Grant: Project Grant

Pregnant women are often excluded from clinical trials due to safety concerns, leaving a critical gap in understanding how medications prescribed during pregnancy may affect both the mother and fetus. As a result, many pregnant women have limited access to safe and effective treatments, especially for conditions like preeclampsia, a life-threatening pregnancy complication. Our research aims to bridge this gap by combining cutting-edge lab-based models of the placenta with artificial intelligence (AI) to improve drug safety and accelerate the discovery of new treatments for pregnancy-related conditions. We have developed 3D placenta models that mimic key functions of the human placenta, enabling us to study drug transfer between mother and baby and the progression of pregnancy complications like preeclampsia. Simultaneously, we have created machine learning (ML) models that can predict which drugs cross the placenta and identify potential treatment targets for preeclampsia. However, lab models and AI alone cannot fully address the complexities of pregnancy-related drug development. By integrating these two approaches, we can enhance the accuracy of drug safety predictions, refine AI-discovered drug candidates, and improve treatment options for pregnant women. With support from experts in placental biology, machine learning, and molecular research, as well as industry collaborators, we aim to achieve two major goals: (1) predict how drugs move across the placenta and (2) develop first-in-class drug candidates for preeclampsia. To do this, we will validate our placenta models with real drug data, enhance our AI models to improve drug prediction, and test new drug candidates identified through AI to see if they can effectively treat preeclampsia. This project represents a major step forward in developing safer medications for pregnant women, leading to better maternal and fetal health.