By Allison Proffitt

November 18, 2020 | Medidata, TriNetX, and Datavant announced a partnership last month that the companies hope will accelerate the use of real-world data (RWD) to power clinical research. The partnership will enable users of Medidata’s end-to-end clinical research platform to securely link their clinical data with patient consent to de-identified patient data without unblinding the study. The solution leverages Datavant’s Patient Key technology and data ecosystem, as well as RWD from TriNetX’s global network of healthcare organizations who participate in this program.

“The partnership is really about incorporating all kinds of data,” Maulik Mehta, Chief Business Officer at TriNetX, told Clinical Research News. Everything from clinical trial data, health records data, claims data, patient-reported data, and sensor and wearable data can be valuable. “We really want to incorporate all kinds of data to get the full aspect of what the patient is experiencing,” he said, “both within a trial, when a trial is finished, and when the drug is actually approved.” 

Pooling and integrating all of those datasets offers a more complete picture of the patient experience, the companies believe—and they aren’t alone. “There’s a big push to leverage real world evidence in the marketplace,” Mehta observed. “The FDA continues to push this as well. It allows organizations to scientifically better assess how successful their drug is compared to if there’s no therapy out there, or compared to other therapies out there.”

Real World Data For A Real Time Pandemic

TriNetX has been gathering and organizing real world data since its founding in 2013. The company has partnerships in more than 30 countries with more than 170 healthcare organizations representing more than 400 million patients globally, Mehta said. The platform houses anonymized data that pharmaceutical companies can mine looking for the right partners for trials. If they find a fit, they can reach out to sites who then have access to the re-identified patient lists of interest. 

Case in point: last week the University of Oxford used the TriNetX Network to look at the impact of COVID-19 on mental health. The team accessed de-identified electronic medical records (EMR) data of 69 million individuals, 62,354 of whom had been diagnosed with COVID-19 between Jan. 20, 2020 and Aug. 1, 2020. “By use of the TriNetX user interface, cohorts can be created based on specified inclusion and exclusion criteria and matched for confounding variables using the built-in propensity score matching capability,” the authors wrote in their November 9 Lancet Psychiatry paper (DOI: 10.1016/S2215-0366(20)30462-4). “Outcomes of interest are then compared between cohorts over defined time periods.”

The research team found that a diagnosis of COVID-19 was associated with increased incidence of a first diagnosis of anxiety, depression, or insomnia in the following 14 to 90 days compared to any other group of patients. The study also revealed an increase of the rate of dementia and more relapses in people with a history of psychiatric problems in COVID-19 patients. Overall, almost one in five patients received a psychiatric diagnosis within 90 days of contracting COVID-19. 

These kinds of studies—especially longitudinal ones—will be increasingly important, Mehta said. “Life science companies are always exploring different ways to reduce cost of clinical care and drug development costs holistically,” he said. “They can use these types of data to potentially design hybrid trials,” with smaller study arms, using RWD to supply control data. Real world treatment patterns are also used to inform novel therapy development and adoption. It’s an approach that saves time and cost—less patients, less sites, less investigators—Mehta said.    

Finally, companies are also using the data to conduct long-term safety studies, he added, providing FDA with post-approval surveillance and monitoring data. “There’s lots of different use cases,” he said. “Ultimately it all helps reduce the cost of medicine and the overall cost of development.” 

TrialNetX’s partnership with Medidata and Datavant is meant to make all of this go more smoothly, “creating a unified data feedback loop between the clinical trial and the real world and expands the possibilities for analytics conducted during and after clinical trials while keeping the clinical study blinded,” said Arnaub Chatterjee, senior vice president of Product at Acorn AI by Medidata, in a statement announcing the news.

Patients enrolled in a clinical trial utilizing Medidata’s solutions will have the option to grant consent for their data to be linkable using Datavant’s de-identified Patient Keys to both TriNetX’s broad RWD assets and Datavant’s open data ecosystem. This enables sponsors to cost-effectively study the efficacy and safety of their therapies for many years after the completion of the trial with less risk of losing patients to follow-up. 

The three companies are pursuing an open, partnership-first approach, they said in a statement, looking forward to continued collaboration across the industry to modernize the clinical trial infrastructure for patient benefit.

Plus, Mehta points out, the partnership allows long-term learning without additional burden on the patient, scaling research in ways that haven’t been done before. “Now we have their de-identified information. This the part where Datavant can now—based on certain de-identifiers—bring in other kinds of data around the patient, but we don’t know who that patient is anymore.”