Stability indicating methods for the analysis of cefprozil in the presence of its alkaline induced degradation product

Application of signal processing techniques for the spectroscopic analysis of dolutegravir and lamivudine: a comparative assessment and greenness appraisal

HIV treatment has greatly improved over the years, with the introduction of antiretroviral drugs that target the virus and suppress its replication. Dolutegravir and lamivudine are two such antiretroviral drugs that are commonly used in HIV treatment regimens. Herein, three spectrophotometric methods manipulating ratio spectra were developed for the simultaneous analysis of dolutegravir and lamivudine in their binary mixtures. These methods include mathematical processing stages like ratio difference method or signal processing approaches such as the first derivative of the ratio spectra, and continuous wavelet transform. The developed spectrophotometric methods exploit the characteristic spectral differences between dolutegravir and lamivudine in order to quantify them simultaneously. These methods have shown promising results in terms of sensitivity and selectivity as validated per the ICH guidelines. Moreover, these methods offer a straightforward and economical alternative to more intricate analytical methodologies like high-performance liquid chromatography. By incorporating the analytical eco-scale and AGREE for greenness evaluation of the proposed methods, we can further ensure that these techniques are effective and environmentally friendly, aligning with the principles of green chemistry. This evaluation will provide a comprehensive understanding of the environmental friendliness of these spectrophotometric methods in pharmaceutical analysis.

Augmented least squares, a powerful chemometric approach for the spectroscopic analysis of the antiretroviral therapy abacavir, lamivudine and dolutegravir in their ternary mixture

Augmented least squares models such as concentration residual augmented classical least squares (CRACLS) and spectral residual augmented classical least squares (SRACLS) are powerful chemometric approaches that can be applied for spectroscopic analysis of many pharmaceutical compounds. Herein, both CRACLS and SRACL have been employed for UV spectral analysis of three antiretroviral therapy namely abacavir (ACV), lamivudine (LMV) and dolutegravir (DTG) in their ternary mixture. A partial factorial design has been utilized for calibration set construction then both CRACLS and SRACLS models have been optimized regarding the number of iterations and principal components, respectively, using a leave-one-out cross-validation procedure. It was found that a higher number of iterations and principal components were required for modelling the minor component DTG indicating more augmentation procedures to improve the models' accuracy. Validation of the proposed models was performed using external validation set of 13 mixtures and different validation parameters have been evaluated regarding models' predictive abilities. Both models showed excellent performance for analyzing ACV and LMV with relative root mean square error of prediction (RRMSEP) below 2 %. However, higher RRMSEP values around 5 % were observed for the minor component DTG suggesting that these models should be utilized with caution when analyzing minor components in mixtures. Furthermore, the suggested models have been applied for analyzing ACV, LMV and DTG in their pharmaceutical formulation and excellent agreement was observed between the suggested models and the reported chromatographic method posing these models as powerful chemometric approaches for quality control analysis of many pharmaceutical compounds.

Eco-Friendly UV-Spectrophotometric Methods Employing Magnetic Nano-Composite Polymer for the Extraction and Analysis of Sexual Boosters in Adulterated Food Products: Application of Computer-Aided Design

BACKGROUND

Solid phase extraction (SPE) techniques, based on computationally designed magnetic-based multi-targeting molecular imprinted polymer (MT-MIP), combined with UV spectrophotometric approaches provide advantages in the examination of counterfeit samples.

OBJECTIVE

The current work describes an innovative and sustainable methodology for the simultaneous determination of tadalafil (TAD) and dapoxetine hydrochloride (DAP) in aphrodisiac counterfeit products (honey and instant coffee) utilizing SPE exploiting MT-MIP. Additionally, an innovative UV spectrophotometric method capable of resolving TAD in its pharmaceutical binary mixtures with DAP was developed. A novel computational approach was implemented to tailor the synthesis and design of the MT-MIP particles.

METHODS

We applied a newly developed UV spectrophotometric method which was based on a Fourier self-deconvolution (FSD) method coupled with the isoabsorptive point for determination of TAD and DAP in pharmaceutical dosage form. We also applied an SPE process based on MT-MIP designed particles, assisting in the analysis of both drugs in counterfeit food samples. The SPE process and the UV spectroscopic methodology were assessed regarding their greenness using the pioneering green analytical procedure index (GAPI), analytical greeness including sample preparation (AGREEprep) and AGREE tools. The synthesized MT-MIP particles were characterized by scanning electron microscopy and energy-dispersive x-ray spectroscopy.

RESULTS

The suggested spectrophotometric methods revealed a wide linear concentration range of 2-50 µg/mL with lower LODs in the range of 0.604-0.994 µg/mL. Additionally, the suggested method demonstrated the utmost sensitivity and eco-friendliness for their target in its mixed dosage form and counterfeit food products.

CONCLUSION

The SPE process and the developed analytical UV spectroscopic methodology were validated as per the ICH guidelines, and were found to be suitable for overseeing some counterfeiting activities in commercially available honey and instant coffee aphrodisiac products.

HIGHLIGHTS

An SPE method based on MT-MIP magnetic-based polymer and a UV spectroscopic method were successfully developed for analysis of TAD and DAP in different matrices.

Earth friendly spectrophotometric methods based on different manipulation approaches for simultaneous determination of aspirin and omeprazole in binary mixture and pharmaceutical dosage form: Comparative statistical study

Aspirin and omeprazole combining has proven their effectiveness clinically in the treatment and prevention of cardiovascular diseases in patient with gastric diseases and gastric ulcers. Simultaneous determination of omeprazole and aspirin in their combination is a challenge due to the overlapping spectra of these drugs. Six smart and different spectrophotometric methods were developed for the analysis of omeprazole and aspirin in binary mixture and pharmaceutical dosage form. These smart methods characterized by simplicity and accuracy. The first two methods based on minimal mathematical data processing based on the zero order absorption spectra were; dual wavelength and advanced absorbance subtraction methods. The third method is first and second derivative spectrophotometric method that based on derivative spectra. The last three methods based on ratio spectra manipulation are named; ratio difference, mean centering and derivative ratio spectrophotometric methods. The linearity range of omeprazole was 2-20 μg/mL for dual wavelength method and 2-30 μg/mL for the other ones, while aspirin showed a good linearity over a range of 2.5-30 μg/mL for all methods. The correlation coefficients were greater than 0.999. The results of the developed methods are statistically compared with each other and with the results of the reported HPLC method showing no significant difference. The greenness of the developed methods was assessed using eco-scale scoring method revealing excellent greenness of the applied methods. This spectrophotometric methods is more sensitive and greener with comparing by the reported one so, these developed methods are considered eco-friendly to the environment.

Analysis of the ternary antiretroviral therapy dolutegravir, lamivudine and abacavir using UV spectrophotometry and chemometric tools

Herein, a simple spectrophotometric method coupled with chemometric techniques i.e. partial least square (PLS) and genetic algorithm (GA) were utilized for the simultaneous determination of the vital ternary antiretroviral therapy dolutegravir (DTG), lamivudine (LMV), and abacavir (ACV) in their combined dosage form. Calibration (25 samples) and validation (13 samples) sets were prepared for these drugs at different concentrations via implementing partial factorial experimental designs. The zero order UV spectra of calibration and validation sets were measured and then subjected for further chemometric analysis. Partial least squares with/without variable selection procedures i.e. genetic algorithm (GA) were utilized to untangle the UV spectral overlapping of these mixtures. Cross-validation and external validation methods were applied to compare the performance of these chemometric techniques in terms of accuracy and predictive abilities. It was found that six latent variables were optimum for modelling DTG, four latent variables for modelling LMV and three latent variables for modelling ACV. Although, good recoveries with prompt predictive ability were attained by these PLS, GA-PLS showed better analytical performance owing to its capability to remove redundant variables i.e. the number of absorbance variables have been reduced to about 21-29%. The proposed chemometric methods can be reliably applied for simultaneous determination of DTG, LMV, and ACV in their laboratory prepared mixtures and pharmaceutical preparation posing these chemometric methods as worthy and substantial analytical tools in in-process testing and quality control analysis of many antiretroviral pharmaceutical preparations.

Advanced eco-friendly UV spectrophotometric approach for resolving overlapped spectral signals of antihypertensive agents in their binary and tertiary pharmaceutical dosage form

Cardiovascular disorders are among the foremost causes of death worldwide, especially hypertension, a silent killer syndrome that requires multiple drug therapy for proper management. This work presents novel and green spectrophotometric methods for the concurrent analysis of Amlodipine (AML), Telmisartan (TEL), Hydrochlorothiazide (HCTZ), and Chlorthalidone (CLO) in their pharmaceutical dosage form. The suggested methods were Fourier-self deconvolution, amplitude factor, and first derivative methods developed and validated for the simultaneous determination of a tertiary mixture of AML, TEL, and HCTZ in TELVAS 3D 80 mg tablet and a binary mixture of TEL and CLO in TELMIKIND-CT 40 tablets. The investigated methods revealed limits of detection 0.7283 µg/ml for AML and ranging from 0.0121 to 0.0433, 0.1547 to 0.1767 µg/ml and 0.0578 to 0.1262 µg/ml for TEL, HCTZ, and CLO, respectively.The greenness of the suggested techniques was examined by an eco-scale scoring method called the penalty points, which revealed that the methods were excellent green regarding several parameters as reagents, instrument, and waste safety. The introduced methods' validity was investigated by resolving prepared laboratory mixtures containing different AML, TEL, HCTZ, or TEL and CLO ratios. Furthermore, the introduced methods were ensured by the standard addition technique. Finally, the obtained results were statistically compared by the reported spectrophotometric methods, showing no significant difference concerning precision and accuracy.

Spectrophotometric Determination of Aspirin and Omeprazole in the presence of Salicylic Acid as a Degradation Product: A Comparative Evaluation of Different Univariate/Multivariate Post Processing Algorithms

BACKGROUND

A recent combination of aspirin (ASP) and omeprazole (OMP) has been presented in a fixed dosage form for treatment of many CVD, particularly in patients with gastric diseases. However, ASP is very sensitive to degradation into salicylic acid (SAL) as its main degradation product. Hence, it is very important to develop methods for the determination of ASP and OMP in the presence of SAL.

OBJECTIVE

In this study, UV spectrophotometry assisted by different univariate/multivariate post processing algorithms have been presented for quantitative determination of ASP, OMP and SAL without any prior separation.

METHODS

The univariate/multivariate algorithms include double divisor ratio difference and double divisor mean centering as the univariate approaches while the multivariate methods include principal component regression (PCR) and partial least squares (PLS) models. Validation of the univariate methods was done according to the ICH guidelines while the multivariate models were validated using external validation set.

RESULTS

The univariate algorithms displayed excellent regression and validation capabilities in terms of linearity, accuracy, precision, and selectivity. Regarding PCR and PLS, the number of latent variables were carefully optimized, and the model's validation criteria displayed excellent recoveries and lower errors of prediction.

CONCLUSION

Our findings indicate that the developed methods were comparable to the only reported chromatographic methods but with much shorter analysis time and simplicity.

HIGHLIGHTS

Overall, this report presents the first spectrophotometric methods applied for determination of possible combination of ASP, OMP, and SAL, and poses theses methods as valuable analytical tools in in-process testing and quality control analysis.

Multivariable Manipulation of Spectrophotometric Data with Genetic Algorithm Selection for Novel Quantitative Resolution of Five Antiviral Drugs in Their Pharmaceutical Products

BACKGROUND

In many real-world situations there are many components in a mixture that produce an enormous amount of information.

OBJECTIVE

The main task is to build up balanced models that convert these data into meaningful information to deal with. Hence, different chemometric models were applied for the analysis of data obtained from a mixture containing sofosbuvir, ledipasvir, velpatasvir, daclatasvir, and valacyclovir that were recently used internationally for their antiviral activity.

METHODS

Partial Least Squares, Spectral Residual Augmented Classical Least Squares, and Concentration Residual Augmented Classical Least Squares designs were applied with and without variable selection procedure [Genetic Algorithm (GA)]. The methods were used for the quantitative analysis of the drugs in laboratory prepared mixtures and real market sample through handling the UV spectral data.

RESULTS

Robust models were obtained by applying GA. The proposed methods were found to be rapid, simple, and required no preliminary separation steps.

CONCLUSION

These models can be used on a routine basis in quality control laboratories or factories giving competitor results to those obtained by the reported methods.

HIGHLIGHTS

The proposed models offer a powerful analytical alternative for laboratories that consider economic strategies in their requirements.

An evaluation of different bio-inspired feature selection techniques on multivariate calibration models in spectroscopy

Herein, two new swarm intelligence based algorithms namely; grey wolf optimization (GWO) and antlion optimization (ALO) algorithms were presented, for the first time, as variable selection tools in spectroscopic data analysis. In order to assess the performance of these algorithms, they were applied along with the recently introduced firefly algorithm (FFA) and the well-established genetic algorithm (GA) and particle swarm optimization (PSO) algorithm on four different spectroscopic datasets of varying sizes and nature (UV and IR). Partial least squares (PLS) regression models were built using the selected variables by these algorithms along with the full spectral data as the reference models. The obtained results prove that the ALO and GWO optimization algorithms select variables in most cases less than GA and PSO while keeping the PLS performance almost the same. Accordingly, these algorithms can be successfully used for variable selection in spectroscopic data analysis.

Smart UV spectrophotometric methods based on simple mathematical filtration for the simultaneous determination of celecoxib and ramipril in their pharmaceutical mixtures with amlodipine: A comparative statistical study

Two newly introduced pharmaceutical mixtures of amlodipine/celecoxib and amlodipine/ramipril were developed to manage hypertension and the associated osteoarthritis. The current work presents three newly developed UV spectrophotometric methods depending on minimal mathematical manipulations on the zero-order spectrum namely: absorption correction, induced dual-wavelength, and Fourier self deconvoluted method; for the simultaneous determination of celecoxib and ramipril in their pharmaceutical combined dosage forms with amlodipine. In absorption correction and induced dual-wavelength method, celecoxib and ramipril were determined at 253 and 222 nm for absorption correction and (251-270 nm) and (222-230 nm) for induced dual-wavelength method, respectively from the zero-order spectrum after calculating the absorption correction and equality factors for amlodipine. Amlodipine itself was determined at 361 nm from the zero-order spectrum in both methods. In Fourier self deconvoluted method, celecoxib and amlodipine zero-order spectra were deconvoluted, using the spectrophotometer software built-in Fourier wavelet function, and then was determined at 360 and 269 nm, respectively. The proposed methods were simple, accurate, and sensitive requiring minimal mathematical manipulations saving the time needed for analysis. The methods were linear over the range of (5-60 μg/ml), (5-30 μg/ml), and (5-110 μg/ml) for each of amlodipine, celecoxib, and ramipril, respectively. The limit of detection was in the range of (0.5781-0.7132 μg/ml) for amlodipine, (0.6497-1.0450 μg/ml) for celecoxib, and (0.0001-0.0003 μg/ml) for ramipril that indicated the sensitivity of these suggested methods. All methods were validated as per ICH recommendations regarding linearity, range, accuracy, precision, and selectivity. A statistical comparative study executed for the proposed methods with each other and with the reported methods showed no significant difference between the proposed methods and the reported methods.

Insights into flibanserin oxidative stress degradation pathway: in silico – in vitro toxicity assessment of its degradates

Characterization of the degradation products of pharmaceutical drugs is essential to assess their safety.

Analysis of quinary therapy targeting multiple cardiovascular diseases using UV spectrophotometry and chemometric tools

Herein, UV spectrophotometry assisted by multivariate chemometric analysis have been presented for quantitative determination of complex quinary therapy containing atenolol, ramipril, hydrochlorothiazide, simvastatin and aspirin without any prior separation. Such combination is very useful for treating various cardiovascular diseases (CVD) including high blood pressure, hypercholesterolemia in addition to its antiplatelet aggregating activity. Calibration (15 samples) and validation (10 samples) sets were prepared of different concentrations for these drugs via implementing partial factorial experimental design. The zero order UV spectra of these sets were recorded and then subjected for further chemometric analysis. Partial least square (PLS) with/without variable selection procedure i.e. genetic algorithm (GA) were employed to untangle the UV spectral overlapping of these mixtures. The performance of these chemometric techniques were compared in terms of accuracy and predictive abilities using cross-validation and external validation methods. It was found that PLS provides good recoveries with prompt predictive ability albeit GA-PLS exhibited better analytical performance owing to its capability to remove redundant variables i.e. the number of absorbance variables had been reduced to about 19-28%. The developed methods allowed reliable determination of such complex therapy in its laboratory prepared mixtures and pharmaceutical preparation within comparable results to those reported by HPLC method, posing these chemometric methods as valuable and indispensable analytical tools in in-process testing and quality control analysis of many pharmaceutical compounds targeting CVD.

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.

Full spectrum and selected spectrum based chemometric methods for the simultaneous determination of Cinnarizine and Dimenhydrinate in laboratory prepared mixtures and pharmaceutical dosage form

Three chemometric methods namely, concentration residual augmented classical least squares (CRACLS), spectral residual augmented classical least squares (SRACLS) and partial least squares (PLS) were applied for the simultaneous quantitative determination of Cinnarizine and Dimenhydrinate in their binary mixtures. All techniques were applied with and without variable selection using genetic algorithm (GA) resulting in six models (CRACLS, GA-CRACLS, SRACLS, GA-SRACLS, PLS, GA-PLS). These models were applied for the simultaneous determination of the drugs in their laboratory prepared mixtures and pharmaceutical dosage form via handling their UV spectral data. It was found that GA based models are simpler and more robust than those built with the full spectral data. The proposed models were found to be simple, fast and require no preliminary separation steps; so they can be used for the routine analysis of this binary mixture in quality control laboratories.