Digital binary code concept.
Credit: metamorworks/Getty Images

Oncology-focused real-world evidence (RWE) company ConcertAI and molecular science and technology company Caris Life Sciences announced they will develop a clinico-genomic data platform that combines comprehensive molecular profiling data with reference-standard clinical data to enable precision oncology research. The partnership expands on an agreement reached by the companies in January this year to create a broad drug development platform.

In the coming months the two companies plan to create a prospectively generated, EHR-enabled database of molecular, clinical, and multi-modal data with the goal of enabling novel insights for the development of precision medicine therapeutics and clinical trials management targeting pharma and academic centers alike. The companies envision the scale of data in the platform to be the largest focused on oncology research. It will enable multi-year oncology research programs focused on specific cancers, translational research of molecular targets, clinical development and post-approval evidence gathering and the increased use of RWE in the support of clinical trials.

“The future of cancer care will be driven by massive amounts of comprehensive biological and clinical data,” said David Spetzler, president of Caris. “Combining the deep clinical data at ConcertAI with the whole exome and whole transcriptome sequencing and other data at Caris enables researchers to discover new associations and information to improve patient care, versus datasets with smaller panels that inherently cover only what is known.”

The partnership will build upon Caris’ leading position in molecular profiling and will leverage its real-world database of hundreds of thousands of cases that include genomic, transcriptomic, and proteomic data. It also has significant whole-slide imaging data that includes both H&E and IHC slides. ConcertAI, meanwhile, brings its collection of research-grade clinical data encompassing oncology, hematology, and urological cancer—a database that spans the outcomes of nearly seven million patients.

“By building novel research assets at population scale, integrated with leading technologies and talent, we can partner with both academic researchers and biopharma innovators to accelerate new insights into the underpinnings of cancer biology, rapidly translate these insights to the clinic, and enable novel clinical development approaches,” said Jeff Elton, CEO of ConcertAI. “Ultimately, the facilitation of broad-based access to data of this depth and scale, beyond most public or private initiatives, will aid all cancer patients, especially those underserved with few current therapeutic options available to them.”

Caris has continued to strengthen its oncology testing and research capabilities over the past few years via its Precision Oncology Alliance, a network of cancer centers across the U.S. that are actively taking a precision approach to oncology care. Alliance members are provided with a range of support services from Caris which includes access to Caris CODEai, the company’s clinical outcomes and molecular database, its molecular profiling services, clinical trials management and the Caris Molecular Tumor Board which provides alliance members with expert guidance for specific patient cases. To date, the company has profiled more than 490,000 patients.

“The Caris Precision Oncology Alliance leverages the opportunities of big data, artificial intelligence and the collaborative research initiatives of our members to identify predictive and prognostic markers to further advance the integration of molecular profiling into all aspects of cancer care,” noted Chadi Nabhan, chairman of the Precision Oncology Alliance on the company’s website.

ConcertAI, founded in 2018, has been carving its niche in the industry by leveraging real-world data and artificial intelligence to enable clinical development and clinical trials, while also providing post-approval services that include comparative effectiveness data to monitor drugs in real-world populations, adverse event detection and evaluation, and treatment pattern analysis, among others.

Also of Interest