The colon cancer drugs Erbitux and Vectibix, for instance, do not work for the 40 percent of patients whose tumors have a particular genetic mutation. The Food and Drug Administration held a meeting this month to discuss whether patients should be tested to narrow use of the drugs, which cost $8,000 to $10,000 a month.
To some extent this sort of thing is a gimme; intelligent & proactive patients already “help” their medical professionals by channeling them appropriately in terms of decisions because with the veritable tsunami of data no human can truly keep up. One aspect of personalized medicine is population level data. To give an example for myself, my doctor told me that I wasn’t overweight. Well, actually for my population (South Asian) it seems rather clear that heuristics based on BMI normed to European Americans underestimates the risks of conditions heightened at particular weight thresholds (e.g., Type II Diabetes). Combined with family information I’m always trying to keep my BMI on the low end of normal, because there’s normal for one population, and normal for another.
Personalized medicine takes it to the next level. The example above is an obvious one, but what about drug combinations where the differences are on the margins of effect? If you have risks for illnesses a sum of marginal effects is not trivial, but it is probably not realistic to assume that your personal physician will be aware of all these “moving parts.” Welcome to the world where everyone should have a basic familiar with probability and cost vs. benefit, at least if they want to get the maximum bang from the medicinal buck.