Accurate Quantitation of Unknowns in Non-Target LC-MS Analysis Using Experimentally Measured Response Factors

While LC-MS is a powerful tool for non-target chemical analysis, accurate quantitation of the detected species remains a significant challenge. Traditionally, detected chemical features have been quantified using the calibration curve and response factor of a known surrogate analyte, a practice called "semi-quantitation". This approach provides efficient quantitative estimates but comes with inherent uncertainty as any difference between the surrogate response factor and true response factor of the unknown manifests as quantitative error. The situation is compounded by the large variability of ESI response factors for homologous chemical species with even small structural differences.

This work explores the utility of using a series of increasing LC injection volumes to experimentally measure the response factors of unknowns detected in non-target analysis. The measured response factor can then be used to perform quantitation without the uncertainty associated with the "semi-quantitation" approach. Modern LC-MS systems are capable of making these series of varied volume injections in an automated way. Additionally, review of the response for a particular chemical feature across the injection series is an effective technique to filter out false-positive features.