Optimata takes the guesswork out of clinical testing

The use of Optimata’s biosimulation technology represents a major paradigm shift in how drugs are developed.Suppose you’re a drug developer and your new drug has been proved effective in clinical testing. How can you decide what the optimal dosage is …

The use of Optimata’s biosimulation technology represents a major paradigm shift in how drugs are developed.Suppose you’re a drug developer and your new drug has been proved effective in clinical testing.

How can you decide what the optimal dosage is for real-life patients? Until now, you’d have to conduct expensive and inefficient conduct dosage escalation trials until the optimal dosage is identified.

But with a new Israeli-developed, computer-generated method called the Virtual Patient Engine, the optimal dose can be calculated rather than guessed at. Moreover, the VPE calculates the most appropriate timing and frequency of the administration of the drug according to the varying dynamics of the disease.

The innovative VPE, developed by Optimata, a young Israeli company located in Ramat Gan, accurately predicts how patients will respond to a drug compound. The in-silico technology combines computer models of human physiology, of the disease and of the therapeutic impact of a compound, with the advantage that the Engine can perform an unlimited number of virtual trials using an infinite combination of dosages, treatment schedules and patient characteristics.

By this revolutionary biosimulation breakthrough in simulating, predicting and optimizing the response of patients to drug administration, Optimata is replacing the trial and error approach and taking a giant step toward “personalized medicine.”

The company was founded in 1999 by Professor Zvia Agur, Chairperson and CEO of Optimata. An eminent international bio-mathematician she has made major contributions to the theory of disease dynamics as well as chemotherapy and vaccine optimization.

The VPE recently displayed glowing results on an actual case, as reported in the British Journal of Haematology. Two companies – Genentech and Pharmacia – had been struggling to develop a drug called thrombopoietin (TPO)
that would increase the production of blood platelets in chemotherapy patients. Development was halted after it was realized that the treatment caused severe immunological reactions in the patients.

“They contacted us,” Agur told Globes, “and we developed a suitable model, which we claimed could enable the use of lower doses at higher frequencies. In fact, the results of tests on mice proved that our predictions were absolutely accurate.”

“The study results offer new hope for TPO and suggest that Optimata’s technology can be used to rescue other drugs which have failed in clinical trials, or enable the developers of other drugs to reduce dramatically the risk of trials failing,” added Yoel Berdugo, Vice President of Business Development

Developing one new drug takes an estimated period of 12-15 years at a cost of over $500 million. Over $150 million of that is lost to experimentation failures, with a clinical trial failure rate of over 80%. Post genomics and new drug discovery technologies generating novel therapies impose increasing difficulty to the clinical development process. In realizing the potential of these novel therapies, traditional issues in drug development are now even more challenging. Indication selection, patient population selection, dosing and dosing interval determination are crucial factors in developing a novel therapy.

The above mentioned factors are approached in many different ways, yet the regulatory success rate is, at best, constant. It is clear that the post-genomics era has generated revolutionary technologies of drug development. Without a significant change in the drug development paradigm, the potential of novel drugs will not be fully realized. More specifically, the pharmaceutical and the biotechnology industries need to replace the inefficient trial and error method of drug development with a system whereby clinical trials are conducted only for decisive validations.

Optimata’s Virtual Patient Engine enables investigators to assess indications, patient population groups and efficacy/toxicity trade-offs with the goal of a-priori identifying the most clinically efficacious treatment protocols. As such, the Virtual Patient Engine can be deployed during the entire development process, from pre-clinical testing to phase IV clinical trials. While its full revolutionary potential is realized when accompanying the drug development process throughout, its accuracy in capturing the clinical reality can be utilized for optimizing:

“The use of Optimata’s biosimulation technology represents a major paradigm shift in how drugs are developed,” said Agur. “Instead of using trial-and-error tests on animal and human subjects, we offer predictive biomathematical models which are highly accurate and significantly reduce risks and costs.”

The VPE examines drugs’ effect on the body
by creating models of all the processes relating to a drug’s effects and running them through a computer. These processes include the way a disease develops, the drug’s interaction with the patient, and its side-effects.
These can be expressed as algorithms for mathematical equations. It is only
necessary to take the relevant systems into account. In the case of cancer this means blood and bone marrow.

The result is an algorithm containing hundreds of factors. The goal is to create a “virtual patient” to whom questions can be asked, and, just as important, to create predictions of a drug’s effects before clinical trials begin. It’s no secret that clinical trials currently use the “shot in the dark” method. Agur is trying to change the paradigm and put clinical trials on a predictive basis.

How will this help? First, it will save on clinical trials and all matters relating to drug protocol. “The clinical trials should only serve to verify predictions during the drug development process,” declared Agur. The
algorithms are designed to determine in advance which cancer each and every drug should be directed, dosage, and frequency, and the optimal combinations of existing treatments. “This will improve development time, and reduce the number of patients participating in the trials,” she said.

Agur admits that it will be difficult to convince the authorities in charge of clinical trials to rely on algorithms, but says that it’s inevitable.

“There won’t be a need to repeat the trials, and go back from the Phase III to Phase II to examine another indication. That’s a terrible waste. We’ve begun cooperation with one company, and have already sent them back to the pre-clinical stage to expand the indications. Without
us, their patient population would have been limited.”

The method is designed to determine the drug’s optimal use at the molecule selection stage at the start of the R&D process. “We don’t discover drugs; we work at the development stage. It’s important for us to be involved at the even before the pre-clinical phase, in order to suggest which trials will be critical,” said Agur.

Optimata focuses on cancerous tumors and various blood diseases. The system is ready to handle treatment of scirrhous (hard) tumors, and the company is developing algorithms for CNS diseases.

“We’re currently engaged in developing a virtual patient engine for the central nervous system which would focus on diseases like Parkinson’s and Alzheimers. We’re doing fine tuning and verification of the precision of prediction in prospective human trials,” Agur told ISRAEL21c.

Agur, a biomathematician by training, does not believe that genetics are the be-all and end-all. “The post-human genome project era has created huge databases, but the question is whether they it will really improve cancer treatments. There are no tools now to predict the effect of various treatments. The genome is important in itself, but it you should remember
that mapping the genome is just one dimension and that genetic processes work at more than one level. Genetics only marks human potential. Beyond the genome are molecules, cells, cell populations, which Optimata addresses. Genetic information has become a preliminary piece of the equation.”

Optimata’s business model is based on drug development collaboration with pharmaceutical companies. Collaboration can be at the R&D or product stages, forming a foundation for future work. Optimata is paid a percentage of the product’s development cost that reflects the pharmaceutical company’s savings by using Optimata algorithms.

“The Virtual Patient Engine is ready and has already been used by a big pharma company based in Europe and the U.S. We’re currently in negotiations with several drug developing companies,” Agur told ISRAEL21c.

Initial returns from this business model came with Optimata’s first revenue in January 2001, following a development agreement with Novartis
Novartis paid Optimata for an analysis
mechanism for drugs in the advanced development stages. Novartis will pay additional sums on the basis of development milestones.

Optimata also signed an agreement with the Swiss Group for Clinical Cancer Research (SAKK), which focuses on lymphoma.

Potential partners, besides pharmaceutical and biopharmaceutical companies, are clinical trial companies, health services providers and doctors. “Our vision is to reach the doctors in clinics,” says Agur.

Agur doesn’t discount applying the VPE to over-the-counter products.
“One day, everything will be an over the counter product. But it’s necessary to take into account that drug development is an intensive process. We emphasize timing, dosage, and frequency. But there are also nuances: which patient will respond and which won’t. The final product that a doctor receives does not require our input. I assume that it might be an off-the-shelf product if the drug companies want it to be.”

(Based on a report in Globes)