Steven J. Altschuler and Lani F. Wu, mathematicians skilled in developing models to find meaningful patterns among mountains of data, worked with Timothy J. Mitchison of Harvard Medical School to automate microscopic imaging of drug-treated cells and recast the resulting scans in a computer-friendly format. The result: a method dubbed "cytological profiling" that trains computers to recognize cell status and health from cellular images, virtually automating microscopic scanning for various types of abnormalities.
"The resulting profiles of cellular changes wrought by drugs at various dosages provide information on drug mechanism that is highly relevant to understanding the specificity and toxicity of drugs," says Altschuler, research fellow at the Bauer Center for Genomics Research in Harvard's Faculty of Arts and Sciences. "The information gleaned includes many key indicators of drugs' potential usefulness and limitations as medicines."
"We actually started out on this project thinking that this could be a good research tool," adds Wu, research fellow at the Bauer Center. "We've now discovered, to our surprise, that it may also prove a powerful tool for drug discovery."
High-throughput cytological profiling lets scientists test numerous variables at once, wringing countless discrete cellular measurements from a single experiment. Faced with scores of drugs holding the potential to combat a given disease, researchers could hone in on the most promising drugs in a fraction of the time of current methods.