With the cost of drug development hitting the $5 billion mark and 94 percent of drugs failing at some point in clinical development, pharmaceutical companies have been turning to new tools to help clinical trial design: computers and robots.
A couple of Wall Street Journal articles highlight this trend.
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One notes that in June, the U.S. Food and Drug Administration and the European Medicines Agency endorsed a simulator from the Critical Path Institute to help develop Alzheimer’s disease treatments. Additional simulators are in the works for tuberculosis, Huntington’s disease and Parkinson’s disease.
Simulators process test parameters for a clinical trial – like drug dosage to use, how many patients to include and how long the trial should be – and show researchers whether those criteria will produce a statistically significant result for a particular treatment.
The article said Pfizer (NYSE: PFE) is using the simulator to design trials in four Alzheimer’s drug-development programs. Richard Lalonde, Pfizer’s global head of clinical pharmacology, said the simulator offers a way to fail early in the R&D process when it’s cheaper compared with when it enters clinical trials, when failure gets much more expensive. That’s a perspective shared by author and scientist Siddhartha Mukherjee in a recent talk at biotechnology conference Life Sciences Future.
Robots are also playing a role. In a compelling multimedia feature on clinical trials, the Journal calls attention to robots like Kalypsis at the NIH Chemical Genomics Center in Rockville, Md. Its lab uses robots to screen potential treatments for rare diseases far more efficiently and faster than it would take scientists to do manually.
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Some companies are finding other ways to use big data in the preclinical phase. Stanford University spinout Numedii is using big data analytics to find new targets for FDA-approved drugs.
[Photo from flickr user Thomas Hawk]
