Mynomx Inc. (formerly Precision Wellness, Inc.), a Silicon Valley-based company at the intersection of next-generation AI analytics and the latest medical and nutrition science, today announced the scientific validation of their cardio and metabolic predictive models against 2.5M patient population through two sponsored research studies with Stanford University.
People with underlying cardiometabolic conditions and comorbidities that include: inflammation, hypertension, obesity, diabetes, and cardiovascular disorders have the highest complication and mortality rates when it comes to the Novel Coronavirus (COVID-19). Through predictive risk stratification, the at-risk population in our communities can be identified and supported through intervention programs directed towards changing their risk profile and decreasing the risk of complications due to COVID-19.
"Proper COVID community response programs need the foresight and insight to accurately predict the risk in our communities, as a necessary first step to deploying intervention programs that can mitigate this risk," explains Farzad Naimi, a serial entrepreneur, and managing partner at RONA Holdings, and currently spearheading a United Communities initiative to bridge the underprivileged communities with personalized nutrition programs that boost their immune systems.
Mynomx predictive analytics have been designed to deliver the most accurate prediction and stratification of the at-risk population for cardiometabolic disorder validated by these two studies.
The first sponsored research program was conducted in conjunction with Stanford University and UK Biobank. In this study, Mynomx (formerly Precision Wellness) demonstrates the high predictive performance of its next-generation AI-driven risk models against the UK biobank database of almost half a million patient population. - reference press release and scientific publication.
"Early identification of individuals at risk of cardiovascular events is the most effective approach to changing the course of these diseases and preventing the occurrence of catastrophic events," notes Dr. Mehrdad Rezaee, President of Cardiac and Vascular Care and Mynomx co-founder.
The second sponsored research study was conducted in conjunction with Stanford University using the Stanford Medicine Research Data Repository (STARR). The STARR database contains electronic health record (EHR) data for more than 2.1 million patients from 2000-2017.
"This level of validation in a very large population is important to establish the accuracy of the risk assessment models, as well as to demonstrate their applicability using different external data sources," stresses Dr. Arsia Takeh, Head of Data Science at Mynomx, who conducted both these studies in conjunction with Dr. Andrea Ganna of Broad Institute and Dr. Erik Inglesson, formerly Professor of Cardiovascular Medicine at Stanford University.
To learn more about the development and validation of the Mynomx next-generation risk engine for CMD, contact us for scientific publications.
Mynomx is a leading scientific based food personalization company that offers organizations and individuals an advanced, integrative approach to managing their health through personalized health insights and nutritional intervention. The data-driven Mynomx analytic platform, powered by the latest in nutritional science at the molecular level, multi-omics, and next-generation AI, offers the means to manage health through "food as medicine," preventing disease and supporting healthy aging. In addition to serving individuals, this platform is ideal for insurance and self-insured organization, corporate wellness, testing, and diagnostic companies as well as food retailers, seeking deeper personalization and engagement. To learn more, visit www.mynomx.com.