Evidence map›Paper›PMID 34400352›Full record

ReviewDrug discovery today2022

Evaluating the performance of drug-repurposing technologies.

James Schuler, Zackary Falls, William Mangione, Matthew L Hudson, Liana Bruggemann, Ram Samudrala

Full text readReview
In one paragraph

Review in Drug discovery today, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Techniques and Strategies in Drug Design and Discovery.International journal of molecular sciences · 2024
    Article
  20. Review
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

6 authors.

James SchulerDepartment of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA. Electronic address: jcschule@buffalo.edu.
Zackary FallsDepartment of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.
William MangioneDepartment of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.
Matthew L HudsonDepartment of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.
Liana BruggemannDepartment of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.
Ram SamudralaDepartment of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA. Electronic address: ram@compbio.org.

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
National Library of Medicine Conference 2022T15LM012495 · NLM · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI PETER L. ELKIN · 2017 to 2026
$4.3M
NOVEL PARADIGMS FOR DRUG DISCOVERY: COMPUTATIONAL MULTITARGET SCREENINGDP1LM011509 · NLM · UNIVERSITY OF WASHINGTON · PI SAMUDRALA, RAM · 2012 to 2014
$2.4M
NOVEL PARADIGMS FOR DRUG DISCOVERY: COMPUTATIONAL MULTITARGET SCREENINGDP1OD006779 · OD · UNIVERSITY OF WASHINGTON · PI SAMUDRALA, RAM · 2010 to 2011
$1.7M
Acquisition of High Performance Data and Computing Infrastructure to Advance Biomedical ResearchS10OD024973 · OD · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI FURLANI, THOMAS · 2019 to 2019
$1.0M
NCATS NIH HHS UL1 TR001412NIH HHS DP1 OD006779NLM NIH HHS DP1 LM011509NLM NIH HHS T15 LM012495
6 · The paper itself

Abstract

Drug-repurposing technologies are growing in number and maturing. However, comparisons to each other and to reality are hindered because of a lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross-platform comparability, enabling us to continue to strive toward optimal repurposing by decreasing the time and cost of drug discovery and development.

Indexed as

Drug EvaluationDrug RepositioningBiomedical TechnologyComputational BiologyHumansMedical InformaticsArea under the curveBiomedical InformaticsComputational drug repositioningComputational drug repurposingDrug repositioningDrug repurposingNormalized discounted cumulative gainPerformance evaluationPerformance metricsValidation

Identifiers

PMID34400352
PMCPMC10014214

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read9
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.