NIH VideoCast - Pharmocogenetics, Clinical Avatars and Predictions of Personalized Medicine

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Pharmocogenetics, Clinical Avatars and Predictions of Personalized Medicine

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Air date:	Wednesday, November 4, 2009, 10:30:00 AM Time displayed is Eastern Time, Washington DC Local
Views:	Total views: 109 * This only includes stats from October 2011 and forward.
Category:	Special
Runtime:	01:31:16
Closed captioning:	Check box to display CC outside of the video Note: You can drag the captioning window around and resize it
Description:	NLM Informatics Lecture Series Dr. Tonellato presents a general approach, mathematical model and computational method to predict clinical efficacy of genetic discoveries using ‘clinical avatars’ to conduct simulations of the effect of genotypes on risk, diagnosis and treatment. Clinical avatars are individual medical data records produced from a stochastic model and statistical parameters developed to reflect actual patient populations. The approach is used to detect differences between predictions of two warfarin dosing prediction algorithms applied to several representative patient populations (US general, African American, Asian). Clinical variables (clinical, prescription, and genetic) used in the model were derived from examination of published warfarin prediction and decision support algorithms. Clinical avatars are then produced with variables and population means, variances and dependencies consistent with those found in the literature. Simulations demonstrate strengths and weaknesses of the dosing algorithms depend on population characteristics, size and genetic frequencies. All modeling, computations and simulations are conducted on our cloud computing environment. Examples of the strategy, methods, and simulations in other areas of personalized medicine such as cancer risk prediction will be discussed. Acrobat Slides

NLM Title:	Pharmocogenetics, clinical avatars, and predictions of personalized medicine / Peter J. Tonellato.
Author:	Tonellato, Peter J. National Institutes of Health (U.S.)
Publisher:
Abstract:	(CIT): NLM Informatics Lecture Series Dr. Tonellato presents a general approach, mathematical model and computational method to predict clinical efficacy of genetic discoveries using "clinical avatars" to conduct simulations of the effect of genotypes on risk, diagnosis and treatment. Clinical avatars are individual medical data records produced from a stochastic model and statistical parameters developed to reflect actual patient populations. The approach is used to detect differences between predictions of two warfarin dosing prediction algorithms applied to several representative patient populations (US general, African American, Asian). Clinical variables (clinical, prescription, and genetic) used in the model were derived from examination of published warfarin prediction and decision support algorithms. Clinical avatars are then produced with variables and population means, variances and dependencies consistent with those found in the literature. Simulations demonstrate strengths and weaknesses of the dosing algorithms depend on population characteristics, size and genetic frequencies. All modeling, computations and simulations are conducted on our cloud computing environment. Examples of the strategy, methods, and simulations in other areas of personalized medicine such as cancer risk prediction will be discussed. Acrobat Slides.
Subjects:	Biomarkers, Pharmacological Computer Simulation Models, Theoretical Pharmacogenetics Precision Medicine Warfarin--pharmacology
Publication Types:	Lecture Webcast
NLM Classification:	QV 38
NLM ID:	101520503
CIT Live ID:	8136
Permanent link:	https://videocast.nih.gov/watch=8136

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