Artificial Intelligence in Precision Drug Delivery: From Machine Learning to Intelligent Nanomedicine

Abstract

Artificial intelligence (AI) is rapidly transforming pharmaceutical research by enabling more precise, efficient, and patient-centered drug delivery strategies. The integration of machine learning, deep learning, and advanced computational techniques with nanotechnology has opened new opportunities for designing intelligent drug delivery systems capable of improving therapeutic outcomes while reducing adverse effects. AI-driven approaches support various stages of pharmaceutical development, including formulation optimization, prediction of drug-carrier interactions, controlled drug release, personalized dosing, and real-time therapeutic monitoring. These technologies also facilitate the development of advanced nanocarriers, targeted drug delivery platforms, and smart nanomedicine for complex diseases such as cancer and neurological disorders.

This review provides a comprehensive overview of recent advances in AI-assisted precision drug delivery, highlighting its applications in nanoparticle engineering, intelligent nanomedicine, pharmaceutical manufacturing, quality control, personalized medicine, and AI-enabled nanorobotics. The review further discusses current limitations related to data availability, algorithm transparency, regulatory considerations, ethical challenges, and clinical implementation. Finally, emerging trends such as explainable artificial intelligence (XAI), digital twins, generative AI, and autonomous nanotherapeutic systems are explored as promising directions for the next generation of precision medicine. Collectively, AI-driven technologies have the potential to reshape drug delivery by improving formulation design, enhancing therapeutic precision, accelerating pharmaceutical innovation, and supporting the transition toward personalized healthcare.