Analytical Method Development and Validation of Dasatinib in Bulk and Pharmaceutical Formulation using Quality by Design

 

Jayendrasingh P. Bayas*, M. Sumithra

Department of Pharmaceutical Chemistry and Analysis, School of Pharmaceutical Sciences, VISTAS,

Vels University, Chennai 600 117, India.

 

ABSTRACT:

The accurate, fast, cost effective and robust RP- HPLC chromatographic method was developed and validated by using Quality by Design approach as per the ICH guidelines, for Linearity, Accuracy, Interday-Intraday Precision, Specificity and Selectivity, Robustness, Solution stability. The Design of Experiment was carried out by using 3 level factorial designs using design expert software. Change in pH and Mobile Phase concentration is considered for design of experiment. Based on the results obtained from screening of various mobile phase Acetonitrile as to Water having proportion 50:50 at 4 pH and Maximum Wavelength 315nm were selected for the analysis of Dasatinib by employing QbD methodology. The HPLC method is more sensitive, accurate and precise compared to the previously reported method. There was no interference of excipients in the recovery study. The low value of %RSD, molar extinction coefficient (L mol-1 cm-1) suggested that the developed method is sensitive. The proposed high-performance liquid chromatographic method proved to be convenient simple, cost effective and effective for the quality control of Dasatinib.

 

 

 

INTRODUCTION:

In Pharmaceutical industry the safety and efficacy of product is dependent on quality of product. To increase the quality of product the scientific tools such as Quality by Design and Product Analytical Technology can be used. These tools are useful for minimizing the risk as well they are cost effective. Analytical Quality by Design (AQbD). As per ICH, QbD is defined as “A systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management.”^1-4

 

AqbD works by collecting synthetic route information, literature search, Identification and assessment risk, optimization of the method and Designing of Experiment (DOE), Identification of critical quality attributes and validation of developed analytical method.⁵

 

Dasatinib is an oral dual BCR/ABL and Src family tyrosine kinase inhibitor approved for use in patients with chronic myelogenous leukaemia (CML). The main targets of Dasatinib, are BCRABL, SRC, Ephrins and GFR. Dasatinib is used for the treatment of adults with chronic, accelerated, or myeloid or lymphoid blast phase chronic myeloid leukemia with resistance or intolerance to prior therapy. Also indicated for the treatment of adults with Philadelphia chromosome-positive acute lymphoblastic leukemia with resistance or intolerance to prior therapy.⁶

 

Numbers of literature reports are available for estimation of dasatinib using liquid chromatographic methods, Stability Indicating HPTLC and LC Determination of Dasatinib in Pharmaceutical Dosage Form, High-performance liquid chromatographic–mass spectrometric Method, High-performance liquid chromatographic method, Validation of RP-HPLC method but various challenges are high degree of variability and cost of the methods used are still present. As method validation as per ICH Guidelines does not offer reliability in method variability, thus AQbD approach is used as the cost-effective tool for analytical method development of the Dasatinib.^7-11

 

Fig. 1 Chemical structure of Dasatinib

 

MATERIAL AND METHODS:^12-21

Chemicals and reagents:  

Dasatinib was obtained as Gift Sample from Sun Pharmaceutical Industry Ltd, Baroda, Acetonitrile and Methanol was obtained from Merck Life Sciences Pvt. Ltd, Mumbai. All other reagents were of analytical grade.

 

Instrumentation:

The proposed work was carried out on using Borwin software, JASCO HPLC (Model Series 2000) using PU 200 pump, Rheodyne Injector is used as sample injector port, Shimadzu UV-visible spectrophotometer (model UV-1800 series), A Fast ultrasonicate cleaner was used for degassing the mobile phase. Chemline pH Meter 101 is used for pH determination.

 

Selection of Solvents:

Solubility of Dasatinib was determined in various solvents like water, methanol, ethanol and Acetonitrile.

 

Dasatinib Stock Solution:

Stock solution was prepared by dissolving 10 mg Dasatinib in Acetonitrile and then diluted with Acetonitrile in 10 ml of volumetric flask to get concentration of 1000 µg/ml.

 

Dasatinib Working Standard Solution:

From the resulting solution 0.1 ml was diluted to 10 ml with Acetonitrile to obtain concentration of 10 µg/ml of Dasatinib.

 

Determination of λ Max

From the standard stock solution further dilutions were done using Acetonitrile and scanned over the range of 200-400 nm and the spectra were overlain. It was observed that drug showed considerable absorbance at 315 nm.

 

Design of Experiment:

·       Column C18:

Design Expert 8 Software has different facility to develop experiment such as Miscellaneous Method, Selected Factorial design was Central Composition Method due to it has flexibility to change/add/delete any parameter at any time when our experiment is going on.it provide facility to give standard run at one time at only one mobile phase.

 

Trials Run Given By Design Expert 8 Software:

Standard concentration of Dasatinib was taken 20µg/ml. Miscellaneous Factorial design gave 9 run at different pH, Solvent proportion Three Solvent Combination with 9 runs for each Solvent Combination. Software gives its 27 runs.

 

Table: 1 Trials given by software

 

OPTIMIZATION:

1.     Screening Design:

 

 

2.     Optimization Result:

Dasatinib trials in solvent ratio of 50:50 at pH 4 for

A)   Methanol: Water Less theoretical plates was observed and the results were non-satisfactory.

B)   Acetonitrile: Water More theoretical plates was observed and the results were satisfactory

 

3.     Optimized Result:

Optimized trials suggested by software based on desirability value:

This methodology is initially based on constructing a desirability function for each individual response. The scale of individual desirability function ranges between i= 0, for completely undesirable response and i =1, for fully desired response. Selection of trial was based on maximum desirability value. Therefore, first trial which was having desirability one (i=1) selected for method optimization. Optimized trials suggested by software based on desirability value for Acetonitrile: Water ratio of 50:50 at pH 4 shows Asymmetry 0.6, Retention time 4.086, Theoretical plates 8500 and Percent Desirability 0.992.

 

Optimized chromatographic conditions:

Mobile phase: Water: ACN (50:50 v/v), pH of buffer: 4, Analytical column: C₁₈ column Waters X Bridge (4.6× 250mm id. particle size 5µm), UV detection: 315nm, Injection volume: 20µL, Flow rate: 1.00mL min ^-1, Temperature: Ambient, Run time: 4.085 min.

 

4. Effect of independent variables:

4.1 Effect of independent variables on retention time (Y₁):

The equation for response surface quadratic model is as follows

Y₁ =  +0.019 +4.27 *A + 0.031* B + 0.056 * A * B + 8.34* A²  - 0.028* B²

Where, X₁= A, X₂ = B

A graphical representation of amount of Water (A) and pH (B). An increase Amount of Water in resulted in increase in retention time (Y₁), while increase or decrease in pH resulted in no effect in retention time (Y₁). Combination of amount of water and pH showed decrease in response.

 

Three-dimensional plot for retention time as a function of pH and amount of Water.

 

Fit summary:

Quadratic model was suggested by the software.

ANOVA: ANOVA of developed Full three level factorial model for retention time (Y₁).

Values of "Prob > F" (p- value) less than 0.0500 indicate model terms are significant. In this case A, B, AB,are significant model terms.

 

Table: 2 Optimized trials suggested by software based on desirability value

 

4.2 Effect of independent variables on Asymmetry (Y₂):

The model for response Y₂ (Asymmetry) is as follows:

Y₂ =        +0.033 +0.47 *A + 0.15* B - 0.23 * A * B + 1.60 * A²  - 0.050* B²

Where, X₁= A, X₂ = B

a graphical representation of amount of Water (A) and pH (B), An increase Amount of Water in resulted in increase in Asymmetry(Y₂), while decrease in pH resulted in decrease in Asymmetry(Y₂).

 

Three-dimensional plot for Asymmetry as a function of pH and amount of water.

Fit summary:

Response Surface Linear Model was suggested by the software.

ANOVA: ANOVA of developed CCD model for Asymmetry (Y₂).

Values of "Prob > F" (p- value) less than 0.0500 indicate model terms are significant.

In this case A, B are significant model terms.  

 

Table : 3 Significance of p value on model terms of Asymmetry

 

For response Y₂, factor X₁ was having synergistic effect with p value 0.0070. Therefore, we can conclude that increment in amount of Water was responsible for increase in Asymmetry. Factor X₂ was having antagonistic effect with p value 0.0602. Therefore, we can conclude that decrease in pH was responsible for increase in Asymmetry.

 

4.3 Effect of independent variables on Theoretical Plates (Y₃):

The model for response Y₃ (theoretical plates) is as follows:

Y_{3 =} -2920.33 -4368.50 *A -2954.83* B + 4811.25 * A * B + 15034.50* A²  +4380.50* B²

Where, X1= A, X2 = B

Following figure shows a graphical representation of amount of Water (A) and pH (B). An increase amount of Water and pH showed antagonistic effect on response (Y₃) individually.

 

Three-dimensional plot for Theoretical Plates as a function of pH and amount of water.

Fit summary: Quadratic model was suggested by the software

ANOVA: ANOVA of developed CCD model for Theoretical Plates (Y₃).

Values of "Prob > F" (p- value) less than 0.0500 indicate model terms are significant.  In this case A, B are significant model terms. 

Table: 4 Significance of p value on model terms of theoretical plates

 

For response Y₃, factor pH of Water was having antagonistic effect with p value 0.0475. Therefore, we can conclude that increment in pH of buffer was responsible for decrease in theoretical plates. Amount of Water was responsible for significant decrease in theoretical plates with significant p value of 0.021.

 

4.4 Effect of independent variables on Area (Y₄):

The model for response Y₄ (Area) is as follows:

Y₄= -1.093E+005 -2.140E+005*A – 56253.00*B + 84028.00 *A*B + 5.689E+005*A²  + 1.639E+005*B²

Where, X1= A, X2 = B

Figure shows a graphical representation of amount of Water (A) and pH (B). A decrease amount of Water and pH showed increase in response (Y₄) individually.

 

 

 

Three-dimensional plot for Area as a function of pH and amount of water.

Fit summary: Quadratic model was suggested by the software

ANOVA: ANOVA of developed CCD model for Area (Y₄).

Values of "Prob > F" (p- value) less than 0.0500 indicate model terms are significant.  In this case A, B are significant model terms. 

 

Table: 5 Significance of p value on model terms of Area

For response Y₄, factor amount of Water was having antagonistic effect with p value 0.0255. Therefore, we can conclude that increment in pH of water was responsible for decrease in Area. pH of Water was responsible for significant increase in Area with significant p value of 0.0428.

 

VALIDATION OF RP-HPLC METHOD:

The proposed RP-HPLC method was validated in terms of system suitability, specificity, precision, accuracy and robustness as per the International Conference on Harmonization (ICH) guidelines.

 

1.     Linearity:

The linearity was observed in the range of 10-60 ug/ml and regression coefficient found to be 0.998. The stock solutions of standard Dasatinib were diluted to six different known concentrations. Linearity graph of concentration (as x-value) versus area (as y-value) were plotted and correlation coefficient, y-intercept and slope of the regression were calculated.  The linear calibration plot showed good linearity with higher value of the coefficient of correlation (R²) of 0.998. This revealed that all the responses were within the specified acceptance limit indicating high degree of closeness of the predicted data with the observed ones.

 

 

Fig. 2 Calibration Curve of Dasatinib

 

 

Fig. 3 Overlay of Dasatinib

 

2.     System Suitability:

System-suitability tests are an integral part of method development and are used to ensure adequate performance of the chromatographic system. Retention time (Rt), number of theoretical plates (N) and tailing factor (T) were evaluated for six replicate injections of the drug at a concentration of 20 µg/ml. The results shows retention time of 4.085, Tailing Factor 1.205 and number of theoretical plates 8500.

 

 

Fig.: 4 A typical chromatogram of Dasatinib [Concentration 20ug/ml]

 

3.     Specificity:

Chromatogram of blank was taken as shown in Fig. 4 Chromatogram of Dasatinib showed peak at a retention time of 4.085 min. The mobile phase designed for the method resolved the drug very efficiently. The Retention time of Dasatinib was 4.085 ± 0.68 min. The wavelength 315 nm was selected for detection because; it resulted in better detection sensitivity for the drug. Percent RSD was found less than 1.5.

 

Table: 6 Specificity of Dasatinib by HPLC method

 

4.     Sensitivity:

The sensitivity of measurement of Dasatinib by use of the proposed method was estimated in terms of the limit of detection (LOD) and the limit of quantification (LOQ). The LOD and LOQ were calculated by the use of signal to noise ratio. In order to estimate the LOD and LOQ values, the blank sample was injected six times and the peak area of this blank was calculated as noise level. The LOD was calculated as three times the noise level, while ten times the noise value gave the LOQ. LOD and LOQ were found to be 0.00847 and 0.02566 respectively.

 

5.     Precision:

Demonstration of precision was done under two categories. The injection repeatability (System Precision) was assessed by using six injections of the standard solution of Dasatinib and the % RSD of the replicate injections was calculated. In addition, to demonstrate the precision of method (Method Precision), six samples from the same batch of formulation were analyzed individually and the assay content of each sample was estimated. The average for the six determinations was calculated along with the % RSD for the replicate determinations. Both the system precision and method precision were subjected for inter-day and intra-day variations as reported in following tables.

 

6.     Accuracy:

Recovery studies by the standard addition method were performed with a view to justify the accuracy of the proposed method. Previously analyzed samples of Dasatinib (20 µg/ml) were spiked with 80, 100, and 120 % extra Dasatinib standard and the mixtures were analyzed by the proposed method. Standard deviation of the % recovery were calculated and reported in following table.

 

7.     Robustness:

Robustness is a measure of capacity of a method to remain unaffected by small, but deliberate variations in the method conditions, and is indications of the reliability of the method. A method is robust, if it is unaffected by small changes in operating conditions. To determine the robustness of this method, the experimental conditions were deliberately altered at three different levels and retention time and chromatographic response were evaluated. One factor at a time was changed to study the effect. Variation of mobile phase composition (Acetonitrile: Water and Acetonitrile: buffer) and mobile phase flow rate by 0.9 ml/min (0.8 and 1 ml/min) had no significant effect on the retention time and chromatographic response of the 20 µg/ml solution, indicating that the method was robust.

 

Table: 7 Intraday and Inter-day Precision of Dasatinib at 315 nm

Table: 8 Accuracy of Dasatinib at 315 nm.

 

CONCLUSION:  

A very few analytical methods appeared in the literature for the determination of Dasatinib includes HPLC, HPTLC and UV- Visible spectrophotometric methods. In view of the above fact, some simple analytical methods were planned to develop with sensitivity, accuracy, precision and economical. In the present investigation HPLC method (Using Quality by Design) for the quantitative estimation of Dasatinib in bulk drug and per ICH guidelines pharmaceutical formulations has been developed. HPLC methods were validated as and results of linearity, precision, accuracy, Specificity, System suitability and robustness pass the limit. The HPLC method is more sensitive, accurate and precise compared to the previously reported method. There was no any interference of excipients in the recovery study. The low value of %RSD, molar extinction coefficient (L mol-1 cm-1) suggested that the developed methods are sensitive. The proposed high-performance liquid chromatographic method has also been evaluated over the accuracy, precision and robustness and proved to be convenient and effective for the quality control of  Dasatinib. Developed method was found simple and cost effective for the quality control of Dasatinib.

 

Validation of the AQbD method had given excellent linearity, accuracy, precision, system suitability and robustness values. Moreover, the lower solvent consumption leads to a cost effective and environmentally friendly Spectroscopic procedure. Thus, the proposed methodology is rapid, selective, requires a simple sample preparation procedure, and represents a good procedure for Dasatinib. 

 

ACKNOWLEDGEMENT:  

The authors are grateful to the authorities of JSPM’s Charak College of Pharmacy ana Research, Wagholi, Pune-412 207 Maharashtra.

 

CONFLICT OF INTEREST:

The authors declare no conflict of interest.

 

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Accepted on 20.06.2020           © RJPT All right reserved

Research J. Pharm. and Tech 2021; 14(3):1591-1596.