Shu Boles, we often worry about consolidation of care, but is there an upside to it? Does it allow you to broaden the technology you can make available and improve patient care?
Dr. Boles (Qiagen): Yes. The breadth of technologies we offer as a vendor can streamline the workflow, from blood tube to automated extraction to automated laboratory prep and variant interpretation. We would love to offer that to consolidated labs to help handle high testing volumes. It can then be standardized across different sites.
Gilbert Hakim, is there adequate competition in genomic IT as it’s serving laboratories and pathologists today?
Gilbert Hakim (SCC Soft Computer): I don’t believe so. The problem is fundamental in terms of the requirements of next-gen sequencing and genomics. For example, cytogenetics is becoming molecular as well; HLA has seeped into next-gen sequencing, which seeps into donor testing and transplants. It requires enormous capital to develop software that is end-user configurable so end users don’t have to go to the vendor. We started in the early 2000s and now have a huge library of workflows that we can drop in. It cost close to $200 million to develop the engine itself, so the end user can change, for example, going from 96 to 192 to 384 wells. The companies operating in our market, especially in genetics, are so small they cannot invest in creating an end-user-configurable engine. That’s why many clients who buy these systems find that within a couple of years, their product becomes obsolete and the new instruments can’t connect to anything. The fundamental problem is developing and maintaining this type of application and giving power to the end user to configure their own system as instrument chips change or other methods reduce turnaround time. It all has to do with data interpretation and accessibility.
We have a rules engine that flags a particular disease based on parameters within CP/AP, genetics, and blood services to prompt pathologist review. Each pathologist can create a library of what to look at if conditions for certain diseases occur. This dramatically improves efficiency by directing pathologists to the areas supported by the data versus the vast data in CP, AP, genetics. Unfortunately, the decision-making for purchasing this type of application has been taken out of the hands of scientists at the bench and has nothing to do with the application’s functionality or usability.
Jeremy Segal, is there vigorous competition among companies to innovate?
Dr. Segal (University of Chicago): The scale of innovation occurring now is dramatic. We have a lot to evaluate. Even the basic sequencing itself isn’t as straightforward as it used to be. We’ve gone from two major players to many. There’s a new Roche instrument coming out that could disrupt the large-scale genomics market. There are many emerging smaller-scale sequencers as well. Some have similar data-type outputs to the Illumina platforms we use and might be easily integrated into our existing tests. Others produce different types of outputs that would require wet lab alterations or pipeline re-engineering, but which might allow us to perform new and different types of tests. Many companies are coming up with novel types of assays and analysis algorithms, including options for methylation-based analysis and minimal residual disease detection.
I am inundated with the many possible applications and innovations to review. But the nature of being in a clinical lab means you can’t just latch on to the newest technology. You have to wait and see which are maturing, usable, and well supported before onboarding them to support clinical testing. We’re in a waiting phase, but that won’t go on forever, and we will end up integrating some of it soon, but we still have to determine which ones.