World Journal of
Pharmaceutical and Life Sciences

THE ROLE OF ARTIFICIAL INTELLIGENCE IN ADVANCING TRANSDERMAL DRUG DELIVERY SYSTEMS

*Ayalasomayajula Lakshmi Usha, Jagadeesh Panda, J. Meghana, B. Arthi Saranya, K. Karthik Sreeram, M. Chandralekha, P. Parimala Rani

ABSTRACT

Transdermal drug delivery systems (TDDS) are gaining significant attention in pharmaceutical science for their ability to deliver drugs in a controlled, non-invasive manner, improving bioavailability and patient adherence while avoiding first-pass metabolism. However, TDDS are limited by challenges such as the skin’s permeability barrier, particularly the stratum corneum, and the need for optimized formulations. Factors such as skin type, hydration levels, and age further complicate the development of effective systems. Designing efficient TDDS is complex and requires careful consideration of drug–skin interactions, excipient selection, and formulation stability. Artificial intelligence (AI) is emerging as a powerful tool to address these challenges. By utilizing techniques such as machine learning and predictive modeling, AI can accurately forecast drug permeation, optimize formulation parameters, and assist in designing novel carriers with enhanced performance. Personalized transdermal drug delivery systems are increasingly being developed to align with individual patient profiles, thereby enhancing therapeutic precision and efficacy. Innovations such as sensor-integrated patches enable dynamic modulation of drug release in response to real-time physiological feedback, ensuring optimal therapeutic outcomes. AI also streamlines the pharmaceutical workflow—from disease diagnosis to predicting drug penetration and distribution within skin layers—thus facilitating the development of efficient and targeted formulations. This review highlights the impact of AI in TDDS and discusses applications of advanced computational models including Deep Neural Networks (DNN), Artificial Neural Networks (ANN), BIOSIM, COMSOL Multiphysics, K-Nearest Neighbours (KNN), and Support Vector Machines (SVM). These technologies have the potential to overcome current limitations in transdermal delivery, offering innovative solutions for both dermatological and systemic conditions, and ultimately improving patient care through advanced drug delivery strategies.

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