Salman Akhtar, Mohammad Kalim Ahmad Khan, Khwaja Osama2025-05-162020978-981-15-6814-510.1007/978-981-15-6815-2_12http://136.232.12.194:4000/handle/123456789/1212Book: Computer-Aided Drug Design Editor Dev Bukhsh SinghPharmaceutical industries are multibillionaire setups with a diligent team ofscientists, researchers, technical manpower, and investors. A major concern ofsuch industries is to always curtail the time and cost factor associated with them.Bioinformatics involving machine learning (ML) methods have come to theforefront to address this problem. The predictive and statistical efficacy of MLmethodologies has even proven to propose better leads than a wet lab pipeline.This chapter aims to give a brief overview of underlying principles of mainly GAsand ANNs as popular ML algorithms and deeper insight into their robustapplications in the field of modern day drug design. It also attempts to share thefuture prospects of such ML techniques and their limitations with possiblesolutions hereafter.en-USMachine learningGenetic algorithmsArtificial neural networksDrugdesigningDeep learningSupport vector machinesBook chapter