Precision Medicine’s Coming Surge

New Opportunities In the Age of Precision Medicine

Emerging technologies and increased pressure to contain health costs are creating greater opportunity for precision medicine. Unsustainable health costs are fueling a new “triple aim” of better health and patient experiences at lower cost.[i] Precision medicine, in particular, could become a key tool to contain costs by better matching patients to treatments = better outcomes.

Worldwide, health costs are expected to reach $10 trillion by 2020. [II] In almost a dozen countries, health costs now consume about 10% or more of GDP. In the US that figure is almost 18%. Health costs have been rising much faster than income in many countries.

This trajectory is unsustainable.

While healthcare has enjoyed a tremendous boom over the last couple decades, we’re now in the middle of a shake up. This could be the perfect opportunity for personalized medicine to finally emerge, albeit in a slightly altered form and under the new heading of “precision” medicine. The field has been struggling for decades, despite a loyal following and some high profile successes. Proponents have long argued it could improve quality and lower the cost of healthcare by reducing the use of ineffective treatments. The vision is of an explosion in genomics-related diagnostics that would help physicians match drugs to “the right” patient.

Just a handful of companion diagnostic tests has been approved by the US FDA so far, [III]and the vast majority of these tests help guide prescribing of targeted cancer drugs. Why has progress been so slow, what is changing and why will precision medicine finally succeed?

Radical Market Shifts

The pioneers in this field have faced many obstacles. New genomics-based products are often poorly understood even by the specialists who are supposed to use them. 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 take $100s of millions 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 employ’s new technology.

Another major hurdle to personalized medicine has been the overall lack of incentives for cost-effectiveness in the healthcare system. For decades, US consumers have been largely blind to costs and payers have had difficulty restricting access even to ineffective or duplicative treatments. Consumers valued freedom of choice above all else and were 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 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.

The recent push for value-based healthcare, however, creates powerful new incentives to improve efficiency. New payment systems are being adopted that reward doctors for quality rather than quantity and shift more risk from payers onto providers.

Bundled payments, for example, provide a single pre-determined lump sum for all the services related to one medical episode. Pay-for-performance initiatives provide financial rewards for efficiency and quality care. In some of these settings, doctors have to be efficient to be profitable. In others, they will reap shared savings if they can cut costs. This is the beginning of the six-sigmazation of healthcare.

It is not clear how quickly these initiatives will be widely implemented, or whether they will be successful. It’s estimated that 90% of healthcare in the US is still currently paid for based on fee-for-service.[iv]

But the cost of employer-based health insurance has shot up by 80% in this country since 2003.[v] By 2033, the cost of a family health insurance premium in the US is expected to equal the median household income.[vi] In the US, out-of-pocket costs for consumers are also increasing at a rapid pace, leading to more unpaid medical bills and greater hospital debt.[vii] Towns, cities, states and even the federal government are struggling to find painless ways to reduce health costs.

This should lead to steadily increasing competition between providers for already stretched health spending. It should also fuel a new emphasis on the dual goal of cost-effectiveness and better outcomes.

Other important changes ahead include the growth in integrated delivery systems, as big hospitals acquire their smaller competitors, independent physician practices, and other facilities such as nursing homes or outpatient clinics. More than 100 hospital acquisitions occurred last year alone, compared to 50 or 60 per year from 2005 to 2009.[viii] These new systems will have a unique opportunity to start delivering coordinated care and to improve the health of local populations. (For more, please see: Healthcare Reboot)

The explosion in big data and the emergence of many new technologies, particularly in digital health, are also creating whole new fields, such as remote monitoring and telehealth. These advances will spur the practice of data-driven healthcare: Treatment standards based on big data, including that from clinical studies and medical records. The hospital systems that are most efficient will be most competitive. The data will tell them how to gain that efficiency.

Increasingly, doctors will use data to determine which are the most effective treatments for specific patients. Is chemotherapy at the end of life useless in some patients, if so, why subject them to it? Hospitals will expect physicians to practice according to standards of care. Their performance will be tracked and those who don’t follow the standards may be penalized.

Patients, meanwhile, will be more quickly routed to the most appropriate care setting and treatment. Does that patient really need to be in the hospital? Or would they do just as well in a nursing home, which is much less expensive. If they want higher cost treatment that is not deemed more effective, they may have to pay for it themselves. Reams of data will also be reported to payers. Based on that data, providers will be penalized or reap shared savings or quality bonuses.

As noted earlier, it’s not just in the US where costs are becoming a growing consideration. They are rising unsustainably around the globe, [ix],[x]squeezing a growing number of government budgets. This creates a new worldwide opportunity for products that can cut health costs without compromising quality of care. (For more, please see: Heathcare Reboot 2)

The US has more innovative companies than anywhere else in the world. Firms that can offer a great value proposition will be better positioned for this growing value-based market.

Big Data Meets DNA

The idea of personalized medicine grew out of the genomic revolution. Researchers had long known that genes affected response to drugs.[xi] For example, only half of the 75 million people in the US with hypertension can control their disease with medication. There are also dozens of genetic variations known to impact response to specific drugs.

Then the 3 billion base pairs of the human genome were finally completely sequenced by early 2000, and the amount of genomic data grew exponentially. Scientists expected this would lead to many new tests could be developed to help physicians better tailor treatments specifically to individual biology. Work was begun to map many more individual genomes and try to link those to drug responses or disease risk. As the cost of genome sequencing has plummeted, and the speed increased, this work has surged.

This idea got an especially strong start in oncology, because tumors are driven by genetic mutations. One of the first successes was Genentech’s breast cancer treatment Herceptin. That drug and its companion diagnostic test were approved simultaneously in 1998.[xii] The test measures levels of HER2, a protein that is overexpressed in some tumors. Herceptin was approved only for use in women with that marker. While that limited market may have initially dampened the drug’s sales, it’s not clear it would have been approved at all if it hadn’t been targeted to that subgroup group of patients.

Several other top-selling targeted cancer drugs followed,[xiii] and oncology has far outstripped all other indications in terms of the application of molecular diagnostics. The Pharmaceutical Research and Manufacturers of America (PhRMA) reported that more than 900 medicines and vaccines where in development against cancer by 2012.[xiv] Many of these are targeted therapies. The overall market for cancer treatments reached nearly $36 billion in the US alone in 2012.[xv]

Setbacks and Complications

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.[xvi] 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.[xvii][xviii] It’s been estimated that over $100 million has spent looking for such variations, with few clearly important targets unearthed so far.

Even the idea that each cancer has a single Achilles’ heel has also proven to be an over-simplification. Neoplasms, it turns out, may have multiple drivers, and they can change over time.

Finding the optimal treatment for a single patient is clearly often going to be much more complicated than scientists anticipated. All of that said – we are making significant progress.

The Rise of Precision Medicine

Today, many much more sophisticated approaches to unearthing biomarkers are emerging. Some experts refer to this new approach as precision medicine. It still focuses on creating high-value diagnostics, but compared to personalized medicine, it represents a broader notion: Being able to precisely characterize a disease, rather than finding a specific treatment that matches a patient’s unique biology. We’re no longer looking for just that one telling mutation, which then becomes the target for a test or a new drug. We are accepting that diseases may involve multiple pathways and these could vary from individual to individual.

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. [xix]

Diagnostics maker Foundation Medicine is one example of this new approach. The company’s first test, Foundation One, analyzes tumors using next-generation sequencing for over 200 specific markers and then predicts the best treatments for the patient. Foundationrecently netted a generous $106 million in an IPO, which is significant for a diagnostics firm.

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 potential for new products from this next generation science is immense.

Targeted cancer drugs alone are a major market. Eleven of the twelve cancer drugs approved by the FDA last year alone cost more than $100,000 per year in the US, and some cost more than $300,000.[xx] 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.

Faster Drug Development

Precision medicine can also speed drug development. That is an important advantage as those costs have also ballooned. Trials such as BATTLE, I-Spy, and the lung cancer Master Protocol aim to use biomarkers and novel designs to speed drugs to the clinic.

The idea is to match patients to optimal candidate therapies based on tumor markers. If these therapies are correctly targeted, then tumors should respond relatively quickly, the study designers say.

The Master Protocol will use Foundation Medicine’s next-generation sequencing platform to screen 500 to 1000 patients a year for various mutations. Patients will be grouped into “sub studies” that will evaluate a c-MET inhibitor, an FGFR tyrosine kinase inhibitor, a PI3 kinase inhibitor, a CDK4/6 inhibitor and an anti-PD-L1 monoclonal antibody. No marker exists for PD-L1 yet, and it’s a very promising target. So, patients who do not quality for any of the other subgroups will receive that agent.[xxi]

This approach has tremendous potential. Take Amgen’s Vectibix. The company originally tried to get to market with a biomarker for EGFR (epidermal growth factor). Although it seemed like an obvious target based on what was known about how the drug worked at that time, there wasn’t good hard data supporting the marker. The drug was stalled by regulatory agencies. Amgen sent tumor samples in for further analysis and eventually came up with a new marker – KRAS.

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. Some providers are already eagerly building up databases of genomic data from clinical samples. These could be the source of many tests.

Case Studies:

• Roche Holding AG’s Zelboraf was designed to target melanoma tumors carrying a specific mutation. In an early-stage trial, eight out of ten patients experienced significant tumor shrinkage. Even though the drug was designed specifically against tumors with mutations in BRAF V600E, the company had to carry out an expensive and time-consuming randomized control trial (RCT) of almost 700 patients.[xxii] The trial compared the drug’s effectiveness against the standard treatment — the chemotherapy dacarbazine, which is considered woefully ineffective. RCTs are considered the gold standard by the FDA for approving drugs. Critics are increasingly arguing, however, that targeted drugs require different processes. If a drug is expected to work better in a subset of patients, do you still need to carry out RCTs of a mixed population? There is a growing consensus that RCTs will not continue to be necessary for truly targeted therapies, or at least they will not need to be so large.

• In 2013 GlaxoSmithKline won FDA approval for Tafinlar, another drug targeting BRAF V600E. That approval was based on a trial of just 250 patients. Because the mechanism of 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 fewer patients had to receive dacarbazine and the researchers were able to demonstrate the drug’s efficacy more quickly than is usual.[xxiii]

A New Competitive Landscape

While technology is advancing, however, the cost environment is rapidly changing. An estimated 30 million people will gain access to insurance under the Affordable Care Act (ACA), creating many new customers for healthcare firms.[xxiv] The ACA itself contains few provisions for cost control, and those it has are expected to be difficult to implement. However, it opens the door to payment reform and private payers are also using bold new tactics to cut costs.

For example, a growing number of employers are shifting retirees or workers onto “private exchanges.”[xxv] These are online shopping sites for private health insurer. But this type of plan is very different from traditional employer-based health insurance, because the employer provides a defined sum for the worker’s health benefit. As a result the employer can cap their exposure to health costs increases. The employee, meanwhile, will need to shop according to their means.

As premiums and workers’ out-of-pocket costs have steadily risen,more people have also delayed seeking healthcare or sought cheaper alternatives. The rates of visits to retail clinics, which provide lower-priced care for some common conditions, quadrupled between 2006 and 2009,[xxvi] and that figure is expected to double between 2012 and 2015.[xxvii]

Employers have even started to embrace narrow networks, which are also increasingly common in government-subsidized plans. In 2012, the city of Los Angeles made headlines when it shifted its employees to an HMO plan that that did not include two of the region’s highest profile hospitals — Cedars-Sinai and Ronald Reagan UCLA Medical Center. This move was expected to save the cash-strapped city $7.6 million a year. [xxviii]

All these trends are putting more pressure on providers to reduce their prices and costs.Several months after Los Angeles made that change, UCLA Health System’s president announced it would cut costs by 30% over the next few years.[xxix] Even the world-renowned Cleveland Clinic is feeling the pressure, announcing it would cut $300 million in costs, in part through layoffs.[xxx]

The days of ever-escalating health costs are coming to an end. Healthcare providers seeking to maximize their revenue will need to use every strategy and tool available to stay competitive.

Why Precision Medicine?

Precision medicine will offer providers an advantage in two key ways: They will be able to attract more patients by documenting that they provide higher quality care. They can also reduce waste by restricting the use of high-cost treatments to patients who can actually benefit from them.

Pharmaceutical companies are also more likely to support precision medicine going forward. They are under pressure to reduce the cost of drug development and demonstrate the value of their products. As payers seek more and more price concessions from providers, doctors will have much greater incentive to practice more efficiently.

In this new cost-conscious environment, pharmaceutical companies will find it increasingly difficult to defend the widespread use of drugs with modest benefits that are known to work only in a subset of the population. Tests that can distinguish which patients will respond best, and thereby reduce the unnecessary use of expensive drugs, can both help companies cut drug development costs and make the argument for the drug’s value.

Better Technologies and Evidence

The field of personalized medicine was driven by the genetic revolution in basic science, which gave scientists powerful tools for understanding individual responses to therapies. To date, the diagnostic industry has brought to market more tests to help doctors make complex choices about which drug is right for which patient. But there are still many more known associations between genetic variations and drug responses than there are tests.[xxxi]

The insurance industry, meanwhile, has been resistant to personalized medicine, demanding solid evidence. 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).

We are approaching a turning point, however.

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 is spending $100 million over a 5 year period on such a division. And they are not the only institution investing at this level.

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. Those not investing may be at a significant disadvantage.

It’s also vital to watch developments in the tools sector. Many of today’s diagnostics were first studied at tools companies, where there is less regulation and thus more innovation. This product is often tested in close collaboration with academic groups and can advance surprisingly rapidly.

Looking Out

The hurdles are clear:

• The cost of developing truly valuable molecular diagnostics is high. Genomic Health’s OncotypeDx was developed with samples from 2600 breast cancer patients as well as ~500 clinical trial patients and required over $100M to bring to market. Myriad’s database also required over a $100M of dollars and years to create.

• Diagnostics makers also typically have to fight harder than pharmaceutical manufacturers to get the types of prices that reflect their true value. This has only become more difficult under new CMS regulations .[xxxii]

• The regulatory pathway is less clear than that for pharmaceuticals. The future is uncertain for both CLIA-certified home brew testing and FDA-approved pathways. As a result, developers could face challenges if their chosen pathway undergoes change. Or they just choose the wrong path for their product. .

• With the explosion in genomics and related technologies, doctors are having a hard time keeping up. Test makers need to understand all of the challenges physicians face in their daily work and make it easy for them to incorporate new tests.

But the potential is also evident. Healthcare costs are consuming about 1/5th of US GDP. We can only control that figure by making the system more efficient, and increasingly, that’s the type of technology and processes the rest of the world will want.

There should be steady growth in precision medicine over the next few years, including many creative new 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 US will spread around the globe, leading, finally, to the maturation of the field of personalized or precision medicine.