Artificial Intelligence, Machine Learning & Digital Drug Delivery

Artificial intelligence and machine learning are increasingly influencing pharmaceutical formulation, delivery-system design, drug targeting, and clinical decision-making. This track explores how computational technologies can accelerate the discovery and optimization of drug delivery platforms. Sessions will examine AI-assisted formulation development, predictive modeling, pharmacokinetic analysis, drug-release prediction, nanoparticle design, patient stratification, and delivery-route selection. Researchers will discuss how large datasets can be used to identify relationships between formulation parameters and therapeutic outcomes. Digital twins, computational simulations, automated experimentation, and data-driven optimization will also be explored. Particular attention will be given to integrating AI with precision medicine and personalized drug delivery. The track will address challenges involving data quality, model validation, interpretability, regulatory acceptance, and responsible use of artificial intelligence. By connecting pharmaceutical scientists, data scientists, engineers, and clinicians, the sessions will demonstrate how computational approaches can reduce development timelines, improve formulation performance, and support the creation of smarter and more individualized drug delivery systems.

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