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Prediction of Potential Adverse Effects

A predictive pharmaco-safety network has been proposed by Cami and colleagues,50 where known drug-safety relationship networks are combined with adverse event information and detailed biological network information on several drugs as a means to predict likely but prospectively unknown adverse events. In this approach more directed surveillance programs can be instituted for drugs under development and those marketed. A multiple evidence fusion method for both approved and novel molecules was developed by Cao and colleagues51. In this approach the authors assumed that drug behavior at different biological levels would provide predictive information on adverse effects, and that semantic relationships between adverse reactions would aid in predicting new or unknown adverse reactions for certain drugs. They also found that drug-adverse-effect networks would allow the inference of unknown associations. These evaluations used similarity measures with drug and adverse event pairs. The authors concluded that these methods are inherently beneficial especially in drug discovery during target selection, drug repositioning, and multi-target inquiry and development. In addition, the methods provide a better focus for large-scale clinical trials, and more focused post-marketing drug surveillance.50-52

 
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