In previous blogs, I’ve discussed how the cloud, in its myriad dimensions, is central to disaggregation of care, value-based care and advanced AI/ML for both disease discovery and diagnostics. The cloud is also at the core of much of the innovation and evolution in life sciences.
However, there is a widespread perception that life sciences companies generally have been slow on the uptake of the full range and potential of cloud technology. While some of these concerns are valid, they bypass the technical and operational advantages the cloud confers. It’s a nuanced situation, so perspective is warranted.
COVID and the Cloud
The pursuit of COVID-19 treatments, dependent as they are on data gathering and sharing between organizations and across borders, is a catalyst in the equation of digital change and alignment across the life sciences industry. The essential discovery process for a potential pandemic cure requires a cloud-powered ability to manage, distribute and analyze big data globally. In fact, international sharing in pursuit of useful treatments to combat the COVID-19 scourge is evidenced by the widespread dissemination and application of models such as those from Oxford and the University of Washington.
The cloud provides a mechanism for continuously refreshed data, which in turn informs artificial intelligence/machine learning (AI/ML) algorithms that can benefit vaccine and therapeutics research.
One example is Moderna, a leading researcher in the COVID-19 arena that used the cloud’s breadth and power in numerous ways, enabling it to identify a potential vaccine in a mere blink of time. Moderna uses AWS in the following ways:
- As the platform for designing drug candidates.
- To apply ML to optimize the molecular sequence to facilitate manufacturing.
- For its manufacturing systems, optimizing the conversion of molecular sequences to actual vaccines.
- To swiftly transfer its manufacturing models to partners.
Another example is Sanofi’s partnership with Google Cloud and its migration to the Google Cloud Platform. To accelerate innovation, Sanofi can leverage the cloud’s infrastructure, analytics and AI/ML capabilities. Google deploys resources with industry expertise, and its cloud is geared to handle the vast amount of data involved in the life sciences industry.
Meanwhile, Swiss pharmaceutical company Novartis is collaborating with Microsoft to deliver AI to all its users’ desktops so the tools are applicable to every process. This approach ensures AI is used in its intensive scientific research – which is also cloud-enabled.
With work from home (WFH) now widespread (and likely to persist long-term), clouds afford huge workforce savings, slicing operational costs, curbing IT outlays and enabling multiple divisions or companies to simultaneously share enterprise data stores securely and without redundancy.
Dealing with the Data Deluge
Another factor rendering the cloud essential to drug and biologic discovery and medical device innovation is the sheer scale of the data and variables involved. The number of studies on conditions and new treatments for disease in the U.S. is huge, and new research adds to the knowledge developed almost daily on existing treatments.
The thousands of interactions in a clinical trial contribute to billions of data points collected by the public health system from which trends, patterns and insights are discerned from the interactions of the trillions of cells and microbes that comprise one person. This essentially boundless field of data requires cloud scalability to support our quest for insight and knowledge.
Historically, those thousands of interactions in a clinic took place in-person. However, in the COVID-19 era, teletherapy has become the primary means of clinician-consumer interaction. The rapid and likely sustained transition to virtual engagement further binds the clinical and commercial interests of drug and device manufacturers, healthcare providers and healthcare payers. The interdependencies to support telehealth – such as ensuring the doctor has the information she needs for treatment, payers receive confirmation treatment was used and biopharma companies confirm that treatment was effective – require cloud infrastructure to enable data ingestion, effective analytics and secure sharing.
Pace of Adoption
Amid all this, the uptake of cloud computing in life sciences has been understandably gradual: Security concerns and stringent compliance demands, existing legacy investments, costs associated with high-performance computing (HPC), talent attraction and retention, and a highly complex and disparate ecosystem – all these factors suggest a go-slow approach. But cloud technology and management has progressed rapidly, and with the pandemic as a catalyst, we see adoption of cloud across the enterprise as a near-certainty.
According to Gartner, earlier reluctance and delays have been largely overcome, and a cloud-first strategy is standard at most life sciences companies. However, multitenant adoption still faces resistance in the manufacturing and clinical labs functions. Smaller startups are widely adopting cloud-only approaches, while medium-sized companies are implementing cloud “opportunistically.” Larger organizations are reconfiguring their on-premises legacy systems to facilitate cloud usage. IT teams are motivated by the fact that AI and IoT, for examples, work best in the cloud.
According to IDC research, pharma is somewhat ahead of biotech in cloud deployment, with the gap largest for omnichannel content and external industry data analytics, and also leads in adopting industry-specific cloud solutions, especially for product lifecycle management (PLM). Significant percentages of organizations in both sectors have customized cloud solutions in place.
Reaping Cloud Benefits
Operationally, the cloud facilitates standard business process development, improving flows within the enterprise and enabling non-value-adding processes to be offloaded. Cloud management itself can be sourced to trusted partners to the precise degree desired, requiring strategic choices among private, public and hybrid options.
A successful migration to the cloud for life sciences organizations can take many forms, but the dividends it pays in research and commercial operations are meaningful. We expect rapid acceleration in cloud uptake across the bio-pharma and medical device industries, and we foresee established players catching up to digital natives, which are already deploying decision process automation via data management systems and AI/ML.
Outsourcing cloud management itself is a strategic move, and as science advances in the fight against COVID-19, as treatments become more targeted, and as care access and delivery evolves to virtual solutions, scalable, secure cloud platforms and tools will be enablers of a healthier population.
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