Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

In Annales pharmaceutiques francaises

Artificial intelligence (AI) encompasses technologies recapitulating four dimensions of human intelligence, i.e. sensing, thinking, acting and learning. The convergence of technological advances in those fields allows to integrate massive data and build probabilistic models of a problem. The latter can be continuously updated by incorporating new data to inform decision-making and predict the future. In support of drug discovery and development, AI allows to generate disease models using data obtained following extensive molecular profiling of patients. Given its superior computational power, AI can integrate those big multimodal data to generate models allowing (i) to represent patient heterogeneity and (ii) identify therapeutic targets with inferences of causality in the pathophysiology. Additional computational analyses can help identifying and optimizing drugs interacting with these targets, or even repurposing existing molecules for a new indication. AI-based modeling further supports the identification of biomarkers of efficacy, the selection of appropriate combination therapies and the design of innovative clinical studies with virtual placebo groups. The convergence of biotechnologies, drug sciences and AI is fostering the emergence of a computational precision medicine predicted to yield therapies or preventive measures precisely tailored to patient characteristics in terms of their physiology, disease features and environmental risk exposure.

Moingeon Philippe


Artificial intelligence, Biotechnologies, biotechnologies, computational medicine, disease model, drug development, développement médicamenteux, intelligence artificielle, intelligent machines, machines intelligentes, modèle de maladie, médecine computationnelle, médecine de précision, precision medicine