Artificial intelligence-driven drug development against autoimmune diseases

被引：16

作者：

Moingeon, Philippe ^{[1
,2
]}

机构：

[1] Servier Labs, Res & Dev, 50 Rue Carnot, F-92150 Suresnes, France

[2] French Acad Pharm, 4 Ave Observ, F-75006 Paris, France

来源：

TRENDS IN PHARMACOLOGICAL SCIENCES | 2023年 / 44卷 / 07期

关键词：

artificial intelligence; autoimmune diseases; biomarker; computational precision medicine; drug development;

D O I：

10.1016/j.tips.2023.04.005

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Artificial intelligence (AI)-based predictive models are being used to foster a pre-cision medicine approach to treat complex chronic diseases such as autoim-mune and autoinflammatory disorders (AIIDs). In the past few years the first models of systemic lupus erythematosus (SLE), primary Sj & ouml;gren syndrome (pSS), and rheumatoid arthritis (RA) have been produced by molecular profiling of patients using omic technologies and integrating the data with AI. These ad-vances have confirmed a complex pathophysiology involving multiple proinflam-matory pathways and also provide evidence for shared molecular dysregulation across different AIIDs. I discuss how models are used to stratify patients, assess causality in pathophysiology, design drug candidates in silico, and predict drug efficacy in virtual patients. By relating individual patient characteristics to the predicted properties of millions of drug candidates, these models can improve the management of AIIDs through more personalized treatments.

引用

页码：411 / 424

页数：14

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