The Future of Intelligence for Life Sciences: Transcending Boundaries

The Future of Intelligence for Life Sciences: Transcending Boundaries

This IDC Perspective explores the challenges and opportunities associated with building intelligent life science enterprises, with an eye toward the future of intelligence in life sciences. Siloed data systems, clunky data integration strategies, and cost-intensive and laborious analytical methodologies have slowed down innovation and escalated costs. The life science industry was in urgent need of being rescued from being drowned by an unwieldy flood of data, which wasn't generating meaningful insights. Performance-intensive computing (PIC), driven by a parallelization of workloads, is providing life science companies with the power to learn, the power to grow, and the power to innovate. The pandemic has not only accelerated the need for innovation but also emphasized the need for collaboration. The ability to bring the COVID-19 vaccine to the market in less than a year and implement efficient mass-vaccination campaigns across the globe has served as a proof of concept to the industry of the importance of leveraging compute capability to drive innovation, implement smart supply chains, ensure equitable access, and build trust."Data, data everywhere, but a paucity of data-driven insights to drive future strategies has been the angst of this industry for a long time. GPU-powered transformer models based on deep learning neural network architecture to power accelerated innovation, federated leaning platforms to drive co-innovation strategies, and the use of data fabric models to generate real-time insights from scattered, diverse data sources, growing exponentially every day, will yield incredibly valuable intelligence that will reshape the future of the life science industry," said Dr. Nimita Limaye, research vice president, Life Sciences R&D Strategy and Technology at IDC."Life science companies have invested heavily in digital transformation and are poised to take the next step in designing intelligent enterprises. These investments will pay off in the future in a more productive knowledge workforce, efficient operations and a foothold in assuring successful product strategies and execution in the future," according to Michael Townsend, research director for Life Sciences Commercial Strategies at IDC Health Insights.

Please Note: Extended description available upon request.


Executive Snapshot
Situation Overview
Future of Intelligence Defined
Challenges
Path to Intelligence
Ability to Synthesize Information
Capacity to Learn
Delivery of Insights at Scale
Value from the Economies of Intelligence
Advice for the Technology Buyer
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Related Research
Synopsis

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