMENT
AND VALIDATION AND
CHARACTERIZEATION OF THE MODELS
WE CURRENTLY HAVE, WE'VE GOT
MODELS, THEY NEED TO BE PUT INTO
PRACTICE MORE.
AND SECONDLY, KIND OF THE
INVESTMENT IN KIND OF THESE
RELATIONSHIP BUILDING, MESSAGES,
CHANGING THE SCIENTIFIC MIND AND
HOW SCIENTISTS PIECE THINGS.
SO THAT NAMs ARE APPROACH
ACKNOWLEDGE, THEY THINK NAMs
ARE GOOD, THEY SEE THERE IS
PROFESSIONAL PRESSURES, EVEN IF
IT'S VIEWING THE EARLY ADOPTERS,
VIEWING SUCCESS OF THAT, MAKING
IT EASIER TO ENGAGE, PROVIDING
TRAINING, CONNECTING THEM WITH
COMMERCIAL PARTNERS TO RUN
ASSAYS FOR THEM SO THEY DON'T
HAVE TO BE AN EXPERT IN THAT
ASSAY.
ALL OF THESE CAN HELP ADVANCE
NAMs AND I'LL JUST SAY
CONNECTING WITH PEOPLE WHO ARE
CURRENTLY DOING ANIMAL RESEARCH
BECAUSE ULTIMATELY THOSE ARE THE
PEOPLE THAT WE WANT TO START
WORKING WITH NAMs EVEN MORE.
>>YEAH, I WOULD JUST SUGGEST
THAT WE NEED TO BE VERY MINDFUL
ABOUT THESE TENSIONS I BROUGHT
UP AT THE BEGINNING BETWEEN
INCENTIVE STRUCTURES AND
PRIORITIES OF ACADEMIC SECTOR,
COMMERCIAL SECTOR, BIOLOGY
VERSUS ENGINEERING, AND ALSO
APPLICATION, END USER VERSUS
DEVELOPMENT.
I THINK FUNDING AGENCIES AND
REGULATORY AGENCIES, NIST, I'M
GLAD NIST WAS REPRESENTED
EARLIER, THEY NEED TO STEP IN AT
DIFFERENT PLACES ALONG THE
SPECTRUM OF THESE PARADIGMS.
ONE EXAMPLE OF THAT OUR START-UP
COMPANY HAS GOTTEN SBIR GRANTS,
INNOVATION SHOULD NOT BE A
REVIEW CRITERION FOR SBIR GRANT.
THINK ABOUT IT. THE DEVELOPMENT
HAS DONE, IT'S NOT INNOVATIVE
ANYMORE.
YOU'RE TRYING TO MAKE THIS THING
INVENTED IN A LAB OR MAYBE STTR,
LET'S SAY, WHY IS INNOVATION A
REVIEW CRITERION?
THOSE ARE THE THINGS WE NEED TO
BE VERY MINDFUL OF.
THINK ABOUT WHAT THE TARGET
AUDIENCE IS FOR THIS INCENTIVE
VERSUS THAT INCENTIVE, THIS
PRIORITY VERSUS THAT PRIORITY.
THE TENSION THAT EXISTS BETWEEN
THESE PARADIGMS.
I THINK THAT'S SOMETHING THAT
ALL OF US ARE GOING TO HAVE TO
PAY ATTENTION TO.
>>NICHOLAS IS NEXT, MANU LAST
>>I WANT TO REMIND EVERYBODY
ABOUT ENORMOUS AMOUNT OF DATA WE
GENERATE EVERY DAY THROUGH
PRACTICE OF MEDICINE.
EVERY DAY MILLIONS OF PATIENTS
ARE PRESCRIBED MEDICINES, AND
THEY ARE UNIQUE IN THE
MEDICATIONS AND COMORBIDITYS AND
BACKGROUNDS AND ENVIRONMENTAL
EXPOSURES.
AND IT MAKES THEM UNIQUE AND
AVAILABLE DATA POINT USED TO
ENHANCE MODELS, TO AUGMENT AND
CREATE NEW ONES, I WANT TO
HIGHLIGHT THAT TO CONTINUE.
THANK YOU.
>>I'D LIKE TO THINK ABOUT THE
LONG GAME FOR NAMs.
IF WE'RE THINKING ABOUT SOCIETY
UPTAKE, PATIENT UPTAKE, CULTURAL
UPTAKE, TO HAVE THE WORKFORCE
THAT WOULD CONTINUE DEVELOPMENT,
FEDERAL AGENCIES WE'VE BEEN
TALKING ABOUT ALL HAVE EDUCATION
ARMS AND/OR FUND TRAINING
PROGRAMS.
THE EARLIER THEY FUND TRAINING
PROGRAMS INTO UNDERGRAD GRADUATE
INSTITUTIONS, EVEN DOWN INTO
HIGH SCHOOLS, YOUNG PEOPLE TELL
FAMILY MEMBERS I LEARNED ABOUT
THIS ON A CHIP TODAY IN CLASS,
WHEN TECHNOLOGY DEVELOPED
SUFFICIENTLY WHERE IT'S NOW IN
PRACTICE, EVERYONE'S BEING ASKED
TO ON AS IT, IT LOWERS THAT
BARRIER.
AGAIN, MAKING SURE TO REACH ALL
SELL. -- ALL SEGMENT OF THE
POPULATION.
>>THANK YOU.
WE APPRECIATE THE FEEDBACK.
HOPEFULLY SOMETHING FROM WHAT
YOU SAID WILL BE TAKEN BY THE
AUDIENCE.
BACK TO YOU, HOWARD.
>>THANK YOU, DR. BAINES.
AS WE WRAP UP TODAY'S WORKSHOP
WE WANT TO THANK ALL THE
PRESENTERS AND PANELISTS WHO
SHARED VIEWS TODAY, OUR
MODERATORS AROUND WORKING GROUP
MEMBERS AND ALL OF YOU JOINING
US ONLINE.
THE PURPOSE HAS BEEN TO
HIGHLIGHT CURRENT STATE OF
NAMs AND HEAR FROM EXPERTS ON
CHALLENGES AND FUTURE PROMISES.
WE APPRECIATE HEARING FROM ALL
GUEST SPEAKERS, FEEDBACK FROM
THE WORKSHOP AND RESPONSE RFI
WILL PLAY A VALUABLE ROLE IN
INFORMING WORKING GROUP AS WE
MAKE OUR FINAL DECISION.
AS WE WRAP UP I OFFER A FEW
PRELIMINARY INTERIM REFLECTIONS
ON THE DAY.
WE'VE HEARD SO MUCH, IT'S A LOT
TO THINK ABOUT.
IN SESSION 1 WE HEARD ABOUT HOW
NAMs ARE BEING UTILIZEED IN
DIFFERENT FIELDS AND SECTORS,
EMPHASIZES IMPORTANCE OF PUTTING
TOGETHER DIVERSE
MULTI-DISCIPLINARY TEAMS WITH
THE RIGHT KNOWLEDGE.
AND BREAKING DOWN SILOS, CREATE
BE COLLABORATORIES BETWEEN
GROUPS, CREATING STANDARD
LANGUAGE AND INFRASTRUCTURE TO
FOSTER INTEROPERABILITY AND
MODELS.
WE HEARD ABOUT CHALLENGES WITH
REPRODUCIBILITY IN SOME CURRENT
MODELS AND OPPORTUNITIES OF
NAMs OR COMBINATIONS OF NAMs
TO FILL GAPS, IN PARTICULAR
NAMs MAY REPRESENT HUMAN
DIVERSITY AND VARIABILITY, IT
DOES NOT -- NOT POSSIBLE, OUR
TRADITIONAL ANIMAL MODELS, THIS
IS REALLY POTENTIALLY A GREAT
OPPORTUNITY.
IN SESSION 2 THE ROLE OF
DIFFERENT SECTORS COULD PLAY IN
USE AND DEVELOPMENT OF NAMs
WAS HIGHLIGHTED, AND THIS
DISCUSSION I THINK COMING ACROSS
STRONGLY WAS THE THEME TO THINK
ABOUT ALL THE STAKEHOLDER GROUPS
THROUGH THE ENTIRE LIFE CYCLE OF
NAMs DEVELOPMENT AND USE,
INCLUDING SCIENTIST, INDUSTRY
PARTNERS USING THEM, REGULATORS
WHO MIGHT BE EVALUATING THEM AND
USING THEM TO MAKE DECISIONS, A
COMMUNITIES INFORMED BY THEM, A
THEME ABOUT ENGAGING EARLY ON TO
SEE HOW THEY WOULD LIKE THIS
TECHNOLOGY TO BE USED.
THESE EFFORTS WILL REQUIRE
SPECIAL ATTENTION TO
COMMUNICATION, OUTREACH,
LANGUAGE, THE NEED,
INTERPRETATIONS OF THE PROBLEM.
AND THIS IS A RECURRING THEME,
WE NEED TO BRING MANY PEOPLE
FROM PREVIOUSLY SILOED AREAS
TOGETHER TO MAKE SOMETHING
THAT'S GREATER THAN THE SUM OF
ITS PARTS.
THE SPEAKERS FROM SESSION 3
DISCUSSED HIGH PRIORITY NEEDS
FOR INTEGRATED AND MULTI-SYSTEM
MODELS.
AND ONE MAJOR THEME THAT EMERGED
WAS NEED TO BUILD CONFIDENCE, IN
THE COMMUNITY, SCIENTIFIC
COMMUNITY FOR USE, THEIR USE, TO
MAKE DECISIONS BASED ON THESE
MODELS.
SO THIS INCLUDES NEED FOR
VALIDATION, QUALIFICATION
ASSISTANCE, THINKING
IMPLEMENTATION AND END USERS
NEEDS FROM THE BEGINNING OF
DEVELOPMENT.
ANOTHER TOPIC BROUGHT UP WAS
MOVING TECHNOLOGY FROM BENCH TO
BROAD USE REQUIRES LONG-TERM
INVESTMENTS HAVING A COMMON
LANGUAGE, THE RIGHT CROSS-SECTOR
TEAMS IN PLACE TO BRING THESE
PEOPLE TOGETHER FROM THE
BEGINNING.
ANOTHER IMPORTANT POINT IS THAT
WHILE THERE'S TREMENDOUS
PROMISE, THE GROUP ACKNOWLEDGED
THAT WE'RE NOT READY AT THIS
POINT TO GET RID OF ANIMAL
MODELS.
IN PARTICULAR CURRENT NAMs ARE
NOT ABLE TO FULLY REPRESENT
HUMAN COMPLEXITY, LOOKING FOR
LONGER TERM EFFECTS, AND ONE
LIMITATIONS SOME OF THE NAMs
MAYBE DERIVED FROM SMALL NUMBER
OF INDIVIDUALS, CELL SOURCE,
MUCH BETTER COMPARISON BETWEEN
ANIMAL MODELS AND NAMs AND
HUMANS ARE NEEDED TO FIGURE OUT
DIFFERENCES IN SYSTEM OF
TRANSLATION.
SESSION 4 WE HEARD FROM SPEAKERS
ABOUT ADDRESSING NEEDS TO
LEVERAGE LARGE DIVERSITY, TO
MAXIMIZE -- MAXIMUM USEFUL
NAMs, BEST MODELS TO ANSWER
RESEARCH QUESTIONS, DIFFERENT
QUESTIONS DEMAND DIFFERENT
MODELS AND TECHNOLOGIES.
WE HEARD ABOUT THE NEED FOR HIGH
QUALITY DATA AND, AGAIN, THAT
SHOULD COME FROM NAM DEVELOPERS
WHO HAVE A DEEP UNDERSTANDING OF
THE MODELS USED AND ALSO
IMPORTANCE OF UNDERSTANDING END
USER NEED, WHETHER IT'S A
PATIENT, A PHYSICIAN, RESEARCHER
OR PHARMACEUTICAL DEVELOPER, AND
WE HEARD ABOUT HAVING FEDERATED
DATA, THIS IS DIRECTLY TO THE
NEXT POINT, TRANSPARENCY IS
CRITICAL, ESPECIALLY
TRANSPARENCY ABOUT WHAT IS BEING
MODELS AND WHAT THAT COULD
PREVENT OVERSELLING OF THESE
TECHNOLOGIES.
AND IT WAS NOTED OVERSELLING THE
PROMISE OF NOVEL METHODS COULD
SET BACK THE FIELD BY
POTENTIALLY LEADING TO
DISAPPOINTMENT AND LOWER
CONFIDENCE AND MISTRUST,
SOMETHING TO STRIKE BALANCE ON.
SPEAKERS ALSO DISCUSSED HOW
COMPUTATIONAL MODELS CAN BE USED
TO EVALUATE NAMs AND HELP
INFORM OPTIMAL DESIGN
EXPERIMENT, A VERY GOOD USE OF
POTENTIAL ARTIFICIAL
INTELLIGENCE BECAUSE POTENTIAL
SEARCH SPACE FOR OPTIMAL DESIGNS
IS BASICALLY VERY LARGE SO THIS
IS A GOOD APPLICATION OR
COMPUTATION.
AND FINALLY IN THIS LAST SESSION
WE HEARD ABOUT HOW TO EQUITABLY
DEPLOY ROBUST AND RELIABLE
NAMs, DISCUSSING NEED TO THINK
ABOUT EQUITY, ACCESS TO
TECHNOLOGY FROM EARLY IN
DEVELOPMENT PROCESS, INVOLVING
MAKING THEM ABLE TO BE USED BY
PEOPLE IN LOW RESOURCE AREAS,
MAKE IT EASY TO USE AND ACCESS.
WE HEARD ABOUT VERY GOOD IDEAS
ABOUT WORKFORCE DEVELOPMENT THAT
WE COULD TRAIN ADDITIONAL USERS
TO CATALYZE DISSEMINATION AND
UPTAKE OF NAMs AND THIS THEN
SPEAKS TO THE POINT ABOUT THERE
SHOULD BE MULTIPLE ENTRY POINTS
FOR ENGINEERS, BIOLOGISTS,
SCIENTISTS WITH BACKGROUNDS NOT
PREVIOUSLY INVOLVED, COULD GET
IN TRYING, DEPLOY NAMs.
FINALLY WE HEARD ABOUT
INTEGRATING NAMs EARLIER ON
DRUG DEVELOPMENT PROCESS, AND
THERE'S THIS PROMISE THAT RELIES
ON THE POSSIBILITY THAT NAMs
WILL PERHAPS IN THE FUTURE
REFLECT DIVERSITY OF PATIENT
POPULATIONS, ALSO AGAIN THE
THEME THAT THERE COULD BE A
VIRTUOUS LOOP OF DIFFERENT
MODELS, WHERE DIFFERENT MODELS
COMING IN, WHERE DATA FROM
PATIENTS ARE USED TO GENERATE
HIGH HYPOTHESES AND LARGE SCALE
MODELS.
IT'S BEEN AN INCREDIBLE DAY,
SOME IDEAS HOW NIH COULD HELP
ACCELERATE THE DEVELOPMENT AND
USE OF NAMs.
OUR WORKING GROUP WILL CONSIDER
ALL THE IDEAS AND PERSPECTIVES
THAT WERE RAISED TODAY.
AND THROUGH AN RFI TO INFORM NIH
ON INVESTMENTS THAT COULD BE
MADE TO PROVIDE THE GREATEST
BANK FOR THE BUCK IN THE FIELD
AND THESE TECHNOLOGIES, ULTIMATE
GOAL TO ACCELERATE PROGRESS AND
UNDERSTANDING AND IMPROVING
HUMAN HEALTH.
IF ANYONE IS INTERESTED IN
SUBMITTING WRITTEN PUBLIC
COMMENTS, IF YOU WANT THEM
CONSIDERED AS WE PREPARE FINAL
REPORT FROM THESE PROCEEDINGS,
WE WOULD BE GRATEFUL TO HAVE YOU
SUBMIT YOUR RESPONSE TO OUR RFI
REQUEST FOR INFORMATION BY
SEPTEMBER 5.
I THANK DR. SEGER FOR HER
ENTHUSIASTIC ENDORSEMENT AND
PARTICIPATION IN THIS PROCESS
AND A LINK TO THE RFI IS
AVAILABLE ON THE REGISTRATION
SITE FOR THIS EVENT.
ALSO I'LL POINT OUT THE
RECORDING WILL BE AVAILABLE ON
THE NIH VIDEOCAST WEBSITE WITHIN
THE NEXT WEEK OR SO.
STAY TUNED FOR MORE OUTPUTS
BASED ON TODAY'S DISCUSSION.
TO END, I WANT TO THANK A LARGE
GROUP OF PEOPLE WHO MADE THIS
SPECIAL DAY POSSIBLE.
FIRST I WANT TO THANK THE
MODERATORS FOR GUIDING
DISCUSSIONS, KEEPING US ON TIME
AND TO SPEAKERS FOR SHARING
VALUABLE INSIGHTS.
THERE'S A TEAM OF PEOPLE BEHIND
THE SCENES WHO THAT -- WHO MADE
THIS POSSIBLE, EXECUTIVE
SECRETARYS AND CONTRACTORS,
STAFF SUPPORT, AND VIDEOCAST AND
EVENT MANAGEMENT TEAMS.
WE ALSO WOULD LIKE TO SHARE
APPRECIATION FOR THE ASL
INTERPRETERS, MAJOR THING TODAY
WAS HOW COMPLEX THE LINGO
BETWEEN SECTORS IS A BEARER TO
COLLABORATIONS, OUR INTERPRETERS
HAD TO HANDLE THAT ON THE FLY
TODAY.
I WANT TO THANK MY CO-CHAIR DR.
LYRIC JORGENSON, A A WORKSHOP
IS A HUGE PRIORITY,
UNFORTUNATELY NOT ABLE TO ATTEND
AND SORRY TO MISS TODAY.
I WOULD LIKE TO THANK EVERYONE
FOR PARTICIPATING AND WATCHING
VIA VIDEOCAST.
WE'RE NOW ADJOURNED.
THANK YOU SO MUCH.