Current problem:

Currently, metabolomics approaches are hampered by complex, time-consuming workflows that are difficult to implement in real-world scenarios. These existing workflows feature high costs for the consumables, required for sample pre-processing (most of which are not optimized for metabolomics platforms) and rely on very highly trained metabolomics experts to both to run the analytical instrumentation and interpret the resulting data. 

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