Evidence map›Paper›PMID 38487691›Full record

ArticleBiological imaging2023

Cell painting transfer increases screening hit rate.

Ethan Cohen, Maxime Corbe, Cláudio A Franco, Francisca F Vasconcelos, Franck Perez, Elaine Del Nery, Guillaume Bollot, Auguste Genovesio

Open access · diamondAbstract read
In one paragraph

Article in Biological imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.2field-weighted citation impact, top 9% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Cross-Modal Graph Contrastive Learning with Cellular Images.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    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

8 authors at 2 institutions in 2 countries.

Ethan CohenComputational Bioimaging and Bioinformatics, Institut de Biologie de l'Ecole Normale Supérieure, PSL University, Paris, France.
Maxime CorbeComputational Bioimaging and Bioinformatics, Institut de Biologie de l'Ecole Normale Supérieure, PSL University, Paris, France.
Cláudio A FrancoInstituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.
Francisca F VasconcelosInstituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.
Franck PerezBiophenics Laboratory, Institut Curie, PSL Research University, Department of Translational Research, Cell and Tissue Imaging Facility (PICT-IBiSA), Paris, France.
Elaine Del NeryBiophenics Laboratory, Institut Curie, PSL Research University, Department of Translational Research, Cell and Tissue Imaging Facility (PICT-IBiSA), Paris, France.
Guillaume BollotSynsight, 4 Rue Pierre Fontaine, 91000 Évry-Courcouronnes, France.
Auguste GenovesioComputational Bioimaging and Bioinformatics, Institut de Biologie de l'Ecole Normale Supérieure, PSL University, Paris, France.ORCID https://orcid.org/0000-0003-1877-5595
Université Paris Sciences et Lettres · FRUniversity of Lisbon · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug discovery uses high throughput screening to identify compounds that interact with a molecular target or that alter a phenotype favorably. The cautious selection of molecules used for such a screening is instrumental and is tightly related to the hit rate. In this work, we wondered if cell painting, a general-purpose image-based assay, could be used as an efficient proxy for compound selection, thus increasing the success rate of a specific assay. To this end, we considered cell painting images with 30,000 molecules treatments, and selected compounds that produced a visual effect close to the positive control of an assay, by using the Frechet Inception Distance. We then compared the hit rates of such a preselection with what was actually obtained in real screening campaigns. As a result, cell painting would have permitted a significant increase in the success rate and, even for one of the assays, would have allowed to reach 80% of the hits with 10 times fewer compounds to test. We conclude that images of a cell painting assay can be directly used for compound selection prior to screening, and we provide a simple quantitative approach in order to do so.

Indexed as

cell paintingdrug discoveryhigh content screeningtransfer learning

Identifiers

PMID38487691
PMCPMC10936370
OpenAlexW4323051567

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.