Four chemometric models enhanced by Latin hypercube sampling design for quantification of anti-COVID drugs: sustainability profiling through multiple greenness, carbon footprint, blueness, and whiteness metrics

BMC Chemistry, Journal Year: 2024, Volume and Issue: 18(1)

Published: March 18, 2024

Abstract Montelukast sodium (MLK) and Levocetirizine dihydrochloride (LCZ) are widely prescribed medications with promising therapeutic potential against COVID-19. However, existing analytical methods for their quantification unsustainable, relying on toxic solvents expensive instrumentation. Herein, we pioneer a green, cost-effective chemometrics approach MLK LCZ analysis using UV spectroscopy intelligent multivariate calibration. Following multilevel multifactor experimental design, spectral data was acquired 25 synthetic mixtures modeled via classical least squares (CLS), principal component regression (PCR), partial (PLS), genetic algorithm-PLS (GA-PLS) techniques. Latin hypercube sampling (LHS) strategically constructed an optimal validation set of 13 unbiased predictive performance assessment. optimization the models regarding latent variables (LVs) wavelength region, optimum root mean square error cross-validation (RMSECV) attained at 2 LVs 210–400 nm range (191 points). The GA-PLS model demonstrated superb accuracy, recovery percentages (R%) from 98 to 102% both analytes, calibration (RMSEC) prediction (RMSEP) (0.0943, 0.1872) (0.1926, 0.1779) LCZ, respectively, as well bias-corrected (BCMSEP) -0.0029 0.0176, relative (RRMSEP) reaching 0.7516 0.6585, limits detection (LOD) 0.0813 0.2273 respectively. Practical pharmaceutical sample successfully confirmed standard additions. We further conducted pioneering multidimensional sustainability evaluations state-of-the-art greenness, blueness, whiteness tools. method favorable environmental metrics across all assessment obtained Green National Environmental Method Index (NEMI), Complementary Analytical Procedure (ComplexGAPI) quadrants affirmed green principles. Additionally, had high Greenness Metric (AGREE) score (0.90) low carbon footprint (0.021), indicating friendliness. also applied blueness assessments Blue Applicability Grade (BAGI) Red–Green–Blue 12 (RGB 12) algorithms. BAGI (90) RGB (90.8) scores method's strong applicability, cost-effectiveness, sustainability. This work puts forward optimal, economically viable chemistry paradigm quality control aligned sustainable development goals.

Language: Английский

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Application of machine learning assisted multi-variate UV spectrophotometric models augmented by kennard stone clustering algorithm for quantifying recently approved nasal spray combination of mometasone and olopatadine along with two genotoxic impurities: comprehensive sustainability assessment

BMC Chemistry, Journal Year: 2025, Volume and Issue: 19(1)

Published: April 15, 2025

The recent approval of the nasal spray combination mometasone (MOM) and olopatadine (OLO) presents a significant analytical challenge, as only single reported method exists for its determination, deviating from eco-friendly practices. This study addresses this critical gap by pioneering application machine learning techniques to develop robust UV spectrophotometric approach simultaneous quantification MOM OLO, along with two genotoxic impurities: 4-dimethylamino pyridine (DAP) methyl para-toluene sulfonate (MTS). By simultaneously determining these highly concerning impurities active pharmaceutical ingredients, underscores paramount significance in upholding rigorous quality standards safeguarding patient safety. Applying multilevel-multifactor experimental design, calibration set was meticulously chosen at five different concentrations, yielding 25 mixtures central levels 4, 46.5, 2.5, 3 µg/mL MOM, OLA, MTS, DAP, respectively. key innovation lies strategic implementation Kennard-Stone Clustering Algorithm create validation thirteen mixtures, resolving limitations chemometric methods' random data splitting. ensures unbiased evaluation across full concentration space, improving method's reliability sustainability. robustness rigorously tested using distinct models: principal component regression, classical least squares, partial genetic algorithm-partial multivariate curve resolution-alternating demonstrating broad applicability diverse modeling techniques. All models successfully determined all components excellent recovery, low bias-corrected prediction, adequate limits detection. Greenness Index Spider Charts Green Solvents Selection Tool were used choose environmentally conscious solvents. A comprehensive sustainability assessment employed six state-of-the-art tools, including national environmental index, complementary green procedure greenness metric, blue grade carbon footprint analysis, red-green-blue 12 metrics. Favorable results metrics affirmed eco-friendliness, real-world applicability, cost-effectiveness, supporting sustainable development goals control processes.

Language: Английский

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Greenness, whiteness, and blueness assessment with spider chart solvents evaluation of HPTLC-densitometric method for quantifying a triple combination anti-Helicobacter pylori therapy

Sustainable Chemistry and Pharmacy, Journal Year: 2023, Volume and Issue: 37, P. 101412 - 101412

Published: Dec. 25, 2023

Language: Английский

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Sustainable chemometric methods boosted by Latin hypercube technique for quantifying the recently FDA-approved combination of bupivacaine and meloxicam in the presence of bupivacaine carcinogenic impurity: Comprehensive greenness, blueness, and whiteness assessments

Microchemical Journal, Journal Year: 2024, Volume and Issue: 200, P. 110276 - 110276

Published: March 2, 2024

Language: Английский

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Sustainable quantification of glycopyrronium, indacaterol, and mometasone along with two genotoxic impurities in a recently approved fixed-dose breezhaler formulations and biological fluids: A machine learning-augmented UV-spectroscopic approach

Microchemical Journal, Journal Year: 2024, Volume and Issue: 206, P. 111586 - 111586

Published: Sept. 6, 2024

Language: Английский

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Optimized Hesperidin-Loaded Lipid Nanoparticles with Tea Tree Oil for Enhanced Wound Healing: Formulation, Characterization, and Evaluation

Pharmaceuticals, Journal Year: 2025, Volume and Issue: 18(3), P. 290 - 290

Published: Feb. 20, 2025

Objectives: This study aimed to develop hesperidin solid lipid nanoparticles (HESP-SLNs) enhance their stability, solubility, and sustained release for wound healing; further enhancement was achieved through prepared nanostructured carriers (HESP-NLCs) using Tea Tree Oil (TTO) explore synergistic efficacy. Methods: A factorial design of 24 trials established evaluate the influence type (X1), conc (%) (X2), surfactant (X3), sonication amplitude (X4) HESP-SLNs on particle size (nm) (Y1), polydispersibility index (Y2), zeta potential (Y3), encapsulation efficiency (Y4). The optimized formula selected utilizing Design Expert® software version 13, which additionally enhanced by preparing TTO-loaded HESP-NLCs. In vitro release, Raman spectroscopy, transmission electron microscopy were carried out both nanoparticles. Cytotoxicity, in vivo wound-healing assessments, skin irritancy tests performed performance TTO-incorporated HESP-NLCs compared HESP-SLNs. Results: demonstrated PS (280 ± 1.35 nm), ZP (−39.4 0.92 mV), PDI (0.239 0.012), EE% (88.2 2.09%). NLCs Q6% (95.14%) vs. (79.69%), SLNs showed superior antimicrobial Both exhibited spherical morphology compatibility between HESP excipients. highest closure percentage, supported histological analysis inflammatory biomarker outcomes. Cytotoxicity evaluation 87% cell viability untreated HSF cells, test confirmed safety NLCs. Conclusions: are promising candidates exhibiting capabilities, making them a therapeutic option cutaneous management.

Language: Английский

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Revealing the adulteration of sesame oil products by portable Raman spectrometer and 1D CNN vector regression: A comparative study with chemometrics and colorimetry

Food Chemistry, Journal Year: 2023, Volume and Issue: 436, P. 137694 - 137694

Published: Oct. 14, 2023

Language: Английский

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A Recycled-Material-Based Electrochemical Eco-sensor for Sensitive Detection of Antischistosomal Drug Residues in Bovine-Derived Food Samples

BioChip Journal, Journal Year: 2024, Volume and Issue: 18(2), P. 257 - 274

Published: March 8, 2024

Abstract Veterinary drug residues in food have emerged as an urgent threat to consumer safety. Herein, we present the first square wave voltammetric method for trace-level detection of cinnarizine residues, a recently used antischistosomal drug, bovine samples. The depends on electrochemical oxidation after modification carbon paste sensor with recycled Al 2 O 3 -NPs functionalized multi-walled nanoparticles. produced (Al -NPs/ MWCNTs/CPE) was characterized using transmission electron microscope, scanning Fourier-transform infrared spectroscopy, energy-dispersive spectrometer, and X-ray diffractometer that confirm successful incorporation -NPs/MWCNTs composite into modified electrode. As expected, active surface area transfer processes were accelerated by modification, which evidenced cyclic voltammetry, chronoamperometric studies, scan rate impedance spectroscopy. Compared previous techniques, this facile demonstrated enhancements across critical analytical criteria including limit 0.17 nM, linear response 5–100 nM ( r = 0.998), accuracy ranging from 96.5 103.2%, precision below 0.81% relative standard deviation, reproducibility within 0.36% range, 20 s time applicability spiked matrices. In addition, five different greenness whiteness tools quantified exceptional environmental friendliness, economic feasibility waste reduction 63%–93%, reaffirming alignment sustainability paradigms. These advantages support practical adoption quality control especially laboratories lacking expensive instrumentation. Overall, ingenious reconciles nanotechnology innovation circular economy ethos tackle safety challenge, guided holistically metrics.

Language: Английский

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A sustainable data processing approach using ultraviolet-spectroscopy as a powerful spectral resolution tool for simultaneously estimating newly approved eye solution in the presence of extremely carcinogenic impurity aided with various greenness and whiteness assessment perspectives: Application to aqueous humor

Journal of Chemical Research, Journal Year: 2023, Volume and Issue: 47(5)

Published: Sept. 1, 2023

Drug impurities are now seen as a major threat to drug safety around the world, especially when it comes carcinogenic impurities. Here, we present first spectrophotometric approach for quantification of lignocaine and fluorescein in presence 2,6-xylidine, lignocaine’s impurity. The depends on overcoming unresolved bands through data processing strategy employing 10 affordable, simple, sensitive methods. Fluorescein analysis (1–16 μg mL −1 ) was performed using direct ultraviolet spectrophotometry (D 0 at 478 nm; then, ratio subtraction method allowed removal interference caused by spectrum. From resulting spectra, 2,6-xylidine (40–160 can be efficiently determined 280 nm. However, (72–320 analyzed different ultraviolet-based methods, including continuous wavelet transform, derivative Savitzky–Golay filters, mean centering, second spectra difference spectrophotometry, extended subtraction, absorbance Q-absorbance ratio, area under curve. In line with International Council Harmonization Technical Requirements Pharmaceuticals Human Use (ICH), presented evaluated its coefficients determination, detection limits, relative standard deviations. Similarly, developed assessed whiteness, greenness, sustainability five assessment tools, National Environmental Method Index, Eco-Scale Assessment, Complementary Green Analytical Procedure Greenness Metric, RGB12, offering promising results. Owing satisfactory analytical performance, besides sustainability, affordability, simplicity, cost efficiency their application quality control situ minimal-infrastructure laboratories increases, increasing surveillance potential.

Language: Английский

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Insights on ecological spectroscopic techniques recently adopted for pharmaceutical analysis: A comprehensive review from the perspective of greenness assessment metrics systems application

TrAC Trends in Analytical Chemistry, Journal Year: 2023, Volume and Issue: 170, P. 117435 - 117435

Published: Nov. 16, 2023

Language: Английский

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