Principle Component Regression Method Research Articles

Comparison of Chemometric assisted UV Spectrophotometric and RP-HPLC Method for the simultaneous determination of Ofloxacin and Tinidazole in their Combined dosage form

In present work, chemometric-assisted UV spectrophotometric methods as well as RP-HPLC method were developed for the simultaneous estimation of Ofloxacin and Tinidazole in their combined pharmaceutical dosage form. The two chemometric methods i.e. principle component regression (PCR) and partial least square regression (PLS) were successfully applied to quantify each drug in mixture using UV absorption spectra in range of 280 to 320nm at ∆λ of 0.5nm. Chemometric model development was done using 24 binary mixture solutions and 12 solutions were used for validation of model. The chemometric-assisted analysis does not require any prior separation step. In addition, RP-HPLC method was also developed using THERMOSIL C18 column with a mobile phase consisting ofAcetonitrile: Phosphate Buffer (85:15% v/v), flow rate of 1 ml/min and quantification was achieved using UV detector at 300 nm. The methods were successfully applied for the simultaneous determination of these drugs in synthetic mixture. The results obtained for analysis by PCR and PLS methods were compared with RP-HPLC method and a good agreement was found.

Simultaneous kinetic-potentiometric determination of levodopa and carbidopa using multivariate calibration methods

Partial least squares (PLS) and principle component regression (PCR) multivariate calibration methods were applied to the simultaneous determination of carbidopa and levodopa using kinetic data from novel potentiometry methods. These methods were based on the rate of chloride ion production in the reaction of carbidopa and levodopa with N-chlorosuccinimide (NCS) which was monitored by a chloride ion-selective electrode. The experimental data shows suitability of ion-selective electrodes (ISEs) to be used as detectors not only for the direct determination of chloride ion but also for simultaneous kinetic-potentiometric analysis using chemometric methods. These methods are based on the differences observed in the production rate of chloride ions. The results show that simultaneous determination of carbidopa and levodopa can be performed in their concentration ranges of 1.0-14.0 and 0.5-25.0 μg/mL, respectively. The total relative standard errors for applying PCR and PLS methods to 9 synthetic samples in the concentration range of 2.0-13.0 μg/mL for carbidopa and 1.0-18.0 μg/mL for levodopa were 4.81 and 4.29, respectively. The effects of certain additives used as excipients upon the reaction rate were determined to assess selectivity of the method. Both methods (PLS and PCR) were validated using a set of synthetic sample mixtures and then were successfully applied to the determination of carbidopa and levodopa in several commercially available mixture formulations. The recoveries were satisfactory and comparable to those obtained by applying the reference Pharmacopoeia method of high performance liquid chromatography.

İlaç Formülasyonundaki Asetilsalisilik Asit, Parasetamol ve Kafeinin Kemometrik Metotlarla Tayini

In this study, the results of ultraviolet spectrophotometry of paracetamol, acetylsalicylic acid and caffeine active substances in tablet drug sample were evaluated together with chemometric methods. In the experimental study, the synthetic mixtures were prepared by taking each drug from the active ingredient after obtaining the individual pure spectra of the substances. At the next stage, a tablet sample analysis was performed. From the chemometric methods, the principle component regression method (PCR) and the partial least squares method (PLS) have been successfully applied in the quantification of the synthetic mixtures and the tablet sample. When the data obtained are statistically analyzed, both the calculated recovery values ​​are high and the standard deviations are small enough. In addition, F-test was applied in terms of the suitability of the method and the results were found to be compatible. The results obtained with the help of applied chemometric methods are very fast, simple and reliable results.

Determination of the Colorants in Various Samples by Chemometric Methods Using Statistical Chemistry

partial least square and principal component regression methods were applied to various mixtures of Allura Red and Brilliant Blue to determine the concentrations. Colorants, at the same time, were analyzed with UV-spectrophotometry in chemical separation. The obtained experimental data have been evaluated by chemometric methods as Partial Least Squares (PLS) and Principle Component Regression (PCR). In the first step, the synthetic mixtures containing three-color material were examined, and the obtained results were applied to the PCR and PLS. In the next step, using PLS and PCR methods, the quantities of Allura Red and Brilliant Blue in commercial beverage, samples were measured at the same time. The results were compared statistically.

QSAR studies of 7-methyljuglone derivatives as antitubercular agents

The emergence of multidrug resistance strains of Mycobacterium tuberculosis and the continuing pandemic of tuberculosis (TB) leads to the urgent development of the new potent antitubercular agents. Hence, an effort to develop new and more effective agents to treat TB emphasis was focused on quantification of structure–activity relationship of 7-methyljuglone derivatives. A set of twenty-five 7-methyljuglone derivatives with antitubercular activity were subjected to two-dimensional quantitative structure activity relationship study using various combination of thermodynamic, electronic, and spatial descriptors by the software Vlife Molecular Drug Design suite 3.0. After performing QSAR study, it was found that the model developed by multiple linear regression method (Model I) was more statistically significant in compare to the model developed by principle component regression method (Model II), as Model I having correlation coefficient (r) = 0.9591, coefficient of determination (r2) = 0.8823, Fischer test (F) = 39.7105, q2 = 0.7871, r2 SE = 0.2112, q2 SE = 0.2598, pred_r2 = 0.4916, pred_r2 SE = 0.7483 relating to descriptors XA-hydrophobic area and dipole moment which were having significant correlation with biological activity. The predictive power of this model was discerned by taking test series which gave significant statistical results. Thus, this validated model brings important structural insight to aid in the design of novel antitubercular agents.

Abstract P2-09-10: Feasibility Assessment of Pharmacogenomic Predictors Developed from Breast Cancer Cell Lines To Predict Breast Cancer Patient Pathological Response in Neoadjuvant Chemotherapy

Abstract Background: Studies of developing pharmacogenomic predictors from cancer cell lines to predict cancer patient clinical response and outcome to chemotherapy have yielded both positive and negative results. The variability in these results may arise from the noise inherent of microarray technology as well as the small sample size of in cell line studies. Therefore, it is greatly needed to evaluate the feasibility of using cell lines to develop pharmacogenomic predictors of patient pathological response. Material and Methods: Thirty breast cancer cell lines were exposed to 10 concentrations of paclitaxel-5-fluorouracil-doxorubicin-cyclophosphamide (TFAC) to measure in vitro chemosensitivity. Two independent and publicly available microarray datasets (Hoeflich and Neve) on these breast cancer cell lines together with the chemosensitivity results were used to identify pharmacogenomic predictors from each dataset. Two independent clinical trials (Hess and Popovici) with publically available data, having 130 and 100 patients respectively, were used as test sets to validate the accuracy of the pharmacogenomic predictors. All patients received TFAC as neoadjuvant therapy and the gene expression profiles of patients were assessed before receiving chemotherapy treatment. The patient's pathological complete response (pCR) was determined after treatment to evaluate the chemotherapy efficacy. The pharmacogenomic predictors developed from each of the cell line studies were evaluated for their ability to predict patient pCR in each of the clinical trials using the supervised principle component regression method. Results: The pharmacogenomic predictors identified from the Hoeflich and Neve cell line data (training sets) predicted pCR of the patients in the two clinical trials (test sets) with 64%-68% accuracy, 70%-87% sensitivity, and 60%-67% specificity when 100 genes were selected as pharmacogenomic predictors (Table 1). Conclusions: The four independent prediction results generated in this study demonstrate the feasibility of using breast cancer cell lines to identify pharmacogenomic predictors of response to chemotherapy treatment for breast cancer patients. Future studies will examine the use of drug responses from primary cultures of patient tumors to develop pharmacogenomic predictors of breast cancer patient responses to chemotherapy treatment. Table 1. Prediction of breast cancer patients’ pCR by pharmacogenomic predictors derived from breast cancer cell lines. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-09-10.

Improving power in genetic-association studies via wavelet transformation

BackgroundA key to increasing the power of multilocus association tests is to reduce the number of degrees of freedom by suppressing noise from data. One of the difficulties is to decide how much noise to suppress. An often overlooked problem is that commonly used association tests based on genotype data cannot utilize the genetic information contained in spatial ordering of SNPs (see proof in the Appendix), which may prevent them from achieving higher power.ResultsWe develop a score test based on wavelet transform with empirical Bayesian thresholding. Extensive simulation studies are carried out under various LD structures as well as using HapMap data from many different chromosomes for both qualitative and quantitative traits. Simulation results show that the proposed test automatically adjusts the level of noise suppression according to LD structures, and it is able to consistently achieve higher or similar powers than many commonly used association tests including the principle component regression method (PCReg).ConclusionThe wavelet-based score test automatically suppresses the right amount of noise and uses the information contained in spatial ordering of SNPs to achieve higher power.

Simultaneous Kinetic‐Potentiometric Determination of Hydrazine and Thiosemicarbazide by Partial Least Squares and Principle Component Regression Methods

AbstractSimultaneous determination of hydrazine (HZ) and thiosemicarbazide (TSC) by partial least squares (PLS) and principle component regression (PCR) was carried out based on kinetic data of novel potentiometry. The rate of chloride ion production in reaction of HZ and TSC with N‐chlorosuccinimide (NCS) was monitored by a chloride ion‐selective electrode. The experimental dada shows not only the good ability of ion‐selective electrodes (ISEs) as detectors for the direct determination of chloride ions but also for simultaneous kinetic‐potentiometric analysis using chemometrics methods. The methods are based on the difference observed in the production rate of chloride ions. The results show that simultaneous determination of HZ and TSC can be performed in their concentration ranges of 0.7‐20.0 and 0.5‐20.0 μg mL−1, respectively. The total relative standard error for applying PLS and PCR methods to 9 synthetic samples in the concentration ranges of 0.8‐10 μg mL−1 of TSC and 1.0‐12.0 μg mL−1 of HZ was 4.62 and 4.98, respectively. The effects of certain foreign ions upon the reaction rate were determined for the assessment of the selectivity of the method. Both methods (PLS and PCR) were validated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ and TSC in water samples.

Solid-phase extraction and simultaneous determination of trace amounts of sulphonated and azo sulphonated dyes using microemulsion-modified-zeolite and multivariate calibration

A simple and rapid analytical method for the determination of trace levels of five sulphonated and azo sulphonated reactive dyes: Cibacron Reactive Blue 2 (C-Blue, trisulphonated dye), Cibacron Reactive Red 4 (C-Red, tetrasulphonated azo dye), Cibacron Reactive Yellow 2 (C-Yellow, trisulphonated azo dye), Levafix Brilliant Red E-4BA (L-Red, trisulphonated dye), and Levafix Brilliant Blue E-4BA (L-Blue, disulphonated dye) in water is presented. Initially, the dyes were preconcentrated from 250 ml of water samples with solid-phase extraction using natural zeolite sample previously modified with a microemulsion. The modified zeolite exhibited an excellent extraction for the dyes from solution. The parameters that influence quantitative recovery of reactive dyes like amount of extractant, volume of dye solution, pH, ionic strength, and extraction–elution flow rate were varied and optimized. After elution of the adsorbed dyes, the concentration of dyes was determined spectrophotometrically with the aid of principle component regression (PCR) method without separation of dyes. The results obtained from PCR method were comparable to those obtained from HPLC method confirming the effectiveness of the proposed method. With the aid of SPE by M-zeolite, the concentration of dyes could be reproducibly detected over the range 25–200 ppb for C-Yellow and L-Blue and from 50 to 250 ppb for C-Blue, C-Red, and L-Red. The multivariate detection limits of dyes were found to be 15 ppb for C-Yellow and L-Blue and 25 ppb for C-Blue, C-Red, and L-Red dyes. The proposed chemometric method gave recoveries from 85.4 to 115.3% and R.S.D. from 1.0 to 14.5% for determination of the five dyes without any prior separation for solutes.

Simultaneous determination of Nifuroxazide and Drotaverine hydrochloride in pharmaceutical preparations by bivariate and multivariate spectral analysis

The quantitative predictive abilities of the new and simple bivariate spectrophotometric method are compared with the results obtained by the use of multivariate calibration methods [the classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS)], using the information contained in the absorption spectra of the appropriate solutions. Mixtures of the two drugs Nifuroxazide (NIF) and Drotaverine hydrochloride (DRO) were resolved by application of the bivariate method. The different chemometric approaches were applied also with previous optimization of the calibration matrix, as they are useful in simultaneous inclusion of many spectral wavelengths. The results found by application of the bivariate, CLS, PCR and PLS methods for the simultaneous determinations of mixtures of both components containing 2–12 μg ml −1 of NIF and 2–8 μg ml −1 of DRO are reported. Both approaches were satisfactorily applied to the simultaneous determination of NIF and DRO in pure form and in pharmaceutical formulation. The results were in accordance with those given by the EVA Pharma reference spectrophotometric method.

Simultaneous Kinetic‐Spectrophotometric Determination of Hydrazine and its Derivatives by Partial Least Squares and Principle Component Regression Methods

AbstractSimultaneous kinetic‐spectrophotometric determination of a ternary mixture of hydrazine (HZ) and its derivatives by principal component regression (PCR) and partial least squares (PLS) calibration is described. The methods were based on the difference observed in the reduction rate of iron(III) with HZ, thiosemicarbazide (TSCZ) and phenylhydrazine (PHZ) in the presence of 2,2′‐bipyridine (Bpy). The colored complex of [Fe(Bpy)3]2+ was formed in sodium dodecyl sulfate (SDS) as micellar media, and then monitored at 520 nm. The results showed that simultaneous determination of HZ, TSCZ and PHZ could be performed in their concentration ranges of 1.0–70.0, 0.2–6.0 and 0.1–10.0 μg mL−1, respectively. The root mean squares errors of prediction (RMSEP) of HZ, TSCZ and PHZ were 0.719, 0.164 and 0.105 (for PLS) 0.788, 0.166 and 0.993 (for PCR), respectively. Both methods (PCR and PLS) were validated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ, TSCZ and PHZ in water samples.

Simultaneous determination of domperidone and cinnarizine in a binary mixture using derivative spectrophotometry, partial least squares and principle component regression calibration.

This work is concerned with the simultaneous determination of domperidone maleate (DOM) and cinnarizine (CINN) in a binary mixture form, without previous separation, by two different techniques. The first method is the application of derivative spectrophotometry where the linearity range and percentage recoveries for DOM and CINN were 2.5-30 micro g mL(-1), 5-25 micro g mL(-1) and 100.06+/-1.157, 99.93+/-1.377, respectively. The second method depends on the application of partial least squares (PLS) and principle component regression (PCR) models. A training set consisting of 10 mixtures containing 5-20 micro g mL(-1) for each component was used for the construction of the PCR and PLS models. These models were used after their validation for the prediction of the concentration of DOM and CINN in their mixtures. The proposed procedures were successfully applied for the simultaneous determination of both drugs in laboratory prepared mixtures and in commercial tablet preparations. The validity of the proposed methods was assessed by applying the standard addition technique where the percentage recovery of the added standard was found to be 99.98+/-0.297 and 99.84+/-0.700 for DOM and CINN, respectively, using the derivative spectrophotometric method and 100.29+/-0.398 and 100.11+/-0.363 for DOM and CINN, respectively, using the PLS and PCR methods. The proposed procedures are rapid, simple, require no preliminary separation steps and can be used for routine analysis of both drugs in quality control laboratories.