A framework for application of quantitative property-property relationships (QPPRs) in physiologically based pharmacokinetic (PBPK) models for high-throughput prediction of internal dose of inhaled organic chemicals

Chébékoué, Sandrine Fleur; Krishnan, Kannan

doi:10.1016/j.chemosphere.2018.10.041

Cited by 5 publications

(3 citation statements)

References 41 publications

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“…This feature allows not only easier high-throughput investigations (P B:A coefficients do not need to be looked up in literature), but more importantly, it provides the opportunity to run simulations on the thousands of chemicals (with a known structure) that have not yet been investigated to the point of having a literature value for P B:A . Future integration of httk with open source F up and CL INT in silico quantitative property-property relationship (QPPR) based estimators, such as those included in Chebekoue et al .,( 41 ) would make this PBTK model usable for thousands of chemicals without in vitro toxicokinetic data.…”

Section: Discussionmentioning

confidence: 99%

Development and evaluation of a high throughput inhalation model for organic chemicals

Linakis

Sayre

Pearce

et al. 2020

J Expo Sci Environ Epidemiol

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Currently it is difficult to prospectively estimate human toxicokinetics (particularly for novel chemicals) in a high-throughput manner. The R software package httk has been developed, in part, to address this deficiency, and the aim of this investigation was to develop a generalized inhalation model for httk . The structure of the inhalation model was developed from two previously published physiologically-based models from Jongeneelen et al. (2011) and Clewell et al. (2001) while calculated physicochemical data was obtained from EPA’s CompTox Chemicals Dashboard. In total, 142 exposure scenarios across 41 volatile organic chemicals were modeled and compared to published data. The slope of the regression line of best fit between log-transformed simulated and observed combined measured plasma and blood concentrations was 0.46 with an r 2 = 0.45 and a Root Mean Square Error (RMSE) of direct comparison between the log-transformed simulated and observed values of 1.11.. Approximately 5.1% (n = 108) of the data points analyzed were > 2 orders of magnitude different than expected. The volatile organic chemicals examined in this investigation represent small, generally lipophilic molecules. Ultimately this paper details a generalized inhalation component that integrates with the httk physiologically-based toxicokinetic model to provide high-throughput estimates of inhalation chemical exposures.

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Section: Discussionmentioning

confidence: 99%

Development and evaluation of a high throughput inhalation model for organic chemicals

Linakis

Sayre

Pearce

et al. 2020

J Expo Sci Environ Epidemiol

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“…Although increasingly more proof-of-concepts of bottomup PBK modelling approaches are available to the scientific community (Basketter et al 2012;Coecke et al 2013;Gajewska et al 2014;OECD 2020aOECD , b, 2021, challenges remain regarding the acceptance of PBK model results in regulatory risk assessments (Bopp et al 2019;Paini et al 2021a;Wambaugh et al 2019). For example, the use of generic PBK models to prioritise chemicals with the highest likelihood of causing health effects is accepted by regulators to varying degrees and depends on the risk assessment application and context (Chebekoue and Krishnan 2019).…”

Section: Acceptance By Regulatorsmentioning

confidence: 99%

Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment

et al. 2022

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With an increasing need to incorporate new approach methodologies (NAMs) in chemical risk assessment and the concomitant need to phase out animal testing, the interpretation of in vitro assay readouts for quantitative hazard characterisation becomes more important. Physiologically based kinetic (PBK) models, which simulate the fate of chemicals in tissues of the body, play an essential role in extrapolating in vitro effect concentrations to in vivo bioequivalent exposures. As PBK-based testing approaches evolve, it will become essential to standardise PBK modelling approaches towards a consensus approach that can be used in quantitative in vitro-to-in vivo extrapolation (QIVIVE) studies for regulatory chemical risk assessment based on in vitro assays. Based on results of an ECETOC expert workshop, steps are recommended that can improve regulatory adoption: (1) define context and implementation, taking into consideration model complexity for building fit-for-purpose PBK models, (2) harmonise physiological input parameters and their distribution and define criteria for quality chemical-specific parameters, especially in the absence of in vivo data, (3) apply Good Modelling Practices (GMP) to achieve transparency and design a stepwise approach for PBK model development for risk assessors, (4) evaluate model predictions using alternatives to in vivo PK data including read-across approaches, (5) use case studies to facilitate discussions between modellers and regulators of chemical risk assessment. Proof-of-concepts of generic PBK modelling approaches are published in the scientific literature at an increasing rate. Working on the previously proposed steps is, therefore, needed to gain confidence in PBK modelling approaches for regulatory use.

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“…An approach for the estimation of adipose/blood partition coefficients through QSAR for 67 environmental chemicals, which was also used for gap filling of the logP (adipose/blood) data for 513 chemicals from the US EPA, was reported by Jean et al [ 143 ]. Quantitative property-property relationships (QPPRs) have been applied to the high-throughput prediction of internal dose of inhaled organic chemicals in PBPK models [ 144 ], while physiologically based toxicokinetic (PBTK) model parameters have been calculated by Sarigiannis et al [ 145 ] and Savvateeva et al [ 146 ]. Research specific to parameters of nanomaterial PBPK models is less common but increasing—a method combining an artificial intelligence-based cell simulation and a calibrated fluorescence assay that quantifies rate constant for biological interactions between NMs and individual cells is proposed by Price and Gesquiere [ 147 ].…”

Section: Model Evaluation and Validationmentioning

confidence: 99%

Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials

et al. 2020

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There have been efforts to develop physiologically based pharmacokinetic (PBPK) models for nanomaterials (NMs). Since NMs have quite different kinetic behaviors, the applicability of the approaches and techniques that are utilized in current PBPK models for NMs is warranted. Most PBPK models simulate a size-independent endocytosis from tissues or blood. In the lungs, dosimetry and the air-liquid interface (ALI) models have sometimes been used to estimate NM deposition and translocation into the circulatory system. In the gastrointestinal (GI) tract, kinetics data are needed for mechanistic understanding of NM behavior as well as their absorption through GI mucus and their subsequent hepatobiliary excretion into feces. Following absorption, permeability (Pt) and partition coefficients (PCs) are needed to simulate partitioning from the circulatory system into various organs. Furthermore, mechanistic modelling of organ- and species-specific NM corona formation is in its infancy. More recently, some PBPK models have included the mononuclear phagocyte system (MPS). Most notably, dissolution, a key elimination process for NMs, is only empirically added in some PBPK models. Nevertheless, despite the many challenges still present, there have been great advances in the development and application of PBPK models for hazard assessment and risk assessment of NMs.

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A framework for application of quantitative property-property relationships (QPPRs) in physiologically based pharmacokinetic (PBPK) models for high-throughput prediction of internal dose of inhaled organic chemicals

Cited by 5 publications

References 41 publications

Development and evaluation of a high throughput inhalation model for organic chemicals

Development and evaluation of a high throughput inhalation model for organic chemicals

Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment

Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials

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