Jahnavi Vellanki, Industry Researcher, Brownsburg, IN 46112, USA
Artificial Intelligence and Machine Learning are revolutionizing pharmaceutical lifecycle management, maximizing drug discovery, clinical trials, manufacturing, supply chain, regulatory compliance, and pharmacovigilance. Predictive analytics by leveraging AI improve the selection of drug candidates, reduce late-stage failures, and enhance clinical research capabilities. AI-driven intelligent manufacturing gained the achievement in real-time quality assurance, predictive maintenance, process optimization, and AI-fueled supply chain management streamlines accurate forecasting and inventory management. AI enhances the performance of compliance with regulations using automated documentation, detection of adverse drug reactions, and real-time verification. AI-assisted post-market surveillance deploy the advantage of safety monitoring and risk detection. While these advances are promising, issues of data privacy, algorithmic bias, ethics, and regulatory hurdles continue to hamper progress. Explainable AI (XAI) for transparency, integration of blockchain with AI for secure data handling, and AI-based personalized medicine for patient-tailored treatment are research areas where future efforts are needed. Conquering these challenges will make it possible for AI to lead innovation, efficiency, and ethical development in pharmaceutical lifecycle management.
Artificial Intelligence, Machine Learning, Drug Discovery, Regulatory Compliance, Pharmacovigilance, Personalized Medicine.
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