Revolutionizing -Drug Discovery with AI

Drug development through Artificial Intelligence (AI) creates fundamental changes in the pharmaceutical industry by boosting both productivities along with precision and economic performance. The current drug development framework requires several expensive and lengthy years at billions of dollars to successfully deliver a new pharmaceutical to markets. New pharmaceutical technologies that include machine learning (ML) deep learning and natural language processing (NLP) continue to scale up their use within various pharmaceutical stages to quicken the drug development process. In preclinical and clinical development, AI facilitates efficient trial design, patient recruitment, and biomarker discovery. Analytics models predict how drugs will work in patients which helps scientists to develop optimal dosing schedules that lead to decreased trial failures. Post-market surveillance receives improvement through Artificial Intelligence implementation which provides superior analysis of real-world evidence and pharmacovigilance capabilities. AI operational transformation encounters limitations from existing challenges that combine poor data quality together with difficult model interpretation as well as regulatory approval requirements. The resolution of these problems needs combined work between universities academia, industrial organizations, and regulatory groups to create ethical guidelines while developing better information integration systems