Matthias von Herrath, MD: Software Accurately Predicts Optimization of Type 1 Diabetes Treatment
By: Almas Eftekhari
In 2003, a team of leading experts began developing an innovative, virtual means to advance research efforts for type 1 diabetes treatment and prevention. In collaboration with Entelos, Inc. and with funding from the American Diabetes Association, they created the Type 1 Diabetes PhysioLab Platform -- a computer-based model that simulates the pathophysiology of type 1 diabetes in rodents from birth throughout disease progression.
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The cutting-edge technology allows scientists to explore alternatives in treatment that are difficult or impractical to measure in laboratory and clinical testing. The model provides key information about when the introduction of treatment would be most effective or when the course of the disease changes. Researchers can then translate the data for human use and predict how people with diabetes may respond to the therapy.
In a study published in the December 2010 issue of Diabetes, Matthias von Herrath, MD. from the La Jolla Institute for Allergy and Immunology confirmed the accuracy of computer modeling in enhancing drug efficacy against type 1 diabetes. Through virtual simulation of nasal insulin therapy, the model revealed critical factors, such as dose timing and frequency that optimize the treatment's effectiveness. Based on the model, Dr. von Herrath implemented the experimental design in his laboratory, and his results verified the model’s successful predictive ability.
"By allowing us to pre-test our theories using computer models, we can ensure that the more time-intensive and costly process of laboratory testing is focused on the most promising therapeutic strategies, with the greatest chance of success," said the senior author.
Dr. von Herrath encourages further development toward a human-based platform to support the design of clinical trials and accelerate treatment goals. "Since early stage human clinical trials can cost $10 million or more, predicting the right conditions to try is important." He envisions that with a human model, "personalized simulations will become possible and customized treatments could be suggested on an individual basis."
(G. Fousteri, J. R. Chan, Y. Zheng, C. Whiting, A. Dave, D. Bresson, M. Croft, M. von Herrath. Virtual Optimization of Nasal Insulin Therapy Predicts Immunization Frequency to Be Crucial for Diabetes Protection. Diabetes, 2010; 59 (12): 3148 DOI: 10.2337/db10-0561)