Leveraging Physiological Data from Literature into a Pharmacokinetic Model to Support Informative Clinical Study Design in Pregnant Women

Abstract

Physiological changes during pregnancy can effect pharmacokinetic (PK) parameters, which may lead to altered dose requirements. We aimed to leverage literature-based physiological changes during pregnancy into a PK model and compare its performance to a published reference model in pregnant women and to use the literature-based model to determine informative PK sampling times for a clinical study that aims to quantify the PK of enoxaparin throughout pregnancy. Changes in total body water (BW) and creatinine clearance (CRCL) during pregnancy were described using regression models. BW and CRCL were linked to a PK model of enoxaparin in non-pregnant women. Performance of the literature-based PK model was compared to a previously published empirical reference model. D-optimal sampling times were determined and evaluated for literature-based and reference models. The literature-based model adequately predicted anti-Xa plasma concentrations when compared to reference model predictions. An informative sampling design was successfully developed, with parameters expected with good precision (RSE < 36.4%). A literature-based model describing enoxaparin PK during pregnancy was developed and evaluated. The modelling framework could be used to support development of informative designs in pregnancy when prior models are unavailable.