Self-reporting data assets and their representation in the pharmaceutical industry

• Published in: Drug discovery today 2022-01, Vol.27 (1), p.207-214
• Main Authors: Della Corte, Dennis, Colsman, Wolfgang, Fessenmayr, Heiko, Sawczuk da Silva, Alexandre, Vanderwall, Dana E.
• Format: Article
• Language: English
• Subjects: ADF; AnIML; Data Accuracy; Data Curation - methods; Data Curation - standards; Data format; Data model; Diffusion of Innovation; Drug Industry - methods; Drug Industry - organization & administration; FAIR data; Humans; Information Dissemination - methods; JCAMP-DX; JSON; Ontology; Pharmaceutical data; Proof of Concept Study; Reference Standards; Research Design - standards; Scientific data; Technology, Pharmaceutical - methods
• ISSN: 1359-6446; 1878-5832
• DOI: 10.1016/j.drudis.2021.07.019

•Self-reporting data assets are introduced as an implementation of FAIR data.•Requirements for SRDAs are extracted from top pharma and biotech workflows.•A fit/gap analysis for Allotrope Data Format, AnIML, JCAMP-DX, and JSON is presented.•Allotrope Data Format is found to be the best representation for SRDAs. Standardizing data is crucial for preserving and exchanging scientific information. In particular, recording the context in which data were created ensures that information remains findable, accessible, interoperable, and reusable. Here, we introduce the concept of self-reporting data assets (SRDAs), which preserve data and contextual information. SRDAs are an abstract concept, which requires a suitable data format for implementation. Four promising data formats or languages are popularly used to represent data in pharma: JCAMP-DX, JSON, AnIML, and, more recently, the Allotrope Data Format (ADF). Here, we evaluate these four options in common use cases within the pharmaceutical industry using multiple criteria. The evaluation shows that ADF is the most suitable format for the implementation of SRDAs.