The Debate on Personalized Medicine: Costs and Equal Access

Imagine a drug that could be tailored to you, developed from your genetic makeup, your medical data, and the trajectory of your illness – all of the particularities of you – with the caveat of a million-dollar price tag. Would you take it?  This is the dilemma that personalized medicine faces. Personalized medicine – sometimes termed precision medicine – is an approach to medicine that enables targeted treatment of patients. Instead of blanket diagnoses for often very diverse diseases, personalized medicine tailors therapy to each individual based on their predicted response or risk of disease.

With the completion of the Human Genome Project in 2003, researchers finally had the entire DNA sequence of the human genome. This was a revolutionary breakthrough in medical research, and scientists could now target specific disease genes to develop therapy. Breakthroughs like Ivacaftor – a drug to treat patients with a specific mutation of cystic fibrosis – showed the promise of personalized medicine to revolutionize healthcare. Ivacaftor was dubbed “the most important drug of 2012” and “a wonder drug”. It was capable of treating the cause of cystic fibrosis, not just the symptoms as was previously the focus of medicine. With personalized medicine’s success stories and media attention, the Obama administration became a major proponent of the continued development of personalized medicine, launching the Precision Medicine Initiative and providing $215 million in funding. Combined with big data analytics that are enabling wide-scale analysis of patient data – such as the Precision Medicine Initiative’s Cohort Program of about a million volunteerswhose health data are collected and analyzed to gain insights into the biological, environmental, and behavioral factors that drive disease – personalized medicine is revolutionizing healthcare by making it possible to create effective medical treatments for every person.

But others wonder, is it really every person? Along with its novel successes, personalized medicine has been followed by the problem of high costs. Ivacaftor took decades to develop, costs $300,000 a year per patient, and is useless in the 95% of cystic fibrosis patients that have a different mutation. Of the 5% of patients that it does treat, claims have been made that its efficacy is roughly equal to three much less costly and universally applicable treatments, such as high-dose ibuprofen, aerosolized saline, and the antibiotic azithromycin. On the other hand, Gleevec, a targeted cancer therapy, is a different story, and has led to significant improvements in patient recovery and multi-cancer applicability. For chronic myolegenous leukemia, a study showed that Gleevec increased survival rates five years after diagnosis from 30% to 89%, albeit at significant cost ($146,000 a year).

Are these high costs worth the small proportion of patients that have so far been successfully treated? While personalized medicine holds significant promise, it remains to be seen if it can be sustainable. Some argue that though we are at the beginnings of our foray into personalized medicine research, leading to high costs, personalized medicine could decrease healthcare costs in the long term. This would be accomplished through the growth of technology, such as the digitalization of health care and next-generation sequencing technologies in the clinic. If these technologies expand to clinics, it will be much easier for clinics to devise personalized treatment plans, thereby making them less expensive. Government policy can also make costly medicines more affordable for patients. Indeed, a cornerstone of the Affordable Care Act has been its aim to reduce prescription drug prices.

Others assert that personalized medicine increases health inequities and is a wasteful way of spending government resources. They argue that the money and people pouring into the advancement of precision medicine takes away from resources for the broader population for whom personalized treatments are unthinkably costly. Instead of clinical care, targeting societal factors may be more effective at improving healthcare. To draw an example from personal experience, patients of the Ethembeni HIV Clinic in South Africa, where I worked for a summer, had access to free first-line and second-line antiretroviral treatments. However, I observed that many patients nonetheless didn’t make it to the hospital due to the higher priority of getting basic necessities, a lack of transportation money to get to the hospital hours away, and societal stigma that prevented men from leaving work for an appointment. As a result, the first-line and second-line therapies developed resistance, leaving patients with no options to continue fighting their disease – even though more effective (and more expensive) third line regimens exist in wealthier nations. In the US, societal resources are also undoubtedly a limiting factor for healthcare in poorer communities.

While we must recognize these drawbacks, recent advances and increasing scientific and technological progress give promise to future forms of personalized medicine that are both more effective and more affordable. Continued scientific progress is changing the treatment of lung cancer, as personalized therapies target the perennial issue of tumor resistance. The growth in availability of data, cloud-based data storage, and powerful machine learning technologies make it possible to glean more insights from patient data than ever before. National database Genomic Data Commons aims to unify genomic cancer data to support precision medicine, while technology-based research organization Verily Life Sciences (formerly a division of Google X) has joined in on Obama’s Precision Medicine Initiative. Alongside technological advances, the growth of organizations, companies, and startups competing to transform healthcare can lower prices and spur cost reductions that could eventually make personalized therapy both affordable and effective.

 

Image courtesy of Flickr. Originally published by S&S on December 22, 2016.

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