21st Century Medicine: Now It’s Personal

Two patients present with identical symptoms and diagnoses. Each is prescribed the same medication, and several weeks later, the first patient is responding well with improved symptoms and minimal side effects. The second patient, however, experiences debilitating side effects and escalating symptoms, and actually seems worse after taking the medication as prescribed. Two patients. One diagnosis. Same medication. Dramatically different results. This scenario is increasingly the norm for practitioners across the country, indicating that the “one-size-fits-all” approach to medical care is both outdated and ineffective.

Historically, healthcare practitioners were faced with the dilemma of offering cookie-cutter treatments to patients whose age, lifestyle and health history make their outcomes far from predictable. With recent research, scientists have discovered that even a person’s genes can influence their response to medication, and these findings are driving an entire industry toward a new age of patient-specific care. Is the long-predicted age of personalized medicine finally on the horizon?

Pioneering the P4 Approach

An old folktale describes what happens when a group of blind men encounter an elephant. Each man touches a different part of the elephant and gives a description of what he believes an elephant is. The first person touches the elephant’s trunk and claims the elephant is a snake. The second person touches the elephant’s leg and declares it is a tree. The third reaches out and touches the elephant’s ear and confirms it is a sail. The moral of the story is that if the three men had collaborated and holistically examined the elephant, its true identity would have been revealed. This is the concept behind a new approach to medicine called P4.

The P4 medical approach hinges on four pillars: predictive, preventive, personalized and participatory. This approach is intended to help identify the right drug for the right patient at the right time, thereby avoiding the prescription of costly and ineffective drugs and preventing potentially harmful side effects. Some say the practice of P4 medicine may be achievable in the next five to 10 years, and at the forefront of this concept is biologist and researcher Leroy E. Hood, MD, PhD, co-founder of Seattle’s Institute for Systems Biology.¹ “P4 medicine will provide actionable opportunities and revolutionize medicine. It will save billions of dollars in healthcare costs, and [it] will force a reluctant healthcare system to accept a radical change in how we deal with medicine,” said Dr. Hood in a recent interview.

P4 systems medicine, as Dr. Hood conceptualizes it, uses a holistic approach and new computational tools to analyze large amounts of molecular, cellular, phenotypic and medical data for specific patients. In other words, it evaluates the entire elephant. The first step in the process is to generate clouds of billions of data points for each person. As Dr. Hood described in a Science Translational Medicine editorial, “Medicine will be informed by computational analyses that reduce high-dimensional data to actionable hypotheses designed with the intent of optimizing wellness and minimizing disease in individual patients.”

The next step in this approach integrates the data clouds in technologies and strategies designed to optimize wellness and minimize disease. Over the next three to five years, Dr. Hood will embark on a comprehensive study involving 100,000 healthy patients. The study will continue for 20 to 25 years and review six different data sets to generate data clouds for analysis. Analysis will involve various body systems and functions, including the brain, heart, colon, lymphatic systems, liver, lungs, chromosomes and insulin levels.

Because the project involves a large number of patients who will be in good health when the study begins, the generated matrix will quantitatively define wellness. But, as the project proceeds, the data clouds will display when and how individuals transition from good to poor health. If scientists can identify both the transition point to disease early on and the earliest mechanism of disease, the theory is they could then intervene and reverse the disease before it has time to progress.1

The P4 collaboration between genetic knowledge and clinical studies is expected to contribute significantly to advances in preventive and prospective medicine. Perhaps the biggest concern is that the developers of molecular diagnostics are still not well-aligned with the pharmaceutical manufacturers whose products might be affected by diagnostics. Experts say more collaboration is needed between the diagnostic test developers, who are focused on targeting early drug development efforts, and the pharmaceutical companies that manufacture and sell the drugs.²

Despite the hurdles, P4 medicine has the potential to minimize the increasing costs of medical care, a goal shared by most stakeholders. Some predict P4 could become the foundation of future global healthcare, and, in a perfect world, would allow the focus of medicine to shift from curing disease to maintaining wellness, affecting everything from the economic cost of sick-leave pay to general population productivity.²

Biomarker-Based Diagnostics

Studies similar to the one being embarked upon by Dr. Hood have spurred the beginning of a major paradigm shift in healthcare away from “one-size-fits-all” approaches toward customized, patient-tailored therapies. In recent years, pharmaceutical companies have begun focusing on biomarker-based diagnostics and companion diagnostic tests that identify a patient’s likelihood of responding to a drug or experiencing side effects. Biomarkers, molecular substances in the body that can be used to indicate health or disease, can be found in tissue, blood, urine and other body fluids. Prostate and ovarian cancers are two examples of how the use of biomarkers are currently being used for individualized diagnosis and treatment.²

As with all new theories and treatment approaches, the challenge is to find the balance between patient benefits, economic value and clinical merit. The two main groups of companion diagnostics include tests developed after a drug has come to market and tests simultaneously developed as a companion to the drug. Today, a majority of drugs in the developmental pipeline are accompanied by associated biomarker programs, and that number is expected to increase. Such companion diagnostic tests can improve research productivity by decreasing trial sizes, increasing the speed to market and supporting higher drug prices.

These types of diagnostic tests are also showing potential in significantly reducing the costs of clinical trials. A recent report estimates more than $130 million in savings for pharmaceutical companies per approved compound.² Realistically, scientific and clinical factors place limits on the pace of such developments. In many cases, the current scientific knowledge is insufficient to select for specific biomarkers at early stages of a disease. In other instances, there is no immediate clinical need for companion diagnostics. And, from an economic standpoint, the prospect of generating greater market value for a product after it launches is more important for pharmaceutical and biomedical companies than investing in technology that would make the development itself more effective.²

Additionally, pharmaceutical companies are more likely to invest in diagnostics and technologies that impact larger groups, such as infectious diseases, immunology and oncology, with the latter being the most advanced field for personalized medicine to date. In contrast, disease states where incentives are not significant enough to encourage investment, despite technical feasibility and clinical need, include categories like antipsychotics and anticoagulants.²

Predictive Medical Care

With healthcare costs at an all-time high, the prospect of diagnosing disease before it strikes, and prescribing interventional therapy to prevent it rather than treating it, is intriguing. In a recent study, scientists were able to predict that a man was at a higher risk for developing type 2 diabetes and over a twoyear period tracked his health as he developed the disease. Even better, because they caught it so early, they were able to reverse the diabetes with lifestyle changes. This man’s glucose levels have since returned to normal.³

Despite widespread skepticism, there are already several proven applications of personalized medicine making headlines. Physicians are currently using predictive testing for certain cancers to determine who might be in a high-risk category. It’s been proven that mutations of the BRCA-1 and BRCA-2 genes can heighten a woman’s risk of developing breast and/or ovarian cancers.⁴ Patients who have a family history of these cancers can now request a genetic test that would look for mutations of those specific genes. A positive test allows the patients to consider preventive options such as precancer mastectomy or hysterectomy. Lifestyle changes, as in the case with the prediabetic patient, could also be considered to mitigate risk factors.

Colon cancer is the third most commonly diagnosed cancer and the second leading cause of cancer death in men and women combined in the U.S. Lynch syndrome, an inherited illness linked to colorectal cancer, has several genetic links, and if a patient tests positive for this gene, a physician may recommend getting colonoscopies earlier than the current “over 50” guidelines, tailoring the screening regimen to the patient rather than the general population.

All diseases have a genetic component, whether inherited or resulting from the body’s response to environmental stresses such as viruses or toxins. Ultimately, the goal is to learn how a faulty gene might cause disease, and then use this information to treat, cure or even prevent various diseases. Of course, some information garnered from genetic testing is only beneficial from a research perspective; at this point, knowing certain patients have a likelihood of developing Alzheimer’s disease still leaves them powerless to do anything about it.

The Quest for Pharmacogenomics

Another emerging form of personalized medicine is called pharmacogenomics, which uses genetics to predict an individual’s response to a drug. Proponents of pharmacogenomics say this is the future of pharmaceuticals, since people’s genetic makeups can impact how and whether they respond to medications. Supporters argue that using genes to guide drug use would lead to more effective therapies, while detractors say the science simply is not refined enough to help most patients.

Pharmacogenomics is already being used for some commonly prescribed medications, and recently, two large prescription drug companies announced plans to offer in-pharmacy genetic testing as part of the prescription-filling process. Under this process, certain prescriptions would trigger physician notification about available genetic testing, which would then be offered as an option to the patient. The testing would presumably help physicians customize prescriptions to fit individual needs, ward off undesirable side effects and optimize patient outcomes.5

Tests are now available that can help predict whether people with cancer or other diseases are likely to have good responses or bad reactions to certain medications. One such test looks at a group of enzymes that are responsible for breaking down and eliminating more than 30 types of medications, including antidepressants, chemotherapy drugs and heart medications. Due to their genetic makeup, some people aren’t able to break down these medications fast enough. The medications can then build up in the body and cause severe side effects. Conversely, some people break down these medications too quickly, before they have a chance to work. Genetic testing can identify people with these genetic variations to enable doctors to make more informed prescribing decisions, thus increasing the likelihood of treatment success and minimizing the risk of side effects.⁶

Supporters of pharmacogenomics say it has the potential to improve patient safety and decrease overall healthcare costs. It may also provide an opportunity to advance the field of genetic study by collecting data on genetic testing results and drug effectiveness. However, critics argue that we don’t yet understand enough about the human genome (and how it interacts with the environment and other factors) to routinely use genes as the basis for medical decisions. And, since pharmacogenomics is a relatively new science, insurance companies may not reimburse for the cost of genetic testing.⁷ “There are still a relatively small number of drugs where pharmacogenomics actually plays a role, but this could drastically expand over the next five years,” said Scott Weiss, a physician at Harvard Medical School and interim director of the Partners Healthcare Center for Personalized Genetic Medicine. “Antidepressants, asthma meds, anti-arrhythmia drugs, lipidlowering drugs — some of the biggest sellers in terms of drug use nationally — could potentially have pharmacogenetic implications.”⁸