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As the industry began to lean into decentralized clinical trials during the pandemic, it discovered the model’s valuable potential.

Proof Positive: Decentralized Trials Drive Value

Driving down costs and clarifying the value of trial components is imperative to get drugs to market

Ingrid Oakley-Girvan, PhD, MPH

As a scientist, researcher, and educator for more than 25 years, Ingrid Oakley-Girvan, PhD, MPH, has developed a holistic perspective—ensuring a patient-driven focus is combined with data-driven science. As senior vice-president of research and strategy for Medable, she draws on her strong technical, analytic, and genetics background to improve the clinical trial experience for patients. She has a keen focus on modernizing clinical trials, the digital virtual health care space, and creating technology and tools to collect precision data.

The cost of drug development is high and increasing—Tufts Center for the Study of Drug Development (CSDD) estimates the total capitalized cost for an approved new compound at $2.6 billion USD1—and the process is lengthy. These factors prolong and limit access to new therapeutics to treat patients. One study found that for every $1 billion USD spent on research and development, the number of new drugs approved has decreased by 50 percent every nine years since 1950.2

Driving down costs, plus greater clarity around the value of certain clinical trial components, is imperative to get drugs to market and address the needs of diverse patients. 

As the industry began to lean into decentralized clinical trials (DCTs) during the coronavirus pandemic to ensure trials could continue remotely, it discovered the model’s valuable potential. New research from Tufts CSDD now highlights substantial net benefits for the use of DCTs in drug development.

An evaluation of prior industry data combined with selected data from the portfolio of DCT studies on the Medable DCT platform demonstrated that in Phase 2 studies, the typical DCT deployment for a clinical trial resulting in a one-to-three-month time savings yields a net benefit that is up to five times greater than the required upfront investment. In Phase 3 studies, a similar time savings yields a net benefit that is up to 14 times greater than the required upfront investment.

These conclusions started with a data-driven analysis of the value proposition and return on investment for DCTs using an expected net present value (eNPV) model.* The benefits from DCT deployment that were measured and applied to the financial modeling were derived from published benchmarks on clinical trial cycle time, cost, and performance, as well as conservative assumptions about the impact of, and the investment required to deploy, a DCT.

Key findings include:

1. DCTs reduce development cycle times

In this analysis, cycle time reductions associated with DCT deployments had a substantially greater impact on net financial benefits than any other factor. The need to improve cycle time is great as 85 percent of all clinical trials will experience some sort of delay, with the financial impact of delays costing between $600,000–$8 million dollars a day.3 A benefit of DCTs may include more rapid trial completion.

2. DCTs lower clinical trial screen failure rates

Although 85 percent of people say they wish to participate in research, more than 70 percent live more than two hours away from their study site.4 Other figures are even more sobering: less than 5 percent of the US population participates in clinical research,5 up to 50 percent of trials are not completed because of insufficient enrollment,and 30 percent of participants drop out of studies.7 

Perceived participant burden is associated with screen failures and retention rates, and it increases clinical trial timelines. DCTs have the potential to reduce this burden and thereby reduce screen failure incidence and increase retention rates.

DCTs shift the paradigm to allow people to participate in clinical trials outside of the typical clinical site, enabling faster screening, more convenient consent and enrollment, and in some cases, the remote delivery of an intervention and the measurement of outcomes. These same factors also reduce burdens on participants by reducing time and travel costs, which can be especially important for patients who are seriously ill.

3. DCTs have fewer protocol amendments

Protocol amendments often cause delays and dramatically increase the costs of developing new therapies. Previous work by Tufts CSDD found that 57 percent of protocols had at least one substantial amendment, with a mean number of 2.2 amendments for Phase 2 trials and 2.3 for Phase 3 trials with commensurate costs of $141,000 and $535,000 USD, respectively, for each substantial amendment.8 Protocol amendments take time and incur direct costs, such as increased investigative site time and fees and contract change orders.

The historic Tufts analysis offers new hope for a better model of conducting clinical research. Ultimately, these findings and future research will help promote more innovation and increase the pace of drug discovery.

*NOTE: Because many Phase 2 and 3 clinical trials do not result in regulatory approval of an investigational medical product or drug, calculating the eNPV is a dependable way to estimate potential return on investment, as the eNPV analysis combines risks of failure with actual costs and other drivers of value.


  1. DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: New estimates of R&D costs. Journal of Health Economics. 2016;47:20-33. doi:10.1016/j.jhealeco.2016.01.012
  2. Scannell JW, Blanckley A, Boldon H, Warrington B. Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov. 2012;11(3):191-200. doi:10.1038/nrd3681
  3. How to avoid costly Clinical Research delays | Blog. MESM. Accessed December 1, 2021.
  4. Sanofi launches new virtual trials offering with Science 37. FierceBiotech. Accessed December 23, 2021.
  5. Coravos A. Decentralized clinical trials. Medium. Published October 19, 2018. Accessed December 23, 2021.
  6. Topaloglu U, Palchuk MB. Using a Federated Network of Real-World Data to Optimize Clinical Trials Operations. JCO Clinical Cancer Informatics. 2018;(2):1- 10. doi:10.1200/CCI.17.00067\
  7. Retention in Clinical Trials: Keeping Patients on Protocols. Advarra. Accessed December 23, 2021.
  8. Getz KA, Stergiopoulos S, Short M, et al. The Impact of Protocol Amendments on Clinical Trial Performance and Cost. Ther Innov Regul Sci. 2016;50(4):436-441. doi:10.1177/2168479016632271