Current Challenges and Future Perspectives: Pharmacovigilance

With the identification and prevention of adverse drug events, pharmacovigilance increases patient safety. Although there are obstacles that limit the detection of adverse drug events, many adverse drug events go unreported or are reported incorrectly. Large data sets from diverse sources, such as wearable medical devices and electronic health records, are one difficulty. Artificial intelligence, which includes machine learning techniques like deep learning and natural language processing, can identify and gather data on adverse medication reactions, automating the pharmacovigilance process and enhancing the monitoring of well-known and well-documented adverse drug reactions. In addition, artificial intelligence techniques can help in identifying and preventing adverse medication events due to the rising demand for telehealth services for treating both acute and chronic disorders. In this review, we discuss the current and future perspectives of pharmacovigilance that may be useful to improve the quality of pharmacovigilance and the role of artificial intelligence in telehealth practices.