Bioinformatics Research on Drug Sensitivity Prediction

Yaojia Chen; Liran Juan; Xiao Lv; Lei Shi

doi:10.3389/fphar.2021.799712

Bioinformatics Research on Drug Sensitivity Prediction

Front Pharmacol. 2021 Dec 9:12:799712. doi: 10.3389/fphar.2021.799712. eCollection 2021.

Authors

Yaojia Chen¹, Liran Juan², Xiao Lv³, Lei Shi⁴

Affiliations

¹ Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.
² School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
³ Beidahuang Industry Group General Hospital, Harbin, China.
⁴ Department of Spine Surgery Changzheng Hospital, Naval Medical University, Shanghai, China.

Abstract

Modeling-based anti-cancer drug sensitivity prediction has been extensively studied in recent years. While most drug sensitivity prediction models only use gene expression data, the remarkable impacts of gene mutation, methylation, and copy number variation on drug sensitivity are neglected. Drug sensitivity prediction can both help protect patients from some adverse drug reactions and improve the efficacy of treatment. Genomics data are extremely useful for drug sensitivity prediction task. This article reviews the role of drug sensitivity prediction, describes a variety of methods for predicting drug sensitivity. Moreover, the research significance of drug sensitivity prediction, as well as existing problems are well discussed.

Keywords: anti-cancer; database; deep learning; drug sensitivity; machine learning.

Publication types

Review