Entelos, Inc, a simulation and modelling company focused on human health, announced that the US Patent and Trademark Office has granted US Patent No. 7,654,955 entitled "Apparatus and Methods for Assessing Metabolic Substrate Utilization" to the company. These methods further strengthen the Entelos Metabolism PhysioLab platform and leverage insights about human physiology that can lead to improved diagnosis, clinical testing, and personalized treatment across a highly variable patient population. This method may also be used to improve the selection of patients for clinical trials of metabolic therapies and diagnostics.

"We are pleased to add this new patent to cap our leadership position in metabolic disorders such as diabetes and obesity," stated Jeff Trimmer, CSO of Entelos. "Our biosimulation platforms and insightful 'what if' scenarios have already led to better decisions in R&D and this new diagnostic capability can stratify patients based on underlying differences in their disease state to optimize care."

It has been estimated that pharmaceutical companies spend more than US$ 1 billion and over 12 years of R&D to get a new medicine to patients. Successful development of new, more effective treatments for diabetes and obesity has been especially difficult since patients vary widely and the effects of diet, exercise, and drug therapies on human physiology are highly unpredictable. Any insights that can be used to better predict a patient's response to complex treatment regimens could thus accelerate progress in diabetes and obesity research.

The newly patented method extends the ability of the Entelos Metabolism PhysioLab platform to explore, simulate, and predict differences in fuel utilization (e.g., fat, carbohydrate, and protein metabolism) between patients, a key predictor in responses to treatment.

The Entelos Metabolism PhysioLab platform is an innovative, predictive computer model that represents the underlying physiology of metabolic disorders such as obesity and diabetes and uses simulated "virtual patients" to help predict responses. These virtual patients enable new therapies and interventions to be efficiently "flight tested" in a computer before expensive clinical testing in humans, reducing the risk and time to market for novel drugs. The best treatment approaches for specific patient types can be identified earlier, potentially leading to the development of more predictive companion diagnostics and personalized care.

Entelos is a life sciences company applying next-generation predictive technologies to revolutionize the way medicines are discovered, developed, and utilized.