Publications by authors named "P Moingeon"
Harnessing the power of AI-based models to accelerate drug discovery against immune diseases.
Expert Rev Clin Immunol
October 2024
Article Synopsis
- Primary Sjögren disease (pSD) is an autoimmune disease that causes dryness in the body and is not yet treatable effectively.
- Researchers studied blood samples from pSD patients to find groups of genes (called Consensus gene Modules) that reveal important information about the disease.
- They discovered that different gene groups could predict how well patients respond to certain treatments, which could help doctors find better ways to help people with pSD in the future.
Artificial intelligence and machine learning enable the construction of predictive models, which are currently used to assist in decision-making throughout the process of drug discovery and development. These computational models can be used to represent the heterogeneity of a disease, identify therapeutic targets, design and optimize drug candidates, and evaluate the efficacy of these drugs on virtual patients or digital twins. By combining detailed patient characteristics with the prediction of potential drug-candidate properties, artificial intelligence promotes the emergence of a "computational" precision medicine, allowing for more personalized treatments, better tailored to patient specificities with the aid of such predictive models.
View Article and Find Full Text PDFObjective: While the involvement of IL-7/IL-7R axis in pSS has been described in relation to T cells, little is known about the contribution of this pathway in relationship with other immune cells, and its implication in autoimmunity. Using high-content multiomics data, we aimed at characterizing IL-7R expressing cells and the involvement of IL-7/IL-7R pathway in pSS pathophysiology.
Methods: An IL-7 signature established using RNA-sequencing of human PBMCs incubated with IL-7 was applied to 304 pSS patients, and on RNA-Seq datasets from tissue biopsies.