PRODUCT

PCa GnRH Agonists Simulator

PCa GnRH Agonists Simulator enables simulations of clinical trials on a virtual population of prostate cancer patients being treated with a GnRH agonist

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Gold Standard

The reference model to predict testosterone suppression following GnRH agonists therapy

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Display and Export

Results can easily be visualized and downloaded in CSV format and a simulation report is available in PDF

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Easy to Use

Well-designed wizard that step-by-step guides the user through the setup and run of the simulation

Gonadotropin-releasing hormone (GnRH) agonists is  widely used to treat prostate cancer patients, which is one of the most frequent cancers in men. GnRH agonists are generally administered with slow release formulations which result into improvement of patients’ compliance and quality of life in addition to therapeutic benefits.

PCa GnRH Agonists Simulator is based on a semi-mechanistic pharmacokinetic  /pharmacodynamic computational model which describes the process of testosterone suppression by a GnRH agonist treatment in prostate cancer patients. The computational model has been calibrated on data obtained from triptorelin and leuprorelin clinical trials and it can be easily applied to any GnRH agonists.

PCa GnRH Agonists Simulator enables simulations of clinical trials on a virtual population of prostate cancer patients being treated with a GnRH agonist. The tool can be used to explore different trial design scenarios in terms of GnRH agonists pharmacokinetic and pharmacodynamic properties, single and multiple dosing, administration route, formulation type, virtual population size as well as testosterone castration limit.

Research team

PCa GnRH Agonists Simulator is the result of a collaboration between the University of Navarra and InSilicoTrials Technologies.

Articles & publications

Prashanth Rawla

Aylin Sertkaya, Hui-Hsing Wong, Amber Jessup and Trinidad Beleche

Chi Heem Wong, Kien Wei Siah, Andrew W Lo

U.S. Department of Health and Human Services, Food and Drug Administration. Innovation or stagnation?
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