Physiologically-based pharmacokinetic and toxicokinetic models in cancer risk assessment

The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment

Toxicokinetics plays a crucial role in the health risk assessments of xenobiotics. Classical compartmental models are limited in their ability to determine chemical concentrations in specific organs or tissues, particularly target organs or tissues, and their limited interspecific and exposure route extrapolation hinders satisfactory health risk assessment. In contrast, physiologically based toxicokinetic (PBTK) models quantitatively describe the absorption, distribution, metabolism, and excretion of chemicals across various exposure routes and doses in organisms, establishing correlations with toxic effects. Consequently, PBTK models serve as potent tools for extrapolation and provide a theoretical foundation for health risk assessment and management. This review outlines the construction and application of PBTK models in health risk assessment while analyzing their limitations and future perspectives.

A Physiological-Based Pharmacokinetic Model For The Broad Spectrum Antimicrobial Zinc Pyrithione: II. Dermal Absorption And Dosimetry In The Rat

The broad spectrum antimicrobial/antifungal zinc pyrithione (ZnPT) is used in products ranging from antifouling paint to antidandruff shampoo. The hazard profile of ZnPT was established based upon comprehensive toxicological testing, and products containing this biocide have been safely used for years. The purpose of this study was to create a dermal physiologically based pharmacokinetic (PBPK) model for ZnPT in the rat for improving dose-response analysis of ZnPT-induced toxicity where reversible hindlimb weakness was the endpoint used as the basis for ZnPT risk assessments. Previously, we developed a PBPK model which simulated the kinetics of pyrithione (PT) and its major metabolites 2-(methylsulfonyl)pyridine and S-glucuronide conjugates in blood and tissues of rats following oral ZnPT administration. The dermal model was optimized utilizing in vitro dermal penetration investigations conducted with rat skin and with historical data from a dermal repeat dose study using rats. The model replicated the observed temporal patterns and elimination kinetics of [¹⁴C]PT equivalents in blood and urine during and following repeated dermal dosing and replicated the observed dose-dependencies of absorption, blood [¹⁴C]PT equivalents and plasma PT concentrations. The model provided internal dosimetry predictions for a benchmark dose analysis of hindlimb weakness in rats that combined dermal, gavage and dietary studies into a single internal dose-response model with area-under-the-curve (AUC) for plasma PT, the toxic moiety in the rat, as the internal dose metric. This PBPK model has predictive validity for calculating internal doses of PT and/or [¹⁴C]PT equivalents from different routes of exposure in the rat.

Mechanisms of DNA-reactive and epigenetic chemical carcinogens: applications to carcinogenicity testing and risk assessment

Chemicals with carcinogenic activity in either animals or humans produce increases in neoplasia through diverse mechanisms. One mechanism is reaction with nuclear DNA. Other mechanisms consist of epigenetic effects involving either modifications of regulatory macromolecules or perturbation of cellular regulatory processes. The basis for distinguishing between carcinogens that have either DNA reactivity or an epigenetic activity as their primary mechanism of action is detailed in this review. In addition, important applications of information on these mechanisms of action to carcinogenicity testing and human risk assessment are discussed.

A physiologically based pharmacokinetic model for the broad-spectrum antimicrobial zinc pyrithione: I. Development and verification

The broad-spectrum antimicrobial zinc pyrithione (ZnPT) is used in numerous products ranging from in-can preservative/mildicide in paints to antidandruff shampoo. Although products containing ZnPT have a long history of safe use, regulatory agencies routinely set limits of exposure based upon toxicological considerations. The objective of this study was to create a physiologically based pharmacokinetic (PBPK) model for ZnPT in the rat for improving dose-response analysis of ZnPT-induced toxicity, reversible hindlimb weakness, the endpoint that has been used as the basis for ZnPT risk assessments. A rat oral PBPK model was developed that includes compartments for plasma, liver, kidneys, muscle, brain, and rapidly and slowly perfused tissues. Pyrithione metabolism to 2-(methylsulfonyl)pyridine (MSP) and glucuronide conjugates was incorporated into the model. The model was parameterized and optimized based upon data from single-dose intravenous (iv) and oral gavage pharmacokinetic studies of radiolabeled pyrithione ([¹⁴C]PT) administered as zinc [¹⁴C]-pyrithione (Zn-[¹⁴C]PT) to adult female rats. It was further evaluated and refined using data from repeated, multidose oral gavage and dietary studies of Zn[¹⁴C]PT in the adult female rat that included measurements of plasma PT concentration, the putative toxic species. The model replicated the observed short-term elimination kinetics of PT in plasma and [¹⁴C]PT in whole blood following single doses and longer term temporal patterns of plasma and blood concentrations during repeated dosing schedules. The model also accounted for production and rapid elimination of S-glucuronide conjugates (SG) of 2-pyridinethiol and 2-pyridinethiol-1-oxide in urine, as well as production and slower elimination of MSP, the major [¹⁴C]PT species in blood within several hours following administration of ZnPT. The model provided internal dosimetry predictions for a benchmark dose (BMD) analysis of hindlimb weakness in rats, and was used to combine gavage and dietary studies into a single internal dose-response model with area under the curve (AUC) for plasma PT as the internal dose metric. This PBPK model has predictive validity for calculating internal doses of PT and/or [¹⁴C]PT from different routes of exposure in the rat.

A physiologically based pharmacokinetic model of rifampin in mice

One problem associated with regimen-based development of antituberculosis (anti-TB) drugs is the difficulty of a systematic and thorough in vivo evaluation of the large number of possible regimens that arise from consideration of multiple drugs tested together. A mathematical model capable of simulating the pharmacokinetics and pharmacodynamics of experimental combination chemotherapy of TB offers a way to mitigate this problem by extending the use of available data to investigate regimens that are not initially tested. In order to increase the available mathematical tools needed to support such a model for preclinical anti-TB drug development, we constructed a preliminary whole-body physiologically based pharmacokinetic (PBPK) model of rifampin in mice, using data from the literature. Interindividual variability was approximated using Monte Carlo (MC) simulation with assigned probability distributions for the model parameters. An MC sensitivity analysis was also performed to determine correlations between model parameters and plasma concentration to inform future model development. Model predictions for rifampin concentrations in plasma, liver, kidneys, and lungs, following oral administration, were generally in agreement with published experimental data from multiple studies. Sensitive model parameters included those descriptive of oral absorption, total clearance, and partitioning of rifampin between blood and muscle. This PBPK model can serve as a starting point for the integration of rifampin pharmacokinetics in mice into a larger mathematical framework, including the immune response to Mycobacterium tuberculosis infection, and pharmacokinetic models for other anti-TB drugs.

Physiologically-based pharmacokinetic (PBPK) models in toxicity testing and risk assessment

Physiologically-based pharmacokinetic (PBPK) modeling offers a scientifically-sound framework for integrating mechanistic data on absorption, distribution, metabolism and elimination to predict the time-course of parent chemical, metabolite(s) or biomarkers in the exposed organism. A major advantage of PBPK models is their ability to forecast the impact of specific mechanistic processes and determinants on the tissue dose. In this regard, they facilitate integration of data obtained with in vitro and in silico methods, for making predictions of the tissue dosimetry in the whole animal, thus reducing and/or refining the use of animals in pharmacokinetic and toxicity studies. This chapter presents the principles and practice of PBPK modeling, as well as the application of these models in toxicity testing and health risk assessments.

A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim^® and MoBi^® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

Whole body physiologically-based pharmacokinetic models: their use in clinical drug development

BACKGROUND

Whole-body physiologically-based pharmacokinetic (WB-PBPK) models mathematically describe an organism as a closed circulatory system consisting of compartments that represent the organs important for compound absorption, distribution, metabolism and elimination.

OBJECTIVES

To review the current state of WB-PBPK model use in the clinical phases of drug development.

METHODS

A qualitative description of the WB-PBPK model structure is included along with a review of the varying methods available for input parameterisation. Current and potential WB-PBPK model application in clinical development is discussed.

CONCLUSIONS

This modelling tool is at present used for small and large molecule drug development primarily as a means to scale pharmacokinetics from animals to humans based on physiology. The pharmaceutical industry is active in employing these models to clinical drug development although the applications in use now are narrow in comparison to the potential. Expanded integration of WB-PBPK models into the drug development process will only be achieved with staff training, managerial will, success stories and regulatory agency openness.

Methods for assessing uncertainty in fundamental assumptions and associated models for cancer risk assessment

The distributional approach for uncertainty analysis in cancer risk assessment is reviewed and extended. The method considers a combination of bioassay study results, targeted experiments, and expert judgment regarding biological mechanisms to predict a probability distribution for uncertain cancer risks. Probabilities are assigned to alternative model components, including the determination of human carcinogenicity, mode of action, the dosimetry measure for exposure, the mathematical form of the dose-response relationship, the experimental data set(s) used to fit the relationship, and the formula used for interspecies extrapolation. Alternative software platforms for implementing the method are considered, including Bayesian belief networks (BBNs) that facilitate assignment of prior probabilities, specification of relationships among model components, and identification of all output nodes on the probability tree. The method is demonstrated using the application of Evans, Sielken, and co-workers for predicting cancer risk from formaldehyde inhalation exposure. Uncertainty distributions are derived for maximum likelihood estimate (MLE) and 95th percentile upper confidence limit (UCL) unit cancer risk estimates, and the effects of resolving selected model uncertainties on these distributions are demonstrated, considering both perfect and partial information for these model components. A method for synthesizing the results of multiple mechanistic studies is introduced, considering the assessed sensitivities and selectivities of the studies for their targeted effects. A highly simplified example is presented illustrating assessment of genotoxicity based on studies of DNA damage response caused by naphthalene and its metabolites. The approach can provide a formal mechanism for synthesizing multiple sources of information using a transparent and replicable weight-of-evidence procedure.

Extrahepatic metabolism by CYP2E1 in PBPK modeling of lipophilic volatile organic chemicals: impacts on metabolic parameter estimation and prediction of dose metrics

Physiologically based pharmacokinetic (PBPK) models are increasingly available for environmental chemicals and applied in risk assessments. Volatile organic compounds (VOCs) are important pollutants in air, soil, and water. CYP2E1 metabolically activates many VOCs in animals and humans. Despite its presence in extrahepatic tissues, the metabolism by CYP2E1 is often described as restricted to the liver in PBPK models, unless target tissue dose metrics in extrahepatic tissues are needed for the model application, including risk assessment. The impact of accounting for extrahepatic metabolism by CYP2E1 on the estimation of metabolic parameters and the prediction of dose metrics was evaluated for three lipophilic VOCs: vinyl chloride, trichloroethylene, and carbon tetrachloride. Metabolic parameters estimated from fitting gas uptake data with and without extrahepatic metabolism were similar. The impact of extrahepatic metabolism on PBPK predictions was evaluated using inhalation exposure scenarios relevant for animal toxicity studies and human risk assessment. Although small, the relative role of extrahepatic metabolism and the differences in the predicted dose metrics were greater at low exposure concentrations. The impact was species dependent and influenced by Km for CYP2E1. The current study indicates that inhalation modeling for several representative VOCs that are CYP2E1 substrates is not affected by the inclusion of extrahepatic metabolism, implying that liver-only metabolism may be a reasonable simplification for PBPK modeling of lipophilic VOCs. The PBPK predictions using this assumption can be applied confidently for risk assessment, but this conclusion should not necessarily be applied to VOCs that are metabolized by other enzymes.

Whole-body physiologically based pharmacokinetic models

This review summarizes the most recent developments in and applications of physiologically based pharmacokinetic (PBPK) modeling methodology originating from both the pharmaceutical and environmental toxicology areas. It focuses on works published in the last 5 years, although older seminal papers have also been referenced. After a brief introduction to the field and several essential definitions, the main body of the text is structured to follow the major steps of a typical PBPK modeling exercise. Various applications of the methodology are briefly described. The major future trends and perspectives are outlined. The main conclusion from the review of the available literature is that PBPK modeling, despite its obvious potential and recent incremental developments, has not taken the place it deserves, especially in pharmaceutical and drug development sciences.