Life Sciences companies are navigating unfamiliar waters. A shift in consumer-preference to digital and value-based care, the dizzying speed of technological advancement and a renewed focus on patient-centric solutions have coalesced to present new challenges for traditionally slow-moving life sciences businesses.
The convergence of these factors has also given rise to a new, digital, data ecosystem of healthcare – Connected Health. Connected Health technologies have been widely recognized as the ‘next big thing’, offering benefits such as increasing patient engagement, improving quality of care and improved patient experience. While these technologies have already begun to be realized in consumer fitness applications and digital therapeutics, the life sciences industry has not been as successful. Faced with a breadth of legacy challenges from regulatory issues to sluggish innovation and drawn-out approval processes, adoption and implementation have been slow to get off the ground in the commercial sector.
So how can companies capitalize on these connected health technologies, drive both innovation and revenue objectives and scale and mature them to drive lasting healthcare transformation? In short, the foundation for effective digital transformation in life sciences needs to be a unified and holistic data approach, one which looks widely and blends smart, modern technology with human capabilities to drive intelligent innovations.
De-siloing business data: driving outcomes across the value chain
Until now, life sciences has been marked by a siloed digital culture, where data has resided in different departments and with different teams. This disjointed system has made it difficult for healthcare and life sciences practitioners within an organization to draw insights from one another, and as such can prevent them collectively from providing accurate healthcare design and delivery.
The answer? Integrating data sets and simplifying the management and extraction of data to empower and activate a connected healthcare ecosystem. Doing this successfully has the potential to provide an extended, 360-degree view of a patient sat within the wider healthcare system/chain. Just look at the Apple Watch; integrating pedometric, diastolic, systolic and sleep data (to name a few) it gives consumers a thorough understanding of their day-to-day health. Feeding into the wider Apple Health application, Apple now has a full perspective on an individual on one singular, unified platform. From here it can drive a diverse set of products and services towards them.
Life sciences organizations should take note. By accessing a catalogue of data from various teams across the value chain – from R&D, to manufacturing, commercial and so on – Life Sciences companies can build a knowledge-graph, rich in clinical and operational data insights. Developing a unified platform where this data can be hosted, stored and accessed easily? Even better. Decentralizing data allows separate pockets of the enterprise to drive positive outcomes for both business and patients – for science teams this may mean speeding up analysis, while for manufacturing this may mean better demand planning and for commercial teams this may mean understanding patient experiences and journeys better.
From de-siloed to data ecosystems: building a network of data-sharing
When it comes to solving big problems and providing accurate results, there’s often strength in numbers. Well, the same rings true for the life sciences industry. Data sharing between stakeholders, whether that be patients, healthcare providers, payers or pharmacists – has a transformative potential for the nature of healthcare provision, shifting from traditional reactive, symptom-based care toward proactive, personalized care. However, crossing these previously well-guarded borders requires a systematic and cultural shift – which traditionally has been time consuming, ineffective, and clunky. All of which make it unsurprising that life sciences companies have been hesitant to adopt this approach.
But to drive potentially life-changing R&D and future innovations, life sciences organizations will need to widen their perspectives and look outside the walls of their own laboratories. Collaborating, partnering, and even sharing data, these companies can draw on knowledge and expertise from around the world. The result? A cross-pollination of deep scientific and healthcare expertise at scale.
Perhaps the most impactful possibility data ecosystems offer, is accelerating new drug discoveries. Collecting and comparing clinical trial data from across the world, at scale, can help speed up the process of identifying, validating, and approving new drugs and healthcare treatments. As such, Life Sciences companies can then bring safer, more effective therapies and solutions to market faster.
Looking outwards for societal good
Digital healthcare hubs or initiatives are cropping up across the world, highlighting a willingness to collaborate within the industry. However, the landscape is observing an uptick in the number of strategic investments by big pharma looking to start-ups’ technology to address their digital transformation needs.
In this ‘trustless’ industry, collaboration, not domination, holds more potential for delivering positive health outcomes and wider societal good. The industry should realize the potential of trust and lean towards partnerships rather than monopolies. To ensure this can be done fairly and seamlessly, data must be made Findable, Accessible, Interoperable, and Reusable (F.A.I.R). Doing so will ensure data can be used for further research and to foster further good.
Trusting the data: governing with skill
Having the best technology means absolutely nothing if you can’t use it correctly. And with this heightened view on data ecosystems comes an enhanced scrutiny on data governance, ownership, and management. Those looking to navigate these murky waters and fully capitalize on the benefits of data will need to govern with trust. An essential first step is making sure data meets all necessary requirements and standards.
But as the industry adapts, so too will regulations. Companies must employ a level of flexibility and agility to continue to successfully leverage data ecosystems. This is where the unified data platform will again come in handy, as this centrally managed connected health system will help drive transparency in the regulatory process.
Previously, dealing with data may have fallen to a small IT team cooped up in a back-room, acting as important, yet almost external, contributors. But as Life Sciences companies transition towards a more unified, connected ecosystem, so too must the governance of data. IT teams must become absorbed, integrated and part-and-parcel of the wider organization. Doing so will require the upskilling of current staff along with the attraction and retention of new data-driven skills.
Connected Health innovation continues to move in full force, transforming the business and delivery of healthcare products and services. Data ecosystems and the holistic approach that underpins them offers an accessible, scalable and valuable solution to the world of healthcare. So yes, Life Sciences businesses might have a tricky job – but there are tangible and useful tools they can use to drive lasting and transformative change.
By Olivier Zitoun, Global Life Sciences Industry Lead at Capgemini
