Even the most benign medications, like ibuprofen, can have side effects. When you get into the really “big league” prescription drugs aimed at mitigating major infections or cancers, the potential for serious side effects grows significantly.
Currently, the Food and Drug Administration (FDA) and World Health Organization lead the way in cataloguing important adverse drug reaction (ADR) information, based on reports made by physicians and pharmacists across the nation. A huge problem with this method, however, is that many ADRs go unreported.
Exciting new technology, however, could change the playing field for drug development. A research team at the University of Medicine and Dentistry of New Jersey have developed an artificial neural network that can help identify ADRs early in the drug development process. The network, which is a mathematical model of the biological neural network made as computer software, proved to be 99.87 percent accurate in predicting ADRs.
The model is fed information on current pharmaceuticals and adverse reactions associated with these drugs, and researchers are working hard to continue the model’s “training” by introducing thousands of additional drug molecules and ADRs into its repertoire.
Of course, the accuracy of this new technology relies heavily on the FDA’s current bank of adverse events, which are reported by physicians and pharmacists. Studies have shown, however, that many adverse reactions and events go unreported by healthcare workers, which leaves us questioning—how accurate can this promising new model be until ADR reporting is improved in the front lines?
If you or a loved one has experienced an adverse drug reaction, reach out to our firm now by clicking on the live chat feature on this page.
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