Mark Murcko | Boston Biotech Watch

By Steve Dickman, CEO, CBT Advisors

Can you create biological insight on a laptop? If you could, it might overturn a fundamental paradigm of drug discovery: that it takes a great scientist or team of scientists to find a clear path through the messy complexity of biology. In the conventional model, sometimes the scientist is at a university. Other times she is in a company. But always, always, there is a series of iterative interactions – scientist running experiments in lab, scientist struggling to interpret results, scientist designing new experiments, scientist analyzing new results – until biological insight arises. If it ever does.

Of course, many drug discovery advances over the past thirty years have been driven by technological innovation: combinatorial chemistry; high-throughput screening; vastly improved imaging and prediction software; and rapid and reproducible assays run in some cases by robots on groups of cells or even individual cells leading to large and hopefully meaningful datasets.

But none of these advances has replaced the “Aha” moment of insight that arises from a human being’s engagement with a biological phenomenon that is thorny or one that had not even been perceived to exist. I always expected – and still do expect – to find that kind of insight in labs, not on laptops.

But now a renowned Stanford professor-turned-Silicon Valley venture capitalist, Vijay Pande, has set his sights on this challenge. Pande, the architect of the award-winning Folding@Home project and himself an award-winner in computational biology, recently joined a top Palo-Alto-based venture fund, Andreesen Horowitz, which formed a new $200 million fund to invest in “cloud biology” and other areas of software companies in the bio space. To read the post, click here or copy-paste http://onforb.es/1Sq3Q2G.

By Steve Dickman, CEO, CBT Advisors

What good is big data for drug discovery? Not much, if you ask the pharmaceutical industry. The world’s drugmakers have other challenges right now and, with a few notable exceptions like PatientsLikeMe, neither consumer-driven nor patient-driven “big data” seems to be part of the solution.

Even in the apparently more data-driven field of healthcare services, big data keeps bumping up against regulatory and practical barriers. As I wrote earlier this month, a funny thing happened to 23andme on the way to its now-on-hold million-person database….

Mark Murcko, Feyi Olopade and Ajit Singh (Image courtesy EBD Group)

A recent panel of experts argued that trends in big data will drive up its relevance and provide a navigable path toward greater utility both in pharma and in healthcare. The panelists at the workshop I put together for the 2014 Biotech Showcase in San Francisco last week hinted that the time will soon come when “big data” is as much a part of both drug discovery and healthcare as it is of financial forecasting and choosing driving routes that minimize traffic.

Click here to watch the video of the panel or copy-paste the link:

http://www.partnering360.com/insight/showroom/id/445

The companies that presented are NuMedii, a venture-backed company that calls itself a “digital pharma company” tackling drug discovery itself; and CancerIQ, a data analytics company focusing on aggregating data on how cancer patients are treated and using it to upgrade the treatment that can be provided in different geographies and types of hospitals.

Joining the CEOs of NuMedii and CancerIQ were Ajit Singh, a venture capitalist with Artiman Ventures who taught electrical engineering and neuroscience at Princeton and then ran global businesses for Siemens in oncology and digital radiology; and Mark Murcko, the former chief technology officer of Vertex Pharmaceuticals who is now running a consulting firm and advising computer-powered drug discovery firms such as Schrodinger and Nimbus Discovery.

Due to these engaging and insightful speakers, this was a fascinating panel that delivered all sorts of hints about what looks like an upcoming turning point. Topics included (time stamps on video in parentheses):

What sort of venture investor would understand a big data company in healthcare, IT or life science? (10:10) and (12:45)
Where do big data startups go to even get their data given the high degree of regulation? (27:00) and (28:50)
How can innovative startups avoid being stopped cold by HIPAA? (21:30)
What will be the turning point at which the pharmaceutical industry sees big data as a driver of solutions rather than just noise? (32:40) and (38:00) and (52:20)
Is genomic data “big data”? (17:00)
How can “sparse data” be just as useful as “big data” in solving certain problems? (43:00)
How can newly industrialized countries like India and China contribute to models that might be useful in the United States and Europe? Will they “go first” in some sense in using big data? (44:30)

Gini Deshpande, Founder-CEO of NuMedii (Image courtesy EBD Group)

Here is a more complete list of time stamps:

(2:00) Definition of Big Data “Things one can do at a large scale that cannot be done at a smaller one to extract new insights or create new forms of value in ways that change markets, organizations, the relationship between citizens and governments and more.” (From the 2013 book Big Data: A Revolution That Will Transform How We Live, Work and Think by Mayer-Schönberger and Cukier)
(3:00) Gini Deshpande self-introduction. “At NuMedii, we are a digital pharma company. We are focused on leveraging the vast amounts of life sciences big data that is out there and translating it into drugs with a higher probability of therapeutic and commercial success….We are a pharma company. We leverage the data and turn the data into drug candidates.”
(4:20) Mark Murcko self-introduction.
(5:10) Feyi Olopade self-introduction. “My co-founder is my mother. She is a nutty professor slash clinical oncologist slash MacArthur genius fellow. It was my mother’s vision to start using data and analytics to deliver more precision treatment and more precision risk assessment….We hope to democratize access to premium cancer care by helping providers deliver data-driven decisions.”
(6:35) Ajit Singh self-introduction
(7:45) In the world of healthcare, the analytics revolution has barely begun
(10:10) How NuMedii bridges the (large) gap between healthcare investors and IT investors
(12:45) How CancerIQ bridges the same gap
(14:35) Early days of analytics: Shared Medical Systems
(17:00) Why genomic data may not be big data
(20:35) How 23andme learned the hard way about regulation of medical data
(21:30) On overcoming HIPAA: a fascinating framework
(25:00) Why IT investing is easier: world of atoms vs. world of bits
(27:00) How CancerIQ gets its data
(28:50) How NuMedii gets its data
(32:40) Why pharma is still (mostly) focused on the drug candidates
(38:00) The importance of actionability
(41:00) Q&A: How to de-identify health data
(42:15) Cancer patients are very willing to share their (personal) information
(43:00) The best data may not be big data
(44:30) International big data in healthcare – will it take the lead? Case: India
(49:00) Case: China
(52:20) Why pharma does not yet trust “black box” models – they do not tell a story, says Murcko

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