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.     

Sensitivity analysis for physiologically based pharmacokinetic models

The present study evaluates the sensitivity of pharmacokinetic model output to variability in the biochemical and metabolic input parameters. Pharmacokinetic models of three chemicals are chosen for analysis: styrene, methylchloroform, and methylene chloride. Results show that model sensitivities are time-, dose-, and species-dependent and that the most sensitive parameters are the maximum Michaelis-Menten metabolism rate Vmax and the blood/air and fat/air partition coefficients. For humans, the muscle/air partition coefficient is also important. Model output is insensitive to the Michaelis-Menten parameter Km (except for low doses) and to other tissue/air partition coefficients.     

Sensitivity analysis for physiologically based pharmacokinetic models

The present study evaluates the sensitivity of pharmacokinetic model output to variability in the biochemical and metabolic input parameters. Pharmacokinetic models of three chemicals are chosen for analysis: styrene, methylchloroform, and methylene chloride. Results show that model sensitivities are time-, dose-, and species-dependent and that the most sensitive parameters are the maximum Michaelis-Menten metabolism rate V_max and the blood/air and fat/air partition coefficients. For humans, the muscle/air partition coefficient is also important. Model output is insensitive to the MichaelisMenten parameter K _m (except for low doses) and to other tissue/air partition coefficients.Although the research described in this article has been funded wholly or in part by the U.S. Environmental Protection Agency through Interagency Agreement No. IAG DW89932633-01-0 to Martin Marietta Energy Systems, Inc., it has not been subjected to Agency policy review and therefore does not necessarily reflect the views of the Agency.     

Clearance constants in physiologically based pharmacokinetic models.

The intrinsic clearance of an organ is usually approximated by the apparent clearance from that organ in the development of a physiologically based pharmacokinetic model. In this study, the exact relationship between the two clearances was derived and analyzed. When the extraction ratio of the drug was small (less than 0.05), the approximation was reasonable. However, when the extraction ratio was high (greater than 0.2), serious errors could be made by using the approximation. These errors could be as much as 50% reduction in the estimated extraction ratio and as much as an order-of-magnitude difference in the intrinsic clearance.     

生理药代动力学模型在药物基因组学中的应用

生理药代动力学模型作为药代动力学的新兴工具,可以有效用于表征各种情况下由基因组学多态性导致的体内药动学变化.本文介绍生理药代动力学模型在药物基因组学研究中的基本原理并讨论其适用性,从I相代谢酶、II相代谢酶和转运体的基因多态性角度总结了模型的应用情况,以期了解药物基因组学的新型研究手段,为促进药物临床应用和提高药物研发...     

Evaluation of a generic physiologically based pharmacokinetic model for lineshape analysis

BACKGROUND and objective: The mechanistic framework of physiologically based pharmacokinetic (PBPK) models makes them uniquely suited to hypothesis testing and lineshape analysis, which help provide valuable insights into mechanisms that contribute to the observed concentration-time profiles. The aim of this article is to evaluate the utility of PBPK models for simulating oral lineshapes by optimizing clearance and distribution parameters through fitting observed intravenous pharmacokinetic profiles. METHODS: A generic PBPK model, built in-house using MATLAB software and incorporating absorption, metabolism, distribution, biliary and renal elimination models, was employed for simulation of the concentration-time profiles of nine marketed drugs with diverse physicochemical and pharmacokinetic profiles and absorption rates determined solely by transcellular or paracellular permeability and solubility. The model is based on easily available physicochemical properties of compounds such as the log P, acid dissociation constant and solubility, and in vitro pharmacokinetic data such as Caco-2 permeability, the fraction of the compound unbound in plasma, and microsomal or hepatocyte intrinsic clearance. Clearance and distribution parameters optimized through simulation of intravenous profiles were used to simulate their corresponding oral profiles, which are determined by a multitude of parameters, both compound-dependent and physiological. Comparison of the simulated and observed oral profiles was done using goodness-of-fit parameters such as the reduced chi(2) statistic. Fold errors were calculated for the area under the plasma concentration-time curve (AUC), maximum plasma concentration (C(max)) and time to reach the C(max) (t(max)), to assess the accuracy of predictions. RESULTS: The approach of predicting the oral profiles by optimizing the clearance and distribution parameters using the observed intravenous profile seemed to perform well for the nine compounds chosen for the study. The mean fold error for oral pharmacokinetic parameters, such as the C(max), t(max) and AUC, and for lineshape simulation was within 2-fold. CONCLUSIONS: The validation of the generic PBPK model built in-house demonstrated that as long as the absorption profile of a compound is determined solely by solubility and paracellular or transcellular permeability, the PBPK simulations of oral profiles using optimized parameters from intravenous simulations provide reasonably good agreement with the observed profile with respect to both the lineshape fit and prediction of pharmacokinetic parameters. Therefore, any lineshape mismatch between PBPK simulated and observed oral profiles can be interpreted suitably to gain mechanistic insights into the pharmacokinetic processes that have resulted in the observed lineshape. A strategy has been proposed to identify involvement of carrier-mediated transport; clearance saturation; enterohepatic recirculation of the parent compound; extra-hepatic, extra-gut elimination; higher in vivo solubility than predicted in vitro; drug-induced gastric emptying delays; gut loss and regional variation in gut absorption.     

Development and evaluation of a generic physiologically based pharmacokinetic model for children

BACKGROUND: Clinical trials in children are being encouraged by regulatory authorities in light of the immense off-label and unlicensed use of drugs in the paediatric population. The use of in silico techniques for pharmacokinetic prediction will aid in the development of paediatric clinical trials by guiding dosing regimens, ensuring efficient blood sampling times, maximising therapeutic effect and potentially reducing the number of children required for the study. The goal of this study was to extend an existing physiologically based pharmacokinetic (PBPK) model for adults to reflect the age-related physiological changes in children from birth to 18 years of age and, in conjunction with a previously developed age-specific clearance model, to evaluate the accuracy of the paediatric PBPK model to predict paediatric plasma profiles. METHODS: The age-dependence of bodyweight, height, organ weights, blood flows, interstitial space and vascular space were taken from the literature. Physiological parameters that were used in the PBPK model were checked against literature values to ensure consistency. These included cardiac output, portal vein flow, extracellular water, total body water, lipid and protein. Five model compounds (paracetamol [acetaminophen], alfentanil, morphine, theophylline and levofloxacin) were then examined by gathering the plasma concentration-time profiles, volumes of distribution and elimination half-lives from different ages of children and adults. First, the adult data were used to ensure accurate prediction of pharmacokinetic profiles. The model was then scaled to the specific age of children in the study, including the scaling of clearance, and the generated plasma concentration profiles, volumes of distribution and elimination half-lives were compared with literature values. RESULTS: Physiological scaling produced highly age-dependent cardiac output, portal vein flow, extracellular water, total body water, lipid and protein values that well represented literature data. The pharmacokinetic profiles in children for the five compounds were well predicted and the trends associated with age were evident. Thus, young neonates had plasma concentrations greater than the adults and older children had concentrations less than the adults. Eighty-three percent, 97% and 87% of the predicted plasma concentrations, volumes of distribution and elimination half-lives, respectively, were within 50% of the study reported values. There was no age-dependent bias for term neonates to 18 years of age when examining volumes of distribution and elimination half-lives. CONCLUSION: This study suggests that the developed paediatric PBPK model can be used to scale pharmacokinetics from adults. The accurate prediction of pharmacokinetic parameters in children will aid in the development of dosing regimens and sampling times, thus increasing the efficiency of paediatric clinical trials.     

Comparison of three physiologically based pharmacokinetic models of benzene disposition

We assess the goodness of fit of three physiologically based models of benzene pharmacokinetics to experimental data in Fischer-344 rats. These models were independently developed and published. Large differences in the quality of the fit are observed. In addition, the parameter values leading to acceptable fits are spread over the entire range of physiologically plausible values and can be quite different from average or standard values. On the other hand, choosing standard values for the parameters does not ensure good predictions of all tissue levels. These results emphasize the difficulty of a rigorous calibration of physiological models, and the need for further research in this area, including precise experimental determination of parameter values. Physiological models are powerful tools, but for risk assessment purposes simpler models, making equivalent use of the crucial data, are probably preferable.     

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.     

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.     

Recent advances in physiologically based pharmacokinetic and pharmacodynamic models for anticancer nanomedicines

Archives of Pharmacal Research - Nanoparticles (NPs) have distinct pharmacokinetic (PK) properties and can potentially improve the absorption, distribution, metabolism, and elimination (ADME) of...     

Development and utilization of physiologically based pharmacokinetic models for toxicological applications

Recent advances in physiologically based pharmacokinetic (PB-PK) modeling have introduced novel approaches for evaluating toxicological problems. Because PB-PK models are amenable to extrapolation of tissue dosimetry, they are increasingly being applied to chemical risk assessment. This paper reviews the development of PB-PK modeling for toxicological applications. It briefly compares and contrasts the fundamental differences between conventional compartmental analysis and PB-PK modeling. The theory and principles, data requirements and the methodologies to obtain them, and the steps to construct PB-PK models are described. A comprehensive listing of PB-PK models for environmental chemicals developed to date is referenced. Salient applications of PB-PK modeling to toxicological problems are illustrated with examples. Finally, the uncertainties and limitations in PB-PK modeling are also discussed.     

In vitro metabolism of methylene chloride in human and animal tissues: use in physiologically based pharmacokinetic models

Physiologically based pharmacokinetic (PB-PK) models describe the dynamic behavior of chemicals and their metabolites in individual tissues of living animals. Because PB-PK models contain specific parameters related to the physiological and biochemical properties of different species as well as the physical chemical characteristics of individual chemicals, they are useful tools for performing high dose/low dose, dose route, and interspecies extrapolations in hazard evaluations. An example of such extrapolation has been presented by M. E. Andersen, H. J. Clewell III, M. L. Gargas, F. A. Smith, and R. H. Reitz (Toxicol. Appl. Pharmacol. 87, 185-205, 1987), who employed a PB-PK model for methylene chloride (CH2Cl2) to estimate the chronic toxicity of this material. However, one limitation of this PB-PK model was that the metabolic rate constants for the glutathione-S-transferase (GST) pathway in humans were estimated by allometric scaling rather than from experimental data. In this paper we report studies designed to estimate the in vivo rates of metabolism of CH2Cl2 from in vitro incubations of lung and liver tissues from B6C3F1 mice, F344 rats, Syrian Golden hamsters, and humans. A procedure for calculating in vivo metabolic rate constants from the in vitro studies is presented. This procedure was validated by making extrapolations with mixed function oxidase enzymes (MFO) acting on CH2Cl2, where both in vitro and in vivo rates of metabolism are known. The in vitro rate constants for the two enzyme systems are consistent with the hypothesis presented by Andersen et al. that metabolism of CH2Cl2 occurs in vivo by two competing pathways: a high-affinity saturable pathway (identified as MFO) and a low-affinity first-order pathway (identified as GST). The metabolic rate constants for GST obtained from these studies are also consistent with the hypothesis of Andersen et al. that production of large quantities of glutathione/CH2Cl2 conjugates in vivo may increase the frequency with which lung and liver tumors develop in some species of animals (e.g., B6C3F1 mouse). When in vivo studies in humans are unavailable, in vitro enzyme assays provide a reasonable method for estimating metabolic rate constants.     

基于生理药代动力学模型在药物评价中的应用进展

基于生理的药代动力学(PBPK)模型是当前药物研究领域的重要方法,已被广泛应用于药物发现和开发的各个阶段。在药物发现阶段,利用PBPK模型对药物药代动力学性质进行预测,完成对候选药物的筛选;在临床前阶段,通过结合体外数据和生理放大系数,利用PBPK模型预测候选药物在动物和人的整体药代动力学行为,并结合体外代谢实验,可提前预测药物药物相互作用;在临床阶段,PBPK模型有助于预测不同参照人群(不同年龄、不同疾病状态、不同种族)的差异,尤其是对儿童给药剂量及采样时间的预测。目前,PBPK模型的输入参数多为群体均值,难以达到服务个体的目的。在个体化需求前提下,要求模型的输入参数更能反映个体特征,且导入更加符合实际生理条件的时间参数。本文综述了PBPK模型的原理和特征,及其在药物发现阶段、临床前开发阶段、临床开发阶段、药物相互作用和个体化用药的应用,并简要介绍了常用的PBPK软件的特点。     

生理药代动力学模型的进展与应用

本文在概述生理药代动力学模型(简称生理模型)基本特点的基础上,摘要评述生理模型自1990年至1995年在药物代谢过程及危险性评估方面有代表意义的应用进展。还讨论了生理模型发展前景的展望。     

Development and specification of physiologically based pharmacokinetic models for use in risk assessment

Risk assessments are performed to estimate the conditions under which individuals or populations may be harmed by exposure to environmental or occupational chemicals. In the absence of quantitative data in the human, this process is often dependent upon the use of animal and in vitro data to estimate human response. To reduce the uncertainty inherent in such extrapolations, there has been considerable interest in the development of physiologically based pharmacokinetic (PBPK) models of toxic chemicals for application in quantitative risk assessments. PBPK models are effective tools for integrating diverse dose-response and mechanistic data in order to more accurately predict human risk. Yet, for these models to be useful and trustworthy in performing the necessary extrapolations (species, doses, exposure scenarios), they must be thoughtfully constructed in accordance with known biology and pharmacokinetics, documented in a form that is transparent to risk assessors, and shown to be robust using diverse and appropriate data. This paper describes the process of PBPK model development and highlights issues related to the specification of model structure and parameters, model evaluation, and consideration of uncertainty. Examples are provided to illustrate approaches for selecting a "preferred" model from multiple alternatives.     

生理药动学模型在固体口服制剂一致性评价中的应用

在固体口服制剂仿制药一致性评价中,如何评价仿制药与参比制剂体外溶出曲线差异对生物等效性的影响具有重要意义。本文总结重大新药创制专项课题“化药制剂质量评价关键技术研究”(No. 2015ZX09303001-001)课题的研究成果,通过对典型案例的介绍,阐述建立PBPK模型的原理与建模方法;利用PBPK模型,预测药物体外溶出曲线的变化对其PK参数的影响,评价制剂处方,建立/评价生理相关溶出度测定方法等;以推进在一致性评价中更好地依据体外溶出曲线预测其体内的生物等效性的应用。