Accelerating innovation that leads to more advances and better patient outcomes

In our conversations with life sciences CEOs, we know that two key questions are top of mind:

  • How do I innovate faster to bring novel treatments to market that address unmet needs?
  • How do I create better experiences for healthcare providers (HCPs), patients and our talent?

As companies migrate to the cloud to reduce operational costs and advance their technology capabilities across their business, there is a tremendous opportunity to leapfrog outdated ways of interacting, while reimagining experiences that support new ways of working within and across core business functions.

Life sciences companies are transforming the way they operate, communicate, share information and deliver services in order to meet the growing demands and expectations of the industry. This transformation is no small task, so many leaders are looking toward solutions that can help unlock the massive potential value of new technologies—and one of the most exciting among them is edge computing.

Understanding edge computing

In many ways, we already use edge computing in our daily lives through products such as smart-speakers, smartwatches, intelligent thermostats, and more—essentially any device that computes locally and talks to cloud-based platforms and applications.

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Edge is where digital meets physical and real-time data can be used to reimagine processes, experiences and business functions at scale.

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Edge enables computation where the data resides—either on a device, an instrument, or other equipment in the lab—while still benefiting from all the capabilities offered by the cloud. It integrates centralized and distributed architectures to improve experiences, connect data and create seamless, personalized, contextually relevant, real-time communication in a connected world.

Some industries are already taking advantage of the full capabilities of the Cloud Continuum with an integrated architecture across cloud, on-prem and edge. Have you ever wondered how your favorite fast-food store knows just how many waffle fries should be cooked per minute? By computing at the edge each store can adjust corporate forecasts with specific on-site, real-time data from their kitchen and point-of-sale systems. Using edge, they can make sure everyone’s fries are crispy, whether it’s a slow afternoon or a crush of families after a little league game.

This hyper-personalization is made available by treating cloud as an integrated and orchestrated set of capabilities (from the cloud to the edge) rather than a migration shift.

Four ways edge computing unlocks value

Edge computing offers opportunities to make work more compelling across many functions in life sciences—from digital labs and clinical trials to intelligent supply chains and launching new treatments. In fact, there are four ways edge computing could provide immediate value to the industry:

  1. Faster: Edge reduces latency. Imagine an Amazon Go experience that anticipates what a HCP needs next based on the progression of a particular patient— with tech that fades into the background. Or developing talent and activating sales reps with a similar guided set of cues with real-time data to assist them as they navigate their roles.
  2. More economical: Edge lowers the costs of data management. Imagine being able to detect sample quality and produce required documentation as the work happens, with the computer as the second set of eyes. Or being able to conduct clinical trials with participating patients distributed across the globe and relevant health information is continuously monitored, collected, analyzed and shared.
  3. Always on: Edge increases up-time. Imagine labs that are always connected, continuously running experiments and never miss connecting the latest information. This could help predict maintenance issues, supply shortages and/or diagnostic tool limitations before they happen.
  4. More private: Edge enhances privacy and security. Imagine tailoring HCP experiences without comprising privacy and ensuring they obtain the best fitting product information for the patient profile they are serving and treating exactly when they need it.

Together, these opportunities reveal the real-time interactions and split-second automation that will drive innovation and make work more intelligent, focused and faster paced. When capabilities reside on the edge, the business can capture all the activity that’s happening in the moment—and react immediately.

Edge computing also enables learning over time, delivering actionable insights that give life sciences companies the ability to reimagine and trial new treatments and experiences, measure results, adapt, scale seamlessly and more. When those new experiences anticipate what the scientist needs before they do, it’s because the ecosystem is continually getting smarter information based on everyone’s experiences over time.

So, it’s a question of when, not if, we take life sciences to the edge.

In our next post in this series, we will take a deep dive on edge computing and how it supports digital labs. Follow us on LinkedIn to learn more.

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Shelley Evenson

Managing Director – Song

Nina Lynch

Managing Director – Song

Andrea Smyth

Associate Director, Cloud First

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