For years, real-time analytics have helped people to see patterns in data about traffic, weather, and the stock market. The pharmaceutical industry has plenty of ways it could benefit from real-time data feedback, and one of the obvious ones is in finding bottlenecks that slow down patient enrollment in the clinical trials that cost the industry $35 billion a year.
If a San Francisco-based software company called DecisionView is successful, it could end up teaching Big Pharma some powerful lessons about real-time data analytics, which could in turn enable drugmakers to get more of its studies done on time and budget.
DecisionView, a private software company with 40 employees, is releasing a new report on clinical trial enrollment patterns, based on a deep pool of data it has gathered on trials from top drugmakers like Merck, GlaxoSmithKline, and Roche. The report, which encompasses 730 trials conducted between 2005 and 2011, sums up data on patient enrollment at 35,000 clinical sites, across 14 different disease categories, in 85 countries.
There’s no single earth-shaking conclusion, CEO Linda Drumright says, but there are lots of fine-grained details for clinical trial planners to comb through. For example, when looking at Brazil, Russia, India and China, the analysis shows China enrolls significantly more patients per study, but takes the longest time to recruit. India and Brazil are the fastest at enrolling patients once studies are ongoing, in an average of 26 weeks. Trials get up and running the quickest in Russia (31 weeks on average), while Brazil takes the longest to get the trials started (55 weeks).
The report is intended to establish a benchmark that pharma companies can use to see how well they’re doing at organizing their own clinical trials. By drilling deeper into data on enrollment patterns of trials, site by site, disease by disease, and comparing each study’s performance to the data in the report, DecisionView is betting that pharma companies will be able to make mid-stream adjustments to trials that can keep studies from dragging on and wasting too much money. It’s a huge industry bugaboo, as an estimated 94 percent of industry-run trials finish behind schedule, and sponsors are said to lose an average of $8 million a day when a drug’s arrival on the market is delayed. Each year, about $35 billion is spent on clinical trials, and about 13,000 trials are enrolling in the U.S. at any given time, meaning there’s big business in helping things run more smoothly.
“It’s insufficient to make guesses when you are betting so much money,” Drumright says.
DecisionView, backed by Granite Ventures and Aeris Capital, has gradually built up some momentum for its offerings since it was founded in 2004. GlaxoSmithKline became its first major pharma customer in 2007. While DecisionView doesn’t disclose its annual revenues, Drumright says eight of the world’s top 10 pharma companies use its product, revenues have almost tripled since 2010, and the company expects to break even this year.
The idea at DecisionView is all about helping companies do a better job of planning the fastest, best possible trial of, say, a new rheumatoid arthritis drug at 100 sites around the world—and then make sure that such a train and all its moving parts remains on track. While there are companies out there with software designed to randomize patients in trials, or help manage data from clinical trials in an FDA-validated way, there wasn’t really a corporate software program specifically for getting patients enrolled on time, Drumright says. Companies were using Excel spreadsheets to track enrollment, or homebrewed software, and weren’t really getting real-time visibility into specific sites, regions, or countries, where enrollment had bogged down, she says.
To deal with that, the DecisionView program contains what Drumright calls a “forecasting engine” where a company can take its own past experience, and experience from industry benchmarks, to put together a plan for how long it should take to enroll, say, 1,000 patients at 100 sites around the world in the hypothetical arthritis study. Data and assumptions get entered about where the patients are supposed to come from. The forecast gets updated as data comes in from ongoing studies. “We can say, ‘here’s how far off track you are, and then enable you to do scenario modeling to deal with it,'” Drumright says.
In what ought to be a serious red flag to pharma company shareholders, some companies struggle to adopt this type of technology, Drumright says, because they don’t really have consistent planning processes for clinical trials, much less an ability to adjust their plans on the fly. “It’s a big cultural change to implement our solution at some companies,” Drumright says. “But once they’ve done it, they’ve thought of all the various plans, and all rescue strategies they might use, they can leverage the information in the way they never could before.”
The report coming out today is what DecisionView hopes will be the first of many, Drumright says. Several of the pharma companies asked DecisionView to produce this resource, in hopes that by creating an accurate, third-party source for enrollment patterns, the whole industry could benefit, Drumright says. There are other benchmarks out there on enrollment times, but for this one, DecisionView insisted that companies who participated dumped in “the good, bad, and ugly” data, not just from cherry-picked studies, Drumright says. By sharing the warts-and-all data, she says pharma customers hope to be able to highlight certain trouble spots, or regions, which will enable everybody to steer clear.
The initial report is far from comprehensive, but as more companies pool their data, and more studies get dumped in the database, it should become a richer resource, Drumright says. DecisionView’s plan is to update a summary report periodically, she says, and offer it to its paying customers as an added feature of one of its software programs, which companies pay for on a per-study, per-year basis.
Drumright wouldn’t say how much she charges for the software, but she’s clearly been asked a million times how DecisionView justifies its price. As more data comes in from customers, DecisionView crunches through it to show its value. The company boasts on its website that it can reduce trial delays by 30-40 days on average, and reduce “non-performing” sites by one-third.
“The customers are bleeding a lot of money,” Drumright says. “I save them a lot more money than I cost them.”
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