Screening Cancer Immunotherapy: When Engineering Approaches Meet Artificial Intelligence. Issue 19 (13th August 2020)

• Record Type: Journal Article
• Authors: Zhou, Xingwu; Qu, Moyuan; Tebon, Peyton; Jiang, Xing; Wang, Canran; Xue, Yumeng; Zhu, Jixiang; Zhang, Shiming; Oklu, Rahmi; Sengupta, Shiladitya; Sun, Wujin; Khademhosseini, Ali
• Is Part Of: Advanced science. Volume 7:Issue 19(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-13
• Subjects: artificial intelligence -- cancer immunotherapy -- drug screening -- high‐throughput screening -- tissue engineering; Science -- Periodicals; 505
• DOI: 10.1002/advs.202001447
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: Immunotherapy is a class of promising anticancer treatments that has recently gained attention due to surging numbers of FDA approvals and extensive preclinical studies demonstrating efficacy. Nevertheless, further clinical implementation has been limited by high variability in patient response to different immunotherapeutic agents. These treatments currently do not have reliable predictors of efficacy and may lead to side effects. The future development of additional immunotherapy options and the prediction of patient‐specific response to treatment require advanced screening platforms associated with accurate and rapid data interpretation. Advanced engineering approaches ranging from sequencing and gene editing, to tumor organoids engineering, bioprinted tissues, and organs‐on‐a‐chip systems facilitate the screening of cancer immunotherapies by recreating the intrinsic and extrinsic features of a tumor and its microenvironment. High‐throughput platform development and progress in artificial intelligence can also improve the efficiency and accuracy of screening methods. Here, these engineering approaches in screening cancer immunotherapies are highlighted, and a discussion of the future perspectives and challenges associated with these emerging fields to further advance the clinical use of state‐of‐the‐art cancer immunotherapies are provided. Abstract : Advanced engineering approaches and progress in artificial intelligence can contribute to the development of cancer immunotherapy by uncovering alternative treatment targets and identifying hallmarks of treatment response, efficacy, and side effects. Screening approaches, including sequencing, gene editing, tumor organoids engineering, bioprinting, and organs‐on‐a‐chip, combined with high‐throughput screening and artificial intelligence are promising in accelerating broader application of cancer immunotherapy for a larger population.