The Pitfalls of the Traditional Model
For years, Western medicine has taken an imprecise approach to new drugs: Test new drugs on as large a group as possible in a clinical trial, and if enough of those participants benefit, make the drug available to the general public. Sure, this wide-cast net may not help everyone, goes the theory, but with such large numbers, it’s bound to catch a fair number. Plus, it appears efficient, as it deals with thousands of patients with a single trial and a single drug. However, medical professionals are beginning to remark on the flaws in this system.
Even drugs that pass rigorous clinical trials may help surprisingly few patients: the top ten highest-grossing drugs in the US only help between 1/4 and 1/25 of the people who take them. These disappointing figures are exacerbated by the fact that clinical trials disproportionately enlist white participants, whose responses to given drugs are not necessarily identical to other ethnicities’ responses. Trials also tend to focus heavily on chemical analyses to the point of ignoring genetic and environmental factors that play an important role in medication.
Moving Towards Personalized Medicine
Perhaps, it’s time to explore a “precision” approach. Generally, this model means taking into account more factors that affect individuals’ responsiveness to drugs. It may even involve ultra-personalized, one-person studies. In these, the participant would test out a drug, and be tracked in a detailed way over a long period of time, with attention given to genetic and environmental factors. The story wouldn’t end with studying a single person; the results of all these trials together would be aggregated to yield information that is predictive for members of the wider population. By using patterns found in the aggregate data, doctors may be able to more accurately predict how well a treatment will work for a given subset of the population.
Of course, there are significant barriers to the use of one-person studies, chief among them cost. Tailoring trials to individuals tends to cost more than running a broad, one-size-fits all study. Nonetheless, this new model seems slowly to be gaining traction. In January 2015, President Obama announced that he would seek $215 million for the Precision Medicine Initiative, which proposes to use patients’ specific genetic and physiological characteristics to better treat them. Of this, the FDA would receive $10 million to build personalized-medicine databases and to examine its regulatory processes for personalized treatments. Following suit, this year the state of California also unveiled a $3 million precision-medicine project to investigate personalized treatments and diagnoses. As time goes on, we may see a real paradigm shift in how doctors study and treat patients, to understand them as unique individuals whose data points reveal truths about the wider population, rather than the other way around.