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Automating DUID methods using robotics for rapid high throughput sample preparation – Analysis of Delta-9-Tetrahydrocannabinol and its major metabolite Delta-9-tetrahydrocannabinol acid in whole blood - 15/08/22

Doi : 10.1016/j.toxac.2022.06.154 
Charlotte Cattell , Aaron Mcmillan, Mark Evans, Susan Grosse, Mark Parkin
 Toxicology, Eurofins forensic services, London, United Kingdom 

Corresponding author.

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Riassunto

Aim/Objective

To fully automate, using liquid-handling robotics, a liquid chromatography tandem mass spectrometry method for the analysis of delta-9-tetrahydrocannabinol (THC) and delta-9-tetrahydrocannabinol acid (THC-A) in whole blood.

Introduction

Uptake in usage of ultra-high performance liquid chromatography (UHPLC) has led to development of methods with very fast (typically<5minutes) chromatographic run times used in the forensic toxicology laboratory. Nevertheless, use of whole blood for quantitative analysis continues to present challenges for delivering high throughput methods with rapid analysis times. Whole blood requires the use of solid phase extraction (SPE) for sample pre-treatment and preparation, which is time consuming and labour intensive. Recent developments in SPE technologies have produced 96-well format platforms that are used to extract greater number of samples in parallel and are ideally suitable for automated liquid handlers. With recent sensitivity increases in mass spectrometers, smaller volumes (<250μL per aliquot of blood) can be used for extraction in 96-well plates. This facilitates the use of robotic platforms together with rapid liquid chromatography tandem mass spectrometry (LC-MS/MS) methods to give truly high throughput and fast analytical methods, increasing method efficiencies, reducing human intervention and errors. Here we present the development, validation and implementation of a fully automated robotic sample preparation method for whole blood for analysis of THC and THC-A in UK driving under the influence of drugs (DUID) cases.

Method

Aliquots (200μL) of blank blood and casework samples previously dispensed into 96-well plates by a robotic system (BRAND) were prepared by the liquid handling system (Hamilton). Casework samples and blank blood were spiked with internal standard and blank blood samples were further spiked to produce calibrants and quality controls. The plate is then mixed with the addition of a cell lysis solution and the aliquots transferred to a protein/lipid depletion (PPT) plate (Waters). A positive pressure manifold was used to draw the solution through the PPT plate into a collection plate where the precipitate was dried. The precipitate was reconstituted and loaded by the Hamilton onto a C18 microelution SPE plate (Waters). Following extraction, the samples are reconstituted and the collection plate is placed in the autosampler for analysis. The LC-MS/MS method consists of a 2.1mm×50mm, 1.7μm, C18 column running a 4minute gradient of water and acetonitrile with 0.1% formic acid.

Results

The method was successfully validated, with LLOQs for THC and THC-A of 1μg/L and 5μg/L, respectively. Precision (%CV) for THC was<8% and<6% for THC-A. Accuracy was within 15% of the spiked concentration for THC and THC-A across all validation batches (n=11). The robotic platform was able to undertake sample pre-treatment and extraction in 3.5hours. A batch of 40 casework samples can be completed in 13hours including the LC-MS/MS run time.

Discussion

The introduction of this method to our laboratory has resulted in a significant increase in the speed for a sample to be processed and results obtained. We can prepare and extract double the amount of samples in less than half the time taken by our manual method. We have reduced the amount of sample used and decreased our turnaround times all for our customer's benefit.

Conclusion

Full automation of the sample preparation of whole blood samples using liquid handling robots can significantly improve laboratory throughput and capacity and efficiently utilise high speed chromatography providing rapid analysis from start to finish.

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© 2022  Pubblicato da Elsevier Masson SAS.
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Vol 34 - N° 3S

P. S100 - Settembre 2022 Ritorno al numero
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