Research, supply chain, manufacturing, and sales increasingly depend on partnerships in a digital ecosystem. Cloud-based analytics makes it possible to collaborate intelligently at scale.
For years, life sciences companies have been justifiably cautious about moving their data science functions into the cloud. Although the industry’s central purpose is to accelerate innovation in science and healthcare, companies are conservative when it comes to data—and with good reason. 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.
The idea of letting data live outside the corporate network, then, has always raised alarm bells. This has put a dampener on cloud adoption throughout the industry. Compared to other industries such as retail, and even banking, life science companies are lagging far behind the curve where cloud-based analytics is concerned.
The law of unintended consequences
However, keeping data science on-premises has its downsides too. Unlike other regulated industries, where it’s perfectly normal for initiatives to run over multiple years and the pace of change can be relatively slow, 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 organization is unable to respond quickly, teams tend to take matters into their own hands. This results in fragmentation, with hundreds of teams running their own systems, which makes central data governance and information security almost impossible to achieve.
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 customized 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
In fact, as analysts such as Gartner now argue, it’s time for life sciences companies to take another look at cloud-based analytics. A cloud platform that can expand to meet the needs of research, manufacturing, sales, and other business areas — not only facilitates innovation — 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. Banking, government, and other highly regulated sectors 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 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.
The power of partnership
At SAS, we’ve built a partnership with Microsoft that makes cloud-based analytics a compelling proposition for life sciences companies. Our unique advantage is that while Microsoft’s Azure cloud offers the flexible, scalable infrastructure to launch new projects in minutes, SAS brings a data science platform that not only encompasses classical statistics, optimization, 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.
We’re working with leading life sciences companies around the world to unlock the benefits of data science in the cloud. To learn more about how we can help your team take the next step, reach out to me today: Pippa White | LinkedIn