Transform Your Enterprise Data with FAIR Principles

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

Like many industries, pharmaceutical companies have seen the amount of data collected multiply over recent years. Navigating through an ever-growing array of data silos is becoming an increasing burden to data scientists involved in the research and development of new drugs. But what if researchers didn’t have to spend days sifting through hundreds of different data repositories, waiting on responses from other teams within the organisation or reading a new research article only to find the information was out of date or inaccurate?

FAIR Data Principles for Pharmas: Findable

In this first blog post in a series of four, we will explore how by using MarkLogic as a Data Hub, multiple pharmaceutical companies have made their data ‘findable’ – the F in the FAIR data principles that act as guidelines to improve the findability, accessibility, interoperability and reuse of digital assets.

By making their data findable, pharma companies that use a MarkLogic Data Hub benefit from greater efficiencies in the R&D organisations, which in turn can have a significant knock-on effect in terms of shortening time to market and reducing costs for new drug development.

The MarkLogic Data Hub enables pharma organisations to ingest all of their data as-is and then harmonise it to get an accurate and consistent representation of all their data. Underpinning the multi-model Data Hub are powerful document and semantic capabilities that enable you to enhance your data with ‘globally unique identifiers’. This means you can easily define the relationships between disparate pieces of data, allowing you to connect the dots and make data even more findable in a way that cannot be realised using other technologies.

MarkLogic’s powerful linked data capabilities enable you to connect the dots and see all of the relationships in your data through one pane of glass. Both internal and external sources of data can be integrated to provide a holistic view of your research data. It makes it possible to make requests and ask questions such as: “Find experts on the effect of exercise on insulin resistance.” Or, “What is the market potential of developing a drug that targets this protein?”

Using MarkLogic’s envelope design pattern, when documents are ingested or harmonised, they can be wrapped with as much data as you want. This typically shows the provenance of data – when the document was created, its source, who authored it, when it was last changed as well as any enrichment to the document itself. By wrapping the document rather than keeping separate sources for metadata and data, search can be much more powerful as there is a single place to look up all of the facts.

MarkLogic has some of the most powerful search functionality available. It has been at the heart of our technology for more than 15 years, and to this day, it is still critical to our success, and of course, to making data more ‘findable’. One of the leading pharma companies we’re working with today is AbbVie, which describes the enterprise search that MarkLogic has enabled as the ‘Google for AbbVie’. Hear more about how AbbVie has dramatically increased its speed to insight by using the MarkLogic Data Hub.

Interested in making your data FAIR? In the rest of this blog series, we will explore how MarkLogic enables pharma companies to achieve ‘accessible’, ‘interoperable’ and ‘reusable’ data. In the meantime, however, why not try out the MarkLogic Pharma Research Hub – a revolutionary new application to facilitate drug discovery built on top of the MarkLogic Data Hub.

Learn More

• Read the blog post, Introducing the MarkLogic Pharma Research Hub.
• Get the IDC Customer Spotlight, Creating an Extensible Data Platform at a Leading U.S. Biopharmaceutical Company.
• Watch Amgen: Semantic Technology Assisted Data Harmonizing and Joining Optimizes Transportation.