This blog is the third of a four-part series that explores the importance of FAIR (Findable, Accessible, Interoperable, Reusable) principles for pharmaceutical companies looking for a data platform to tackle their most critical business problems.

FAIR Data Principles for Pharmas: Interoperable

Data is interoperable when it can be integrated with other data sources and when other applications can easily interface with it. In the pharmaceutical industry, MarkLogic has successfully been used for mission-critical applications within Johnson & Johnson, AbbVie and many other top global pharma companies.

Most of our pharma clients are using ontologies to great effect. By using ontologies, these companies get an enriched view of their data. Properties of data can be defined with authority across datasets, which improves the confidence in substantiating facts from the data.

An ontology can give you a centralised place to define your data, which leads to greater possibilities when integrating data. Datasets can be integrated from disparate sources and even from beyond the organisation itself. Some powerful outcomes of using ontologies include gaining greater insight into the connections within your data and even the possibility of inferring non-obvious facts.

For pharma companies, there is a rich ecosystem of ontology and linked datasets that can be used to enhance your own data. Sources like Snomed, RxNorm, UniProt and PubMed are all useful sources for R&D, and MarkLogic is able to easily integrate them into a Data Hub alongside a pharma company’s own data such as drug development data, clinical trials and market data as part of our Pharma Research Hub offering.

By integrating data, organisations can boost the insights delivered from their data, but perhaps more importantly, they can also get a ‘single source of truth’ knowledge base that can benefit the entire company. Knowledge and data will no longer be lost within small factions of the enterprise.

Consistently among the pharma companies we have engaged with, we see that the speed at which they can integrate data from disparate data sources using MarkLogic technology is dramatically faster than if they used traditional relational database technologies. Indeed, many companies begin speaking with us after a failed attempt at integrating data using a relational database with an extract, transform, load (ETL) pipeline.

MarkLogic does away with ETL and upfront modelling of your data, with the result being faster time to results and a greater agility to respond to changing business demands.

AbbVie is one example of an enterprise that has achieved great success thanks in part to the interoperability of its data. Internal researchers at AbbVie previously had to navigate multiple internal data sources as well as multiple terms for an individual drug. These repositories had varying degrees of indexing and organisation. By using MarkLogic, AbbVie has been able to design a flexible system incorporating data harmonisation and enrichment using ontologies and MarkLogic Semantics. The result is that researchers can now query all of the integrated data in a single sub-second search.


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