Vol. 7, Issue 2, Part A (2025)

The intersection of Artificial Intelligence (AI) and 3D printing is revolutionizing the area of pharmaceutical sciences, with accurate formulation of drugs, optimal manufacture, and state-of-the-art personalized medicine. AI-based predictive modelling improves drug-excipient compatibility, optimizes controlled-release dosage forms, and minimizes formulation design complexity. AI enables real-time monitoring and adaptive control, which ensures consistency in quality, minimizes defects, and maximizes production scalability. In emerging drug delivery technologies, AI hastened advancements in nanotechnology formulation, intelligent polymers, and 3D printing with bioprinting that usher in controlled-release targeted drug delivery and regenerative medicine. A combination of deep learning, reinforcement learning, and generative AI enhances defect detection and intelligent optimization of print conditions and materials in 3D-printed nanodrug delivery systems. AI-driven quality control systems prevent regulatory nonconformity with FDA and EMA standards, and predictive maintenance processes minimize equipment downtime, optimizing drug manufacturing efficiency. Regulatory compliance, ethical issues, and data protection concerns persist despite the use of these technologies. Having strong AI validation systems, enhancing model interpretability, and standardizing AI-driven formulation forecasts are essential for full adoption. Future work would involve augmenting the predictive power of AI, augmenting AI-enabled bioprinting accuracy, and combining AI with 4D printing to achieve dynamic drug release systems. With ongoing cross-disciplinary interaction between AI experts, pharmaceutical scientists, and regulators, AI-powered 3D printing will transform the manufacture of drugs, making them safer, more effective, and highly customized drug therapies.