Quantifying and predicting the heterogeneous treatment effect of pharmacogenomic drugs

Type de poste
Niveau d'étude minimal
Durée du poste
Contrat renouvelable
Contrat renouvelable
Détails de renouvellement
Renouvelable 1 fois.
Date de prise de fonction
Date de fin de validité de l'annonce

LORIA - INRIA Nancy-Grand Est - Equipe Orpailleur
Campus Scientifique, BP 239
54506 Vandoeuvre-lès-Nancy

Adrien Coulet
Anne Gégout-Petit
Email du/des contacts

The aim of this postdococtoral project is to build upon previous results by first developing approaches that from EHR data identify without a priori groups of patients with distinct response profiles to particular drugs. Second, discovered groups will be used to identify predictors of drug response profiles.We want to study the use of the causal inference framework (Hernàn and Rubins, 2019), and in particular of double robust approaches to identify groups with heterogeneous treatment effect, or in other words with significantly different drug response profiles. Through others, (Athey and Imbens, 2016) introduced Causal Trees for subgroup analyses. Those are regression trees with modified splitting rules that maximise the difference in treatment effect between groups. Causal Trees have been reused to propose an ensemble method named Causal Forest that has the advantage of being non-parametric and consistent in many settings.These models will allow us to estimate the causal effect of the phenotype on the drug response.A second objective of the project is to develop high performance predictive models for drug response profiles that we aim at identifying with causal methods.These models can be seen as classifiers that assign individuals to a specific profile. A first challenge here is to develop real predictive models ,i.e., models that are trained only on data collected prior to the prescription of the drug.A second challenge is to identify a subset of good predictive features that may help in interpreting group belonging and heterogeneous drug responses.The set of drug studies will first be pharmacogenomic drugs, i.e, drugs known to present a variability in the population for genomic reasons, and will potentially be extended in a second time to other drugs of interest

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