Development, Testing, Parameterisation and Calibration of a Human PBPK Model for the Plasticiser, Di-(2-propylheptyl) Phthalate (DPHP) Using in Silico, in vitro and Human Biomonitoring Data

Abstract

A physiologically based pharmacokinetic model for Di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the biokinetics in humans after single oral doses. The model was parameterized with in vitro and in silico derived parameters and uncertainty and sensitivity analysis was used during the model development process to assess structure, biological plausibility and behaviour prior to simulation and analysis of human biological monitoring data. To provide possible explanations for some of the counter-intuitive behaviour of the biological monitoring data the model included a simple lymphatic uptake process for DPHP and enterohepatic recirculation (EHR) for DPHP and the mono ester metabolite mono-(2-propylheptyl) phthalate (MPHP). The model was used to simultaneously simulate the concentration-time profiles of blood DPHP, MPHP and the urinary excretion of two metabolites, mono-(2-propyl-6-hydroxyheptyl) phthalate (OH-MPHP) and mono-(2-propyl-6-carboxyhexyl) phthalate (cx-MPHP). The availability of blood and urine measurements permitted a more robust qualitative and quantitative investigation of the importance of EHR and lymphatic uptake. Satisfactory prediction of blood DPHP and urinary metabolites was obtained whereas blood MPHP was less satisfactory. However, the delayed peak of DPHP concentration relative to MPHP in blood and second order metabolites in urine could be explained as a result of three processes: 1) DPHP entering the systemic circulation from the lymph, 2) rapid and very high protein binding and 3) the efficiency of the liver in removing DPHP absorbed via the hepatic route. The use of sensitivity analysis is considered important in the evaluation of uncertainty around in vitro and in silico derived parameters. By quantifying their impact on model output sufficient confidence in the use of a model should be afforded. This approach could expand the use of PBPK models since parameterization with in silico techniques allows for rapid model development. This in turn could assist in reducing the use of animals in toxicological evaluations by enhancing the utility of “read across” techniques.

Derivation of a Human In Vivo Benchmark Dose for Bisphenol A from ToxCast In Vitro Concentration Response Data Using a Computational Workflow for Probabilistic Quantitative In Vitro to In Vivo Extrapolation

“…The biokinetics of bisphenol A following single oral doses were described using a PBK model previously developed for the plasticizer DPHP (McNally et al, 2021), with adaptions to model structure made, as necessary. The final model described entry of BPA through ingestion with absorption of BPA from the stomach and intestines and a simple model of the lymphatic system describing uptake of BPA via the lacteals in the small intestine and entering venous blood after bypassing the liver.…”

“…The final structure of the model described above followed the iterative model development process (incorporating uncertainty and sensitivity analysis) documented in McNally et al (2021). Table 1 lists a glossary of parameters name and abbreviations.…”

“…The in vitro metabolic rate constants for the biotransformation of BPA to BPAG and BPA to BPAS were taken from (Mazur et al, 2010) and scaled to whole liver and gut using the microsomal protein yield (Pacifici et al, 1988;Soars et al, 2002) and mass of the liver or gut. Default values for uptake and elimination rate parameters were based on corresponding terms in McNally et al (2021) and subsequently refined through tuning parameters to better represent the trends in data from the human volunteer study reported in Thayer et al (2015). The default model assumed 80% of the administered BPA was absorbed through the hepatic route, with a further 5% absorbed through the lymphatic route with the complementary 15% passing through unabsorbed (Thayer et al, 2015).…”

Development, testing, parameterisation, and calibration of a human PBPK model for the plasticiser, di-(2-ethylhexyl) terephthalate (DEHTP) using in silico, in vitro and human biomonitoring data

“…The aim of this study was to develop a PBPK model for DEHTP based on the model structure for di-(2-propylheptyl) phthalate (DPHP) described previously, with a minor modification, to interpret the venous blood concentrations and urinary excretion of the metabolites in exposed people ( McNally et al, 2021 ). We use the model to understand the metabolism and urinary excretion kinetics of DEHTP following a single oral dose of 50 mg DEHTP to three male volunteers in controlled study ( Lessmann et al, 2016 ).…”

The Role of “Physiologically Based Pharmacokinetic Model (PBPK)” New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment

“…For instance, a PBPK model was developed for DPHP using lymphatic uptake and EHR to predict the plasma and urine concentration, including the delayed peak. The author explained that the inclusion of three processes (systemic circulation to lymph movement, high protein binding and efflux of absorbed chemical from liver via hepatic route) were able to explain the data [ 26 ]. The important point here is that, for kinetic modeling, it is imperative to understand the experimental data and gain mechanistic knowledge before diving into the calibration and optimization of the model.…”