Pippa White, senior global account director for Life Sciences at SAS, explores the reservations many in the industry have and highlights why now is the time to embrace analytics in the cloud.
Key insights:
- Athough almost every sector has embraced cloud-based solutions, which have driven significant progress, the life sciences industry still has its reservations.
- There's value in being able to spin up specific, highly customised environments for each project’s needs - one much easier to achieve in a cloud environment than on-premises.
- An analytics partner can provide a data science platform that encompasses classical statistics and AI, and governs the data science lifecycle from end to end.
Almost every sector has embraced cloud-based solutions which have driven significant progress, however, the life sciences industry has had its reservations. Regulatory scrutiny and reputational risk mean that information security is paramount where patient medical records are concerned, and the results of clinical trials are commercially sensitive too. As cloud-based systems continue to develop in functionality and safety, becoming a cornerstone of the cutting edge in most sectors, cloud analytics is becoming vital for modern demands.
The law of unintended consequences
Keeping data science on-premise has its downsides. Unlike some other regulated industries, pharmaceutical research is much faster paced. As we’ve seen over the past two years, in the face of a global pandemic, the race to find a vaccine can’t wait for the IT department to complete a company-wide technology rollout.
When a new initiative starts, the team needs the right data science infrastructure in place from day one—and if the central IT organisation is unable to respond quickly, teams tend to take matters into their own hands. This results in fragmentation, making central data governance and information security almost impossible to achieve.
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Similarly, when teams are working on projects in a wide variety of research areas, from oncology and biopharma to rare diseases and vaccines, a one-size-fits-all infrastructure is not going to be optimal for everyone. There’s real value in being able to spin up specific, highly customised environments for each project’s needs, and spin them down again when they’re no longer needed. This is much easier (and more cost-effective) to achieve in a cloud environment than on-premises.
How cloud analytics can help you take back control
It’s time for life sciences companies to take another look at cloud-based analytics. A cloud platform capable of expanding to meet the needs of research, manufacturing, sales, and other business areas actually improves control and governance. By making the platform flexible enough to meet new requirements in hours or days rather than weeks or months, you eliminate the motivation for line-of-business teams to break away from corporate standards and build their own shadow IT systems.
At the same time, cloud data security and privacy are no longer open questions. Highly regulated sectors, such as banking and government, have proven that cloud systems can be just as secure as on-premises infrastructure, and regulators are getting on board too. The industry’s response to the COVID-19 crisis showed what we can achieve by extending ecosystem partnerships and sharing data in the cloud, and regulators played a key role in those collaborations.
A compelling proposition
Cloud-based analytics can be a compelling proposition for life sciences companies. While a cloud provider offers the flexible, scalable infrastructure to launch new projects in minutes, an analytics partner can provide a data science platform that not only encompasses classical statistics, optimisation, and artificial intelligence/machine learning, but also manages and governs the data science lifecycle from end to end.
That means every dataset is traced back to its original source, every model is tracked to ensure it has received the right approvals before it is put into production, and every decision is auditable and explainable. So, you can ensure your use of data and analytics is ethical, transparent, and compliant with all your regulatory reporting requirements.