Greenness, blueness and whiteness evaluated-chemometric approach enhanced by Latin hypercube technique for the analysis of lidocaine, diclofenac and carcinogenic impurity 2,6-dimethylaniline

Halim, Michael K.; Badran, Osama M.; Abbas, Ahmed Emad F.

doi:10.1016/j.scp.2024.101463

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…A range of chemometrics techniques including CLS, PCR, PLS, and GA-PLS were implemented. These approaches were chosen based on their demonstrated ability to handle multi-component analysis and extract latent predictive information even with significant collinearity and interactions between constituents [ 13 , 15 ]. This enabled accurate quantification despite the significant spectral overlaps seen in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…This motivated the integration of UV–vis with chemometrics, establishing a synergistic combination extracting meaningful chemical information from complex backgrounds, quintessential in analytical chemistry [ 12 ]. Thereby transforming UV spectrophotometry into a value-added green analytical tool suitable for economical, routine pharmaceutical quality control, as evidenced in recent literature [ 13 – 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…While simple to implement, random partitioning risks insufficiently representing the full modeled chemical space, frequently causing biased accuracy estimates conflicting with sustainability objectives like reliability and resource efficiency. To address this significant limitation, we strategically leverage the Latin Hypercube sampling (LHS) design, systematically dividing each modeled variable into equal probability strata and sampling each to ensure excellent coverage and balance when constructing validation sets [ 13 ]. Thereby enabling robust, unbiased assessment of predictive capabilities on new samples.…”

Section: Introductionmentioning

confidence: 99%

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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

Katamesh,

Abbas,

Mahmoud

2024

BMC Chemistry

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

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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

Katamesh,

Abbas,

Mahmoud

2024

BMC Chemistry

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Derivatization‐free sustainable spectrofluorimetric estimation of antihistamine drug mizolastine in pharmaceutical and biological matrices

Mohamed,

Omar,

Zeid

et al. 2024

Luminescence

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Mizolastine is an antihistamine drug that is commonly used for treatment of chronic urticaria and allergic rhinitis. In this study, a facile, rapid, and sustainable fluorimetric method was established for the estimation of mizolastine in pharmaceutical and biological matrices for the first time. The approach methodology relied on the direct assessment of mizolastine's intrinsic fluorescence at 313 nm after excitation at 272 nm. This intrinsic fluorescence, stemming from the benzimidazole fluorophore moiety in mizolastine structure, serves as a distinctive marker for its precise quantification in the spiked human plasma and pharmaceutical formulations with high %recovery. The method exhibits reasonable sensitivity with lower limits of detection and quantification of 5.4 and 16.6 ng mL−1, respectively, across a concentration range of 25.0–2000.0 and 50–1000 ng mL−1 for the standard mizolastine analysis and mizolastine assay in the plasma sample, respectively. Moreover, the established method was applied to assess tablet content uniformity and mizolastine assay in plasma samples with high recoveries (98.50%–100.20%). Such applications underscore the method's potential applicability within quality control laboratories, preventing the need for sample preparation or laborious extraction steps. Finally, the method's sustainability and practicality were confirmed by applying different greenness and whiteness metrics, yielding excellent results.

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Highly sensitive analysis of fatty aldehydes in vegetable oils using a novel coumarin-based fluorescent probe by HPLC for quality control

Zhang,

Zhu,

Xie

et al. 2024

Microchemical Journal

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Greenness, blueness and whiteness evaluated-chemometric approach enhanced by Latin hypercube technique for the analysis of lidocaine, diclofenac and carcinogenic impurity 2,6-dimethylaniline

Cited by 6 publications

References 36 publications

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

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

Derivatization‐free sustainable spectrofluorimetric estimation of antihistamine drug mizolastine in pharmaceutical and biological matrices

Highly sensitive analysis of fatty aldehydes in vegetable oils using a novel coumarin-based fluorescent probe by HPLC for quality control

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