CHEMOMETRICS ASSISTED SPECTROSCOPIC METHOD DEVELOPMENT AND VALIDATION FOR SIMULTANEOUS DETERMINATION OF SOFOSBUVIR AND DACLATASVIR DIHYDROCHLORIDE IN TABLET FORMULATION

INDIAN DRUGS ◽  
2020 ◽  
Vol 57 (03) ◽  
pp. 37-46
Author(s):  
Sapna M Rathod ◽  
Paresh U Patel
Keyword(s):  
Method Development ◽  
Spectroscopic Method ◽  
Principal Component ◽  
Tablet Formulation ◽  
Partial Least Square ◽  
Least Square ◽  
Simultaneous Estimation ◽  
Mixed Solution ◽  
Chemometric Methods ◽  
Validation Set

Four chemometric methods, namely Classical Least Square (CLS), Inverse Least Square (ILS), Partial Least Square (PLS) and Principal Component Regression (PCR), were developed for the simultaneous estimation of sofosbuvir and daclatasvir dihydrochloride in tablet formulation. Full factorial design was used to construct calibration set as well as validation set. Twenty five mixed solutions were prepared for calibration set and sixteen mixed solution of drugs were prepared for validation set. The absorbance of all prepared solutions was measured in the range of 230 nm to 335 nm at 16 wavelength points at an interval of 7 nm. Linearity was observed in the range of 10 – 90 µg/mL for sofosbuvir and 4 - 20 µg/mL for daclatasvir dihydrochloride. The developed chemometric methods were validated in terms of precision and accuracy as per ICH guidelines. The developed methods can be applied for the routine quantitative analysis of formulation.

DEVELOPMENT AND VALIDATION OF CHEMOMETRIC-ASSISTED UV-SPECTROPHOTOMETRIC METHOD FOR EPIGALLOCATECHIN GALLATE AND CURCUMIN IN TABLET FORMULATION

INDIAN DRUGS ◽  
2020 ◽  
Vol 57 (04) ◽  
pp. 45-51
Author(s):  
N. C. Patel ◽  
A. P. Patel ◽  
J. K. Patel
Keyword(s):  
Epigallocatechin Gallate ◽  
Tablet Formulation ◽  
Partial Least Square ◽  
Least Square ◽  
Data Matrix ◽  
Simultaneous Estimation ◽  
Calibration Data ◽  
Mixed Solution ◽  
Validation Set ◽  
Development And Validation

A chemometric method, Partial Least Square, was applied for the simultaneous estimation of epigallocatechin gallate and curcumin in tablet formulation. Twenty five mixed sample solutions were prepared for chemometric calibration as training set and sixteen mixed solution for validation set using Full Factorial Design. The absorbance data matrix was obtained by measuring absorbance at 20 different wavelengths in the range of 220 to 410 nm (Δλ = 10 nm). The developed calibration data was used to test tablet formulation containing epigallocatechin gallate and curcumin. The developed methods were validated using RMSECV and RMSEP. The chemometric calculations were performed using Minitab 16.1.1 and Microsoft Excel 2010. The method is also more accurate and precise than conventional UV methods.

DEVELOPMENT AND VALIDATION OF A CHEMOMETRICS ASSISTED SPECTROSCOPIC METHOD FOR THE SIMULTANEOUS ESTIMATION OF GALLIC ACID, ELLAGIC ACID AND CURCUMIN IN POLYHERBAL ANTIDIABETIC FORMULATIONS

INDIAN DRUGS ◽  
2019 ◽  
Vol 56 (06) ◽  
pp. 67-73
Author(s):  
M. A Shah ◽  
◽  
H. U. Patel ◽  
H.A Raj
Keyword(s):  
Gallic Acid ◽  
Ellagic Acid ◽  
Spectroscopic Method ◽  
Least Square ◽  
Data Matrix ◽  
Simultaneous Estimation ◽  
Chemometric Methods ◽  
Mixed Solutions ◽  
Validation Set ◽  
Development And Validation

Two chemometric methods, Inverse Least Square (ILS) and Classical Least Square (CLS), were applied for the simultaneous estimation of gallic acid, ellagic acid and curcumin in polyherbal antidiabetic formulation. Twenty mixed solutions were prepared for the chemometric calibration as training set and 10 mixed solutions were prepared as validation set. The absorbance data matrix was obtained by measuring the absorbance at 20 different wavelengths, from 241 to 279 nm with the interval of 2 nm (Δλ= 2 nm). The developed calibrations were successfully tested for three antidiabetic polyherbal formulations for their gallic acid, ellagic acid and curcumin contents. Developed methods were validated and root mean square error of precision (RMSEP) was determined. Both chemometric methods in this study can be satisfactorily used for the quantitative analysis in polyherbal dosage forms. The chemometric calculations were performed by using the chemometrics toolbox with MATLAB R2015a software.

SIMULTANEOUS ESTIMATION OF EMITRICITABINE, EFAVIRENZ, TENOFOVIR DISPROXIL FUMARATE BY CHEMOMETRY AND REVERSE PHASE-HIGH PERFORMANCE LIQUID CHROMATOGRAPHY

INDIAN DRUGS ◽  
2016 ◽  
Vol 53 (06) ◽  
pp. 62-69
Author(s):  
G. Ramya Kumari ◽  
◽  
N. C Deepika ◽  
Krishnamurthy Bhat
Keyword(s):  
High Performance ◽  
Ultra Violet ◽  
Hplc Method ◽  
Tablet Formulation ◽  
Partial Least Square ◽  
Least Square ◽  
Ternary Mixtures ◽  
Data Matrix ◽  
Simultaneous Estimation ◽  
Tenofovir Df

A chemometric ultra-violet spectrophotometric method of analysis, Partial Least Square (PLS) method was applied to simultaneous assay of emitricitrabine, efavirenz and tenofovir disoproxil fumarate (DF) in their combined dosage tablet formulation. For comparison of this chemometric method a HPLC method for simultaneous determination of emitricitabine, efavirenz and tenofovir DF in combination was developed. Twenty one mixed solutions were prepared for chemometric calibration set and twenty one ternary mixtures were prepared as validation sets. The absorbance data matrix for training set was obtained by recording absorbance within wavelength range 230-290 nm at 2nm intervals. The developed multivariate and HPLC methods were successfully tested for laboratory mixtures as well as commercial tablet formulation of emitricitrabine, efavirenz, tenofovir DF.

SIMULTANEOUS ESTIMATION OF TELMISARTAN, HYDROCHLOROTHIAZIDE AND AMLODIPINE BESYLATE IN TABLET PREPARATION BY CHEMOMETRIC ASSISTED SPECTROPHOTOMETRIC ANALYSIS

INDIAN DRUGS ◽  
2018 ◽  
Vol 55 (07) ◽  
pp. 59-66
Author(s):  
A. S Ghule ◽  
T. Thomas ◽  
M. Joseph ◽  
K. S. Navya Sree ◽  
K. Bhat
Keyword(s):  
Spectrophotometric Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Data Matrix ◽  
Simultaneous Estimation ◽  
Amlodipine Besylate ◽  
Mixed Solutions ◽  
Validation Set ◽  
Tablet Preparation

A chemometric method was developed by application of Partial Least Square regression to for the simultaneous estimation of telmisartan, hydrochlorothiazide and amlodipine besylate in tablet preparations. Calibration set was prepared considering seven sets; each set with twenty-four mixed solutions and twenty-one ternary mixed solutions, were prepared as a validation set. The absorbance data matrix for training set was obtained by recording absorbance within wavelength range 220-320 nm at 2nm intervals. The developed method was validated according to ICH Q2 (R1) guidelines and results were reported. The developed and validated multivariate method was successfully tested for laboratory mixtures as well as commercial tablet formulation of telmisartan, hydrochlorothiazide and amlodipine besylate.

scholarly journals Developing an Algorithm for Discriminating Oral Cancerous and Normal Tissues Using Raman Spectroscopy

2021 ◽  
Vol 11 (11) ◽  
pp. 1165
Author(s):  
Mukta Sharma ◽  
Ming-Jer Jeng ◽  
Chi-Kuang Young ◽  
Shiang-Fu Huang ◽  
Liann-Be Chang
Keyword(s):  
Raman Spectroscopy ◽  
Surgical Resection ◽  
Ex Vivo ◽  
Spectroscopic Method ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Validation Dataset ◽  
Linear Discriminant

The aim of this study was to investigate the clinical potential of Raman spectroscopy (RS) in detecting oral squamous cell carcinoma (OSCC) in tumor and healthy tissues in surgical resection specimens during surgery. Raman experiments were performed on cryopreserved specimens from patients with OSCC. Univariate and multivariate analysis was performed based on the fingerprint region (700–1800 cm−1) of the Raman spectra. One hundred thirty-one ex-vivo Raman experiments were performed on 131 surgical resection specimens obtained from 67 patients. The principal component analysis (PCA) and partial least square (PLS) methods with linear discriminant analysis (LDA) were applied on an independent validation dataset. Both models were able to differentiate between the tissue types, but PLS–LDA showed 100% accuracy, sensitivity, and specificity. In this study, Raman measurements of fresh resection tissue specimens demonstrated that OSCC had significantly higher nucleic acid, protein, and several amino acid contents than adjacent healthy tissues. The specific spectral information obtained in this study can be used to develop an in vivo Raman spectroscopic method for the tumor-free resection boundary during surgery.

Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Khairunnisa Khairunnisa ◽  
Rizka Pitri ◽  
Victor P Butar-Butar ◽  
Agus M Soleh
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Principal Component Regression ◽  
Circulation Model ◽  
Principal Component ◽  
Meteorological Station ◽  
Grid Size ◽  
Partial Least Square ◽  
Least Square ◽  
Output Data

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.

scholarly journals A Novel Validated Injectable Colistimethate Sodium Analysis Combining Advanced Chemometrics and Design of Experiments

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1546
Author(s):  
Ioanna Dagla ◽  
Anthony Tsarbopoulos ◽  
Evagelos Gikas
Keyword(s):  
Design Of Experiments ◽  
High Performance ◽  
Similarity Index ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Distance Measures ◽  
Linear Regression Models ◽  
Colistimethate Sodium

Colistimethate sodium (CMS) is widely administrated for the treatment of life-threatening infections caused by multidrug-resistant Gram-negative bacteria. Until now, the quality control of CMS formulations has been based on microbiological assays. Herein, an ultra-high-performance liquid chromatography coupled to ultraviolet detector methodology was developed for the quantitation of CMS in injectable formulations. The design of experiments was performed for the optimization of the chromatographic parameters. The chromatographic separation was achieved using a Waters Acquity BEH C8 column employing gradient elution with a mobile phase consisting of (A) 0.001 M aq. ammonium formate and (B) methanol/acetonitrile 79/21 (v/v). CMS compounds were detected at 214 nm. In all, 23 univariate linear-regression models were constructed to measure CMS compounds separately, and one partial least-square regression (PLSr) model constructed to assess the total CMS amount in formulations. The method was validated over the range 100–220 μg mL−1. The developed methodology was employed to analyze several batches of CMS injectable formulations that were also compared against a reference batch employing a Principal Component Analysis, similarity and distance measures, heatmaps and the structural similarity index. The methodology was based on freely available software in order to be readily available for the pharmaceutical industry.

scholarly journals The inflammatory profile of cerebrospinal fluid, plasma, and saliva from patients with severe neuropathic pain and healthy controls-a pilot study

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Mika Jönsson ◽  
Björn Gerdle ◽  
Bijar Ghafouri ◽  
Emmanuel Bäckryd
Keyword(s):  
Cerebrospinal Fluid ◽  
Neuropathic Pain ◽  
Pain Intensity ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Therapeutic Interventions ◽  
Healthy Controls ◽  
Inflammatory Profile

Abstract Background Neuropathic pain (NeuP) is a complex, debilitating condition of the somatosensory system, where dysregulation between pro- and anti-inflammatory cytokines and chemokines are believed to play a pivotal role. As of date, there is no ubiquitously accepted diagnostic test for NeuP and current therapeutic interventions are lacking in efficacy. The aim of this study was to investigate the ability of three biofluids - saliva, plasma, and cerebrospinal fluid (CSF), to discriminate an inflammatory profile at a central, systemic, and peripheral level in NeuP patients compared to healthy controls. Methods The concentrations of 71 cytokines, chemokines and growth factors in saliva, plasma, and CSF samples from 13 patients with peripheral NeuP and 13 healthy controls were analyzed using a multiplex-immunoassay based on an electrochemiluminescent detection method. The NeuP patients were recruited from a clinical trial of intrathecal bolus injection of ziconotide (ClinicalTrials.gov identifier NCT01373983). Multivariate data analysis (principal component analysis and orthogonal partial least square regression) was used to identify proteins significant for group discrimination and protein correlation to pain intensity. Proteins with variable influence of projection (VIP) value higher than 1 (combined with the jack-knifed confidence intervals in the coefficients plot not including zero) were considered significant. Results We found 17 cytokines/chemokines that were significantly up- or down-regulated in NeuP patients compared to healthy controls. Of these 17 proteins, 8 were from saliva, 7 from plasma, and 2 from CSF samples. The correlation analysis showed that the most important proteins that correlated to pain intensity were found in plasma (VIP > 1). Conclusions Investigation of the inflammatory profile of NeuP showed that most of the significant proteins for group separation were found in the less invasive biofluids of saliva and plasma. Within the NeuP patient group it was also seen that proteins in plasma had the highest correlation to pain intensity. These preliminary results indicate a potential for further biomarker research in the more easily accessible biofluids of saliva and plasma for chronic peripheral neuropathic pain where a combination of YKL-40 and MIP-1α in saliva might be of special interest for future studies that also include other non-neuropathic pain states.

scholarly journals A fast and low-cost approach to quality control of alcohol-based hand sanitizer using portable near infrared spectrometer and chemometrics

2021 ◽  
pp. 096703352098731
Author(s):  
Adenilton C da Silva ◽  
Lívia PD Ribeiro ◽  
Ruth MB Vidal ◽  
Wladiana O Matos ◽  
Gisele S Lopes
Keyword(s):  
Quality Control ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Chemical Components ◽  
Linear Discriminant ◽  
Hand Sanitizer

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

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