A human PBPK model for ethanol describing inhibition of gastric motility

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science

A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.

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

Introduction: A physiologically based biokinetic model for di (2-ethylhexyl) adipate (DEHA) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHA following a single oral dosage of 50 mg to two male and two female volunteers. Methods: The model was parameterized using in vitro and in silico methods such as, measured intrinsic hepatic clearance scaled from in vitro to in vivo and algorithmically predicted parameters such as plasma unbound fraction and tissue:blood partition coefficients (PCs). Calibration of the DEHA model was achieved using concentrations of specific downstream metabolites of DEHA excreted in urine. The total fractions of ingested DEHA eliminated as specific metabolites were estimated and were sufficient for interpreting the human biomonitoring data. Results: The specific metabolites of DEHA, mono-2-ethyl-5-hydroxyhexyl adipate (5OH-MEHA), mono-2-ethyl-5-oxohexyl adipate (5oxo-MEHA), mono-5-carboxy-2-ethylpentyl adipate (5cx-MEPA) only accounted for ∼0.45% of the ingested DEHA. Importantly, the measurements of adipic acid, a non-specific metabolite of DEHA, proved to be important in model calibration. Discussion: The very prominent trends in the urinary excretion of the metabolites, 5cx-MEPA and 5OH-MEHA allowed the important absorption mechanisms of DEHA to be modelled. The model should be useful for the study of exposure to DEHA of the general human population.

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

A physiologically based pharmacokinetic model for di-(2-ethylhexyl) terephthalate (DEHTP) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHTP following a single oral dose of 50 mg to three male volunteers. In vitro and in silico methods were used to generate parameters for the model. For example, measured intrinsic hepatic clearance scaled from in vitro to in vivo and plasma unbound fraction and tissue:blood partition coefficients (PCs) were predicted algorithmically. Whereas the development and calibration of the DPHP model was based upon two data streams, blood concentrations of parent chemical and first metabolite and the urinary excretion of metabolites, the model for DEHTP was calibrated against a single data stream, the urinary excretion of metabolites. Despite the model form and structure being identical significant quantitative differences in lymphatic uptake between the models were observed. In contrast to DPHP the fraction of ingested DEHTP entering lymphatic circulation was much greater and of a similar magnitude to that entering the liver with evidence for the dual uptake mechanisms discernible in the urinary excretion data. Further, the absolute amounts absorbed by the study participants, were much higher for DEHTP relative to DPHP. The in silico algorithm for predicting protein binding performed poorly with an error of more than two orders of magnitude. The extent of plasma protein binding has important implications for the persistence of parent chemical in venous blood-inferences on the behaviour of this class of highly lipophilic chemicals, based on calculations of chemical properties, should be made with extreme caution. Attempting read across for this class of highly lipophilic chemicals should be undertaken with caution since basic adjustments to PCs and metabolism parameters would be insufficient, even when the structure of the model itself is appropriate. Therefore, validation of a model parameterized entirely with in vitro and in silico derived parameters would need to be calibrated against several human biomonitoring data streams to constitute a data rich source chemical to afford confidence for future evaluations of other similar chemicals using the read-across approach.

Development of a Physiologically Based Pharmacokinetic Model for Prediction of Ethanol Concentration-Time Profile in Different Organs

AIMS

A physiologically based pharmacokinetic (PBPK) modeling approach was used to simulate the concentration-time profile of ethanol (EtOH) in stomach, duodenum, plasma and other tissues upon consumption of beer and whiskey under fasted and fed conditions.

METHODS

A full PBPK model was developed for EtOH using the advanced dissolution, absorption and metabolism (ADAM) model fully integrated into the Simcyp Simulator® 15 (Simcyp Ltd., Sheffield, UK). The prediction performance of the developed model was verified and the EtOH concentration-time profile in different organs was predicted.

RESULTS

Simcyp simulation showed ≤ 2-fold difference in values of EtOH area under the concentration-time curve (AUC) in stomach and duodenum as compared to the observed values. Moreover, the simulated EtOH maximum concentration (Cmax), time to reach Cmax (Tmax) and AUC in plasma were comparable to the observed values. We showed that liver is exposed to the highest EtOH concentration, faster than other organs (Cmax = 839.50 mg/L and Tmax = 0.53 h), while brain exposure of EtOH (AUC = 1139.43 mg·h/L) is the highest among all other organs. Sensitivity analyses (SAs) showed direct proportion of EtOH rate and extent of absorption with administered EtOH dose and inverse relationship with gastric emptying time (GE) and steady-state volume of distribution (Vss).

CONCLUSIONS

The current PBPK model approach might help with designing in vitro experiments in the area of alcohol organ damage or alcohol-drug interaction studies.

Development, Testing, Parameterization, and Calibration of a Human Physiologically Based Pharmacokinetic Model for the Plasticizer, Hexamoll® Diisononyl-Cyclohexane-1, 2-Dicarboxylate Using In Silico, In Vitro, and Human Biomonitoring Data

A physiologically based pharmacokinetic model for Hexamoll^® diisononyl-cyclohexane-1, 2-dicarboxylate 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 behavior prior to simulation and analysis of human biological monitoring data. The model provided good simulations of the urinary excretion (Curine) of two metabolites; cyclohexane-1,2-dicarboxylic acid mono hydroxyisononyl ester (OH-MINCH) and cyclohexane-1, 2-dicarboxylic acid mono carboxyisononyl ester (cx-MINCH) from the biotransformation of mono-isononyl-cyclohexane-1, 2-dicarboxylate (MINCH), the monoester metabolite of di-isononyl-cyclohexane-1,2-dicarboxylate. However, good simulations could be obtained, with and without, a lymphatic compartment. Selection of an appropriate model structure was informed by sensitivity analysis which could identify and quantify the contribution to variability in Curine by parameters, such as, the fraction of oral dose that directly entered the lymphatic compartment and therefore by-passed the liver and the fraction of MINCH bio-transformed to cx-MINCH and OH-MINCH. By constraining these parameters within biologically plausible limits the presence of a lymphatic compartment was deemed an important component of model structure. Furthermore, the use of sensitivity analysis is important in the evaluation of uncertainty around in silico derived parameters. By quantifying their impact on model output sufficient confidence in the use of a model should be afforded. This type of approach could expand the use of physiologically based pharmacokinetic 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.

The application of global sensitivity analysis in the development of a physiologically based pharmacokinetic model for m-xylene and ethanol co-exposure in humans

Global sensitivity analysis (SA) was used during the development phase of a binary chemical physiologically based pharmacokinetic (PBPK) model used for the analysis of m-xylene and ethanol co-exposure in humans. SA was used to identify those parameters which had the most significant impact on variability of venous blood and exhaled m-xylene and urinary excretion of the major metabolite of m-xylene metabolism, 3-methyl hippuric acid. This analysis informed the selection of parameters for estimation/calibration by fitting to measured biological monitoring (BM) data in a Bayesian framework using Markov chain Monte Carlo (MCMC) simulation. Data generated in controlled human studies were shown to be useful for investigating the structure and quantitative outputs of PBPK models as well as the biological plausibility and variability of parameters for which measured values were not available. This approach ensured that a priori knowledge in the form of prior distributions was ascribed only to those parameters that were identified as having the greatest impact on variability. This is an efficient approach which helps reduce computational cost.

MEGen: A Physiologically Based Pharmacokinetic Model Generator

Physiologically based pharmacokinetic models are being used in an increasing number of different areas. However, they are perceived as complex, data hungry, resource intensive, and time consuming. In addition, model validation and verification are hindered by the relative complexity of the equations. To begin to address these issues a web application called MEGen for the rapid construction and documentation of bespoke deterministic PBPK model code is under development. MEGen comprises a parameter database and a model code generator that produces code for use in several commercial software packages and one that is freely available. Here we present an overview of the current capabilities of MEGen, and discuss future developments.

Modeling of corneal and retinal pharmacokinetics after periocular drug administration

PURPOSE

To develop pharmacokinetics models to describe the disposition of small lipophilic molecules in the cornea and retina after periocular (subconjunctival or posterior subconjunctival) administration.

METHODS

Compartmental pharmacokinetics analysis was performed on the corneal and retinal data obtained after periocular administration of 3 mg of celecoxib (a selective COX-2 inhibitor) to Brown Norway (BN) rats. Berkeley Madonna, a differential and difference equation-based modeling software, was used for the pharmacokinetics modeling. The data were fit to different compartment models with first-order input and disposition, and the best fit was selected on the basis of coefficient of regression and Akaike information criteria (AIC). The models were validated by using the celecoxib data from a prior study in Sprague-Dawley (SD) rats. The corneal model was also fit to the corneal data for prednisolone at a dose of 2.61 mg in albino rabbits, and the model was validated at two other doses of prednisolone (0.261 and 26.1 mg) in these rabbits. Model simulations were performed with the finalized model to understand the effect of formulation on corneal and retinal pharmacokinetics after periocular administration.

RESULTS

Celecoxib kinetics in the BN rat cornea can be described by a two-compartment (periocular space and cornea, with a dissolution step for periocular formulation) model, with parallel elimination from the cornea and the periocular space. The inclusion of a distribution compartment or a dissolution step for celecoxib suspension did not lead to an overall improvement in the corneal data fit compared with the two-compartment model. The more important parameter for enhanced fit and explaining the apparent lack of an increase phase in the corneal levels is the inclusion of the initial leak-back of the dose from the periocular space into the precorneal area. The predicted celecoxib concentrations from this model also showed very good correlation (r = 0.99) with the observed values in the SD rat corneas. Similar pharmacokinetics models explain drug delivery to the cornea in rat and rabbit animal models. Retinal pharmacokinetics after periocular drug administration can be explained with a four-compartment (periocular space, choroid-containing transfer compartment, retina, and distribution compartment) model with elimination from the periocular space, retina, and choroid compartment. Inclusion of a dissolution-release step before the drug is available for absorption or elimination better explains retinal t(max). Good fits were obtained in both the BN (r = 0.99) and SD (r = 0.99) rats for retinal celecoxib using the same model; however, the parameter estimates differed.

CONCLUSIONS

Corneal and retinal pharmacokinetics of small lipophilic molecules after periocular administration can be described by compartment models. The modeling analysis shows that (1) leak-back from the site of administration most likely contributes to the apparent lack of an increase phase in corneal concentrations; (2) elimination via the conjunctival or periocular blood and lymphatic systems contributes significantly to drug clearance after periocular injection; (3) corneal pharmacokinetics of small lipophilic molecules can be explained by using similar models in rats and rabbits; and (4) although there are differences in some retinal pharmacokinetics parameters between the pigmented and nonpigmented rats, the physiological basis of these differences has yet to be ascertained.