jueves, 30 de mayo de 2013

Big Data in Biotech: Where do we go from here? OBR-Bay @ UCSF, June 17th

ORIGINAL: Oxbridge Biotech
by Nick Mordwinkin, OBR-Bay
Tuesday, 28th May 2013
Do big questions come from big data?

SAN FRANCISCO, California – Big data in the Silicon Valley is about more than just getting people to click ads. The real promise lies in understanding health from the molecular to the population level. Recently “Big Data” has become almost cliché, a buzzword bandied about The Valley by tech stars leveraging their mathematical acumen to crunch site visits and bounce rates to deliver ever more potent advertisements. But the real promise of Big Data lies in health care. As the cost of acquiring data lowers, academia and industry are amassing data by the petabyte (that’s 1,000 terabytes) from 
  • microarrays, 
  • high-throughput sequencing, 
  • drug compound libraries, and even 
  • patient data
For example, when the Human Genome Project wrapped up in 2003, it took more than a decade and billions of dollars to appreciate the 20,000 genes buried within the 3 billion bases.

Now another 3 billion bases can be sequenced in a morning. The price has continued to fall, from billions in the 1990s, to $10M in 2007, to less than $1000 today – a vertiginous decline outpacing Gordon Moore’s eponymous law. From sequencing in the clinic, to predictive modeling of drug compounds, evidence-based medicine and massive clinical trials – the commercial potential of Big Data is approaching an inflection point in the life sciences. The real question is, how do we take mountains of this data from the server closet and the cloud and translate it into clinically relevant outcomes? As AstraZeneca’s Vice President of R&D, John Reynders, warns, “big data is only going to be as good as the questions that are being asked of it.” And now even billionaire philanthropist Li Ka Shing is getting in the act. Recently his foundation awarded Oxford University £20 million ($31 million) to help establish the Li Ka Shing Centre for Health Information and Discovery, which will include a Big Data Institute. The goal of this center is to analyze large data sets from DNA sequencing, electronic medical records, and other sources in order to advance knowledge about treatments and diseases such as Alzheimer’s, diabetes, and cancer.

Locally, more and more Bay Area startups are springing up with a major focus on collecting and interpreting Big Data. Syapse, which was founded at Stanford University in 2008, aims at disrupting healthcare by “bringing omics into routine medical use.” Their suite of cloud-based applications enables the generation and use of next generation genomic sequencing to diagnostic companies hospitals, laboratories, research institutions, insurance companies, and medical clinics, with the ultimate goal of improving patient care by helping clinicians with the diagnosis and treatment of patients. Syapse recently raised $3 million in series A financing led by The Social+Capital Partnership.

To help answer these questions, Oxbridge Biotech Roundtable’s OBR-Bay chapter is holding a panel discussion on Monday, June 17 entitled “The Commercial Potential of Big Data in Biotech”. The event will be held at Genentech Hall at the University of California, San Francisco Mission Bay Campus, and led by Sarah Aerni, Senior Data Scientist at Pivotal, and Jonathan Hirsch, Founder and President at Syapse.

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