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Supporting Prospective Pregnancy Trials via Modeling and Simulation: Lessons From the Past and Recommendations for the Future.
- Source :
- Journal of Clinical Pharmacology; Jun2023 Supplement 1, Vol. 63, pS51-S61, 11p
- Publication Year :
- 2023
-
Abstract
- Despite the increasing awareness and guidance to support drug research and development in the pregnant population, there is still a high unmet medical need and off‐label use in the pregnant population for mainstream, acute, chronic, rare disease, and vaccination/prophylactic use. There are many obstacles to enrolling the pregnant population in a study, ranging from ethical considerations, the complexity of the pregnancy stages, postpartum, fetus–mother interaction, and drug transfer to breast milk during lactation and impacts on neonates. This review will outline the common challenges of incorporating physiological differences in the pregnant population and historical but noninformative practice in a past clinical trial in pregnant women that led to labeling difficulties. The recommendations of different modeling approaches, such as a population pharmacokinetic model, physiologically based pharmacokinetic modeling, model‐based meta‐analysis, and quantitative system pharmacology modeling, are presented with some examples. Finally, we outline the gaps in the medical need for the pregnant population by classifying various types of diseases and some considerations that exist to support the use of medicines in this area. Ideas on the potential framework to support clinical trials and collaboration examples are also presented that could also accelerate understanding of drug research and medicine/prophylactics/vaccines in the pregnant population. [ABSTRACT FROM AUTHOR]
- Subjects :
- CLINICAL trials
PREGNANCY
SIMULATION methods in education
Subjects
Details
- Language :
- English
- ISSN :
- 00912700
- Volume :
- 63
- Database :
- Complementary Index
- Journal :
- Journal of Clinical Pharmacology
- Publication Type :
- Academic Journal
- Accession number :
- 164352436
- Full Text :
- https://doi.org/10.1002/jcph.2284