What’s in a Name? A Lot, When It Comes to ‘Precision Medicine’

2/4/13Follow @xconomy

Personalized medicine was supposed to be the pot of gold at the end of the rainbow. It was going to be the payoff our society would see after investing in the Human Genome Project and so much other biomedical research. While most people on the street can’t say what it means, anybody can understand the standard definition on Wikipedia. It’s about “the customization of healthcare, with decisions and practices being tailored to the individual patient by use of genetic or other information.”

But just as the concept started gaining impressive momentum last year, a movement is afoot to redefine it under a new banner of “Precision Medicine.”

Normally, I’m not that interested in semantic debates like “Personalized vs. Precision Medicine,” and this one carries the whiff of one of those endless trivial quarrels. I first heard about “precision medicine” a few weeks ago when talking with a newly hired GE executive, Risa Stack. My initial reaction was that it sounded like a vague attempt at corporate rebranding that might be about distancing the company from the hype around “personalized medicine.” Even worse, I thought it might represent a weak backpedaling from the hard social and policy decisions that must underpin any effort to deliver real personalized medicine.

Turns out “precision medicine” has been gaining currency in academic, clinical, and corporate circles for a few months. While a few friends on Twitter have helpfully pointed out this term has been around for years, “precision medicine” started picking up steam in a report from the National Research Council in November. The committee that wrote the report was co-chaired by two of the most influential names in cancer research—UCSF Chancellor Susan Desmond-Hellmann and Charles Sawyers of Memorial Sloan-Kettering Cancer Center in New York.

UCSF Chancellor Susan Desmond-Hellmann

Consider some of the actions that have occurred since that report:

—One of America’s most influential corporations, GE, started using the “Precision Medicine” term itself. GE has also recently hired three Silicon Valley venture capitalists, including Stack and former Mohr Davidow partners Sue Siegel and Rowan Chapman, in the movement to help it identify the opportunities, especially in new molecular diagnostics, imaging, and analytics/software.

—Two of the country’s leading medical centers—Weill Cornell Medical College and New York Presbyterian Hospital—announced last week they are going to work together on a new Institute for Precision Medicine, which they described as “a translational medicine research hub that will use leading edge technology to create targeted treatments based on patients’ genetic profiles.”

—Desmond-Hellmann’s home institution of UCSF announced that it will hold a summit in May with a mission to “Drive the Precision Medicine Revolution.” UCSF said it aims to “harness the wealth of data available from the human genome and the subsequent wave of research into the molecular basis of disease and integrate it on both a personal and global level with information on environmental factors and patients’ electronic medical records.”

By this point, you’re probably wondering, how is any of this different from personalized medicine? There’s a fairly concise definition in the National Research Council report, which essentially argues that precision medicine is a broader, more inclusive term than “personalized.” Many people, myself included, have used the “personalized medicine” phrase in a broad sense to include important molecularly targeted cancer drugs, like Roche’s vemurafenib (Zelboraf) or Pfizer’s crizotinib (Xalkori), that are a whole lot more precise than old-fashioned chemo drugs. I’ve also used the term to describe powerful new kinds of molecular diagnostics that can guide treatment decisions, like Genomic Health’s Oncotype Dx, CardioDx’s Corus CAD, or Nodality’s Single Cell Network Profiling test.

What the “precision medicine” movement argues, correctly, is that these types of innovations allow for more precise diagnosis and treatment of patients at the molecular level.

Here’s what the NRC committee said about its choice of term:

“As used in this report, ‘Precision medicine’ refers to the tailoring of medical treatment to the individual characteristics of each patient. It does not literally mean the creation of drugs or medical devices that are unique to a patient, but rather the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease, in the biology and/or prognosis of those diseases they may develop, or in their response to a specific treatment. Preventive or therapeutic interventions can then be concentrated on those who will benefit, sparing expense and side effects for those who will not. Although the term ‘Personalized Medicine’ is also used to convey this meaning, that term is sometimes misinterpreted as implying that unique treatments can be designed for each individual. For this reason, the Committee thinks that the term ‘Precision Medicine’ is preferable to ‘Personalized Medicine.’”

What the committee doesn’t say in writing—but which many surely were thinking—is that the new term also provides a way to give this concept a fresh start. Leading biomedical researchers and companies have been talking up personalized medicine for a decade now, and there’s still not a very long list of successful products you could file under this header. Personalized medicine, with so much promise unfulfilled as of yet, has picked up a lot of negative baggage in research and clinical circles.

Last week, when I visited Stanford University and Caltech on reporting trips, the negativity toward the personalized medicine movement was striking. Three biomedical researchers shooke their heads at me when I said I had attended the Personalized Medicine World Conference earlier in the week in Mountain View, CA.

“I think [precision medicine] is fine,” says Stephen Friend, the president of Seattle-based Sage Bionetworks, a nonprofit building an open-source biological database for researchers and physicians. “The old term is not yet delivering as soon as hyped.”

Momentum for this renaming effort came from Stephen Galli, the chair of pathology at Stanford University, according to fellow NRC committee member Maynard Olson of the University of Washington. Olson, one of the leaders of the Human Genome Project, says he was quickly persuaded by Galli’s argument. The gist is that personalized medicine has largely been associated with single anecdotal success stories. Those kinds of advances are extremely valuable if they happen to a member of your family, and they can make for great experiments that generate new scientific hypotheses, like the work Mike Snyder has done at Stanford.

But “N of 1” experiments make a weak foundation for physicians who want their decisions to rest on medical evidence. Physicians are more likely to join the movement if they see a way to get more and more data on patients to help sharpen up their sometimes shaky attempts to diagnose disease. Precision, basically, is the opposite of ambiguity. Physicians are bound to listen closely to something that can help them out of the ambiguity zone. Think for a second, about “flu-like symptoms.” How valuable would it be for a physician if someone had a quick, cheap, super-accurate blood test that could say someone’s “flu-like symptoms” were actually from H5N1 “bird flu” or malaria?

“When (Galli) first brought up the idea, I think most committee members thought ‘precision medicine’ sounded odd, but he won everyone over quickly as we considered the suggestion,” Olson says. “The gist of the idea is to distance genomic medicine from any suggestion of a retreat from evidence-based to anecdotal medicine. If you think about it, nearly all high-profile claims of success in ‘personalized medicine’ have been n = 1 anecdotes. Medicine has been there—we do not want to go back.”

There are other arguments that personalized medicine has struggled with, particularly cost and data-sharing. Especially during a time of healthcare cost-control, it will cost way too much to get everybody’s genome, transcriptome, metabolome, proteome and other ‘omes socked away in electronic health records. Cost needs to keep coming down. And big medical institutions also need to figure out how to play in the same sandbox with biomedical researchers. Today, most physicians don’t have a clue of what to do with the precious information they might get from the genome of, say, a tumor sample. Even if they did know how to use it, they’d probably be afraid to share their samples and data with other physicians and researchers, because of patient privacy concerns and legal liability fears.

These are tough issues. They are social, economic, and political barriers not easily broken down by exponential technology progress.

Personally, I like the term “personalized medicine” and all of the long-term grandiosity it conveys. Precision medicine, to my ear, sounds more incremental, less inspiring. But if Galli and his fellow clinicians see value in the term “precision medicine,” and they recoil at some limited definition of “personalized medicine,” then maybe it’s time to let the clinicians have their way. The clinicians need to contribute samples, and data, that researchers can use, and the researchers need to send back the insights and data they get to the clinicians and drug companies. While egos may be wrapped up in personalized medicine, the movement will never coalesce without physicians and physician/scientists in leading roles. A switch in vocabulary is a pretty small sacrifice to make on the road to more custom-tailored healthcare.

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  • Paul Sonnier

    I still say Dr. Eric Topol has it right in saying “Individualized Medicine” is better than Personalized Medicine, which connotes Concierge Medicine. Precision Medicine seems like what medicine has always been improving in doing. Not exactly a term capturing how medicine is evolving to treat each individual.

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  • Phil Eidelberg

    Does “subpopulation” mean the same as “phenotype”?

    • Mike Thompson, MDPhD

      No. A subpopulation could be a genotype that does not have a phenotypic correlate.