Consider hypertension. It is one of the most prevalent diseases in America, and the single most common reason that people visit their doctors. In spite of that, less than half of people taking drugs to treat they hypertension actually have their blood pressure under control. Why is that? Well, partly because people don't change their lifestyles to combat the disease, but also because there is no way to identify which patient will respond to which drug. Hypertension is extremely heterogeneous, and it stands to reason that different subsets will respond to different medicines. For now, though, there is neither a way to easily assign a person to a subset of hypertensions, nor a mapping for which drug best treats which subtype.

But let's back up for a second. Why is hypertension so common? What leads to a person developing hypertension? For now the best predictors of hypertension are age (the older you are, the higher your risk of high blood pressure) and family history (if your relatives have high blood pressure, you're more likely to, also). But that casts a very wide net, and it's difficult to identify the people who would most benefit from early interventions to prevent them from developing hypertension. One potential application of personalized medicine is being able to combine all of the information available to make better predictions about who is really at risk of developing hypertension

Finding and targeting those at risk, though, will not stop everyone from getting hypertension. And the next potential application of personalized medicine is determining who will respond to which drug. This type of prediction is currently not even considered as part of treating a patient, rather the physician makes an educated guess about what drug may work and then monitors to see if the dosage needs to be increased or if another drug needs to be tried. But by identifying subsets of hypertensives and identifying which drugs work best in a subset, hypertension treatment will not only be more effective, there will likely be fewer adverse reactions and less wasted money.

Now that we know what personalized medicine is, the next three posts will cover the scientific, policy, and ethical issues that face the field. I don't intend to lay out much in the way of answers, and I also doubt that my listing of problems will be exhaustive. Rather, I want to convey a sense of the breadth of the issues that I'll be discussing in more depth over the next few months.