Spectrofluorometric determination of futibatinib in human plasma and pharmaceutical formulations.

Futibatinib is a powerful inhibitor of fibroblast growth factor receptors that impedes its phosphorylation and subsequently leading to a reduction in in cell viability across various cell lines. Futibatinib was approved for initial use as an effective treatment for several diseases, including non-small cell lung cancer and breast cancer. Herein, a novel selective fluorescence probe was created for futibatinib quantification in various matrices, including pharmaceutical formulation and human plasma. The technique primarily depends on futibatinib's chemical conversion into a fluorescent product through a reaction with trimethylamine and bromoacetyl bromide. The created fluorescent probe exhibits maximum emission peak at 338 nm upon excitation at 248 nm. The method provided a low detection limit of 0.120 ng/mL and maintained a linear concentration-dependent relationship across the range of 1-200 ng/mL. High sensitivity, accuracy and precision were demonstrated for futibatinib quantification in pharmaceutical formulation and spiked plasma matrix by the method, which was validated in accordance with ICH requirements.

Determination of valsartan and pitavastatin using synchronous spectrofluorimetry and augmented least squares chemometric models: A comparative study with greenness and blueness assessment.

Hypertension and hyperlipidemia are two common conditions that require effective management to reduce the risk of cardiovascular diseases. Among the medications commonly used for the treatment of these conditions, valsartan and pitavastatin have shown significant efficacy in lowering blood pressure and cholesterol levels, respectively. In this study, synchronous spectrofluorimetry coupled to chemometric analysis tools, specifically concentration residual augmented classical least squares (CRACLS) and spectral residual augmented classical least squares (SRACLS), was employed for the determination of valsartan and pitavastatin simultaneously. The developed models exhibited excellent predictive performance with relative root mean square error of prediction (RRMSEP) of 2.253 and 2.1381 for valsartan and pitavastatin, respectively. Hence, these models were successfully applied to the analysis of synthetic samples and commercial formulations as well as plasma samples with high accuracy and precision. Besides, the greenness and blueness profiles of the determined samples were also evaluated to assess their environmental impact and analytical practicability. The results demonstrated excellent greenness and blueness scores with AGREE score of 0.7 and BAGI score of 75 posing the proposed method as reliable and sensitive approach for the determination of valsartan and pitavastatin with potential applications in pharmaceutical quality control, bioanalytical studies, and therapeutic drug monitoring.

Spectrophotometric determination of celecoxib and tramadol in the new approved formulated dosage form using principle component regression assistive model.

Celecoxib and tramadol have been combined in a novel FDA-approved medication to address acute pain disorders requiring opioid treatment when other analgesics proved either intolerable or ineffective. The absorbance spectra of celecoxib and tramadol exhibit significant overlap, posing challenges for their individual quantification. This study introduces a spectrophotometric quantification approach for celecoxib and tramadol using a principle component regression assistive model to assist resolving the overlapped spectra and quantifying both drugs in their binary mixture. The model was constructed by establishing calibration and validation sets for the celecoxib and tramadol mixture, employing a five-level, two-factor experimental design, resulting in 25 samples. Spectral data from these mixtures were measured and preprocessed to eliminate noise in the 200-210 nm range and zero absorbance values in the 290-400 nm range. Consequently, the dataset was streamlined to 81 variables. The predicted concentrations were compared with the known concentrations of celecoxib and tramadol, and the errors in the predictions were evidenced calculating root mean square error of cross-validation and root mean square error of prediction. Validation results demonstrate the efficacy of the models in predicting outcomes; recovery rates approaching 100 % are demonstrated with relative root mean square error of prediction (RRMSEP) values of 0.052 and 0.164 for tramadol and celecoxib, respectively. The selectivity was further evaluated by quantifying celecoxib and tramadol in the presence of potentially interfering drugs. The model demonstrated success in quantifying celecoxib and tramadol in laboratory-prepared tablets, producing metrics consistent with those reported in previously established spectrophotometric methods.

Unveiling the altered metabolic pathways induced by nivolumab in non-small cell lung cancer via GC-MS metabolomics approach coupled with multivariate analysis.

This research investigates the effects of the immunotherapeutic agent nivolumab on the metabolism of lung cancer cells (NCI-H1975) using GC-MS metabolomic profiling. Multivariate analysis such as unsupervised PCA and supervised OPLS-DA along with univariate analysis and pathway analysis were employed to explore the metabolomic data and identify altered metabolic pathways induced by nivolumab treatment. The study revealed distinct metabolic alterations in cancer cells, linked to proliferative and survival advantages, such as enhanced glycolysis, increased glutaminolysis, and modified amino acid metabolism. Key findings indicate elevated levels of glycolysis-related metabolites (glycine, alanine, pyruvate, and lactate) and TCA cycle intermediates (succinate, fumarate, malate) in cancer cells, with a significant decrease following nivolumab treatment. Additionally, lower levels of aspartic acid and citrate in cancer cells imply altered nucleotide synthesis and fatty acid production essential for tumor growth. Treatment with nivolumab also reduced oleic acid levels, indicative of its effect on disrupted lipid metabolism. Our research shows nivolumab's potential to modify metabolic pathways involved in lung cancer progression, suggesting its dual role in cancer therapy: as an immune response modulator and a metabolic pathway disruptor.

Spectrofluorometric determination of calcium in the human nasal secretions investigating the association with olfactory function.

Ionic microenvironment of the nasal secretions especially calcium ions play essential role in the olfactory transmission. However, there is a critical need to determine the free calcium levels in healthy people's nasal secretions in contrast to those of patients with olfactory impairment. A selective spectrofluorometric method was created to quantify nasal calcium levels utilizing its quenching ability to the fluorescence of the functionalized carbon quantum dots. The surface of carbon quantum dots was functionalized with calcium ionophore A23187 and ion association complex, calcium phosphotungstate, to improve the selectively to quantify calcium ions. The functionalized carbon quantum dots exhibited a concentration-dependent fluorescence quenching upon interaction with calcium ions. Different factors influencing the quenching process were done to provide efficient analytical process. The new method, demonstrated accurate calcium determination over the concentration range of 200-4000 ng/mL. The suggested technique was used to measure the calcium in the nasal secretions of both healthy people and patients with olfactory impairment. The findings revealed significantly higher calcium levels in the patient with olfactory dysfunction (healthy vs. patient; 735 ± 20 ng/mL vs. 2987 ± 37 ng/mL, p < 0.05).

Synchronous spectrofluorimetry and chemometric modeling: A synergistic approach for analyzing simeprevir and daclatasvir, with application to pharmacokinetics evaluation.

Simeprevir and daclatasvir represent a cornerstone in the management of Hepatitis C Virus infection, a global health concern that affects millions of people worldwide. In this study, we propose a synergistic approach combining synchronous spectrofluorimetry and chemometric modeling i.e. Partial Least Squares (PLS-1) for the analysis of simeprevir and daclatasvir in different matrices. Moreover, the study employs firefly algorithms to further optimize the chemometric models via selecting the most informative features thus improving the accuracy and robustness of the calibration models. The firefly algorithm was able to reduce the number of selected wavelengths to 47-44% for simeprevir and daclatasvir, respectively offering a fast and sensitive technique for the determination of simeprevir and daclatasvir. Validation results underscore the models' effectiveness, as evidenced by recovery rates close to 100% with relative root mean square error of prediction (RRMSEP) of 2.253 and 2.1381 for simeprevir and daclatasvir, respectively. Moreover, the proposed models have been applied to determine the pharmacokinetics of simeprevir and daclatasvir, providing valuable insights into their distribution and elimination patterns. Overall, the study demonstrates the effectiveness of synchronous spectrofluorimetry coupled with multivariate calibration optimized by firefly algorithms in accurately determining and quantifying simeprevir and daclatasvir in HCV antiviral treatment, offering potential applications in pharmaceutical formulation analysis and pharmacokinetic studies for these drugs.

Development of a highly sensitive and green first-derivative synchronous fluorescence spectroscopic method for the simultaneous quantification of telmisartan and rosuvastatin: Greenness metric assessment and application to a pharmacokinetic study in rats.

Hypertension and hyperlipidemia frequently coexist and are correlated with elevated cardiovascular adverse outcomes. Fixed dose combination tablets containing antihypertensive and antihyperlipidemic drugs have the potential to improve patient compliance. Telmisartan and rosuvastatin fixed dose combination tablet has been recently formulated. This study provided the first fluorescence spectroscopic method for simultaneously quantifying telmisartan and rosuvastatin in tablet dosage form and plasma. The native fluorescence spectra of telmisartan and rosuvastatin completely overlapped, making direct measurement unachievable. However, through the implementation of synchronous fluorescence measurements of telmisartan and rosuvastatin at a Δλ = 60, distinct narrow bands were observed at 358 nm and 375 nm, respectively. Regrettably, the challenge of overlapping remained unresolved. Nevertheless, by converting these synchronous spectra into first-order spectra, the problem of overlapping was completely resolved. This conversion also allowed for the selective quantification of telmisartan and rosuvastatin at 374 nm and 358 nm, respectively. The validity of this method was confirmed in accordance with ICH guidelines, yielding satisfactory results in terms of the validation characteristics. The method demonstrated linear relationships between the response and the studied drugs concentrations in working range of 50-1000 ng/mL for telmisartan and 100-2000 ng/mL for rosuvastatin. The described methodology was applied for the pharmacokinetic study of telmisartan and rosuvastatin in rat plasma after a single oral dose of 4 mg/kg telmisartan and 50 mg/kg rosuvastatin. Pharmacokinetic analyses revealed a moderate drug-drug interaction between the two drugs, which was not considered to be clinically significant. Moreover, the described method was assessed in terms of sensitivity and environmental sustainability against three previously documented methods. The comparison effectively underscores the supremacy of the proposed technique over the documented techniques.

Nitrogen-doped carbon quantum dots as a novel treatment for black fungal bone infections (Mucormycosis): in vitro and in vivo study.

Most fungal bone and joint infections (arthritis) are caused by Mucormycosis (Mucor indicus). These infections may be difficult to treat and may lead to chronic bone disorders and disabilities, thus the use of new antifungal materials in bone disorders is vital, particularly in immunocompromised individuals, such as those who have contracted coronavirus disease 2019 (COVID-19). Herein, we reported for the first time the preparation of nitrogen-doped carbon quantum dots (N/CQDs) and a nitrogen-doped mesoporous carbon (N/MC) using a quick micro-wave preparation and hydrothermal approach. The structure and morphology were analysed using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and surface area analyser. Minimum inhibitory concentration (MIC), disc diffusion tests, minimum fungicidal concentration (MFC) and antifungal inhibitory percentages were measured to investigate the antifungal activity of N/CQDs and N/MC nanostructures. In addition to the in vivo antifungal activity in rats as determined by wound induction and infection, pathogen count and histological studies were also performed. According to in vitro and in vivo testing, both N/CQDs with small size and N/MC with porous structure had a significant antifungal impact on a variety of bone-infecting bacteria, including Mucor infection. In conclusion, the present investigation demonstrates that functional N/CQDs and N/MC are effective antifungal agents against a range of microbial pathogenic bone disorders in immunocompromised individuals, with stronger and superior fungicidal activity for N/CQDs than N/MC in vitro and in vivo studies.

Therapeutic implications of dapagliflozin on the metabolomics profile of diabetic rats: A GC-MS investigation coupled with multivariate analysis.

BACKGROUND: Diabetes mellitus is a complex metabolic disorder with systemic implications, necessitating the search for reliable biomarkers and therapeutic strategies. This study investigates the metabolomics profile alterations in diabetic rats, with a focus on the therapeutic effects of Dapagliflozin, a drug known to inhibit renal glucose reabsorption, using Gas Chromatography-Mass Spectrometry analysis. METHODS: A GC-MS based metabolomics approach combined with multivariate and univariate statistical analyses was utilized to study serum samples from a diabetic model of Wistar rats, treated with dapagliflozin. Metabolomics pathways analysis was also performed to identify the altered metabolic pathways associated with the disease and the intervention. RESULTS: Dapagliflozin treatment in diabetic rats resulted in normalized levels of metabolites associated with insulin resistance, notably branched-chain and aromatic amino acids. Improvements in glycine metabolism were observed, suggesting a modulatory role of the drug. Additionally, reduced palmitic acid levels indicated an alleviation of lipotoxic effects. The metabolic changes indicate a restorative effect of dapagliflozin on diabetes-induced metabolic perturbations. CONCLUSIONS: The comprehensive metabolomics analysis demonstrated the potential of GC-MS in revealing significant metabolic pathway alterations due to dapagliflozin treatment in diabetic model rats. The therapy induced normalization of key metabolic disturbances, providing insights that could advance personalized diabetes mellitus management and therapeutic monitoring, highlighting the utility of metabolomics in understanding drug mechanisms and effects.

Spectrofluorimetric determination of vitamin D in the serum of autistic and healthy children using functionalized graphene quantum dots.

Vitamin D is one of the most essential nutrients for brain development, and deficiencies during pregnancy and early childhood development might be associated with autism. Regular monitoring of serum 25-hydroxyvitamin D3 level could help in early diagnosis and therapy. Analytical measurement of serum 25-hydroxyvitamin D3 level using the traditional matrix-matched calibration technique yields inaccurate results due to absence of serum matrix free from 25-hydroxyvitamin D3. The aim of this work was to develop a validated spectrofluorimetric methodology based on the standard addition approach for quantifying 25-hydroxyvitamin D3 levels in real serum samples of autistic children. The spectrofluorimetric methodology utilizes functionalized graphene quantum dots as a fluorescent probe for selective quantification of 25-hydroxyvitamin D3 level, which is based on measuring the quenching properties of 25-hydroxyvitamin D3 on a fluorescent probe. The standard addition approach exhibits a minimal matrix interference since it identically utilizes the same matrix of each study sample for creating its own calibration curve. The method was validated using the guidelines outlined in ICH M10 draft for endogenous compounds quantification. The method was successfully applied for quantifying the serum 25-hydroxyvitamin D3 levels in autistic and healthy children, and autistic children had significantly lower serum 25-hydroxyvitamin D3 levels (with a mean ± SD of 23.80 ± 17.19) when compared to healthy children (with a mean ± SD of 50.13 ± 18.74, P < 0.001). These results suggested an association between vitamin D deficiency and autism.

A fluorescence chemo sensor approach for determination of finerenone in pharmaceutical formulation and human plasma: Method development and validation.

Finerenone, a non-steroidal mineralocorticoid receptor antagonist, has gained recent approval for treating cardiovascular and kidney-related conditions. Herein, an innovative fluorescence chemo sensor was developed for the determination of finerenone in the pharmaceutical dosage form and the plasma matrix. The method is basically based on chemical transformation of finerenone into a fluorescent product through sequential reactions. This transformation occurs through a sequence of steps involving the interaction of finerenone with trimethylamine, resulting in the formation of a nucleophilic intermediate that subsequently reacts with bromoacetyl bromide to form fluorescent product, (S)-N-(2-bromoacetyl)-4-(4-cyano-2-methoxyphenyl)-5-ethoxy-2,8-dimethyl-1,4-dihydro-1,6-naphthyridine-3-carboxamide. The formed fluorescent product exhibits defined emission peak at 338 nm when excited at 248 nm. Significant concentration-dependent fluorescence enhancement was obtained enabling precise finerenone determination in the pharmaceutical formulation and plasma matrix. The method was optimized and validated providing sensitive determination over linearity range of 1-200 ng/mL with a lower limit of detection at 0.280 ng/mL. This strategy provides an efficient, economical substitute and straightforward, more sensitive analytical method for finerenone assessment in various matrices, in contrast to the previously published method, high-performance liquid chromatography-tandem mass spectrometry, which is expensive and time-consuming.

Derivative spectroscopy and wavelet transform as green spectrophotometric methods for abacavir and lamivudine measurement.

Herein, two different sustainable and green signal processing spectrophotometric approaches, namely, derivative spectroscopy and wavelet transform, have been utilized for effective measurement of the antiretroviral therapy abacavir and lamivudine in their pharmaceutical formulations. These methods were used to enhance the spectral data and differentiate between the absorption bands of abacavir and lamivudine in order to accurately measure their concentrations. For determining abacavir and lamivudine, the first derivative spectrophotometric method has been applied to the zero-order and ratio spectra of both drugs. The same approach has been tested using the continuous wavelet transform method where a second order 2.4 of rbio and bior wavelet families were found to be optimum for measuring both drugs. Validation of the proposed methods affirmed their reliability in terms of linearity over the concentration range 1.5-30 µg/mL and 1.5-36 µg/mL for abacavir and lamivudine, respectively, precision (RSD < 2 %), and accuracy with mean recoveries ranging between 98 % and 102 %. Additionally, these spectrophotometric methodologies were applied to real pharmaceutical preparations and yielded results congruent with a prior chromatographic method. Most prominently, the proposed methods stood out for their greenness and sustainability with 97 points as evaluated by the analytical eco-scale method and a score value of 0.79 as analyzed by AGREE method, thereby making them suitable for resource-limited settings and highlighting the potential for broader application of green analytical methods in pharmaceutical analysis.

Efficient and eco-friendly detection of gabapentin using nitrogen-doped carbon quantum dots: an analytical and green chemistry approach.

This study presents the development of an eco-friendly and highly selective mitrogen-doped carbon quantum dot based sensor (N-CQDs) for the detection of gabapentin - a commonly misused drug. A detailed characterization of N-CQDs spectral features and their interaction with gabapentin is provided. The optimal conditions for sensing, including pH value, buffer volume, N-CQDs concentration, and incubation time, were established. The results showed excellent fluorescence quenching at 475 nm (λex = 380 nm) due to the dynamic quenching mechanism, and the sensor demonstrated excellent linearity in the 0.5-8.0 µg mL-1 concentration range with correlation coefficients of more than 0.999, a limit of detection (LOD) of 0.160 and limit of quantification (LOQ) of 0.480 µg mL-1. The accuracy of the proposed sensor was acceptable with a mean accuracy of 99.91 for gabapentin detection. In addition, precision values were within the acceptable range, with RSD% below 2% indicating good repeatability and reproducibility of the sensor. Selectivity was validated using common excipients and pooled plasma samples. The proposed sensor accurately estimated gabapentin concentration in commercial pharmaceutical formulations and spiked plasma samples, exhibiting excellent comparability with previously published methods. The 'greenness' of the sensing system was evaluated using the Analytical GREEnness calculator, revealing low environmental impact and strong alignment with green chemistry principles with a greenness score of 0.76. Thus, the developed N-CQDs-based sensor offers a promising, eco-friendly, and effective tool for gabapentin detection in various situations, ranging from clinical therapeutics to forensic science.

Electronic, mechanical, and thermal properties of zirconium dioxide nanotube interacting with poly lactic-co-glycolic acid and chitosan as potential agents in bone tissue engineering: insights from computational approaches.

For the first time, the interaction of the Poly lactic-co-glycolic acid (PLGA) and Chitosan (CH) with Zirconium dioxide (ZrO2) nanotube was studied using density functional theory (DFT). The binding energies of the most stable configurations of PLGA and CH monomers absorbed on ZrO2 were calculated using density functional theory (DFT) methods. The obtained results indicate that both CH and PLGA monomers were chemisorbed on the surface of ZrO2. The interaction between PLGA and ZrO2 is stronger than that of CH due to its shorter equilibrium interval and higher binding energy. In addition, the electronic density of states (DOS) of the most stable configuration was computed to estimate the electronic properties of the PLGA/CH absorbed on ZrO2. Also, the molecular dynamics (MD) simulations were computed to investigate the mechanical properties of all studied compounds in individual and nanocomposite phases. MD simulation revealed that the shear and bulk moduli of PLGA, CH as well as Young's modulus increase upon interacting with the ZrO2 surface. As a result, the mechanical properties of PLGA and CH are improved by adding ZrO2 to the polymer matrix. The results showed that the elastic modulus of PLGA and CH nanocomposites decreased with increasing temperature. These findings indicate that PLGA-ZrO2 nanocomposites have mechanical and thermal properties, suggesting that they could be exploited as potential agents in biomedical sectors such as bone tissue engineering and drug delivery.Communicated by Ramaswamy H. Sarma.

Innovative spectrofluorometric method for determination of harmaline and harmine in different matrices.

Harmaline and harmine are naturally occurring closely related ß-carboline alkaloids found in Peganum and Banisteriopsis plants. They have historical significance in traditional practices due to their potential psychoactive and therapeutic properties. Herein, a highly sensitive spectrofluorometric method was developed for the quantifying of harmaline and harmine in diverse matrices, including pure forms, seed samples, and spiked plasma. The procedures lie in addressing the challenge of overlapping fluorescence spectra exhibited by harmaline and harmine through the incorporation of hydroxypropyl-ß-cyclodextrin, altering their chemical properties and fluorescence characteristics. Synchronous fluorescence measurements coupled with first derivative mathematical technique make it possible to distinguish between the harmaline and harmine at 419 and 456 nm, respectively. The method effectiveness is demonstrated through spectral analysis, optimization of the measurement conditions, adopting validation parameters and application to the pure form, seed samples and spiked human plasma. This methodology facilitates accurate determination of these alkaloids over the concentration range of 10─200 ng/mL. Thus, the developed approach provides a robust mean for the precise determination of harmaline and harmine, contributing to analytical chemistry's ongoing efforts to address complex challenges in quantification across diverse matrices.

Prospects of earthworm coelomic fluid as a potential therapeutic agent to treat cancer.

Cancer is a major public health concern because it is one of the main causes of morbidity and mortality worldwide. As a result, numerous studies have reported the development of new therapeutic compounds with the aim of selectively treating cancer while having little negative influence on healthy cells. In this context, earthworm coelomic fluid has been acknowledged as a rich source of several bioactive substances that may exhibit promising anticancer activity. Therefore, the objective of the present review is to evaluate the findings of the reported studies exploring the antitumor effects of coelomic fluid in the context of its possible utilization as a natural therapeutic agent to cure different types of cancer. The possible mechanisms underlying the coelomic fluid's anticancerous potential as well as the possibility for future development of cutting-edge therapeutic agents utilizing coelomic fluid-derived natural bioactive compounds to treat cancer disorders have been discussed along with future challenges. In addition, the feasibility of encapsulation of bioactive compounds derived from coelomic fluid with nanomaterials that could be further explored to attain more effective anticancer competence is discussed.

Spectrofluorometric quantitative analysis of aripiprazole based on quenching of natural derived carbon quantum dots in spiked human plasma.

Autism spectrum disorder is a significant concern worldwide, particularly in Middle Eastern countries. Aripiprazole, a psychiatric medicine that works as a partial agonist at D2 receptors, is often used for autism-related behavior issues in children. Monitoring the therapy of aripiprazole could enhance the safety and effectiveness of treatment for autistic individuals. The purpose of this study was to develop a highly sensitive and environmentally friendly method for analysis of aripiprazole in plasma matrix. To achieve this, water-soluble N-carbon quantum dots were produced from a natural green precursor, guava fruit, and used in fluorescence quenching spectroscopy to determine the presence of aripiprazole. The synthesized dots were analyzed and characterized using transmission electron microscopy and Fourier transform infrared spectroscopy, and they showed a strong fluorescence emission peak at 475 nm. The proposed method was validated according to ICH M10 guidelines and was shown to be highly sensitive, allowing for nanoscale determination of aripiprazole in plasma matrix. Additionally, the method was compared to a previously reported spectrophotometric method, and it was found to be more sensitive and consistent with the principles of green analytical chemistry.

Recent Analytical Advances for Decoding Metabolic Reprogramming in Lung Cancer.

Lung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.

Development and validation of analytical methods for selective determination of albuterol and budesonide in Airsupra inhalation aerosol using spectrophotometry.

Airsupra inhalation aerosol is a recently approved FDA medication that combines albuterol and budesonide for treating or preventing bronchoconstriction and lowering the risk of relapses in asthma patients who are 18 years of age and older. To selectively determine albuterol and budesonide in both pure and pharmaceutical dosage forms, two analytical methods were developed: the zero-order absorption method and the dual-wavelength method. Even though the two drugs absorption spectra overlapped, the distinctive peak of budesonide at the zero absorbance point of albuterol, 245 nm, allowed for direct detection of budesonide in the combination using the zero-order absorption method. The mathematical dual-wavelength method, on the other hand, allowed for the measurement of both albuterol and budesonide by choosing two wavelengths for each drug in such a way that the absorbance difference for the second drug was zero. Budesonide exhibited comparable absorbance values at wavelengths 227 and 261.40 nm; hence, these two wavelengths were utilized to identify albuterol; similarly, 221.40 and 231.20 nm were chosen to determine budesonide in their binary mixes. The methods were validated according to the ICH guideline for validation of analytical procedures Q2(R1) and demonstrated excellent linearity, sensitivity, accuracy, precision, and selectivity for determining both drugs in synthetic mixed solutions and pharmaceutical formulations. The availability of these analytical methods would be valuable for the pharmaceutical industry and regulatory authorities for quality control and assessment of pharmaceutical formulations containing albuterol and budesonide.

Application of a nucleophilic substitution reaction for spectrofluorimetric determination of aripiprazole in pharmaceutical dosage form and plasma matrix; greenness assessment.

Aripiprazole is an antipsychotic medicine used to treat a variety of mental disorders, including irritability linked with autism disorder in children. Herein, a green and highly sensitive spectrofluorimetric method was developed for the determination of aripiprazole in pharmaceutical dosage form and plasma matrix. The method based on the formation of a fluorescent adduct from the nucleophilic substitution reaction of 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole (NBD-chloride) with aripiprazole, which can be detected at 542 nm following excitation at 481 nm. Factors that affect the development and fluorescence sensitivity of the reaction product were investigated and optimized. The reaction yielded the most optimal fluorescence responses when it was performed using 1.5 mL of 0.2 % w/v NBD-chloride, 1.5 mL of borate buffer pH 9, heating at 80 °C for 20 min, and ethanol as a diluting solvent. The method was validated as per ICH guidelines for analytical and bioanalytical procedures. Good linearity was established between the fluorescence responses of the reaction product and aripiprazole concentrations in the range of 100-1200 ng/mL with adequate accuracy and precision results. The applied method was very sensitive and selectively determined aripiprazole in pharmaceutical and plasma matrices with no interferences. Furthermore, the compliance of the proposed method with the principles of green analytical chemistry was evaluated in comparison with the reported method using analytical eco-scale and AGREE metrics. The outputs proved that the proposed method complied more with the principles of green analytical chemistry than the reported method.