Background Antihypertensives are the most commonly prescribed medications in pregnancy. However, pregnant women are often excluded from clinical trials due to ethical concerns, making it difficult to accurately dose, access efficacy and safety outcomes. Many physiological changes occur in pregnancy, for example, fluctuations in tissue volumes and organ blood flows, necessitating alternative or adaptive dosing regimens to ensure efficacious and safe drug delivery. PBPK modeling is a series of mathematical equations that estimate the pharmacokinetics of drugs in real time for dynamically changing life-stages such as pregnancy. These organ compartment concentration estimations help determine if the desired internal concentration is achieved with the external dosage. Characterizing drug interactions with the body’s physiological parameters is key to accurately describing the pharmacokinetics. We implemented drug and model-based sensitivity analysis of the PBPK model to determine key contributing factors to overall drug exposure. Results Nifedipine was used as an initial case study and represents a highly protein bound, single cytochrome-P450 metabolized drug. Physiological equations capturing pregnancy related changes were gathered from the literature and implemented in our PBPK pregnancy model. The normalized sensitivity coefficient (NSC) was calculated for various model input parameters using area under the curve (AUC) as the observed model output. Then parameters with the highest NSCs were used to estimate their individual contributions to the cumulative change in AUC during each pregnancy trimester. Intrinsic clearance consistently contributed to over 70% of changes; whereas body weight and hepatic blood flow contributions increased over trimesters (7%, 26%, 41% and 7%, 12%, 27% respectively). Conclusions Our method allows for the estimation of the extent each parameter contributes to pregnancy related pharmacokinetic changes. This could help prioritize parameterization of future PBPK models in data-sparse life-stages, thus improving prediction capabilities and sensitivity assessments of PBPK modeling for use as a regulatory tool.

Contribution of parameter sensitivities to the predictive potential of pregnancy-induced pharmacokinetic changes for antihypertensives using physiologically based pharmacokinetic (PBPK) modeling

ACS Fall 2020 Virtual Meeting

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.