A tissue composition-based algorithm for predicting tissue:air partition coefficients of organic chemicals

Interspecies scaling of toxicity reference values in human health versus ecological risk assessments: A critical review

Risk assessments that focus on anthropogenic chemicals in environmental media-whether considering human health or ecological effects-often rely on toxicity data from experimentally studied species to estimate safe exposures for species that lack similar data. Current default extrapolation approaches used in both human health risk assessments and ecological risk assessments (ERAs) account for differences in body weight between the test organisms and the species of interest, but the two default approaches differ in important ways. Human health risk assessments currently employ a default based on body weight raised to the three-quarters power. Ecological risk assessments for wildlife (i.e., mammals and birds) are typically based directly on body weight, as measured in the test organism and receptor species. This review describes differences in the experimental data underlying these default practices and discusses the many factors that affect interspecies variability in chemical exposures. The interplay of these different factors can lead to substantial departures from default expectations. Alternative methodologies for conducting more accurate interspecies extrapolations in ERAs for wildlife are discussed, including tissue-based toxicity reference values, physiologically based toxicokinetic and/or toxicodynamic modeling, chemical read-across, and a system of categorical defaults based on route of exposure and toxic mode of action. Integr Environ Assess Manag 2024;20:749-764. © 2023 SETAC.

Co-PBK: a computational biomonitoring tool for assessing chronic internal exposure to chemicals and metabolites

Toxic chemicals are released into the environment through diverse human activities. An increasing number of chronic diseases are associated with ambient pollution, thus posing a threat to people. Given the high consumption of resources for human biomonitoring, this study proposed coupled physiologically-based kinetic (co-PBK) modeling matrices as a biomonitoring tool for simplifying chronic internal exposure estimates of environmental chemicals and their metabolites using naphthalene (NAP) and its metabolites (i.e., 1-OHN and 2-OHN) as simulation examples. According to the simulation of the steady-state mass among various organs/tissues via the co-PBK modeling matrices, fat had the highest potential bioaccumulation of NAP and its metabolites. With respect to body fluids, 1-OHN and 2-OHN tended to bioaccumulate more in the bile than in the urine. According to the sensitivity analysis, the calculated sensitivity factors for the first-order kinetics-based rate constants imply that due to the biotransformation process, target organs/tissues (e.g., liver and kidneys) would be continuously exposed to more NAP metabolites under chronic exposure. Meanwhile, 1-OHN may be more stably transported to the urine than 2-OHN for further human biomonitoring during long-term internal exposure. According to the case study of simulating population chronic exposure to NAP in Shenzhen, the co-PBK modeling estimated the population exposure to NAP with an intake rate of 8.77 × 10-2 mg d-1 and the aggregated urinary concentration of NAP metabolites of 2.60 μg L-1. Furthermore, the accuracy of the urinary levels between the real-world data and the values simulated by the co-PBK modeling was assessed and the root-mean-square error of c1-OHN,urine was found to be lower than that of c2-OHN,urine.

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.

High-throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling

Chemical ionization plays an important role in many aspects of pharmacokinetic (PK) processes such as protein binding, tissue partitioning, and apparent volume of distribution at steady state (Vdss). Here, estimates of ionization equilibrium constants (i.e., pKa) were analyzed for 8132 pharmaceuticals and 24,281 other compounds to which humans might be exposed in the environment. Results revealed broad differences in the ionization of pharmaceutical chemicals and chemicals with either near-field (in the home) or far-field sources. The utility of these high-throughput ionization predictions was evaluated via a case-study of predicted PK Vdss for 22 compounds monitored in the blood and serum of the U.S. population by the U.S. Centers for Disease Control and Prevention National Health and Nutrition Examination Survey (NHANES). The chemical distribution ratio between water and tissue was estimated using predicted ionization states characterized by pKa. Probability distributions corresponding to ionizable atom types (IATs) were then used to analyze the sensitivity of predicted Vdss on predicted pKa using Monte Carlo methods. 8 of the 22 compounds were predicted to be ionizable. For 5 of the 8 the predictions based upon ionization are significantly different from what would be predicted for a neutral compound. For all but one (foramsulfuron), the probability distribution of predicted Vdss generated by IAT sensitivity analysis spans both the neutral prediction and the prediction using ionization. As new data sets of chemical-specific information on metabolism and excretion for hundreds of chemicals are being made available (e.g., Wetmore et al., 2015), high-throughput methods for calculating Vdss and tissue-specific PK distribution coefficients will allow the rapid construction of PK models to provide context for both biomonitoring data and high-throughput toxicity screening studies such as Tox21 and ToxCast.

Use of Pharmacokinetic Data Under the FDA's Redbook II Guidelines for Direct Food Additives

Experience with food additive petitions submited after publication of the Food and Drug Administration's Redbook I (U. S. FDA, 1982) guide lines indicated a number of areas in which improvements were needed, and advances in toxicol-ogy testing during the last decade required additional rev is ions. In March 1993, the FDA's Center for Food Safety and Applied Nutrition (CFSAN) distributed copies of a draft of Redbook II for public comment. Since that time, revisions have been made based on comments received on the initial draft. This article describes the rationale for Redbook II guidance on the design of pharm acoki-netic studies and discusses some common problems the FDA has encountered in reviewing pharmacokine tic data submitted as part of food additive petitions. Points emphasized are that (1) pharmaco kinetic information is needed for the interpretation of toxicity studies and is most use ful when conducted before major toxicity studies, (2) the use of whole-body autoradiography is encouraged as a means to select tissues of interest, and as a substitute for dissection and tis-sue sampling, (3) kinetic and mechanistic studies conducted with blood compo-nents, tissue slices, hepatocytes, and othercell types in vitro ofien provide more useful information on the fate of chemicals in specific tissues than information extracted from whole-animal studies. The intention of th e new guide lines for pharmaco kinetic studies is to increase the information content of data gathered and to encourage the use of pharmaco kinetic models and results in the selection of doses for subchronic, chronic, and developmental toxicity studies.

A review of environmental and occupational exposure to xylene and its health concerns

Xylene is a cyclic hydrocarbon, and an environmental pollutant. It is also used in dyes, paints, polishes, medical technology and different industries as a solvent. Xylene easily vaporizes and divides by sunlight into other harmless chemicals. The aim of the present review is to collect the evidence of the xylene toxicity, related to non-cancerous health hazards, as well as to provide possible effective measurement to minimize its risk ratio. For current study a bibliographic search of more than 250 peer-reviewed papers in scientific data including PubMed, and Google Scholar about xylene was done. But approximately 130 peer-reviewed papers relevant to xylene were included (Figure 1(Fig. 1)). All scientific data was reviewed with key words of "xylene toxicity", "xylene toxic health effects", "environmental volatile organic compounds", "human exposure to xylene", "xylene poisoning in laboratory workers", "effects of xylene along with other hydrocarbons", "neurotoxicity of selected hydrocarbons", and "toxic effects of particular xylene isomers in animals". According to these studies, xylene is released into the atmosphere as fugitive emissions from petrochemical industries, fire, cigarette, from different vehicles. Short term exposure to mixed xylene or their individual isomers result in irritation of the nose, eyes and throat subsequently leading toward neurological, gastrointestinal and reproductive harmful effects. In addition long term exposure to xylene may cause hazardous effects on respiratory system, central nervous system, cardiovascular system, and renal system. The health concerns of xylene are well documented in animals and human. It is important to improve health policies, launch xylene related health and toxicity awareness campaigns, to get rid of its dangerous outcomes. Chronic diseases have become a threat to human globally, with special prominence in regions, where xylene is used with other chemicals (benzene, toluene etc.) especially in petroleum and rubber industry. The mechanism of toxicity and interactions with endocrine system should be followed up which is the main threat to human health.

Analysis of the distribution of organic compounds and drugs between biological tissues in the framework of solute partitioning in aqueous two-phase systems

Distribution of organic compounds between different biological tissues may be considered in the framework of solute partitioning in aqueous two-phase systems.

A review of environmental and occupational exposure to xylene and its health concerns

Xylene is a cyclic hydrocarbon, and an environmental pollutant. It is also used in dyes, paints, polishes, medical technology and different industries as a solvent. Xylene easily vaporizes and divides by sunlight into other harmless chemicals. The aim of the present review is to collect the evidence of the xylene toxicity, related to non-cancerous health hazards, as well as to provide possible effective measurement to minimize its risk ratio. For current study a bibliographic search of more than 250 peer-reviewed papers in scientific data including PubMed, and Google Scholar about xylene was done. But approximately 130 peer-reviewed papers relevant to xylene were included (Figure 1(Fig. 1)). All scientific data was reviewed with key words of "xylene toxicity", "xylene toxic health effects", "environmental volatile organic compounds", "human exposure to xylene", "xylene poisoning in laboratory workers", "effects of xylene along with other hydrocarbons", "neurotoxicity of selected hydrocarbons", and "toxic effects of particular xylene isomers in animals". According to these studies, xylene is released into the atmosphere as fugitive emissions from petrochemical industries, fire, cigarette, from different vehicles. Short term exposure to mixed xylene or their individual isomers result in irritation of the nose, eyes and throat subsequently leading toward neurological, gastrointestinal and reproductive harmful effects. In addition long term exposure to xylene may cause hazardous effects on respiratory system, central nervous system, cardiovascular system, and renal system. The health concerns of xylene are well documented in animals and human. It is important to improve health policies, launch xylene related health and toxicity awareness campaigns, to get rid of its dangerous outcomes. Chronic diseases have become a threat to human globally, with special prominence in regions, where xylene is used with other chemicals (benzene, toluene etc.) especially in petroleum and rubber industry. The mechanism of toxicity and interactions with endocrine system should be followed up which is the main threat to human health.

Toxicokinetic Model Development for the Insensitive Munitions Component 2,4-Dinitroanisole

The Armed Forces are developing new explosives that are less susceptible to unintentional detonation (insensitive munitions [IMX]). 2,4-Dinitroanisole (DNAN) is a component of IMX. Toxicokinetic data for DNAN are required to support interpretation of toxicology studies and refinement of dose estimates for human risk assessment. Male Sprague-Dawley rats were dosed by gavage (5, 20, or 80 mg DNAN/kg), and blood and tissue samples were analyzed to determine the levels of DNAN and its metabolite 2,4-dinitrophenol (DNP). These data and data from the literature were used to develop preliminary physiologically based pharmacokinetic (PBPK) models. The model simulations indicated saturable metabolism of DNAN in rats at higher tested doses. The PBPK model was extrapolated to estimate the toxicokinetics of DNAN and DNP in humans, allowing the estimation of human-equivalent no-effect levels of DNAN exposure from no-observed adverse effect levels determined in laboratory animals, which may guide the selection of exposure limits for DNAN.

Toxicokinetic Model Development for the Insensitive Munitions Component 3-Nitro-1,2,4-Triazol-5-One

3-Nitro-1,2,4-triazol-5-one (NTO) is a component of insensitive munitions that are potential replacements for conventional explosives. Toxicokinetic data can aid in the interpretation of toxicity studies and interspecies extrapolation, but only limited data on the toxicokinetics and metabolism of NTO are available. To supplement these limited data, further in vivo studies of NTO in rats were conducted and blood concentrations were measured, tissue distribution of NTO was estimated using an in silico method, and physiologically based pharmacokinetic models of the disposition of NTO in rats and macaques were developed and extrapolated to humans. The model predictions can be used to extrapolate from designated points of departure identified from rat toxicology studies to provide a scientific basis for estimates of acceptable human exposure levels for NTO.

PBTK modelling platforms and parameter estimation tools to enable animal-free risk assessment: recommendations from a joint EPAA--EURL ECVAM ADME workshop

Information on toxicokinetics is critical for animal-free human risk assessment. Human external exposure must be translated into human tissue doses and compared with in vitro actual cell exposure associated to effects (in vitro-in vivo comparison). Data on absorption, distribution, metabolism and excretion in humans (ADME) could be generated using in vitro and QSAR tools. Physiologically-based toxicokinetic (PBTK) computer modelling could serve to integrate disparate in vitro and in silico findings. However, there are only few freely-available PBTK platforms currently available. And although some ADME parameters can be reasonably estimated in vitro or in silico, important gaps exist. Examples include unknown or limited applicability domains and lack of (high-throughput) tools to measure penetration of barriers, partitioning between blood and tissues and metabolic clearance. This paper is based on a joint EPAA--EURL ECVAM expert meeting. It provides a state-of-the-art overview of the availability of PBTK platforms as well as the in vitro and in silico methods to parameterise basic (Tier 1) PBTK models. Five high-priority issues are presented that provide the prerequisites for wider use of non-animal based PBTK modelling for animal-free chemical risk assessment.

Development of a decision tree to classify the most accurate tissue-specific tissue to plasma partition coefficient algorithm for a given compound

Physiologically based pharmacokinetic (PBPK) modeling is a tool used in drug discovery and human health risk assessment. PBPK models are mathematical representations of the anatomy, physiology and biochemistry of an organism and are used to predict a drug's pharmacokinetics in various situations. Tissue to plasma partition coefficients (Kp), key PBPK model parameters, define the steady-state concentration differential between tissue and plasma and are used to predict the volume of distribution. The experimental determination of these parameters once limited the development of PBPK models; however, in silico prediction methods were introduced to overcome this issue. The developed algorithms vary in input parameters and prediction accuracy, and none are considered standard, warranting further research. In this study, a novel decision-tree-based Kp prediction method was developed using six previously published algorithms. The aim of the developed classifier was to identify the most accurate tissue-specific Kp prediction algorithm for a new drug. A dataset consisting of 122 drugs was used to train the classifier and identify the most accurate Kp prediction algorithm for a certain physicochemical space. Three versions of tissue-specific classifiers were developed and were dependent on the necessary inputs. The use of the classifier resulted in a better prediction accuracy than that of any single Kp prediction algorithm for all tissues, the current mode of use in PBPK model building. Because built-in estimation equations for those input parameters are not necessarily available, this Kp prediction tool will provide Kp prediction when only limited input parameters are available. The presented innovative method will improve tissue distribution prediction accuracy, thus enhancing the confidence in PBPK modeling outputs.

Quantitative Property-Property Relationship for Screening-Level Prediction of Intrinsic Clearance of Volatile Organic Chemicals in Rats and Its Integration within PBPK Models to Predict Inhalation Pharmacokinetics in Humans

The objectives of this study were (i) to develop a screening-level Quantitative property-property relationship (QPPR) for intrinsic clearance (CL_int) obtained from in vivo animal studies and (ii) to incorporate it with human physiology in a PBPK model for predicting the inhalation pharmacokinetics of VOCs. CL_int, calculated as the ratio of the in vivo V_max (μmol/h/kg bw rat) to the K_m (μM), was obtained for 26 VOCs from the literature. The QPPR model resulting from stepwise linear regression analysis passed the validation step (R² = 0.8; leave-one-out cross-validation Q² = 0.75) for CL_int normalized to the phospholipid (PL) affinity of the VOCs. The QPPR facilitated the calculation of CL_int (L PL/h/kg bw rat) from the input data on log P_ow, log blood: water PC and ionization potential. The predictions of the QPPR as lower and upper bounds of the 95% mean confidence intervals (LMCI and UMCI, resp.) were then integrated within a human PBPK model. The ratio of the maximum (using LMCI for CL_int) to minimum (using UMCI for CL_int) AUC predicted by the QPPR-PBPK model was 1.36 ± 0.4 and ranged from 1.06 (1,1-dichloroethylene) to 2.8 (isoprene). Overall, the integrated QPPR-PBPK modeling method developed in this study is a pragmatic way of characterizing the impact of the lack of knowledge of CL_int in predicting human pharmacokinetics of VOCs, as well as the impact of prediction uncertainty of CL_int on human pharmacokinetics of VOCs.

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.

Linking fate model in freshwater and PBPK model to assess human internal dosimetry of B(a)P associated with drinking water

In the present study, we demonstrate an integrated modeling approach for predicting internal tissue concentrations of chemicals by coupling a multimedia environmental model and a generic physiologically based pharmacokinetic (PBPK) model. A case study was designed for a region situated on the Seine river watershed, downstream of the Paris megacity, and for benzo(a)pyrene emitted from industrial zones in the region. In this case study, these two models are linked only by water intake from riverine system for the multimedia model into human body for the PBPK model. The limited monitoring data sets of B(a)P concentrations in bottom sediment and in raw river water, obtained at the downstream of Paris, were used to re-construct long-term daily concentrations of B(a)P in river water. The re-construction of long-term series of B(a)P level played a key role for the intermediate model calibration (conducted in multimedia model) and thus for improving model input to PBPK model. In order to take into account the parametric uncertainty in the model inputs, some input parameters relevant for the multimedia model were given by probability density functions (PDFs); some generic PDFs were updated with site-specific measurements by a Bayesian approach. The results of this study showed that the multimedia model fits well with actual annual measurements in sediments over one decade. No accumulation of B(a)P in the organs was observed. In conclusion, this case study demonstrated the feasibility of a full-chain assessment combining multimedia environmental predictions and PBPK modeling, including uncertainty and sensitivity analyses.

QSARs for PBPK modelling of environmental contaminants

Physiologically-based pharmacokinetic (PBPK) models are increasingly finding use in risk assessment applications of data-rich compounds. However, it is a challenge to determine the chemical-specific parameters for these models, particularly in time- and resource-limiting situations. In this regard, SARs, QSARs and QPPRs are potentially useful for computing the chemical-specific input parameters of PBPK models. Based on the frequency of occurrence of molecular fragments (CH(3), CH(2), CH, C, C=C, H, benzene ring and H in benzene ring structure) and exposure conditions, the available QSAR-PBPK models facilitate the simulation of tissue and blood concentrations for some inhaled volatile organic chemicals. The application domain of existing QSARs for developing PBPK models is limited, due to lack of relevant data for diverse chemicals and mechanisms. Even though this approach is conceptually applicable to non-volatile and high molecular weight organics as well, it is more challenging to predict the other PBPK model parameters required for modelling the kinetics of these chemicals (particularly tissue diffusion coefficients, association constants for binding and oral absorption rates). As the level of our understanding of the mechanistic basis of toxicokinetic processes improves, QSARs to provide a priori predictions of key chemical-specific PBPK parameters can be developed to expedite the internal dose-based health risk assessments in data-poor situations.

Toxicokinetic Considerations in Predicting Toxicity

The ability of a compound to elicit a toxic effect within an organism is dependent upon three factors (i) the external exposure of the organism to the toxicant in the environment or via the food chain (ii) the internal uptake of the compound into the organism and its transport to the site of action in sufficient concentration and (iii) the inherent toxicity of the compound. The in silico prediction of toxicity and the role of external exposure have been dealt with in other chapters of this book. This chapter focuses on the importance of ‘internal exposure’ i.e. the absorption, distribution, metabolism and elimination (ADME) properties of compounds which determine their toxicokinetic profile. An introduction to key concepts in toxicokinetics will be provided, along with examples of modelling approaches and software available to predict these properties. A brief introduction will also be given into the theory of physiologically-based toxicokinetic modelling.

A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals

The algorithms in the literature focusing to predict tissue:blood PC (P(tb)) for environmental chemicals and tissue:plasma PC based on total (K(p)) or unbound concentration (K(pu)) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P(tb), K(p) and K(pu) for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such a way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P(tb), K(p) or K(pu) of muscle (n=174), liver (n=139) and adipose tissue (n=141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.

Biokinetic modeling and in vitro-in vivo extrapolations

The introduction of in vitro methodologies in the toxicological risk assessment process requires a number of prerequisites regarding both the toxicodynamics and the biokinetics of the compounds under study. In vitro systems will need to be relevant for measuring those structural and physiological changes that are good indicators for adverse effects. Furthermore, the dose metric found to have an effect in the in vitro system should be relevant. One element in defining the appropriate dose metric is related to the kinetic behavior of the compound in the in vitro system: binding to proteins, binding to plastic, evaporation, and the interaction between the culture medium and the cells. Ways to measure and model "in vitro biokinetics" are described. Second, the appropriate dose metric in vitro, e.g., the effective concentration, will need to be extrapolated to relevant in vivo exposure scenarios. The application of physiologically based biokinetic modelling is essential in such extrapolations. The parameters needed to build these models often can be estimated based on nonanimal data, namely chemical properties (QSARs) and in vitro experiments.

Physiological modeling and derivation of the rat to human toxicokinetic uncertainty factor for the carbamate pesticide aldicarb

Aldicarb (ALD, 2-methyl-2-(methylthio)-propionalaldehyde O-(methyl-carbamoyl) oxime, Temik) is widely used as an insecticide, nematocide and acaricide and it is oxidized to aldicarb sulfoxide (ALX) and aldicarb sulfone (ALU). Neither a toxicokinetic model nor an estimate of the target tissue dose of ALD and its metabolites in exposed organisms is available. The objective of this study was: (i) to develop a physiologically based toxicokinetic (PBTK) model for ALD in the rat and humans, and (ii) to determine the interspecies toxicokinetic uncertainty factor (UF(AH-TK)) of ALD. The model consists of a series of mass balance differential equations that describe the time course behavior of ALD in blood, liver, kidney, lungs, brain, fat, and rest of the body compartments. The physiological parameters of the model (blood flow rates, cardiac output, and tissue volumes) were obtained from the literature, while the maximum velocity (mg/kg/min) and the Michaelis constant (mg/l) for ALD oxidation in rats and humans were determined by in vitro AH-TK microsomal assays. The estimation of the tissue:blood partition coefficient was accomplished within the PBTK model by representing the tissues as a composite of neutral lipids, phospholipids and water, and providing the vegetable oil:water partition coefficient as input parameter. The validity of the rat PBTK model was assessed by comparing the model simulations of ALX time course blood concentrations and the inhibition patterns of acetylcholinesterase (AChE) in erythrocytes and plasma obtained by administering rats ALD (0.1 and 0.4 mg/kg, iv). The human PBTK model was validated by comparing the simulations of AChE inhibition patterns in blood with human experimental data obtained from oral administrations of ALD. The UF(AH-TK) for ALD was determined by dividing the areas under the blood and brain concentration vs time curve (AUCCV, AUCCBR) for ALD and ALX in the rat and in human exposed to the same dose. The results indicate that with respect to parent chemical, equivalent applied doses in rats and humans result in a 9.5-fold difference in the AUC(CV) and AUC(AH-TK) respectively, in the two species, and 17-fold difference in the AUC(CV) and AUC(CBR) with respect to the metabolite. In other words, in order to have toxicokinetic equivalence in rats and humans, the former species must be exposed to a dose that is 9.5 and 17 times higher than the human with respect to the parent chemical and the metabolite respectively. Overall, the present study demonstrates the applicability of PBTK models in the quantitative evaluation of UH(AH-TK), and shows that their current default values are inaccurate, at least with respect to ALD, which has potential negative implications in the alleged protection of risk estimates derived from them.

A simulation model for the prediction of tissue:plasma partition coefficients for drug residues in natural casings

Tissue residues arise from the exposure of animals to undesirable substances in animal feed materials and drinking water and to the therapeutic or zootechnical use of veterinary medicinal products. In the framework of this study, an advanced toxicokinetic model was developed to predict the likelihood of residue disposition of licensed veterinary products in natural casings used as envelope for a variety of meat products, such as sausages. The model proved suitable for the calculation of drug concentrations in the muscles of pigs, cattle and sheep, the major species of which intestines are used. On the basis of drug concentrations in muscle tissue, the model allowed a prediction of intestinal concentrations and residues in the intestines that remained equal to or below the concentrations in muscle tissue, the major consumable product of slaughter animals. Subsequently, residues in intestines were found to be below the maximum residue limit value for muscle tissue when drugs were used according to prescribed procedures, including the application of appropriate withdrawal times. Considering the low consumption of natural casings (which represents only about 1-2% of the weight of a normal sausage), it was concluded that the exposure to drug residues from casings is negligible.

Permeation of tecnazene through human skin in vitro as assessed by HS-SPME and GC-MS

Permeation of tecnazene into and through human cadaver skin in vitro was assessed using a CC-MS method employing HS-SPME for receptor solution analyses. Two doses of tecnazene dissolved in acetone, corresponding to 103 and 864 microg/cm2 of tecnazene, were applied to skin mounted on Franz diffusion cells and placed in a fume hood. Cells were either occluded with aluminum foil or left unoccluded. Total absorption of tecnazene (dermis + receptor fluid) after 48 h was 2.2-6.1% of the applied dose for the unoccluded treatments and 22-33% for the occluded treatments. Potentially absorbed dose including all tecnazene that may have eventually permeated the skin ranged from 10% unoccluded to 42-53% occluded. Accumulation in the receptor solutions was satisfactorily described by a working diffusion model after upward adjustment of the partition coefficient for tecnazene in all skin layers by a factor of 5-16 versus a priori values. However, residual amounts of tecnazene in both the epidermis and dermis were higher than those estimated from the model, suggesting the existence of tissue binding not accounted for in the calculation. The results indicate that the diffusion model as presently calibrated may significantly underestimate both systemic absorption and skin concentrations of highly lipophilic compounds, as predicted from data generated from in vitro skin permeation assays. Model predictions could be improved by better accounting for partitioning into the epidermis and dermis.

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.

Physiologically based pharmacokinetic modeling of persistent organic pollutants for lifetime exposure assessment: a new tool in breast cancer epidemiologic studies

BACKGROUND

Despite experimental evidence, most epidemiologic studies to date have not supported an association between exposure to persistent organic pollutants (POP) and breast cancer incidence in humans. This may be attributable to difficulties in estimating blood/tissue POP concentration at critical time periods of carcinogenesis.

OBJECTIVES

In this work we aimed to develop a tool to estimate lifetime POP blood/tissue exposure and levels during any hypothesized time window of susceptibility in breast cancer development.

METHODS

We developed a physiologically based pharmacokinetic (PBPK) model that can account for any given physiologic lifetime history. Using data on pregnancies, height, weight, and age, the model estimates the values of physiologic parameters (e.g., organ volume, composition, and blood flow) throughout a woman's entire life. We assessed the lifetime toxicokinetic profile (LTP) for various exposure scenarios and physiologic factors (i.e., breast-feeding, growth, pregnancy, lactation, and weight changes).

RESULTS

Simulations for three POPs [hexachlorobenzene, polychlorinated biphenyl (PCB)-153, PCB-180] using different lifetime physiologic profiles showed that the same blood concentration at 55 years of age can be reached despite totally different LTP. Aside from exposure levels, lactation periods and weight profile history were shown to be the factors that had the greatest impact on the LTP.

CONCLUSIONS

This new lifetime PBPK model, which showed the limitations of using a single sample value obtained around the time of diagnosis for lifetime exposure assessment, will enable researchers conducting environmental epidemiology studies to reduce uncertainty linked to past POP exposure estimation and to consider exposure during time windows that are hypothesized to be mechanistically critical in carcinogenesis.

An integrated QSPR-PBPK modelling approach for in vitro-in vivo extrapolation of pharmacokinetics in rats

In vitro data on metabolism and partitioning may be integrated within physiologically-based pharmacokinetic (PBPK) models to provide simulations of the kinetics and bioaccumulation of chemicals in intact organisms. Quantitative structure-property relationship (QSPR) modelling of available in vitro data may be performed to predict metabolism rates and partition coefficients (PCs) for developing in vivo PBPK models. The objective of the present study was to develop an integrated QSPR-PBPK modelling approach for the conduct of in vitro to in vivo extrapolation. For this purpose, data on rat blood:air (P(b)) and fat:air (P(f)) PCs, as well as intrinsic metabolic clearance (CL(int)) obtained using rat liver slices for some C(5)-C(10) volatile organic compounds (VOCs) were compiled from the literature. Multilinear additive QSPR models for P(f), P(b) and CL(int) were developed based on the number and nature of molecular fragments in these VOCs (CH(3), CH(2), CH, C, C=C, H, benzene ring and H in benzene ring structure). The mean estimated/experimental (est/exp) ratios (+/-SD; range) were 1.0 (+/-0.04; 0.93 - 1.06) for log P(f), 1.08 (+/-0.26; 0.70 - 1.62) for log P(b), and 1.07 (+/- 0.21; 0.80 - 1.44) for CL(int). By accounting for the difference in the content of neutral lipids in fat and other tissues, the liver : air and muscle : air PCs of the compounds investigated in this study, with the excerption of n-decane, were adequately predicted from P(f). Integrating the QSPRs for P(f), P(b) and CL(int) within a rat PBPK model, simulations of inhalation pharmacokinetics of several VOCs were generated on the basis of molecular structure, for a given exposure scenario. The integrated QSPR-PBPK model developed in this study is a potentially useful tool for predicting in vivo kinetics and bioaccumulation of chemicals in rats under poor data situations.

Approaches to acrylamide physiologically based toxicokinetic modeling for exploring child-adult dosimetry differences

Dietary exposure to acrylamide is common as a result of its formation during the cooking of carbohydrate foods. This leads to widespread human exposure in adults and children alike. Acrylamide is neurotoxic and is metabolized by cytochrome P-450 (CYP) 2E1 to a mutagenic epoxide, glycidamide. This article describes a modeling framework for assessing acrylamide and glycidamide dosimetry in rats and human adults and children. The challenges in building a physiologically based toxicokinetic (PBTK) model that is compatible with existing rat and human data are described, with an emphasis on calibration against the hemoglobin adduct database. This exploratory PBTK model was adapted to children by incorporating life-stage-specific parameters consistent with children's changing physiology and metabolic capacity for processes involved in acrylamide disposition in terms of CYP2E1, glutathione conjugation, and epoxide hydrolase. Monte Carlo analysis was used to simulate the distribution of internal doses to gain an initial understanding of the range of child/adult differences possible. This analysis suggests modest dosimetry differences between children and adults, with area-under-the-curve (AUC) doses for the 99th percentile child up to fivefold greater than the median adult for both acrylamide and glycidamide. Early life immaturities tended to exert a greater effect on acrylamide than glycidamide dosimetry because immaturities in CYP2E1 and glutathione counteract one another for glycidamide AUC, but both lead to greater acrylamide dose. The analysis points toward glutathione conjugation parameters as being particularly influential and uncertain in early life, making this a key area for future research.

Physiologically based modeling of the inhalation pharmacokinetics of ethylbenzene in B6C3F1 mice

A physiologically based pharmacokinetic (PBPK) model was developed for inhaled ethylbenzene (EB) in B6C3F1 mice. The mouse physiological parameters were obtained from the literature, but the blood:air and tissue:air partition coefficients were determined by vial equilibration technique. The maximal velocity for hepatic metabolism (Vmax) obtained from a previously published rat study was increased by a factor of approximately 3 to account for enzyme induction during repeated exposures. The Michaelis affinity constant (Km) for hepatic metabolism of EB, obtained from a previously published rat PBPK modeling study, was kept unchanged during single and repeated exposure scenarios. Hepatic metabolism alone could not adequately describe the clearance of EB from mouse blood. Additional metabolism was assumed to be localized in the lung. The parameters for pulmonary metabolism were obtained by optimization of PBPK model fits to kinetic data collected following exposures to 75-1000 ppm. The PBPK model successfully predicted all available blood and tissue concentration data in mice exposed to 75 or 750 ppm EB. Overall, the results indicate that the rate of EB clearance is markedly higher in B6C3F1 mice than rats or humans and exceeds the hepatic metabolism capacity. Available biochemical evidence is consistent with a significant role for pulmonary metabolism; however, the extent to which the extrahepatic metabolism is localized in the lung is unclear. Overall, the PBPK model developed for the mouse adequately simulated the blood and tissue kinetics of EB by accounting for its high rate of clearance.

Age-dependent partition coefficients for a mixture of volatile organic solvents in Sprague-Dawley rats and humans

The absorption, distribution, metabolism, and excretion of volatile organic compounds (VOCs) are critically determined by a few chemical-specific factors, notably their blood and tissue partition coefficients (PC) and metabolism. Age-specific values for PCs in rats have rarely been reported or utilized in pharmacokinetic modeling for predicting dosimetry in toxicity studies with rats progressing through their lifestages. A mixture of six VOCs (benzene, chloroform, methyl ethyl ketone, methylene chloride, trichloroethylene, and perchloroethylene) was used to determine blood:air and tissue:air PCs in rats at three different ages (postnatal d 10, 60 d, and 2 yr) and blood:air PCs in pediatric and adult human blood. No differences with age in human blood:air PCs for the six compounds were observed. Rat blood:air PCs increased with age varying with compound. Tissue:air PCs showed tissue-specific changes with age. Water-soluble methyl ethyl ketone showed no age-dependent differences. Partition coefficients, particularly the blood:air PC, are key determinants of the rodent and human blood concentrations; age-appropriate values improve the accuracy of pharmacokinetic model predictions of population variability and age-specific exposures.

Air to liver partition coefficients for volatile organic compounds and blood to liver partition coefficients for volatile organic compounds and drugs

Values of in vitro air to liver partition coefficients, K(liver), of VOCs have been collected from the literature. For 124 VOCs, application of the Abraham solvation equation to logK(liver) yielded a correlation equation with R(2)=0.927 and SD=0.26 log units. Combination of the logK(liver) values with logK(blood) values leads to in vitro blood to liver partition coefficients, as logP(liver) for VOCs; an Abraham solvation equation can correlate 125 such values with R(2)=0.583 and SD=0.23 log units. Values of in vivo logP(liver) for 85 drugs were collected, and were correlated with R(2)=0.522 and SD=0.42 log units. When the logP(liver) values for VOCs and drugs were combined, an Abraham solvation equation could correlate the 210 compounds with R(2)=0.544 and SD=0.32 log units. Division of the 210 compounds into a training set and a test set, each of 105 compounds, showed that the training equation could predict logP(liver) values with an average error of 0.05 and a standard deviation of 0.34 log units.

Evaluation of physiologically based pharmacokinetic models for use in risk assessment

Physiologically based pharmacokinetic (PBPK) models are sophisticated dosimetry models that offer great flexibility in modeling exposure scenarios for which there are limited data. This is particularly of relevance to assessing human exposure to environmental toxicants, which often requires a number of extrapolations across species, route, or dose levels. The continued development of PBPK models ensures that regulatory agencies will increasingly experience the need to evaluate available models for their application in risk assessment. To date, there are few published criteria or well-defined standards for evaluating these models. Herein, important considerations for evaluating such models are described. The evaluation of PBPK models intended for risk assessment applications should include a consideration of: model purpose, model structure, mathematical representation, parameter estimation, computer implementation, predictive capacity and statistical analyses. Model purpose and structure require qualitative checks on the biological plausibility of a model. Mathematical representation, parameter estimation, computer implementation involve an assessment of the coding of the model, as well as the selection and justification of the physical, physicochemical and biochemical parameters chosen to represent a biological organism. Finally, the predictive capacity and sensitivity, variability and uncertainty of the model are analysed so that the applicability of a model for risk assessment can be determined. Published in 2007 by John Wiley & Sons, Ltd.

Physiologically-Based Toxicokinetic Modeling of Durene (1,2,3,5-Tetramethylbenzene) and Isodurene (1,2,4,5-Tetramethylbenzene) in Humans

OBJECTIVES

Physiologically-based toxicokinetic (PB-TK) models are developed to simulate absorption, distribution and excretion of xenobiotics. PB-TK models consist of several groups of compartments, where tissues are grouped together according to physiological parameters (tissue blood flows, tissue group volumes) and physicochemical properties (partition coefficients, metabolic constants). Tetramethylbenzene (TETMB), a mixture of its three isomers: prenitene (1,2,3,4-TETMB), isodurene (1,2,3,5-TETMB), and durene (1,2,4,5-TETMB) is an essential component of numerous commercial preparations of organic solvents. The aim of the study was to develop the PB-TK model for two TETMB isomers, durene and isodurene, in humans.

MATERIALS AND METHODS

The assumed PB-TK model groups organs and tissues into five physiological compartments: fat tissue, muscles, organs, liver, and brain. The brain has been considered as a separate compartment due to the potential neurotoxicity of TETMB. Water/air, oil/air and blood/air partition coefficients for durene and isodurene were measured in vitro. Tissue/air partition coefficients were calculated from values of olive/air and water/air partition coefficients and the average fat and water content in different tissues. Tissue/blood partition coefficients were calculated as a tissue/air quotient and the blood/air partition coefficient measured in vitro. The Michaelis-Menten constant (KM) values and maximum metabolism rate constant (VMAX) for selected metabolites of durene and isodurene were obtained in vitro using microsomal fraction of the human liver.

RESULTS

The developed model was validated against experimental data obtained earlier as a result of an 8-h exposure of volunteers to durene and isodurene vapors of 10 and 25 mg/m3. The prediction of both TETMB isomers concentration in blood as well as of the elimination rates of 2,4,5-TMBA and 2,3,5-TMBA were close to the results of experimental exposures.

CONCLUSIONS

Simulations of one working week inhalation exposure to aromatic hydrocarbons indicate that the elaborated PB-TK model may be used to predict the chemical distribution in different body compartments, based on physicochemical properties.

Development of physiologically based toxicokinetic models for improving the human indoor exposure assessment to water contaminants: trichloroethylene and trihalomethanes

Generally, ingestion is the only route of exposure that is considered in the risk assessment of drinking water contaminants. However, it is well known that a number of these contaminants are volatile and lipophilic and therefore highly susceptible to being absorbed through other routes, mainly inhalation and dermal. The objective of this study was to develop physiologically based human toxicokinetic (PBTK) models for trihalomethanes (THM) and trichloroethylene (TCE) that will facilitate (1) the estimation of internal exposure to these chemicals for various multimedia indoor exposure scenarios, and (2) consideration of the impact of biological variability in the estimation of internal doses. Five PBTK models describing absorption through ingestion, inhalation and skin were developed for these contaminants. Their concentrations in ambient air were estimated from their respective tap water concentrations and their physicochemical characteristics. Algebraic descriptions of the physiological parameters, varying as a function of age, gender and diverse anthropometric parameters, allow the prediction of the influence of interindividual variations on absorbed dose and internal dosimetry. Simulations for various scenarios were done for a typical human (i.e., 70 kg, 1.7 m) as well as for humans of both genders varying in age from 1 to 90 years. Simulations show that ingestion contributes to less than 50% of the total absorbed dose or metabolized dose for all chemicals. This contribution to internal dosimetry, such as maximal venous blood concentrations (Cmax) and the area under the venous blood concentration time curve (AUC), decreases markedly (e.g., as low as 0.9% of Cmax for bromodichloromethane). The importance of this contribution varies mainly as a function of shower duration. Moreover, model simulations indicate that multimedia exposure is more elevated in children than adults (i.e., up to 200% of the adult internal dose). The models developed in this study allow characterization of the influence of the different routes of exposure and an improved estimation of the realistic multimedia exposure to volatile organic chemicals present in drinking water. Hence, such models will greatly improve health risk assessment for these chemicals.

Air to fat and blood to fat distribution of volatile organic compounds and drugs: Linear free energy analyses

Partition coefficients, K(fat), from air to human fat and to rat fat have been collected for 129 volatile organic compounds, VOCs. A linear free energy relationship, LFER, correlates the 129 values of log K(fat) with R(2)=0.958 and a standard deviation, S.D., of 0.194 log units. Use of training and test sets gives a predictive assessment of around 0.20 log units. Combination of log K(fat) with our previously listed values of log K(blood) enables blood/plasma to fat partition coefficients, as log P(fat), to be obtained for 126 VOCs. These values can be correlated with R(2)=0.847, S.D.=0.304 log units; the latter is also our assessment of the predictive capability of the LFER. Values of log P(fat) have been collected for 46 drugs, and can be fitted to an LFER with R(2)=0.811 and S.D.=0.355 log units. Unlike partition into brain or muscle, the data for VOCs and drugs cannot be combined. There are marked discrepancies for PCBs for which partition from blood/plasma into fat is very much less than that calculated from the data on VOCs or from the data on drugs.

Antinociceptive effects, metabolism and disposition of ketamine in ponies under target-controlled drug infusion

Ketamine is widely used as an anesthetic in a variety of drug combinations in human and veterinary medicine. Recently, it gained new interest for use in long-term pain therapy administered in sub-anesthetic doses in humans and animals. The purpose of this study was to develop a physiologically based pharmacokinetic (PBPk) model for ketamine in ponies and to investigate the effect of low-dose ketamine infusion on the amplitude and the duration of the nociceptive withdrawal reflex (NWR). A target-controlled infusion (TCI) of ketamine with a target plasma level of 1 microg/ml S-ketamine over 120 min under isoflurane anesthesia was performed in Shetland ponies. A quantitative electromyographic assessment of the NWR was done before, during and after the TCI. Plasma levels of R-/S-ketamine and R-/S-norketamine were determined by enantioselective capillary electrophoresis. These data and two additional data sets from bolus studies were used to build a PBPk model for ketamine in ponies. The peak-to-peak amplitude and the duration of the NWR decreased significantly during TCI and returned slowly toward baseline values after the end of TCI. The PBPk model provides reliable prediction of plasma and tissue levels of R- and S-ketamine and R- and S-norketamine. Furthermore, biotransformation of ketamine takes place in the liver and in the lung via first-pass metabolism. Plasma concentrations of S-norketamine were higher compared to R-norketamine during TCI at all time points. Analysis of the data suggested identical biotransformation rates from the parent compounds to the principle metabolites (R- and S-norketamine) but different downstream metabolism to further metabolites. The PBPk model can provide predictions of R- and S-ketamine and norketamine concentrations in other clinical settings (e.g. horses).

Analysis of algorithms predicting blood:air and tissue:blood partition coefficients from solvent partition coefficients for prevalent components of JP-8 jet fuel

Algorithms predicting tissue and blood partition coefficients (PCs) from solvent properties were compared to assess their usefulness in a petroleum mixture physiologically based pharmacokinetic/pharmacodynamic model. Measured blood:air and tissue:blood PCs for rat and human tissues were sought from literature resources for 14 prevalent jet fuel (JP-8) components. Average experimental PCs were compared with predicted PCs calculated using algorithms from 9 published sources. Algorithms chosen used solvent PCs (octanol:water, saline or water:air, oil:air coefficients) due to the relative accessibility of these parameters. Tissue:blood PCs were calculated from ratios of predicted tissue:air and experimental blood:air values (PCEB). Of the 231 calculated values, 27% performed within +/- 20% of the experimental PC values. Physiologically based equations (based on water and lipid components of a tissue type) did not perform as well as empirical equations (derived from linear regression of experimental PC data) and hybrid equations (physiological parameters and empirical factors combined) for the jet fuel components. The major limitation encountered in this analysis was the lack of experimental data for the selected JP-8 constituents. PCEB values were compared with tissue:blood PCs calculated from ratios of predicted tissue:air and predicted blood:air values (PCPB). Overall, 68% of PCEB values had smaller absolute % errors than PCPB values. If calculated PC values must be used in models, a comparison of experimental and predicted PCs for chemically similar compounds would estimate the expected error level in calculated values.

Human exposure and internal dose assessments of acrylamide in food

This review provides a framework contributing to the risk assessment of acrylamide in food. It is based on the outcome of the ILSI Europe FOSIE process, a risk assessment framework for chemicals in foods and adds to the overall framework by focusing especially on exposure assessment and internal dose assessment of acrylamide in food. Since the finding that acrylamide is formed in food during heat processing and preparation of food, much effort has been (and still is being) put into understanding its mechanism of formation, on developing analytical methods and determination of levels in food, and on evaluation of its toxicity and potential toxicity and potential human health consequences. Although several exposure estimations have been proposed, a systematic review of key information relevant to exposure assessment is currently lacking. The European and North American branches of the International Life Sciences Institute, ILSI, discussed critical aspects of exposure assessment, parameters influencing the outcome of exposure assessment and summarised data relevant to the acrylamide exposure assessment to aid the risk characterisation process. This paper reviews the data on acrylamide levels in food including its formation and analytical methods, the determination of human consumption patterns, dietary intake of the general population, estimation of maximum intake levels and identification of groups of potentially high intakes. Possible options and consequences of mitigation efforts to reduce exposure are discussed. Furthermore the association of intake levels with biomarkers of exposure and internal dose, considering aspects of bioavailability, is reviewed, and a physiologically-based toxicokinetic (PBTK) model is described that provides a good description of the kinetics of acrylamide in the rat. Each of the sections concludes with a summary of remaining gaps and uncertainties.

Physiologically Based Pharmacokinetic/Pharmacodynamic Model for the Organophosphorus Pesticide Diazinon

Diazinon (DZN) is an organophosphorus pesticide with the possibility for widespread exposures. The toxicological effects of DZN are primarily mediated through the effects of its toxic metabolite, DZN-oxon on acetylcholinesterases, which results in accumulation of acetylcholine at neuronal junctions. A physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model was developed to quantitatively assess the kinetics of DZN and its metabolites in blood and the inhibition of cholinesterases in plasma, RBC, brain, and diaphragm. Focused in vivo pharmacokinetic studies were conducted in male Sprague-Dawley rats and the data were used to refine the model. No overt toxicity was noted following doses up to 100mg/kg. However, cholinesterases in plasma, RBC, brain and diaphragm were substantially inhibited at doses of 50 mg/kg. In plasma, total cholinesterase was inhibited to less than 20% of control by 6 h post dosing with 100 mg/kg. Inhibition of brain acetylcholinesterase (AChE) following 100 mg/kg exposures was approximately 30% of control by 6 h. Diaphragm butyrylcholinesterase (BuChE) inhibition following 100 mg/kg dosing was to less than 20% of control by 6 h. The PBPK/PD model was used to describe the concentrations of DZN and its major, inactive metabolite, 2-isopropyl-4-methyl-6-hydroxypyrimidine (IMHP) in plasma and urinary elimination of IMHP. The fit of the model to plasma, RBC, brain, and diaphragm total cholinesterase and BuChE activity was also assessed and the model was further validated by fitting data from the open literature for intraperitoneal, intravenous, and oral exposures to DZN. The model was shown to quantitatively estimate target tissue dosimetry and cholinesterase inhibition following several routes of exposures. This model further confirms the usefulness of the model structure previously validated for chlorpyrifos and shows the potential utility of the model framework for other related organophosphate pesticides.

On the mechanism of drug-induced acceleration of phospholipid translocation in the human erythrocyte membrane

Small amphiphilic compounds (M(r)<200 Da) such as anaesthetics and hexane derivatives with different polar groups produced a concentration-dependent acceleration of the slow passive transbilayer movement of NBD-labelled phosphatidylcholine in the human erythrocyte membrane. Above a threshold concentration characteristic for each compound, the flip rate gradually increased at increasing concentrations in the medium. For compound concentrations required to produce a defined flip acceleration, corresponding membrane concentrations were estimated using reported octanol/water partition coefficients. The effective threshold membrane concentrations (50-150 mmol l(-1)) varied in the order: hexylamine>isoflurane=hexanoic acid>hexanol=chloroform>hexanethiol=1,1,2,2-tetrachloroethane>chlorohexane. Apolar hexane, which mainly distributes in the apolar membrane core, was much less effective and supersaturating concentrations were required to enhance flip. Localization of the drug at the lipid-water interface seems to be required for flip acceleration. Such a localization may increase the lateral pressure in this region and the bilayer curvature stress with concomitant decrease of order and rigidity at the interface. This unspecific bilayer perturbation is proposed to enhance the probability of formation of hydrophobic defects in the bilayer, facilitating penetration of the polar head group of the phospholipid into the apolar membrane core.

Whole body pharmacokinetic models

The aim of the current review is to summarise the present status of physiologically based pharmacokinetic (PBPK) modelling and its applications in drug research, and thus serve as a reference point to people interested in the methodology. The review is structured into three major sections. The first discusses the existing methodologies and techniques of PBPK model development. The second describes some of the most interesting PBPK model implementations published. The final section is devoted to a discussion of the current limitations and the possible future developments of the PBPK modelling approach. The current review is focused on papers dealing with the pharmacokinetics and/or toxicokinetics of medicinal compounds; references discussing PBPK models of environmental compounds are mentioned only if they represent considerable methodological developments or reveal interesting interpretations and/or applications.The major conclusion of the review is that, despite its significant potential, PBPK modelling has not seen the development and implementation it deserves, especially in the drug discovery, research and development processes. The main reason for this is that the successful development and implementation of a PBPK model is seen to require the investment of significant experience, effort, time and resources. Yet, a substantial body of PBPK-related research has been accumulated that can facilitate the PBPK modelling and implementation process. What is probably lagging behind is the expertise component, where the demand for appropriately qualified staff far outreaches availability.