Entelos,
Inc., a simulation and modeling company focused on human
health, announced today that the U.S. Patent and Trademark Office has
granted U.S. 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.
“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.”
“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 $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.
Ultra-processed foods drive obesity and metabolic risks