One of the most valuable assets for any organisation is its data. However, most pharmaceutical companies are unable to realise its true value as a result of either i) deploying a data management system that is geared towards entering rather than mining data and/or ii) replacing such systems over time, resulting in silos of legacy data.
The way in which an organisation captures and manages its data is fundamental to addressing this problem. A wider scientific community initiative has resulted in the establishment of the FAIR principles to ensure that data is Findable, Accessible, Interoperable and Reusable. Although initially focused on the accessibility of public domain data, the FAIR principles are rapidly gaining interest from the pharmaceutical industry.
The benefits of FAIR can be illustrated using the example of bioassay data management. A significant proportion of the pre-clinical data that has been accumulated by every pharmaceutical company is a result of conducting a range of biological assays to characterise drug targets and evaluate potential therapeutic molecules. Databases dedicated to managing bioassay data contain an amazing wealth of R&D knowledge and, as such, provide a rich resource for mining with both scientific and operational questions.
When implementing a change in data management strategy, it should not be limited to legacy data. Based on FAIR principles, SciBite uses semantic enrichment to unlock the value of bioassay data via retrospective analysis of existing data and via SciBite Forms: an intelligent data entry solution for newly generated data.
To learn more, download the full use case.
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