Evidence map›Paper›PMID 19396735›Full record

ReviewCurrent opinion in drug discovery & development2009

Pooling in high-throughput drug screening.

Raghunandan M Kainkaryam, Peter J Woolf

Abstract readReview
In one paragraph

Review in Current opinion in drug discovery & development, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Phenotypic Screening inPharmaceuticals (Basel, Switzerland) · 2020
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. 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

2 authors.

Raghunandan M KainkaryamDepartment of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Peter J Woolf

Funding

Nation Center- Integrative Biomedical Informatics(RMI)U54DA021519 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ATHEY, BRIAN DAVID · 2005 to 2010
$21.3M
NIDA NIH HHS U54 DA021519NIDA NIH HHS U54-DA-021519
6 · The paper itself

Abstract

Pooling in HTS refers to the act of testing mixtures of compounds in a primary screen to accurately identify hits for secondary screening. The reduction in the number of tests needed to screen a compound library by pooling can also be extended to achieve much-needed error tolerance in HTS. Despite the success of HTS in other biological experiments, pooling in high-throughput drug screening has been a controversial and often marginalized paradigm. At first appearance, pooling appears to promise gains from reduced effort, or possibly could create more problems than solutions. However, this article demonstrates that pooling is a practical and necessary part of HTS: discussions include the rationale for pooling compounds in HTS, a unifying view of pooling design theory, a review of past attempts at pooling and their success, and recent advances in the field.

Indexed as

Meta-Analysis as TopicCombinatorial Chemistry TechniquesDrug DiscoveryDrug Evaluation, Preclinical

Identifiers

PMID19396735
PMCPMC3204799

What OpenQuestion holds

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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.