The selection of an appropriate signal detection method is pivotal in the identification process of safety signals in pharmacovigilance. Nevertheless, the early detection of safety signals is even more important to prevent the occurrence of another thalidomide tragedy in humans. Spontaneous reports, follow-up studies, scientific literature, preclinical & clinical studies, are valuable sources of adverse events; but on the other hand, these reported adverse events are extremely diverse, hence comprehending this can result in formulating the right signal detection and evaluation strategies. Broadly, signal detection methods fall into two categories: qualitative and quantitative, each having its significance; while the quantitative methods help to handle the voluminous data during signal detection, the qualitative one does its part to pick the rare signals. Hence, there is no single universal method that would be a perfect fit to identify safety signals from all data sources or for all types of adverse events. Further, the signal detection process involves a series of steps right from signal detection to its final assessment & submission, to regulatory authorities confirming a signal as a 'possible safety alert'. Finally, the completed task of finding a confirmed safety alert would be meaningless if it does not reach the end-users of the drug concerned. Therefore, effective communication to health care professionals, patients including clinical trial subjects, pharmaceutical companies, and other stakeholders is equally important.
Mining Safety Signals in Spontaneous Reports Database Using Concept Analysis