This grant seeks to develop AI/ML models using real-world data to monitor clinical outcomes when patients switch between complex generics and brand-name drugs.
This grant aims to improve prediction of food/drug interactions for high-risk oral drugs by using a lab model that mimics the gut to assess drug performance.
This grant aims to create PBPK models for long-acting injectable suspensions and implants, predicting drug release by linking formulation attributes to in-vivo performance.
This grant funds innovative research to develop or improve broadly applicable models, materials, and methodologies for studying multiple body systems or diseases relevant to human health, excluding single disease or system studies.
This grant supports developing non-invasive imaging to measure how topical drugs penetrate the skin, aiming for a new way to test topical drug bioequivalence.