Phenomix and the Mayo Clinic partnered to test the effectiveness of the MyPhenome test.
While GLP-1s have shown themselves to be effective as weight loss medications, they are obviously not going to work for everyone. Since these are powerful medications that can cause significant side effects, it’s important that these drugs only by people who will benefit from them.
Weight loss medications aren't effective for everyone, and can come with serious side effects.
Phenomix Sciences and the Mayo Clinic published the results of tests to determine the effectiveness of a genetic obesity test.
The test can determine which medications are most likely to work based upon an individual's phenotype.
Phenomix Sciences published the results of a study conducted in partnership with the Mayo Clinic that tested the effectiveness of a genetic obesity test.1 MyPhenome is designed to predict the potential weight loss response a patient will have when taking commonly prescribed anti-obesity medications.
Dr. Andres Acosta, MD, PhD, led the research team at Mayo Clinic. In a press release, he said, “We now have published evidence that a genetic test can help guide obesity medication selection based on individual biology, not just weight or BMI, supporting a more targeted approach to obesity treatment. This is a meaningful step forward in moving obesity care from trial-and-error to precision medicine."
Phenomix Sciences CEO Mark Bagnall added, “Publication of our test results in such a high-profile journal reinforces our commitment to patients and physicians that our products will be based on top quality science and leading-edge technology. It also validates our core belief that obesity should be treated based on every individual's biology. MyPhenome can help identify who is most likely to benefit from different medications, potentially reducing side effects and improving adherence, while helping payers and providers avoid costly delays. The implications extend beyond clinical practice into how we design and conduct clinical trials for faster and more effective drug development. We're proud to be working alongside Mayo Clinic to validate and scale this personalized approach."
The study is published in Cell Metabolism and differentiated subjects into different groups: hungry brain phenotype and hungry gut phenotype. Subjects in the hungry brain phenotype responded better to phentermine/topiramate, while hungry gut phenotype subjects responded better to GLP-1s.
"Precision medicine has transformed fields like oncology, and this research is a powerful example of how obesity treatment is now following suit," said James Madara, CEO of the American Medical Association and chairman of Health2047 in the same press release. "Health2047 is proud to have supported Phenomix Sciences as they pioneered this shift with tools like MyPhenome."
In May of this year, Phenommix Sciences also revealed findings that show that its algorithms can be used to predict side effects when using these medications.2
In a press release issued at the time, Dr. Acosta said, “These findings represent a meaningful advancement in how we approach obesity treatment at an individual level. By identifying which patients are more likely to experience side effects before starting therapy, we can improve tolerability, support long-term adherence, and better match the right treatment to the right patient. This is a critical step toward delivering on the promise of truly personalized obesity care."
In the same press release, Bagnall also said, “This study underscores the power of predictive tools like MyPhenome to transform how we approach obesity treatment––not just in the clinic, but in the drug development pipeline. By identifying patients at risk for side effects before treatment begins, we can match the right patient to the right therapy, increase real-world adherence, and dramatically improve clinical trial efficiency through smarter patient selection. Our strategic partnership with Mayo Clinic, and its dedicated research team including Drs. Acosta and Frederick, have been critical in validating this precision medicine approach."
