Enhancing inclusivity in clinical trials: Model‐informed drug development for pregnant individuals in the era of personalized medicine.

This article discusses the lack of representation of pregnant individuals in clinical trials and drug development, resulting in a lack of safety and efficacy data for this population. It emphasizes the potential of model-informed drug development (MIDD) tools and the importance of collaboration between pharmaceutical companies and regulatory agencies. The article explores various MIDD methods, such as PBPK modeling, toxicology modeling, and QSP, and their applications in addressing the challenges faced in drug development for pregnant individuals. It also mentions the use of real-world data and machine learning to study the effects of drugs during pregnancy. The article calls for inclusivity in clinical trials and drug development for pregnant individuals and highlights the need for postmarketing studies to gather essential information on the safety of medicines used during pregnancy. It also suggests the use of machine learning and real-world data to identify potentially unsafe drugs for the fetus. Overall, the article emphasizes the need to bridge the knowledge gap and improve access to safe and effective therapies for pregnant individuals. [Extracted from the article]