Greg Reh, Vice Chairman, and U.S. and Global Life Sciences Leader, Deloitte LLP
Biopharmaceutical manufacturers rely on technology to discover and develop breakthrough treatments that can turn deadly diseases into manageable chronic conditions—or sometimes cure a disease altogether. But the costs of developing a new therapy and bringing it to market can top $2 billion;1 and the research and development (R&D) process often relies on a clinical-trial model that has changed little since the 1990s.
Costs are now increasing faster than revenues, which makes this model unsustainable. A Deloitte analysis of the return on pharmaceutical R&D investments among 12 large biopharma companies revealed a sustained decline—from 10.1% in 2010 to 3.2% in 2017.
Technology could help solve for some productivity challenges in the clinical-trial stage of drug development. It can help biopharmaceutical companies pull more meaningful data from trials and speed cycle times for products in development. Patients could see benefits, too, including higher satisfaction rates and better overall experiences during each phase of the trial.
Deloitte recently interviewed 43 leaders across the clinical-development ecosystem to understand how digital technologies are being used (or not) by biopharmaceutical firms. The full findings, published in “Digital R&D: Transforming the future of clinical development,” focused on understanding the relatively slow adoption of digital technologies in clinical development.
Surprisingly, many clinical trials still rely on paper. Even the largest and most technically advanced organizations are often only beginning to integrate digital technologies into their clinical development processes.
What are the barriers?
The interviewees recognize the potential for digital technologies to transform clinical development. But they also acknowledge challenges, such as data infrastructure problems (including interoperability issues), privacy rules, and a lack of data standards. There are also regulatory and cultural considerations. These issues can make it difficult to take advantage of new technologies and data sources. Moreover, interviewees agreed that issues related to the safety, performance, and reliability of new technologies must be addressed before they could be included in clinical development.
What are the opportunities?
Reach and enroll a more diverse patient base: Regulators, treating clinicians, and payers stress the need for greater demographic heterogeneity in study populations. Digital technologies can support the recruitment of a more diverse and representative study population, which could also help sponsors better understand the benefits and risks of new therapies across different sub-populations before going to market.
Furthermore, digital technologies can help researchers more accurately assess trial feasibility, and adjust inclusion-exclusion criteria accordingly. Such technologies can help enroll a more diverse patient base more quickly compared to traditional approaches. Case in point: Using a cloud-based platform, a technology-enabled clinical research company recruited patients for a rare-disease trial 20 to 30 times faster than could have been possible using more traditional recruitment methods. The company sifted through patient records from hundreds of trial sites across the U.S., and the result was a diverse study population.
Remove barriers to trial participation: An estimated 70 percent of prospective clinical-trial participants live more than two hours from the nearest study center, which could impact their willingness and ability to participate.2 The ability to conduct virtual clinical trials could encourage more patients to participate. One virtual trial screened more than 8,000 individuals and enrolled 372 participants within seven months to test a topical acne formulation, reducing projected enrollment time by approximately 30 to 50 percent.
Improve drug adherence: Ensuring medication adherence among patients is an ongoing challenge during clinical trials, and it is becoming increasingly difficult as treatment regimens become more complex. Adherence ensures that the effect of an investigational drug is fully reflected in the data. Some adherence tools use facial recognition to confirm that a medicine has been ingested, and generate non-adherence alerts to investigators.
Another example is a platform piloted by a large pharma company that leverages multiple technologies to automate investigational product supply and track adherence. At the trial site, the platform receives data from scanners to track the receipt, dispensation, and return of medication kits – eliminating paper documentation and reducing manual errors. To improve adherence, dosing instructions and instructional videos are sent to participants’ smartphones. Smart medication blister packs register each pill as it is removed, providing a means of continuous monitoring and early intervention in case of non-adherence.
Capture patient-centered endpoints: Advances in sensors and mobile technologies have made it easier to continuously collect patient-generated data. New technologies also make it possible to electronically gather patient-reported outcomes, including the ways an intervention impacts a patient’s quality of life. For example, a biopharma company created an app that gathers data from surveys and smartphone sensors on issues that rheumatoid arthritis patients face, such as joint pain and fatigue. The study found that raw accelerometer data from the phones could be converted into a score that was much more precise than motion-scoring exercises conducted in a physician’s office.
Analytical insights on clinical and patient-reported outcomes can also provide a competitive advantage and support the case for reimbursement.
Expand collaboration: The use of blockchain could make it easier to securely store and share clinical data—even among competitors. For example, organizations can securely share patient information and adverse events with organizations they collaborate with, or interim results with sponsors and regulators. The technology also can be used to manage and track informed consent across multiple sites, systems, and protocols.
Further, companies can consider experimenting with digital technologies by participating in industry consortia. Possible benefits include minimizing risks through shared investments in joint projects; incorporation of multi-stakeholder perspectives (patients, investigators, treating clinicians, payers, regulators); access to interdisciplinary expertise around analytics, endpoint validation and technology development; and data sharing.
A comprehensive digital R&D strategy can be essential to process large amounts of data effectively, make business decisions quickly and accurately, and generate evidence that supports the development of future products. Many of the business leaders we interviewed expressed a desire to be fast followers. Given the complexity of operationalizing a digital strategy, they understand the risks in falling behind. However, digital technology could allow early adopters to develop better patient experiences, deeper insights, and faster cycle times for future therapies.
Read more: Digital R&D: Transforming the future of clinical development
Endnotes
1http://csdd.tufts.edu/news/complete_story/pr_tufts_csdd_2014_cost_study
2https://www.fiercebiotech.com/cro/sanofi-launches-new-virtual-trials-offering-science-37