Resolution of fivecomponent mixture using mean centering ratio and inverse least squares chemometrics
 Mahmoud Mohamed Issa^{1},
 R’afat Mahmoud Nejem^{2}Email author,
 Alaa Mohamed Abu Shanab^{3} and
 Nahed Talab Shaat^{4}
https://doi.org/10.1186/1752153X7152
© Issa et al.; licensee Chemistry Central Ltd. 2013
Received: 18 June 2013
Accepted: 9 September 2013
Published: 12 September 2013
Abstract
Background
A comparative study of the use of mean centering of ratio spectra and inverse least squares for the resolution of paracetamol, methylparaben, propylparaben, chlorpheniramine maleate and pseudoephedrine hydrochloride has been achieved showing that the two chemometric methods provide a good example of the high resolving power of these techniques. Method (I) is the mean centering of ratio spectra which depends on using the mean centered ratio spectra in four successive steps that eliminates the derivative steps and therefore the signal to noise ratio is improved. The absorption spectra of prepared solutions were measured in the range of 220–280 nm. Method (II) is based on the inverse least squares that depend on updating developed multivariate calibration model. The absorption spectra of the prepared mixtures in the range 230–270 nm were recorded.
Results
The linear concentration ranges were 0–25.6, 0–15.0, 0–15.0, 0–45.0 and 0–100.0 μg mL^{1} for paracetamol, methylparaben, propylparaben, chlorpheniramine maleate and pseudoephedrine hydrochloride, respectively. The mean recoveries for simultaneous determination were between 99.9101.3% for the two methods. The two developed methods have been successfully used for prediction of fivecomponent mixture in Decamol Flu syrup with good selectivity, high sensitivity and extremely low detection limit.
Conclusion
No published method has been reported for simultaneous determination of the five components of this mixture so that the results of the mean centering of ratio spectra method were compared with those of the proposed inverse least squares method. Statistical comparison was performed using ttest and Fratio at P = 0.05. There was no significant difference between the results.
Keywords
Background
Paracetamol (PA) is an analgesic and antipyretic agent [1], which is associated with pseudoephedrine hydrochloride (PS), a direct and indirectacting sympathomimetic agent [2] and chlorpheniramine maleate (CH), a potent antihistaminic [3], in addition to methylparaben (MP) and propylparaben (PP), which are used as preservatives. The combination of PA, CH and PS is used for symptomatic treatment of coughs and the common cold. The UV absorption spectra of PA, MP, PP, CH, and PS displays considerable overlapping, where the application of the conventional spectrophotometry failed to resolve it. No spectrophotmetric analytical method has been reported for the simultaneous determination of PA, MP, PP, CH, and PS in a multicomponent mixture.
While official methods have been reported for the determination of each of these drugs alone in their formulations [4], the most prominent method for simultaneous determination of PA, MP, PP, CH, and PS is the HPLC, GCMS or LCMS [5–11]. However, these reported methods suffered from using solvents of high cost, timeconsuming extraction procedure and long chromatographic retention time. In addition, the United States pharmacopeia suggested the reduction in amount of toxic organic solvents which used in HPLC assays that caused harm to human health and environment [12]. Therefore, chemometricassisted spectrophotometry as a simple, rapid and low cost method can be a good alternative one if it is combined with multivariate calibration methods for determination of a complex in pharmaceutical quality control laboratories. The development of chemometric techniques has enabled the application to the analysis of complex mixtures without the need for any prior separation.
In particular, mean centering of ratio spectra (MCR) is used to remove the contribution of absorbing reagent from data matrix precisely and therefore the absorbance of reagent(s) is exactly eliminated [13–15]. Mean centering of ratio spectra have been presented by Afkhami and Bahram [16] applied for simultaneous analysis of binary and ternary mixture [17–22] MCR method has the advantage of eliminating the derivative steps and therefor the signaltonoise is not degraded.
Multivariate calibration technique is gaining publicity for quantification of multicomponent system even in the presence of intense spectral overlap between analytes [23, 24]. Classical least squares, partial least squares, principal component regression and inverse least squares are the most common multivariate calibration tool due to their powerful calibration and ease of implementation [25–31].
In the present work a simple, rapid and inexpensive mean centering of ratio spectra (MCR) and inverse least squares methods (ILS) are developed for the resolution of fivecomponent mixture. The results of the two chemometric assisted spectrophotometric methods were compared with each other.
Theoretical background
MCR developed method
where

A_{m} is the vector of the absorbance of the mixture,

α_{PA}, α_{MP}, α_{PP}, α_{CH}, and α_{PS} are the absorptivity vectors of PA, MP, PP, CH

and PS and C_{PA}, C_{MP}, C_{PP}, C_{CH}, and C_{PS} are the concentrations of PA, MP, PP, CH and PS, respectively.
Equation (6) is the mathematical basis of multicomponent analysis which permits the determination of the concentration of each compounds without interference from the other components of the mixture.
In practice, the signal of the fourth ratio spectrum of PS is dependent only on the concentration value C_{PS} and $\frac{{A}_{m}}{{\alpha}_{\mathrm{CH}}}$, but is independent of the concentration values C_{PA}, C_{MP}, C_{PP}, and C_{CH} in the mixture. In the developed method, the concentration C_{PS} in the mixture is proportional to the amount of $\mathit{mc}\phantom{\rule{1.12em}{0ex}}\frac{\mathit{mc}y/\mathit{mc}Z}{\mathit{mc}\phantom{\rule{0.24em}{0ex}}o}$ corresponding to a maximum or minimum point.
A calibration curve could be constructed by plotting $\mathit{mc}\phantom{\rule{1.12em}{0ex}}\frac{\mathit{mc}y/\mathit{mc}Z}{\mathit{mc}\phantom{\rule{0.24em}{0ex}}o}$ against different concentration of PS. As explained previously, this technique can be used for other systems, particularly for more than five components system. By using the calibration curve, the concentration of PS was determined in a sample containing PA, MA, PP and CH. The concentrations of the other components (PA, MA, PP and CH) are determined separately by analogous procedures of PS.
ILS method
This model appears to be the best approach for almost all quantitative analyses since no knowledge of the sample composition is needed beyond the concentrations of the constituents of interest.
Materials and methods
Instrumentation and software
A shimadzu (Kyoto, Japan) UV1650 PC, UVVisible doublebeam spectrophotometer with two matched 1 cm pathlength quartz cells was used. This instrument is used for all the absorbance measurements. Using the “online matrix calculator bluebit, powered by Net Matrix Library (http://www.bluebit.gr/matrixcalculator), all the treatment of data was performed. The subsequent statistical manipulations were performed by transferring the spectral data to Microsoft Excel 2010 program and SPSS.
Reagents and materials
Pharmaceutical grade of PA, MP, PP, CH and PS with claimed purities of 99.8, 99.9, 99.7, 99.7 and 99.9%, respectively according to manufactures certificate were kindly donated by the Middle East pharmaceuticals and cosmetics laboratories, Palestine.
Decamol Flu syrup (batch number 1943) (Middle East pharmaceuticals and cosmetics laboratories, Palestine) was used. Each 5.0 ml contains 160 mg PA, 5.0 mg MP, 1.0 mg PP, 1.0 mg CH and 1.0 mg PS.
Stock standard and working solutions
Stock solutions of PA, MP, PP, CH and PS were independently prepared by dissolving 100.0 mg of each in 100.0 mL of 0.1 M HCl (Merck). Working solutions were prepared by transferring appropriate volumes of the stock solutions to separate 25.0 ml volumetric flasks and diluted to their marks with 0.1 M HCl. A series of five solutions of each compound in the concentration range of 0–25.6 μg mL^{1} for PA, 0–15.0 μg mL^{1} MP, 0–15.0 μg mL^{1} PP, 0–45.0 μg mL^{1} CH and 0–100.0 μg mL^{1} PS was obtained from the stock solutions. A 25 laboratory sample mixtures containing different ratios of the five studied components were prepared and used in the calibration and validation sets.
Procedures
Mean centering of ratio spectra method (MCR)
The absorption spectra of prepared solutions were measured in the range of 220–280 nm. Beer’s law was obeyed for all compounds over the entire wavelengths (220–280 nm).
The first, second, third and fourth ratio spectra data
Drug  X  Y  Z  O  Divisors used 

PS  $\frac{{A}_{m}}{{\alpha}_{\mathrm{CH}}}$  $\frac{\mathit{mc}\phantom{\rule{0.12em}{0ex}}x}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PA}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\mathit{mc}\frac{{\alpha}_{\mathit{MP}}}{{\alpha}_{\mathit{CH}}}}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PA}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\phantom{\rule{0.5em}{0ex}}\mathit{mc}\phantom{\rule{0.12em}{0ex}}\frac{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PP}}/{\alpha}_{\mathit{CH}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PA}}/{\alpha}_{\mathit{CH}}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}z}$  1.0 μg mL^{1} CH 
CH  $\frac{{A}_{m}}{{\alpha}_{\mathit{PA}}}$  $\frac{\mathit{mc}\phantom{\rule{0.12em}{0ex}}x}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PP}}}{{\alpha}_{\mathit{PA}}}}$  $\frac{\mathit{mc}\frac{{\alpha}_{\mathit{MP}}}{{\alpha}_{\mathit{PA}}}}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PP}}}{{\alpha}_{\mathit{PA}}}}$  $\frac{\phantom{\rule{0.5em}{0ex}}\mathit{mc}\phantom{\rule{0.12em}{0ex}}\frac{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PS}}/{\alpha}_{\mathit{PA}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PP}}/{\alpha}_{\mathit{PA}}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}z}$  10.0 μg mL^{1} PA 
PP  $\frac{{A}_{m}}{{\alpha}_{\mathit{CH}}}$  $\frac{\mathit{mc}\phantom{\rule{0.12em}{0ex}}x}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PA}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\mathit{mc}\frac{{\alpha}_{\mathit{MP}}}{{\alpha}_{\mathit{CH}}}}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PA}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\phantom{\rule{0.5em}{0ex}}\mathit{mc}\phantom{\rule{0.12em}{0ex}}\frac{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PS}}/{\alpha}_{\mathit{CH}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PA}}/{\alpha}_{\mathit{CH}}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}z}$  10.0 μg mL^{1} CH 
MP  $\frac{{A}_{m}}{{\alpha}_{\mathrm{CH}}}$  $\frac{\mathit{mc}\phantom{\rule{0.12em}{0ex}}x}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PA}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\mathit{mc}\frac{{\alpha}_{\mathit{PP}}}{{\alpha}_{\mathit{CH}}}}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PA}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\phantom{\rule{0.5em}{0ex}}\mathit{mc}\phantom{\rule{0.12em}{0ex}}\frac{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PS}}/{\alpha}_{\mathit{CH}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PA}}/{\alpha}_{\mathit{CH}}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}z}$  10.0 μg mL^{1} CH 
PA  $\frac{{A}_{m}}{{\alpha}_{\mathrm{CH}}}$  $\frac{\mathit{mc}\phantom{\rule{0.12em}{0ex}}x}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PS}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\mathit{mc}\frac{{\alpha}_{\mathit{MP}}}{{\alpha}_{\mathit{CH}}}}{\mathit{mc}\frac{\phantom{\rule{0.12em}{0ex}}{\alpha}_{\mathit{PS}}}{{\alpha}_{\mathit{CH}}}}$  $\frac{\phantom{\rule{0.5em}{0ex}}\mathit{mc}\phantom{\rule{0.12em}{0ex}}\frac{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PP}}/{\alpha}_{\mathit{CH}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}{\alpha}_{\mathit{PS}}/{\alpha}_{\mathit{CH}}}}{\mathit{mc}\phantom{\rule{0.5em}{0ex}}z}$  10.0 μg mL^{1} CH 
The mean centered values of the fourth ratio spectra at 265, 230, 230, 240 and 260 nm for PA, MP, PP, CH and PS, respectively were measured and plotted against the correspond concentration of each drug to construct their calibration curves.
Different synthetic mixtures containing different ratios of PA, MP, PP, CH and PS within their calibration ranges were prepared. The spectra of these mixtures were recorded and the MCR procedure was performed to predict the concentration of each compound in the mixture.
2.0 ml of Decamol Flu syrup was transferred to 100.0 ml volumetric flasks (five times) dissolved in 0.1 M HCl. Then 1 ml of the solution was transferred to 25.0 ml volumetric flasks and the volume was completed with the same solvent. The proposed method was applied to the prepared solutions.
Inverse least squares method (ILS)
Concentrations of PA, PS, MP, PP and CH (μg mL ^{ 1 } ) in the calibration and validation sets
Sample No.  PA  PS  MP  PP  CH 

1  15.0  0.00  1.50  3.00  4.00 
2  25.6  5.00  1.50  3.00  5.00 
3  25.6  7.00  0.80  0.16  3.00 
4^{*}  20.0  2.40  0.80  0.16  5.00 
5  20.0  0.00  4.00  5.00  5.00 
6  25.6  0.00  4.00  5.00  4.00 
7  10.0  10.0  1.50  3.00  3.00 
8^{*}  15.0  5.00  2.00  4.00  2.00 
9  10.0  0.00  4.00  5.00  4.00 
10  20.0  7.00  1.50  3.00  2.00 
11^{*}  20.0  5.00  1.00  2.00  0.16 
12  5.00  10.0  2.00  4.00  4.00 
13  10.0  2.40  2.00  4.00  2.00 
14^{*}  25.6  0.00  1.00  2.00  5.00 
15^{*}  15.0  7.00  1.00  2.00  4.00 
16  20.0  7.00  2.00  4.00  3.00 
17  5.00  2.40  1.00  2.00  3.00 
18^{*}  15.0  5.00  0.80  0.16  0.16 
19  25.6  2.40  2.00  4.00  0.16 
20^{*}  5.00  10.0  1.50  3.00  5.00 
21  5.00  7.00  4.00  5.00  2.00 
22  10.0  2.40  1.00  2.00  4.00 
23^{*}  20.0  10.0  0.80  0.16  0.16 
24  15.0  10.0  4.00  5.00  0.16 
25  5.00  5.00  0.80  0.16  3.00 
Results and discussion
Mean centering of ratio spectra method (MCR)
The developed MCR method depends on the mean centering of ratio spectra, it eliminates the derivative steps and therefore signal to noise ratio is enhanced [16] and it has been applied for resolving the fivecomponent mixture.
In order to optimize the developed MCR method, effect of divisor on the selectivity of the method has been tested. Different concentrations of each CH, PS and MP were tested. Results in Table 1 shows that the divisor had a great effect on the selectivity of determination of PA, MP, PP, CH and PS where reproducible and good results have been obtained upon using concentration of 10.0 μg mL^{1} of CH (for PP, MP and PA), 1.0 μg mL^{1} CH (for PS) and 10.0 μg mL^{1} PA (for CH) as divisors. On the other hand, changing the concentration of the divisor had no significant effect on the analytical parameters. The amount of Δλ had no effect on the mean centering of ratio spectra. A Δλ of 5 nm was used.
Analytical characteristics for analysis of PA, PS, MP, PP and CH by MCR method
Analyte  λ (nm)  Calibration equations  R^{2}  Linear concentration range (μg mL^{1})  LOD (μg mL^{1}) 

PA  265.0  Y = 47.28C + 2.6  0.9999  025.6  0.05 
MP  230.0  Y = 224.6C2.03  0.9991  015.0  0.05 
PP  230.0  Y = −13.0C + 1.13  0.9995  015.0  0.05 
CH  240.0  Y = 29.77C + 1.13  0.9981  045.0  0.08 
PS  260.0  Y = −35.75C1.25  0.9967  0100.0  0.08 
To check the reproducibility of the method, the relative standard deviation (R.S.D) for five replicate determinations of 5.0 μg mL^{1} of each PA, MP, PP, CH and PS, in fivecomponent mixtures were obtained as 1.91, 1.58, 1.58, 2.45 and 1.66%, respectively. The mean recoveries for simultaneous determination of the five components were obtained as 100.0, 99.9, 100.1, 101.3 and 101.1% for PA, MP, PP, CH and PS, respectively.
Analysis of PA, PS, MP, PP and CH in synthetic mixture by MCR method
Taken (μg mL^{1})  Found (μg mL^{1})  Recovery, %  

PA  MP  PP  CH  PS  PA  MP  PP  CH  PS  PA  MP  PP  CH  PS 
20.0  0.80  0.16  5.00  2.40  20.19  0.816  0.158  5.14  2.38  100.95  102.0  99.0  102.8  99.0 
15.0  2.00  4.00  2.00  5.00  14.92  1.93  4.10  2.12  4.96  99.74  96.0  102.5  106.0  99.2 
20.0  1.00  2.00  0.16  5.00  20.40  0.99  2.02  0.17  4.99  102.10  99.0  101.0  106.0  99.8 
25.6  1.00  2.00  5.00  0.00  25.31  0.98  2.06  4.91  0.00  98.88  98.0  103.0  98.2  102 
15.0  1.00  2.00  4.00  7.00  15.41  1.00  1.90  3.93  7.23  102.73  100.0  95.0  98.3  103.3 
15.0  0.80  0.16  0.16  5.00  15.17  0.832  0.16  0.155  5.11  101.11  104.0  100.0  97.0  102.2 
5.00  1.50  3.00  5.00  10.0  4.95  1.55  3.08  5.19  10.3  99.00  103.3  102.3  103.8  103.0 
20.0  0.80  0.16  0.16  10.0  19.72  0.776  0.157  0.157  10.0  98.60  97.0  98.0  98.0  100.0 
Mean recovery  100.39  99.91  100.10  101.26  101.06  
R.S.E single (%)  1.381  3.123  2.864  2.959  2.183  
R.S.E_{t} (total) (%)  1.624 
Inverse least squares method (ILS)
where, C_{PA}, C_{MP}, C_{CH}, C_{PP} and C_{PS} are the concentration of PA, MP, CH, PP and PS, respectively. The absorbance values at nine points, (230–270 nm) as in Figure 1 for samples were introduced to into the above equations. The concentration of the five component mixtures in Decamol Flu syrup was calculated.
Analytical Characteristics for analysis of PA, MP, PP, CH and PS by ILS method
To check the reproducibility of the method, the R.S.D for five replicate determinations of 5.0 μg mL^{1} each of PA, MP, PP, CH and PS, in the mixtures were obtained as 1.72, 2.13, 1.45, 2.02, and 1.33%, respectively. The mean recoveries were 99.95, 100.38, 100.64, 100.10 and 99.91% for PA, MP, PP, CH and PS respectively.
Results for several experiments of validation tests for analysis of PA, MP, PP, CH and PS by ILS method
Taken (μg mL^{1})  Found (μg mL^{1})  Recovery, %  

PA  MP  PP  CH  PS  PA  MP  PP  CH  PS  PA  MP  PP  CH  PS 
20.0  0.80  0.16  5.00  2.40  20.11  0.79  0.165  4.93  2.36  100.55  98.75  103.03  98.6  98.33 
15.0  2.00  4.00  2.00  5.00  15.22  2.04  4.08  1.98  5.02  101.74  102.0  102.0  99.0  100.4 
20.0  1.00  2.00  0.16  5.00  19.96  0.99  2.03  0.156  5.07  99.80  99.0  101.5  97.5  101.4 
25.6  1.00  2.00  5.00  0.00  25.09  1.00  2.00  5.05  0.00  97.73  100.0  100.0  101.0   
15.0  1.00  2.00  4.00  7.00  14.98  0.98  2.06  4.08  7.08  99.97  98.0  103.0  102.0  101.14 
15.0  0.80  0.16  0.16  5.00  15.13  0.81  0.157  0.160  5.00  100.87  101.25  98.13  100.0  100.0 
5.00  1.50  3.00  5.00  10.0  4.930  1.56  3.02  5.04  9.81  98.60  104.0  97.33  100.8  98.10 
20.0  0.80  0.16  0.16  10.0  20.12  0.80  0.160  0.163  10.0  100.6  100.0  100.0  101.88  100.0 
Mean recovery  99.95  100.38  100.64  100.1  99.91  
S.E.P  0.233  0.127  0.1465  0.144  0.178  
S.E.C  0.466  0.154  0.193  0.189  0.257 
Good coincidence was observed for the assay results by applications of the two methods described in this paper. Comparison of the results in Table 4 and Table 6 proves that the analytical characteristics obtained by MCR method were similar to those obtained by ILS method. These methods appear to be the preeminant approach for almost quantitative analysis, since no knowledge for the sample composition is required beyond the concentrations of the constituents of interest, where the concentration of the analytes in real samples is always unknown.
Analysis of pharmaceutical syrup
Determination of PA, MP, PP, CH and PS in commercial syrup using the proposed methods
Sample No.  Concentration (μg mL^{1})  Recovery, %  

MCR  ILS  
PA  MP  PP  CH  PS  PA  MP  PP  CH  PS  PA  MP  PP  CH  PS  
1  15.36  0.48  0.180  0.100  1.44  98.96  98.00  103.0  98.20  102.0  100.2  97.80  102.1  101.2  99.80 
2  17.92  0.56  0.112  0.112  1.68  99.00  99.00  99.30  99.80  101.4  100.6  99.60  103.1  100.5  99.60 
3  20.43  0.64  0.960  0.960  1.92  101.10  99.60  98.80  100.8  100.1  101.6  101.2  101.4  101.9  99.90 
4  23.04  0.72  0.144  0.144  2.16  100.51  100.3  100.2  99.40  99.40  99.30  101.4  101.3  101.3  98.60 
5  25.60  0.80  0.160  0.160  2.40  100.31  98.20  100.6  98.30  98.30  99.60  98.60  102.1  100.6  100.2 
Mean recovery  100.0  99.00  100.4  99.30  100.6  100.3  99.70  102.0  101.1  99.60  
S.D.^{a}  0.970  0.960  1.620  1.090  0.990  0.900  1.580  0.720  0.570  0.610  
t^{b}  1.280  0.860  0.980  1.610  1.110  
F^{b}  1.160  0.370  5.060  3.660  2.630 
Conclusion
MCR and ILS developed methods were applied for the determination of fivecomponent mixture of PA, MP, PP, CH and PA, where no knowledge for the sample composition is required beyond the concentrations of the constituents of interest. A comparative study of the use of MCR and ILS methods for the resolution of fivecomponent mixture of PA, MP , PP, CH and PS has been accomplished showing that the two multivariate calibration methods provide, with adequate software support, a clear example of the high resolving power of these techniques. These methods have the advantage of high sensitivity, extremely low detection limit, good selectivity, rapid analysis and inexpensive instruments. Furthermore, while working with these methods, one does not need to use toxic organic solvents. In other words, they belong to green chemistry. The developed MCR and ILS methods were found to be suitable for the routine simultaneous determination of PA, MP, PP, CH and PS in pharmaceutical syrup.
Declarations
Acknowledgement
The authors would like to express their appreciation and thanks to the Middle East pharmaceuticals and cosmetics laboratories, Palestine, for the provision of the necessary pharmaceuticals to carry out this work. The authors would also express their sincere appreciations to Chemistry department, Alaqsa university, Palestine, for providing necessary facilities for the work. Also, we thank Mr. Mohd M. Issa for his assist.
Authors’ Affiliations
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