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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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