Bruce Aronow, PhD, senior study author and Co-Director of the Computational Medicine Center at Cincinnati Children’s, says:
“One of the capabilities that makes AERSMine different from any other clinical data mining system is its ability to use knowledge frameworks—ontologies—to form groupings of patients, medications, and outcomes. We believe this provides unprecedented power to explore negative and positive drug effects.”
EARLY SIGNS OF SUCCESS
The researchers evaluated the tool by running a series of analyses involving three important classes of drugs: 1) lithium, which is used to treat manic depression/bipolar disorder; 2) anti-tumor necrosis factor (anti-TNF) drugs, which is used to treat inflammatory conditions; and 3) Non-steroidal anti-inflammatory drugs (NSAIDs) used for pain management.
Their analysis of lithium, for example, showed that 22,575 patients had used the drug with a total of 4,180 adverse drug events. AERSMine-dissected data shows that 327 adverse events significantly correlated with patients that use lithium (such as aggression, anger, suicidal tendencies, etc.) have a significantly reduced rate of occurrence in patients taking angiotensin receptor blockers (ARBs) to control hypertension.
The intriguing possibility suggested by AERSMine analysis is that ARBs might protect bipolar patients taking lithium from its potentially dangerous side effects.
Meanwhile, authors detected other potential connections by studying the use of NSAIDs for arthritis and chronic pain. They detected differential rates of adverse clinical events depending on whether people used propionic acid derivatives (like ibuprofen) or cox-2 inhibitors. They also detected patient groups for whom the risks of NSAID adverse events are much lower than others.