The pharmaceutical manufacturing sector plays a crucial role in global healthcare through the production of life-saving medicines, necessitating stringent innovation, safety, and accuracy in its operations. This systematic review explores how advanced technologies, including artificial intelligence (AI), internet of things (IoT), blockchain, and automated laboratories can be integrated into pharmaceutical quality assurance processes to enhance product integrity and patient safety. Recent implementations demonstrate significant improvements: AI-powered visual inspection systems have reduced defect detection time by 60% while increasing accuracy by 25% compared to manual processes; IoT sensor networks in Pfizer's COVID-19 vaccine cold chain reduced temperature excursions by 87%; blockchain implementations by MediLedger reduced counterfeit drug incidents by 35% in pilot programs; and automated laboratory systems decreased testing turnaround times by 40% while reducing human error rates by 67%. Despite these benefits, implementation challenges persist, including regulatory compliance requirements, data privacy concerns, integration with legacy systems, and workforce retraining needs. This review uniquely examines the interdisciplinary synergies between these technologies, proposing an integrated framework that combines AI analytics with blockchain verification and IoT monitoring to create end-to-end pharmaceutical quality assurance systems with unprecedented levels of transparency and reliability.
Krishnan et al. (Sun,) studied this question.