Mayo Clinic and Phenomix Collaboration Enhances Personalized Obesity Treatment Using AI

Transforming Obesity Treatment with AI



In a groundbreaking development for the field of obesity medicine, Phenomix Sciences has partnered with the Mayo Clinic to introduce an innovative AI algorithm capable of predicting side effects associated with GLP-1 therapies. This collaboration, highlighted during the Digestive Disease Week (DDW) 2025, signifies a notable advancement in personalized healthcare, with the potential to refine treatment approaches and enhance patient adherence.

Understanding the Study



The research, led by renowned obesity specialist Dr. Andres Acosta, utilized machine learning to analyze genetic risk scores (GRS) from 110 participants in a post-hoc analysis of a randomized controlled trial focused on liraglutide, a GLP-1 medication. The findings revealed a startling correlation: patients identified with a high-risk genetic profile were over twice as likely to experience nausea as a side effect when compared to those with a low-risk score. Specifically, the rate of nausea in high-risk patients soared to 68%, while only 30% of those with a lower risk reported similar effects.

Nausea is often the most prevalent side effect reported by patients undergoing GLP-1 therapy, with estimates suggesting that up to 40% may experience it, resulting in a significant number discontinuing treatment. This study underlines the crucial need for predictive analytics in order to enhance the patient experience and maintain treatment adherence.

The Impact of Predictive Insights



The implications of this research extend far beyond individual patient outcomes. By employing predictive modeling, healthcare providers can better match patients with the most suitable medications from the outset, minimizing the likelihood of treatment discontinuation due to adverse side effects. This not only streamlines patient management but also reduces unnecessary emergency room visits triggered by intolerable symptoms.

The study’s principal author, Dr. Thomas Fredrick, emphasized that this predictive capability allows for more balanced treatment strategies tailored to individual patient profiles. By considering potential side effects during the treatment planning process, healthcare providers can significantly enhance the quality of care.

Previous Research Foundations



This study is part of an ongoing body of research in precision medicine. Last year, Phenomix introduced its pioneering MyPhenome test, designed to identify patients likely to respond positively to semaglutide, another GLP-1 medication. The MyPhenome test offers a straightforward saliva swab that assesses biological variables contributing to obesity, thereby assisting doctors in crafting personalized treatment plans.

The latest findings further develop this narrative by distinguishing not just who may benefit from GLP-1s, but also those at risk of adverse reactions. This dual analysis of patient response fundamentally shifts how obesity medication can be applied in clinical settings.

Looking Ahead: Future of Personalized Obesity Treatment



Phenomix CEO Mark Bagnall asserted that these findings showcase the transformative potential of predictive tools in reshaping obesity therapy. By identifying patients susceptible to side effects prior to initiating treatment, healthcare professionals can enhance overall adherence and improve the efficiency of clinical trials through more informed participant selection.

The partnership with Mayo Clinic, along with its dedicated team, has played a pivotal role in validating this approach to precision medicine, which stands to revolutionize how obesity is treated across the healthcare spectrum.

With studies like these paving the way for more personalized treatment options, the future of obesity care looks remarkably promising. By aligning patient genetics with drug development, Phenomix is not just advancing treatment efficacy but also shaping a more responsive and individualized healthcare landscape.

For further insights into Phenomix Sciences and their research endeavors, visit phenomixsciences.com.

Topics Health)

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