Evidence map›Paper›PMID 33244000›Full record

ArticleScientific reports2020

Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.

Vishal B Siramshetty, Pranav Shah, Edward Kerns, Kimloan Nguyen, Kyeong Ri Yu, Md Kabir, Jordan Williams, Jorge Neyra, Noel Southall, Ðắc-Trung Nguyễn and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Employing Automated Machine Learning (AutoML) Methods to Facilitate theJournal of chemical information and modeling · 2025
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Artificial Intelligence in ADME Property Prediction.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. HybridACS pharmacology & translational science · 2021
    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

11 authors.

Vishal B Siramshetty *National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Pranav Shah *National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Edward KernsNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Kimloan NguyenNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Kyeong Ri YuNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Md KabirNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Jordan WilliamsNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Jorge NeyraNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Noel SouthallNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Ðắc-Trung NguyễnNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA.
Xin XuNational Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, MD, 20850, USA. xin.xu3@nih.gov.

Funding

TRAINING PROGRAM IN CANCER THERAPYT32CA078207 · NCI · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI James J Manfredi · 1999 to 2026
$11.6M
NCI NIH HHS T32 CA078207
6 · The paper itself

Abstract

Hepatic metabolic stability is a key pharmacokinetic parameter in drug discovery. Metabolic stability is usually assessed in microsomal fractions and only the best compounds progress in the drug discovery process. A high-throughput single time point substrate depletion assay in rat liver microsomes (RLM) is employed at the National Center for Advancing Translational Sciences. Between 2012 and 2020, RLM stability data was generated for ~ 24,000 compounds from more than 250 projects that cover a wide range of pharmacological targets and cellular pathways. Although a crucial endpoint, little or no data exists in the public domain. In this study, computational models were developed for predicting RLM stability using different machine learning methods. In addition, a retrospective time-split validation was performed, and local models were built for projects that performed poorly with global models. Further analysis revealed inherent medicinal chemistry knowledge potentially useful to chemists in the pursuit of synthesizing metabolically stable compounds. In addition, we deposited experimental data for ~ 2500 compounds in the PubChem bioassay database (AID: 1508591). The global prediction models are made publicly accessible ( https://opendata.ncats.nih.gov/adme ). This is to the best of our knowledge, the first publicly available RLM prediction model built using high-quality data generated at a single laboratory.

Indexed as

AnimalsComputer SimulationDatabases, FactualDrug DiscoveryHigh-Throughput Screening AssaysLiverMachine LearningMaleMicrosomes, LiverNational Center for Advancing Translational Sciences (U.S.)Pharmaceutical PreparationsQuantitative Structure-Activity RelationshipRatsRats, Sprague-DawleyRetrospective StudiesUnited StatesPharmaceutical Preparations

Identifiers

PMID33244000
PMCPMC7693334

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.