为公共健康风险评估建立透明的毒物动力学模型

Sarah E. Davidson-Fritz, Caroline L. Ring, Celia M. Schacht, Marina V. Evans, Xiaoqing Chang, Miyuki Breen, Gregory S. Honda, Elaina Kenyon, Matthew W. Linakis, Annabel Meade, Robert G. Pearce, Mark A. Sfeir, James P. Sluka, Michael J. Devito, John F. Wambaugh
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摘要

毒物动力学描述了人体对化学品的吸收、分布、代谢和排出。毒物动力学模型的预测为化学品风险评估提供了关键信息。传统上,这些预测是从实验动物物种(如大鼠)的数据推断到人类。最近,毒物动力学已被用于从体外毒理学新方法(NAMs)外推至体内。对于成千上万的商业化学品来说,通常无法获得特定化学品的体内毒代动力学数据。因此,我们收集了大量测量特定化学品毒代动力学的体外数据。通过这些数据可以建立高通量毒代动力学或 HTTK 模型。httk 使用开源语言 MCSim 来描述分区和基于生理的毒物动力学(PBTK)模型,MCSim 可以将模型描述转换为高速 C 代码脚本。新模型可通过 R 的开源软件包开发功能、模型文档文件(R 脚本)和 HTTK 模型描述代码文件(C 脚本)集成到 httk 中。除了 HTTK 模型外,httk 还提供了一系列功能,如单位转换、模型参数化、用于不确定性传播和生物变异性的蒙特卡罗模拟、用于评估模型预测的体内衍生数据以及其他模型实用功能。在此,我们将详细介绍如何将新的 HTTK 模型添加到 httk 中,并利用软件包中已有的数据和功能。作为演示,我们介绍了如何将气体吸入 PBTK 模型集成到 httk 中。以 httk 为代表的现代建模方法可以实现清晰的交流、可重现性和公众监督。httk 的目的是为毒物动力学、生物信息学和公共健康风险评估提供一个透明、开源的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enabling Transparent Toxicokinetic Modeling for Public Health Risk Assessment
Toxicokinetics describes the absorption, distribution, metabolism, and elimination of chemicals by the body. Predictions from toxicokinetic models provide key information for chemical risk assessment. Traditionally, these predictions extrapolate from experimental animal species data (for example, in rats) to humans. More recently, toxicokinetics has been used for extrapolation from in vitro new approach methods (NAMs) for toxicology to in vivo. Chemical-specific in vivo toxicokinetic data are often unavailable for the thousands of chemicals in commerce. Therefore, large amounts of in vitro data measuring chemical-specific toxicokinetics have been collected. These data enable high-throughput toxicokinetic or HTTK modeling. The httk R package provides a library of chemical-specific data from peer-reviewed HTTK studies. httk further provides a suite of tools for parameterizing and evaluating toxicokinetic models. httk uses the open-source language MCSim to describe models for compartmental and physiologically based toxicokinetics (PBTK), MCSim can convert the model descriptions into a high-speed C code script. New models are integrated into httk using the open-source package development functionality in R, a model documentation file (R script), and the HTTK model description code file (C script). In addition to HTTK models, httk provides a series of functionalities such as unit conversion, model parameterization, Monte Carlo simulations for uncertainty propagation and biological variability, in vivo-derived data for evaluating model predictions, and other model utility functions. Here, we describe in detail how to add new HTTK models to httk and take advantage of the pre-existing data and functionality in the package. As a demonstration, we describe the integration of the gas inhalation PBTK model into httk. Modern modeling approaches, as exemplified by httk, allow for clear communication, reproducibility, and public scrutiny. The intention of httk is to provide a transparent, open-source tool for toxicokinetics, bioinformatics, and public health risk assessment.
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