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• W3033125220 startingPage "961" @default.
• W3033125220 abstract "Signal detection is the most pivotal activity of signal management to guarantee that drugs maintain a positive risk-benefit ratio during their lifetime on the market. Signal detection is based on the systematic evaluation of available data sources, which have recently been extended in order to improve timely and comprehensive signal detection of drug safety problems.In recent years, attempts have been made to incorporate pharmacological data for the prediction of safety signals. Previous studies have shown that data on the pharmacological targets of drugs are predictive of post-marketing adverse events. However, current approaches limit such predictions to adverse events expected from the interaction of a drug with the main pharmacological target and do not take off-target interactions into consideration.The authors propose the application of predictive modeling techniques utilizing pharmacological data from public databases for predicting drug-target-event relationships deriving from main- and off-target binding and from which potential safety signals can be deduced. Additionally, they provide an operative procedure for the identification of clinically relevant subgroups for predicted safety signals." @default.
• W3033125220 created "2020-06-12" @default.
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• W3033125220 date "2020-06-25" @default.
• W3033125220 modified "2023-10-10" @default.
• W3033125220 title "Utilizing drug-target-event relationships to unveil safety patterns in pharmacovigilance" @default.
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• W3033125220 doi "https://doi.org/10.1080/14740338.2020.1780208" @default.
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