Creating more open and interoperable systems
It may be a challenge for commercial pharmaceutical companies to share proprietary data today, but many are sharing noncompetitive, HIPAA-compliant placebo data across studies without privacy concerns. They are doing so via an application programming interface (API)–first approach (a strategy which anticipates data-sharing across applications by design and allows for standardized, programmatic connection of applications). This approach creates a technical foundation for interoperable data-sharing as future collaboration incentives and cultural norms change and as an alternative to more open models (i.e. open APIs). The API-first organizations have frameworks that:
- Rank, flag, and categorize data sets for regulatory purposes
- Manage shareable and nonshareable data
- Establish baseline and incremental controls as greater security is needed
In health care, wearables are API-first technologies that allow data to be shared from devices to digital apps with privacy controls in place. Available in shareable and manageable formats, this data can be distributed across organizations for R&D purposes.
Cloud data warehouses, storage archives, and more
The cloud encrypts all data at rest and offers a variety of storage options for data with high input/output requirements. It also allows unique scale-up/scale-down capabilities. These advantages enable researchers to ingest petabytes of data at a given time and run queries by scaling up compute on-demand and temporarily, only paying for additional capacity when used. At the same time, the cloud offers dense/cold archive storage for long-term archival needs.
Scalable cloud ecosystem infrastructure
A vast majority (94%) of respondents believe real-world evidence in R&D will become increasingly important by 2022.23 A scalable cloud ecosystem would allow hospitals to share real-world data across their internal and external public/private networks to accelerate the entire ecosystem’s ability to target novel diseases or subpopulations who express major diseases differently. This is the cloud’s network effect in action—with just one important data set. To play that scenario forward, collaborative cloud ecosystems require the right operating model, such as a third-party arbiter, and incentives to ensure data safety, risk management, and IP protection—which is a journey still in progress to achieving these network benefits.
Research has shown that a network of ecosystems can help harness and accelerate distributed innovation for complex, externally-driven problems.24 It can facilitate a more collaborative approach and enables more diverse perspectives.25 Deloitte’s Transforming Clinical Development research has found some organizations are already experimenting with transformative approaches to drug development, such as use of real-world evidence and adaptive trials. Scaling the use of these approaches requires an ecosystem model wherein companies work collaboratively and transparently with multiple stakeholders. From a technology perspective, companies require interoperable data, knowledge management, and analytics platforms and processes, as well as scalable and secure cloud capabilities.26
From an R&D perspective, Deloitte’s 2020 Real World Evidence survey reveals that 16 out of 17 participating companies are using cloud platforms for real-world evidence and all the surveyed mature companies have a centralized, primarily cloud-based analytics platform.27 A scalable cloud ecosystem would allow hospitals to share real-world data across their internal and external public/private networks to accelerate their ability to target rare and novel diseases and cater to underrepresented populations. This could also open the door to cloud ML services to predict acute events like sepsis and understand disease states and linkages, such as congestive heart failure and diabetes.
The COVID-19 Healthcare Coalition, a private sector-led collaborative response to coronavirus, developed a cloud-native platform with secure/authenticated cloud storage, a data ingestion pipeline to sort/understand 300+ curated resources, and a big query searchable metadata repository for secure, scalable collaborative research. The platform has enabled members to support frontline responders and researchers and to improve treatment, regiments, vaccines, and device testing.28