Talked to a friend today who is trying to get a biotech startup off the ground. The company has an interesting product that could provide quick genetic information on cancer. What is really missing now in the world of molecular diagnostics is a way to rapidly assess disease status. By rapid, I mean less than a day and ideally within the span of an office visit. There has always been a big push for diagnosis from a molecular standpoint because that mode of diagnosis as the potential to be the most rapid, sensitive, etc. and (hopefully) least invasive for the patient. You can see the initial stages of the later in the growing debate over merger of radiology and pathology on the Lab Soft News blog. What is missing now to a large extent is a platform (and possibly a mindset) to monitor the response of a cancer to therapy and give guidance for therapy selection. There are a few instances of this happening (CML and gleevec come to mind), but there needs to be more.
Anyway, back to 4/C exam prep. The topic of frailty models just cruised past. The ability to adjust survival based on covariates is a powerful modeling approach. It reminds me of sliding mode control theory that I learned as a engineer...adjust the dynamics to fit the current model. In actuarial math, I have already studied/learned how to correct for inflation and how to splice models together for simple cases, but the generation of really finely-grained models seems like the next logical step. Is what molecular diagnostics really has in store for the actuarial world? Chris Anderson's excellent book The Long Tail speaks to this and clearly shows the growth/exposure of finely-grained consumerism via the web and other modern technologies. I really wonder with all of the data that these technologies can generate, are the models (and modelers) there and ready for the integration? From a recent article in CAP Today, It looks like at least one molecular lab is talking to/working with insurance companies.Should be fun...back to 4/C.
