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InSilico Medicine Opens US Office, Prepares to Launch Drug Discovery Software for Aging Research Market


InSilico Medicine, a newly minted bioinformatics company, is hoping to build a business by providing software that supports research focused on drugs that have the potential to slow or reverse age-related processes.

The company, which officially opened its doors earlier this month, has set up shop in Baltimore and will soon begin marketing a product called Geroscope. With this product, InSilico is targeting the pharmaceutical industry and large clinical institutions. The company is positioning its offering as a computational platform for screening and predicting the effectiveness of drugs that suppress aging-related processes. The system works by comparing differences in gene expression and signaling pathway data collected from cells in different tissues in older individuals versus those taken from younger healthy individuals. It then looks for drugs that can stimulate the pathways in older cells to behave as they do in the younger cells. It's currently being validated in cell lines and model organisms with a full launch planned for later this year.

Geroscope is based on similar technological concepts that underlie a system called OncoFinder, which is used to select and rank personalized cancer therapies. That platform is owned and used internally by Pathway Pharmaceuticals, a Hong Kong-based pharma company. In Silico Medicine licenses the technology from them.

Alex Zhavoronkov, InSilico Medicine's CEO, was one of OncoFinder's developers. Explaining how the technology came to be used at Pathway and now at his company, he told BioInform that the process began with research projects where he and others were analyzing gene expression data collected from patients with tumors. They developed the computational methods, he said, of mapping gene expression data onto various cellular pathways that are activated in cancer cases, and for ranking drugs that targeted these pathways and successfully killed the cells gone wrong or sent them into a state that was as close to normal as possible. They used the system to analyze data from various solid and blood-based tumors including bladder cancer, head and neck cancer, and leukemia.

After validating the algorithms that would eventually comprise the OncoFinder software in almost 1,000 cancer patients, Zhavoronkov and colleagues commercialized the technology first in Russia providing it as a service to oncologists there who were looking for more guidance in selecting treatments for their patients, and then they expanded the technology to China where Pathway Pharma used it in their drug discovery efforts. "After that we realized this particular personalized medicine approach can be used for drug discovery for aging research," he told BioInform. "We could take gene expression data from the 'young cell' and look at the signaling pathway activation profile that is characteristic to that tissue and to that specific age of the patient" and then compare it to the same sort of data collected from cells in older individuals.

The key to the technology, and what makes it a cut above similar systems, according to Zhavoronkov, is that "we found the fine line between too much complexity and too little complexity." Some groups have "tried to rank targeted compounds by looking essentially at every single genome in [a given] network, [but they can't] really find good correlations from patient to patient and from norm to cancer."

Instead of looking at all possible pathways in cells, "we identified a limited number of pathways. So, for cancer, we look at pathways that are related to cancer," for example, some of the metabolic and cell cycle pathways for a total of just over 100 pathways. "That is easier at looking at a [large dataset] with unrelated elements, which is an approach that some groups have taken," he said. They also look at what they believe is an appropriate number of elements per pathway — about 65 to 70 elements on average, he said. "It's much more accurate and more effective than looking at a very small [number of] individual network elements," for example, just 10 or 15 elements.

InSilico Medicine has finished developing its version of the software — which includes some new capabilities in addition to those that are in its source software — and it is now validating the tool in human fibroblasts and nematodes. The company also constructed internal databases of gene expression data from young healthy cells in a variety of tissues that it has gleaned from both open-source and commercial repositories as well as various drug compounds with known molecular targets. The validation tests are being done in conjunction with laboratories in academic institutions here in the US, China, and Russia, Zhavoronkov said. They plan to publish the results of these tests this in July, after which they will begin making the software available for use in clinical contexts.

Zhavoronkov said that the company hopes to begin offering Geroscope for clinical use either just before or during an Aging Research Symposium at this year's MipTec conference — a drug discovery and life sciences research event that will be held in Basel, Switzerland on Sept. 23 – 25. Currently the software is available for research use. Customers that fall into this category — academic research institutions mostly — don’t have to pay a licensing fee. Rather the company forms research collaborations with these clients where it provides access to its servers and expertise and works in concert to analyze the data these groups generate. In return, it receives a share of the proceeds of any intellectual property that's generated over the course of the project. Zhavoronkov didn't disclose the exact percentage. Its pharmaceutical clients on the other hand pay an undisclosed "milestone payment," Zhavoronkov said, to access to company's software and expertise.

InSilico Medicine sees a number of potential areas where its software could be useful. Besides helping researchers identify novel treatments, Geroscope could help pharma customers identify and rank potentially useful geroprotective drugs from lists of approved treatements, Zhavoronkov said. "We can take a very large number of drugs with known molecular targets, run it through Geroscope and rank them placing those known to have beneficial effects on age-related processes higher up on the totem pole.

Another benefit of the system is its ability to help clients tailor treatments to individuals. "We know there could be similar phenotypes in people that age, but we all age at very different rates and for very different reasons … and we all metabolize drugs differently," Zhavoronkov said. "A system which helps you … predict the efficacy of a combination of drugs, some of which may already be approved for various therapeutic reasons for various conditions, is much more valuable than having a general one pill fits all strategy."

Finally, Geroscope could help pharma companies select participants who will derive the most benefit from clinical trials. Since "most drugs will not work in two different patients in exactly the same way, we will be able to help predict the outcome of [applying] various therapies on specific patients" prior to enrolling that patient in a clinical trial, he said.

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