Cargando…

Microfluidic technology and simulation models in studying pharmacokinetics during pregnancy

Introduction: Preterm birth rates and maternal and neonatal mortality remain concerning global health issues, necessitating improved strategies for testing therapeutic compounds during pregnancy. Current 2D or 3D cell models and animal models often fail to provide data that can effectively translate...

Descripción completa

Detalles Bibliográficos
Autores principales: Kammala, Ananth K., Richardson, Lauren S., Radnaa, Enkhtuya, Han, Arum, Menon, Ramkumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469630/
https://www.ncbi.nlm.nih.gov/pubmed/37663251
http://dx.doi.org/10.3389/fphar.2023.1241815
Descripción
Sumario:Introduction: Preterm birth rates and maternal and neonatal mortality remain concerning global health issues, necessitating improved strategies for testing therapeutic compounds during pregnancy. Current 2D or 3D cell models and animal models often fail to provide data that can effectively translate into clinical trials, leading to pregnant women being excluded from drug development considerations and clinical studies. To address this limitation, we explored the utility of in silico simulation modeling and microfluidic-based organ-on-a-chip platforms to assess potential interventional agents. Methods: We developed a multi-organ feto-maternal interface on-chip (FMi-PLA-OOC) utilizing microfluidic channels to maintain intercellular interactions among seven different cell types (fetal membrane-decidua-placenta). This platform enabled the investigation of drug pharmacokinetics in vitro. Pravastatin, a model drug known for its efficacy in reducing oxidative stress and inflammation during pregnancy and currently in clinical trials, was used to test its transfer rate across both feto-maternal interfaces. The data obtained from FMi-PLA-OOC were compared with existing data from in vivo animal models and ex vivo placenta perfusion models. Additionally, we employed mechanistically based simulation software (Gastroplus®) to predict pravastatin pharmacokinetics in pregnant subjects based on validated nonpregnant drug data. Results: Pravastatin transfer across the FMi-PLA-OOC and predicted pharmacokinetics in the in silico models were found to be similar, approximately 18%. In contrast, animal models showed supraphysiologic drug accumulation in the amniotic fluid, reaching approximately 33%. Discussion: The results from this study suggest that the FMi-PLA-OOC and in silico models can serve as alternative methods for studying drug pharmacokinetics during pregnancy, providing valuable insights into drug transport and metabolism across the placenta and fetal membranes. These advanced platforms offer promising opportunities for safe, reliable, and faster testing of therapeutic compounds, potentially reducing the number of pregnant women referred to as “therapeutic orphans” due to the lack of consideration in drug development and clinical trials. By bridging the gap between preclinical studies and clinical trials, these approaches hold great promise in improving maternal and neonatal health outcomes.