TriNetX teams up with Sanofi, Cornell for better clinical trial design

Global data network. Image: Pixabay
TriNetX's platform uses EHR data to help drug developers with clinical trial protocol design and study site and participant identification. (Pixabay)

Clinical research network company TriNetX recently announced that Sanofi is using its technology to help streamline clinical trial design and accelerate drug development cycle times, and that Cornell University’s Weill Cornell Medicine has joined its healthcare organization network.

The company’s platform includes de-identified patient data from their electronic health records contributed by healthcare facilities within TriNetX’s network. Drug developers and CROs can query against that data to improve clinical trial protocol design, as well as for study site and participant identification.

It’s no secret in the drug development world that amendments to protocol design and lack of patient enrollment can significantly slow down the process. CEO Gadi Lachman explained to FierceCRO how gaining access to patient data through TriNetX’s platform can help with clinical trial protocol design.

“All too often, inclusion/exclusion criteria are chosen without verifying the impact on the availability of a cohort, and as a result creates future avoidable amendments,” said Lachman. Using TriNetX’s platform, biopharma or CRO users can build models of clinical trial protocols based on aggregate information from real patients. And researchers can quickly predict how their protocols might work (or not) in real-world settings and make changes accordingly.

RELATED: Celgene teams up with TriNetX for ‘next-gen’ drug trial design

“TriNetX was the first electronic health record system that we fully implemented here at Sanofi. What attracted us to the system was the ability to do real-time querying in support of our protocol simplification optimization goals,” said Victoria DiBiaso, Sanofi’s global head of clinical operations strategy and collaboration, in a recent videoed interview with TriNetX. Lachman said Sanofi actually started using TriNetX in 2016 for protocol design, feasibility, and site selection. 

What’s more, patient data can be traced to healthcare organizations, and their identity could be declassified for potential recruitment into a clinical trial. For healthcare facilities like Cornell, joining the network gets them hardware and software that are incorporated with their existing IT infrastructure, and what’s more important, it could potentially bring new clinical research opportunities for the patients.

TriNetX’s network now includes 68 healthcare organizations, representing several hundred facilities treating nearly 100 million patients globally, and 22 of the largest biopharma companies and CROs are currently using its platform, said Lachman. All told, the platform has been used to analyze nearly 6,000 protocols, and 1,312 trials have thus far been offered to healthcare organizations.

In addition to the structured data already available in its platform, TriNetX recently made its natural language processing (NLP) service, based on technology from German text-mining and machine-learning company Averbis, fully available to its customers.

NLP is a field within computer science in which software reads free text to mine interesting data and transform it into discrete data points. In TriNetX’s case, the technique is used to extract information like diagnoses, medications and lab results from physicians’ notes and clinical reports, said Lachman.

“NLP is valuable in this case because it helps enrich the data about a patient,” explained Lachman. “NLP is important for protocol design because a significant number of criteria that are used as inclusion and exclusion criteria are terms that are not available as discrete fields from an EHR, but may be captured in free text notes.”

Headquartered in Cambridge, Massachusetts, TriNetX now has regional offices in London, Sydney and Sao Paulo, and Lachman said it is also working closely with Sanofi on its international expansion efforts.