Evidence map›Paper›PMID 29843542›Full record

ArticleSLAS discovery : advancing life sciences R & D2018

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

John Joslin, James Gilligan, Paul Anderson, Catherine Garcia, Orzala Sharif, Janice Hampton, Steven Cohen, Miranda King, Bin Zhou, Shumei Jiang and 15 more

Abstract read
In one paragraph

Article in SLAS discovery : advancing life sciences R & D, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Applications of Flow Cytometry in Drug Discovery and Translational Research.International journal of molecular sciences · 2024
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Modern deep learning in bioinformatics.Journal of molecular cell biology · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. 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

25 authors.

John Joslin1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
James Gilligan1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Paul Anderson1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Catherine Garcia1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Orzala Sharif1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Janice Hampton1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Steven Cohen1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Miranda King1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Bin Zhou1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Shumei Jiang1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Christopher Trussell1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Robert Dunn1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
John W Fathman1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Jennifer L Snead1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Anthony E Boitano1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Tommy Nguyen1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Michael Conner1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Mike Cooke1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Jennifer Harris1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Ed Ainscow1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Yingyao Zhou1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Chris Shaw1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Dan Sipes1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
James Mainquist1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.
Scott Lesley1 Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Indexed as

Drug DiscoveryFlow CytometryHigh-Throughput Screening AssaysAutomation, LaboratoryBlood PlateletsCell LineComputational BiologyData AnalysisDrug Evaluation, PreclinicalHumansHybridomasT-Lymphocyte Subsetsdrug discoveryhigh-throughput flow cytometryhigh-throughput screeningphenotypic screening

Identifiers

PMID29843542
PMCPMC6055113

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.