Harry Glorikian Senior Executive, Board Director, Consultant, and Author
This emerging field could overcome the hurdles that stood in the way of a personalized medicine revolution.
Emerging technologies, big data, and increased pressure to contain health costs are creating a major opportunity for precision medicine. Diagnostic makers still face high hurdles to commercialization, but through better strategic planning and innovative collaboration they can embrace this opportunity and help make precision medicine a key tool in the push for more efficient healthcare delivery. Precision medicine can also become a key differentiator in an increasingly cost-conscious and competitive healthcare delivery landscape.
Worldwide, health costs are expected to reach $10 trillion by 2020.1 In almost a dozen countries, health costs now consume about 10% or more of GDP. In the U.S. that figure is almost 18%. Health costs are also rising much faster than income in many countries. This is not sustainable, and we are already seeing big shifts, particularly in the U.S., where costs are fueling a new “triple aim” of better health and patient experiences at lower cost.2 Under new payment systems and plans providers will be taking on a lot more economic risk, and patients will be paying more out of their own pockets.
As the focus shifts to cost containment, it will create new opportunity for the emerging field of precision medicine—the science of tailoring treatments to specific patient characteristics. Thanks to the sequencing of the human genome, multiple technological advances, and the rise in electronic medical records, we are finally reaching a point where we can indeed better define patient subgroups and match them to optimal therapies.
To many, the field of personalized medicine has been a disappointment. The U.S. FDA has approved just 18 companion diagnostic tests so far,3 and the vast majority of these tests help guide prescribing of targeted cancer drugs. But precision medicine, with its new emphasis on a broader range of data and better new tools, should overcome many of the hurdles that stood in the way of a personalized medicine revolution.
The pioneers in this field have faced many obstacles. Even the specialists supposed to use them often poorly understand new genomics-based products. They can be difficult to incorporate into standard workflows and are often not adequately validated. These products typically provide much lower profit margins than therapeutics or devices, but it can still require hundreds of millions of dollars to develop a single test. In addition, the current reimbursement system makes it difficult to obtain prices that reflect a test’s true value or its development cost, particularly if it employs expensive new technology.
Another problem has been the overall lack of incentives for cost-effectiveness in the healthcare system. U.S. consumers have long been blind to costs and payers have had difficulty restricting access even to ineffective or duplicative treatments. Consumers have valued freedom of choice above all else and used to be inured to costs. Physicians could determine if drugs worked based on trial and error. There was no good financial reason to do otherwise. Even ineffective treatments could become top sellers.
The insurance industry has also been resistant. It is also slow to reimburse diagnostics makers for high-value products. It’s considered standard, for example, to charge over $100,000 for a cancer therapeutic, but many patients still don’t see the same value-proposition in a test that can determine which women are at disproportionate risk of developing breast cancer (i.e., Myriad’s BRACAnalysis test). They expect diagnostics to be cheap, even if they are life saving.
The pharmaceutical industry has also strongly favored one-size-fits-all style prescribing. Tests that segment markets aren’t attractive unless they essentially rescue a drug. That is, the drug would not have been approved without a companion test. And big pharma is one of the few industries with the money to fuel new biomedical fields.
Big Data Meets DNA
Oncology is the one area where targeted treatment has been hugely successful, because tumors are driven by genetic mutations. One of the first home runs was Genentech’s breast cancer treatment Herceptin. That drug and its companion diagnostic test were approved simultaneously in 1998, and today the drug still brings in over $1 billion a year. The test measures levels of HER2, a protein that is overexpressed in some tumors. Several other top-selling targeted cancer drugs followed.4
But in other fields, the fruits of genomics were not as obvious. Since 2005 and today, about 1,500 genetic association studies have been published.5 These have found hundreds of variations linked to a wide variety of conditions, including diabetes, Crohn’s disease, and heart disease. But most of these variations contribute only slightly to the risk of developing a particular disease.6 It’s been estimated that over $100 million has spent looking for such variations, with few clearly important targets unearthed so far.
But many more sophisticated approaches to unearthing biomarkers are emerging. This is fueled not just by a greater understanding of human biology and its complexity, but by next-generation tools that enable much more precise measurements of all types of biological markers including DNA, RNA, and proteins. For example, point errors in genome sequences have dropped from 1 in 100,000 to 1 in 10 million.7
Over the last few years, gene sequencing has become orders of magnitude faster and less expensive. Hospital systems are investing millions of dollars to create genomic medicine units. Mount Sinai alone spent $100 million on such a division. Currently, those units mainly address oncology or hard-to-diagnose diseases. But these hospitals are making the investment in part because they recognize that genomics’ hour is approaching and it will be much more integrated into medicine overall.
Researchers are also looking beyond genomic data. The Center for Assessment Technology and Continuous Health (CATCH), aims to enable “a new understanding of wellness and disease through systemically identifying and annotating patient phenotypes.” They will “improve measurement of patient phenotypes with novel technologies and devices.” By phenotype, CATCH researchers mean a much wider range of data then we previously even knew existed. They will be measuring cellular, behavioral, and other common phenotypes along with things such as the patient’s microbiome, sensor readings from respiratory cilia, and immune cell genotypes.
The amount of clinical data available is also increasing and providing new insights. Archimedes, for example, is a Kaiser Permanente spinoff that uses a mathematical model to analyze healthcare questions. One of their simulations predicted that by prescribing two generic, low-cost drugs to lower cholesterol and blood pressure, Kaiser could prevent many heart attacks and strokes among diabetes and cardiac patients.
Further, pharmaceutical companies are starting to realize that they can greatly accelerate clinical trials by using biomarkers. In 2013 GlaxoSmithKline won FDA approval for Tafinlar for melanoma. That approval was based on a trial of just 250 patients. Because the drug’s mechanism—targeting BRAF V600E—had been established, they were able to enroll many more patients (three times as many) in the Tafinlar arm, versus the control arm. As a result, the company was able to demonstrate the drug’s efficacy more quickly than is usual.8
The potential for new products from this combination of new data and next-generation technologies is immense.
Tests to guide prescribing of cancer drugs alone are a major opportunity. The Pharmaceutical Research and Manufacturers of America (PhRMA) reported that more than 900 medicines and vaccines where in development against cancer by 2012.9 The overall market for cancer treatments reached nearly $36 billion in the U.S. alone in 2012.10 Eleven of the twelve cancer drugs approved by the FDA last year alone cost more than $100,000 per year in the U.S., and some cost more than $300,000.11 Many of these drugs work only in a subset of patients, but biomarkers of response are not yet available for all of them.
Tests that can be used to predict response to such drugs will become more lucrative in the new cost-conscious healthcare environment.
A Rising Opportunity
There should be steady growth in precision medicine over the next few years, including many new creative collaborations, particularly between academic medical centers and diagnostic developers. Investors will also begin to recognize the unique value proposition that precision medicine offers in this new age of healthcare cost constraints. Rapid and extreme innovation in the U.S. will spread around the globe, leading, finally, to the maturation of the field of personalized or precision medicine.
To succeed in this new rapidly changing environment, however, precision medicine test makers will need to optimize their strategy. That means picking the right targets, developing them along the appropriate path, providing substantive evidence of their value and cost-effectiveness, and determining exactly when, where, and how the tests should be implemented in the healthcare system workflow.
1 Analysis by Scientia Advisors, based on data from Datamonitor, SG Gowen Therapeutics Outlook 2007, Frost & Sullivan, Bain and Company and the Center for Medicare and Medicaid Services.