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Gaining ground with genomics
SANTA CLARA, Calif.—NextBio and Genophen, a Stanford University spinout company, have announced the formation of a partnership that aims to advance the adoption of genomics for disease prevention and wellness. Both companies bring with them informatics platforms designed to handle and interpret the reams of data that come with combining genomic and medical data into more accurate, personalized treatment plans.
Under this partnership, Genophen will have access to the NextBio Clinical platform for use in interpreting full-genome sequencing data, and will be able to combine that data with information on a person's environmental, behavioral and clinical factors to produce more tailored disease prevention and wellness plans for its members. No financial details were disclosed.
"Genophen 's aim is to make the dream of personalized medicine a tangible reality," Saeid Akhtari, president and CEO of NextBio, said in a press release. "Our partnership allows NextBio to take a first step towards the use of genomics for wellness and disease prevention, one of the ultimate goals of modern medicine."
Akhtari says the two companies were in discussions for several months prior to the announcement of the partnership, and conducted a pilot project before making the agreement final. He adds that NextBio is "very impressed with Genophen's team, technology and their vision for personalized preventive medicine."
"Genophen is the first company to take lifestyle factors in synergy with genetic information derived from full-genome sequencing to create a personalized health risk assessment and a set of recommendations for each individual," Dr. Hossein Fakhrai-Rad, co-founder, CEO and president of Genophen, commented in a statement. "NextBio's vast and comprehensive repository of curated genomic and clinical data from the public domain adds depth to our analysis. This partnership with NextBio Clinical enables us to efficiently analyze and interpret whole-genome data."
The partnership, Akhtari points out, provides Genophen with "a comprehensive platform for interpreting their clients' full-genome sequence and providing clinically relevant variants."
"Genophen integrates the genomics data provided by NextBio with medical, behavioral and environmental data to assess an individual's risk for multifactorial chronic diseases such as diabetes, heart disease and cancer, among others," he explains. "They have a network of trained physicians who will review the personalized health assessment data with the patients to help them understand their health risks, the impact of genomics on their health and proper action they can take to reduce their risks of developing multifactorial chronic diseases."
Akhtari says that NextBio introduced its NextBio Clinical platform in 2012, with the goal of "providing a comprehensive solution for rapidly expanding clinical application of genomics." NextBio's platform enables data aggregation and interpretation on a large scale for both research and clinical applications, offering a new solution for the massive amount of data generated by genomic sequencing. The platform, which recently passed an independent HIPAA audit, is capable of analyzing petabytes of data, and is delivered as a software-as-a-service solution. NextBio's platform can integrate data from a variety of sources, including public data as well as a patient's own clinical and molecular data. Akhtari says that he expects "the fastest growing applications of clinical genomics to be in cancer care, diagnostics, preventive medicine and wellness."
Genophen notes on its website that its platform begins with data modeling, combining a patient's information, including pharmacogenomics, with "published and curated genetic data, published scientific data and health databases to create our fact tables and conduct meta-data analysis and build our algorithms." A patient's risk for chronic diseases such as diabetes, heart disease, stroke and cancer is determined through "genetic analysis, statistical modeling, mathematical risk modeling and prediction analysis," and then a treatment recommendation is generated based on multidimensional data modeling that "considers many factors and sub-factors to capture complex relationships between diseases and risk factors."