The Inverse Problem Accounting for Therapeutic Variability: Development of a Practical Strategy to Maximally Extract Information from Limited Clinical Data

Project Type: 
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This project is part of sustained efforts to deal with the complex relationship of dose-exposure-effect of drugs. The software to be developed will build on metrics with mathematical foundations that update empirical methods within the evolving computational power.

Project Leader(s): 

Postdoctoral fellow: Dr. Olivier Barrière, Faculty of Pharmacy, Université de Montréal

Lead faculty member: Dr. Fahima Nekka, Faculty of Pharmacy, Université de Montréal

Pharmacometrics (PM) is an emerging research area defined as “the science that interprets and describes pharmacology in a quantitative fashion to aid efficient drug development and/or regulatory decision”. Over the years, Dr. Nekka’s team has encompassed deep thinking on how to join and enhance emerging worldwide efforts to make mathematical modeling and simulation a complementary language to the usual empirical and clinical methods used in drug discovery and development. This work is part of these sustained efforts to deal with the complex relationship of dose-exposure-effect of drugs. The major concern is about maximising the information-load, reliability and transferability of the proposed methods. The forward problem of linking drug intake to pharmacokinetics has a related inverse problem for the reconstruction of drug intake from limited clinical data. The software we want to develop will build on metrics with mathematical foundations that update empirical methods within the evolving computational power.