GENERATIVE AI IN DRUG DISCOVERY: FROM MOLECULAR GENERATION TO POST MARKETING SURVEILLANCE

Kavitha R.*, Arundathi P., Hemalatha K. K. and Allen D.

ABSTRACT

Pharmaceutical industries experience revolutionary changes through artificial intelligence integration which transforms all pharmaceutical activities from discovery processes through post-market surveillance. Artificial intelligence algorithms use large amounts of data to discover new therapeutic targets and predict molecular interactions with highly accurate precision which leads to faster drug discovery processes. Through formulation optimization AI finds ideal excipients that prove effective for enhancing drug absorption as it determines compound stability better than manual testing methods. Intelligent automation in pharmaceutical manufacturing supports real-time process optimization and predictive maintaining while reducing waste which leads to high-quality cost-effective drug production. AI quality control systems built with predictive analytics and computer vision capabilities discover manufacturing deviations while checking that regulatory needs remain in compliance. AI-based pharmacovigilance operates as a transformative tool for post-market surveillance to discover drug side effects quickly and track treatment performance using big data analysis methods. The full potential of AI depends on resolving key hurdles that include clear algorithm processes as well as secure data and adaptable regulatory environments. The study shows how AI technologies transform pharmaceutical sciences by creating a smarter and more efficient patient-centered path for future pharmaceutical work.

Keywords: AI in Pharma, Intelligent Drug Discovery, Smart Formulation, AI-Driven Manufacturing, Predictive Quality Control.