Discovering cures for cancer, for Alzheimer’s, for multiple sclerosis, for Parkinson’s, for the halting and reversing of aging itself, may not require the development of new drugs. It may mean discovering properties and therapies in drugs already developed and used for other diseases.
That’s the principle driving bioinformatics start-up Insilico Medicine, a Baltimore-based company utilizing GPU-accelerated NVIDIA advanced scale computing to power deep learning neural nets using massive datasets for drug repurposing research that targets aging and age-related diseases.
Drug re-targeting is not new. One of the best known cases is rapamycin, a drug originally thought to be an antifungal agent before it became widely used in in organ transplantation and then as a cancer fighter. Other companies have pursued drug re-purposing as a development strategy, but Dr. Alex Zhavoronkov, Insilico CEO, said his company using big data analytics to scale the strategy to a level never previously attempted.
Insilico researchers not only generate their own data, they ”scavenge” existing datasets that pharmaceutical companies and research institutions have retired because they were too small, in themselves, to provide much research value. Aggregated and analyzed, the data is providing Insilico, its pharmaceutical partners and physicians with insights into how medications designed and approved for one ailment can be redirected to attack another.
“We’ve found a way to suture together our data with many other databases,” said Zhavoronkov, “and then it starts making sense.” Altogether, Insilico has 3 million gene expression samples amounting to hundreds of terabytes of data. “The breakthrough is combining so many pieces of the puzzle in one particular place,” he said, explaining that Hadoop has been instrumental to harmonizing large amounts of unstructured, weakly related data, and then running Insilico’s drug scoring algorithms against it.
In February 2015 at the Personalized Medicine World Conference in Mountain View, CA, Insilico was recognized as the “Most Promising Company” in the fields of human genetics and personalized medicine. In March, Insilico was one of 12 finalists selected to present at the Early Stage Challenge at NVIDIA’s 2015 GPU Technology Conference. In partnership with Novartis last September, Insilico organized an international aging forum at Basel Life Science Week in Switzerland. The company also launched bioinformatics research partnerships with ATLAS Generation (stem cell research), Vision Genomics (ocular diseases); Pathway (cancer research); and Canada Cancer and Aging (personalized medicine and aging research). And the company said Insilico research papers have been published in 50 peer-reviewed journals over the past two years.
Insilico has configured four NVIDIA DevBox desktop supercomputer, using TESLA K80 GPU accelerators and four Titan X graphics cards, for a total of 28TF of processing power.
NVIDIA GPUs are the foundational technology driving deep learning techniques used by Insilico to compare healthy and diseased tissues, as well as aged and young tissues, and then to test – in digital formats – the impacts of drugs on those tissues to restore them to health and youth.
The full article appears in HPCwire’s sister publication EnterpriseTech. Link: http://www.enterprisetech.com/2015/12/09/gpu-accelerated-deep-neural-nets-look-for-cures-that-already-exist/