Re-assessment and optimisation of an organic acid extraction method for automation

Abstract

Sample preparation is a necessary prerequisite for GC/MS analysis of urinary organic acids for clinical diagnosis of inborn errors of metabolism (IEM). The sample clean-up step in the analytical process poses a challenge. It involves the isolation of the analytes of interest by an extraction process from a complex matrix to one that is more suitable for the analytical platform. As opposed to a fully automated and high throughput sample preparation protocol, the existing in-house urinary organic acid extraction method is still performed manually. It is a labour-intensive and time consuming, requires multiple exhaustive pipetting steps and uses large amounts of toxic solvents that can be hazardous to health. Literature documents the progress made in miniaturising and automating the solvent extraction, but scarce literature is available on how this has been applied to the urinary extraction of organic acids. Thus, the development of a method that can be fully automated would improve the sample throughput and eliminate the intense labour and most of the other setbacks associated with manual extraction. The aim of the study was to reassess the in-house organic acid extraction method and optimise it for automation. The experimental workflow involved the selection of an initial suitable miscible solvent for rapid extraction of organic acids and one that would enable better extraction of very polar organic acids. This was followed by the selection of a suitable immiscible solvent that would ensure good isolation of organic acids, quick evaporation and clear phase separation that would render centrifugation unnecessary. The solvent ratios and volumes were optimised and miniaturised to small volumes of solvents. The miniaturised organic acid protocol was translated into a fully automated extraction procedure on a liquid AutoSampler. The automated method was validated for linearity, imprecision, recovery and inaccuracy. A two-phase extraction system using two optimal solvents, acetonitrile and ethyl acetate, were found to be efficient in the extraction of urinary organic acids. It enabled efficient and rapid extraction. The analytical range of the method for most of the analytes was established to be between 1 – 500 mg/l. The correlation coefficient (r) of all analytes was generally > 0.99, with two exceptions. The analytical ranges of the specific analytes showed that the test results within these ranges are reliable and can be reported. The repeatability was generally below 20%, but had higher within laboratory precision. The automated method’s overall imprecision was better than the in-house method. The inaccuracy of the method was determined by a method comparison experiment with ERNDIM EQAS samples for quantitative organic acids. The mean of the test results was compared to the mean of all the laboratories. The proportional systematic error of the method ranged from -0.18 to 2.06. The constant systematic error for the analytes was -5.75 and 5.66. The total error of the method determined demonstrated a reduction in random and systematic errors when compared to the current in-house manual method. It was also noted that the correlation coefficient between the new method and the expected results was substantially better when compared to the current in-house method and by implication that the regression model fit was substantially better. This creates an opportunity for bias correction through the use of extraction factors, instrument response factors, the use of external calibration curves or reassignment of standard/calibrator concentrations for the new method as opposed to the current in house method where this is not an option. Based on the findings in this study, it was concluded that an automated procedure for LLE of urinary organic acids was successfully developed. The goal of having a method that could give consistent extraction and meet the criteria for automation was achieved. All the extraction steps were optimised and the method proved to have good extraction efficiencies for organic acids and to improve on the performance of the existing in-house method.