Bioassay protocol metadata annotation: Proposed standards adoption

We present a standardized metadata template for assays used in pharmaceutical drug discovery research, according to the FAIR principles. We also describe the use of an automated tool for annotating assays from a variety of sources, including PubChem, commercial assay providers, and the peer-reviewed literature, to this metadata template. Adoption of a standardized metadata template will allow drug discovery scientists to better understand and compare the increasing amounts of assay data becoming available, and will facilitate the use of artificial intelligence tools and other computational methods for analysis and prediction. Since bioassays drive advances in biomedical research, improvements in assay metadata can improve productivity in discovery of new therapeutics, platform technologies, and assay methods.

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Publication Details

Journal
SLAS DISCOVERY
Published
2024-10-19
DOI
https://doi.org/10.1016/j.slasd.2024.100188
Citations
1
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.23
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article

Bioassay protocol metadata annotation: Proposed standards adoption

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Bioassay protocol metadata annotation: Proposed standards adoption

Ellen L. Berg, Christopher Southan, Dana E. Vanderwall, Alex M. Clark, Isabella Feierberg, Rama Balakrishnan, Christopher Butler, Vladimir Makarov, Sheryl P. Denker, Samantha Jeschonek, Jason Harris, Peter Winstanley, T Ikeda
article en
1 citations

Abstract

We present a standardized metadata template for assays used in pharmaceutical drug discovery research, according to the FAIR principles. We also describe the use of an automated tool for annotating assays from a variety of sources, including PubChem, commercial assay providers, and the peer-reviewed literature, to this metadata template. Adoption of a standardized metadata template will allow drug discovery scientists to better understand and compare the increasing amounts of assay data becoming available, and will facilitate the use of artificial intelligence tools and other computational methods for analysis and prediction. Since bioassays drive advances in biomedical research, improvements in assay metadata can improve productivity in discovery of new therapeutics, platform technologies, and assay methods.

SLAS DISCOVERYVol. 29(8)
Palo Alto Research Center (US), AbbVie (United States) (US), Medicines Discovery Catapult (GB), Gene Therapy Laboratory (FR), AstraZeneca (South Korea) (KR), Jnana Therapeutics (United States) (US), Hydrosolutions (Switzerland) (CH), Reed Medical (United Kingdom) (GB), Mundipharma (United Kingdom) (GB), Semantic Designs (United States) (US), Collaborative Drug Discovery (United States) (US), AstraZeneca (United States) (US), Universitas Islam Makassar (ID), University of Edinburgh (GB)
Climate action
Openalex Percentile: Top 42%
Biomedical Text Mining and Ontologies
0.23
DOIOpen Access PDFOpenAlex
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