Search

The article discusses the challenges of drug exposure to fetuses and infants during pregnancy and lactation, leading to the exclusion of pregnant and lactating women from clinical trials. Regulatory initiatives like the Diversity Action Plan and E21 Efficacy Guidelines aim to increase inclusion in clinical studies. Pharmacometrics and systems pharmacology play a crucial role in making studies more inclusive and optimizing drug therapy for pregnant and lactating women. The article highlights the importance of robust data on drug exposure, non-clinical safety data, and quantitative applications to inform drug therapy decisions for pregnant and lactating women. [Extracted from the article]

The article discusses the underutilization of pharmacometrics in obstetrics and maternal-fetal medicine research, despite the widespread use of medications during pregnancy. It highlights the importance of leveraging mathematical models like PBPK and PopPK approaches to predict maternal and fetal drug exposure, optimize therapeutic regimens, and address drug safety concerns. The text also emphasizes the need for advanced modeling approaches to improve drug dosing, efficacy, and safety profiles during pregnancy, as well as the challenges and barriers hindering the implementation of pharmacometrics in obstetrics. Overall, the article underscores the potential of pharmacometrics to enhance personalized drug therapy for pregnant women and improve outcomes for both mother and baby. [Extracted from the article]

The article discusses the challenges of using medicines during pregnancy due to limited clinical data and the need for a clinical pharmacology extrapolation framework to support pregnancy drug development strategies. It highlights the regulatory landscape, the impact of pregnancy-related physiological changes on drug exposure, and the importance of including pregnant women in clinical trials. The article emphasizes the need for an extrapolation approach to generate data in pregnancy, focusing on mother and fetal safety management, study design, and labeling updates. Additionally, it suggests using model-informed drug development (MIDD) approaches, such as physiologically-based pharmacokinetic (PBPK) modeling, to predict drug exposure and inform dosing decisions during pregnancy. [Extracted from the article]

The article discusses the underrepresentation of pregnant individuals in clinical trials and drug development programs, leading to a lack of safety and efficacy data for this population. It highlights the importance of model‐informed drug development (MIDD) tools and early engagement between pharmaceutical companies and regulatory agencies. The use of physiologically-based pharmacokinetic (PBPK) modeling, toxicology modeling, quantitative systems pharmacology, real-world data, and machine learning are proposed as methods to enhance drug development for pregnant individuals. Efforts to improve inclusivity in clinical trials for pregnant individuals are ongoing, with regulatory agencies emphasizing the need for postmarketing required (PMR) studies to gather essential information. [Extracted from the article]

It is critical to understand the impact of significant physiological changes during pregnancy on the extent of maternal and fetal drug exposure. Fostemsavir (FTR) is a prodrug of temsavir (TMR) and is approved in combination with other antiretrovirals for multi‐drug‐resistant human immunodeficiency virus (HIV) infections. This physiologically based pharmacokinetic model (PBPK) study was used to estimate TMR PK in pregnant populations during each trimester of pregnancy to inform FTR dosing. A PBPK model was developed and validated for TMR using PK data collected following intravenous TMR and oral FTR dosing (immediate‐release and extended‐release tablets) in healthy volunteers. Predicted TMR concentration–time profiles accurately predicted the reported clinical data and variability in healthy (dense data) and pregnant (sparse data) populations. Predicted versus observed TMR geometric mean (CV%) clearance following intravenous administration was 18.01 (29) versus 17 (21) (L/h). Predicted versus observed TMR AUC0–inf (ng.h/mL) in healthy volunteers following FTR administration of the extended‐release tablet were 9542 (66) versus 7339 (33). The validated TMR PBPK model was then applied to predict TMR PK in a population of pregnant individuals during each trimester. Simulations showed TMR AUC in pregnant individuals receiving FTR 600 mg twice daily was decreased by 25% and 38% in the second and third trimesters, respectively. However, TMR exposure remained within the range observed in nonpregnant adults with no need for dose adjustment. The current PBPK model can also be applied for the prediction of local tissue concentrations and drug–drug interactions in pregnancy. [ABSTRACT FROM AUTHOR]

We have previously developed a maternal‐fetal physiologically‐based pharmacokinetic (m‐f PBPK) model to dynamically predict (and verify) fetal‐maternal exposure to drugs that passively diffuse across the placenta. Here, we extended the application of this model to dynamically predict fetal exposure to drugs which are effluxed by placental P‐glycoprotein, namely the antenatal corticosteroids (ACS; dexamethasone [DEX], and betamethasone [BET]). To do so, we estimated both the placental P‐gp mediated efflux clearance (CL) and the passive diffusion CL of the ACS. The efficacy and toxicity of the currently used maternal ACS dosing regimens to prevent neonatal respiratory distress syndrome could be improved by altering their dosing regimens. Therefore, to illustrate the utility of our m‐f PBPK model, we used it to design alternative dosing regimens of DEX and BET that could potentially improve their efficacy and reduce their toxicity. The redesigned dosing regimens are convenient to administer, maintain maternal‐fetal exposure (area under the concentration‐time curve [AUC]) or maximum plasma concentration (Cmax) or both (DEX and BET) or minimize maternal exposure while maintaining fetal drug plasma concentrations above the minimum therapeutic threshold of 1 ng/ml for 48 h (BET only; based on efficacy data in sheep). To our knowledge, this is the first study to dynamically predict fetal plasma concentrations of placental P‐gp effluxed drugs. Our approach and our m‐f PBPK model could be used in the future to predict maternal‐fetal exposure to any drug and to design alternative dosing regimens of the drug. [ABSTRACT FROM AUTHOR]