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Abstract

Aim: Develop and implement a highly effective, reliable, precise, and validated analytical method for analyzing Metopimazine in both bulk and pharmaceutical dosage forms, utilizing a quality-by-design (QbD) approach. Background: Metopimazine, an antiemetic drug, has limited research in analysis. Comprehensive analytical technique design and validation are necessary for efficient, rapid, and accurate qualification in pharmaceutical dosage form. Objectives: A novel and efficient reversed-phase high-performance liquid chromatography (RP-HPLC) method was developed and validated for analyzing Metopimazine in its bulk form and pharmaceutical preparations, employing a quality-by-design (QbD) strategy. Materials and methods: Box Behnken Design experimental trial,analyzed using Design Expert® software, determined that retention duration, peak symmetry, and NTP (number of theoretical plates) were the determining variables for Critical Analytical Attributes (CAAs). The actual experimental data corresponded with the predicted data. Results: The optimized chromatographic conditions involved a mobile phase of Methanol: Water 45:55 v/v with pH maintained at 3.5 and a flow rate 1 mL/min. Furthermore, the oven temperature was set at 25?C, with a 266 nanometer. The stationary phase was HiQsil C18 (250 x 4.6 mm i.d., 5 µ) column and the detection was carried out using a PDA detector with a run time of 6 minutes. In order to validate the method, parameters such as linearity, specificity, precision and accuracy were evaluated. Conclusion: A high-performance liquid chromatography (HPLC) method was successfully developed and validated to determine the concentration of a drug in bulk and tablet forms, adhering to the acceptable standards outlined in the ICH guidelines.

Keywords

Quality by Design, Metopimazine, HPLC, Critical Method Parameters, Critical Analytical attributes.

Introduction

Metopimazine is an Antiemetic agent chemically known as 1-(3-[2-(Methylsulfonyl) phenothiazin-10-yl]propyl)-4-piperidine carboxamide. It refers to the phenothiazine drug class, which also includes tricyclic compounds containing nitrogen and sulphur.1 Pale yellowish white crystalline powder, insoluble in water, soluble in DMSO (Dimethyl sulfoxide) and methanol, melts at 170.5°C.2,3,4. A method for estimating Metopimazine, which involves chromatographic separation by using a fluorescence detector, and HPTLC analysis.5,6 Quality by Design (QbD) is a rigorous manufacturing process in pharmaceutical industry, with ICH Q11 [2] for drug substance development and ICH Q8 [1] for pharmaceutical development.7,8. According to QbD's definition, it is "a systematic approach to development that begins with predefined objectives and emphasizes understanding and control, based on sound science and quality risk management."  This method provides a reliable, well-planned, method that serves its intended function and works as expected throughout its lifecycle.9,10,11,12. The literature review reveals insufficient research on Metopimazine analysis, indicating the need for improved techniques.  There is no RP-HPLC method for determining Metopimazine in bulk and pharmaceutical dosage form using quality-by-design approach. The present study was done to develop a simple, reliable, precise, and validated method for the analytical determination of Metopimazine in bulk and pharmaceutical dosage form using the analytical quality by design approach.13,14.

       
            Metopimazine Structure 2-4.png
       

Figure.1 Metopimazine Structure 2-4

MATERIALS AND METHODS:

Chemicals and Reagents:

Metopimazine was provided as a gift sample by Micro Lab Thane. The 7.5 mg Vogalib tablet used in the commercial dose formulation was purchased from Cephalon Pharmaceutical Co. in Mumbai. All the chemicals and reagents used for analysis like acetonitrile, methanol was HPLC grade and procured from Merck Chemicals in India.

Instrumentation:

The determination of Metopimazine was conducted using an HPLC (JASCO LC System-1200 series) equipped with an autosampler, column oven, and wavelength detector. This system features a photodiode array detector, a quaternary pump, and a Rheodyne injector with a 20 µL loop. Separation was achieved using a HiQsil C18 column (250 x 4.6 mm i.d., 5 µm). Before quantification, the column was consistently saturated with the solvent system to ensure effective separation, with this process repeated each time prior to analysis.

Procedure for Standard Stock Solution: A standard stock solution was prepared by accurately weighing 100 mg of Metopimazine into a 100 mL volumetric flask and diluting it with methanol to achieve a concentration of 1000 µg/mL. An aliquot of 1 mL from this standard stock solution was further diluted with methanol in a 10 mL volumetric flask to obtain a sub-stock solution with a concentration of 100 µg/mL.

Preparation of Solution and Selection of Wavelength: One milliliter (1 mL) of the sub-stock solution (100 µg/mL) was taken and diluted to 10 mL with methanol, resulting in a 10 µg/mL solution. This solution was scanned across the 400 to 200 nanometer range, identifying the maximum absorbance at 266 nanometers.

Procedure for Sample Stock Solution: For the sample stock solution, twenty tablets were accurately weighed and ground into a fine powder. An amount equivalent to 10 mg of Metopimazine was calculated, transferred to a 100 mL volumetric flask, and diluted with methanol. The mixture was sonicated for 15 minutes. From this solution, 1 mL was taken and diluted to 10 mL with methanol to achieve a concentration of 100 µg/mL.

Optimization of Mobile Phase:

To identify the optimal mobile phase, several solvents with various compositions were examined.


Table.no.1List of Mobile Phase Compositions examined

 

Mobile phase

Ratio

Remark

1.

ACN: Water

50:50

Poor resolution, Shoulder peak

2.

Methanol: Water

50:50

Peak absent

3.

Methanol: Water

55:45

Peak broadening

4.

Methanol: Water

60:40

Peak Splitting

5.

Methanol: Water

70:30

Poor resolution

6.

Methanol: Water

75:25

Peak broadening

7.

Methanol: Water (pH:3.5)

70:30

Peak Splitting

8.

Methanol: Water (pH:3.5)

50:50

Peak tailing

9.

Methanol: Water (pH:3.5)

45:55

Peak was symmetric


Chromatographic Conditions

Before usage, the mobile phase of a 45:55 Methanol:Water mixture with pH maintained at 3.5 was filtered, degassed, and sonicated. The stationary phase was a HiQsil C18 (250 x 4.6 mm i.d., 5). A thermostatically controlled column oven maintained the column's temperature at 25°C. The flow rate was kept constant at 1 mL/min. The flow rate was maintained at 1 mL/min. The injection volume was 10 µL, and detection was carried out using a PDA detector set to 266 nanometers.

Experimental Design:

The experimental design was developed using Design-Expert software version 10 to examine various variables and verify the method's performance. The composition of mobile phase A, the composition of mobile phase B, and the flow rate were identified as the Critical Method Parameters (CMPs) for the execution of the experiment. Table.no.2 presents the qualified values of the variables analyzed. Retention duration, peak symmetry, and the number of theoretical plates were employed in the experimental design as Critical Analytical Attributes (CAAs) that were controlled and expected to affect method outcomes. For the experimental plan, a 33-factorial design with three components at three levels was taken into consideration. The initial approach involved using the Box-Behnken design, but it was later determined that the process is non-linear. Table 3 presents the experimental observations and the Design of Experiment (DOE) plan.

Assessing the results of the experiment and determining the final conditions for the method:

The experimental design included 13 runs with various method conditions, which were assessed for retention time, peak symmetry, and the number of theoretical plates. A response surface Box-Behnken statistical screening strategy was employed to optimize and evaluate the main effects, interaction effects, and quadratic effects. Design Expert® (Version 10.0, Stat-Ease Inc.) was used to explore quadratic response surfaces using a 3-factor, 3-level design.


Table.no.2 Independent variables: factors and levels

Factors

Level 1

Level 2

Level 3

Composition of mobile phase A

40

45

50

Composition of mobile phase B

50

55

60

Flow rate

0.95

1.00

1.05


Table.no.3 Box Behnken Design Plan and Responses

 

 

Std

 

 

Run

Factor 1

Factor 2

Factor 3

Response 1

Response 2

Response

3

A: Composition of mobile phase A

B: Composition

of mobile phase

B

C: Flow rate

NTP

Retention time

Symmetric factor

5

1

40

55

0.95

2416

7.135

1.712

1

2

40

50

1

2972

6.813

1.722

4

3

50

60

1

1908

6.824

1.724

13

4

45

55

1

3065

6.547

1.5

3

5

40

60

1

2604

6.916

1.839

6

6

50

55

0.95

2616

7.135

1.712

12

7

45

60

1.05

1014

5.613

1.204

9

8

45

50

0.95

2924

7.218

1.818

2

9

50

50

1

2417

6.932

1.618

10

10

45

60

0.95

1097

7.323

1.832

11

11

45

50

1.05

2165

5.71

1.11

8

12

50

55

1.05

2221

5.521

1.211

7

13

40

55

1.05

1093

5.418

1.096


Method Validation:

Through laboratory testing, method validation is a technique for analysis that establishes if the procedure's performance characteristics meeting the requirements for the intended analytical implementation. The method's specificity, selectivity, linearity and range, accuracy, precision, robustness, limit of detection, and limit of quantitation were all assessed in accordance with the ICH Q2(R1) guidelines.

System suitability:

System suitability testing was done to determine the instrument's acceptance requirements. The percentage relative standard deviation (% RSD) of various components, such as retention time, asymmetry, and theoretical plates, were calculated. There should be no more than 2.0% RSD throughout five replicates.

Linearity:

The slope, intercept, and correlation coefficient data were used to evaluate the linearity of Metopimazine within the concentration range of 2-12 µg/mL.

Precision:

The precision for the preferred method was calculated. Results of precision analysis reveal that the proposed approach is precise and that its %RSD was below the limit (below 2%), with a standard deviation of less than 2. 

Accuracy:

To verify the accuracy of the method, an analysis of recovery from a commercial formulation was conducted at three standard addition levels. The recovery percentage of Metopimazine was determined, with a standard deviation of less than 2, indicating the method's accuracy. The percentage of recovery was found to be 99.98%. The relative standard deviation (RSD) was calculated to ensure that the data met the permissible limits.

Specificity:

The interference of any potential degradation products has been studied to assess the specificity. The solutions for the test sample and the standard were both scanned separately in the 200–400 nanometer range.

Robustness:

By varying the mobile phase's composition and wavelength, the three dilutions were examined under various conditions. Calculations were used to determine the assay's % RSD.

Assay:

Twenty tablets were accurately weighed and ground into a fine powder for the Metopimazine assay. A quantity of 50 mg of the powder was estimated and transferred to a 50 mL volumetric flask, diluted with methanol, and sonicated for 15 minutes. Next, 1 mL of the resulting stock solution was transferred to a 10 mL volumetric flask and diluted with methanol to prepare a solution with a concentration of 100 µg/mL. A 1 mL aliquot of this solution was then transferred to a 10 mL volumetric flask and diluted with methanol to obtain a solution with a concentration of 10 µg/mL. For HPLC analysis, 10 µL of the specified dilution was injected.

RESULTS AND DISCUSSION:

The proposed work developed and evaluated an RP-HPLC technique for estimating Metopimazine in bulk and pharmaceutical dosage form. Metopimazine consequently showed good solubility in the initial solvent that was selected for it. Additionally, the chromatographic conditions were examined, and the parameters were defined. Metopimazine demonstrated a high peak in the mobile phase Methanol: water (45:55) with pH maintained at 3.5 with a retention time of 6.53 minutes.

Implementation of Qbd:

The statistical analysis of the experimental observations was conducted using Design Expert® software (Version 10.0, Stat-Ease Inc.) with the Box-Behnken design. The inputs utilized by the software are presented in Tables 5 and 6.

Thirteen runs were selected to be done once the design was implemented and inputs were put into the software. A statistical assessment regarding the degrees of freedom (Table.no.7, Table.no.8, and Table.no.9) as well as a contour plot of retention time, standard error of design, and symmetric factor, as shown in Figures 4, 5, and 6, were generated after the 13 runs were finished. The software was provided with the responses,considering retention time,peak symmetry,and NTPs ( number of theoretical plates).

       
            Chromatogram of Metopimazine using Methanol Water 45 55 at pH 3 5.png
       

Figure.2 Chromatogram of Metopimazine using Methanol: Water (45:55) at pH 3.5


Table.no.4 Optimization of Chromatographic Conditions

Parameters

Results

Column

HiQsil C18 (250 x 4.6 mm i.d.,5)

Flow rate

1.0 mL/minute

Detector

PDA

Detector wavelength

266 nm

Injection volume

10.00 µL

Retention time

6.53 minute

Mobile phase

Methanol: Water (45:55) with pH maintained at 3.5


Method Validation:

Linearity

For the concentration against area graph, the Metopimazine showed a correlation coefficient of 0.9998, a slope of 1795.7, and a y-intercept of 226.33. The drug indicated linearity between the concentration range of 2–12 µg/mL, as shown in Figure 6.

Precision

As observed in Table.no 12, the precision results reveal that the suggested method is accurate because the standard deviation is less than 2.

Accuracy

Table. no. 11 illustrates the accuracy results. The standard deviation was less than 2, indicating that the method is accurate, and the percentage recovery was 100.69.


Table.no.5 Box-Behnken design description for optimization

Study type

Response surface

Design type

Box-Behnken

Design model

Quadratic

Runs

13


Table.no.6 Description of the Box-Behnken design's optimisation strategy

Factor

Name

Units

Type

Subtype

Minimum

Maximum

A

Composition of mobile phase A

%

Numeric

 

Continuous

40

50

B

Composition of mobile phase B

%

Numeric

 

Continuous

50

60

C

Flow rate

mL/min

Numeric

Continuous

0.95

1.05


Table.no.7 Analysis of the degrees of freedom

Response

R1

R2

R3

Name

NTP

Retention time

Symmetric factor

Observation

13

13

13

Analysis

Polynomial

Polynomial

Polynomial

Minimum

1014

5.418

1.096

Maximum

3065

7.323

1.839

Ratio

3.02268

1.35161

1.67792

Model

Linear

Quadratic

Quadratic


Table.no.8 Result of optimized chromatographic method

 

 

Response

 

 

Parameter

Observed

Analysis

 

 

Inference

p-value

(<0.05)

r-value

(-1 to +1)

R1

NTP

0.1623

0.2252

Not significant

R2

Retention time

0.0003

0.9985

Significant

R3

Symmetric factor

0.0239

0.9126

Significant


       
            Retention time contour plot.png
       

Figure.4 Retention time contour plot

       
            Standard error of Design contour plot.png
       

Figure.5 Standard error of Design contour plot

       
            Contour plot of Symmetric factor.png
       

Figure.6 Contour plot of Symmetric factor


Table.no.9 Obtained solutions for optimized condition

Run

Std

A: Composition of mobile phase A

B: Composition of mobile phase B

C: Flow rate

NTP

Retention time

Symmetric factor

13

4

45

55

1

3065

6.547

1.5


Linearity:


Table.no.10 Data of linearity

Sr.no.

Concentration

Peak Area

1

2 µg/mL

1994

2

4 µg/mL

3856

3

6 µg/mL

5616

4

8 µg/mL

7362

5

10 µg/mL

9279

6

12 µg/mL

10961


       
            Linearity curve of Metopimazine.png
       

Figure.6 Linearity curve of Metopimazine

Accuracy:


Table.no.11 Data of accuracy

 

Sample

Standard

Total Conc.

 

Peak Area

Calculated Conc.

 

%Recovery

 

Mean

SD

%RSD

 

80%

4

3.2

7.2

6767

7.193051

99.782

 

100.29

 

1.314

 

1.310

4

3.2

7.2

6826

7.257112

101.78

4

3.2

7.2

6753

7.17785

99.307

 

100%

4

4

8

7544

8.036699

100.91

 

100.61

 

1.050

 

1.043

4

4

8

7490

7.978067

99.451

4

4

8

7565

8.059501

101.48

 

120%

4

4.8

8.8

8271

8.826059

100.54

 

101.19

 

0.644

 

0.637

4

4.8

8.8

8300

8.857546

101.19

4

4.8

8.8

8328

8.887948

101.83

Overall average

100.69

Overall SD

1.002

Overall % RSD

0.996


Precision:


Table.no.12 Data of precision

Sr.no.

Concentration

(µg/ml)

Area

System Precision

Method Precision

1.

10

8711

9971

2.

10

8781

9896

3.

10

8422

9754

4.

10

8689

9880

5.

10

8602

9978

6.

10

8807

9695

Mean

8668.667

9862.333

Standard Deviation

140.8896

115.2123

Relative Standard Deviation

0.016253

 

0.011682

 

% Relative Standard Deviation

1.625274

1.168205


Robustness:


Table.no.13 Data of robustness

 

 

 

1.

2.

3.

Mean

SD

%RSD

 

 

Flow rate

 

0.95

Area

10305

10310

10304

10306.33

3.21455

0.03119

Rt

7.600

7.613

7.608

7.607

0.006557

0.086203

Ntp

3512

3524

3543

3526.333

15.63117

0.44327

 

1.05

Area

11410

11408

11399

11405.67

5.859465

0.051373

Rt

4.942

4.95

4.962

4.951333

0.010066

0.203308

Ntp

2221

2245

2230

2232

12.12436

0.543206

 

 

Temperature

 

25

Area

8878

9480

8968

9108.667

324.7173

3.564927

Rt

6.436

6.500

6.492

6.476

0.034871

0.538468

Ntp

3089

3099

3082

3090

8.544004

0.276505

 

35

Area

11733

11789

11452

11658

180.5852

1.549024

Rt

6.142

6.110

6.209

6.153667

0.050521

0.820984

Ntp

3961

4013

3986

3986.667

26.00641

0.652335

 

 

Wavelength

 

264

Area

12886

12709

12621

12738.67

134.9679

1.059514

Rt

5.525

5.642

5.497

5.554667

0.076918

1.38474

Ntp

2784

2807

2821

2804

18.68154

0.666246

 

268

Area

12456

12553

12159

12389.33

205.286

1.656957

Rt

5.708

5.704

5.716

5.709333

0.00611

0.10702

Ntp

2827

2817

2878

2840.667

32.71595

1.1517


Assay:


Table.no.14 Outcomes using the HPLC method for determining the dosage of Metopimazine in tablet

Tablet formulation

Label claim(mg/tab)

Estimated label claim (mg/tab)

% purity

Metopimazine

7.5 mg

6.9 mg

99.97%


CONCLUSION:

The current AQbD research was carried out to examine the results of many variables and to assess method performances. This present study emphasises the application of the analytical QbD method in the development of a reliable RP-HPLC technique to analyse Metopimazine. The experimental results assisted in identifying high-risk CMPs (Column temperature, flow rate, and mobile phase ratio) and their effects on CAAs (retention time, symmetric factor, and a number of theoretical plates). The validated parameters all satisfied the requirements defined in the ICH guidelines. Metopimazine was estimated using an effective, precisely calculated, and reliable HPLC approach for both bulk and its tablet dosage form.

ACKNOWLEDGEMENT:

The author wishes to express their heartfelt gratitude to the principal, Dr. Ashish Jain Sir, the head of department, Dr. Bhushan Rane Sir, and assistant professor, Mr. Mukesh Patil Sir for their able guidance and support in completing my research work. We are grateful to the administration of Shri. D.D. Vispute College of Pharmacy and Research Centre, New Panvel, Navi Mumbai, Maharashtra, India, for providing us with the best facilities.

REFERENCES

  1. Karicherla V, Phani K, Bodireddy MR, Prashanth KB, Gajula MR, Pramod K. A Simple and Commercially Viable Process for Improved Yields of Metopimazine, a Dopamine D2-Receptor Antagonist. Org Process Res Dev. 2017 May 19;21(5):720–31.
  2. Metopimazine - Wikipedia [Internet]. [cited 2023 May 1]. Available from: https://en.wikipedia.org/wiki/Metopimazine
  3. ChemicalBook [Internet]. [cited 2023 Jun 5]. metopimazine | 14008-44-7. Available from: https://www.chemicalbook.com/ChemicalProductProperty_EN_CB0934482.htm
  4. PubChem. Metopimazine [Internet]. [cited 2023 Apr 30]. Available from: https://pubchem.ncbi.nlm.nih.gov/compound/26388
  5. Angelo HR, Herrstedt J, Jorgensen M. High-performance liquid chromatographic method with fluorescence detection for the simultaneous determination of metopimazine and its acid metabolite in serum. J Chromatogr B Biomed Sci App. 1989 Jan;496:472–7.
  6. Naguib IA, Abdelrahman MM. Stability indicating HPTLC method for determination of Metopimazine in pharmaceutical formulation and human plasma. Beni-Suef Univ J Basic Appl Sci. 2014 Mar;3(1):52–62.
  7. Tietje C, Brouder A, editors. International conference on harmonisation of technical requirements for registration of pharmaceuticals for human use. In: Handbook of Transnational Economic Governance Regimes [Internet]. Brill | Nijhoff; 2010 [cited 2023 Jun 14]. p. 1041–53. Available from: https://brill.com/view/book/edcoll/9789004181564/Bej.9789004163300.i-1081_085.xml
  8. ICH guideline Q11 on development and manufacture of drug substances (chemical entities and biotechnological/biological entities), Step 3.
  9. Reid GL, Morgado J, Barnett K, Harrington B, Wang J, Harwood J, et al. Analytical Quality by Design (AQbD) in Pharmaceutical Development | American Pharmaceutical Review - The Review of American Pharmaceutical Business & Technology [Internet]. [cited 2023 Jun 9]. Available from: https://www.americanpharmaceuticalreview.com/Featured-Articles/144191-Analytical-Quality-by-Design-AQbD-in-Pharmaceutical-Development/
  10. Borman P, Chatfield M, Nethercote P, Thompson D, Truman K. The application of quality by design to analytical methods. Pharm Technol. 2007 Dec 1; 31:142–52.
  11. Patil, A.; Pethe, A.; Quality by Design (QbD): A new concept for development of quality pharmaceuticals. International Journal of Pharmaceutical Quality Assurance.2013, 4(2); 13-19.
  12. Nagar P, Garg M, Chauhan C, Kumar R, Chaudhary AK. Analytical Quality by Design (AQBD) Approach for HPLC Method Development, Method Optimization and Validation. International Journal of Pharmaceutical Quality Assurance. 2022;13(2):103-110.
  13. Gupta V, Jain ADKJ, Gill NS, Guptan K. Development and validation of HPLC method-a review. International research journal of pharmaceutical and applied sciences 2012; 2(4): 17-25.
  14. Thamman M. A review on high-performance liquid chromatography (HPLC). Res Rev: J Pharm Anal. 2016; 5: 22-8.

Reference

  1. Karicherla V, Phani K, Bodireddy MR, Prashanth KB, Gajula MR, Pramod K. A Simple and Commercially Viable Process for Improved Yields of Metopimazine, a Dopamine D2-Receptor Antagonist. Org Process Res Dev. 2017 May 19;21(5):720–31.
  2. Metopimazine - Wikipedia [Internet]. [cited 2023 May 1]. Available from: https://en.wikipedia.org/wiki/Metopimazine
  3. ChemicalBook [Internet]. [cited 2023 Jun 5]. metopimazine | 14008-44-7. Available from: https://www.chemicalbook.com/ChemicalProductProperty_EN_CB0934482.htm
  4. PubChem. Metopimazine [Internet]. [cited 2023 Apr 30]. Available from: https://pubchem.ncbi.nlm.nih.gov/compound/26388
  5. Angelo HR, Herrstedt J, Jorgensen M. High-performance liquid chromatographic method with fluorescence detection for the simultaneous determination of metopimazine and its acid metabolite in serum. J Chromatogr B Biomed Sci App. 1989 Jan;496:472–7.
  6. Naguib IA, Abdelrahman MM. Stability indicating HPTLC method for determination of Metopimazine in pharmaceutical formulation and human plasma. Beni-Suef Univ J Basic Appl Sci. 2014 Mar;3(1):52–62.
  7. Tietje C, Brouder A, editors. International conference on harmonisation of technical requirements for registration of pharmaceuticals for human use. In: Handbook of Transnational Economic Governance Regimes [Internet]. Brill | Nijhoff; 2010 [cited 2023 Jun 14]. p. 1041–53. Available from: https://brill.com/view/book/edcoll/9789004181564/Bej.9789004163300.i-1081_085.xml
  8. ICH guideline Q11 on development and manufacture of drug substances (chemical entities and biotechnological/biological entities), Step 3.
  9. Reid GL, Morgado J, Barnett K, Harrington B, Wang J, Harwood J, et al. Analytical Quality by Design (AQbD) in Pharmaceutical Development | American Pharmaceutical Review - The Review of American Pharmaceutical Business & Technology [Internet]. [cited 2023 Jun 9]. Available from: https://www.americanpharmaceuticalreview.com/Featured-Articles/144191-Analytical-Quality-by-Design-AQbD-in-Pharmaceutical-Development/
  10. Borman P, Chatfield M, Nethercote P, Thompson D, Truman K. The application of quality by design to analytical methods. Pharm Technol. 2007 Dec 1; 31:142–52.
  11. Patil, A.; Pethe, A.; Quality by Design (QbD): A new concept for development of quality pharmaceuticals. International Journal of Pharmaceutical Quality Assurance.2013, 4(2); 13-19.
  12. Nagar P, Garg M, Chauhan C, Kumar R, Chaudhary AK. Analytical Quality by Design (AQBD) Approach for HPLC Method Development, Method Optimization and Validation. International Journal of Pharmaceutical Quality Assurance. 2022;13(2):103-110.
  13. Gupta V, Jain ADKJ, Gill NS, Guptan K. Development and validation of HPLC method-a review. International research journal of pharmaceutical and applied sciences 2012; 2(4): 17-25.
  14. Thamman M. A review on high-performance liquid chromatography (HPLC). Res Rev: J Pharm Anal. 2016; 5: 22-8.

Photo
Dr.Mukesh S.Patil
Corresponding author

Shri.D.D.Vispute College of Pharmacy & Research Center

Photo
Sonal B. Bangar
Co-author

Shri.D.D.Vispute College of Pharmacy & Research Center

Photo
Tanmay Kamble
Co-author

Shri.D.D.Vispute College of Pharmacy & Research Center

Photo
Dr.Ashish Jain
Co-author

Shri.D.D.Vispute College of Pharmacy & Research Center

Bangar Sonal B., Patil Mukesh S.*, Jain Ashish S., Kamble Tanmay S., Development of a rapid LC method for Metopimazine based on a Quality by Design (QbD) approach, Int. J. of Pharm. Sci., 2024, Vol 2, Issue 12, 955-965. https://doi.org/10.5281/zenodo.14326663

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