When artificial intelligence meets PD-1/PD-L1 inhibitors: Population screening, response prediction and efficacy evaluation. (June 2022)

• Record Type: Journal Article
• Authors: Jin, Weiqiu; Luo, Qingquan
• Is Part Of: Computers in biology and medicine. Volume 145(2022)
• Publication Date: 2022-06
• Subjects: PD-1 -- PD-L1 -- Immunotherapy -- Artificial intelligence; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2022.105499
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Programmed cell death protein-1 (PD-1) and its ligand (programmed death ligand 1, PD-L1) inhibitors, as the rising stars of immunotherapy, have been widely used in clinical practice, and the corresponding population screening, response prediction and efficacy evaluation have become increasingly important in clinic. Artificial Intelligence (AI) can help us uncover effective information from clinical data such as medical history, images, laboratory results, sequencing data, etc., which can help us solve above problems and enrich the methodology of clinical research. In this way, AI researches related to PD-1/PD-L1 inhibitors have been emerging. Based on an introduction of AI fundamentals in medicine, this review systematically summarizes the existing AI studies related to PD-1/PD-L1 immunotherapy in three aspects: population screening, response prediction and efficacy evaluation, and briefly outlooks the development direction of AI studies related to PD-1/PD-L1 inhibitors. Highlights: PD-1 and its ligand (PD-L1) inhibitors are the rising stars of immunotherapy. The corresponding population screening, response prediction and efficacy evaluation have become increasingly important. The existing AI studies related to PD-1/PD-L1 immunotherapy in three aspects (population screening, response prediction and efficacy evaluation) are reviewed. The development direction of AI studies related to PD-1/PD-L1 inhibitors is discussed.