By Jiawei Wang and Mo Maniruzzaman
Pharmaceutical Engineering and 3D Printing (PharmE3D) Lab, Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin
Artificial Intelligence (AI) and Machine Learning (ML) have recently attracted tremendous research attention in pharmaceutical product development and emerged as powerful tools to improve drug manufacturing efficiency and process optimization and monitoring. We provide an overview of the recent advancement of AI/ML on the related fields of pharmaceutical drug delivery, use of innovative nanomedicine technologies, and applications in emerging 3D printed and bioprinted drug delivery systems. Despite some challenges i.e., lack of large, standardized datasets, application of AI/ML models will help streamline the development of efficient drug delivery systems with programmable pharmaceutical attributes, representing a new paradigm for digital pharmaceutical science.
Part One in this article series is available.