Tufts links decentralized clinical trials to shorter cycle times, cost savings

By Nick Taylor

- Last updated on GMT

(ma_rish/iStock via Getty Images Plus)
(ma_rish/iStock via Getty Images Plus)

Related tags Tufts Medable Decentralized trials Virtual clinical trials Clinical trials software

In a partnership with Medable, a center at the university discovered costs linked to investing in decentralized studies far outweigh the eventual benefits.

The upfront investment needed to switch to decentralized clinical trials (DCTs) is dwarfed by savings tied to benefits of the model such as shorter cycle times, according to the Tufts Center for the Study of Drug Development (CSDD).

To run DCTs, sponsors must invest in technologies and processes that allow the replacement of in-person meetings with remote interactions. Advocates of the approach have long argued the upfront costs will be offset by efficiencies gained by reducing the need for face-to-face interactions with patients, but there is a need for data to quantify the payoff.

Tufts CSDD worked with software provider Medable to generate the data. The researchers looked at data on more than 150 clinical trials enabled by Medable software to assess the expected net present value (eNPV) benefits of DCTs.

Deploying a DCT strategy for a drug development program has been shown to create substantial eNPV benefits for the investment​,” said Pamela Tenaerts, chief scientific officer at Medable. “These are based on assumptions of a modest one-to-three months reduction in cycle times, as well as reduction in screen failures rates and amendments​.”

According to the study, a typical Phase II DCT deployment that cuts the clinical trial timeline by between one and three months yields a net benefit that is up to five times greater than the upfront investment required. In Phase III, the net benefit balloons to up to 14 times the upfront investment.

The savings are driven by shorter cycle times. With most clinical trials experiencing delays, and every day costing more than $1m USD in some trials once the full financial impact is calculated, there is a strong case for any investment that shortens cycle times.

A decentralized approach creates the potential for faster recruitment because studies can cast a wider geographic net as the well-known travel barrier in which most patients live more than 2.5 hours from a site is removed. We anticipate that, ultimately, this will lead to faster times to database lock and we are collecting data to evaluate this​,” said Tenaerts.

Loosening the link between geography and participation in clinical trials may also help to reduce the rate of screening failures. Medable has partnered with a global site network solely on screening support, said Tenaerts, and that “has resulted in screening time improvement​.”

Reductions in protocol amendments are another potential benefit of DCTs. With fewer research sites, DCTs have fewer institutional review boards, potentially leading to lower regulatory costs and increased flexibility around protocol changes. A clearer picture of the impact of DCTs on amendments may appear as the data improves.

Medable is working with customers to track various metrics related to DCTs, the number of amendments is one of them.  We encourage other organizations to also track the assumptions that were part of the analysis - cycle times, screen failures, rates, and amendments - so that the model can be updated into the future​,” said Tenaerts.

Related news

Show more

Related products

show more

Saama accelerates data review processes

Saama accelerates data review processes

Content provided by Saama | 25-Mar-2024 | Infographic

In this new infographic, learn how Saama accelerates data review processes. Only Saama has AI/ML models trained for life sciences on over 300 million data...

More Data, More Insights, More Progress

More Data, More Insights, More Progress

Content provided by Saama | 04-Mar-2024 | Case Study

The sponsor’s clinical development team needed a flexible solution to quickly visualize patient and site data in a single location

Using Define-XML to build more efficient studies

Using Define-XML to build more efficient studies

Content provided by Formedix | 14-Nov-2023 | White Paper

It is commonly thought that Define-XML is simply a dataset descriptor: a way to document what datasets look like, including the names and labels of datasets...

Related suppliers

Follow us


View more