Application of PLS and PCR as Multivariate Calibration Techniques for Simultaneous Estimation of Ofloxacin and Ornidazole in Binary Mixtures
A. S. Sutar*, M. B. Mangsule
School of Pharmacy, Dr. Vishwanath Karad MIT World Peace University, Pune - 411038, India.
*Corresponding Author E-mail: abhijitsutar@gmail.com
ABSTRACT:
Two chemometric methods PLS and PCR were used to simultaneously estimate Ofloxacin and Ornidazole in binary mixtures. Mean centering is used as a preprocessing tool and then PLS and PCR models were built with help of calibration and validation set. These methods showed good results for validation parameters including accuracy, precision, linearity, robustness etc. at the same time lower values of RMSEP, PRESS and RMSECV shows statistical significance of the developed methods. Results show that multivariate calibrations techniques can be successfully used to analyses Ofloxacin and Ornidazole in pharmaceutical formulations.
KEYWORDS: Chemometrics, Partial Least Square, Principal component, Validation, Ofloxacin, Ornidazole.
INTRODUCTION:
This work demonstrates accurate, precise, and robust multivariate methods to simultaneously determine Ofloxacin and Ornidazole in binary mixture.
Chemometrics is the science of obtaining information from chemical systems. Partial Least Square Regression (PLS) and Principal Component Analysis (PCR) are the two most widely employed multivariate calibration methods to determine a specific compound qualitatively and quantitatively. A relationship is developed from the instrumental data and mathematical model is developed to predict the composition of analyte of interest from the sample. Theoretical details of these methods and applications can be found in the literature.8-10.
MATERIAL AND METHODS:
UV-VIS spectrophotometer (Lab India UV 3200) was used for the measurement of absorbance of ofloxacin and ornidazole within the range of 200-400nm with an interval of 1nm and slit width of 1 nm was used to collect the spectra. All spectral measurement were performed using quartz sample cell and methanol as a reference. Solo 9.0 (Eigenvector) with was used to perform Partial Least Square and Partial Component Regression techniques.
Chemicals and Reagents:
Highly reputed pharmaceutical companies provided Ofloxacin and Ornidazole as a gift sample, accompanied with a certificate of analysis. Solvents and reagents of spectroscopic grade were used. Pharmaceutical tablet formulation were purchased from local pharmacy shop.
Preparation of standard solution:
The standard stock solutions of Ofloxacin and Ornidazole were prepared by weighing 10mg of each drug and dissolving it in enough methanol to make up the volume up to 100ml. This standard stock solution was diluted to a concentration range of 2-12mcg/ml for Ofloxacin and 5-60mcg/ml for Ornidazole. The resulting solutions were scanned in the UV spectrophotometer in the range of 200 nm to 400nm.
Chemometric Method:
PCR and PLS are the tools which are used for factor analysis using multivariate analysis. Initial step in both methods involve preparation of calibration set with known concentration of both drugs in a binary mixture. All the solutions with varying concentrations of ofloxacin and ornidazole were scanned between 200 nm to 400 nm. Second step involve preparation of validation set with known concentration of analyte. Finally, a model will be developed and used for determination of concentration from the sample. Sample solutions were scanned within given range of wavelength and further processed with the PLS toolbox. Mean centering preprocessing was used for smoothing the raw data. In case of PLS two latent variables were used and in case of PCR two principal components were selected based on PRESS value. Venetian blinds method was used as a cross validation tool. Table 1 shows the calibration set that was used to develop the model.
Table 1. The composition of calibration set
|
Sample number |
Ofloxacin (ug/ml) |
Ornidazole (ug/ml) |
|
|
1 |
0.5 |
1.25 |
|
|
2 |
1 |
2.5 |
|
|
3 |
1.5 |
3.75 |
|
|
4 |
2 |
5 |
|
|
5 |
2.5 |
6.25 |
|
|
6 |
3 |
7.5 |
|
|
7 |
3.5 |
8.75 |
|
|
8 |
4 |
10 |
|
|
9 |
4.5 |
11.25 |
|
|
10 |
5 |
12.5 |
|
|
11 |
5.5 |
13.75 |
|
|
12 |
66 |
15 |
|
|
13 |
6.5 |
16.25 |
|
|
14 |
7 |
17.5 |
|
|
15 |
7.5 |
18.75 |
|
|
16 |
8 |
20 |
|
|
17 |
8.5 |
21.25 |
|
18 |
9 |
22.5 |
|
19 |
9.5 |
23.75 |
|
20 |
10 |
25 |
|
21 |
10.5 |
26.5 |
|
22 |
11 |
27.5 |
|
23 |
11.5 |
28.75 |
|
24 |
12 |
30 |
RESULTS AND DISCUSSION:
The PRESS value (Prediction Error Sum of Square) was computed, and the number of optimum components was chosen based on this value. It is shown in fig 1 and 2 for Ofloxacin and Ornidazole respectively.
Figure 1. PRESS PCR Plot
Figure 2. PRESS plot for PLS
With the values obtained by the Standard Error of Calibration (SEC) and the Root Mean Standard Error of Prediction (RMSEP) the prediction capability of these methods were evaluated. The developed PCR and PLS models were validated with the help of a validation set of 12 random samples was prepared developed model was applied and concentration of both analytes was determined with the results of amount recovered, percentage recovery and standard deviation is shown in table 2.
Table 2. Predicted validation using PCR and PLS methods
|
Method |
PLS |
PCR |
|||||||
|
OFX |
ORNI |
OFX |
ORNI |
OFX |
ORNI |
||||
|
Actual ug/ml |
predicted |
%R* |
predicted |
%R* |
Predicted |
%R* |
predicted |
%R* |
|
|
2 |
5 |
1.98 |
99 |
4.99 |
99.8 |
2.01 |
100.5 |
5.04 |
100.8 |
|
3 |
7.5 |
2.96 |
98.66 |
7.48 |
99.73 |
3.04 |
101.3333 |
7.51 |
100.1333 |
|
4 |
10 |
3.97 |
99.25 |
10.04 |
100.4 |
3.96 |
99 |
10.09 |
100.9 |
|
5 |
12.5 |
4.96 |
99.2 |
12.47 |
99.76 |
4.99 |
99.8 |
12.505 |
100.04 |
|
6 |
15 |
6.02 |
100.33 |
15.03 |
100.2 |
5.98 |
99.66667 |
14.98 |
99.86667 |
|
7 |
17.5 |
7.04 |
100.57 |
17.51 |
100.05 |
7.02 |
100.2857 |
17.47 |
99.82857 |
|
8 |
20 |
7.95 |
99.37 |
19.98 |
99.9 |
7.98 |
99.75 |
20.05 |
100.25 |
|
9 |
22.5 |
8.96 |
99.55 |
22.46 |
99.82 |
9.03 |
100.3333 |
22.513 |
100.0578 |
|
10 |
25 |
10.06 |
100.6 |
25.06 |
100.24 |
10.06 |
100.6 |
25.06 |
100.24 |
|
11 |
27.5 |
11.02 |
100.18 |
27.5 |
100 |
11.04 |
100.3636 |
27.52 |
100.0727 |
|
12 |
30 |
11.98 |
99.83 |
29.98 |
99.93 |
12.05 |
100.4167 |
30.11 |
100.3667 |
|
|
|
Mean |
99.68 |
|
99.98 |
Mean |
100.1863 |
|
100.2323 |
|
|
|
SD |
0.6599 |
|
0.2175 |
SD |
0.609768 |
|
0.344371 |
|
|
|
%RSD |
0.6620 |
|
0.2176 |
%RSD |
0.608634 |
|
0.343573 |
Method Validation:
Validation of the following validation parameters precision, accuracy, limit of detection, and limit of quantitation, linearity was done with the help of the developed Partial Least Square (PLS) and Principal Component Regression (PCR) chemometric techniques. Linearity of the method was studied using calibration curve which shows linearity from 2-12 mcg/ml and 5-60 mcg/ml. The USP guidelines were used to calculate the Limits of Detection (LOD) and Limits of Quantitation (LOQ), results of regression analysis is shown in table 3 and calibration curves are shown in fig 3 and 4.
Table 3. Results of the regression analysis
|
Parameter |
PLS |
PCR |
||
|
OFX |
ORNI |
OFX |
ORNI |
|
|
Linearity |
2-12 |
5-60 |
2-12 |
5-60 |
|
Correlation Coefficient |
0.9978 |
0.9992 |
0.9983 |
0.9988 |
|
RMSEP |
0.5398 |
0.7233 |
0.9523 |
0.6311 |
|
RMSECV |
0.9251 |
0.8933 |
0.8203 |
0.7194 |
|
LOD |
0.527 |
0.976 |
0.487 |
0.874 |
|
LOQ |
1.487 |
1.917 |
1.197 |
1.744 |
Figure 3. Calibration curve for Ofloxacin
Figure 4. Calibration curve for Ornidazole
Accuracy studies were performed using recovery studies at three levels of 80%, 100% and 120% with standard addition method as per regulatory guidelines. Standard solutions of Ofloxacin and Ornidazole were spiked into sample solutions that were pre analyzed, and the resulting solutions were scanned in the 200-400nm range. Tables 4 and 5 demonstrate the results by using the developed PCR and PLS models to estimate the concentrations of both compounds.
Interday and Intraday precision was calculated using mid concentration and it was done in triplicate. Standard deviation and relative standard deviation were used to evaluate the precision of the method. Both methods showed good precision below 2 which is within the specified range of regulatory guidelines, results are shown in table 6 and 7.
Table 4 Validation parameter (Accuracy) data- Ofloxacin (using PCR and PLS techniques)
|
Level |
Sample conc. ug/ml |
Standard added ug/ml |
Total conc. ug/ml |
Recovered conc. ug/ml |
% Recovery |
|||
|
|
PLS |
PCR |
PLS |
PCR |
||||
|
80% |
4 |
3.2 |
7.2 |
7.17 |
7.25 |
99.58 |
100.69 |
|
|
4 |
3.2 |
7.2 |
7.19 |
7.28 |
99.86 |
101.11 |
||
|
4 |
3.2 |
7.2 |
7.21 |
7.32 |
100.13 |
101.66 |
||
|
100% |
4 |
4 |
8 |
7.98 |
8.12 |
99.75 |
101.5 |
|
|
4 |
4 |
8 |
7.96 |
8.1 |
99.5 |
101.25 |
||
|
4 |
4 |
8 |
8.02 |
8.09 |
100.25 |
101.12 |
||
|
120% |
4 |
4.8 |
8.8 |
8.82 |
8.9 |
100.22 |
101.13 |
|
|
4 |
4.8 |
8.8 |
8.81 |
8.93 |
100.11 |
101.47 |
||
|
4 |
4.8 |
8.8 |
8.79 |
8.86 |
99.88 |
100.68 |
||
|
Mean |
|
|
|
|
|
99.92 |
101.18 |
|
|
SD |
|
|
|
|
|
0.2765 |
0.3402 |
|
|
%RSD |
|
|
|
|
|
0.2767 |
0.3362 |
|
Table 5 Validation parameter (Accuracy) data- Ornidazole (using PCR and PLS techniques)
|
Level |
Sample conc. ug/ml |
Standard added ug/ml |
Total conc. ug/ml |
Recovered conc. ug/ml |
% Recovery |
||
|
|
PLS |
PCR |
PLS |
PCR |
|||
|
80% |
10 |
8 |
18 |
17.98 |
18.29 |
99.88 |
101.61 |
|
10 |
8 |
18 |
17.95 |
18.25 |
99.72 |
101.38 |
|
|
10 |
8 |
18 |
18.08 |
18.23 |
100.44 |
101.27 |
|
|
100% |
10 |
10 |
20 |
20.1 |
20.27 |
100.5 |
101.35 |
|
10 |
10 |
20 |
19.94 |
20.34 |
99.7 |
101.7 |
|
|
10 |
10 |
20 |
19.86 |
20.29 |
99.3 |
101.45 |
|
|
120% |
10 |
12 |
22 |
21.93 |
22.27 |
99.68 |
101.22 |
|
10 |
12 |
22 |
21.98 |
22.38 |
99.90 |
101.72 |
|
|
10 |
12 |
22 |
22.03 |
21.89 |
100.13 |
99.5 |
|
|
Mean |
|
|
|
|
|
99.92 |
101.24 |
|
SD |
|
|
|
|
|
0.3853 |
0.6794 |
|
%RSD |
|
|
|
|
|
0.3856 |
0.6711 |
Table 6 Inter-Day Precision
|
Amount Taken μg/ml |
Predicted Conc.(μg/ml) |
% Recovery |
|||||||
|
PCR |
PLS |
PCR |
PLS |
||||||
|
OFX |
ORNI |
OFX |
ORNI |
OFX |
ORNI |
OFX |
ORNI |
OFX |
ORNI |
|
4 |
10 |
4.01 |
10.11 |
4.06 |
10.08 |
101.5 |
101.1 |
101.5 |
100.8 |
|
4 |
10 |
4.08 |
10.07 |
4.04 |
10.12 |
101 |
100.7 |
101 |
101.2 |
|
4 |
10 |
4.05 |
10.04 |
3.93 |
10.07 |
98.25 |
100.4 |
98.25 |
100.7 |
|
4 |
10 |
4.11 |
10.03 |
4.06 |
10.14 |
101.5 |
100.3 |
101.5 |
101.4 |
|
4 |
10 |
4.08 |
9.97 |
3.99 |
10.19 |
99.75 |
99.7 |
99.75 |
101.9 |
|
4 |
10 |
4.13 |
9.94 |
4.07 |
10.05 |
101.75 |
99.4 |
101.75 |
100.5 |
|
Mean |
4.025 |
10.1083 |
100.625 |
100.267 |
100.625 |
101.083 |
|||
|
SD |
0.05468 |
0.05193 |
1.36702 |
0.62823 |
1.36702 |
0.51929 |
|||
|
%RSD |
1.35853 |
0.51373 |
1.35853 |
0.62655 |
1.35853 |
0.51373 |
|||
Table 7. Assay results-Actual values and Predicted values using PLS and PCR techniques (Ofloxacin, Ornidazole)
|
Method |
PLS |
PCR |
|||||||
|
OFX |
ORNI |
OFX |
ORNI |
OFX |
ORNI |
||||
|
Actual ug/ml |
predicted |
%R* |
predicted |
%R* |
Predicted |
%R* |
predicted |
%R* |
|
|
4 |
10 |
3.99 |
99.75 |
10.11 |
101.1 |
4.1 |
102.5 |
10.13 |
101.3 |
|
4 |
10 |
4.02 |
100.5 |
10.12 |
101.2 |
4.06 |
101.5 |
10.15 |
101.5 |
|
4 |
10 |
4.04 |
101 |
10.03 |
100.3 |
4.02 |
100.5 |
10.11 |
101.1 |
|
4 |
10 |
3.99 |
99.75 |
10.06 |
100.6 |
4.01 |
100.25 |
10.07 |
100.7 |
|
4 |
10 |
3.96 |
99 |
9.96 |
99.6 |
4.08 |
102 |
10.04 |
100.4 |
|
4 |
10 |
4.06 |
101.5 |
9.98 |
99.8 |
4.05 |
101.25 |
10.17 |
101.7 |
|
Mean |
|
100.25 |
|
100.43 |
|
101.33 |
|
101.11 |
|
|
SD |
|
0.9219 |
|
0.6592 |
|
0.8612 |
|
0.4915 |
|
|
%RSD |
|
0.9196 |
|
0.6564 |
|
0.8498 |
|
0.4861 |
|
Formulation Analysis:
The average weight of each tablet was estimated after twenty tablets were accurately weighed. Weighed powder containing 10mg of ofloxacin and 25mg of ornidazole was put in a 100mL volumetric flask. After adding 30mL of methanol, the solution was shaken for 15minutes before filtering. With methanol, the filtrate and washing were diluted to the desired concentration of 100g/ml. This solution was utilised to do further research. Table 8 shows the results.
CONCLUSION:
Two chemometric approaches were reported for estimating Ofloxacin and Ornidazole in binary mixtures simultaneously. The developed methods can be successfully used for determination of these analytes in their pharmaceutical formulations. Validation results show that the methods are accurate, precise and robust and can be used for routine analysis in laboratory.
ACKNOWLEDGEMENT:
The authors are grateful to the administration of MIT World Peace University for providing the required facilities for the experiment to be carried out.
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Received on 10.02.2022 Modified on 16.05.2022
Accepted on 03.09.2022 ©Asian Pharma Press All Right Reserved
Asian J. Pharm. Ana. 2022; 12(4):228-232.
DOI: 10.52711/2231-5675.2022.00037