A Systematic Literature Review on Drug Synergy Prediction Techniques

Abstract

Synergistic combinations of drugs are extensively utilized for cancer treatment. However, prediction of drug synergy is defined as an ill-posed problem. Because manual testing is only implementable on small group of drugs. Recently, many researchers have utilized machine and deep learning models for drug synergy prediction. The main objective of this paper is to systematically review the drug synergy prediction techniques. We have considered some recently designed machine and deep learning-based drug synergy prediction techniques. Thereafter, we have reviewed these papers and compared some of them with each other based upon certain characteristics. From, this systematic literature review, it has been found that the prediction of drug synergy using machine and deep learning is still an open area of research. The techniques applied so far suffer from hyper-parameters tuning issue. Finally, we have discussed some future scope to improve the drug synergy prediction techniques