An estimated 1.3 million people in the United States alone are injured each year from medication errors, and the U.S. Federal Drug Administration (FDA) has been working to reduce the possibilities of these errors, such as a documented case in which a patient needed an injection of Narcan but received Norcuron and went into cardiac arrest.
A few years ago, the FDA turned to Project Performance Corporation (PPC), a U.S. software company, to ensure they don't approve the names of new drugs that may easily be confused with any one of the more than 4,400 drugs that have already been approved.
PPC looked at the problem and then, based on a tip from a professor at the University of Maryland, turned to Dr. Greg Kondrak, a professor in the University of Alberta Department of Computing Science.
"During my PhD research, I wrote a program called ALINE for identifying similar-sounding words in the world's languages. The program incorporates techniques developed in linguistics and bioinformatics," Kondrak said. "At the time some people criticized it because they felt it wouldn't ever have a practical application."
PPC analyzed Kondrak's program and felt it might help with their project. Kondrak gave them ALINE and then created a new program for them, BI SIM, which analyzes and compares the spelling of words.
PPC combined Kondrak's programs into a system that the FDA has been using for the past two years to analyze proposed drug names and rank them in terms of confusability, both phonetically and orthographically, with existing drugs.
"The FDA used to have dozens of people scouring the lists of names to check if the proposed ones were too similar to any of them, and this wasn't a good use of resources, and it wasn't always effective--people make mistakes," Kondrak said. "But now one perso
Source:University of Alberta