This week, I attended the Consumer Genomics Show (more so a “clinical genomics” show). In a session on Next Generation Sequencing led by five industry experts, a recurring observation was that, on the one hand, steady investments in sequencing technology was indeed delivering breathtaking value and driving down sequencing costs – bravo indeed and a new generation of discoveries are upon us!
However, on the other hand, without broad use of new software to analyze this massive volume of data, this group reported an “information bottleneck” for researchers — exacerbated by a culture of free, fragmented software.
So what to do?
I, for one, am quite optimistic on the topic.
I think that NIH and market forces will resoundingly address the challenge. I heard from Eric Green, director of NHGRI, that his team and the NIH see the bottleneck as a critical issue and they are taking steps to adjust their priorities accordingly.
And, while researchers in the past, may have made significant discoveries with free and varied software, I contend that the following market forces are encouraging the best of them and their organizations to substantially and positively raise their software aspirations:
- the data volumes in whole-genome projects simply demands a new generation of analysis methods, tools, and platforms — and providers are responding.
- more and more research happens in partnership, requiring collaboration software to share data, intermediate findings, and discoveries — again, solutions exist.
- more and more organizations will want to inject public studies directly into their research, remove silos, and create a “continuous/growing/queryable database of variant information” — available today.
- more and more research will be aimed at personalized medicine, diagnostic testing, and clinical applications – areas that call for strict and documented information exchange.
- bioinformatics teams and companies will utilize emerging sequence database systems to arm researchers with powerful new discovery applications. (In a conversation yesterday with George Church, he commented: “how could it be any other way” when I asked if he envisioned the industry moving to such systems.)
All told, motivated by these opportunities, I believe that we are entering an “Information Renaissance” — powered by sequencing + software technology!
Keep in mind that the answers lie in the sequence data — and researchers will not stop until they get them. And if high-quality, fair-priced software is required to get at them, so be it. Increasingly, great software is becoming a “must have” with “must have” rewards.
I’ve seen this happen in other professions as they turned to computers. Electrical engineers started with free or home-grown software to mostly capture schematic drawings. Then chip manufacturing technology exploded and a $5B electronic design automation (EDA) software industry was born. Soon software was synthesizing whole circuitry from simple specs, placing and routing millions of transistors on chips, simulating whole systems before manufacturing, even telling you how to test the chip after manufacturing – all “must have’s” that have co-powered Moore’s Law for over 20 years.
So, as exciting as sequencing performance has made Life Science research in the past decade, I suggest that a co-powered “Information Renaissance” will take us to new levels of discovery. And we all very much look forward to it!