Evidence map›Paper›PMID 34472587›Full record

ArticleBriefings in bioinformatics2022

Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments.

Ziaurrehman Tanoli, Jehad Aldahdooh, Farhan Alam, Yinyin Wang, Umair Seemab, Maddalena Fratelli, Petr Pavlis, Marian Hajduch, Florence Bietrix, Philip Gribbon and 9 more

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Intrinsically Disordered Proteins: An Overview.International journal of molecular sciences · 2022
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Ziaurrehman TanoliResearch Program in Systems Oncology, Faculty of medicine, University of Helsinki, Finland.
Jehad AldahdoohResearch Program in Systems Oncology, Faculty of medicine, University of Helsinki, Finland.
Farhan AlamResearch Program in Systems Oncology, Faculty of medicine, University of Helsinki, Finland.
Yinyin WangResearch Program in Systems Oncology, Faculty of medicine, University of Helsinki, Finland.
Umair SeemabResearch Program in Systems Oncology, Faculty of medicine, University of Helsinki, Finland.
Maddalena FratelliIstituto di Ricerche Farmacologiche Mario Negri IRCCS, Italy.
Petr PavlisInstitute of Molecular and Translational Medicine, Czech.
Marian HajduchInstitute of Molecular and Translational Medicine, Czech.
Florence BietrixEuropean Infrastructure for Translational Medicine, UK.
Philip GribbonFraunhofer Institute for Molecular Biology and Applied Ecology, Germany.
Andrea ZalianiFraunhofer Institute for Molecular Biology and Applied Ecology, Germany.
Matthew D HallNational Center for Advancing Translational Sciences, USA.
Min ShenNational Center for Advancing Translational Sciences, USA.
Kyle BrimacombeNational Center for Advancing Translational Sciences, USA.
Evgeny KulesskiyInstitute for Molecular Medicine Finland, University of Helsinki, Finland.
Jani SaarelaInstitute for Molecular Medicine Finland, University of Helsinki, Finland.
Krister WennerbergBiotech Research & Innovation Centre (BRIC), University of Copenhagen, Denmark.
Markus Vähä-KoskelaInstitute for Molecular Medicine Finland, University of Helsinki, Finland.
Jing TangResearch Program in Systems Oncology, Faculty of medicine, University of Helsinki, Finland.

Funding

Academy of Finland 317680EOSC-Life 824087European Research Council 716063
6 · The paper itself

Abstract

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of Minimal Information for Chemosensitivity Assays (MICHA), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies as well as six recently conducted COVID-19 studies. With the MICHA web server and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

Indexed as

data integration toolsdrug discoverydrug sensitivity assaysFAIR research data

Identifiers

PMID34472587
PMCPMC8769689

What OpenQuestion holds

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LicenceCC BY
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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.