Evidence map›Paper›PMID 29032447›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2017

Evaluation and calibration of high-throughput predictions of chemical distribution to tissues.

Robert G Pearce, R Woodrow Setzer, Jimena L Davis, John F Wambaugh

Open access · greenAbstract read
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.3field-weighted citation impact, top 13% of its field
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

23 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. Informatics for toxicokinetics.Journal of pharmacokinetics and pharmacodynamics · 2025
    Article
  4. Article
  5. Article
  6. Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling.Toxicological sciences : an official journal of the Society of Toxicology · 2023
    Article
  7. Article
  8. Article
  9. Evaluation of a rapid, generic human gestational dose model.Reproductive toxicology (Elmsford, N.Y.) · 2022
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. High-throughput PBTK models forExpert opinion on drug metabolism & toxicology · 2021
    Review
  15. Development and evaluation of a high throughput inhalation model for organic chemicals.Journal of exposure science & environmental epidemiology · 2020
    Article
  16. Article
  17. Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization.Toxicological sciences : an official journal of the Society of Toxicology · 2019
    Article
  18. The Next Generation Blueprint of Computational Toxicology at the U.S. Environmental Protection Agency.Toxicological sciences : an official journal of the Society of Toxicology · 2019
    Article
  19. Article
  20. 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

4 authors at 2 institutions in 1 country.

Robert G PearceNational Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, 109 T.W. Alexander Dr, Durham, NC, 27711, USA.
R Woodrow SetzerNational Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, 109 T.W. Alexander Dr, Durham, NC, 27711, USA.
Jimena L DavisNational Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, 109 T.W. Alexander Dr, Durham, NC, 27711, USA.
John F WambaughNational Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, 109 T.W. Alexander Dr, Durham, NC, 27711, USA. Wambaugh.John@epa.gov.ORCID http://orcid.org/0000-0002-4024-534X
Environmental Protection Agency · USOak Ridge Associated Universities · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Toxicokinetics (TK) provides critical information for integrating chemical toxicity and exposure assessments in order to determine potential chemical risk (i.e., the margin between toxic doses and plausible exposures). For thousands of chemicals that are present in our environment, in vivo TK data are lacking. The publicly available R package "httk" (version 1.8, named for "high throughput TK") draws from a database of in vitro data and physico-chemical properties in order to run physiologically-based TK (PBTK) models for 553 compounds. The PBTK model parameters include tissue:plasma partition coefficients (K

Indexed as

Models, BiologicalAnimalsCalibrationComputer SimulationDrug Evaluation, PreclinicalDrug-Related Side Effects and Adverse ReactionsHigh-Throughput Screening AssaysHumansPharmaceutical PreparationsRatsTissue DistributionToxicity TestsPharmaceutical PreparationsDistributionHigh throughput toxicokineticshttkPartition coefficientsPBPKPBTKPhysiologically based toxicokineticsStatistical analysisVolume of distribution

Identifiers

PMID29032447
PMCPMC6186149
OpenAlexW2763017468

What OpenQuestion holds

Textmetadata
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.