I dropped in today on the Personalized Medicine Meeting, an annual conference put together by Burrill & Co, a health care/technology consultancy. Amid all the hype over personalized medicine, I was glad to hear lots of attention paid to early stage interventions - meaning predictive and preventative strategies, rather than pharmacogenomics, which is the traditional face of personalized medicine. Indeed, there was a fairly manifest distinction drawn throughout the day between the pharmaceutical industry's approach to medicine and biotech's - and Steve Burrill set the tone when he called pharma's business model all but dead.
We'll see about that - but there were three telling stats that came up during the day. Together, they make quite the case for personalized medicine.
1) Half of all prescriptions don't work for the patients. Most drugs have an efficacy between 20 and 80 percent, averaging around 50 percent. Meaning that they only have their intended effect half the time. That might be awesome in baseball, but it's hardly reassuring in medicine.
2) Chemotherapy is effective - defined as remission - in just 5 to 10 percent of breast and colon cancer cases. This is likewise startling (the stat comes from Randall Scott of Genomic Health). And factor in the fact that chemo costs about $30,000 per patient per year, and there's a massively ineffecient treatment module out there.
3) Six weeks - that's how long it takes, give or take, for a physician to determine whether a given antidepressant is working for a patient. And given that only half of drugs work, that's a rather long time for a patient to go effectively without a treatment for their depression or mental illness. (This from Wolfgang Sadee, chair of the pharmacology department at Ohio State).
And one more observation that's not, technically, a statistic: The prognosis of a given patient is always a guess. Physicians know almost nothing about how a specific treatment will work for a specific patient. When a physician says a treatment works in 50 percent of cases (or 75 percent or 20 percent), they're always using population terms. There's no way to quantify how well those averages might or might not apply to any given patient (this observation comes from the Mayo Clinic's Franklyn Prendergast). It may be an obvious statement - but think about it from the patient's POV - there's no way medicine can accurately predict whether a treatment will work for them. That's, again, remarkable.
Together, these factors make a pretty damning case against current therapeutics. Basically, medicine today is a blunt instrument â€“ too blunt for a 21st century science.