Two and three way spectrophotometric-assisted multivariate determination of linezolid in the presence of its alkaline and oxidative degradation products and application to pharmaceutical formulation

Univariate versus multivariate spectrophotometric data analysis of triamterene and xipamide; a quantitative and qualitative greenly profiled comparative study

Triamterene (TRI) and xipamide (XIP) mixture is used as a binary medication of antihypertension which is considered as a major cause of premature death worldwide. The purpose of this research is the quantitative and qualitative analysis of this binary mixture by green univariate and multivariate spectrophotometric methods. Univariate methods were zero order absorption spectra method (D⁰) and Fourier self-deconvolution (FSD), as TRI was directly determined by D⁰ at 367.0 nm in the range (2.00-10.00 µg/mL), where XIP show no interference. While XIP was determined by FSD at 261.0 nm in the range (2.00-8.00 µg/mL), where TRI show zero crossing. Multivariate methods were Partial Least Squares, Principal Component Regression, Artificial Neural Networks, and Multivariate Curve Resolution-Alternating Least Squares. A training set of 25 mixtures with different quantities of the tested components was used to construct and evaluate them, 3 latent variables were displayed using an experimental design. A set of 18 synthetic mixtures with concentrations ranging from (3.00-7.00 µg/mL) for TRI and (2.00-6.00 µg/mL) for XIP, were used to construct the calibration models. A collection of seven synthetic mixtures with various quantities was applied to build the validation models. All the proposed approaches quantitative analyses were evaluated using recoveries as a percentage, root mean square error of prediction, and standard error of prediction. Strong multivariate statistical tools were presented by these models, and they were used to analyze the combined dosage form available on the Egyptian market. The proposed techniques were evaluated in accordance with ICH recommendations, where they are capable of overcoming challenges including spectral overlaps and collinearity. When the suggested approaches and the published one were statistically compared, there was no discernible difference between them. The green analytical method index and eco-scale tools were applied for assessment of the established models greenness. The suggested techniques can be used in product testing laboratories for standard pharmaceutical analysis of the substances being studied.

Simultaneous spectrophotometric determination of drug components from their dosage formulations

Spectrophotometry is a quick and reliable method for determining the composition of a variety of complex drug mixtures. Several mathematical models are available for the resolution of complex multicomponent UV spectra. UV spectrophotometric methods have the inherent capacity to resolve the interlaced spectra of complex mixtures quickly and appropriately, particularly for quantitative determination of components of mixture where several costly tools are not available. These methods also have the benefit of lower operational costs as they are operated using lesser amounts of analytical grade solvents and generate less waste. In this review, we discussed the theoretical background of different UV spectrometric methods for quantitative analysis of drug mixtures. The main focus of this review is to describe and report applications of extended Beer's law-based multicomponent analysis and to highlight the recent developments in the simultaneous determination of drug components from their complex mixtures.

Why should the pharmaceutical industry claim for the implementation of second-order chemometric models-A critical review

Today, pharmaceutical products are submitted to a large number of analytical tests, planned to either ensure or construct their quality. The official methods of analysis used to perform these determinations are very different in nature, but almost all demand the intensive use of reagents and manpower as major drawbacks. Thus, analytical development is continuously evolving to find fast and smart approaches. First-order chemometric models are well-known in the pharmaceutical industry, and are extensively used in many fields. Such is the impact of chemometric models that regulatory agencies include them in guidelines and compendia. However, the mention or practical application of higher-order models in the pharmaceutical industry is rather scarce. Herein, we try to bring a brief introduction to chemometric models and useful literature references, focusing on higher-order chemometric models (HOCM) applied to reduce manpower, reagent consumption, and time of analysis, without sacrificing accuracy or precision, while gaining selectivity and sensitivity. The advantages and drawbacks of HOCM are also discussed, and the comparison to first-order chemometric models is also analyzed. Along the work, HOCM are evidenced as a powerful tool for the pharmaceutical industry; moreover, its implementation is shown during several steps of production, such as identification, purity test and assay, and other applications as homogeneity of API distribution, Process Analytical Technology (PAT), Quality by Design (QbD) or natural product fingerprinting. Among these topics, qualitative and quantitative applications were covered. Experimental approaches of chemometrics coupled to several analytical techniques such as UV-vis, fluorescence and vibrational spectroscopies (NIR, MIR and Raman), and other techniques as hyphenated-chromatography and electrochemical techniques applied to production and analysis are discussed throughout this work.

Chemometrics Approaches in Forced Degradation Studies of Pharmaceutical Drugs

Chemometrics is the chemistry field responsible for planning and extracting the maximum of information of experiments from chemical data using mathematical tools (linear algebra, statistics, and so on). Active pharmaceutical ingredients (APIs) can form impurities when exposed to excipients or environmental variables such as light, high temperatures, acidic or basic conditions, humidity, and oxidative environment. By considering that these impurities can affect the safety and efficacy of the drug product, it is necessary to know how these impurities are yielded and to establish the pathway of their formation. In this context, forced degradation studies of pharmaceutical drugs have been used for the characterization of physicochemical stability of APIs. These studies are also essential in the validation of analytical methodologies, in order to prove the selectivity of methods for the API and its impurities and to create strategies to avoid the formation of degradation products. This review aims to demonstrate how forced degradation studies have been actually performed and the applications of chemometric tools in related studies. Some papers are going to be discussed to exemplify the chemometric applications in forced degradation studies.

A critical review of HPLC-based analytical methods for quantification of Linezolid

Linezolid is a synthetic antimicrobial agent belonging to the oxazolidinone class. Since its approval in the year 2000 until now, linezolid remains the main representative drug for the oxazolidinone class of drugs, which is used in therapy due to its unique mode of action, which involves inhibition of protein synthesis. As linezolid holds great importance in antimicrobial therapy, it is necessary to compile the various analytical methods that have been reported in the literature for its analysis. Analytical techniques used for pharmaceutical analyses and therapeutic drug monitoring play an important role in comprehending the aspects regarding bioavailability, bioequivalence, and therapeutic monitoring during patient follow-ups. Even though linezolid has had the approval for clinical use for more than 18 years now, most of the analytical methods for its determination reported in the scientific literature are the ones which utilize HPLC. Therefore, the present review provides a summary of the HPLC-based methods used in the determination and quantification of linezolid in different matrices since the time of its discovery.

Linezolid-A Review of Analytical Methods in Pharmaceuticals and Biological Matrices

Bacterial resistance to antibiotics is a growing phenomenon in the world. Considering the relevance of antimicrobials for population and the reduction in the registration of new antimicrobials by regulatory agencies, proper quality control is required to minimize the spread of bacterial resistance and ensure the effectiveness of a treatment, as well as safety for the patient. The recent addition to the antimicrobial world is the oxazolidinone classes of antibiotics, especially useful to treat infections caused by Gram-positive bacteria. Eperezolid and linezolid (LIN) are the two members of the oxazolidinone class of antibiotics. LIN was the first oxazolidinone approved by the Food and Drug Administration. The present review focuses on the analytical methods for the assessment of LIN in pharmaceuticals and biological matrices. The critical validation parameters like the linearity, limit of detection, limit of quantification are discussed for the individual method. Also the critical quality attributes like the sensitivity and the sample preparation techniques for bioanalytical methods are also discussed. Furthermore, some future trends that can be incorporated in the determination of similar drugs are also suggested.

Multiway analysis methods applied to the fluorescence excitation-emission dataset for the simultaneous quantification of valsartan and amlodipine in tablets

In this study, excitation-emission matrix datasets, which have strong overlapping bands, were processed by using four different chemometric calibration algorithms consisting of parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares for the simultaneous quantitative estimation of valsartan and amlodipine besylate in tablets. In analyses, preliminary separation step was not used before the application of parallel factor analysis Tucker3, three-way partial least squares and unfolded partial least squares approaches for the analysis of the related drug substances in samples. Three-way excitation-emission matrix data array was obtained by concatenating excitation-emission matrices of the calibration set, validation set, and commercial tablet samples. The excitation-emission matrix data array was used to get parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares calibrations and to predict the amounts of valsartan and amlodipine besylate in samples. For all the methods, calibration and prediction of valsartan and amlodipine besylate were performed in the working concentration ranges of 0.25-4.50μg/mL. The validity and the performance of all the proposed methods were checked by using the validation parameters. From the analysis results, it was concluded that the described two-way and three-way algorithmic methods were very useful for the simultaneous quantitative resolution and routine analysis of the related drug substances in marketed samples.

A chemometric-assisted method for the simultaneous determination of malachite green and crystal violet in water based on absorbance-pH data generated by a homemade pH gradient apparatus

An attractive method of generating second-order data was developed by a dropping technique to generate pH gradient simultaneously coupled with diode-array spectrophotometer scanning. A homemade apparatus designed for the pH gradient. The method and the homemade apparatus were used to simultaneously determine malachite green (MG) and crystal violet (CV) in water samples. The absorbance-pH second-order data of MG or CV were obtained from the spectra of MG or CV in a series of pH values of HCl-KCl solution. The second-order data of mixtures containing MG and CV that coexisted with interferents were analyzed using multidimensional partial least-squares with residual bilinearization. The method and homemade apparatus were used to simultaneously determine MG and CV in fish farming water samples and in river ones with satisfactory results. The presented method and the homemade apparatus could serve as an alternative tool to handle some analysis problems.

Monitoring simultaneous photocatalytic-ozonation of mixture of pharmaceuticals in the presence of immobilized TiO2 nanoparticles using MCR-ALS: Identification of intermediates and multi-response optimization approach

The present study has focused on the degradation of a mixture of three pharmaceuticals, i.e. methyldopa (MDP), nalidixic acid (NAD) and famotidine (FAM) which were quantified simultaneously during photocatalytic-ozonation process. The experiments were conducted in a semi-batch reactor where TiO2 nanoparticles (crystallites mean size 8nm) were immobilized on ceramic plates irradiated by UV-A light in the proximity of oxygen and/or ozone. The surface morphology and roughness of the bare and TiO2-coated ceramic plates were analyzed using scanning electron microscopy (SEM) and atomic force microscopy (AFM). An analytical methodology was successfully developed based on both recording ultraviolet-visible (UV-Vis) spectra during the degradation process and a data analysis using multivariate curve resolution with alternating least squares (MCR-ALS). This methodology enabled the researchers to obtain the concentration and spectral profiles of the chemical compounds which were involved in the process. A central composite design was used to study the effect of several factors on multiple responses namely MDP removal (Y1), NAD removal (Y2) and FAM removal (Y3) in the simultaneous photocatalytic-ozonation of these pharmaceuticals. A multi-response optimization procedure based on global desirability of the factors was used to simultaneously maximize Y1, Y2 and Y3. The results of the global desirability revealed that 8mg/L MAD, 8mg/L NAD, 8mg/L FAM, 6L/h ozone flow rate and a 30min-reaction time were the best conditions under which the optimized values of various responses were Y1=95.03%, Y2=84.93% and Y3=99.15%. Also, the intermediate products of pharmaceuticals generated in the photocatalytic-ozonation process were identified by gas chromatography coupled to mass spectrometry.