What You Should Know:
– Biotech company Phenomix Sciences launches its biobanking registry, marking the first obesity registry to study the impact of personalized treatment based on phenotyping. The impact of this biobanking registry and the data it will yield has the potential to change the entire system’s approach to obesity, from a treatment recommendation to the way payers determine coverage and how the industry combines diagnostics testing with drug therapy.
– The data collected will supplement the 20 billion unique data points that make up the Phenomix Sciences Obesity Platform. Mayo Clinic is the first to enroll in the registry with its Rochester site set to contribute patient outcomes from 2,000 patients undergoing treatment for obesity to its biobank.
Understanding Phenotyping
Phenotyping is a new method for treating obesity and Phenomix, a biotech company, is the first to bring this technology to market with proven results. The announcement of the company’s biobank is the next step to gathering real patient data to better understand phenotypes by looking at patients’ DNA, metabolomics, hormones, patient behavior, assessments, and treatment outcomes. A growing body of evidence indicates that obesity is not a single disease with a single treatment type, but a constellation of diseases.
Obesity’s roots lie in individual DNA; however, evidence suggests there is a complicated web connecting obesity to age, race, and gender, education, and socioeconomic status. Understanding a person’s obesity phenotype — the combination of genes with environmental and behavioral factors — can help pinpoint the cause of weight gain. Phenomix’s phenotypes are based on research from its physician founders, Andres Acosta, MD, Ph.D. and Michael Camilleri, MD of Mayo Clinic, that has demonstrated when patients have been phenotyped and prescribed the right medications, they can achieve up to 16 percent total body weight loss (TBWL).
How The Obesity Biobanking Registry Works
Outcomes data generated from the biobanks across the registry will supplement Phenomix’s database of biological and clinical data matched to the four obesity phenotypes. Insights generated from the database are being used to develop more predictive tests to identify the right intervention for each patient with obesity. This will allow for a better understanding of variability in patient outcomes when undergoing obesity treatments. Despite the justifiable excitement about new weight management products such as semaglutide and tirzepatide, several clinical studies from Phenomix’s founders indicate that patient response varies with underlying phenotype. Thus, for many patients, it will open the door to the most effective and appropriate intervention for their unique phenotype.
The registry will supplement the 20 billion unique data points that already make up the Phenomix Sciences Obesity Platform, and Mayo Clinic’s Rochester site is the first center of excellence to enroll in the registry, with plans to contribute to patient outcomes from 2,000 patients undergoing treatment for obesity to its biobank.
This registry and the data it will yield have the potential to vastly alter treatment approaches to obesity, including the way payers determine coverage and how the industry combines diagnostics testing with drug therapy.
“This unique biobanking registry will provide critical and contemporary data on obesity outcomes, impacting every stakeholder in the episode of care,” said Mark Bagnall, CEO of Phenomix Sciences. “This registry is an important opportunity to make vast strides in how we understand the complexities of obesity treatment. All obesity programs should be seeking the opportunity to participate and contribute to this registry. The more data we have on the variables that contribute to an individual’s obesity diagnosis, the more lives we can save by putting the best treatment plan forward. We believe the investment in the biobanking registry will better support obesity centers by providing concrete evidence and insight into how DNA and other factors need to be considered in treatment. Patients can benefit greatly from achieving the desired outcome the first time around, and payers avoid paying for trial-and-error approaches and can reduce overall co-morbid conditions for members.”
