Evidence map›Paper›PMID 40238721›Full record

ArticlePloS one2025

Enabling transparent toxicokinetic modeling for public health risk assessment.

Sarah E Davidson-Fritz, Caroline L Ring, Marina V Evans, Celia M Schacht, Xiaoqing Chang, Miyuki Breen, Gregory S Honda, Elaina Kenyon, Matthew W Linakis, Annabel Meade and 5 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Incorporating a dermal absorption route into high throughput toxicokinetic modeling.Journal of exposure science & environmental epidemiology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Sarah E Davidson-FritzCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Cincinnati, Ohio, United States of America.
Caroline L RingCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
Marina V EvansCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.ORCID 0000-0002-2479-1738
Celia M SchachtCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
Xiaoqing ChangInotiv, Research Triangle Park, North Carolina, United States of America.
Miyuki BreenCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
Gregory S HondaCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
Elaina KenyonCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
Matthew W LinakisRamboll, Raleigh, North Carolina, United States of America.
Annabel MeadeCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
Robert G PearceCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.ORCID 0000-0003-3168-4049
Mark A SfeirCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
James P SlukaDepartment of Intelligent Systems Engineering and Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America.ORCID 0000-0002-5901-1404
Michael J DevitoCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.
John F WambaughCenter for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.ORCID 0000-0002-4024-534X

Funding

NIH HHS HHSN273201500010C
6 · The paper itself

Abstract

Toxicokinetic modeling describes the absorption, distribution, metabolism, and elimination of chemicals by the body. Chemical-specific in vivo toxicokinetic data is often unavailable for the thousands of chemicals in commerce. However, predictions from generalized toxicokinetic models allow for extrapolation from in vitro toxicological data, obtained via new approach methods (NAMs), to predict in vivo human health outcomes and provide key information on chemicals for public health risk assessment. The httk R package provides an open-source software tool containing a suite of generalized toxicokinetic models covering various exposure scenarios, a library of chemical-specific data from peer-reviewed high-throughput toxicokinetic (HTTK) studies, and other utility functions to parameterize and evaluate toxicokinetic models. Generalized HTTK models in httk use the open-source language MCSim to describe the compartmental and physiologically based toxicokinetics (PBTK). New HTTK models may be integrated into httk with a model description code file (C script generated via MCSim) and a model documentation file (R script). httk provides a series of functionalities such as model parameterization, in vivo-derived data for evaluating model predictions, unit conversion, Monte Carlo simulations for uncertainty propagation and biological variability, and other model utilities. Here, we describe in detail how to add new HTTK models into the httk package to leverage its pre-existing data and functionality. As a demonstration, we describe the integration of a gas inhalation PBTK model. The intention of httk is to provide a transparent, open-source tool for toxicokinetics, bioinformatics, and public health risk assessment that makes use of publicly available data on more than one thousand chemicals.

Indexed as

Models, BiologicalPublic HealthToxicokineticsAnimalsHumansRisk AssessmentSoftware

Identifiers

PMID40238721
PMCPMC12002443

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.