In this era of global political revolution, fueled by an ongoing communications technology revolution, there is a quiet but equally profound revolution afoot in health care. It's called, simply, personalized medicine.
Personalized medicine proposes the customization of health care, with decisions and practices being tailored to the individual patient with the use of his or her genetic information and other unique molecular data.
Personalized medicine promises to allow health care practitioners to provide effective medical treatments based on the specific characteristics of each patient. Importantly, this approach can limit or eliminate therapies that wouldn't provide benefit and reduce the trial and error that doctors often rely upon to identify the right drug at the right dose. (Think TV doc Gregory House.)
In addition to limiting damaging side effects in individuals who won't respond to a given treatment, costs to treat these patients can be greatly reduced.
While these promises are lofty, we already see encouraging progress.
More than a dozen current drugs suggest or require genetic or protein tests for patients to guide selection of the right drug and the right dose. For the blood thinning drug warfarin, with 2 million new prescriptions each year and about a 1 percent adverse reaction rate, it's been estimated that the genetic test to identify those patients who respond poorly could avert 17,000 strokes each year in the U.S. alone. That will reduce health care costs.
Personalized medicine seems a likely pathway to finding a 'cure' for our health care system, with the potential to provide both improved care and reduction in costs.
Barriers to realizing this promise are falling, especially with the rapid pace of developing technologies that facilitate personalized medicine. These developments are driven by two key goals: the first is to obtain the unique DNA sequence of each patient, the genome sequence. This sequence of 3 billion chemical 'nucleotides' comprises our genetic repertoire as well as our genetic susceptibility to many diseases.
The Human Genome Project, started in the 1980s by the National Institutes of Health, provided the first human genome 10 years ago, the result of decades of intensive research at sites around the world. The price tag for that effort was about $3.8 billion. The pace of technology development since the 1980s enabling large scale genome sequencing exceeds that even of computer chips. The one-day, $1,000 human genome sequence is expected this year with a recently unveiled technology that costs about one-third of other state-of-the-art sequencers.
A second goal for personalized medicine is to include each patient's genome sequence in an electronic medical record that also includes family and patient medical histories. About half of all Americans already benefit from an EMR. That number is rapidly increasing.
Of course, it isn't enough to simply have the electronic data. Innovative ways to evaluate and mine genome data for disease associations and sequences that are relevant for diagnostic and prognostic uses are needed. Intensive research to bring these data analysis processes to maturity is supported by the NIH and other federal and private granting agencies. Countless businesses are providing services in this space.
These technological developments provide a pretty impressive upside beyond their potential benefits to individual patients. The Human Genome Project provides a notable example: A report from the independent Battelle Memorial Institute last year evaluated the economic impact of this $3.8 billion government project.
In 2010 alone, long after federal funding for the project ended, 310,000 jobs directly attributable to the project were supported in the public and private sectors. The return on that investment was calculated at 14,000 percent during the course of 23 years.
Federal tax revenues attributable to the results of the genome project were $48.9 billion, a 12-fold return on the Fed's NIH investment. State tax revenues of nearly $30 billion are attributable to the project. Ask an investment banker for that sort of rate of return and see how long it takes for the laughter to end. Even venture capitalists don't expect those kinds of returns on their risky, high-return potential investments.
This basic research, a land-on-the-moon project that many thought impossible when launched, has paid huge dividends for the economy and for new medical breakthroughs.
To implement personalized medicine, however, some barriers remain. An understanding of which patients will and which won't respond to a new drug therapy isn't factored into traditional pharmaceutical development approaches. The model for drug companies has been to create drugs that will be used by the largest populations of patients, not customized therapeutics that target only a small percentage of the patient population.
The industry is adapting, but the dollars might not make sense. It now costs nearly $1 billion to get a new drug approved over about a 10-year process. That isn't tenable if the market for the drug is a few million dollars a year or less. Hundreds of millions are needed solely for required testing of safety and efficacy in humans. Efficiencies and new processes will be required.
In addition, as a society we should consider accepting more risk in treating disease. This might include limiting liability for drug companies that act in good faith to bring new drugs to market, and limiting malpractice claims against well-intending practitioners prescribing cutting-edge drugs and therapies.
Although the Genomic Information Non-discrimination Act (GINA) that bars insurance and employment discrimination based on genomic information was enacted in 2008, many citizens remain concerned that their genomic information could be used against them in seeking employment or medical insurance. The larger issue is when such information can be shared and with whom.
The application of genomic information to personalized medicine can only develop if larger numbers of patients are included in the data analysis and mining studies mentioned above. Can we agree that this information may be shared freely for research purposes so long as reasonable efforts are taken to ensure that the data doesn't identify an individual? We are willing to make our personal financial information available electronically and to share that information with companies via e-commerce. Are we less willing to make genomic information available?
Another barrier to adoption of personalized medicine stems from the underlying research studies themselves. Typical research experiments that gather genomic information don't meet clinical standards for accuracy and quality control. The results aren't legally permissible to use for clinical decision-making, or to advise patients.
Should all genomic research in humans be held to clinical -- and much more expensive --standards? That will surely slow the pace of research and raise costs. Alternatively, can we agree that research results be made available to patients with the warning that the data may not be accurate to 'clinical standards' and an explanation of what that means? Are patients able to understand these intricacies?
Many of the issues surrounding the development and popularization of personalized medicine may ultimately be decided by the market. A growing segment of the population is insisting that they receive their own health and genomic data to use as they wish. With the personal genome sequence now available in the private marketplace, and moving within reach of an increasing number of personal budgets, perhaps sharing this information will soon be commonplace. Although this data is terrifically complex, given the previously mentioned 3 billion nucleotides, tools to enable do-it-yourself analyses of these data won't be far behind.
If these barriers are overcome and the promise of personalized medicine is realized, we may see an upside that dwarfs the economic benefits described above that are attributed to the federally funded Human Genome Project.
With directed research, increased clinical use of personal genomic and other high-volume health data, and specific policies that require fair practices in utilizing these data for all citizens, we may be celebrating a thriving and competitive health industry, robust new therapies for the most devastating diseases, and dramatic reductions in disease rates, instead of worrying about the soaring costs of health care.
This article was first published in the Journal of Business, Spokane, Wash.