Science 37 hopes to help researchers produce clinical trial results that are closer to real-world experiences, for the benefit of patients, pharma, and payers.
As the incidence of diabetes continues to climb, so does the overall cost of treatment, now estimated at $245 billion a year in the United States.1 This increasing burden on payers is forcing them to closely examine the real-world effectiveness of approved therapies. Payers also seek to understand how effective a therapy may be in an individual patient, using predictive analytics. This approach, often referred to as precision medicine, supports the use of the most cost-effective treatments as first-line choices.
To address the need for more effective treatments for diabetes, pharmaceutical companies are using the latest developments in biotechnology and genomic science to develop ever more advanced treatments with new mechanisms of action. While these therapies are often more expensive per unit than older ones, they also come with the promise of improving patient outcomes significantly enough to deliver reductions in both short- and long-term costs related to the disease.
Digital technology has become critical in driving more efficient and accurate data collection through all stages of research and development. The ease of use of digital technology is transforming clinical trials and providing data, such as patient-reported outcomes, that are much more reflective of how effective treatments are in the real world.
Traditional randomized controlled clinical trials call for the procedures and treatments to be conducted at brick-and-mortar research centers, which are artificial conditions not necessarily reflective of how the treatments will be used by patients in real life. It shouldn’t be surprising that many of these clinical trials fail to provide the kind of data both providers and payers need to ensure the treatment will work for an individual patient.
As a result, patients may be prescribed a treatment that according to the clinical trials should be effective and that payers believe will be cost-effective—only to find it provides less than ideal outcomes in actual use. Payers thus can spend significant healthcare dollars on treatments that are likely to fail, when the right clinical trial data might have helped to direct providers to a truly effective option for a particular patient.
Digital Technology as the New Foundation
The application of the latest digital technology, including advanced data analytics, has allowed investigators to reimagine clinical trials that enable measurement of variable s that have
proved challenging to collect previously.
Making use of digital technology allows for the passive collection of data from a variety of different sources, including wearable sensors that measure amount of sleep, heart rate, and physical activity. Digital platforms also enable decentralized trials—which incorporate electronic consent, telemedicine capabilities, and accurate data collection conducted outside the research center, at a patient’s home. These can produce data that are far more representative of what patients do with an experimental drug or device as they go about their normal activities.
Digital tools can also be employed for patient recruitment. At my company, we use a number of different digital strategies, including social media, to engage and recruit patients with a
variety of medical conditions. Not only are these tactics useful to recruit for specific trials, but they also allow us the opportunity to establish databases of micro communities for those patients interested in participating in future clinical trials.
Driving Better, More Inclusive Results
Another major hurdle in conducting clinical trials that produce reliable real-world data is identifying and enrolling an appropriate patient population. With traditional trials, patients who cannot travel to a research center are excluded from the pool. Since research centers are often located in larger urban areas, people who live in distant suburbs, or in more rural areas, simply don’t or can’t afford to participate because of factors such as out-of-pocket costs and the time commitment required. In-home clinical trials eliminate many of the barriers to participation and therefore allow far more representative patient populations access to the trial.
This is particularly important when it comes to the need to include people of color or ethnic minorities, individuals who are often seriously underrepresented in clinical trials.2 In many
cases, members of these communities have been shown to respond differently to a treatment that was deemed effective in a clinical trial in which they were not adequately represented. This is vital for evaluating diabetes treatments in the United States because of the disproportionate incidence of the disease among African Americans, Native Americans,3 and those of Latino or Hispanic4 descent.
The importance of including a more diverse population is clear when one considers the early experience with angiotensin-converting enzyme (ACE) inhibitors for the treatment and prevention of hypertension. The drugs were approved after the usual set of randomized controlled trials and appeared to demonstrate excellent results. The trials, however, were unable to recruit a significant number of African American patients—a group who not only suffers from hypertension at a much higher rate than the overall population but responds quite differently to ACE inhibitors. As a result, only after they were prescribed to African Americans was it discovered that ACE inhibitors did not work nearly as well for them
as had been predicted by the clinical trials.5
Expanding Access to Care
Patients enrolled in decentralized trials enabled by digital technology and telemedicine receive healthcare in the convenience of their home, giving them access to care they may not have had otherwise received. The clinical trial itself provides an opportunity to administer more general care for at-risk patients because the trial is effectively enforcing a schedule of interactions between the participant and the investigators. An additional benefit is the potential access to innovative treatments provided by the trial itself. For patients suffering from a serious condition like diabetes, there is a chance for them to be treated with something they might otherwise not qualify to receive.
In summary, innovative companies like mine have invested in hiring physician scientists who have experience working across healthcare sectors including pharma, biotech, clinical care, and academia. This expertise, coupled with innovative digital technology, has enabled us to engage and recruit diverse populations of patients and execute trials efficiently, more reliably, and with more relevant outcomes reflecting real-world experience. The benefits to the patients include access to clinical trials and enhanced care through telemedicine in the
comfort of their homes, the benefit to the payer includes data to support the value proposition of the therapy, and the benefit to our sponsors is in condensing timelines and accelerating time to market.Author Information
Henry Anhalt, DO, is the vice president for medical affairs for Science 37. He is a board-certified pediatrician and pediatric endocrinologist whose work focuses on novel approaches to research and treatment of people living with diabetes and metabolic disorders.References
1. American Diabetes Association. Economic costs of diabetes in the US 2012. Diabetes Care. 2013;36(4):1033-1046. doi: 10.2337/dc12-2625.
2. US Food and Drug Administration Office on Women’s Health Research. Dialogues on diversifying clinical trials. fda.gov/downloads/ScienceResearch/SpecialTopics/WomensHealthResearch/UCM334959.pdf. Published 2011. Accessed February 15, 2018.
3. Centers for Disease Control and Prevention. National diabetes statistics report, 2017. cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf. Published July 17, 2017. Accessed February 15, 2018.
4. Schneiderman N, Llabre M, Cowie CC, et al. Prevalence of diabetes among Hispanics/Latinos from diverse backgrounds: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Diabetes Care. 2014;37(8):2233-2239. doi: 10.2337/dc13-2939.
5. Ogedegbe G, Shan NR, Phillips C, et al. Comparative effectiveness of angiotensin-converting enzyme inhibitor-based treatment on cardiovascular outcomes in hypertensive blacks versus whites. J Am Coll Cardiol. 2015;66(11): 1224-1233. doi: 10.1016/j.jacc.2015.07.021.