"Breast cancer patients currently are all treated according to the same chemotherapy protocols, yet only between 15-65 percent of the patients respond to the chemotherapy. There is a need to find an empirical way of individualizing the therapy for each patient", stated Professor Samuel Ariad, Head of Soroka's Institute of Oncology and Chief Investigator in the study.
In the first part of the study, the prediction accuracy of Optimata's Virtual Patient Engine will be validated using results of 360 patients who were monitored for up to four years after being treated with a chemotherapy drug. Optimata will create a computerized clone for each patient, using the patient's pre-treatment physiological, histopathological and radiological data, as estimated at Soroka. Optimata's researchers will "treat" each Virtual Cancer Patient with the therapy prescribed for each real patient and will predict whether she is expected to develop metastases and in which body locations. These predictions will be then compared with the real results of the 360 patients treated at Soroka.
In the second part of the study, the initial data of 40 breast cancer patients from the above group, who were known to have developed metastases and were treated with either Adriamycin, Docetaxel, Paclitaxel, Vinorelbine or Tamoxifen will be used and their individual metastases dynamics under each one of the above drugs will be retrieved by Optimata's Virtual Patient Engine. Predictions will be compared with the clinical results.
In December of 2004, Optimata initiated a similar validation study in collaboration with Nottingham City Hospital in the United Kingdom. Following completion of these studies, Optimata plans to begin clinical trials using the Virtual Cancer Patient technology to provide optimal dosing and scheduling regimens for actual breast cancer patients on an individual basis.
In addition to improving the use of existing cancer and other drugs, Optimata's platform technology is expected to accelerate the development of new drugs. "The Virtual Patient Engine enables drug developers to rapidly test and optimize drug development in silico, thereby reducing the number of animal and human trials required to bring a new drug to market", stated Professor Zvia Agur, Chairperson and Chief Scientific Officer.
Optimata is a developer of predictive biosimulation technologies for use in drug development and in the individualization of therapeutic treatments. For drug developers, Optimata offers a rational approach for the selection of patient populations and the optimization of drug scheduling and dosage. Optimata's technologies significantly reduce the number of pre-clinical and clinical trials required, enabling trials to be performed only for decisive validations.
Optimata's technology is based on a computer-generated method of accurately predicting how individual patients or patient populations respond to a compound. The technology combines computer models of human physiology, diseases and the therapeutic impact of a compound. The technology enables drug developers to conduct an unlimited number of "virtual trials" to be carried out on an almost infinite combination of dosages, treatment schedules and patient population characteristics.
Optimata has used its Virtual Patient Engine technology in optimization projects for Novartis, the Mayo Clinic and Rotterdam University. Optimata was founded in 1999 by Professor Zvia Agur, a world-renowned biomathematician who has pioneered methods of using computer modelling for optimizing treatment protocols in cancer and pathogenic diseases. For more information you can contact Professor Zvia Agur at Optimata Ltd.