In his January 20, 2015 State of the Union Address, Barack Obama announced that he was “launching a new Precision Medicine Initiative….” In a more detailed conference on the 30th, he described precision medicine as “delivering the right treatments, at the right time, every time to the right person.” Sounds good, right?
But what does that mean exactly? The following definition is from the White House Office of Science and Technology Policy: Precision medicine is medicine “that takes into account individual differences in people’s genes, environments, and lifestyles, making it possible to design highly effective, targeted treatments.” Many people trace the term itself to the 2008 book, The Innovator’s Prescription, by Clayton Christensen of the Harvard Business School. His definition is medicine in which diagnostics are good enough to allow “therapy that is predictably effective for each patient.”
The term “precision medicine” first appeared in Google Trends and in PubMed in 2011. Searches for a related term, “personalized medicine” appeared in 2005. Only in the past week (no doubt due to the State of the Union Address) did searches for precision medicine overtake searches for personalized medicine. Also note that 70% of PubMed hits for precision medicine were published in 2014 or later. What caused the shift to happen in 2011? That was the year of the National Research Council (NRC) report “Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease.” This report favors the new term because it is “less likely to be misinterpreted as meaning that each patient will be treated differently.”
President Obama’s initiative will request $130 million for the National Institutes of Health, $70 million for the National Cancer Institute, $10 million for the FDA, and $5 million for Office of the National Coordinator for Health Information Technology. This $130 million will go toward a “national research cohort of a million or more volunteers,” who will contribute “medical records; profiles of the patient’s genes, metabolites (chemical makeup), and microorganisms in and on the body; environmental and lifestyle data; patient-generated information; and personal device and sensor data.” This type of cohort is mentioned in the NRC report, which terms it the Million American Genomes Initiative (MAGI). It is worth noting that other countries are already working on building similar cohorts, and so is the U.S. in the form of the Million Veteran Program.
Just how hard is it to find these individual differences in people’s genes? You may have heard that any two people are 99.9% genetically similar to each other. If this is the case, it seems like we’re all so similar that this should be easy. But the genome is a big place – even 0.1% difference means that from one person to the next, there are 3 million genetic variants. If you compare one person with diabetes to a person without diabetes, there are many variants that have nothing to do with diabetes. In other words, you can’t separate the signal from the noise without very large numbers of people to study. This is why the Million Veteran Program exists, and why the President is proposing a million Americans
initiative. The NRC report hints that precision medicine has not realized its full potential because these very large sets of data have not been available.
If that sounds difficult, don’t forget that precision medicine also wants to measure people’s environments. Environment and genetics both contribute to disease, but environment can be even harder to measure.
It takes a large cohort to find genes that contribute to common diseases. Now precision medicine sounds hard, right? So, is there any way to do precision medicine now, before these million person cohorts are assembled? If someone develops cancer, the differences between the person and their cancer are not three million— they are only between 1 and 400. So while it’s difficult to compare one person to another person, it’s somewhat easier to compare a person to their cancer cells, which are different from the rest of the cells in their body. Oncology seems to hold the largest potential for precision medicine right now because of this.
But we still run into a smaller version of the same problem here: some of these variants have nothing to do with causing the cancer. Some are “drivers” and some are “passengers.” We want to find the drivers, because if we give a drug that stops the driver, we can stop the speeding car, so to speak. Researchers have already identified driver mutations responsible for about half of lung cancers, for example, but for the other half the drivers are simply unknown. There are probably many of them, hence the $70 million the President is requesting.
There is a second problem that we haven’t mentioned yet: these several hundred driver mutations mean that genetically, lung cancer is really hundreds of diseases (or even millions, if several drivers are present). If only 1% of patients with lung cancer have mutation A, then 10,000 lung cancer patients may need to be screened to run a trial of drug A. Patients all over the country would need to be screened, and it would be burdensome for them to travel to a central study site. Furthermore, one drug company will not want to invest in screening 10,000 patients all by itself.
Luckily there is also a hypothetically easier solution to this problem: all patients with lung cancer could be screened in a systematic way, and the trial drug could travel to the patients rather than vice versa. Furthermore, drug manufacturers could collaborate on the genetic screening. In the end, suppose 10,000 patients nationwide with lung cancer are screened. 100 have driver A, 100 have driver B, and so on up to driver J, perhaps. All those with driver A are randomized to usual treatment or to precision medicine treatment from drug maker A. The 100 with driver B are randomized too, using drug maker B’s drug. Thus, it is really many studies in one, with different drug companies in the same study (which has rarely been done before). The NRC report calls this “pre-competitive collaboration.”
The bottom line? Precision medicine— the right treatments, at the right time, to the right person— sounds good. It will be difficult to assemble very large sets of data on people’s genes and environment, but this is necessary to realize the full potential of precision medicine. And precision medicine for oncology offers perhaps the largest potential today.
During the month of February, leading Experts are poised to hash out the debate online in the NEJM Group Open Forum. Follow along!
Andy Zimolzak, MD, MMSc, is a clinical informatician at the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), where he works on the Precision Oncology Program and the Point of Care Trial program. He is also a practicing internal medicine physician. He completed his MD at Washington University in St. Louis and his internal medicine residency at Saint Louis University. He came to Boston in 2011, where he earned a master's in medical informatics at Harvard / Boston Children's Hospital, studying predictive modeling of medication adherence based on insurance company prescription claims data.Louis Fiore, MD, MPH, is the executive director of the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) and professor of medicine and epidemiology at Boston University. In this role, he oversees the Precision Oncology Program as well as the operations of numerous other clinical trials, observational studies, computational resources, and biobanking efforts. He earned his MD at SUNY Upstate Medical University and his MPH at Harvard School of Public Health. He is board certified in internal medicine, oncology, and hematology.
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