AI-powered transformation of pharmaceutical 3D printing: enhancing precision, efficiency, and personalization

Cloud computing technologies and Internet of Things systems and artificial intelligence (AI) have brought major changes to pharmaceutical 3D printing by promoting new opportunities in designing drugs and manufacturing and personalized medicine delivery. Algorithmic processing through AI improves the modeling of drugs for computation and predicts formulation stability and detects real-time defects in printed dosage forms while boosting operational efficiency. Machine learning systems help optimize printing settings to achieve consistent results and reduce material waste across production batches. The use of artificial intelligence in pharmaceutical 3D printing needs overcoming three major challenges: regulatory hurdles, standards, and data privacy concerns. To overcome these problems, regulatory authorities, pharmaceutical researchers, and technology companies must collaborate to set standards for pharmaceutical data protection as well as compliance frameworks. AI-powered software solutions employ predictive analytics to do quality control in real time, reducing the amount of manufacturing failures. This article discusses regulatory obstacles, data security issues, and standards. Furthermore, identify research gaps so that academics can continue to work on AI-based 3D printing models. The application of AI enables pharmaceutical companies to boost operational efficiency and precision capabilities as well as innovative developments that lead to advanced drug therapies adjusted for individual patients alongside contemporary production methods.