CHICAGO (GenomeWeb) – Over the summer, Mayo Clinic and Nference, a Cambridge, Massachusetts-based maker of artificial intelligence and deep-learning software, formed an interesting sort of joint venture.
The venture, called Qrativ, will synthesize and analyze genomic and clinical data from publicly available databases as well as from research generated at Mayo — but from no other research institutions — in hopes of informing drug discovery. Qrativ and its partners will focus their efforts on finding new treatments for rare diseases and other conditions perceived as underserved in the market.
These treatments could be new compounds or they could simply involve finding additional indications to tests with previously approved drugs, according to Qrativ officials from both Mayo and Nference. (Also involved in the venture are investors Matrix Capital Management and Matrix Partners, who, along with Mayo Clinic, contributed $8.3 million to a Series A financing round announced in July.)
"It is our belief that most disease states have genomic, proteomic, [or] metabolomic signatures that define populations," said Qrativ Cofounder and Chief Medical Officer Andrew Badley, who also directs Mayo Clinic's Office of Translation to Practice. "When faced with a drug with a known mechanism of action, it is our opinion that it's best to target the populations that have abnormalities in that pathway," explained Badley, an internist by training who focuses on infectious diseases.
"At a very broad level, we are using the informatics capabilities in all of these omics spaces to identify key populations that might benefit from new therapies," Badley said.
Qrativ represents an advance from a few years ago because it considers specific clinical information in addition to publicly available gene expression and drug databases in suggesting new indications for existing medications.
"The plan for Qrativ is to leverage both the public data sets and to the proprietary data sets that come out of the labs of many investigators," said Murali Aravamudan, cofounder and CEO of Qrativ as well as CEO of Nference. "One of the interesting aspects of this collaboration is that we work with individual Mayo investigators who have collected various kinds of data," including genetic information.
Public data sets might include the Cancer Genome Atlas and information on specific cell lines, Aravamudan noted.
"When you have a range of these genomic data sets, you can ask: "How can you triangulate insights coming from each of these different individual assets, but still make a holistically derived decision about a certain drug being effective in a certain patient cohort?" Aravamudan said.
Qrativ is calling its platform Darwin.ai, representing a pairing of existing Nference knowledge-synthesis technology and the Mayo and public datasets. It will not be hawking technology or tech services, but rather knowledge gleaned from its analysis.
"At the end of the day, we are about selling an asset, not about selling a platform to other pharma companies. They are making use of the Darwin.ai platform to come to robust conclusions on why we should advance a certain drug or a certain indication for a certain genomic cohort," Aravamudan said.
"The objective of this company is to advance drug assets into human clinical trials," he continued. "The idea is to develop the assets to a reasonable stage — Phase 1 and 2 — and try and sell those assets to pharma companies for further development," preferably at Mayo Clinic.
For now, when it comes to proprietary data, Qrativ will only be working with information generated by Mayo researchers.
"We will use Mayo knowledge, coupled with the knowledge that is generated by Nference, to work on assets that we identify that can come from virtually any space to optimally advance those assets," Badley said.
"Mayo will contribute the expert knowledge of our clinicians and our researchers toward advancing the product. When it comes to performing the clinical trials, if we get to that stage, the goal is for most if not all of those clinical trials to be performed in house at Mayo."
So why did Mayo decide it needed to form a separate company for this purpose? "Because we're not just a clinical trials organization," Badley explained. "We couple the artificial intelligence knowledge generated with state-of-the-art medical knowledge from clinicians who are seeing patients all day, every day to create the optimum path to the clinic."