Optimization of Personalized Treatments – OPT

Personalized or precision medicine aims at giving the “right treatment to the right patient”. It is one of the most promising areas of medical research, but its development is hindered by methodological limitation of studies used. Determining individualized treatment rules (ITR) is an active research field of biostatistics relying on recent statistical methods (machine learning, classification of high-dimensional data) that raises many statistical and computational challenges. For instance if measures of the performance of an ITR have been developed, testing whether personalization provides overall benefit remains an open problem.
In this project, we will develop a statistical test for the benefit of personalization, as well as innovative approaches to identify personalized treatment strategies using data from randomized controlled trials and observational studies, that will be generalized to situations where (1) more than two alternative treatments exist and (2) the treatment is given at some point during the follow-up. Methods will be applied on several real datasets from randomized trials and observational studies.