More on pharmacogenomics from the Personalized Medicine Meeting at UCSF
In the opening panel this am, David Parkinson from Nodality offered a choice: Put yourself in a pharmaceutical company’s shoes: Would you rather have a drug that’s 10% effective for 100,000 or 100% effective for 10,000?
It’s a trick question. Turns out Parkinson is describing the same drug – Gleevec. When your talking about using Gleevec to treat leukemia, it’s effective in just 10 percent of patients. But use Gleevec to treat Chronic Myeloid Leukemia (CML), and you suddenly have something that’s 100 percent effective.
The difference, Parkinson notes, is that Gleevec works in CML by blocking a tumor protein caused by the so-called Philadelphia chromosome, a chromosomal abnormality. Approved by the FDA in 2001, Gleevec represents a huge shift in cancer treatment - instead of using blunt instruments like chemotherapy or bone marrow transplants, which caused broad physiological effects, physicians now can offer a precise treatment that goes after the cancer itself. It is, in other words, the sort of drug we expect we’ll be using all the time, once personalized medicine flourishes.
Gleevec is a lesson in how pharmacogenomics isn’t just going to involve creating new drug molecules; it will also require ew tools applied to old drugs, tools that can separate signal from noise and turn failures into success. In pharma, they call this “drug rescue” – finding drugs that may’ve been shelved for side-effect or efficacy reasons, but through better targeting could be revived. Again, it hearkens to my notion of dark data – the stuff that’s been filed for whatever reasons but now, in new context, might have new value.
In some ways, this sounds totally easy: Drug companies just have to start leveraging their back catalog, and start targeting the niche. In other words, this is simply the arrival of the long tail model to pharma (I’ve been waiting for this for a couple years, having spoken often to my boss, Chris Anderson about how pharma was a looming non-entertainment industry example of an indusry ripe for long tail economics). But it’s been slow to happen - or at least seemingly so, from my outsider perspective. Good to hear, as in this morning’s panel, that the idea is starting to catch on. As panel member Andy Williams from Pfizer acknowledged: The old blockbuster model is changing.