Elsevier

Forensic Science International

Volume 244, November 2014, Pages 302-305
Forensic Science International

Technical Note
DryLab® optimised two-dimensional high performance liquid chromatography for differentiation of ephedrine and pseudoephedrine based methamphetamine samples

https://doi.org/10.1016/j.forsciint.2014.09.018Get rights and content

Highlights

  • Ephedrine and pseudoephedrine resolved in a rapid two dimensional separation.

  • A simple C18:C18 two dimensional separation was exploited.

  • The total analysis time was 15.75 min.

  • Drylab optimisation reduced 2D-HPLC development time significantly.

Abstract

In-silico optimised two-dimensional high performance liquid chromatographic (2D-HPLC) separations of a model methamphetamine seizure sample are described, where an excellent match between simulated and real separations was observed. Targeted separation of model compounds was completed with significantly reduced method development time. This separation was completed in the heart-cutting mode of 2D-HPLC where C18 columns were used in both dimensions taking advantage of the selectivity difference of methanol and acetonitrile as the mobile phases. This method development protocol is most significant when optimising the separation of chemically similar chemical compounds as it eliminates potentially hours of trial and error injections to identify the optimised experimental conditions. After only four screening injections the gradient profile for both 2D-HPLC dimensions could be optimised via simulations, ensuring the baseline resolution of diastereomers (ephedrine and pseudoephedrine) in 9.7 min. Depending on which diastereomer is present the potential synthetic pathway can be categorised.

Introduction

The current limitations of methamphetamine impurity profiling have been recently described by Stojanovska et al. [1] who stated that ‘future research is needed to address the knowledge gaps in regards to the manufacture of drugs of current interest’. Globally, Australia has one of the highest recorded consumption rates of methamphetamine (MA) with an estimated 1/20 residents having trailed it for recreational purposes and 395,000 reported uses in 2010 [2]. Gas and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS), infrared spectroscopy (IR) and capillary electrophoresis (CE) have traditionally been the primary analytical techniques used to generate chemical information from MA seizure samples [3], [4]. Other techniques have been used to study MA samples such as nuclear magnetic resonance spectroscopy (NMR) [5], ion mobility spectrometry [6], isotope ratio mass spectrometry (IRMS) [7] and high performance liquid chromatography (HPLC) [8], [9]. However, having the capacity to rapidly generate chemical fingerprints of seized MA, and its impurities, is of upmost importance to Australian law enforcement agencies in order to track and identify clandestine laboratories.

Characteristic to the synthetic process, the relative concentrations of by-products in the synthetic pathway are somewhat variable. This variability, when coupled with the extensive range of cutting agents commonly used in the production of MA, forms a chemical fingerprint that can be inspected by law enforcement agencies to individualise seizure samples – at times on a batch to batch basis.

The aim of this paper is employ the superior resolving power of two-dimensional high performance liquid chromatography (2D-HPLC) to screen seizure samples and create a chemical fingerprint of production impurities and cutting agents. Two-dimensional HPLC has the capacity to separate complex mixtures via two independent retention mechanisms, which allows for the resolution of otherwise co-eluting species [10]; 2D-HPLC has not previously been used for impurity profiling of MA samples. Simulation software has been used for the first time in order to rapidly optimise a 2D-HPLC separation. This paper outlines the use of the DryLab® software package [11] in order to efficiently optimise the gradient profile of a rapid 2D-HPLC separation of key components in a model methamphetamine seizure sample. This was completed in the heart-cutting mode where only co-eluting peaks were transferred to the second dimension, as identified by simulations. This type of optimisation will ultimately lead to improved chemical fingerprinting of clandestine drug seizure samples.

Section snippets

Standards and Samples

All standards (methamphetamine, ephedrine, pseudoephedrine, paracetamol, caffeine, benzyl alcohol, dimethyl sulfone, benzaldehyde, phenyl-2-propanone (P2P) and diphenylacetone) were obtained from Sigma–Aldrich (Castle Hill, NSW, Australia) and the National Measurement Institute, Australian Government (Port Melbourne, Vic, Australia). High performance liquid chromatography grade acetonitrile (ACN) and methanol was obtained from Ajax Finechem (Taren point, NSW, Australia); deionized water

Results and discussion

DryLab® [12] is a software tool that allows scientists to optimise several chromatographic variables in-silico to rapidly optimise a HPLC separation. It does this by taking the results of two gradient analyses with different gradient times, tG, to obtain values of k0 and S for each solute [13] When pre-elution and post-elution of the solutes can be ignored these parameters can be obtained by solving a set of simultaneous equations [13]:tg,1=t0b1log(2.3k0b1+1)+t0+tDtg,1=t0b1log(2.3k0b1+1)+t0+tD

Conclusions

There are many challenges in the development of optimised chromatographic separations which can be reduced by the use of in-silico optimisation. This study displays the effectiveness of this approach to the analysis of forensic samples highlighting an excellent match between an in-silico and real world separation of the same component mixture. This methodology allows the saving of time with a minimal amount of analytical runs being performed, subsequently saving resources in terms of laboratory

Acknowledgements

LMA acknowledges the support of a Deakin University postgraduate research award. The authors also wish to acknowledge funding from Deakin University's Strategic Research Centre (Chemistry and Biotechnology) and ARC linkage program LP130100681.

References (13)

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