Many of us have adapted what HIT has to offer (it actually was forced down our throats), and now we have severe GERD. (gastrointestinal esophageal reflux disorder). This frequently occurs in those who are obese and who overeat.
I think that is where we are now. Will we be able to keep it down, or vomit IT back to where it came from. I think both may happen.
“When Bio Meets Computer Science.” As expected, it was articulate, thoughtful, and relatively grounded. Nevertheless, I realized at the end I didn’t entirely agree with all the assertions, and I thought it might be worth some discussion.
A16z’s high level thesis – with which I strongly agree– is that there are profound opportunities at the confluence of biology and technology, especially as more undergraduates emerge who are trained in both (apparently the majority of Stanford students take at least one computer course, even though most don’t wind up in computer science or engineering). It’s also true that the new opportunities aren’t simply being able to do existing activities faster or at larger scale – rather, it’s the opportunity to ask and pursue questions you couldn’t have even conceptualized in an earlier era.
The a16z view of this space, as a whole, can be divided into three parts:
(1) Digital therapeutics. Many healthcare problems are behavioral, and digital health companies might address these challenges more effectively, and less expensively, than drug companies. Representative (and portfolio) company:Omada Health (my 2012 post on the company is here; our recent Tech Tonicsinterview with founder Sean Duffy is here)
(2) Cloud Biology. The arrival of highly automated labs will revolutionize biology startups in the same way the arrival of cloud computing revolutionized technology startups. These lab facilities will enable biotech startups to do the experiments they need with greater reliability and without the capex spend; scalable research facilities will be available when needed, and you only pay for what you use (again, like cloud computing). Representative companies in this space: Emerald Cloud Labs; Transcriptic.
(3) Computational Medicine. Physicians and researchers must contend with an overwhelming and ever-increasing amount of data. For instance, a key challenge in oncology is matching many potential cancer drugs to the exact characteristics of the tumor in question. These sorts of problems can be solved with software, which is continuing to get better and cheaper. Representative companies: Foundation Medicine cited as company in the oncology diagnostics space.
Collectively, a16z says, these three trends will lead to an “explosion” of experimental biology and digital health startups, offering the opportunity to develop clinically impactful products for a fraction of the cost of a traditional life science startup, and representing a pointed contrast to the ever-increasing cost of traditional biotech drug development, which seems to follow so-called Eroom’s Law (Moore’s Law in reverse).
First, I worry a16z profoundly underestimates the difficulty of developing a behavioral intervention that’s actually clinically effective, and also underestimates the cost of rigorously proving this (and payors are going to demand credible data before agreeing to cover the cost of an intervention such as Omada’s or Propeller Health’s, which both, by design, target a relatively large number of covered lives). (Addendum: A thoughtful response from Omada notes that they “take on meaningful financial risk,” collecting a “significant portion” of their revenue from customers “only as individual patients achieve clinically-meaningful milestones” — an approach they acknowledge makes for a “nerve-wracking business model.”)
Is Andreessen-Horowitz Right That Software's Poised To Eat Healthcare? - Forbes
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