BioWorld International Correspondent
ZICHRON YA'AKOV, Israel - Optimata Ltd., of Ramat-Gan, raised $1 million to launch clinical trials of its Virtual Patient Engine that will tell doctors what the optimum chemotherapy dosage and schedule is for breast cancer patients.
"This is a milestone in the field of personal medicine and in the use of [information technology] to provide highly accurate individualized therapies for treating cancer patients," said Optimata's chief technology officer, Levon Arakelyan.
Arakelyan told BioWorld International that Optimata has developed a predictive model that could determine the optimal dosage and scheduling of cancer therapies.
"Now patients suffer enormously from side effects of chemotherapy, on one hand, and, on the other hand, do not necessarily get maximal effectivity," he said.
In the first stage of the trials, the Virtual Patient Engine will generate an accuracy score predicting the outcome of conventional drug regimens used in the treatment of breast cancer patients. A set of physiological parameters about each patient is configured into an algorithm and fed into the Virtual Patient Engine, which then shows how treatment will impact tumor load and drug toxicity.
After that, the outcome of patients receiving standard treatment protocols will be compared to patients on individualized regimens designed by the Virtual Patient Engine.
The new funding came from Trimaran Investments, a private European investment group that is Optimata's lead investor, with a grant from the Office of the Chief Scientist of the Ministry of Industry and Trade.
Zvia Agur, who founded Optimata in 1999, explained the benefits of the model.
"Few drugs developed so far based on a purported genetic fingerprint' have been able to predict a patient's response to treatment," he said. "The results are disappointing, despite the significant investment of big pharma in pharmacogenomics. The main reason for such failures is that the reaction of cancer patients to drugs is too complex to be fully accounted for by a small number of genetic mutations.
"We believe that clinical validation of this data-based model will, this year, pave the way to significantly improved drug therapies," he added.