Aims: The search for signals of drug-induced adverse events using spontaneous reporting databases are used in clinical practice and pharmacovigilance research. However, it is difficult for pharmacists unfamiliar with programming to analyze large databases. Therefore, we developed an analysis method that does not require user programming.Methods: An analysis flow was created using KNIME, which allows for intuitive operation of the R language. In addition, the time required to calculate the signal scores was compared for the three personal computers (PCs) with different specifications.Results: The KNIME workflow for this analysis was created using as little R programming as possible and, in principle, only the functions contained within KNIME. Therefore, the KNIME workflow is redundant. However, the analysis results can be obtained instantly on PCs of any specifications. Furthermore, unlike previously reported applications for calculating safety signal scores from spontaneous reporting databases, the signal scores can be calculated using Bayesian statistical methods. Signal scores can be calculated for the Information Component, a measure for single drugs, and for the Ω shrinkage measure, a measure for drug-drug interactions.Conclusion: KNIME can be implemented at a low cost and can be used by users who are unaware of R language programming to calculate signal scores. Furthermore, hawse have demonstrated sufficient scalability of KNME to allow for a more advanced analysis compared with previously reported applications.