Artificial Intelligence–Driven Product Lifecycle Optimization in Biopharmaceutical Manufacturing
Mahendra Deshmukh1 Dr Reetha Dinesh2
1IIBM Scholar, EUROPEAN INSTITUTE OF APPLIED SCIENCE AND MANAGEMENT (EIASM)
2Faculty & Thesis Guide, IIBM
Abstract
Artificial Intelligence (AI) is revolutionizing the biopharmaceutical industry by enabling data-driven decision-making, process automation, and predictive optimization across the product lifecycle. This research explores how AI-driven Product Lifecycle Management (PLM) transforms biopharmaceutical manufacturing by enhancing efficiency, compliance, and sustainability from R&D to commercialization. The study integrates theoretical frameworks with industry case analyses to demonstrate how machine learning (ML), digital twins, and big data analytics optimize formulation, scale-up, quality control, and market surveillance. It also identifies regulatory and ethical challenges associated with AI deployment in regulated environments. The paper concludes with a proposed AI-Integrated Biopharma Lifecycle Optimization Model, offering a roadmap for integrating AI, Quality by Design (QbD), and Good Manufacturing Practices (GMP) into a unified, future-ready PLM framework.
Keywords: Artificial Intelligence, Product Lifecycle Management, Biopharmaceutical Manufacturing, Quality by Design, Digital Twin, Predictive Analytics, Regulatory Compliance.
DOI link – https://doi.org/10.69758/GIMRJ/2510S01V13P005
Download