Annotation of in vivo pharmacology assay data in ChEMBL

Check out our new article that provides a classification of in vivo pharmacology assay data in ChEMBL so that assays that investigate a similar disease or phenotype can be grouped: http://dx.doi.org/doi:10.1038/sdata.2018.230

A substantial dataset of more than 135,000 in vivo assays has been collated as a key resource of animal models for translational medicine within drug discovery. To improve the utility of the in vivo data, an extensive data curation task has been undertaken that allows the assays to be grouped by animal disease model or phenotypic endpoint. The dataset contains previously unavailable information about compounds or drugs tested in animal models and, in conjunction with assay data on protein targets or cell- or tissue- based systems, allows the investigation of the effects of compounds at differing levels of biological complexity. Equally, it enables researchers to identify compounds that have been investigated for a group of disease-, pharmacology- or toxicity-relevant assays.

The annotated in vivo assay dataset is currently available for download at http://dx.doi.org/10.6019/CHEMBL.assayclassification and will also subsequently be accessible as part of a later release of the ChEMBL database (https://www.ebi.ac.uk/chembl/).

The in vivo assay annotation is a significant step forward to start to organise complex whole animal data with multiple measurement types & units, dosage, route of administration etc. To improve the annotation of the data, we would welcome your feedback via our dedicated helpdesk email: chembl-help@ebi.ac.uk, or by contacting the authors of the paper.
This work was supported by the European Union’s Seventh Framework Programme (FP7) under grant agreement no 602156 (HeCaToS 2013-2018 Developing integrative in silico tools for predicting human liver and heart toxicity; www.HeCaToS.eu), the Strategic Awards from the Wellcome Trust (104104/A/14/Z) and by core funding from the European Molecular Biology Laboratory (EMBL).

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