Evidence map›Paper›PMID 31827176›Full record

ArticleScientific reports2019

Development of an in silico prediction system of human renal excretion and clearance from chemical structure information incorporating fraction unbound in plasma as a descriptor.

Reiko Watanabe, Rikiya Ohashi, Tsuyoshi Esaki, Hitoshi Kawashima, Yayoi Natsume-Kitatani, Chioko Nagao, Kenji Mizuguchi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

26 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Dataset of xenobiotics human renal clearance values.Database : the journal of biological databases and curation · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Pharmaceuticals (Basel, Switzerland) · 2024
    Article
  12. Computational exploration ofFrontiers in chemistry · 2024
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
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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

7 authors at 3 institutions in 1 country.

Reiko WatanabeLaboratory of Bioinformatics, AI Center for Health and Biomedical Research, National Institute of Biomedical Innovation Health and Nutrition, Osaka, Japan. reiko-watanabe@nibiohn.go.jp.ORCID http://orcid.org/0000-0001-9359-8731
Rikiya OhashiLaboratory of Bioinformatics, AI Center for Health and Biomedical Research, National Institute of Biomedical Innovation Health and Nutrition, Osaka, Japan. rikiya-ohashi@nibiohn.go.jp.
Tsuyoshi EsakiLaboratory of Bioinformatics, AI Center for Health and Biomedical Research, National Institute of Biomedical Innovation Health and Nutrition, Osaka, Japan.ORCID http://orcid.org/0000-0001-8780-6346
Hitoshi KawashimaLaboratory of Bioinformatics, AI Center for Health and Biomedical Research, National Institute of Biomedical Innovation Health and Nutrition, Osaka, Japan.
Yayoi Natsume-KitataniLaboratory of Bioinformatics, AI Center for Health and Biomedical Research, National Institute of Biomedical Innovation Health and Nutrition, Osaka, Japan.
Chioko NagaoLaboratory of In-silico Drug Design, Center of Drug Design Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan.
Kenji MizuguchiLaboratory of Bioinformatics, AI Center for Health and Biomedical Research, National Institute of Biomedical Innovation Health and Nutrition, Osaka, Japan.ORCID http://orcid.org/0000-0003-3021-7078
National Institute of Biomedical Innovation, Health and Nutrition · JPMitsubishi Group (Japan) · JPShiga University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prediction of pharmacokinetic profiles of new chemical entities is essential in drug development to minimize the risks of potential withdrawals. The excretion of unchanged compounds by the kidney constitutes a major route in drug elimination and plays an important role in pharmacokinetics. Herein, we created in silico prediction models of the fraction of drug excreted unchanged in the urine (f

Indexed as

Computer SimulationPharmacokineticsRenal EliminationHumansModels, Biological

Identifiers

PMID31827176
PMCPMC6906481
OpenAlexW2995744077

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.