Section: New Results

Model based-clustering for pharmacovigilance data

Participants : Gilles Celeux, Christine Keribin, Valérie Robert.

In collaboration with Pascale Tubert-Bitter, Ismael Ahmed and Mohamed Sedki, Gilles Celeux and Christine Keribin has started a research concerning the detection of associations between drugs and adverse events in the framework of the PhD of Valerie Robert. At first, this team has developed a model-based clustering inspired of the latent black model which consists in co-clustering rows and columns of two binary tables imposing the same row ranking. Then it enables to highlight subgroups of individuals sharing the same drug profile and subgroups of adverse effects and drugs with strong interaction. Besides, some sufficient conditions are provided to obtain the identifiability of the model and some studies are experimented on simulated data.