Noninvasive, Quantitative Analysis of Drug Mixtures in Containers Using Spatially Offset Raman Spectroscopy (SORS) and Multivariate Statistical Analysis

In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for noninvasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform noninvasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.

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Quantitative analysis of hepatitis B virus DNA based on raman spectroscopy combined with multivariate statistical methods

Laser Physics Letters ◽

10.1088/1612-202x/ab6855 ◽

2020 ◽

Vol 17 (2) ◽

pp. 025001 ◽

Cited By ~ 1

Author(s):

Yuwan Du ◽

Guodong Lv ◽

Hongyi Li ◽

Dongni Tong ◽

Xiaoyi Lv ◽

...

Keyword(s):

Raman Spectroscopy ◽

Quantitative Analysis ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Statistical Methods ◽

Multivariate Statistical Methods ◽

Multivariate Statistical ◽

Hepatitis B Virus Dna ◽

B Virus

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HPLC-UV Method for Determination of Famotidine from Pharmaceutical Products

Revista de Chimie ◽

10.37358/rc.18.2.6093 ◽

2018 ◽

Vol 69 (2) ◽

pp. 297-299

Author(s):

Adriana Nita ◽

Delia Mirela Tit ◽

Lucian Copolovici ◽

Carmen Elena Melinte (Frunzulica) ◽

Dana Maria Copolovici ◽

...

Keyword(s):

Acetic Acid ◽

Quantitative Analysis ◽

Linear Response ◽

Mobile Phase ◽

Acetic Acid Solution ◽

Pharmaceutical Products ◽

Quantification Limit ◽

Validation Parameters ◽

Hplc Analyses

The aim of this study was to develop and validate a rapid, accurate, and exact method for the quantitative determination of famotidine in pharmaceutical products. The HPLC analyses were performed by using a mobile phase containing methanol:1% acetic acid solution=30:7 (v/v), at a flow rate of 0.4 mL/min.The total time of the method was 10 min, and the retention time of famotidine was 4.16 min. The detection was evaluated at l=267 nm. The method has been validated by using different validation parameters. The linear response of the detector for famotidine peak area was observed at concentrations ranging from 0.1 to 0.0001 mg mL-1 , resulting in a correlation coefficient of 0.99998. The values of the detection limit and of the quantification limit are 0.00048 mg mL-1 and 0.00148 mg mL-1, respectively. The method proposed allowed accurate (with a relative error of less than 2%) and precise (RSD values less than 2.0%) determination of famotidine content in pharmaceutical products and can be used for its rapid quantitative analysis.

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Classification of Chemical and Biological Warfare Agent Simulants by Surface-Enhanced Raman Spectroscopy and Multivariate Statistical Techniques

Applied Spectroscopy ◽

10.1366/000370206776593744 ◽

2006 ◽

Vol 60 (4) ◽

pp. 356-365 ◽

Cited By ~ 55

Author(s):

William F. Pearman ◽

Augustus W. Fountain

Keyword(s):

Raman Spectroscopy ◽

Surface Enhanced Raman Spectroscopy ◽

Statistical Techniques ◽

Biological Warfare ◽

Multivariate Statistical Techniques ◽

Multivariate Statistical ◽

Biological Warfare Agent ◽

Surface Enhanced ◽

Surface Enhanced Raman

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EXPRESS: Characterization of Drug Resistance in Chronic Myeloid Leukemia Cells Based on Laser Tweezers Raman Spectroscopy

Applied Spectroscopy ◽

10.1177/00037028211024581 ◽

2021 ◽

pp. 000370282110245

Author(s):

Qian Zhang ◽

Minlu Ye ◽

Lingyan Wang ◽

Dongmei Jiang ◽

Shuting Yao ◽

...

Keyword(s):

Raman Spectroscopy ◽

Chronic Myeloid Leukemia ◽

Myeloid Leukemia ◽

K562 Cells ◽

Laser Tweezers ◽

Label Free ◽

Multivariate Statistical ◽

Analytical Strategy ◽

Specificity And Sensitivity ◽

Acid Protein

Multidrug resistance (MDR) is highly associated with poor prognosis of chronic myeloid leukemia (CML). This work aims to explore whether the laser tweezers Raman spectroscopy (LTRS) could be practical in separating adriamycin (ADR) resistance CML cells K562/ADR from its parental cells K562, and to explore the potential mechanisms. Detection of LTRS initially reflected the spectral differences caused by chemoresistance including bands assigned to carbohydrates, amino acid, protein, lipids and nucleic acid. In addition, principal components analysis (PCA) as well as the classification and regression trees (CRT) algorithms showed that the specificity and sensitivity were above 90%. Moreover, the band data-based CRT model and receiver operating characteristic (ROC) curve further determined some important bands and band intensity ratios to be reliable indexes in discriminating K562 chemoresistance status. Finally, we highlighted three metabolism pathways correlated with chemoresistance. This work demonstrates that the label-free LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single-cell level for rapid evaluation the chemoresistance status of K562 cells.

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