In the evaluation of high-resolution mass spectrometric data a considerable amount of time and computational power can be spent on matching molecular formulas to the neutral mass of measured ions. During the evaluation of multiple samples using the classical combinatory approach based on molecular building blocks and nested loops, the time consuming step of calculating the molecular mass may be repeated for the same molecular formula multiple times. To avoid repetitive calculations, we implemented a formula library based search approach into our data evaluation pipeline. In our approach, the step of calculating molecular formulas and corresponding masses is limited to the process of building a library. The library calculation requires an a priori definition of the maximum molecular mass and the isotopes contained, e.g. formulas in the mass range of ≤ 650 Da consisting of 12C, 1H, 14N, 16O, 31P, 32S, 13C, and 34S. The subsequent matching process is based on scrolling through a mass-sorted formula library and comparison with a mass-sorted list of measured peaks. The time required for processing is primarily a function of the size of the formula library. Consequently, at constant library size, the matching algorithm becomes more efficient with increasing number of supplied peaks (up to 4700 formula assignments s-1 on a standard workstation) and is thus particularly suited for processing large datasets. We implemented the matching algorithm into our R Shiny based interactive, evaluation software UltraMassExplorer (UME). In combination with the graphical user interface of UME, our algorithm provides the basis for fast and reproducible (re-)analysis of complete sample sets with currently up to 400,000 peaks in a user friendly, integrated environment. The code of our open-source algorithm is available through the UME website [1]. References [1] www.awi.de/en/ume