Mayo Licenses Algorithm for Detecting Genetic Cardiovascular Risk to Medtech Startup
The Mayo Clinic’s expertise in identifying genetic health risks through analyzing medical record data has led it into a collaboration with a Pittsburgh startup seeking to fight an inherited disorder associated with aggressive cardiovascular disease.
2bPrecise LLC announced this month it has licensed a Mayo-developed algorithm capable of quickly identifying genetic risk for a condition called familial hypercholesterolemia (FH) by taking data routinely collected from patients and comparing it to the clinic’s vast database of similar information.
The young company is incorporating the proprietary Mayo algorithm into its cloud-based electronic health records platform with the goal of bringing actionable genomics-based protocols based on patients’ FH status directly to the point of care.
The two parties said they will also be working together on further research to develop genomics protocols for other conditions, in which Mayo would have an unspecified financial interest.
Interpreting complex genomics data into a health record that can be useful for busy physicians making decisions on the go has been something of a Holy Grail for the medical technology community. It is viewed as a key to translating advances in genomics into real-world patient outcomes.
2bPrecise says that’s exactly what its platform can do. The company claims it “harmonizes clinical and genomic information to extract patient-specific insights and present them in an actionable way to the clinician, within their current (electronic health records) workflow.”
The licensed technology is Mayo’s newly-developed algorithm to detect FH, a condition in which inherited genetic mutations cause sufferers to have high levels of LDL (or “bad’) cholesterol in their bloodstreams. The mutations make the liver incapable of removing excess LDL, and the result can lead to premature cardiovascular disease such as heart attacks, strokes and even narrowing of the heart valves.
The algorithm was developed by Mayo cardiologist Dr. Iftikhar Kullo and a pair of colleagues. Their goal was to address significant knowledge gaps about FH—little is actually known about its prevalence and control in the United States. They developed an “ePhenotyping” algorithm for rapid identification of FH in electronic health records. It looks for FH criteria by using clinical data sets, descriptions of family history and presence of indicators observed during physical examinations.
In a study released last year, Kullo found that when he applied the algorithm to a records database of 131,000 individuals seen in primary care between 1993 and 2014, it yielded positive and negative predictive values for FH at 94 percent and 97 percent, respectively.
The study also found that FH’s prevalence in primary care to be one-in-310. Awareness and control of the condition was characterized as “low.”
“Mayo Clinic has a very robust genomics research discipline,” 2bPrecise CEO Assaf Halevy said in an issued release. “The wealth of both genetic research and clinical data within the clinic is staggering. This is why we are so excited to collaborate with premier organizations like Mayo Clinic to advance genomic science and help make it clinically actionable.”