Pharmocogenetics, Clinical Avatars and Predictions of Personalized Medicine

September 17, 2018
Free for AMIA members; $50 for non-members.
Peter Tonellato, PhD

This webinar will present 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. 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. 

Learning Objectives

After participating in this activity, the learner should be better able to:

  • Select pharmacogenetics problems for which clinical avatars are applicable
  • Choose clinical variables to be used in avatar design
  • Apply clinical avatar design to real-world clinical problems

Speaker Information

Peter Tonellato, PhD
Director of the Center for Biomedical Informatics
University of Missouri

Peter Tonellato, PhD, is the founding director of the Center for Biomedical Informatics at the University of Missouri, School of Medicine. Dr. Tonellato brings more than 30 years of experience and mathematics expertise to the role, and he has initiated similar multidisciplinary centers at other academic medical institutions.

Dr. Tonellato has a doctorate in applied mathematics from the University of Arizona and most recently held posts at Harvard Medical School and Brigham and Women’s Hospital, and at the Zilber School of Public Health at the University of Wisconsin, Milwaukee. He has led initiatives to study, test and predict the accuracy and clinical efficacy of genetic discoveries and accelerate their translation to practical clinical use.