A COMPREHENSIVE REVIEW: EXPLORING ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY AND DEVELOPMENT

Abstract

Drug discovery and development process is very lengthy, highly expensive and extremely complex in nature.Traditional methods involve expensive techniques and take many years to bring a new drug to the market.With the advent of new tools and technologies in this field, the major challenge is to reduce the time and cost required for the development of a new drug.These complex problems involve extremely high computations and can be addressed with the help of Artificial Intelligence based techniques.The abstract explores the integration of machine learning, deep learning, and data analytics in predicting drug interactions, optimizing compound synthesis, and accelerating the identification of novel therapeutic candidates.This review presents the literature survey of different research articles published in reputed journals of international publishers such as Springer, Science Direct, IEEE Explore, Elsevier etc.In addition to the in-depth analysis the foreseen challenges and existing limitations associated with drug discovery and development process are also pointed out in bold and humble suggestions have been made for necessary improvements.Readers, who are new to the Feld, will found it useful for enhancing their view about the Feld.