Article

The future of real-world evidence

Biopharma companies focus on end-to-end, AI-driven, internally developed solutions

​Biopharma executives are placing greater emphasis on real-world evidence (RWE), a Deloitte life-sciences survey finds. Leaders increasingly must show value for access, understand the patient journey, and provide more data. The survey shows how RWE plays a role.

MANY biopharma companies are increasingly using real-world evidence (RWE)—clinical evidence about a product’s usage, potential benefits, and risks derived from real-world data (RWD)—not only to demonstrate the value of their products but increasingly to address regulatory requirements, drive drug development, support outcomes-based contracts, and reduce products’ time to market. But are they investing enough? What kind of technology, operating model, and talent upgrades are they considering? Do they face any barriers to adoption? What does the future of RWE look like?

Deloitte’s annual RWE benchmarking survey (the inaugural edition published in 2017) studies how these companies are using RWE, what they are investing in, areas of impact, and the hurdles to successful adoption.

Since we published our first survey, the volume and variety of RWD being generated has continued to expand. Sources now include electronic medical records, health insurance records, genomics, social media, and wearables. The technology platforms and analysis tools available to manage and derive insights continue to evolve, and the application of RWD across the enterprise—and thus the importance biopharma executives are assigning to RWE—has increased. Another important change is that regulatory bodies are working toward providing clarity on the use of RWE for regulatory decision-making. In fact, the FDA has taken steps to provide guidelines around the use of RWE, and is collaborating with the industry to explore its uses.1

The findings of Deloitte’s second survey not only reflect and elaborate on these changes but also shed light on how 20 leading biopharmaceutical companies are trying to optimize the use of RWE through investment, application, external partnerships, and technology.

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A focus on end-to-end enterprise solutions

This year’s survey shows that biopharma companies are investing more in RWE capabilities, with a focus on end-to-end solutions that address the entire product life cycle. In the survey, 90 percent of respondents have either already established or are currently investing in building RWE capabilities for use across the entire product life cycle, though only 45 percent currently have capabilities mature enough to do so.

According to respondents, stakeholder pressure to demonstrate the value of treatments and a shift toward personalized care, as well as new business imperatives such as value-based contracting, novel clinical trial design and execution, and support for regulatory submission, are helping drive this effort.

Building an in-house engine

Though biopharma companies have traditionally relied on external vendors for RWD collection and analysis, many are now opting to develop these RWE capabilities in-house: 70 percent of respondents are building or increasing capabilities to conduct more of their RWE studies internally, and 15 percent are building capabilities to exclusively resource studies internally.

This means more spending on RWE-related talent and technology, and our survey results corroborate this. The two biggest increases in investment over the next year are expected to be in people (30 percent) and technology platforms (25 percent) to support the organization’s RWE capability. Hiring experts to build and implement RWE-enabling systems, such as machine learning systems, may be the prime and immediate focus. But it is also important to make RWD and analytics accessible to a wide range of internal stakeholders, calling for investment in the right technology platforms and external partnerships to democratize the uses and insights that RWD promises.

Investing in talent and technology

Like other industries, some biopharma companies are overhauling their IT platforms and strategies to support the big data analytics that are central to RWD analysis and insight. The trend appears to be toward a centralized, largely cloud-based enterprise platform that is capable of data ingestion and integration, advanced analytics, visualization, and knowledge management.

And as the volume, variety, and velocity of structured and unstructured real-world data grow, artificial intelligence and machine learning will likely be required to adequately capitalize on the potential of health care data to generate life-saving insights such as identifying patients with undiagnosed or underdiagnosed diseases. In our survey, only 60 percent of respondents report currently using machine learning, but almost all—95 percent—expect to use it for RWE in coming years.

Another interesting trend is the increasing use of nontraditional RWD such as purpose-built linked data (such as clinical data linked to molecular data) and data generated from patients’ wearables or health apps to generate RWE. Evidence generated from these sources could provide quicker and deeper insights into disease progression, treatment pathways, and patient benefit. This trend can also create new opportunities for partnerships with health systems, patient advocacy groups, digital health start-ups, and even patients themselves over time. While less than 60 percent of companies are currently using these data sources, several expect to increase their use in the next 12–18 months.

Overcoming barriers to adoption and value

While our research shows that the intent to adopt and apply RWE is there, execution is not easy: 75 percent of respondents said lack of receptivity by external stakeholders such as payers and providers is a major barrier to the development of RWE capabilities, 70 percent cite internal stakeholders’ lack of understanding, and 65 percent, lack of access to the necessary external data.

Visible buy-in and support from executive-level leadership is necessary to change the company’s mindset and drive broader adoption of real-world data use across the enterprise, while lack of receptivity from external stakeholders can be overcome through transparent communication and new collaborative models for engagement. Strategic partnerships can also be important for the integrated adoption of RWE, especially when it comes to data access.

An overall solution to all these challenges could be new operating models and governance that can bring about a shift in cultural mindset and breaking down of organizational siloes. Some companies are experimenting with such models.

As the importance of RWE continues to rise, the answers for biopharma companies seem to lie in enterprisewide technology solutions, new operating models to support end-to-end evidence management, and external partnerships. To learn more about this year’s survey and how RWE is contributing to the changing landscape of biopharma product development, read the complete article on Deloitte Insights.

Authors

Brett Davis is a principal in the life sciences and health care consulting practice of Deloitte Consulting LLP, and general manager of ConvergeHEALTH by Deloitte. He is based in Philadelphia.

Jeff Morgan is a specialist leader in Deloitte Consulting LLP and a member of the leadership team of ConvergeHEALTH by Deloitte. He is based in Parsippany, NJ. 

Sonal Shah is a senior manager with the Deloitte Center for Health Solutions within Deloitte Services LP and leads the center’s life sciences research. She is based in New York.

Acknowledgments

The authors would like to thank Terry Hisey for his expertise, support, and guidance. The authors would also like to thank Seb BurnettDavid HardisonDeborshi DuttRaveen SharmaKristin FeeneyJodi ReynoldsMary CumminsMike DeLoneGreg RehNeil LesserRalph MarcelloSatish NelanuthulaRamani MosesLauren WallaceLynn SherryJon Louis, and many others who contributed their ideas and insights to this project.

Project team: Karla Feghali, manager, ConvergeHEALTH, was instrumental to survey design, recruiting, and interviews; interpreting study results; and editing the report. Wendell Miranda managed survey recruiting, conducted analysis, created charts and graphics, and wrote sections of the report. Leslie Korenda optimized the survey design and led the data analysis. Ryan Carter helped with recruiting, led interviews, and wrote sections of the report. Sanket Surve programmed the survey, analyzed the raw data, and created data tables. Aleks Lazic provided input into the survey design and results.

Cover image by: Gwen Keraval

Endnotes

1 Jacqueline Corrigan-Curay, “Real world evidence: A path forward,” U.S. Food & Drug Administration, September, 2017. View in article

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