An automated online three-phase electro-extraction setup with machine-vision process monitoring hyphenated to LC-MS analysis

Abstract

Sample preparation is a labor-intensive and time-consuming procedure, especially for the bioanalysis of small-volume samples with low-abundant analytes. To minimize losses and dilution, sample preparation should ideally be hyphenated to downstream on-line analysis such as liquid chromatography-mass spectrometry (LC-MS). In this study, an automated three-phase electro-extraction (EE) method coupled to machine vision was developed, integrated with a robotic autosampler hyphenated to LC-MS. Eight model compounds, i.e. amitriptyline, clemastine, clomipramine, haloperidol, loperamide, propranolol, oxeladin, and verapamil were utilized for the optimization and evaluation of the automated EE setup. The stability of automated EE was evaluated by monitoring the acceptor droplet size by machine vision and recording the current during EE. A Design of Experiment approach (Box-Behnken design) was utilized to optimize the critical parameters of the EE method, i.e., the ratio of formic acid in the sample to acceptor phase, extraction voltage, and extraction time. The developed quadratic models showed good fitness (p < 0.001, R2 > 0.95). Automated EE could be achieved in less than 2 min with enrichment factors (EF) up to 387 and extraction recoveries (ER) up to 97% for academic samples. Finally, the optimized EE method was successfully applied to both spiked human urine and plasma samples with low-concentration (50 ng mL−1) analytes and a low starting sample volume of 20 μL of plasma and urine in 10-fold diluted samples. The developed automated EE setup is easy to operate, provides a fast extraction method for analytes from volume-limited biological samples, and is hyphenated with on-line LC-MS analysis. Therefore, this method can provide fast and automated sample preparation to solve bottlenecks in high-throughput bioanalysis workflows.