Drug companies are already making strides in switching from paper to electronic files. Now they're using analytics to cut down on tests they see as unnecessary and wasteful.
Just by planning more efficient studies, companies can save $3.5 million per trial and cut weeks off the process, according to cloud-based analytics company Medidata. Electronic file transfers, remote patient monitoring and cutting down on tests that don't directly address the main questions that researchers need answered can save companies even more, the company says.
The tactic isn’t without its risks: Cutting down on tests considered unnecessary based on what researchers are looking for could mean missing out on potentially lucrative findings. Viagra, for instance, was initially being developed as a blood pressure drug, said health care analyst Les Funtleyder at investment firm Poliwogg. Virtually by accident, researchers found that the drug was effective in treating erectile dysfunction.
Companies could also face challenges when they apply for drug approval by the the Food and Drug Administration, according to Funtleyder.
"The danger is that if pharma skimps on trials, [data] might not be robust enough for the agencies," Funtleyder said.
But if the time that it takes to get a drug from test tube to market can be shortened, that could save precious time for patients who are seriously ill, said Medidata President Glen de Vries.
"Maybe we can save you $30 million on that study, but more importantly we can help you run a more efficient study and more effective study so you can get your drug into the market faster. That's great for the patients who want that drug, and it’s also great for the life sciences company who's going to generate revenue that much sooner," de Vries told "Big Data Download."
Medidata itself has worked with pharma giants including Johnson & Johnson, GlaxoSmithKline, AstraZeneca and Abbott, but it faces stiff competition from data analytics giants like IBM and Oracle, which are also applying their analytics to health care.
Understanding the long-term side effects still poses a challenge for drug makers, regardless of the analytics involved in planning and executing more effective trials for FDA approval.
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