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Problem Tech Solves

Tech Brief

The traditional clinical trial model has hardly changed in 60-90 years, so, naturally, it is fraught with costly inefficiencies. Because traditional studies are designed around the use of brick-and-mortar clinical sites, with each site responsible for recruiting patients, the geographical barriers this system creates exclude more than 90% of both patients and physicians. Patients are, of course, expected to visit these sites throughout the clinical trial, but because they live an average of 26 miles away, this commute alone can place an immediate burden on many participants and their families. In addition, more than 80% of clinical trials are affected by delays, often because these geographical constraints make patient enrollment difficult for sites, and this can cost study sponsors upwards of $20 million a month in delayed revenue. The site model has been shown to be similarly restrictive in terms of recruiting diverse participant populations. Science 37’s mission is to enable universal access to clinical research — making it easier for patients and providers to participate from anywhere and helping to accelerate the development of treatments that impact patient lives. Unlike traditional studies, decentralized approaches offer a way for clinical studies to follow the patient, not the clinical site, using a mix of sophisticated software and integrated networks. These studies require the deployment of Science 37’s OS, incorporating innovative telehealth.

Tech Differentiators

As with all the greatest examples of tech-driven disruption, Science 37’s story is really about people. More specifically, it’s about the positive impact decentralized approaches to clinical research have on patients’ lives and the healthcare landscape as a whole. Science 37 uses telehealth innovation to: • Develop new life-saving and life-enhancing medicines • Enable universal access to clinical trials for both patients and physicians • Improve the diversity of clinical research so that participant populations better represent disease populations • Disrupt the outdated clinical trial model • Take important steps toward achieving a more equitable healthcare landscape Science 37 does this better than anyone else for a number of reasons: • Science 37 has done this longer than anyone else, having first pioneered decentralized clinical trials in 2014. • Science 37 has handled more decentralized clinical trials than anyone else (125 and counting, to be exact). • Science 37’s OS uses the industry’s first and only truly unified, end-to-end technology platform, that orchestrates workflow, generates evidence, and harmonizes data to the highest degree of accuracy, consistency, and reliability — eliminating the need to deploy multiple, disconnected solutions. • Science 37 has on its payroll many of the finest clinical experts in their respective fields, including Dr. Jonathan Cotlier (dermatology), Dr. Shaalan Beg (oncology), Dr. David Kudrow (migraine), and Dr. Chris Reist (depression). • Science 37 also employs its own mobile nurses, who are trained consistently and to a high degree. • Science 37 boasts extremely high patient satisfaction (NPS) scores and feedback.


The majority of our data comes from measuring the outcomes of real-life decentralized clinical trials that we have run (either wholly, or in part) and comparing these numbers with traditional, site-based clinical research. To date, our decentralized clinical trials have yielded up to 21x faster patient enrollment, 28x greater patient retention, and 3x more diverse patient representation, when compared to traditional clinical trials. We also conduct a number of surveys of clinical execs in the biopharma and CRO spaces, who have consistently perceived the greatest benefits of decentralized clinical trials to be faster enrollment, reduced patient burden, greater retention, and better participant (and provider) diversity. And, because every clinical trial is different, we have developed an ROI Calculator that computes the cost and returns of choosing a decentralized trial vs. a traditional study, taking into account such variables as indication, patient cohort, region, number of sites, duration, phase, etc.

Why Us