High-throughput experimentation is nowadays a well-known technique useful to design large arrays of experiments on microscale, accelerating the exploration of reaction conditions in order to find the most appropriate combination of reaction constituents efficiently. General HTE workflows include the use of HPLC and UPLC, frequently with MS detection to generate results quickly. Additional structural information provided by HRMS can be useful to properly identify reaction products. However, the large amount of data generated in HTE can be overwhelming if scientists do not have the proper software devoted to this task. In the present work, an automatic workflow covering completely the HRMS processing and analysis steps using WebChembase application server will be shown. Routine analytical works such as purity control can be quite time demanding due to the data manipulation that the scientists have to do in order to collect the required information and report the results of the analysis. In this presentation we will show a time saver automation solution using as example an automated purity control analysis monitoring the mass accuracy of the analyte and its response to UV. The complete automatic workflow is divided in two steps: workflow preparation and workflow execution. During the workflow preparation step, the experimental variables will be defined: conditions (time points, solvent, ...), informative variables needed later for reporting (experimenter name, experiment date, …) and/or automatic checks to monitor the processed data, i.e. mass accuracy or UV purity. Additionally, a set of process settings to be applied in the data processing (UV wavelength, noise thresholds, instrument brand and acquisition type, …) should be defined. To start the execution step, the user has to import a sample list including the experiments to process, which is automatically parsed by the system and triggers the data processing using MassChemSite. Once the data is processed, data will be automatically analyzed according to the information given during the experiment definition, adding labels associated to the specified checks. Finally, experimental results can be reviewed, shared and reported. During all the process, raw data is persisted on the database as well as the traceability of the data manipulation. The same procedure can be extended to other workflows including metabolite identification or quantification studies using MALDI-TOF instrumentation.

Automation of HRMS data processing in purity control routine analysis

ACS Spring 2022

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