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A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage
Citation:
Thompson, C., J. Firman, M. Goldsmith, C. Grulke, Y. Tan, A. Paini, P. Penson, R. Sayre, S. Webb, AND J. Madden. A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage. ATLA: Alternatives to Laboratory Animals. Frame, Nottingham, Uk, 49(5):197-208, (2021). https://doi.org/10.1177/02611929211060264
Impact/Purpose:
Humans, like other animals, are exposed daily to a multitude of chemicals of anthropogenic origin, including pharmaceuticals, food additives, pesticides, consumer goods and cosmetic ingredients. However, for the majority of chemicals there is a lack of available data for safety assessment, hence predictive models are essential. Predicting toxicity requires knowledge of both the intrinsic activity of the chemical (or its derivatives) and the extent to which the organism is exposed. Whilst general information regarding absorption, distribution, metabolism or excretion (ADME) may be useful, more accurate prediction requires organ-level concentration-time profiles. Physiologically-based kinetic (PBK) models (synonymous with physiologically-based pharmacokinetic, toxicokinetic or biokinetic (PBPK, PBTK or PBBK) models) are employed in numerous industries to provide such predictions. In summary, the aim of this systematic review was the curation of a data resource for existing PBK models. This resource has been created to assist the development and evaluation of PBK models using existing data, thereby reducing the need to generate new data from animal studies.
Description:
Across multiple sectors, including food, cosmetics and pharmaceutical industries, there is a need to predict the potential effects of xenobiotics. These effects are determined by the intrinsic ability of the substance, or its derivatives, to interact with the biological system, and its concentration–time profile at the target site. Physiologically-based kinetic (PBK) models can predict organ-level concentration–time profiles, however, the models are time and resource intensive to generate de novo. Read-across is an approach used to reduce or replace animal testing, wherein information from a data-rich chemical is used to make predictions for a data-poor chemical. The recent increase in published PBK models presents the opportunity to use a read-across approach for PBK modelling, that is, to use PBK model information from one chemical to inform the development or evaluation of a PBK model for a similar chemical. Essential to this process, is identifying the chemicals for which a PBK model already exists. Herein, the results of a systematic review of existing PBK models, compliant with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format, are presented. Model information, including species, sex, life-stage, route of administration, software platform used and the availability of model equations, was captured for 7541 PBK models. Chemical information (identifiers and physico-chemical properties) has also been recorded for 1150 unique chemicals associated with these models. This PBK model data set has been made readily accessible, as a Microsoft Excel spreadsheet, providing a valuable resource for those developing, using or evaluating PBK models in industry, academia and the regulatory sectors.
URLs/Downloads:
DOI: A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage
https://pubmed.ncbi.nlm.nih.gov/34836462/