“I want the country that eliminated polio and mapped the human genome to lead a new era of medicine -- one that delivers the right treatment at the right time. In some patients with cystic fibrosis, this approach has reversed a disease once thought unstoppable. So tonight, I’m launching a new Precision Medicine Initiative to bring us closer to curing diseases like cancer and diabetes, and to give all of us access to the personalized information we need to keep ourselves and our families healthier. We can do this.”
Photo: White House Tumblr
In what amounted to a few seconds of his hour-long State of the Union address, President Obama announced one of the most significant biological research funding opportunities to come from the federal government in some time. The new Precision Medicine Initiative, slated to inject $215 million into the 2016 federal budget, will bolster research across various disciplines from basic science to healthcare IT to regulatory innovation. While the address itself may have been scant on details, the Obama administration has wasted no time mobilizing key players to execute their promises. If all goes according to plan, the initiative could blow open new opportunities for emerging scientists, and more importantly, for the patients desperate for personalized treatment options.
- The National Institute of Health (NIH) will receive $130 million to develop a voluntary national registry of over 1 million people replete with medical history, genomic, metabolomic (chemical), and microbial data.
- $70 million will go to the National Cancer Institute (NCI) to unravel the genetic basis of cancer and promote clinical trial design guided by genetic analysis.
- $10 million will go to the Food and Drug Administration (FDA) to modernize its review process. With swarms of new sequencing technologies and diagnostic tools the agency will require new expertise and a streamlined regulatory process.
- $5 million will go to the Office of the National Coordinator for Health Information Technology (ONC) to facilitate collection, organization, and secure distribution of all of this new data.
- Just days after the State of the Union the White House invited industry leaders from Merck, Regeneron, Illumina, and Foundation Medicine, among others, to learn more about the President’s intentions.
That’s all great on paper, but what does it mean in reality? How does it fit into the context of today’s science, and where will it guide us?
When the Human Genome Project was completed in 2003, a new door opened to the understanding of the genetic basis of disease. Since then, a handful of drugs have been successful at modifying disease based on these genetic factors, including the cystic fibrosis treatment referenced by the President. According to the Personalized Medicine Coalition, more than 20% (9 out of 41) of the drugs approved by FDA in 2014 were designed in consideration of one or more specific biomarkers aiding in diagnosis. While this may sound impressive, it falls dramatically short of the hopes of early genomics researchers, who had dreamed of a speedier and complete entry of genomics into the clinic.
Since the completion of the Human Genome Project, the cost of sequencing a human genome has plummeted to $1,000 from $3 billion for the first human genome ever sequenced in full. Obama’s initiative is aimed at leveraging that technology to undertake one of the most ambitious projects in medicine: the assembly of a comprehensive database of information from a cohort of 1 million volunteers. Open to academic and industry researchers, the repository of data is intended to provide a large network of clinical information. On the heels of a similar initiative in the UK, which proposes the sequencing of 100,000 genomes, the project highlights an interesting statistical paradigm of precision medicine: it takes a ton of data to design targeted therapies that treat fewer people.
With so many other industries adopting ‘big data’ approaches to find patterns or trends in massive data sets, it’s about time that a concerted big data effort takes hold in health care. The approach will allow scientists to scan a huge amount of medical data for disease associations that may only exist in a small percent of patients, but can be detected easily when that data is compiled in a single collection.
Imagine, for example, that of the 1 million patients in the database 1,000 have had a heart attack before age 35, a pretty rare occurrence. Now of those 1,000, 400 have a mutation in a specific gene. When researchers go back to the original million, they find that only 100 people have the same mutation but did not have a heart attack. The mutation is now a fairly reliable risk factor for early heart attack, spawning a race to understand the biology and develop a drug to correct the gene.
An emerging class of cholesterol-lowering drugs, the PCSK9 inhibitors, were inspired by exactly this approach. The 3,500-patient Dallas Heart Study was designed to investigate risk factors for cardiovascular disease in a large number of patients and found that activity of Protein Convertase Subtilisin/Kexin 9 correlated with elevated levels of cholesterol. With a validated genetic target, industry has raced to develop drugs that will treat Familial Hypercholesterolemia, a rare but very difficult-to-treat disease of severely elevated cholesterol. FDA approval of two of those candidates is expected in the next few months.
Streamlining discovery on a larger scale has been the real challenge in bringing the promise of genomic sequencing to fruition, and it’s why sequencing and data scientists are poised for a big payday. Skeptics (surprisingly, not the spending-averse GOP – this initiative has bipartisan support) argue that such a concerted big data effort is futile, though. While we may uncover the genetic basis of some illnesses, in reality, risk factors for disease involve multiple genes and lifestyle factors, increasing the challenge to find actionable drug targets. Moreover, simply identifying drug targets is only half the battle – the real challenge is designing a drug that works safely and can survive clinical trials and FDA critiques.
These arguments hold some weight, but by assembling mountains of new data in an open-source reference for academia and industry alike, the Precision Medicine Initiative provides the best chance yet for a multi-disciplinary approach to drug discovery.
