CRO

Medidata goes all in on decentralized, virtual capabilities for clinical trials with end-to-end platform

Dassault Systemes’ Medidata is betting big on the virtualization of clinical trials as it rolled out a decentralized technology platform Tuesday.

Medidata, whose cloud platform was used to support the clinical trial life cycle of Moderna’s COVID-19 vaccine, is billing its platform as the most comprehensive suite of unified tools for full decentralization throughout the clinical trial process. That’s Medidata’s way of saying the company believes it has more heft than a field of newly formed startups in the siteless trials space.

The platform combines tech and workflows that allow for remote patient participation and sponsor oversight of patient safety and data quality as well as direct-to-patient services such as coordinating study drug delivery to patients’ homes. Medidata is marketing the product toward drug, vaccine and medical device developers as well as contract research organizations.

“The life science industry has seen accelerating interest and adoption of decentralized trial technology in the wake of the COVID-19 pandemic. Sponsors and CROs are increasingly turning to decentralized trial models in an effort to bring increased efficiency, security, and accessibility to the clinical research process,” said Anthony Costello, president of patient cloud at Medidata, in a statement.

The platform is meant to be used across the spectrum of clinical trials, whether traditional on-site, fully decentralized or a combination hybrid model. As a single platform, Medidata says the product reduces the chances for data discrepancies and transfer lags, which sometimes raise security concerns and increase the possibilities of trial disruption.

Last week, Medidata also unveiled a new technology to engage patients pre- and post-trial for more active participation.

RELATED: Newly minted Medable teams up with CRO Syneos Health for siteless trials push

Medidata’s program comes amid a reimagining of the clinical trial process with a crop of virtual, or siteless trial, startups popping onto the scene throughout the COVID-19 pandemic. Science 37 is one such company to have a breakout year in 2020, and it hopes to capitalize on the surge in decentralized trials by merging with special purpose acquisition company LifeSci Acquisition II. The deal, disclosed last month, is valued just north of $1 billion.

RELATED: Science 37 taps a SPAC to go public, with siteless trial specialist valued at a cool $1B

Another company, Medable, raised $78 million in April and a day later said it penned a pact with CRO Syneos Health for its decentralized capabilities. Further yet, Curebase is the latest newcomer with a $15 million series A last month.

Medidata’s software has been a lifeline to Dassault Systems since being bought at an enterprise value of $5.8 billion in October 2019.

“The mission-critical nature of our platform has been most visible in Life Sciences, where a majority of the COVID-19 clinical trials were conducted with our MEDIDATA software solutions during 2020. The health crisis has very clearly revealed the game-changing nature of our virtual twin experience, from research to patient care,” said Bernard Charles, Dassault CEO and vice chairman, in the company’s fourth-quarter 2020 results. Medidata expanded its customer base 16% in 2020.

Medidata also thinks it can seize on regulatory agencies’ evolving adoption of remote technology as the FDA is expected to release draft guidance on decentralized clinical trials later this year. In March 2019, the agency said it was working with the Clinical Trial Transformation Initiative (CTTI) and other stakeholders to evaluate decentralized clinical trials.

CTTI published its final recommendations (PDF) on conducting decentralized trials in September 2018, concluding that this rethinking of the traditional centralized method could lead to faster participant recruitment, increased diversity in enrolled patients, better retention and higher levels of comfort for participants, among other findings.