Multi-matrix assay of the first melatonergic antidepressant agomelatine by combined liquid chromatography-fluorimetric detection and microextraction by packed sorbent

Greenness assessment of microextraction techniques in therapeutic drug monitoring

Aim: In this study, we evaluated the greenness and whiteness scores for microextraction techniques used in therapeutic drug monitoring. Additionally, the cons and pros of each evaluated method and their impacts on the provided scores are also discussed. Materials & methods: The Analytical Greenness Sample Preparation metric tool and white analytical chemistry principles are used for related published works (2007-2023). Results & conclusion: This study provided valuable insights for developing methods based on microextraction techniques with a balance in greenness and whiteness areas. Some methods based on a specific technique recorded higher scores, making them suitable candidates as green analytical approaches, and some others achieved high scores both in green and white areas with a satisfactory balance between principles.

Miniaturized sample preparation methods for saliva analysis

Saliva, as the first body fluid encountering with the exogenous materials, has good correlation with blood and plays an important role in bioanalysis. However, saliva has not been studied as much as the other biological fluids mainly due to restricted access to its large volumes. In recent years, there is a growing interest for saliva analysis owing to the emergence of miniaturized sample preparation methods. The purpose of this paper is to review all microextraction methods and their principles of operation. In the following, we examine the methods used to analyze saliva up to now and discuss the potential of the other microextraction methods for saliva analysis to encourage research groups for more focus on this important subject area.

Current trends on microextraction by packed sorbent – fundamentals, application fields, innovative improvements and future applications

MEPS, the acronym of microextraction by packed sorbent, is a simple, fast and user- and environmentally-friendly miniaturization of the popular solid-phase extraction technique (SPE).

Enantioseparation and determination of asenapine in biological fluid micromatrices by HPLC with diode array detection

Asenapine is a recent drug approved in the European Union for the treatment of bipolar disorder. An original approach has been developed for asenapine analysis in patients treated with the drug, including miniaturized microsampling procedures, separation and quantitation of drug enantiomers. An original enantioselective method based on high-performance liquid chromatography with diode array detection was developed and applied to the determination of asenapine enantiomer levels in innovative haematic samples: four micromatrices have been tested, two based on dried matrix spots (dried blood spots and dried plasma spots) and two based on volumetric absorptive microsampling (from blood and plasma). Chiral separation was achieved on a cellulose-tris(3,5 dimethylphenylcarbamate) column, with a mobile phase containing bicarbonate buffer and acetonitrile. The method was validated with satisfactory results of linearity and precision on all matrices that showed also a significant performance in terms of stability, feasibility and reliability, when compared to fluid plasma sampling, handling and processing. Among micromatrices, both volumetric absorptive microsampling types were superior to dried matrix spots in terms of data reproducibility and correspondence with plasma levels. The bioanalytical approach proposed herein provides for the first time a chiral high-performance liquid chromatographic method for the determination of asenapine enantiomers, coupled to a very effective microsampling strategy.

Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

Quantitative analysis of drugs in biological matrices by HPLC hyphenated to fluorescence detection

An overview of the state-of-the art in HPLC coupled with fluorescence detection is presented. Over the last 20 years, the increasing number of methodological papers on this topic (4082 between 1994 and 2004 and 7725 between 2004 and 2014) is testament to its utility in bioanalytical applications. Compared with conventional UV absorbance detection used in HPLC, fluorescence detection can greatly enhance the sensitivity leading to limits of detection similar to those obtained with mass spectrometry, offering researchers a sensitive, robust and relatively inexpensive instrumental method. This work will focus on the analysis of pharmaceutical compounds in different biological matrices, either naturally fluorescent or derivatized with a fluorescent agent, and some of them chiral. Therapeutic applications, sample preparation and derivatization, sensitivity for each example are described.

Current advances in biosampling for therapeutic drug monitoring of psychiatric CNS drugs

Many CNS drugs are effective for the treatment of psychiatric disorders. Psychotropic drugs work differently, thus clinical outcomes for many patients may be insufficient. For this reason it could be useful the measurement of drug levels for clinical decision-making. Analytical goals in therapeutic drug monitoring (TDM) should be established by selecting the appropriate biological matrix. The aim of this review is to highlight the usefulness of TDM for antiepileptics, antidepressants and antipsychotics, with a focus on current advances in biosampling. The literature on TDM was reviewed up to March 2015. An overview on the use of alternative biological matrices is provided to address the current issues and advances in the field of biosampling for psychiatric CNS drug TDM.