A Prospective Study on Computer-Aided Drug Design and Drug Discovery

Abstract

Computer-Aided Drug Design (CADD), which bridges the fields of biology and technology, is a revolutionary force in the ever-changing
field of drug development. The historical development of CADD, its classification into structure-based and ligand-based approaches, and its critical function in streamlining and accelerating drug discovery are all covered in this study. As CADD develops, protecting data privacy and integrating a variety of biological data become critical. There are still issues that need strong ethical frameworks and algorithm optimisation. CADD's predictive power is increased by combining machine learning and artificial intelligence, yet scalability issues and ethical issues still exist. Platforms like Open- Source Malaria serve as examples of worldwide initiatives and collaborative efforts that highlight the democratisation of medication research. Although there are ethical conundrums and accessibility issues to be resolved, the intersection of CADD and personalised medicine provides customised therapeutic treatments. Green chemistry, immersive technology, and quantum computing are examples of emerging technologies that have the potential to completely change CADD in the future. Rapid developments in CADD's trajectory foreshadow difficulties in guaranteeing accuracy, mitigating AI biases, and integrating sustainability indicators.In order to create a healthier, more promising future for drug development, this paper's conclusion emphasises the need of taking proactive steps in traversing the ethical, technical, and pedagogical boundaries of CADD.