Abstract

AI: THE REVOLUTIONARY IMPACT ON DRUG DELIVERY SYSTEMS– A NEW ERA IN MEDICINE

Sakila Chandrika*, Dr. Avula Prameela Rani, Kanaparthi Meghana, Kommula Jyothsna, Sadapu Yamini and Velnati Kiran Kumar

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Abstract

Within the pharmaceutical and healthcare industries, this study examines how artificial intelligence (AI) might improve drug delivery systems (DDS). AI technologies are transforming drug formulation through the analysis of large datasets, including patient responses and physicochemical features. This allows formulations to be optimized for targeted distribution and controlled release. The ability to mimic pharmacokinetics and pharmacodynamics using predictive modeling greatly cuts down on the amount of time needed for experimental trials and speeds up the development process. Additionally, AI makes it easier to create intelligent DDS that adjust to physiological changes in real time, guaranteeing accurate drug release in certain settings, such tumors. AI is also essential for personalized medicine delivery, which allows treatment plans to be customized according to patient profiles, including lifestyle and genetic information. Despite these advancements, several challenges remain, including data privacy concerns, the need for large and high-quality datasets, model accuracy, and navigating a complex regulatory landscape. Strategies such as fostering data-sharing initiatives, engaging with regulatory bodies early in development, and investing in explainable AI are essential to overcoming these barriers. Overall, integrating AI into DDS holds immense potential for improving therapeutic outcomes and revolutionizing personalized medicine. By addressing existing challenges collaboratively among researchers, clinicians, and regulatory agencies, the future of drug delivery systems enriched by AI promises safer and more effective therapeutic solutions tailored to individual patient needs.

Keywords: Artificial Intelligence, Drug Delivery Systems, Smart Drug Delivery, Predictive Modelling, Personalized Medicine, Real-Time Monitoring, Nanoparticles, Drug Formulation Optimization.