Personalized Medicine Ultimate Form of Patient-Centricity
Customized treatments are the final step in putting patients at the center of pharma’s operations.
Personalized medicine is the ultimate form of patient-centricity. Identifying patients who are most likely to benefit from specialized treatments, and delivering those treatments to them quickly and effectively, is the Holy Grain of pharma. It promises to improve patient outcomes in a sustainable way, making the industry a trusted healthcare partner. For that to happen, the industry needs to redesign the way it’s collecting clinical evidence and how it interacts with its customers.
Savvy executives are already reaping the benefits of creating personalized treatments. Roche, with its HER2-positive therapies worth a total of US$20 billion in sales that continue to increase, is leading the pack. But others aren’t far behind. Twenty percent of new drugs approved by the FDA in 2014 were personalized medicines, demonstrating that pipelines are flourishing.
As our understanding of disease increases, so does the awareness that the “one size fits all” approach to medicine is misguided. Researchers and clinicians are now recognizing the need to take individual variability into account when planning treatment regimen, driving more resources into personalized medicine. In January this year, President Obama announced a US$215mln national Precision Medicine Initiative that, according to the White House, will “provide clinicians with new tools, knowledge and therapies to select which treatments will work best for which patients.”
“This is the future of medical care,” said Dr. Edward Abrahams, President, Personalized Medicine Coalition, in an interview with eyeforpharma. Personalized Medicine Coalition is an education and advocacy organization representing 250 institutions focused on personalizing treatments across the healthcare spectrum. “We need technologies that allow doctors to target the right medication at the right patient at the right time, improving safety, efficacy and outcomes, while systematically lowering the costs.”
Drugs help half of the people who take them
Sometimes drugs that show promise in clinical trials fail in clinical practice. Abilify (aripriprazole), one of the highest-grossing drugs in the US, improves psychotic symptoms in one out of five people who take it every day. Crestor (rosuvastatin), a popular drug prescribed for high cholesterol, helps one in 20 patients, while Nexium (esomeprazole) improves heartburn in one out of 25 individuals who receive a prescription. According to McKinsey & Co, of the US$292 billion spent in the U.S. on prescription drugs in 2008, as much as US$145 billion went to medications that didn’t help individual patients.
Other times, drugs not only do not help, but can also hurt certain subgroups. Serverent (salmeterol xinafoate) is a drug used in asthma and chronic obstructive pulmonary disease that appears dangerous to people of African-American descent. Safety data released to the FDA in 2003 showed that respiratory-related deaths and life-threatening events occurred four times as often among African-Americans who took the drug than among those who didn’t. Adverse drug reactions account for 4.2-30% of hospital admissions in the U.S. and Canada each year. The total cost associated with side effects is estimated at US$30.1 billion annually in the U.S. alone.
Personalized treatments lead to system savings
Effective use of personalized medicine can save the system a considerable amount of money. Interventions would be delivered quickly and accurately. Resources wouldn’t be wasted on a “trial and error” approach that comes with a high percentage of non-response and a considerable risk of an adverse reaction.
By introducing greater efficiencies into the system and avoiding unnecessary treatments, we’ll be able to lower the overall cost to the healthcare system and increase the value of a particular drug.
According to McKinsey, personalized strategies costing US$100-US$3,000 would generate savings at US$600-US$28,000 per patient. A more targeted study in 2009 demonstrated that US$604 million could be saved annually if the use of Vectibic (pantimmab) and Erbitux (centuximab), drugs used to treat metastatic colorectal cancer, was restricted to patients with the disease whose KRAS gene was not mutated. People without a mutated KRAS are the only group who benefit from the drug.
“By introducing greater efficiencies into the system and avoiding unnecessary treatments, we’ll be able to lower the overall cost to the healthcare system and increase the value of a particular drug. If you give a drug only to people in whom you know it will work, even if it is an expensive individual therapy, you generate savings to the overall system,” Dr. Abrahams explained.
Although payer engagement with personalized medicine remains challenging, the landscape is changing. “Payers are moving away from volume-based approach to a value-based approach,” Dr. Abrahams pointed out. “If they want to pay for outcomes, they will have to do things differently than they have done so far. Payers recognize that personalized medicine is a part of the solution, but they want to see evidence of effectiveness. I hope they will facilitate the collection of that evidence.”
New study designs are needed
Payers want to pay for drugs that work. Demonstrating efficacy in personalized medicine requires a new way of thinking about how clinical evidence is gathered.
First proposals for new approaches to trials came already in 2005, when prominent cancer organizations called for additional testing during and after the trials. Scientists argued that those tests would “highlight individual differences in drug response and detect successful targeted therapies faster” allowing to see whether a drug is working within the first few patients.
At the time, the American Society of Clinical Oncology, the American Association for Cancer Research and the Association of American Cancer Institutes proposed that early clinical trials should include ongoing analysis of patients’ tissue and blood samples that would show whether a drug doesn’t work because of an inappropriate target or because of genetic differences that stop the drug from reaching the target in some sub-populations. Such a design would have allowed research on the lung cancer drug Iressa (gefinitib) to be optimized much sooner. Iressa was already in advanced clinical trials by the time the EGF receptor was identified. The presence of EGF is believed to be a deciding factor in a positive response to Iressa. Had the scientists known that sooner, they would have been able to restrict the trial to patients the drug was likely to work in, saving time and money, not to mention patients’ lives.
Since then, trials like BATTLE-2 and ISPY-2 have emerged. In those trials, multiple drugs in various arms of the study target different molecular alterations, demonstrating the value broad-based genomic profiling of patient tumors.
But more game-changing ideas have emerged recently. N-of-1 trials propose moving away from large-scale trials altogether in favor of methodical study of individual patients rather than whole groups. This is often seen in medical practice where doctors “experiment” with treatments, prescribing a pill and studying the patient’s reaction before either deciding to continue with the proposed regimen or changing it to something else. Done systematically, the traditional “trial and error” approach that tends to waste money might prove useful. Scientists are now developing strategies for formalizing this method. The hope is to collect large volume of data over a long period of time to establish whether existing treatments work better in some sub-populations over others, which is usually difficult to detect in large-scale trials. In addition, N-of-1 trials hold promise to effectively test drugs for rare conditions as well as to explore the repurposing potential of certain drugs already on the market.
Well-designed N-of-1 can also support drug development. Safety assessment dose escalation studies could be optimized depending on metabolic profiles of individual volunteers. Looking at an accumulation of results from a series of N-of-1 studies, researchers would be able to assess the effectiveness of the intervention in groups that e.g. share a particular gene.
Accurately identifying a subpopulation in which a drug is likely to work will lead to narrow indications. Therapies aimed at a small number of patients are generally used by a minority of healthcare professionals often concentrated in large hospitals. Working with a few high-value centers requires a high quality, personalized customer experience, which pharma is still learning to deliver.
All about the patient
Patient outcomes are all that matters and personalized medicine brings that principle into focus. Unlike precision medicine that focuses exclusively on pharmacogenomics, personalized medicine links diagnostics and treatments with individual’s values. It puts patients at the heart of treatment by considering what is important to them. “A patient prefers to be considered a person rather than a target for drugs,” Dr. Abrahams said. This principle should inform product and service development.
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