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The accurate measurement of free analyte concentrations within complex sample matrixes by pre-equilibrium solid-phase microextraction (SPME) has proven challenging due to variations in mass uptake kinetics. For the first time, the effects of the sample binding matrix and tortuosity on the kinetics of analyte extraction (from the sample to the SPME fiber) are demonstrated to be quantitatively symmetrical with those of the desorption of preloaded deuterated standards (from the fiber to the sample matrix). Consequently, kinetic calibration methods can be employed to correct for variation in SPME sampling kinetics, facilitating the application of pre-equilibrium SPME within complex sample systems. This approach was applied ex vivo to measure pharmaceuticals in fish muscle tissues, with results consistent with those obtained from equilibrium SPME and microdialysis. The developed method has the inherent advantages of being more accurate, precise, and reproducible, thus providing the framework for applications where rapid measurement of free analyte concentrations (within complicated sample matrixes such as biological tissues, sediment, and surface water) are required.

To address the challenge of measuring real-time analyte concentrations within dynamic systems, the temporal resolution of the solid-phase microextraction (SPME) approach has been investigated. A mass-uptake model for SPME within a dynamic system was developed and validated, with experimental factors affecting the temporal resolution (sampling time, agitation, SPME fiber dimensions, sample concentration and change rate, and instrument sensitivity) characterized. Calibration methods for time-resolved sampling in a dynamic system were compared. To demonstrate the efficacy of time-resolved SPME, this approach was successfully applied to investigate the binding kinetics between plasma proteins and pharmaceuticals, which verified a decrease in free pharmaceutical concentrations over time in the presence of bovine serum albumin. The current study provides the theoretical and logistical framework for applying SPME to the real-time measurement of dynamic systems, facilitating future SPME applications such as in vivo metabolomic studies.