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Friday’s WSJ features a brutally – I mean brutally — frank article about the dismal state of biotech financing. There are few revelations (certainly not for those readers of this column who I know follow the space closely), and unfortunately, few patches of sunlight. This clip from Play It Again, Sam pretty much captures the tone.
The crisis in financing is having a chilling effect on biomedical innovation. As discussed in my last column, the main problem in our industry is that the sheer cost of drug development has become almost prohibitively expensive, effectively pricing almost everyone but the largest companies out of the market.
While my Forbes colleague Matt Herper suggests this could represent a disruptive opportunity for ultra-lean start-ups, I don’t think this is true in practice. For a start-up or small company, figuring out how to run trials in an extremely capital-efficient way isn’t a competitive advantage, it’s table stakes – it’s what gives you a shot on goal, or maybe two. Given the intrinsically high likelihood of failure, long-term survival requires the ability to advance a portfolio of products through clinical development, something that typically only fairly large companies can afford to do.
The broader challenge is how can you achieve disruptive innovation in a highly-regulated industry?
One approach is to avoid regulation – this is one of the reasons so many digital health companies are pursuing consumer health – they hope to avoid the regulatory morass that has so dampened progress in the medical products industry. As I’ve noted before, it will be interesting to see how this works out – I’ve see a lot of cutsie apps out there, but not much that seems likely to deliver measurable improvements in patient health (i.e. improvements that would be meet the sort of standards both demanded by drug regulators and expected by physicians).
“The sheer cost of drug development has become almost prohibitively expensive, effectively pricing almost everyone but the largest companies out of the market.” — David Shaywitz
I’d further argue there’s a huge need to ensure that emerging digital health technologies are rigorously and credibly evaluated, and iteratively improved by practicing providers (disclosure: achieving this is one of the major goals of the Center for Assessment Technology and Continuous Health [CATCH], a new Boston-based non-profit academic institute that I’m helping to put together, an effort led by MGH Chief of Medicine Dennis Ausiello, and involving several colleagues from MGH).
In the land of digital health, I also worry that there are a lot of developers who I don’t think really understand the gravitas of illness and disease. For many of these folks, wellness is best envisioned as a fun and entertaining diversion, one that should be pursued with enthusiasm and characterized by delight. Yet this whole idea of “gamefication” – while obviously both popular and fundable – doesn’t really connect with so much of what I’ve seen as a physician (and you don’t have to be a physician to understand the distinction – clearly, Jamie Heywood is an it-getter).
Perhaps when you’re 22, wellness is a game, but for most of the patients I recall in internal medicine, it really was anything but; patients have very serious, often existential concerns about their health, and about their ability to work and to provide. What these patients want, expect, and deserve is serious engagement – and not some dipshit app.
As I discussed in my last piece, two other ways of dealing with the current drug development crisis are to reduce the regulatory burden (perhaps via progressive approvals; won’t re-hash here) and to do better science (incidentally, another major ambition of CATCH).
I’ve talked extensively in this space about the need for better science, and what it comes down to is that if we had a better understanding of disease, we could make better drugs. This would reduce the clinical development costs in two major ways: first, by attacking the underlying pathology more successfully (statistically, achieving a larger effect size), you wouldn’t need to study as many patients to demonstrate you’re having an important impact. Second, by better understanding which patients are likely to benefit from your drug, you can better focus your trials; by proactively removing non-responders from your study, you avoid the associated statistical dilution, again achieving a larger effect size.
Most small companies that have succeeded have done so through a combination of the above (a drug that manifestly works demonstrated clearly in optimally-selected patients); orphan drugs are perhaps an extreme example of this approach; Pharmasset’s recent high-profile success is arguably another good example – they were able to demonstrate eye-popping results in early clinical studies, presumably reflecting both the intrinsic properties of their compound and the population they elected to test it in initially (fairly homogenous patients with hepatitis C virus genotypes especially likely to respond).
Success in the early life-science space can be achieved and must be achieved. I’ve huge respect for the entrepreneurs and VC’s who’ve elected not to bail out of the early life-science space, and instead have elected to stay and fight. There’s clearly a tremendous need for further innovation, and great – and well-deserved — rewards for those who are able to figure this out.
David Shaywitz is an AEI adjunct scholar.
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