From Bench to Bedside: Bioanalysis and Translational Science
Sruthi Sarvepalli, MS, PhD (she/her/hers)
Sr. Manager
St. John's University
newark, New Jersey
This presentation delves into the application of AI in dose and dosage form selection within drug development. The session begins by discussing the challenges traditionally associated with dose selection, including variable patient responses and drug efficacy and also requirement of several trials involving multiple participants for dose range estimation. To address these challenges AI-driven approaches are presented as transformative, offering solutions through predictive algorithms and real-time data analysis. The PRECISE CURATE.AI trial is highlighted as a key case study, where AI-assisted dosing reduced the average prescribed dose of capecitabine by 20% in cancer patients, while maintaining efficacy. This AI technology is also being explored in other therapeutic areas, such as diabetes and hypertension, demonstrating AI's broad potential.
The presentation further explores AI's contributions to dosage form selection, where predictive algorithms assist in selecting materials for drug delivery systems and optimizing formulations. This presentation also emphasizes that these advancements come with challenges, including data quality, bias in AI models, and ethical concerns surrounding data ownership. Through rigorous validation, continuous monitoring, and collaborative efforts we can ensure AI applications in drug development are ethical, safe, and effective. By harnessing AI, the pharmaceutical industry can potentially enhance patient outcomes while reducing costs and streamlining the drug development process.