Artificial Intelligence in Drug Discovery and Development

Abstract

Artificial Intelligence (AI) is rapidly transforming drug discovery and development by improving efficiency, accuracy, and speed. Traditional drug development is a lengthy and costly process that may take 10-15 years and require billions of dollars to bring a single drug to market. AI helps overcome these limitations by analysing large biological datasets, predicting outcomes, and supporting decision- making throughout different stages of drug development. Machine learning and generative AI models assist in target identification, de novo drug design, virtual screening, lead optimisation, and prediction of ADEMT properties, thereby reducing late- stage failures and improving overall success rates. AI also plays an important role in clinical trial optimisation through better patient selection, real-time monitoring, and outcome prediction. Growing investments and high adoption rates in the pharmaceutical industry highlight the expanding AI market and its economic impact. Despite its advantages, challenges such as data quality issues, high implementation costs, lack of interpretability, ethical concerns, and regulatory complexities remain significant. In India, AI-based drug discovery is guided by CDSCO regulations, ICMR ethical guidelines, NDCTR 2019, and the Digital Personal Data Protection Act, 2023 to ensure safety and compliance. Overall, AI has strong potential to revolutionize pharmaceutical research by accelerating innovation, reducing costs, and enabling personalized medicine.

Keywords: Artificial Intelligence (AI), Drug Discovery, Molecular Design, validation.