A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage

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.

The funding support and scientific advice provided by the European Partnership for Alternative Approaches to animal testing (EPAA) for the development of this tool (excel spreadsheet) is gratefully acknowledged.

在食品、化妆品及制药等多个行业中，均需要预测外源性物质（xenobiotics）的潜在效应。此类效应由物质或其衍生物与生物系统相互作用的内在能力，及其在靶部位的浓度-时间分布特征共同决定。基于生理学的药代动力学（Physiologically-based kinetic, PBK）模型可预测器官水平的浓度-时间分布特征，但从头构建此类模型往往耗时耗力。交叉参照（read-across）是一种用于减少或替代动物实验的方法，即借助数据充足的化学品的相关信息，对数据匮乏的化学品进行效应预测。近年来已发表的PBK模型数量持续增长，使得我们得以将交叉参照方法应用于PBK建模领域，即通过某一化学品的PBK模型信息，辅助开发或评估同类化学品的PBK模型。该流程的核心环节是识别已构建PBK模型的化学品。本文遵循系统评价与Meta分析首选报告条目（Preferred Reporting Items for Systematic Reviews and Meta-Analyses, PRISMA）规范，对现有PBK模型开展系统综述，现将结果报道如下。本次研究共收集了7541个PBK模型的相关信息，涵盖物种、性别、生命阶段、给药途径、所用软件平台以及模型方程的可获取性。同时，针对与这些模型相关的1150种独特化学品，我们也记录了其化学信息（包括标识符与理化性质）。本PBK数据集已以Microsoft Excel®电子表格的形式公开，可为工业界、学术界及监管领域中从事PBK模型开发、应用或评估的人员提供极具价值的参考资源。

衷心感谢欧洲动物实验替代方法合作伙伴关系（European Partnership for Alternative Approaches to animal testing, EPAA）为本电子表格工具的开发提供的资助支持与科学咨询。