Robust Optimization of Chaotropic Chromatography Assay for Lamotrigine and its Two Impurities in Tablets

Development and robust optimization of the RP-HPLC method for the determination of riociguat and its four impurities in tablets using the AQbD approach

The aim of this work was to develop and optimize the RP-HPLC method for the qualitative and quantitative analysis of riociguat and its four impurities using the Analytical Quality by Design concept. Risk assessment was carried out as a combination of Ishikawa diagram - Control, Noise and eXperimental - Failure mode and effect analysis from where critical method parameters for this study were selected (i.e. acetonitrile content in the mobile phase, concentration of ammonium acetate in aqueous part of mobile phase and column temperature). Their effects on critical method attributes (retention factor of the last eluting peak and separation of critical peak pairs) were further analyzed using the Design of Experiments methodology. The Design Space was defined as the area in which the robustness of the qualitative performance of the developed method is confirmed. Monte Carlo simulations were applied to achieve the defined quality by propagating the error resulting from the calculated coefficients of the mathematical models. The optimal chromatographic conditions included separation on an Xterra® RP18 (150 × 4.6 mm, 3.5 µm) column with a mobile phase consisting of 34 % of acetonitrile and 66 % of aqueous 15 mM ammonium acetate solution pH 5.5, at a column temperature of 36°C. The flow rate was 1 mL/min, the detection wavelength was 210 nm, while the injection volume was 20 µL. Validation of the developed method was performed, which confirmed its reliability in determining the content of riociguat and its four impurities in tablets.

Predicting liquid chromatography-electrospray ionization/mass spectrometry signal from the structure of model compounds and experimental factors; case study of aripiprazole and its impurities

A priori estimation of analyte response is crucial for the efficient development of liquid chromatography-electrospray ionization/mass spectrometry (LC-ESI/MS) methods, but remains a demanding task given the lack of knowledge about the factors affecting the experimental outcome. In this research, we address the challenge of discovering the interactive relationship between signal response and structural properties, method parameters and solvent-related descriptors throughout an approach featuring quantitative structure-property relationship (QSPR) and design of experiments (DoE). To systematically investigate the experimental domain within which QSPR prediction should be undertaken, we varied LC and instrumental factors according to the Box-Behnken DoE scheme. Seven compounds, including aripiprazole and its impurities, were subjected to 57 different experimental conditions, resulting in 399 LC-ESI/MS data endpoints. To obtain a more standard distribution of the measured response, the peak areas were log-transformed before modeling. QSPR predictions were made using features selected by Genetic Algorithm (GA) and providing Gradient Boosted Trees (GBT) with training data. Proposed model showed satisfactory performance on test data with a RMSEP of 1.57 % and a of 96.48 %. This is the first QSPR study in LC-ESI/MS that provided a holistic overview of the analyte's response behavior across the experimental and chemical space. Since intramolecular electronic effects and molecular size were given great importance, the GA-GBT model improved the understanding of signal response generation of model compounds. It also highlighted the need to fine-tune the parameters affecting desolvation and droplet charging efficiency.

Spectrophotometric determination of lamotrigine in plasma samples: Ultrasound-assisted emulsification-microextraction based on a hydrophobic deep eutectic solvent followed by back-extraction

In this study, sensitive detection of lamotrigine in human plasma samples was realized at a low cost approach through ultrasound-assisted emulsification-microextraction based on using a hydrophobic deep eutectic solvent followed by back-extraction (USAEME-DES-BE) method. After extraction, detection and quantification of lamotrigine were done by spectrophotometry in the UV region. The hydrophobicity of the deep eutectic solvent not only eliminates the need of the third solvent as an emulsifying agent but also helps to retrieve lamotrigine from the DES by back-extraction to another aqueous phase. The back extraction process allowed the drug to be measured in the UV region. Central composite design in combination with a desirability function approach was applied for the optimization of the USAEME-DES-BE procedure. Essential factors in the method efficiency were discussed, such as back-extraction solution, time of back-extraction, the ratio of DES components, pH, the volume of DES, salt concentration, and sonication time. The method exhibited a wide dynamic linear range from 0.5 to 10 µg mL^-1 and a limit of detection of 0.15 μg mL^-1. The established method was successfully applied to determine lamotrigine in human plasma samples with satisfactory relative recoveries.

Chaotropic chromatography method development for the determination of aripiprazole and its impurities following analytical quality by design principles

In this paper, development of robust and reliable chaotropic chromatography method for the determination of aripiprazole and its impurities, following Analytical Quality by Design principles is presented. The efficient baseline separation and accurate determination of aripiprazole and its four impurities from tablets were set as Analytical Target Profile. In line with it, the influence of Critical Method Parameters (acetonitrile content, concentration of perchloric acid in water phase, and column temperature) on predefined Critical Method Attributes (separation of the critical pair of peaks, retention of the first and last eluting peak) was investigated with aid of the Central Composite Design. Further on Design Space, where Critical Method Parameters meet predefined acceptance limits with a high level of probability (π ≥ 85%), was computed as a result of performed Monte Carlo simulations. A normal operating conditions corresponding to 34% of acetonitrile, 66% of 42.5 mM perchloric acid, and column temperature at 35°C were selected from created Design Space. Robustness testing of the quantitative performances of the developed method was conducted combining Plackett-Burman design with alias matrix approach. Through the additional validation testing, reliability of the developed method for the use in the routine practice was completely confirmed.