Chromatographic retention behaviour, modelling and optimization of a UHPLC-UV separation of the regioisomers of the Novel Psychoactive Substance (NPS) methoxphenidine (MXP)

A comparative study of the predictive performance of different descriptor calculation tools: Molecular-based elution order modeling and interpretation of retention mechanism for isomeric compounds from METLIN database

In the pharmaceutical industry, the need for analytical standards is a bottleneck for comprehensive evaluation and quality control of intermediate and end products. These are complex mixtures containing structurally related molecules. In this regard, chromatographic peak annotation, especially for critical pairs of isomers and closest structural analogs, can be supported by using a Quantitative Structure Retention Relationship (QSRR) approach. In our study, we investigated the fundamental basis of the reversed-phase (RP) retention mechanism for 1141 isomeric compounds from the METLIN SMRT dataset. Nine different descriptor calculation tools combined with different feature selection methods (genetic algorithm (GA), stepwise, Boruta) and machine learning (ML) approaches (support vector machine (SVM), multiple linear regression (MLR), random forest (RF), XGBoost) were applied to provide a reliable molecular structure-based interpretation of RP retention behaviour of the isomeric compounds. Strict internal and external validation metrics were used to select models with the best predictive capabilities (rtest > 0.73, order of elution > 60 %). For the developed models, mean absolute errors were in the range of 60 to 110 s. Stepwise and GA showed the most suitable performance as descriptor selection methods, while SVM and XGBoost modeling gave satisfactory predictive characteristics in most cases. Validation performed on the published experimental data for structurally related pharmaceutical compounds confirmed the best accuracy of MLR modeling in combination with GA feature selection of general physico-chemical properties. The resulting models will be useful for the prediction of separation and identification of structurally related compounds in pharmaceutical analysis, providing a simultaneous understanding of the interaction mechanisms leading to their retention under RP conditions.

Retention correlation and orthogonality between reversed phase countercurrent chromatography and liquid chromatography based on solvent strength

Correlation of elution performance between reversed phase countercurrent chromatography and liquid chromatography was investigated using five selected natural components. Theoretical guidance for orthogonality of two-dimensional countercurrent chromatography and liquid chromatography was proposed. The difference in retention behavior between countercurrent chromatography and liquid chromatography was studied when the mobile phase was composed of methanol and water by measuring the partition behavior of five selected compounds in two typical biphasic solvent systems composed of n-hexane-ethyl acetate-methanol-water and chloroform-methanol-water. An orthogonal diagram between countercurrent chromatography and liquid chromatography was obtained by normalized treatment of the measured partition coefficients and capacity factors. The experimental results showed that each biphasic solvent system used for countercurrent chromatography had a high orthogonality with liquid chromatography when a specific volume ratio was used.

Metal-Chelating Peptides Separation Using Immobilized Metal Ion Affinity Chromatography: Experimental Methodology and Simulation

Metal-Chelating Peptides (MCPs), obtained from protein hydrolysates, present various applications in the field of nutrition, pharmacy, cosmetic etc. The separation of MCPs from hydrolysates mixture is challenging, yet, techniques based on peptide-metal ion interactions such as Immobilized Metal Ion Affinity Chromatography (IMAC) seem to be efficient. However, separation processes are time consuming and expensive, therefore separation prediction using chromatography modelling and simulation should be necessary. Meanwhile, the obtention of sorption isotherm for chromatography modelling is a crucial step. Thus, Surface Plasmon Resonance (SPR), a biosensor method efficient to screen MCPs in hydrolysates and with similarities to IMAC might be a good option to acquire sorption isotherm. This review highlights IMAC experimental methodology to separate MCPs and how, IMAC chromatography can be modelled using transport dispersive model and input data obtained from SPR for peptides separation simulation.

Recent applications of retention modelling in liquid chromatography

Recent applications of retention modelling in liquid chromatography (2015–2020) are comprehensively reviewed. The fundamentals of the field, which date back much longer, are summarized. Retention modeling is used in retention‐mechanism studies, for determining physical parameters, such as lipophilicity, and for various more‐practical purposes, including method development and optimization, method transfer, and stationary‐phase characterization and comparison. The review focusses on the effects of mobile‐phase composition on retention, but other variables and novel models to describe their effects are also considered. The five most‐common models are addressed in detail, i.e. the log‐linear (linear‐solvent‐strength) model, the quadratic model, the log–log (adsorption) model, the mixed‐mode model, and the Neue–Kuss model. Isocratic and gradient‐elution methods are considered for determining model parameters and the evaluation and validation of fitted models is discussed. Strategies in which retention models are applied for developing and optimizing one‐ and two‐dimensional liquid chromatographic separations are discussed. The review culminates in some overall conclusions and several concrete recommendations.

Interpol review of controlled substances 2016-2019

This review paper covers the forensic-relevant literature in controlled substances from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.

Rapid Identification of Novel Psychoactive and Other Controlled Substances Using Low-Field 1H NMR Spectroscopy

An automated approach to the collection of ¹H NMR (nuclear magnetic resonance) spectra using a benchtop NMR spectrometer and the subsequent analysis, processing, and elucidation of components present in seized drug samples are reported. An algorithm is developed to compare spectral data to a reference library of over 300 ¹H NMR spectra, ranking matches by a correlation-based score. A threshold for identification was set at 0.838, below which identification of the component present was deemed unreliable. Using this system, 432 samples were surveyed and validated against contemporaneously acquired GC-MS (gas chromatography-mass spectrometry) data. Following removal of samples which possessed no peaks in the GC-MS trace or in both the ¹H NMR spectrum and GC-MS trace, the remaining 416 samples matched in 93% of cases. Thirteen of these samples were binary mixtures. A partial match (one component not identified) was obtained for 6% of samples surveyed whilst only 1% of samples did not match at all.

1,2-Diarylethylamine- and Ketamine-Based New Psychoactive Substances

While phencyclidine (PCP) and ketamine remain the most well-studied and widely known dissociative drugs, a number of other agents have appeared since the late 1950s and early 1960s, when the pharmacological potential of this class was first realized. For example, hundreds of compounds have been pursued as part of legitimate research efforts to explore these agents. Some of these found their way out of the research labs and onto illicit markets of the 1960s and following decades as PCP analogs. Other "illicit analogs" apparently never appeared in the scientific literature prior to their existence on clandestine markets, thus originating as novel innovations in the minds of clandestine chemists and their colleagues. Like so much else in this world, new technologies changed this dynamic. In the 1990s individuals separated by vast geographical distances could now communicate nearly instantaneously with ease through the Internet. Some individuals used this newly found opportunity to discuss the chemistry and psychoactive effects of dissociative drugs as well as to collaborate on the design and development of novel dissociative compounds. Similar to modern pharmaceutical companies and academic researchers, these seekers tinkered with the structure of their leads pursuing goals such as improved duration of action, analgesic effects, and reduced toxicity. Whether all these goals were achieved for any individual compound remains to be seen, but their creations have been let out of the bag and are now materialized as defined compositions of matter. Moreover, these creations now exist not only in and of themselves but live on further as permutations into various novel analogs and derivatives. In some cases these compounds have made their way to academic labs where potential clinical applications have been identified. These compounds reached wider distribution when other individuals picked up on these discussions and began to market them as "research chemicals" or "legal highs". The result is a continuously evolving game that is being played between legislatures, law enforcement, and research chemical market players. Two structurally distinct classes that have appeared as dissociative-based new psychoactive substances (NPS) are the 1,2-diarylethylamines and β-keto-arylcyclohexylamines. Examples of the former include diphenidine and various analogs such as fluorolintane and N-ethyl-lanicemine, and examples of the latter are analogs of ketamine such as methoxetamine, deschloroketamine, and 2-fluoro-2-deschloroketamine. The subject of this chapter is the introduction to some of the dissociative NPS from these classes and their known pharmacology that have emerged on the market in recent years.