ABSTRACT
Introduction
Toxicity data are unavailable for many thousands of chemicals in commerce and the environment. Therefore, risk assessors need to rapidly screen these chemicals for potential risk to public health. High-throughput screening (HTS) for in vitro bioactivity, when used with high-throughput toxicokinetic (HTTK) data and models, allows characterization of these thousands of chemicals.
Areas covered
This review covers generic physiologically based toxicokinetic (PBTK) models and high-throughput PBTK modeling for in vitro-in vivo extrapolation (IVIVE) of HTS data. We focus on ‘httk’, a public, open-source set of computational modeling tools and in vitro toxicokinetic (TK) data.
Expert opinion
HTTK benefits chemical risk assessors with its ability to support rapid chemical screening/prioritization, perform IVIVE, and provide provisional TK modeling for large numbers of chemicals using only limited chemical-specific data. Although generic TK model design can increase prediction uncertainty, these models provide offsetting benefits by increasing model implementation accuracy. Also, public distribution of the models and data enhances reproducibility. For the httk package, the modular and open-source design can enable the tool to be used and continuously improved by a broad user community in support of the critical need for high-throughput chemical prioritization and rapid dose estimation to facilitate rapid hazard assessments.
Article highlights
In vitro high-throughput screening (HTS) to efficiently assess potential chemical risk to public health requires toxicokinetics (TK) for in vitro-in vivo extrapolation (IVIVE)
Physiologically based TK models (PBTK) support extrapolation in chemical risk assessment, including IVIVE
The high-throughput toxicokinetics (HTTK) method uses generic PBTK models that can be parameterized for thousands of chemicals with in vitro TK data
The U.S. Environmental Protection Agency (U.S. EPA) provides HTTK methods through the publicly available software package called ‘httk’
HTTK facilitates HTS of chemical libraries for potential risk using only limited data
This box summarizes key points contained in the article.
Acknowledgement
The authors thank Drs. Elaina Kenyon and Todd Zurlinden for their helpful U.S. EPA internal reviews of the manuscript.
Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.