Central Composite Design based Development and Validation of an

RP-HPLC Method for Paclitaxel in Bulk and Pharmaceutical Dosage Form

 

Kiran Kumar Buralla, Varadarajan Parthasarathy*

Department of Pharmacy, Annamalai University, Annamalainagar - 608002, India

 

ABSTRACT:

Objective: Development of an accurate, precise, robust, sensitive, economical and rapid isocratic reverse phase high performance liquid chromatography (RP-HPLC) technique complying quality by design (QbD) and validate according to ICH guidelines for the quantitative estimation of Paclitaxel in bulk and pharmaceutical dosage form. Method: The simultaneous assessment of the Paclitaxel with Nilotanib as internal standard in bulk and pharmaceutical dosage forms with the help of chemometrics, multicriteria decision-making approach. The separation was achieved by utilizing Phenomenex Enable C₁₈ column (Gemini, 15x4.6mm, 5µm particle size) and PDA-UV detection set at 230nm was developed and validation of Paclitaxel in pure form and pharmaceutical formulation, optimized by Derringer’s desirability functions. Chromatographic separation was consisted of a mixture of acetonitrile and KH₂PO₄ (70:30 %v/v, pH 4) adjusted with orthophosphoric acid and the flow rate of 0.8ml/min. Result: Newly developed method resulted in eluting the drug at 3.928min, respectively. The regression coefficients (R²) were observed to be 0.999 for all models. The detection of limits (LOD) was about 9.498ng/ml and quantitation limits (LOQ) were about 31.66ng/ml. The relative standard deviation was observed to be 1.842%. Peak area ratio of the analyte and internal standard was used for the estimation of pharmaceutical formulations. Conclusion: The method was validated by determining its precision, accuracy, and system stability. The results of the investigation demonstrated that the suggested RP-HPLC method is simple, rapid, precise and accurate, which is convenient for the routine determination of Paclitaxel in bulk and pharmaceutical dosage forms.

 

 

 

INTRODUCTION:

Paclitaxel is a mitotic inhibitor; it is one of the broadest range anticancer agents approved by the Food and Drug Administration for the treatment of various types of carcinoma^[1,2]. Molecular formula is C₄₇H₅NO_14, molecular weight is 853.9g/mol, and chemical name is Tax-11-en-9-one-5β-20-epoxy-1, 2α, 4, 7β, 10β, 13α-hexahydroxy-4, 10-diacetate-2-benzoate-13α-phenyl-hippurate^[3] (Fig.1).

 

Figure 1: Chemical Structure of Paclitaxel

 

The literature shows that so many analytical methods were developed for evaluation of the drug by individually or in combination with other drugs. Different analytical methods that contain be reported for evaluations of paclitaxel are HPLC^[4,5] and LC-MS/MS ^[6,7]. The developed methods have been validated according to ICH guidelines for analysis of the drug^[8]. Response surface methodology (RSM) is a statistically designed experimental tool where large numbers of factors are simultaneously examined^[9,10]. The multivariate methodology has advantages incorporated decrease in the number of investigational runs, improves statistical elucidation possibilities and indicates whether parameters interact or not^[11]. CCD is known as a multivariate experimental design which is utilized to improve the chromatographic parameters and their interaction effects and quadratic effects of the mobile phase composition, pH, and flow rate on the peak area ^[12]. The validation of proposed technique is done by the ICH guideline ICH Q2 (R1)^[13].

 

Analytical Quality by Design (AQbD) is a systematic approach to development that starts with a pre-defined aim and emphasizes method comprehension and control based on sound science and quality hazard the executives. AQbD assumes vital role in developing a robust method as an early risk evaluation and recognizes the critical analytical parameters and to concentrate on these factors in method improvement^[14,15,16]. Consequently, the present investigation aimed at the development of a rapid, sensitive and validated RP-HPLC method for the analysis of Paclitaxel in bulk and pharmaceutical dosage forms.

 

MATERIALS AND METHODS:

Chemicals and reagents:

Paclitaxel references sample was a gift sample from Spectrum Laboratories Ltd., Hyderabad, India. HPLC grade chemicals and reagents incorporate acetonitrile, potassium dihydrogen ortho-phosphate buffer and orthophosphoric acid AR grade was obtained from Sd Fine-Chem Ltd, and Milli Q Water (Merk). Paclitaxel is industrially available as Mitotax®100 injection marketed by Dr. Reddy’s Laboratories Ltd., India with a labeled amount of 100mg/16.67ml per Injection.

 

Instrumentation:

The HPLC analysis was carried out on Shimadzu HPLC system (Tokyo, Japan) with two LC-20AD separation modules and SPD-m20A PDA detector. The chromatographic and integrated data were recorded utilizing LC solution data acquisition software. Absorbance spectra were recorded utilizing an UV-Visible double beam spectrophotometer (Systronics 2202 model UV-1601PC, Japan).

 

Statistical software:

Experimental design, data analysis, and desirability function calculation were performed by using version 11 of Design-Expert® programming.

 

Preparation of Buffer:

Weighed 0.680gm of Phosphate Buffer (Potassium dihydrogen orthophosphate) transferred into a 500ml volumetric flask and added 400ml of Milli Q Water (HPLC grade), dissolved by using sonicator or glass rod, and make up the final volume by using solvent. Adjusted the pH of the buffer to 4(±0.5) with ortho-phosphoric acid. Filtered by using membrane filter (Ultipor ®N₆₆ Nylon 6, 6 membrane, 0.45µm).

 

Preparation of Standard Solution:

Stock standard solution of Paclitaxel was prepared in the mobile phase. It was stored at 4⁰C±0.05 and protected from light. Working standard solution of Paclitaxel was freshly prepared by diluting the stock solution with mobile phase before analysis.

 

Preparation of Sample

MITOTAX^®100 injection, it contains 100mg/16.67ml. In this 1.667ml of sample transfer into a 10ml of volumetric flask and added 8ml of mobile phase and sonicated for 1-2 min. The volume made up to 10ml with mobile phase and mixed. Filter the solution through the 0.45µm membrane filter.

 

Preparation of Internal Standard Solution:

The internal standard Nilotanib was taken for accomplishing chromatographic separation at particular retention time for working standard Paclitaxel. For this, 10mg of Nilotanib dissolved in 2ml of mobile phase and volume was adjusted to final volume with mobile phase to form the internal standard solution. Further the solution was suitably diluted to 5mg/ml concentration, and exactly 1ml solution was added to each dilution of standard solution of Paclitaxel.

 

Selection of detection wavelength:

For RP-HPLC method analytical wavelength was determined from UV-spectra of Paclitaxel and Nilotanib recorded by using UV-VIS spectrophotometer. Solutions of both the drugs were scanned in the UV range between 200 to 400nm against blank. Paclitaxel and Nilotanib showed significant absorbance at 230nm using PDA detector as shown in Fig. 2.

 

Figure 2: UV overlay spectra of Paclitaxel and Nilotinib 10 µg/mL in mobile phase

 

Chromatographic Conditions:

The composition of Mobile phase was acetonitrile and phosphate buffer (pH 4) at the proportion of 70:30%v/v was used in isocratic mode at a flow rate of 0.8ml/min. The mobile phase was filtered through 0.45µm Nylon membrane filter and sonicated for 10-15min before use. Injection volume was 20µl and detection was performed at 230nm at ambient temperature.

 

Optimization of RP-HPLC-PDA method:

Initially, trial and error method were applied to gain knowledge about the method performance and recognition of different important independent factors and its effect on dependent factors. The Central-Composite design with response surface was employed for the optimization of experimental conditions of the method. In the present investigation, experiments were planed and performed by the CCD^[17]. In the proposed investigation, 20 trial runs were performed and analyzed for obtained results of retention time, capacity factor, resolution factor, and separation factors in concurring to the Central-Composite Design. Further study was performed using response surface methodology (RSM) to estimate the relationship between the dependent and independent factors using obtained data (Tab. 1).

 

Table 1: Central Composite Design with measured response

Run	Factor A (ACN %v/v)	Factor B (pH)	Factor C (Flow rate)	Response 1 (tR2)	Response 2 (k1)	Response 3 (Rs1,2)	Response 4 (S1,2)
1	70	4	0.8	3.982	1.116	1.616	1.251
2	70	4	1.9	1.676	1.113	1.323	1.252
3	40	6	1.9	0.993	2.146	1.470	1.037
4	55	6.6	1.35	2.824	2.119	0.698	1.123
5	55	5	1.35	4.550	3.146	0.341	1.094
6	55	3.3	1.35	2.369	0.971	1.438	1.267
7	70	6	0.8	4.053	1.388	2.674	1.343
8	55	5	1.35	4.553	3.123	0.512	1.097
9	40	6	0.8	2.569	0.640	0.796	1.191
10	80	5	1.35	1.808	0.314	2.106	1.848
11	55	5	2.27	2.534	2.795	0.435	1.106
12	30	5	1.35	2.502	0.580	2.784	1.089
13	40	4	0.8	17.07	2.774	2.450	2.153
14	40	4	1.9	14.75	1.964	2.136	1.139
15	55	5	0.42	13.28	1.681	4.507	1.931
16	55	5	1.35	4.551	3.146	0.341	1.094
17	55	5	1.35	4.562	3.087	0.444	1.096
18	55	5	1.35	4.559	3.086	0.293	1.095
19	55	5	1.35	4.554	3.124	0.512	1.097
20	70	6	1.9	1.709	1.199	1.331	1.261

Factor A= Acetonitrile content in the mobile phase (%), Factor B= pH of the aqueous phase, Factor C= Flow rate, tR₂= Retention Time, k₁=Capacity, Rs_(1,2)= Resolution and S_(1,2)= Separation

 

Method validation:

The optimized chromatographic method was completely approved by ICH guidelines and Q2B. The calibration curves were tested using one-way ANOVA at 5% significance level^[18].

 

The model was also validated by analysis of variance (ANOVA) utilizing design expert programming, and the outcomes are exhibited in Tab. 2 (A and B). Based on press value, a quadratic model was chosen for responses such as retention time, capacity, resolution and separation factors of Paclitaxel. The significant effects observed with p-value under 0.05, while the low standard deviation (% CV) and adjusted R-square value showed a phenomenal relationship between the trial information and those of the fitted model. The anticipated R-square value was in tolerable concordance with the adjusted R-square value for all responses^[19].

 

Table 2(A): Response models^a and statistical parameters obtained from ANOVA for CCD

Responses	Regression model	Adjusted R2	Model p-value	% C.V	Adequate precision
tR2	+4.50-1.84*A-2.01*B-1.95*C+3.55*AB-0.0940*AC+0.0885*BC-0.5002*A2-0.3441*B2+1.54*C2	0.5436	<0.0315	61.60	6.8553
K1	+3.11-0.2310*A+0.0247*B+0.1741*C+0.2887*AB-0.1110*AC+0.2662*BC-0.8947*A2-0.5065*B2-0.2615*C2	0.7634	<0.0017	24.77	8.4381
Rs1,2	+0 4190-0.0768*A-0.1830*B-0.5949*C+0.4232*AB-0.2495*AC-0.0078*BC+0.6432*A2+0.1563*B2+0.6523*C2	0.6045	<0.0172	49.22	5.7976
S1,2	+1.10+0.0632*A-0.0882*B-0.1931*C+0.1456*AB+0.1359*AC+0.0971*BC+0.1142*A2+0.0175*B2+0.1319*C2	0.5647	<0.0259	16.31	7.6358

 

Table 2(B): ANOVA for response surface reduced quadratic model

Source	Sum of Squares				Mean Square				F-Value				p-Value
	tR2	K1	Rs1,2	S1,2	tR2	K1	Rs1,2	S1,2	tR2	K1	Rs1,2	S1,2	tR2	K1	Rs1,2	S1,2
Model	296.8	16.83	18.3	1.46	32.98	1.87	2.04	0.16	3.5	7.8	4.23	3.74	0.031	0.001	0.01	0.025	Sig
%ACN	46.26	0.729	0.08	0.05	46.23	0.729	0.080	0.05	4.9	3.05	0.16	1.26	0.050	0.111	0.69	0.288
pH	54.95	0.008	0.45	0.10	54.95	0.008	0.457	0.10	5.8	0.03	0.94	2.4	0.036	0.856	0.35	0.148
Flow rate	51.95	0.413	4.83	0.50	51.95	0.413	4.83	0.51	5.5	1.73	10.0	11.7	0.040	0.217	0.01	0.006
Residual	93.86	2.39	4.82	0.43	9.39	0.239	0.481	0.04
Lack of Fit	93.86	2.39	4.77	0.43	18.77	0.478	0.954	0.08					0.0001	0.0001	0.0001	0.0001	Sig
Pure Error	0.0001	0.003	0.04	9.5	0.000	0.0007	0.009	1.9
Cor Total	390.7	19.22	23.1	1.9

ANOVA indicates analysis of variance, df-degrees of freedom, F-Fischers ratio and Sig- Significant

 

In perturbation plots are exhibited for predicted models so as get an impact of an independent factor on a specific response with all other factor held predictable at a reference point. A steepest slope or curvatures indicate the affectability of the response to a specific factor (Fig.3). The pH (factor B) had the most important effect on a retention time tR₂ followed by factor A and C (Fig 3a). The factors pH and flow rate (B and C) had significant effect on K₁ followed by factor A (Fig 3b). The flow rate (factor C) had the most important effect on a Rs_(1,2) followed by factor A and B (Fig 3c). The factors pH and flow rate (B and C) had significant effect on S_(1,2) followed by factor A (Fig 3d).

 

Figure 3: Perturbation plots showing the effect of each independent variables on (a) tR₂ (b) k₁ (c) Rs_(1,2) and (d) S_(1,2), where A is acetonitrile concentration, B is the pH (buffer), C is the flow rate.

 

Response surfaces plots for tR₂, K₁, Rs_(1,2) and S_(1,2) are shown in (Fig. 4) (% ACN concentration was plotted against the pH. Flow rate held at constant at the center value). Examination of perturbation plots and response plots of optimization models demonstrating that the factor A and B had the critical impact on separation of the analytes, while the factor C i.e. the flow rate, is of less significance.

 

Figure 4: Response surfaces related to Acetonitrile (A), pH (B) and Flow rate (C): (a) retention time of the last peak (tR₂), (b) capacity factor first peak (K₁), (c) resolution factor (Rs_(1,2)) and (d) separation factor (S_(1,2)).

 

Validation:

The optimized chromatographic conditions were magnified concern to validation of statement for the system suitability, accuracy, precision, linearity, sensitivity, selectivity and robustness. The optimized RP-HPLC method was validated according to the guidelines of the (ICH) Q2 (R1) for different parameters ^[20].

System suitability:

System suitability tests are referred for evaluated chromatographic system before the sample analysis can start. The system suitability testing was surveyed and %RSD was initiating less than 2% confine demonstrating appropriateness of strategy advancement.

 

Linearity:

Linearity a concentration ranges from 2 to 10µg/ml of Paclitaxel was prepared. The calibrated graph was plotted by taking peak area versus concentration. The correlation coefficient, intercept, slope and linear regression analysis were done^[21]. The results were shown in Tab.3 and Fig. 5.

 

Table 3: Linearity values obtained for Paclitaxel

Conc. (µg/mL)	Ratio of Area (mAU)
2	1.174
4	2.361
6	3.572
8	4.744
10	5.808

 

Figure 5 Calibration curve for Paclitaxel

 

Sensitivity:

With the equation 3.3 and 10, limit of detection (LOD) and quantitation (LOQ) was calculated respectively, where  is the standard deviation of the response (y-intercept) and “S” is the slope of the linearity plot ^[22].

 

Specificity:

It was calculated by comparing experiment results obtained from the analysis of sample solution containing excipient with the results obtained from the standard drug ^[23].

 

Precision:

It was calculated by different concentrations such as 2, 4 and 6µg/ml of Paclitaxel sample were analyzed triplicates ^[24] and the results are shown in Tab. 4.

 

Accuracy:

It is the proximity in the understanding between the accepted true value and the actual results obtained. This investigation is generally assessed by determining the sample of the analyte into the mixture of the samples to be analyzed. For accuracy studies, three different concentrations of solutions such as 8, 10 and 12µg/ml were used. After injecting each concentration mean % recovery was calculated^[25] and the results are shown in Tab. 5.

 

Table 4: Precision values for Paclitaxel

Conc. (µg/mL)	Drug area	Internal Standard	Ratio of area (Drug/IS)	Mean ± SD	% RSD
2	209548	179125	1.169842	1.175 ± 0.005	0.501187
	210418	178968	1.17573
	211288	178811	1.181628
4	420224	178248	2.357524	2.360 ± 0.016	0.681553
	420837	177022	2.377315
	421450	179688	2.345454
6	636542	175366	3.629791	3.598 ± 0.028	0.794085
	639348	178006	3.591722
	640154	179122	3.573844

 

RESULTS AND DISCUSSION:

Linearity:

The results of method validation for linearity revealed that the above assay was linear over the concentration range between 2-10µg/ml for Paclitaxel. The regression coefficient was 0.999 for Paclitaxelare shown inTab.3 and Fig. 5.

 

Precision:

Precision was evaluated by the estimation of intraday precision by assay of three different concentrations of Paclitaxel such as 2, 4 and 6 µg/ml at various time intervals. The RSD (%) for intraday precision for Paclitaxel were in the range of 0.5 – 0.79%, which was within the acceptable limit. The developed method exhibited good precision for the drug shown in Tab. 4

 

Accuracy:

The accuracy of the samples has been computed from measured concentrations of samples extrapolated from calibration curve particularly produced for the determination of the accuracy of the method. The results of accuracy studies for Paclitaxel and Nilotanib are summarized in Tab. 5. It is clearly evident from the result that, %RSD of the compound was found to be less than 2 hence the method can be considered as accurate.

 

Table 5: Accuracy studies for Paclitaxel

Percentage (%)	Paclitaxel (Drug)	Internal Standard	Ratio of Area (Drug/IS)	Mean ± SD	%RSD	%Recovery
80	1890955	177954	10.62609	10.58 ± 0.042	0.405202	100.67
	1890955	178678	10.58303
	1890955	179402	10.54032
100	2082376	178654	11.65592	11.61 ± 0.038	0.32805	99.49
	2082376	179242	11.61768
	2082376	179830	11.57969
120	2292792	179681	12.76035	12.76021 ± 0.001	0.000914	99.37
	2292794	179684	12.76015
	2292794	179684	12.76015

 

Specificity and selectivity:

Specificity and selectivity were considered for the assessment of the presence of interfering components in the working solution of Paclitaxel. The results show that the retention time of Paclitaxel is at 3.928 minutes, respectively. There is no variation in the retention time of the compound as compared to standard drug. They are free from interference from formulation excipients and solvent from each other. This indicates that the method is selected and specific for determination Paclitaxel.

 

Limit of detection and quantification:

The LOD and LOQ of Paclitaxel were estimated as 9.498 and 31.66ng/ml, respectively. The values indicated that the method was extremely sensitive to quantify of the drug.

 

Application of the developed method:

The developed RP-HPLC method is sensitive and specific for the quantitative assurance of Paclitaxel. The technique was approved for various parameters and, consequently has been applied for the estimation of the drug in pharmaceutical dosage forms such as injection. Every sample was analyzed in triplicate after extracting the drug as mentioned in the sample preparation of the investigational section. The recovered amount of Paclitaxel was 99.9% (Tab. 6).

 

Table 6: Assay of Mitotax (Paclitaxel) Injection

Conc. (µg/mL)	Paclitaxel	Internal Standard	Ratio of area (Drug/IS)	Obtained amount	Mean ± SD	% RSD	Labeled amount	% Recovery
10	1040117	177609	5.856218	10.00	9.99 ±0.004	0.0451	100 mg	99.9
	1040336	177790	5.851488	9.991
	1040555	177731	5.854662	9.996

 

None of the other ingredients interfered with the analyte peak. The technique was approved for linearity, precision, accuracy, sensitivity, system suitability, as well as robustness. The developed method is convenient and effective for the quality control as well as simultaneous routine analysis of Mitotax®100 in pharmaceutical dosage forms. The measured signal was exposed to be linear, accurate, and precise over the concentration range tested with a retention time of 3.928 min and made the method economical due to lower solvent consumption. The % RSD for all parameters was observed to be under 2, which shows the validity of technique and assay results obtained by this method are in reasonable agreement. Chromatogram of Paclitaxel is given in Fig. 6.

 

(A) Before Optimization Condition

 

(B) After Optimization Condition

 

(C) Chromatogram of formulation (Mitotax)

 

Figure 6: Chromatograms corresponding to bulk and formulation of Paclitaxel and Nilotinib at 10µg/mL (A) Before optimization (B) After optimization and(C) Formulation (Mitotax).

 

CONCLUSION:

An efficient isocratic reversed-phase high-performance liquid chromatography method was developed, which was optimized and validated for the simultaneous evaluation of Paclitaxel in bulk and pharmaceutical formulations utilizing Chemometrics Multi-Criteria Decision Making-Approach. This method reduces overall assay development time and gives essential information such as affectability of different chromatographic variables and their interaction effects on the qualities of separation. Time of analysis, resolution, and quality of the peaks were at the same time optimized by applying helpful tools of Chemometrics: Central Composite Design and Derringer’s desirability function. The validation study supported the determination of the assay conditions by confirm that the assay was specific, precise, linear, accurate, and robust.

 

ACKNOWLEDGEMENT:

Authors extend thanks to UGC for the financial support through UGC BSR Fellowship. I am thankful to Annamalai University, Mr. A. Arenganathan, Asst. Technical Officer, Department of Pharmacy, Annamalai University, Annamalainagar, Chidambaram, and Tamilnadu-608002 for providing the necessary laboratory facilities and technical support to carry out this Research study.

 

CONFLICT OF INTEREST:

The authors declare that they have no conflict of interest. The article does not contain any studies with animals or human participants performed by any of the authors.

 

ROLE OF THE FUNDING SOURCE:

Kiran Kumar Buralla carried out this study with a financial support in the form of studentship from UGC-BSR (F.25-1/2014-15(BSR)/7-269/2009(BSR), dated 07.10.2015).

 

REFERENCES:

1.      Peltier S, Oger JM, Lagarace F, Couet W, and Benoit JP. Enhanced oral paclitaxel bioavailability after administration of paclitaxel-loaded lipid nanocapsules. Pharmaceutical Research. 2006; 23(6): 1243-50.

2.      ICH Stability testing: photostability testing new drug substances and products international conference on Harmonization, IFPMA, Geneva. (1996).

3.      Chang AE, Ganz PA, Hayes DF, Kinsella T, Pass HI, Schiller JH, and Stone RM. Victor oncology: An Evidence-Based Approach. Springer Science and Business Media.2007; 34.

4.      Kim SC, Yu J, Lee JW, Park ES, Chi SC Sensitive HPLC method for quantitation of paclitaxel (Genexol®) in biological samples with application to preclinical pharmacokinetics and biodistribution. J Pharm Biomed Anal. 2005; 39: 170- 176.

5.      Ciutaru D, Badea I, Lazar L, Nicolescu D, and Tudose A. A HPLC validated assay of paclitaxel’s related impurities in pharmaceutical forms containing Cremophor EL. J Pharm Biomed Anal. 2004; 34: 493-499.

6.      Zhang SQ, Song YN, He XH, Zhong BH, and Zhang ZQ. Liquid chromatography-tandem mass spectrometry for the determination of paclitaxel in rat plasma after intravenous administration of poly (L-glutamic acid)-alanine-paclitaxel conjugate. J Pharm Biomed Anal. 2010; 51: 1169-1174.

7.      Rajender G, and Narayan NGB. Liquid Chromatography–Tandem Mass Spectrometry Method for Determination of Paclitaxel in Human Plasma. Pharmaceutica Analytica Acta. 2010; 1:101.

8.      Guideline IHT. Validation of analytical procedures: text and methodology. Q2 (R1) 2005:1.

9.      Montgomery D. Design and analysis of experiment” New York, John Wiley and Sons (1991).

10.   Shiow-Ling L, and Wen-Chang C. Optimization of medium composition for the production of glycosyltransferase by Aspergillus niger with response surface methodology. Enz. Microb. Technol.1997; 21:436.

11.   Myers RH, and Montgomery DC. Response Surface Methodology: Process and Product Optimization Using Designed Experiments, 2nd ed. Wiley, New York (2002).

12.   Ferreira SL, Bruns RE, Ferreira HS, Matos GD, David JM, Brandao GC, da-Silva EG, Portugal LA, dos-Reis PD, Souza AS, and dos Santos WN. Box-Behnken design: an alternative for the optimization of analytical methods. Anal. Chim. Acta. 2007; 597:179.

13.   International Conference on Harmonization. ICH Q2 (R1)., (2005). Validation of analytical procedures: text and methodology, ICH Secretariat, Geneva.

14.   Bhatt DA, and Rane SI. QbD approach to analytical RP- HPLC method development and its validation. Int. J. Pharm. Pharm. Sci. 2011; 3: 1179–1187.

15.   Bhutani H, Kurmi M, Singh S, Beg S, and Singh B. Quality by design (QbD) in analytical sciences: an overview, Pharm. Times. 2004; 46: 71–75.

16.   Schmidt AH, Stanic M, and Molnar I. In silico robustness testing of a compendial HPLC purity method by using a multidimensional design space build by chromatography modeling- case study pramipexole. J. Pharm. Biomed. Anal. 2014; 91: 97–107.

17.   Chaudhari SR, and Shirkhedar AA. Design of experiment avenue for development and validation of RP-HPLC-PDA method for determination of apremilast in bulk and in-house tablet formulation, Journal of Analytical Science and Technology. 2019; 10:10.

18.   ICH, ICH Draft Guidelines on Validation of Analytical Procedures: Definition and Terminology, Switzerland, Federal Register, IFPMA (1995).

19.   Ajaz A, Mohammad R, Khalid M.A, Kazi M, and Faiyaz S. Box-Behnken supported development and validation of robust RP-HPLC method: An application in estimation of pravastatin in bulk and pharmaceutical dosage form. 2016; 61(2): 2963-2967.

20.   Padmaja N, and Veerabhadram G. Development and validation of analytical method for Simultaneous estimation of Empagliflozin and Linagliptin in bulk drugs and combined dosage forms using UV-visible spectroscopy. Der Pharmacia Lettre. 2015; 7: 306-312.

21.   Beg S, Kohli K, Swain S, Hasnain M S. Development and validation of RP-HPLC method for quantitation of amoxicillin trihydrate in bulk and pharmaceutical formulations using Box-Behnken experimental design. Journal of Liquid Chromatography and Related Technologies. 2011; 35:393–406.

22.   Barmpalexis P, Kanaze FI, and Georgarakis E. Developing an optimizing a validated isocratic reversed phase HPLC separation of nimodipine and impurities in tablet using experimental design methodology. Journal of Pharmaceutical and Biomedical Analysis. 2009; 49:1192-1202.

23.   Suresh R, Manavalan R, Valliappan K. Chemometrics Assisted RP- HPLC Method for the Simultaneous Determination of Levocetirizine, Ambroxol, and Montelukast in Pharmaceutical Formulation International Journal of Pharmaceutical and Chemical Sciences. 2012; 1:1205-1220.

24.   Sujan B, Masud Kaisar Md, Salim Hossain Md. Development and Validation of a Simple and Rapid UV Spectrophotometer Method for Assay of Linagliptin in Bulk and Marketed Dosage Form. Indian Journal of Novel Drug Delivery. 2013; 5:221-224.

25.   Sara SM, Eman IE, Dalia AH, Magda AB. Stability- Indicating HPLC-DAD Method for the Determination of Linagliptin in Tablet Dosage Form: Application to Degradation Kinetics. Journal of Chromatographic Science. 2016; 54:1560–1566.

 

Received on 25.10.2019           Modified on 31.12.2019

Accepted on 05.03.2020         © RJPT All right reserved