Precision medicine is not really new. Doctors have always wanted to deliver increasingly personalized care. The current term describes a goal of delivering the right treatment to the right patient at the right time, based on the patient’s medical history, genome sequence, and even on information, gathered from wearable devices, about lifestyle, behaviors, or environmental exposures: healthcare delivered in an empiric way. When deployed at scale, this would, for example, allow doctors to compare their patient’s symptoms to the histories of similar patients who have been successfully treated in the past. Treatments can thus be tailored to particular subpopulations of patients. To get a sense of the promise of precision medicine—tantalizingly miraculous at times, yet still far from effective implementation—the best example may be cancer.
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The development of resistance is less a reflection of the efficacy of targeted therapeutics than of the cancer’s ability to evolve. Cancer cells proliferate through division, and mutate rapidly. If a single cancer cell among millions happens to be resistant to a particular therapy, that cell and its progeny eventually become dominant drivers of the patient’s disease.
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The reality is that for most patients, advanced lung cancer remains fatal. Leading-edge therapies such as targeted medicine have helped only a subset of the population. “Cancer medicine is the furthest ahead” in the use of genomic analysis to guide therapy, [Deborah] Schrag says, “but it still has a long way to go.”
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