Harnessing the Power of Artificial Intelligence for Pharmaceutics: From Pharmacokinetics Prediction, Formulation, to Manufacturing

Abstract Drug design and optimization remain highly complex processes that must account for pharmacodynamics, pharmacokinetics, toxicity, and manufacturability. Conventional experimental and empirical approaches often struggle to accurately predict pharmacokinetic behavior and therapeutic efficacy, contributing to high attrition rates in late-stage clinical trials. In drug delivery, imprecise targeting and suboptimal formulations can limit therapeutic effectiveness and increase the risk of adverse effects. Artificial intelligence (AI)-driven approaches have demonstrated significant potential in optimizing dosage forms, formulations, and drug bioavailability. Moreover, AI is enabling breakthroughs in pharmaceutical manufacturing by facilitating process optimization and innovation in emerging technologies such as three-dimensional drug printing, microfluidics, and electrospinning. Overall, the integration of AI with advanced pharmaceutical technologies offers transformative opportunities to accelerate drug research and development, enabling more efficient, precise, and personalized pharmaceutical solutions. In this article, we reviewed the application of AI and other advanced technologies in the pharmaceutical industry, focusing on predictions of drug solubility and pharmacokinetics, dosage form design, formulation optimization, bioavailability improvement, and new drug manufacturing technology. We also discussed the opportunities and challenges of AI in the field to fully realize its benefits in further research.