No one knows more about wasteful spending than the government, and healthcare is on top of most people’s list when it comes to wasteful spending. Since 2009 the focus has shifted towards bringing down the cost of healthcare spending. According to the Center for Medicare & Medicaid Services (CMS),”The nation’s healthcare cost is on track to hit $4.6 trillion in 2020, which would account for $1 out of every $5 in the economy.” In March 2010, President Barack Obama signed into law what he hoped would be a comprehensive overhaul of the healthcare industry. However, some feel the focus of his healthcare plan does not dig deep enough into the underlining issue when it comes to skyrocketing healthcare costs.
The buzz circulating the healthcare issue has always been about the increasing prescription drug costs. However, according to several studies, prescription drug costs are actually declining or maintaining a small incremental increase. A recent study released by the IMS Institute, reports that the average cost of both oral and inhaled medicines, which make up 60% of overall spending, have declined in 2010. The report continued to add that the remaining 28% of spending, which were administrative medicines (injections or infusion), have only rose by 5.7%.
Those within the community feel prescription drug costs are not really the issue, and instead, the main issue is the increased cost of the research and development of these drugs. In fact, in 2006 the Congressional Budget Office (CBO) conducted a study due to concerns for the future of drug development amidst increase profitability and slow drug output, and noted, “The pharmaceutical industry spends more on research and development, relative to its sales revenue, than almost any other industry in the United States. According to various estimates, the industry’s real (inflation-adjusted) spending on drug R&D has grown between threefold and six-fold over the past 25 years—and that rise has been closely matched by growth in drugsales.”
Even with this astounding growth in the cost of research and development (R&D), there is no guarantee that any drug will ever make it past the Food and Drug Administration (FDA) approval process before reaching the consumer. Of millions of dollars spent on R&D, approximately five out of every 10,000 potential compounds ever make it to the clinical stage before submission to FDA, according to Pharmaceutical Research and Manufacturers of America’s (PhRMA) research and analysis conducted in 2010. Furthermore, from the potential compounds that have made it past the FDA’s approval and out to the consumer, “Only two of ten approved medicines ever recoup their average cost of development,” PhRMA President and CEO,John Castellani said during this year’s NY Pharma Forum.
The average developing stages for a new drug takes 10–15 years, and within those years there are several trials and errors. The process is not cheap, and there is no guarantee that the drug will either get FDA approval or have a 100% success rate. The direct cost of developing a drug is expense enough, but when you factor in that the firm must pay shareholders a return on their investments, as well as pay to patent the drug, the cost can definitely start to grow. In fact, in 2009 the total cost of R&D for the industry in developing new drugs was reported to be $65.3 billion for U.S. biopharmaceutical companies.
The Personalized Healthcare Movement
But what if drug development companies--from biotechnology to pharmaceuticals and the like-- could drastically decrease their research and development costs, even determine if a drug is worth pursuing via the current chosen path? What if the optimal development direction could be employed because it was determined through processing an almost infinite amount of scenarios?
Aware of the risky and costly undertaking, an increasing number of drug and research companies are abandoning conventional drug development protocols and setting their sights on Personalized Medicine. The Personalized Medicine Coalition believes that gathering a profile of a patient’s genetic make-up can lead to better development and selection of effective drugs and treatments through the use of information technology to help patients and physicians make optimal treatment decisions.
The backbone of personalized medicine is said to be in Health Information Technology (HIT).“Without the ability to bring together, analyze, and organize information that can help illuminate each person’s unique biology and medical history, compare it with large-scale clinical outcomes information, and thereby predict risks and responses to treatments, it is not possible to individualize healthcare,” noted the Personalized Medicine Coalition in their The Case for Personalized Medicine, 2nd Edition.
With this in mind,both pharmaceutical and research firms have started to reach out to companies such as GNS Healthcare, which has developed an analytical software system that can utilize patients’ DNA, molecular, and clinical data to build models predictive of patient outcomes for different drugs both on the market and in development.
What could all this lead to? Not only personalized medicine for individuals but the ability to find the best possible treatment from the data acquired.
“We are doing more and more work with NCI, NIH, and large biopharma companies,” said Colin Hill co-founder of GNS Healthcare Inc., a privately-held biotech company located in Cambridge, Massachusetts.
Just this month GNS announced that it has entered into an agreement with Bristol Myers-Squibb toutilize their machine-learning supercomputing platform, in a collaboration that will focus on the discovery of novel disease biology and biomarkers in the area of immuno-inflammation.
GNS is also currently collaborating with National Cancer Institution (NCI) to accelerate lung cancer research, Brigham and Women’s Hospital (BWH) in their asthma patient therapies, Biogen Idec on rheumatoid arthritis research, as well as other research and drug companies. Colin mentioned that GNS “technology is absolutely a game changer. Our technology is applied in developing new drugs, developing new medicines. It is also now being applied with health insurance companies, and pharmacy benefit managers to mine plan data and determine what actual treatments and interventions are moving the needle on healthcare.”
The Secret to Faster Drugs, Better Treatments and an Actual Cure
Founded in 2000 by both Colin Hill and Iya Khalil, the company utilizes supercomputing technologies, in the form of “big data” analytics to “extract cause-and–effect relationships.”Hill explains GNS technology as “a machine learning tool which is able to discover cause and effect relationships through data, which allows us to match treatments to patients. Our technology answers the question of causation–what happens when they intervene, what happens when they apply a certain drug.”
In order to generate the cause and effect mechanisms Hill and his teammates spent 10 years developing the REFS™ (Reverse Engineering/Forward Simulation) software platform. REFS™ creates simulation models, through algorithms and software, of all the data components and billions of queries to reveal hypothetical scenarios that can expose the best treatment for each patient. REFS is licensed to GNS from their parent company Via Science.
With a focus on the increasing cost of healthcare, many in the personalized medicine industry feel that the government would be wise if they started shifting their focus towards their segment of the industry. As Hill mentioned many of them feel that they are under utilized by the government, "The government is hugely important, but I think the government has not taken advantage of these new approaches, enough, for things that are directly of interest to the government, like the healthcare bill." Hill later went on to explain that he feels that his segment of the industry is essential to helping the government control the cost of healthcare, "At the end of the day there is a need to control healthcare spending, and personalized medicine is at the core."
When asked about his vision for personalized healthcare, Hill said, “[My] vision is where data is collected and ultimately put into a centralized repository in the cloud where technology like ours will be mining the data continuously to determine what’s working and what’s not working for whom.”
Investors want to reduce as much risk as possible when they invest, but the medical drug development industry is known as one of the riskiest of all. Not only do investors have to be conscious of external influences from the broader market and the millions of dollars spent every quarter without a profit in sight -- but perhaps most significant is the FDA approval process, where clinical trials and FDA letters can make or break company. Investors can be on the edge of their seats for at least 3 years waiting for the possibility of gaining from their investment.
Even in the pre-clinical trial stage, inputting data into analytical software could one day eliminate the need for testing on animals and paint a more accurate picture of how drugs and diseases affect human beings –which can substantially mitigate the risk by removing the cost burden.
In the future, it would not be far-fetched to see a system like GNS’ REFS™ technology referred to as a requirement during the FDA approval process to mitigate safety concerns.
The government is slowly taking notice. The Department of Defense, under their Defense Advanced Research Projects Agency (DARPA), funded a case study, conducted by the University of Southern California's Information Sciences Institute, to demonstrate the business and competitive value of modeling, simulation and analysis with HPC in the U.S. private sector. GNS and its supercomputing capabilities were the main focal point of the case study, focusing on the power of HPC to discover new drugs.
Whether or not virtual analytical technology like the one from GNS would be a requirement, it would be to the advantage of all life science companies to utilize the technology and improve drug efficacy, as well as bring drugs to the market faster and significantly reduce costs.