Exploiting the information provided by (bio)chemical reaction networks has proved beneficial for process analysis and design. To this end, parameter uncertainties have to be included in the analysis and design of (bio)chemical processes to ensure reliable model-based results. The goal is to investigate the impact of parameter correlations on (bio)chemical reaction networks and parameter sensitivities. An efficient sensitivity analysis concept is demonstrated with two simulation studies, and the results indicate a significant impact of the parameter correlations on the derived parameter sensitivities and the model-based results in general.