Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling.

Although external concentrations are more readily quantified and often used as the metric for regulating and mitigating exposures to environmental chemicals, the toxicological response to an environmental chemical is more directly related to its internal concentrations than the external concentration. The processes of absorption, distribution, metabolism, and excretion (ADME) determine the quantitative relationship between the external and internal concentrations, and these processes are often susceptible to saturation at high concentrations, which can lead to nonlinear changes in internal concentrations that deviate from proportionality. Using generic physiologically-based pharmacokinetic (PBPK) models, we explored how saturable absorption or clearance influence the shape of the internal to external concentration (IEC) relationship. We used the models for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and models for styrene and caffeine to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. A PBPK modeling approach can be a valuable tool used in the early stages of a chemical safety assessment program to optimize the design of longer-term animal toxicity studies or to interpret study results.

Opportunities and challenges related to saturation of toxicokinetic processes: Implications for risk assessment.

Top dose selection for repeated dose animal studies has generally focused on identification of apical endpoints, use of the limit dose, or determination of a maximum tolerated dose (MTD). The intent is to optimize the ability of toxicity tests performed in a small number of animals to detect effects for hazard identification. An alternative approach, the kinetically derived maximum dose (KMD), has been proposed as a mechanism to integrate toxicokinetic (TK) data into the dose selection process. The approach refers to the dose above which the systemic exposures depart from being proportional to external doses. This non-linear external-internal dose relationship arises from saturation or limitation of TK process(es), such as absorption or metabolism. The importance of TK information is widely acknowledged when assessing human health risks arising from exposures to environmental chemicals, as TK determines the amount of chemical at potential sites of toxicological responses. However, there have been differing opinions and interpretations within the scientific and regulatory communities related to the validity and application of the KMD concept. A multi-stakeholder working group, led by the Health and Environmental Sciences Institute (HESI), was formed to provide an opportunity for impacted stakeholders to address commonly raised scientific and technical issues related to this topic and, more specifically, a weight of evidence approach is recommended to inform design and dose selection for repeated dose animal studies. Commonly raised challenges related to the use of TK data for dose selection are discussed, recommendations are provided, and illustrative case examples are provided to address these challenges or refute misconceptions.

Moving beyond Binary Predictions of Human Drug-Induced Liver Injury (DILI) toward Contrasting Relative Risk Potential.

The hepatic risk matrix (HRM) was developed and used to differentiate lead clinical and back-up drug candidates against competitor/marketed drugs within the same pharmaceutical class for their potential to cause human drug-induced liver injury (DILI). The hybrid HRM scoring system blends physicochemical properties (Rule of Two Model: dose and lipophilicity or Partition Model: dose, ionization state, lipophilicity, and fractional carbon bond saturation) with common toxicity mechanisms (cytotoxicity, mitochondrial dysfunction, and bile salt export pump (BSEP) inhibition) that promote DILI. HRM scores are based on bracketed safety margins (<1, 1-10, 10-100, and >100× clinical Cmax,total). On the basis of well-established clinical safety experience of marketed/withdrawn drug candidates, the background analysis consists of 200 drugs from the Liver Toxicity Knowledge Base annotated as Most-DILI- (79), Less-DILI- (56), No-DILI- (47), and Ambiguous-DILI-concern (18) drugs. Scores were generated for over 21 internal and 7 external drug candidates discontinued for unacceptable incidence/magnitude of liver transaminase elevations during clinical trials or withdrawn for liver injury severity. Both hybrid scoring systems identified 70-80% Most-DILI-concern drugs, but more importantly, stratified successful/unsuccessful drug candidates for liver safety (incidence/severity of transaminase elevations and approved drug labels). Incorporating other mechanisms (reactive metabolite and cytotoxic metabolite generation and hepatic efflux transport inhibition, other than BSEP) to the HRM had minimal beneficial impact in DILI prediction/stratification. As is, the hybrid scoring system was positioned for portfolio assessments to contrast DILI risk potential of small molecule drug candidates in early clinical development. This stratified approach for DILI prediction aided decisions regarding drug candidate progression, follow-up mechanistic work, back-up selection, clinical dose selection, and due diligence assessments in favor of compounds with less implied clinical hepatotoxicity risk.

Translational Modeling in Schizophrenia: Predicting Human Dopamine D2 Receptor Occupancy.

OBJECTIVES: To assess the ability of a previously developed hybrid physiology-based pharmacokinetic-pharmacodynamic (PBPKPD) model in rats to predict the dopamine D2 receptor occupancy (D2RO) in human striatum following administration of antipsychotic drugs. METHODS: A hybrid PBPKPD model, previously developed using information on plasma concentrations, brain exposure and D2RO in rats, was used as the basis for the prediction of D2RO in human. The rat pharmacokinetic and brain physiology parameters were substituted with human population pharmacokinetic parameters and human physiological information. To predict the passive transport across the human blood-brain barrier, apparent permeability values were scaled based on rat and human brain endothelial surface area. Active efflux clearance in brain was scaled from rat to human using both human brain endothelial surface area and MDR1 expression. Binding constants at the D2 receptor were scaled based on the differences between in vitro and in vivo systems of the same species. The predictive power of this physiology-based approach was determined by comparing the D2RO predictions with the observed human D2RO of six antipsychotics at clinically relevant doses. RESULTS: Predicted human D2RO was in good agreement with clinically observed D2RO for five antipsychotics. Models using in vitro information predicted human D2RO well for most of the compounds evaluated in this analysis. However, human D2RO was under-predicted for haloperidol. CONCLUSIONS: The rat hybrid PBPKPD model structure, integrated with in vitro information and human pharmacokinetic and physiological information, constitutes a scientific basis to predict the time course of D2RO in man.

Physiologically based pharmacokinetic prediction of telmisartan in human.

A previously developed physiologically based pharmacokinetic model for hepatic transporter substrates was extended to an organic anion transporting polypeptide substrate, telmisartan. Predictions used in vitro data from sandwich culture human hepatocyte and human liver microsome assays. We have developed a novel method to calibrate partition coefficients (Kps) between nonliver tissues and plasma on the basis of published human positron emission tomography (PET) data to decrease the uncertainty in tissue distribution introduced by in silico-predicted Kps. With in vitro data-predicted hepatic clearances, published empirical scaling factors, and PET-calibrated Kps, the model could accurately recapitulate telmisartan pharmacokinetic (PK) behavior before 2.5 hours. Reasonable predictions also depend on having a model structure that can adequately describe the drug disposition pathways. We showed that the elimination phase (2.5-12 hours) of telmisartan PK could be more accurately recapitulated when enterohepatic recirculation of parent compound derived from intestinal deconjugation of glucuronide metabolite was incorporated into the model. This study demonstrated the usefulness of the previously proposed physiologically based modeling approach for purely predictive intravenous PK simulation and identified additional biologic processes that can be important in prediction.

Dopamine D2 receptor occupancy as a predictor of catalepsy in rats: a pharmacokinetic-pharmacodynamic modeling approach.

OBJECTIVES: Dopamine D2 receptor occupancy (D2RO) is the major determinant of efficacy and safety in schizophrenia drug therapy. Excessive D2RO (>80%) is known to cause catalepsy (CAT) in rats and extrapyramidal side effects (EPS) in human. The objective of this study was to use pharmacokinetic and pharmacodynamic modeling tools to relate CAT with D2RO in rats and to compare that with the relationship between D2RO and EPS in humans. METHODS: Severity of CAT was assessed in rats at hourly intervals over a period of 8 h after antipsychotic drug treatment. An indirect response model with and without Markov elements was used to explain the relationship of D2RO and CAT. RESULTS: Both models explained the CAT data well for olanzapine, paliperidone and risperidone. However, only the model with the Markov elements predicted the CAT severity well for clozapine and haloperidol. The relationship between CAT scores in rat and EPS scores in humans was implemented in a quantitative manner. Risk of EPS not exceeding 10% over placebo correlates with less than 86% D2RO and less than 30% probability of CAT events in rats. CONCLUSION: A quantitative relationship between rat CAT and human EPS was elucidated and may be used in drug discovery to predict the risk of EPS in humans from D2RO and CAT scores measured in rats.

A "middle-out" approach to human pharmacokinetic predictions for OATP substrates using physiologically-based pharmacokinetic modeling.

Physiologically based pharmacokinetic (PBPK) models provide a framework useful for generating credible human pharmacokinetic predictions from data available at the earliest, preclinical stages of pharmaceutical research. With this approach, the pharmacokinetic implications of in vitro data are contextualized via scaling according to independent physiological information. However, in many cases these models also require model-based estimation of additional empirical scaling factors (SFs) in order to accurately recapitulate known human pharmacokinetic behavior. While this practice clearly improves data characterization, the introduction of empirically derived SFs may belie the extrapolative power commonly attributed to PBPK. This is particularly true when such SFs are compound dependent and/or when there are issues with regard to identifiability. As such, when empirically-derived SFs are necessary, a critical evaluation of parameter estimation and model structure are prudent. In this study, we applied a global optimization method to support model-based estimation of a single set of empirical SFs from intravenous clinical data on seven OATP substrates within the context of a previously published PBPK model as well as a revised PBPK model. The revised model with experimentally measured unbound fraction in liver, permeability between liver compartments, and permeability limited distribution to selected tissues improved data characterization. We utilized large-sample approximation and resampling approaches to estimate confidence intervals for the revised model in support of forward predictions that reflect the derived uncertainty. This work illustrates an objective approach to estimating empirically-derived SFs, systematically refining PBPK model performance and conveying the associated confidence in subsequent forward predictions.

Case study illustrating the WHO IPCS guidance on characterization and application of physiologically based pharmacokinetic models in risk assessment.

The World Health Organization (WHO) International Programme on Chemical Safety (IPCS) Guidance on Characterization and Application of Physiologically Based Pharmacokinetic Models in Risk Assessment (IPCS, 2010) describes key principles for risk assessors and model developers. In the WHO Guidance, a template for model documentation was developed and a case study included. Here the WHO Guidance, including the template, is summarized and an additional case study is presented to illustrate its application, based upon an existing risk assessment for 2-butoxyethanol (CAS NO. 111-76-2). The goal of the WHO Guidance and the current paper is to increase regulatory acceptance of complex biologically descriptive pharmacokinetic (or toxicokinetic) models, such as PBPK models, by facilitating communication and successful interaction between modelers and risk assessors.

On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach.

Objectives of the present investigation were: (1) to compare three literature reported tumor growth inhibition (TGI) pharmacodynamic (PD) models and propose an optimal new model that best describes the xenograft TGI data for antibody drug conjugates (ADC), (2) to translate efficacy of the ADC Trastuzumab-emtansine (T-DM1) from mice to patients using the optimized PD model, and (3) to apply the translational strategy to predict clinically efficacious concentrations of a novel in-house anti-5T4 ADC, A1mcMMAF. First, the performance of all four of the PD models (i.e. 3 literature reported + 1 proposed) was evaluated using TGI data of T-DM1 obtained from four different xenografts. Based on the estimates of the pharmacodynamic/pharmacokinetic (PK/PD) modeling, a secondary parameter representing the efficacy index of the drug was calculated, which is termed as the tumor static concentration (TSC). TSC values derived from all four of the models were compared with each other, and with literature reported values, to assess the performance of these models. Subsequently, using the optimized PK/PD model, PD parameters obtained from different cell lines, human PK, and the proposed translational strategy, clinically efficacious doses of T-DM1 were projected. The accuracy of projected efficacious dose range for T-DM1 was verified by comparison with the clinical doses. Aforementioned strategy was then applied to A1mcMMAF for projecting its efficacious concentrations in clinic. TSC values for A1mcMMAF, obtained by fitting TGI data from 4 different xenografts with the proposed PK/PD model, were estimated to range from 0.6 to 11.5 µg mL⁻¹. Accordingly, the clinically efficacious doses for A1mcMMAF were projected retrospectively. All in all, the improved PD model and proposed translational strategy presented here suggest that appropriate correction for the clinical exposure and employing the TSC criterion can help translate mouse TGI data to predict first in human doses of ADCs.

Cerebrospinal fluid ß-Amyloid turnover in the mouse, dog, monkey and human evaluated by systematic quantitative analyses.

BACKGROUND: Reducing brain ß-amyloid (Aß) via inhibition of ß-secretase, or inhibition/modulation of γ-secretase, has been widely pursued as a potential disease-modifying treatment for Alzheimer's disease. Compounds that act through these mechanisms have been screened and characterized with Aß lowering in the brain and/or cerebrospinal fluid (CSF) as the primary pharmacological end point. Interpretation and translation of the pharmacokinetic (PK)/pharmacodynamic (PD) relationship for these compounds is complicated by the relatively slow Aß turnover process in these compartments. OBJECTIVE: To understand Aß turnover kinetics in preclinical species and humans. METHODS: We collected CSF Aß dynamic data after ß- or γ-secretase inhibitor treatment from in-house experiments and the public domain, and analyzed the data using PK/PD modeling to obtain CSF Aß turnover rates (kout) in the mouse, dog, monkey and human. RESULTS: The kout for CSF Aß40 follows allometry (kout = 0.395 × body weight(-0.351)). The kout for CSF Aß40 is approximately 2-fold higher than the turnover of CSF in rodents, but in higher species, the two are comparable. CONCLUSION: The turnover of CSF Aß40 was systematically examined, for the first time, in multiple species through quantitative modeling of multiple data sets. Our result suggests that the clearance mechanisms for CSF Aß in rodents may be different from those in the higher species. The understanding of Aß turnover has considerable implications for the discovery and development of Aß-lowering therapeutics, as illustrated from the perspectives of preclinical PK/PD characterization and preclinical-to-clinical translation.

Mechanistic pharmacokinetic modeling for the prediction of transporter-mediated disposition in humans from sandwich culture human hepatocyte data.

With efforts to reduce cytochrome P450-mediated clearance (CL) during the early stages of drug discovery, transporter-mediated CL mechanisms are becoming more prevalent. However, the prediction of plasma concentration-time profiles for such compounds using physiologically based pharmacokinetic (PBPK) modeling is far less established in comparison with that for compounds with passively mediated pharmacokinetics (PK). In this study, we have assessed the predictability of human PK for seven organic anion-transporting polypeptide (OATP) substrates (pravastatin, cerivastatin, bosentan, fluvastatin, rosuvastatin, valsartan, and repaglinide) for which clinical intravenous data were available. In vitro data generated from the sandwich culture human hepatocyte system were simultaneously fit to estimate parameters describing both uptake and biliary efflux. Use of scaled active uptake, passive distribution, and biliary efflux parameters as inputs into a PBPK model resulted in the overprediction of exposure for all seven drugs investigated, with the exception of pravastatin. Therefore, fitting of in vivo data for each individual drug in the dataset was performed to establish empirical scaling factors to accurately capture their plasma concentration-time profiles. Overall, active uptake and biliary efflux were under- and overpredicted, leading to average empirical scaling factors of 58 and 0.061, respectively; passive diffusion required no scaling factor. This study illustrates the mechanistic and model-driven application of in vitro uptake and efflux data for human PK prediction for OATP substrates. A particular advantage is the ability to capture the multiphasic plasma concentration-time profiles for such compounds using only preclinical data. A prediction strategy for novel OATP substrates is discussed.

In vitro evaluation of hepatic transporter-mediated clinical drug-drug interactions: hepatocyte model optimization and retrospective investigation.

To assess the feasibility of using sandwich-cultured human hepatocytes (SCHHs) as a model to characterize transport kinetics for in vivo pharmacokinetic prediction, the expression of organic anion-transporting polypeptide (OATP) proteins in SCHHs, along with biliary efflux transporters, was confirmed quantitatively by liquid chromatography-tandem mass spectrometry. Rifamycin SV (Rif SV), which was shown to completely block the function of OATP transporters, was selected as an inhibitor to assess the initial rates of active uptake. The optimized SCHH model was applied in a retrospective investigation of compounds with known clinically significant OATP-mediated uptake and was applied further to explore drug-drug interactions (DDIs). Greater than 50% inhibition of active uptake by Rif SV was found to be associated with clinically significant OATP-mediated DDIs. We propose that the in vitro active uptake value therefore could serve as a cutoff for class 3 and 4 compounds of the Biopharmaceutics Drug Disposition Classification System, which could be integrated into the International Transporter Consortium decision tree recommendations to trigger clinical evaluations for potential DDI risks. Furthermore, the kinetics of in vitro hepatobiliary transport obtained from SCHHs, along with protein expression scaling factors, offer an opportunity to predict complex in vivo processes using mathematical models, such as physiologically based pharmacokinetics models.

The evolution of the OATP hepatic uptake transport protein family in DMPK sciences: from obscure liver transporters to key determinants of hepatobiliary clearance.

Over the last two decades the impact on drug pharmacokinetics of the organic anion transporting polypeptides (OATPs: OATP-1B1, 1B3 and 2B1), expressed on the sinusoidal membrane of the hepatocyte, has been increasingly recognized. OATP-mediated uptake into the hepatocyte coupled with subsequent excretion into bile via efflux proteins, such as MRP2, is often referred to as hepatobiliary excretion. OATP transporter proteins can impact some drugs in several ways including pharmacokinetic variability, pharmacodynamic response and drug-drug interactions (DDIs). The impact of transporter mediated hepatic clearance is illustrated with case examples, from the literature and also from the Pfizer portfolio. The currently available in vitro techniques to study the hepatic transporter proteins involved in the hepatobiliary clearance of drugs are reviewed herein along with recent advances in using these in vitro data to predict the human clearance of compounds recognized by hepatic uptake transporters.

Database for physiologically based pharmacokinetic (PBPK) modeling: physiological data for healthy and health-impaired elderly.

Physiologically based pharmacokinetic (PBPK) models have increasingly been employed in chemical health risk assessments. By incorporating individual variability conferred by genetic polymorphisms, health conditions, and physiological changes during development and aging, PBPK models are ideal for predicting chemical disposition in various subpopulations of interest. In order to improve the parameterization of PBPK models for healthy and health-impaired elderly (herein defined as those aged 65 yr and older), physiological parameter values were obtained from the peer-reviewed literature, evaluated, and entered into a Microsoft ACCESS database. Database records include values for key age-specific model inputs such as ventilation rates, organ volumes and blood flows, glomerular filtration rates, and other clearance-related processes. In total, 528 publications were screened for relevant data, resulting in the inclusion of 155 publications comprising 1051 data records for healthy elderly adults and 115 data records for elderly with conditions such as diabetes, chronic obstructive pulmonary disease (COPD), obesity, heart disease, and renal disease. There are no consistent trends across parameters or their associated variance with age; the gross variance in body weight decreased with advancing age, whereas there was no change in variance for brain weight. The database contains some information to inform ethnic and gender differences in parameters; however, the majority of the published data pertain to Asian (mostly Japanese) and Caucasian males. As expected, the number of records tends to decrease with advancing age. In addition to a general lack of data for parameters in the elderly with various health conditions, there is also a dearth of information on blood and tissue composition in all elderly groups. Importantly, there are relatively few records for alveolar ventilation rate; therefore, the relationship between this parameter and cardiac output (usually assumed to be 1:1) in the elderly is not well informed by the database. Despite these limitations, the database represents a potentially useful resource for parameterizing PBPK models for the elderly to facilitate the prediction of dose metrics in older populations for application in risk assessment.

A Physiologically-Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics From In Vitro Data.

Monoclonal antibody (mAb) pharmacokinetics (PK) have largely been predicted via allometric scaling with little consideration for cross-species differences in neonatal Fc receptor (FcRn) affinity or clearance/distribution mechanisms. To address this, we developed a mAb physiologically-based PK model that describes the intracellular trafficking and FcRn recycling of mAbs in a human FcRn transgenic homozygous mouse and human. This model uses mAb-specific in vitro data together with species-specific FcRn tissue expression, tissue volume, and blood-flow physiology to predict mAb in vivo linear PK a priori. The model accurately predicts the terminal half-life of 90% of the mAbs investigated within a twofold error. The mechanistic nature of this model allows us to not only predict linear PK from in vitro data but also explore the PK and target binding of mAbs engineered to have pH-dependent binding to its target or FcRn and could aid in the selection of mAbs with optimal PK and pharmacodynamic properties.

Quantitative systems toxicology (QST) reproduces species differences in PF-04895162 liver safety due to combined mitochondrial and bile acid toxicity.

Many compounds that appear promising in preclinical species, fail in human clinical trials due to safety concerns. The FDA has strongly encouraged the application of modeling in drug development to improve product safety. This study illustrates how DILIsym, a computational representation of liver injury, was able to reproduce species differences in liver toxicity due to PF-04895162 (ICA-105665). PF-04895162, a drug in development for the treatment of epilepsy, was terminated after transaminase elevations were observed in healthy volunteers (NCT01691274). Liver safety concerns had not been raised in preclinical safety studies. DILIsym, which integrates in vitro data on mechanisms of hepatotoxicity with predicted in vivo liver exposure, reproduced clinical hepatotoxicity and the absence of hepatotoxicity observed in the rat. Simulated differences were multifactorial. Simulated liver exposure was greater in humans than rats. The simulated human hepatotoxicity was demonstrated to be due to the interaction between mitochondrial toxicity and bile acid transporter inhibition; elimination of either mechanism from the simulations abrogated injury. The bile acid contribution occurred despite the fact that the IC50 for bile salt export pump (BSEP) inhibition by PF-04895162 was higher (311 µmol/L) than that has been generally thought to contribute to hepatotoxicity. Modeling even higher PF-04895162 liver exposures than were measured in the rat safety studies aggravated mitochondrial toxicity but did not result in rat hepatotoxicity due to insufficient accumulation of cytotoxic bile acid species. This investigative study highlights the potential for combined in vitro and computational screening methods to identify latent hepatotoxic risks and paves the way for similar and prospective studies.

Predicting maternal rat and pup exposures: how different are they?

Risk and safety assessments for early life exposures to environmental chemicals or pharmaceuticals based on cross-species extrapolation would greatly benefit from information on chemical dosimetry in the young. Although relevant toxicity studies involve exposures during multiple life stages, the mother's exposure dose is frequently used for extrapolation of rodent toxicity findings to humans and represents a substantial source of uncertainty. A compartmental pharmacokinetic model augmented with biological information on factors changing during lactation and early postweaning was developed. The model uses adult pharmacokinetics, milk distribution, and relevant postnatal biology to predict dosimetry in the young for chemicals. The model addressed three dosing strategies employed in toxicity studies (gavage, constant ppm diet, and adjusted ppm diet) and the impact of different pharmacokinetic properties such as rates of clearance, milk distribution, and volume of distribution on the pup exposure doses and internal dosimetry. Developmental delays in clearance and recirculation of chemical in excreta from the pup to mother were evaluated. Following comparison with data for two chemicals, predictions were made for theoretical chemicals with a range of characteristics. Pup exposure was generally lower than the mother's with a shorter half-life, lower milk transfer, larger volume of distribution, and gavage dosing, while higher with longer half-life, higher milk transfer, smaller volume of distribution, and dietary exposures. The present model demonstrated pup exposures do not always parallel the mother's. The model predictions can be used to help design early life toxicity and pharmacokinetic studies and better interpret study findings.

Approaches for applications of physiologically based pharmacokinetic models in risk assessment.

Physiologically based pharmacokinetic (PBPK) models are particularly useful for simulating exposures to environmental toxicants for which, unlike pharmaceuticals, there is often little or no human data available to estimate the internal dose of a putative toxic moiety in a target tissue or an appropriate surrogate. This article reviews the current state of knowledge and approaches for application of PBPK models in the process of deriving reference dose, reference concentration, and cancer risk estimates. Examples drawn from previous U.S. Environmental Protection Agency (EPA) risk assessments and human health risk assessments in peer-reviewed literature illustrate the ways and means of using PBPK models to quantify the pharmacokinetic component of the interspecies and intraspecies uncertainty factors as well as to conduct route to route, high dose to low dose and duration extrapolations. The choice of the appropriate dose metric is key to the use of the PBPK models for the various applications in risk assessment. Issues related to whether uncertainty factors are most appropriately applied before or after derivation of human equivalent dose (or concentration) continue to be explored. Scientific progress in the understanding of life stage and genetic differences in dosimetry and their impacts on variability in susceptibility, as well as ongoing development of analytical methods to characterize uncertainty in PBPK models, will make their use in risk assessment increasingly likely. As such, it is anticipated that when PBPK models are used to express adverse tissue responses in terms of the internal target tissue dose of the toxic moiety rather than the external concentration, the scientific basis of, and confidence in, risk assessments will be enhanced.

Comparing single and repeated dosimetry data for perfluorooctane sulfonate in rats.

Perfluorooctane sulfonate (PFOS) is a member of a class of perfluorinated chemicals used in a variety of consumer and industrial applications because of their oleophobic and hydrophobic properties. It has been shown to cause toxicity in adult and developing laboratory animals. Because PFOS has also been shown to be widely distributed throughout the environment, there have been concerns about its potential health risk to humans. Limited pharmacokinetic data for PFOS are available in rodents and humans, while epidemiological studies of workers and extensive toxicity studies in rodents have been performed. The existing pharmacokinetic and toxicity database in rodents can be useful in the cross-species extrapolations needed to evaluate and interpret internal dosimetry in humans. A mathematical model that describes the disposition of PFOS in adult rats following intravenous, oral, and chronic dietary exposures was developed to gain a better understanding of the pharmacokinetics of PFOS and to determine whether single-dose kinetics are predictive of repeated-dose kinetics. In order to characterize existing time-course data, time-dependent and concentration-dependent changes in the pharmacokinetic parameters for urinary and biliary clearance and liver distribution were needed. Whether these time-dependent changes represent inconsistencies across experiments, effects of aging in the rats, or chemically induced changes in pharmacokinetics remains to be determined.