Earlier this year, IBM introduced “Watson Genomic Analytics” a cloud-based service that integrates human genome data with Watson’s cognitive capabilities, processing that data as part of a broader clinical solution that runs a patient’s genome against potential diagnoses and then recommends medical literature associated with the analytics as well as information about potentially relevant pharmaceuticals. The physician who has subscribed to this cloud-based service then shares the information with the patient and the patient’s care team to provide additional insight and evidence enhancing “informed treatment decisions.”
This ambitious initiative, while clear in its simplest “end-state,” is still very much in beta, as IBM partners with some of the best organizations in the genomics industry with a focus around curing cancers including lymphoma, melanoma, pancreatic, ovarian, brain, lung, breast and colorectal.
“This collaboration is about giving clinicians the ability to do for a broader population what is currently only available to a small number – identify personalized, precision cancer treatments,” said Steve Harvey, vice president, IBM Watson Health in a statement. “The technology that we’re applying to this challenge brings the power of cognitive computing to bear on one of the most urgent and pressing issues of our time—the fight against cancer—in a way that has never before been possible.”
Genomics and cancer organizations participating include:
- Ann & Robert H Lurie Children’s Hospital of Chicago
- BC Cancer Agency, City of Hope
- Cleveland Clinic, Duke Cancer Institute
- Fred & Pamela Buffett Cancer Center in Omaha, Nebraska
- McDonnell Genome Institute at Washington University in St. Louis
- New York Genome Center
- Sanford Health
- University of Kansas Cancer Center
- University of North Carolina Lineberger Cancer Center
- University of Southern California Center for Applied Molecular Medicine
- University of Washington Medical Center
- Yale Cancer Center
IBM’s research group is extremely active in genomics across a number of domains beyond clinical human cancers. Their practice areas include:
Plant Genomics, Human Population Genomics, Genomic Medicine (DNA, RNA, ChIP, etc.), Comparative Genomics (across related and distant species) and way out there - Combinatorial Patterns (discovery on biosequences) and then (even farther out) synthetic biology and nanotechnology applied to biology.
Read the Tea Leaves
When a company the size and scope of IBM starts to build an ecosystem of its own, and continues to invest hundreds of millions in R&D, pioneers and new innovators in global genomics start to pay attention in new ways.
Like any emerging field, both scientific and commercial, the global genomics industry has attracted brilliant, visionary entrepreneurs and billions in investment capital. The genomics industry will top USD22 billion by 2020, growing at an estimated CAGR of 10.3% from 2014 to 2020 (according to Grand View Research, Inc., November 2014 study). We are experiencing a “gold rush” not unlike what we experienced in the late 1990’s and early 2000’s with social, mobile and Internet-based communications – fields which feathered the balance sheet of IBM and continues to contribute to their growth creation, also on “the cloud” and “the internet of things.”
The high growth industry of genomics is incredibly fragmented, with many companies, large and small, young and old, competing in the creation and often slow commercialization of components including hardware, software, applications, analytics, and more. Recent launches, such as Helix (with funding from major players, including the sequencer goliath Illumina), highlight the continued push into this space from all sides.
I believe we will reach over $20B in market size by 2020, continuing to grow exponentially to $100B by 2030 (roughly, using Moore’s Law to extrapolate). IBM and Watson will certainly be an important contributor to that growth, and its shareholders will benefit – but IBM and Watson will simply be a part of what will be a diverse, dynamic global market.
Three Areas of Market Opportunity:
An area of great variability in need, capabilities, energy, information, SLA’s, etc. (sample sets in the 1-100 range). Also modest revenue (~$100m scale). This is the traditional area of genomics that has never scaled as much as the pundits (including myself) historically have hypothesized. But from a technical perspective, it is the most aligned with the broad capability set that Watson brings to bear.
Slightly less variability, more focused but still the vast majority of the work is one off or close to that (sample sets in the <1,000 range). (~$1bn scale) An area of recent massive growth and one that will continue to grow at very high rates over the next few years. Traditionally focused on pharma, it is expanding to a variety of other sub domains. This area is one that Watson is certainly aimed towards, but will require 2-3 years to mature into significant revenue streams for IBM Watson.
Clinical Standard of Care
Very little variability, each sample is identical to others, passed through a regulatory process, vetted and then run through multiple clinical operations internal processes before adoption (sample sets in the >1,000,000 range; $100bn scale, and emerging over the next 3-5 years). This is the 800lb gorilla and the one most venture and PE investment in the last few years have focused.
The third set is where an extremely well architected, organized and continually connected and collaborative ecosystem makes sense. We are on the threshold of tremendous growth, over time. Take the entire revenue of genetics to date (estimated at well over $500bn to date), and do a couple of multiples of that and that is the medium (20-30 year) revenue potential for this. Clearly this is the area of longest and highest value for Watson.
Soon, I will write about the differences between R&D, Clinical R&D, and Clinical Standard of Care and how big governments, big academic and research institutions and big companies are required because this is a “pretty big deal” – commercializing and scaling access to genomic data to improve and extend millions of lives. We need to move past re-inventing the wheel every time we want to launch a new genomics tool, diagnostic, etc. to market.