Under a collaboration announced today, San Diego-based Cypher Genomics said it would use its biomarker discovery service to help New Jersey’s Celgene (NASDAQ: CELG) identify key genetic variants among patients who respond well to specific drugs.
If successful, the use of Cypher’s proprietary technology to pinpoint such “functional variants” could enable a drug maker to meet its end-point goals in late-stage clinical trials with far fewer patients, Cypher COO Adam Simpson said yesterday. The potential savings could be huge.
Genetic variation accounts for widely varying response rates that patients show to prescription drugs. As a result, doctors often prescribe a variety of drugs through a trial and error process until they see the appropriate patient response.
Unfortunately, at least a third of the money spent on prescription drugs in the United States is wasted, according to a 2012 study co-authored by Eric Topol, a Cypher Genomics co-founder and a prominent scientific advocate for using a patient’s own genomic data to determine the optimal drug therapy. Topol, who is a San Diego cardiologist, genomic researcher, and director of the Scripps Translational Science Institute (among other things), contends that wasteful patient spending on prescribed drugs that are ineffective or even harmful amounts to more than $100 billion a year in the United States alone.
As co-author Andrew Harper and Topol wrote:
Perhaps the best example of both waste and missed opportunity can be found with the three top-grossing prescription drugs worldwide; TNF α-receptor inhibitors (etanercept (Enbrel), infliximab (Remicade) and adalimumab (Humira)), are used in the treatment of rheumatoid arthritis with aggregate sales of nearly $30 billion. However, these three specific biological agents cost more than $15,000 per patient annually and only 40 percent of individuals respond to treatment.
“What we’re trying to do at Cypher is enable that type of companion diagnostics,” Simpson said, referring to diagnostic tests, including genome sequencing, that identify biomarkers that can be used to determine which patients could be helped by a particular drug and which would not.
While Cypher has conducted genome analytics in previous pharmaceutical studies, Simpson said Cypher’s collaboration with Celgene would be its first official study done with a major pharma. So how much savings could a pharmaceutical realize by using Cypher’s analytics?
Simpson said a study that applied the potential benefits of Cypher’s technology to the actual late-stage trial done for the prostate drug finasteride suggests that Merck could have saved as much as $211 million. That’s because Cypher’s analytics would have reached valid findings with about 1,000 patients instead of the 8,000-plus patients that Merck actually enrolled. The same study said a late-stage trial for the diabetes drug metformin, conducted with about 3,000 patients, could have been done with less than 1,000 with Cypher’s technology—at an estimated savings of about $63 million.
Simpson declined to discuss the financial terms of Cypher’s partnership with Celgene, saying he would not comment on their relationship beyond the press release.
Cypher Genomics developed Coral, its proprietary, high-speed information technology to annotate and analyze the computerized data generated by so-called next-generation genome sequencing machines like Illumina’s HiSeq X Ten. The company also has developed Mantis, a software-as-a-service offering that uses its core genome interpretation technology to identify genetic variants among patients whose genomes have been sequenced.
According to Cypher, manual processes for interpreting genomic data are prohibitively slow and costly (estimated at about $15,000 per genome).
Cypher says its automated genome interpretation technology can quickly identify genetic markers and their contribution to therapeutic responses and disease management. In today’s statement, the company quotes Cypher CEO Ashley Van Zeeland as saying, “Cypher has shown through multiple validation studies that our Coral technology can find novel biomarker signatures in genomic data from small clinical studies.”