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 seeks to develop AI/ML models using real-world data to monitor clinical outcomes when patients switch between complex generics and brand-name drugs.
NIH will fund investigator-initiated multi-site or decentralized clinical trials relevant to its mission, supporting planning and implementation over up to 7 years using a milestone-driven UG3/UH3 grant mechanism.
This upcoming NIH grant will fund innovative preclinical research to develop new methods or agents that selectively target "undruggable" molecules involved in difficult-to-treat human diseases.