I'm definitely an optimist about this, and I have an interest in it. So, grains of salt. But things worth noting:
The lack of labeled data is definitely a challenge, as you call out. But a sizable chunk of what we do is power a platform and network of pathologists to get this data within hours for training purposes. We think there will always be a very real need for human pathologists, but that the bread-and-butter work in pathology can be better handled by well-trained
and thoroughly-validated algorithms.
And yeah, the non-technical issues are just as important as the technical ones:
* There's very limited use of digital imagery in clinical pathology at all. Fortunately, that's not the case in research pathology, and the success we've had in that field has been moving clinical labs toward an investment in digital pathology.
* Reimbursement (in the US) will be an issue. There are only a few options for billing payers for pathology reads, and they aren't necessarily in lock-step with the potential future of the industry.
* Like I mentioned, this opens up a class of analysis that just isn't feasible for humans to perform. It's up to us to show the value of this type of analysis.
* The regulatory environment is a real thing. We aren't hiding from this, and are creating processes that allow us to build and iterate software like we'd like to, while still faithfully meeting our regulatory burden.
So far, we've found our approach to be viable, and we've had some really strong early results with our customers (and solid revenue!). So I'm pretty optimistic, for sure.
I believe these techniques will have a huge impact on how we do pathology as well as things like screening radiology, and that part of that will be by breaking down the silos such specialties work in, at least to a agree. I also think we have quite a way to go on the technical side but it is achievable (not to do everything people dream of, but to make significant improvements).
I also think it will take much, much longer than most people on the research side believe (hope?) to even approach standard of care. These systems are not built to move fast.
I'm glad to hear you are getting good/interesting results, and hope you are focusing more on validation and breadth of data acquisition than a lot of groups do :)
The lack of labeled data is definitely a challenge, as you call out. But a sizable chunk of what we do is power a platform and network of pathologists to get this data within hours for training purposes. We think there will always be a very real need for human pathologists, but that the bread-and-butter work in pathology can be better handled by well-trained and thoroughly-validated algorithms.
And yeah, the non-technical issues are just as important as the technical ones:
* There's very limited use of digital imagery in clinical pathology at all. Fortunately, that's not the case in research pathology, and the success we've had in that field has been moving clinical labs toward an investment in digital pathology.
* Reimbursement (in the US) will be an issue. There are only a few options for billing payers for pathology reads, and they aren't necessarily in lock-step with the potential future of the industry.
* Like I mentioned, this opens up a class of analysis that just isn't feasible for humans to perform. It's up to us to show the value of this type of analysis.
* The regulatory environment is a real thing. We aren't hiding from this, and are creating processes that allow us to build and iterate software like we'd like to, while still faithfully meeting our regulatory burden.
So far, we've found our approach to be viable, and we've had some really strong early results with our customers (and solid revenue!). So I'm pretty optimistic, for sure.