Use of real-world evidence in translational pharmacology research.

Real-world evidence (RWE) refers to observational data gathered outside the formalism of randomized controlled trials, in real life situations, on marketed drugs. While clinical trials are the gold standards to demonstrate the efficacy and tolerability of a medicinal product, the generalizability of their results to actual use in real-life is limited by the biases induced by the very nature of clinical trials; indeed, the patients included in the trials may differ from actual users because of their concomitant diseases or treatments, or other factors excluding them from the trials. Clinical researchers and pharmaceutical industries have hence become increasingly interested in expanding and integrating RWE into clinical research, by capitalizing on the exponential growth in access to data from electronic health records, claims databases, electronic devices, software or mobile applications, registries embedded in clinical practice and social media.

Patient and Graph Embeddings for Predictive Diagnosis of Drug Iatrogenesis.

In the context of the IA.TROMED project we intend to develop and evaluate original algorithmic methods that will rely on semantic enrichment of embeddings by combining new deep learning algorithms, such as models founded on transformers, and symbolic artificial intelligence. The documents' embeddings, the graphs' embeddings of biomedical concepts, and patients' embeddings, all of them semantically enriched with aligned formal ontologies and semantic networks, will constitute a layer that will play the role of a queryable and searchable knowledge base that will supply the IA.

Innovative approaches in CNS drug discovery.

Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients. This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify therapeutic strategies is urgent in the field. This review will first cover the challenges and opportunities of drug discovery in neurology, and then as well as the new models, such as human model stem cells and animal models under development in the field.