Showing papers on "Physiologically based pharmacokinetic modelling published in 1997"
1,286 citations
TL;DR: The utility of PBPK models in the prediction of the kinetics of components of chemical mixtures, by accounting for mechanisms of binary chemical interactions, is demonstrated.
151 citations
TL;DR: Using stepwise regression, it was found that three simple structural descriptors were sufficient to predict adipose:plasma partition coefficients for all 209 PCB congeners, allowing for the calculation of tissue:blood partition coefficient for liver, skin, muscles, and fat for all209 PCB congener.
86 citations
TL;DR: The model predicts that topical application of tretinoin results in an internal exposure that is four to six orders of magnitude lower than a minimally teratogenic dose, resulting in a much lower internal exposure to active retinoids than was inferred from total radioactivity data.
Abstract: Background: A physiologically based pharmacokinetic (PBPK) model for all- trans -retinoic acid (tretinoin) was developed to provide a coherent description of tretinoin absorption, distribution, metabolism, and excretion across species and routes of administration. Objective: The goal of developing such a model is to provide a measure of internal dose that would be a biologically relevant surrogate for administered dose in assessing human teratogenic risk from topically applied tretinoin emollient cream. Methods: The developed PBPK model included compartments for plasma, liver, gut, intestinal lumen, fat, skin, richly and slowly perfused tissues, placenta, and embryo. Tretinoin metabolism to 13- cis retinoic acid, oxidation, and glucuronidation were incorporated. Dose surrogates, including the maximum plasma concentration (C
max ) and area under the concentration-versus-time curve were calculated from the model. Results: The ability of the model to predict tretinoin pharmacokinetics and to extrapolate across species and routes of administration was tested and validated. Model-derived estimates of dose surrogates demonstrated that the internal exposure to retinoids after topical treatment with 0.05% tretinoin emollient cream is minimal in comparison to that for teratogenic oral doses. The ratio of areas under the curve for total active retinoids after teratogenic oral doses in monkeys versus therapeutic topical doses in human beings, for example, was greater than 450,000 to 1. Conclusion: For topical application of tretinoin in human beings, detoxification via the glucuronidation pathway predominates, resulting in a much lower internal exposure to active retinoids than was inferred from total radioactivity data. The model predicts that topical application of tretinoin results in an internal exposure that is four to six orders of magnitude lower than a minimally teratogenic dose. (J Am Acad Dermatol 1997;36:S77-S85.)
66 citations
TL;DR: An improved PBPK model is developed to describe TCDD disposition in eight target tissues and illustrates the validity and the limitation of the model and provides further confirmation of the potential P BPK model for us in optimal experimental design and extrapolation across doses and routes of exposure.
64 citations
TL;DR: The concept of structural identifiability of a model, a requirement to make the estimation of parameters by calibration a meaningful undertaking, is introduced and some general results are given, indicating in what situations the first uniqueness condition either holds or does not.
Abstract: Physiologically based pharmacokinetic (PBPK) models usually contain unknown parameters that need to be estimated by calibration to concentration-time profiles from in vivo experiments. However, even with error-free data, the number of parameters that can be estimated in this way is limited, depending on the particular situation. This paper introduces the concept of structural identifiability of a model, a requirement to make the estimation of parameters by calibration a meaningful undertaking. We briefly discuss the techniques - available from systems analysis - for examining the identifiability of models. Two conditions of uniqueness are involved, one relating to the model's equations and its parameters, the other to the number of available observations in time. The assessment of the first uniqueness condition involves rather tedious matrix algebra, requiring the appropriate mathematical expertise. We therefore give some general results for a particular class of PBPK models, indicating in what situations the first uniqueness condition either holds or does not. The assessment of the second uniqueness condition does not require specialized skills, and the minimum number of observations in time necessary can be easily determined for any particular situation. The practical implications for both modeling strategies and experimental protocols are discussed.
57 citations
TL;DR: The overall sensitivity of the whole-body physiologically based pharmacokinetic (PBPK) model for the distribution kinetics of nine 5-n-alkyl-5-ethyl barbituric acids in arterial blood and 14 tissues is small and the computationally simple Matrix Perturbation Analysis should be used only when an initial idea about the sensitivity of a system is required.
Abstract: Sensitivity analysis studies the effects of the inherent variability and uncertainty in model parameters on the model outputs and may be a useful tool at all stages of the pharmacokinetic modeling process. The present study examined the sensitivity of a whole-body physiologically based pharmacokinetic (PBPK) model for the distribution kinetics of nine 5-n-alkyl-5-ethyl barbituric acids in arterial blood and 14 tissues (lung, liver, kidney, stomach, pancreas, spleen, gut, muscle, adipose, skin, bone, heart, brain, testes) after i.v. bolus administration to rats. The aims were to obtain new insights into the model used, to rank the model parameters involved according to their impact on the model outputs and to study the changes in the sensitivity induced by the increase in the lipophilicity of the homologues on ascending the series. Two approaches for sensitivity analysis have been implemented. The first, based on the Matrix Perturbation Theory, uses a sensitivity index defined as the normalized sensitivity of the 2-norm of the model compartmental matrix to perturbations in its entries. The second approach uses the traditional definition of the normalized sensitivity function as the relative change in a model state (a tissue concentration) corresponding to a relative change in a model parameter. Autosensitivity has been defined as sensitivity of a state to any of its parameters; cross-sensitivity as the sensitivity of a state to any other states' parameters. Using the two approaches, the sensitivity of representative tissue concentrations (lung, liver, kidney, stomach, gut, adipose, heart, and brain) to the following model parameters: tissue-to-unbound plasma partition coefficients, tissue blood flows, unbound renal and intrinsic hepatic clearance, permeability surface area product of the brain, have been analyzed. Both the tissues and the parameters were ranked according to their sensitivity and impact. The following general conclusions were drawn: (i) the overall sensitivity of the system to all parameters involved is small due to the weak connectivity of the system structure; (ii) the time course of both the auto- and cross-sensitivity functions for all tissues depends on the dynamics of the tissues themselves, e.g., the higher the perfusion of a tissue, the higher are both its cross-sensitivity to other tissues' parameters and the cross-sensitivities of other tissues to its parameters; and (iii) with a few exceptions, there is not a marked influence of the lipophilicity of the homologues on either the pattern or the values of the sensitivity functions. The estimates of the sensitivity and the subsequent tissue and parameter rankings may be extended to other drugs, sharing the same common structure of the whole body PBPK model, and having similar model parameters. Results show also that the computationally simple Matrix Perturbation Analysis should be used only when an initial idea about the sensitivity of a system is required. If comprehensive information regarding the sensitivity is needed, the numerically expensive Direct Sensitivity Analysis should be used.
40 citations
TL;DR: The use of Physiologically based pharmacokinetic models in risk assessment, the structural and parameter uncertainty in these models, and a simple illustration of how these characteristics can be incorporated in a statistical analysis of PBPK models are provided.
Abstract: Many extrapolation issues surface in quantitative risk assessments. The extrapolation from high-dose animal studies to low-dose human exposures is of particular concern. Physiologically based pharmacokinetic (PBPK) models are often proposed as tools to mitigate the problems of extrapolation. These models provide a representation of the disposition, metabolism, and excretion of xenobiotics that are believed to possess the potential of inducing adverse human health responses. Given a model of xenobiotic disposition that is applicable for multiple species and appropriate for nonlinearity of the xenobiotic biotransformation process, better extrapolation may be possible. Unfortunately, the true structure of these models (e.g. number of compartments, type of metabolism, etc.) is seldom known, and attributes of these models (tissue volumes, partition coefficients, etc.) are often experimentally determined and often only central measures of these quantities are reported. We describe the use of PBPK models in risk...
38 citations
TL;DR: Findings indicate that MTBE water concentrations of 1 mg/L or below are unlikely to trigger acute CNS effects during bathing and showering, however, MTBE's strong odor may be a secondary but deciding factor regarding the suitability of such water for domestic uses.
Abstract: Methyl t-butyl ether (MTBE) is a gasoline additive that has appeared in private wells as a result of leaking underground storage tanks. Neurological symptoms (headache, dizziness) have been reported from household use of MTBE-affected water, consistent with animal studies showing acute CNS depression from MTBE exposure. The current research evaluates acute CNS effects during bathing/showering by application of physiologically-based pharmacokinetic (PBPK) techniques to compare internal doses in animal toxicity studies to human exposure scenarios. An additional reference point was the delivered dose associated with the acute Minimum Risk Level (MRL) for MTBE established by the Agency for Toxic Substances and Disease Registry. A PBPK model for MTBE and its principal metabolite, t-butyl alcohol (TBA) was developed and validated against published data in rats and humans. PBPK analysis of animal studies showed that acute CNS toxicity after MTBE exposure can be attributed principally to the parent compound since the metabolite (TBA) internal dose was below that needed for CNS effects. The PBPK model was combined with an exposure model for bathing and showering which integrates inhalation and dermal exposures. This modeling indicated that bathing or showering in water containing MTBE at 1 mg/L would produce brain concentrations approximately 1000-fold below the animal effects level and twofold below brain concentrations associated with the acute MRL. These findings indicate that MTBE water concentrations of 1 mg/L or below are unlikely to trigger acute CNS effects during bathing and showering. However, MTBE's strong odor may be a secondary but deciding factor regarding the suitability of such water for domestic uses.
37 citations
TL;DR: Application of these PBPK models of pregnancy in laboratory animal models at teratogenically sensitive periods of development provides exposure values at specific target tissues that provide fundamentally important data to help design and interpret molecular probe investigations into mechanisms of teratogenesis.
Abstract: Physiologically based pharmacokinetic (PBPK) models for pregnancy are inherently more complex than conventional PBPK models due to the growth of the maternal and embryo/ fetal tissues. Physiological parameters such as compartmental volumes or flow rates are relatively constant at any particular time during gestation when an acute experiment might be conducted, but vary greatly throughout the course of gestation (e.g., contrast relative fetal weight during the first month of gestation with the ninth month). Maternal physiological parameters change during gestation, depending upon the particular system; for example, cardiac output increases by -50% during human gestation; plasma protein concentration decreases during pregnancy; overall metabolism remains fairly constant. Maternal compartmental volumes may change by 10–30% embryo/fetal volume increases over a billionfold from conception to birth. Data describing these physiological changes in the human are available from the literature. Human embryo...
36 citations
TL;DR: The studies reported here attempt to continue in the spirit of the new RfC guidelines by incorporating both mechanistic and delivered dose information using a physiologically based pharmacokinetic (PBPK) model, along with quantitative dose-response information using the benchmark dose (BMD) method, into the noncancer risk assessment paradigm.
Abstract: There has been relatively little attention given to incorporating knowledge of mode of action or of dosimetry of active toxic chemical to target tissue sites in the calculation of noncancer exposure guidelines. One exception is the focus in the revised reference concentration (RfC) process on delivered dose adjustments for inhaled materials. The studies reported here attempt to continue in the spirit of the new RfC guidelines by incorporating both mechanistic and delivered dose information using a physiologically based pharmacokinetic (PBPK) model, along with quantitative dose-response information using the benchmark dose (BMD) method, into the noncancer risk assessment paradigm. Two examples of the use of PBPK and BMD techniques in noncancer risk assessment are described: methylene chloride, and trichloroethylene. Minimal risk levels (MRLs) based on PBPK analysis of these chemicals were generally similar to those based on the traditional process, but individual MRLs ranged from roughly 10-fold higher to more than 10-fold lower than existing MRLs that were not based on PBPK modeling. Only two MRLs were based on critical studies that presented adequate data for BMD modeling, and in these two cases the BMD models were unable to provide an acceptable fit to the overall dose-response of the data, even using pharmacokinetic dose metrics. A review of 10 additional chemicals indicated that data reporting in the toxicological literature is often inadequate to support BMD modeling. Three general observations regarding the use of PBPK and BMD modeling in noncancer risk assessment were noted. First, a full PBPK model may not be necessary to support a more accurate risk assessment; often only a simple pharmacokinetic description, or an understanding of basic pharmacokinetic principles, is needed. Second, pharmacokinetic and mode of action considerations are a crucial factor in conducting noncancer risk assessments that involve animal-to-human extrapolation. Third, to support the application of BMD modeling in noncancer risk assessment, reporting of toxicity results in the toxicological literature should include both means and standard deviations for each dose group in the case of quantitative endpoints, such as relative organ weights or testing scores, and should report the number of animals affected in the case of qualitative endpoints.
TL;DR: A generalized PBPK model was developed to describe the disposition of xenobiotics in pregnancy, to examine specific mechanisms of nonlinear conceptal methanol disposition, and to expand the model to extrapolate to low-dose human exposures.
TL;DR: In this article, the authors developed a model of the toxicological interaction reported in rats receiving high oral doses of dichloromethane (DCM) and toluene (TOL), which was then used to assess the relevance of such rodent data on chemical interactions for humans.
TL;DR: This paper introduces a method whereby a minimal PBPK rat model can be produced without tissue sampling, which fits unrelated drugs, providing cross-species scaling of distribution volume from literature-based data.
TL;DR: Data of the present study indicate that the plasma ddI concentration-time profile in patients were better described by the ddI + pentamidine model than byThe ddI model, suggesting that the pentamazine-induced changes in tissue distribution of ddI observed in rats may also occur in humans.
Abstract: Purpose. The goal of this study was to develop physiologically based pharmacokinetic (PBPK) models for 2′,3′-dideoxyinosine (ddI) in rats when the drug was administered alone (ddI model) and with pentamidine (ddI + pentamidine model), and to use these models to evaluate the effect of our previously reported pentamidine-ddI interaction on tissue ddI exposure in humans.
TL;DR: Two new physiologically-based pharmacokinetic (PBPK) models are developed which predict the concentration of Dibromomethane in the blood of rats after dermal vapor exposure and could be a great improvement over previous models in the ability to extrapolate results for different species, doses, and durations.
Abstract: Understanding the absorption of chemicals through the skin is of importance to many fields of study. Biologically-based models can be used to simulate the absorption process and predict the rate of absorption and the amount of the chemical in various parts of the body and skin. When these models consist of physiological and biochemical parameters that can be measured, they can be extremely useful. When a model is appropriately validated, the results can be extrapolated across species to predict the effect of human exposure. In this paper we develop two new physiologically-based pharmacokinetic (PBPK) models which predict the concentration of Dibromomethane in the blood of rats after dermal vapor exposure. These two new models expand a previously developed homogeneous skin model by adding parallel skin subcompartments to represent skin appendages and layered subcompartments to represent the distinct layers of the skin. The predictions of these new models match the experimental data better than the...
TL;DR: The mathematical relations for the sensitivity of the embryo and effect functions on different organs are developed using a physiologically based pharmacokinetic model developed previously.
Abstract: A mathematical structure is described for determining teratogenic sensitivity or susceptibility from analysis of malformation incidence, dose-response, and pharmacokinetic data obtained during pregnancy as a result of exposure to a teratogenic agent. From the dosage or exposure of laboratory animals, embryonic and maternal concentrations of the xenobiotic are calculated using a physiologically based pharmacokinetic (PBPK) model. Malformations observed in the progeny are linked to the PBPK-derived target tissue concentrations with a model for the sensitivity calculated as a function of the embryonic age. The PBPK model for internal disposition of chemicals during pregnancy was developed previously. This report focuses on the development of the mathematical relations for the sensitivity of the embryo and effect functions on different organs. The concentrations of a xenobiotic calculated for the site of action or target tissue(s) in the embryo are weighted using both a nonlinear dose-response curve and a sensitivity distribution function that depends on the age or stage of development of the embryo. This weighted "exposure" of the target tissue is regressed with the number of observed malformations to quantify the parameters of the model. This approach lends itself to integration of diverse sources of experimental data, with hydroxyurea data taken from several sources in the literature as an example. This sensitivity function obtained from laboratory animal data serves as a vehicle for prediction and extrapolation to human pregnancy for the teratogenic potential of a substance.
TL;DR: Although their development has proven to be complex, biologically based dose-response models have the potential to form the basis for a broader understanding of mechanisms of developmental toxicity and for broad predictive utility in developmental toxicity.
01 Sep 1997
TL;DR: To provide a tool potentially useful for risk characterization of pro-oxidant chemicals, a quantitative mathematical model describing biological effects within the target organ was constructed in a way compatible with traditional pharmacokinetic models which describe the internal, local dose of a chemical.
Abstract: : Health risk from chemicals depends on both the extent of exposure and a dose-response relationship, which is reflecting, in turn, the mode of action of chemicals. For quantitative modeling of the mode of action it is necessary to determine the exact chain of events of the chemical interaction with the biological system. To provide a tool potentially useful for risk characterization of pro-oxidant chemicals, a quantitative mathematical model (physiologically based pharmacodynamic or PBPD model) describing biological effects within the target organ was constructed In a way compatible with traditional pharmacokinetic (PBPK) models which describe the internal, local dose of a chemical. Based on the available literature and our own experimental data, the three basic modes of action of pro-oxidant chemicals were modeled and simulated in silico: i. lipid peroxidation (expressed by the formation of thiobarbituric acid reactive substance (TBARS) and the exhalation of ethane); ii. specific interaction of free radicals with homogenous cellular targets; and iii. random interaction of free radicals with multiple cellular targets. Based on the dose-response characteristic verified in vitro, a PBPD model of chemically initiated oxidative stress was developed and calibrated in B6C3Fl mice. The model consisted of three major modules. At first, a biologically based module for chemically induced lipid peroxidation was developed and calibrated in vitro using precision cut mouse liver slices. Next, the parameters describing the mechanism of action of pro-oxidant chemicals were applied to the physiologically based pharmacodynamic module describing chemically induced lipid peroxidation in mice in vivo.
TL;DR: A mathematical model was found that consistently described diverse pharmacokinetics data for a development compound from three pharmacokinetic studies in healthy volunteers and two efficacy and safety studies in patients.
Abstract: A mathematical model was found that consistently described diverse pharmacokinetic data for a development compound from three pharmacokinetic studies in healthy volunteers and two efficacy and safety studies in patients. The model provided: quantification of demographic and random sources of pharmacokinetic variability; estimation of important pharmacokinetic parameters from sparse data; and explanation of observed patterns of pharmacokinetic response.
30 Oct 1997
TL;DR: A generic model for the interactions of ligands (dioxins, polyaromatic hydrocarbons) with the Ah-receptor in the cell was developed and incorporated in a Physiologically Based PharmacoKinetic (PBPK) model of the rat, which was calibrated and validated for TCDD.
Abstract: The interspecies extrapolation of chemical toxicity is traditionally based on the daily administered dose of the chemical. However, in the case of compounds with strong bioaccumulating properties, such as 2,3,7,8-TetraChloroDibenzo-p-Dioxin (TCDD), chronic toxicity is expected to scale better with the amount of TCDD in the body than with the daily administered dose. In order to use the amount of TCDD in the body as the starting point for the extrapolation of TCDD toxicity quantification is needed of the accumulation of TCDD in the body. In order to incorporate the disposition mechanism into the safety evaluation of TCDD we developed a generic model for the interactions of ligands (dioxins, polyaromatic hydrocarbons) with the Ah-receptor in the cell. This cellular model contains the binding of the ligand to the Ah-receptor, the binding of the ligand-Ah-receptor complex to specific DNA binding domains (Xenobiotic Responsive Elements (XRE)), Ah-receptor dependent de novo P450 synthesis and the binding of the ligand to induced P450 proteins together with their metabolism. The Ah-receptor/P450 induction model was incorporated in a Physiologically Based PharmacoKinetic (PBPK) model of the rat. This rat PBPK model was calibrated and validated for TCDD. The PBPK model presented here will be scaled from the rat to man. The human PBPK model will be used to calculate a safe human exposure level to TCDD. This exposure level, which is presented in a separate report, will be compared with the Tolerable Daily Intake of TCDD as calculated with similar modeling techniques by WHO and, more recently, the Health Council of the Netherlands.