For decades, scientists have wrestled with the problem that trusted prescription medications can combine in dangerous ways, often placing Americans at risk when they take more than one drug. Sometimes the dangers are well-documented. In other cases, they remain hidden from everyone: doctors, pharmacists, drugmakers and patients.
But in recent years a new era of data analysis has dawned. Across fields as varied as medicine and finance, researchers are developing powerful new mathematical formulas to reveal patterns within patterns and clues within clues.
The Chicago Tribune, in a unique collaboration with data scientists, pharmacologists and cellular researchers at Columbia University Medical Center, set out to see if these same novel techniques could be used in the hunt for risky drug pairs.
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