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Screening Cancer Immunotherapy: When Engineering Approaches Meet Artificial Intelligence.

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
Source :
Advanced Science. 10/7/2020, Vol. 7 Issue 19, p1-21. 21p.
Publication Year :
2020

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 FROM AUTHOR]

Details

Language :
English
ISSN :
21983844
Volume :
7
Issue :
19
Database :
Academic Search Index
Journal :
Advanced Science
Publication Type :
Academic Journal
Accession number :
146320760
Full Text :
https://doi.org/10.1002/advs.202001447