Industrializing AI-powered drug discovery: lessons learned from the computing platform.

Introduction: As a mid-size international pharmaceutical company, we initiated 4 years ago the launch of a dedicated high-throughput computing platform supporting drug discovery. The platform named ' was built up on the initial predicate to capitalize on our proprietary data while leveraging public data sources in order to foster a Computational Precision Medicine approach with the power of artificial intelligence.

Areas Covered: Specifically, is designed to identify novel therapeutic target candidates.

Model-based computational precision medicine to develop combination therapies for autoimmune diseases.

Introduction: The complex pathophysiology of autoimmune diseases (AIDs) is being progressively deciphered, providing evidence for a multiplicity of pro-inflammatory pathways underlying heterogeneous clinical phenotypes and disease evolution.

Areas Covered: Treatment strategies involving drug combinations are emerging as a preferred option to achieve remission in a vast majority of patients affected by systemic AIDs. The design of appropriate drug combinations can benefit from AID modeling following a comprehensive multi-omics molecular profiling of patients combined with Artificial Intelligence (AI)-powered computational analyses.

Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19.

While establishing worldwide collective immunity with anti SARS-CoV-2 vaccines, COVID-19 remains a major health issue with dramatic ensuing economic consequences. In the transition, repurposing existing drugs remains the fastest cost-effective approach to alleviate the burden on health services, most particularly by reducing the incidence of the acute respiratory distress syndrome associated with severe COVID-19. We undertook a computational repurposing approach to identify candidate therapeutic drugs to control progression towards severe airways inflammation during COVID-19.

IFN-α: A key therapeutic target for multiple autoimmune rheumatic diseases.

Interferon (IFN)-α has emerged as a major therapeutic target for several autoimmune rheumatic diseases. In this review, we focus on clinical and preclinical advances in anti-IFN-α treatments in systemic lupus erythematosus (SLE), primary Sjögren syndrome (pSS), systemic sclerosis (SSc), and dermatomyositis (DM), for which a high medical need persists. Promising achievements were obtained following direct IFN-α neutralization, targeting its production through the cytosolic nucleic acid sensor pathways or by blocking its downstream effects through the type I IFN receptor.

The IgG2 Isotype of Anti-Transcription Intermediary Factor 1γ Autoantibodies Is a Biomarker of Cancer and Mortality in Adult Dermatomyositis.

Objective: Anti-transcription intermediary factor 1γ (anti-TIF1γ) antibodies are the main predictors of cancer in dermatomyositis (DM). Yet, a substantial proportion of anti-TIF1γ-positive DM patients do not develop cancer. This study was undertaken to identify biomarkers to better evaluate the risk of cancer and mortality in DM.

Dermatomyositis and Immune-Mediated Necrotizing Myopathies: A Window on Autoimmunity and Cancer.

Autoimmune myopathies (myositides) are strongly associated with malignancy. The link between myositis and cancer, originally noticed by Bohan and Peter in their classification in 1975 (1), has been evidenced by large population-based cohort studies and a recent meta-analysis. The numerous reports of cases in which the clinical course of myositis reflects that of cancer and the short delay between myositis and cancer onset support the notion that myositis may be an authentic paraneoplastic disorder.