Re. Aims G3 and G5
Contact: Anup Challa, Vanderbilt (firstname.lastname@example.org)
Assessment of the drug safety in pregnancy information necessary for new drug applications (NDAs) remains severely underpowered due to a lack of inclusion of pregnant patients in randomized, controlled drug trials (RCTs) for ethical reasons and the subsequent dearth of knowledge on the effects of many agents on the human maternal-fetal interface. Therefore, most information on drug labels about placental permeability (and its associated risk of fetal harm) is generated from preclinical rodent models with poor reproducibility in human patients. Our group is working with NCATS and FDA to develop reproducible approaches for synthesizing clinical and pre-clinical evidence to enhance knowledge on the safety of drug products in pregnancy. In the pilot stages of this project, we have developed a tool that repurposes electronic health record data from routine primary care encounters to identify drugs with unclear safety signals in pregnancy that appear neuroteratognic; we are now screening our clinical signals, in series, through packagebale models of the human placenta and the fetal brain to generate more physiologically accurate data on the teratogenic potential of common-use drugs. We are creating our approach to drug screening to accomodate the integration of real-world evidence (RWE) from human systems in the assessment of the pregnancy sections of NDAs. Indeed, the human placenta is a key, intermediate model element for generating accurate knowledge on the risks of commercializable candidates to vulnerable populations, but its role in this space is often unconsidered or minimized.
Historically, NIH has not funded data harmonization initiatives. However, to mitigate our inability to systematically study drug response in pregnancy through RCTs--and to assess the effects of drug candidates on sensitive organs like the human placenta in real-time--RWE initiatives provide an adjacent alternative. Successfully executing and validating RWE studies of pregnancy, however, requires support for the largescale harmonization of clinical and preclinical data--not just their generation. To sustain Aims G3 and G5 of the HPP strategic plan, NICHD may consider more explicit support of multi-evidentiary data harmonization and platform study approaches. If it is interested in creating new, innovative programs on the maternal-fetal interface, NICHD may also consider the role of RWE in the translation of biomedical discovery in areas, like pregnancy, where traditional human experiments are often infeasible.