The Pistoia Alliance Tackles Challenges in Data Governance to Advance Digital Transformation in Pharma

Pharmaceutical

The Pistoia Alliance, a global, not-for-profit alliance that advocates for greater collaboration in life sciences R&D, today launched its Data Governance Community of Interest (CoI). The CoI was initiated in response to a roundtable discussion assessing industry priorities. Attendees were senior R&D professionals from pharmaceutical companies including AbbVie, Bayer, Bristol Myers Squibb, Novo Nordisk, Pfizer, Roche and Sanofi, and OSTHUS. Data governance is essential to enable digital transformation in pharmaceuticals and life sciences and to advance innovation. The new CoI will develop and publish best practices and standards for data governance, while also providing a platform for companies to come together to discuss common problems.

“Robust data governance and underlying data sharing infrastructure are essential to accelerate R&D innovation,” commented Dr Steve Arlington, President of The Pistoia Alliance. “The incredible response from the life science community to COVID-19 has demonstrated how much can be achieved when scientists work together. We now need to maintain this mindset and continue collaborating, so that we build an ecosystem to support seamless data sharing and remove this common barrier to innovation. The industry must develop data governance best practices to make working together more straightforward and secure, not just in the event of another public health crisis, but to ensure that we can make rapid progress against all unmet needs.”

“The Pistoia Alliance Tackles Challenges in Data Governance to Advance Digital Transformation in Pharma.“

Without a data governance strategy, secondary uses of data to further innovation are inhibited. For example, synthetic comparator arms in clinical trials; deploying advanced AI/ML & NLP in R&D; and using real world evidence to inform drug discovery and improve clinical trial design. The Pistoia Alliance surveyed the roundtable attendees on their organization’s current implementation of data governance. The results of the survey show there is a clear disparity in the way governance is rolled out across companies. In 44 percent of those surveyed, the chief data officer sits at the functional level rather than the strategic board level. Further, 44 percent reported that they do not have a chief data officer (or similar role) within their organization. This is likely to be causing a disconnect between data governance strategy and implementation, leaving gaps in the processes.

“Many of our members have been voicing similar concerns around data governance, data access, and compliance with legal and regulatory requirements,” commented John Wise, member of the operations team and leader of the Data Governance CoI at The Pistoia Alliance. “In response, we have created this Community of Interest to discuss and address these barriers, and to develop industry-wide best practices. Our aim is to help the life science industry make the most of its data, while it continues its journey of digital transformation.”

The survey also identified several barriers slowing down digitalization and the application of advanced analytics – most commonly siloed application landscape (64%) and siloed organizational landscape cited by 57% of respondents respectively. Today, data assets are often stored in varying formats, and are hard to retrieve, share and are not interoperable. To extract as much value as possible from the data, it needs to be machine readable and actionable; this is critical for data utilization in AI and machine learning. Implementing the FAIR (findable, accessible, interoperable, and reusable) guiding principles, focusing on data quality and strengthening data infrastructure are vital in enabling the life science ecosystem benefit from the data it’s creating. Another significant barrier is cultural resistance, in joint second place, also cited by 57% of those surveyed. To overcome this issue, the life sciences industry must address the longstanding and instinctive cultural bias against data sharing, by not only encouraging it, but incentivizing it.

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