Story URL: http://news.medill.northwestern.edu/chicago/news.aspx?id=228875
Story Retrieval Date: 4/17/2015 11:19:31 AM CST
U.S.-based drugmakers Merck, Pfizer and Johnson & Johnson are among the top 10 global R&D spenders.
Big pharma plus big data could equal big savings
Fifteen percent of Netflix Inc.’s 44.4 million global subscribers watched the second season of “House of Cards” the day it went live.
But Netflix wasn’t surprised. Before it invested in the series, a Venn diagram of viewers’ watching preferences had already predicted a series directed by David Fincher, starring Kevin Spacey and based on a British TV series would hit the sweet spot.
The data mining technique Netflix used relies on “big data,” a fairly recent buzzword. Predictions based on big data analysis are being made in the stock market, the auto market, at the box office and in political elections.
Now “big pharma,” comprising the largest drugmakers in the world, is on the cusp of this new frontier. McKinsey & Co. Inc., a global consultancy, has predicted big data could reduce research and development costs for pharmaceutical makers by $40 billion to $70 billion.
“An era of open information in health care is now under way,” McKinsey said in a research about the big data revolution.
There are plenty of data sources for big pharma to tap into. Thousands of online patient communities grouped by various diseases now exist online. PatientsLikeMe.com connects more than 220,000 patients in more than 2,000 condition groups. The Association of Cancer Online Resources links more than 200 cancer support groups.
On the other end of the health spectrum, fitness apps on mobile devices such as Fitness Buddy, Lose it, Workout Trainer and Nike+ Running, are tracking data on everything from users’ height and weight to their sleep cycles and eating habits.
Some health-care companies are ahead of the curve. London-based AstraZeneca PLC is partnering with HealthCore, the data subsidiary of health-care provider WellPoint, to find the most effective and economical treatments for chronic illnesses and other common diseases. AstraZeneca plans to use the information it derives to decide where to invest its research dollars.
In 2013, another British drugmaker, GlaxoSmithKline PLC, announced a partnership with health analysis company SAS Institute Inc. to provide a globally accessible private cloud for the pharmaceutical industry to securely collaborate on anonymous data from clinical trials.
In the U.S., Pfizer Inc., Eli Lilly & Co. and Novartis AG are partnering to improve the clinicaltrials.gov website. Their goal is to better match the individual health profiles of patients with ongoing clinical trials that might be applicable.
The partnership is backed by the White House’s “Big Data Research and Development Initiative,” a $200 million effort that seeks to greatly improve the techniques used to extract insights from large and complex collections of digital data.
In fact, the U.S. government is a key collector of big data in the health-care field. The National Institutes of Health has made the world’s largest set of data on human genetic variation, the 1,000 Genomes Project, available on the Amazon Web Services cloud for free.
The volume of data is exploding at a speed no one has ever imagined before, industry experts say, and that is challenging drugmakers’ ability to transform the information into additional revenue.
In general, big pharma is a risk-averse industry, analysts say, and it may take 10 to 20 years for a new idea to become a reality. Big pharma’s big data efforts are still in their early days.
Currently drugmakers are cautiously relying on outside contractors instead of internal sources, said Colin Miller, senior vice president of medical affairs at BioClinica Inc., a technology firm that manages global clinical trials.
Data broker IMS Health reported $1.87 billion in revenue for the first nine months in 2013. More than 60 percent of that came from sweeping up data from social media, pharmacies and health-plan claims and selling it to pharmaceutical and biotech companies.
Miller predicted change is coming but not too soon. The pharmaceutical industry thinks “We are not using a new technology until it’s ultimately financially viable and provides profit,” he said.
In marketing and evaluating drug performance, the profit potential of data mining is relatively clear. Every second millions of patients around the world are discussing their drug use experience on social media. The information could allow drugmakers to know immediately how well their and competitors’ medicines are performing and whether changes are needed.
“It’s true that people tweet about medical worries, symptoms, the drugs they take and their side effects,” Jochen Leidner, research analyst from Thomson Reuters, noted recently. “Social media has become such an important factor. Even Google famously used big data analytics to outperform the Centers for Disease Control in predicting the spread of winter flu in the United States.”
But the biggest bang for the buck from big data will show up in lower costs for new product development, industry experts say.
Research and development has always been the most time-consuming and expensive component in drug development. According to a 2013 industry profile by Pharmaceutical Research and Manufacturers of America, it takes 10 to 15 years to bring a drug to market and the process costs $1.2 billion on average. That cost accounts for 16.4 percent of sales, according to the trade group.
Using big data, researchers should be able to evaluate a much larger patient population that will better represent the variability of all potential users. They also should be able to more quickly assess what treatments are most effective for particular conditions and identify patterns related to drug side effects or hospital readmissions.
A big challenge for the industry, however, is to find scientists who understand both data mining and the drug industry. They are likely Ph.D.s who can translate a mess of data into plain English and suggest business strategies for companies.
The new field is so recent that the U.S. Bureau of Labor Statistics hasn’t yet listed a category for data scientists. The U.S. faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers who can make decisions based on the analysis of big data, McKinsey reported.
When big pharma makes its hiring decisions, a background in health care will be key, industry analysts say. Pfizer Inc. recently posted jobs on LinkedIn for senior manager-level data scientists. The listing required applicants to have 10 or more years of pharmaceutical industry experience.