“qbd approach to analytical method development and

www.wjpps.com Vol 5, Issue 5, 2016.

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Alifiya et al. World Journal of Pharmacy and Pharmaceutical Sciences

“QbD APPROACH TO ANALYTICAL METHOD DEVELOPMENT

AND VALIDATION OF PIRACETAM BY HPLC.”

Alifiya S. Rajkotwala*, Shaikh Sirajuddin S., Dr. Zarna R. Dedania,

Dr. Ronak R. Dedania and Dr. S. M. Vijendraswamy

India.

ABSTRACT

Piracetam, a derivative of the neurotransmitter γ-aminobutyric acid

(GABA), has a variety of physiological effects that may result, at least

in part, from the restoration of cell membrane fluidity. Quality by

design (QbD) refers to the achievement of certain predictable quality

with desired and predetermined specifications. A very useful

component of the QbD is the understanding of factors and their

interaction effects by a desired set of experiments. The present study

describes the development of a comprehensive science and risk based HPLC method and

subsequent validation for the analysis of Piracetam active pharmaceutical ingredient (API)

using a quality by design approach. An efficient experimental design based on systematic

scouting of two key components of the RP‐HPLC method (mobile phase and pH) is

presented. The stock solution Piracetam was made in methanol and absorption maximum of

standard solution of Piracetam was found be 205 nm. The chromatographic condition were

optimized with design expert software 10.0 version, i.e; column C18, mobile phase used

buffer (pH 6.5): Acetonitrile+0.1% TEA (80:20), flow rate was 1 ml/min. The described

method was linear (r2 = 0.998) with range 20-70 µg/ml. The precision, ruggedness and

robustness values were also within the prescribed limits (<1% for system precision and <2%

for other parameters). Chromatographic peak purity results indicated the absence of

co‐eluting peaks with the main peak of Piracetam. The proposed method can be used for

routine analysis of Piracetam in quality control laboratories.

KEYWORDS: Quality by design, HPLC, Piracetam, Design approach.

WORLD JOURNAL OF PHARMACY AND PHARMACEUTICAL SCIENCES

SJIF Impact Factor 6.041

Volume 5, Issue 5, 1771-1784 Research Article ISSN 2278 – 4357

*Corresponding Author

Alifiya S. Rajkotwala

India.

Article Received on

21 March 2016,

Revised on 11 April 2016,

Accepted on 01 May 2016

DOI: 10.20959/wjpps20165-6847

http://www.wjpps.com/


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INTRODUCTION

Quality by Design (QbD)[1-4]

is well established in the pharmaceutical industry for

manufacturing processes (ICH Q8 for pharmaceutical development and ICH Q11 for

development and manufacture of drug substances). QbD is “a systematic approach to

development that begins with predefined objectives and emphasizes understanding and

control, based on sound science and quality risk management”. The outcome of using QbD

concepts is a well-understood product and process that consistently delivers its intended

performance. The knowledge obtained during development may support the establishment of

a design space and determines suitable process controls. This same QbD principle has been

applied to the development of analytical methods and is termed “Analytical QbD” (AQbD).

Analogous to process QbD, the outcome of AQbD is well understood, fit for purpose, and

robust method that consistently delivers the intended performance throughout its lifecycle.

High performance liquid chromatography (HPLC)[5-6]

is a type of column chromatography

used frequently for analytical chemistry and biochemistry. RP-HPLC is the choice for the

majority of samples. It consists of a non polar stationary phase and an aqueous, moderately

polar mobile phase. The quality of HPLC methods has become increasingly important in a

QbD environment. For the purpose of QbD for HPLC methods, robustness and ruggedness

should be verified early in the method development stage to ensure method performance over

the lifetime of the product. Otherwise, if a non‐robust or non‐rugged method is adapted,

significant time and resource may be required to redevelop, revalidate and retransfer

analytical methods.

The present work is aimed to develop QbD approach to analytical method development and

validation based of Piracetam by HPLC.

The primary objective of this study was to implement Qbd approach to develop and validate

an RPHPLC method that could separate drug from its potential related substances and to

establish an indepth understanding of the method and build in the quality during the method

development to ensure optimum method performance over the lifetime of the product.

The objectives of this work are as follows[7]

:

To develop and sensitive method for identification of critical attributes by QbD approach

of this Nootropic drug (CNS Stimulant) by RP-HPLC.

To establish a validated test method as per ICH guidelines for the determination of assay

of Piracetam by RPHPLC.



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MATERIALS AND METHODS

Instruments and Reference Standards

HPLC system, FT-IR (Shimadzu), Double Beam UV Spectrophotometer (Shimadzu

UV1800), Pure sample of Piracetam obtained from Exmed pharmaceuticals, Vapi, India.

Methodology

Preparation of Reference Standard Solution

The standard stock solution was prepared by dissolving 100 mg of piracetam in 100 ml

methanol. A 100 µg/ml was prepared by diluting 5ml of stock solution to 50 ml with

methanol. Finally standard sub-stock solution of 10µg/ml was prepared by diluting 1 ml of

the above solution (100µg/ml) to 10 ml with methanol.

Selection of detection wavelength

The detection was carried out in the UV region and wavelength selected for detection was

205 nm in methanol. Solution was prepared in pure methanol and scanned in the range of

200-400 nm.

Method development by QbD approach

1. Define method intent[8-9]

The goals of HPLC method development have to be clearly defined, as pharmaceutical QbD

is a systemic, scientific, risk based, holistic and proactive approach that begins with

predefined objectives and emphasizes product and process understanding and control.

2. Perform experimental design[10-11]

A systematic experimental design is needed to assist with obtaining in‐ depth method

understanding and performing optimization. Here an efficient and comprehensive

experimental design based on systematic scouting of two key components of the RP‐HPLC

method (mobile phase and pH) is presented. It forms a chromatographic database that will

assist with method understanding, optimization and selection. In addition, it can be used to

evaluate and implement change of the method, should it be needed in the future, for example

should the chromatographic column used no longer be commercially available, or an impurity

is no longer relevant.



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Factorial Design

Central composite statistical screening design was used to optimize and evaluate main

effects, interaction effects and quadratic effects of the formulation ingredients on the in-vitro

release of the drug. A 2-factor, 3-level design used is suitable for exploring quadratic

response surfaces and constructing second order polynomial models with Design Expert®

(Version 10.0, Stat-Ease Inc., Minneapolis, MN).

Y = β0 + β1A + β2B + β12AB + β11A2 + β22B2

Where Y is the measured response associated with each factor level combination; β0 is an

intercept; β1 to β22 are regression coefficients computed from the observed experimental

values of Y from experimental runs; and A and B are the coded levels of independent

variables. The terms AB, A2 and B

2 represent the interaction and quadratic terms,

respectively. The factors were selected based on preliminary study. Mobile phase

composition (A) and pH (B) were selected as independent variables. The Retention time,

peak area and peak asymmetry were selected as dependent variables.

Table 1: Coded values for independent variables

Name of the Factor Coded values Level

-1 0 1

Mobile phase composition A 70:30 75:25 80:20

pH B 6.0 6.5 7.0

Table 2: Different batches with their respective composition

Batch code Mobile phase composition(A) pH (B)

P1 -1 -1

P2 -1 0

P3 -1 1

P4 0 -1

P5 0 0

P6 0 0

P7 0 0

P8 0 1

P9 1 -1

P10 1 0

P11 1 1

3. Evaluate experimental results and select final method conditions[12]

These method conditions were evaluated using the three tiered approach. At the first level,

the conditions were evaluated for peaks symmetry, retention time and peaks tailing. This



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resulted in different chromatographic conditions for API. The best suited experimental

conditions shall be optimized using design expert software.

4. Perform risk assessment with robustness and ruggedness evaluation[13]

As the final method is selected against method attributes, it is highly likely that the

selected method is reliable and will remain operational over the lifetime of product.

Therefore, the evaluation of method robustness and ruggedness to be carried out as

the final step of method development is mainly for the method verification and finalization.

A risk‐based approach based on the QbD principles set out in ICH Q8 and Q9 was applied

to the evaluation of method robustness and ruggedness. Structured methodologies for risk

assessment, such as Fishbone diagram can be implemented to identify the potential risk of

the method due to a small change of method parameters or under a variety of conditions

such as different laboratories, analysts, instruments, reagents, days, etc.

5. Define analytical method performance control strategy

As a result of robustness and ruggedness studies, the overall method understanding of

method performance under various conditions can be improved and an analytical method

performance control strategy along with appropriate system suitability criteria can be defined

to manage risk and ensure the method delivers the desirable method attributes. If the risk is

high and is hard to manage, it is an opportunity for the analyst to go back to the database

described in experimental design to find a more appropriate method and to go through the

procedure as described to ensure method robustness and ruggedness.

Analytical method validation

Validation is documented evidence, which provide a high degree of assurance for specific

method. Validation is analytical process by which it is established by laboratory studies that

the performance characteristics of the procedure meet the requirement for intended analytical

application.

Linearity

The linearity of Piracetam was assessed in the range of (20-70 µg/ml) in terms of slope,

intercept and correlation co-efficient values.



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Precision

A. Repeatability

Measure area of standard mixed solutions containing Piracetam 40 µg/ml at 205 nm. The

area of solution was measured 7 times and % RSD was calculated.

B. Intra-Day Precision

Intra-day precision was determined by analyzing Piracetam 40, 50, 60 µg/ml concentrations

were determined 3 times a day interval of 1 hour, simultaneously and %RSD was

calculated.

% RSD should be less than 2.

C. Inter-Day Precision

Inter-day precision was determined by analyzing Piracetam 40, 50, 60 µg/ml concentrations

were determined daily for 3 days and %RSD was calculated.

% RSD should be less 2%.

Accuracy

Accuracy of the method was confirmed by recovery study from marketed formulation at

three level of standard addition. Percentage Recovery of Piracetam was found out.

Recovery between 98-102% justify the accuracy method.

LOD AND LOQ

LOD was calculated out by using following Formula:

DL = 3.3σ/S

σ = Standard Deviation of the Response

S = Slope

LOQ was calculated out by using following Formula:

DL = 10σ/S

σ = Standard Deviation of the Response

S = Slope

Robustness

Robustness of the method was determined by subjecting the method to slight change in the

method condition, individually, the:

Pump flow rate,



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Mobile Phase ratio

% RSD was calculated.

System Suitability Studies

The system suitability was evaluated by five replicate analyses of Piracetam. The column

efficiency and peak asymmetry, Theoretical Plates were calculated for standard solutions.

Assay

Twenty tablets of each formulation of Piracetam were weighed and finely powdered. The

tablet powder equivalent to 100 mg of Piracetam was accurately weighed and transferred to a

100 ml volumetric flask, about 25 ml of methanol was added and the flask was sonicated for

15 min. Dilute 5 ml of resulting solution upto 50 ml with methanol. Further pipette out 0.4 ml

and transfer into 10 ml volumetric flask and dilute upto mark with methanol. The 40 µg/ml

solution was prepared and 20 µl was injected for HPLC analysis.

RESULTS AND DISCUSSION

Optimization of mobile phase

The mobile phase was successfully obtained after the many trials shown in the below table.

Table 3: Optimization of mobile phase

Sr. No. Mobile phase Ratio (v/v) Remark

1 Methanol: Acetonitrile (50:50) Peak was not proper.

2 Methanol: water (80:20) Peak tailing was observed.

3 Methanol: water (50:50) Peak broadening was observed

4 Acetonitrile: water (60:40) Peak was not resolved.

5 Buffer : Acetonitrile + 0.1%TEA (75:25) Peak was observed.

Fig. 1 Chromatogram of Trial 5 – Buffer(pH 6.5): Acetonitrile+0.1 TEA (75:25)



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Optimization of various parameters for Analysis of Piracetam using HPLC

(By Using Central Composite Design)

Table 4: Design Summary for optimization

Study Type Response Surface

Design Type Central Composite

Design

Design Model Quadratic

Runs 11

Fact

or

Nam

e

Un

its

Typ

e

Su

bty

pe

Min

imu

m

Maxim

um

Code 0 1

A Mobile phase mL Numeric Continuous 70.00 80.00

B pH Numeric Continuous 6.5 7

Table 5: Evaluation degrees of freedom of design for optimization of analysis of

Piracetam by HPLC

Res

pon

se

Nam

e

Un

its

An

aly

sis

Min

imu

m

Maxim

um

Rati

o

Mod

el

R1 Retention time min Polynomial 2.76 3.2 1.15942 Quadratic

R2 Area mAU Polynomial 1653767 1718190 1.03896 Linear

R3 Peak assymetry

Polynomial 1.15 1.71 1.48696 Quadratic

OPTIMIZED CONDITION OBTAINED

It was obtained by studying all responses in different experimental condition using Design

expert 10.0 software.

Table 6: Obtained solution for optimized formulation

Code Mobile

Phase pH

Retention

time Area

Peak

asymmetry Desirability

P10 80 6.58 2.9 1694739 1.5 0.83



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Fig. 2: 3D surface plot of desirability for obtaining optimized formulation.

Fig. 3: Chromatogram obtained from the optimized condition

Table 7: Predicted v/s Observed value

Response Predicted value Observed value % Prediction error

Retention time 2.9 2.86 -1.39%

Peak Area 1694739 1707834 0.76%

Peak Asymmetry 1.5 1.35 10%

Table 8: Final Optimized Method Condition

Sr.No. Parameters Results

1 Column C-18

2 Mobile Phase Buffer pH 6.5: Acetonitrile+0.1% TEA

(80:20 v/v)

3 Flow rate 1 mL/min



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4 Injection Volume 20 µl

5 Detection wavelength 205 nm

6 Run time 10 min

Method Validation

System Suitability

Table 9: System suitability test for Piracetam

Acceptance criteria Result

The %RSD for five replicate injections of

Standard preparation for piracetam

should be NMT 2.0.

0.23

The Tailing factor for the piracetam from

standard preparation should be NMT 2.0 1.15

Theoretical plates for piracetam peak

should be NLT 2000. 10768.34

Linearity

Fig. 4: Chromatogram of Linearity

Table 10: Linearity for Piracetam

Sr.No Conc(µg/ml) Peak Area (Mean±SD); (n=7)

1 20 838555.40 ± 829.34

2 30 1249573.80 ± 7561.83

3 40 16877327.20 ± 6276.22

4 50 2080673.00 ± 6393.48

5 60 2405964.00 ± 5892.26

6 70 2816071.60 ± 7060.84



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Fig. 5: Calibration Curve for Piracetam

Precision

Repeatability

TABLE 11: Data for Repeatability of Piracetam

Con.(µg/ml) Area Mean S.D %RSD

40 1690267.20

1685190.34 10612.30 0.63

40 1675245.20

40 1697289.20

40 1680230.20 40 1670743.20

40 1684307.20

Interday and Intraday Precision

TABLE 12: Data for Interday and Intraday of Piracetam

Sr.No Precision Period Conc(µg/ml) Mean SD %RSD

1 Interday Precision

40 1674117.00 13699.18 0.82

50 2075999.67 13947.16 0.67

60 2403348.00 12632.00 0.53

2 Intraday Precision

40 1668853.33 9416.95 0.56

50 2074643.00 13114.88 0.63

60 2420649.00 10120.84 0.42



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Recovery/Accuracy

Table 13: Recovery of Piracetam

Level

Amount

from the

sample

Amount of

standard

Piracetam

Spiked

Total

amount

(µg/ml)

Total Area

(Mean)

Recovered

amount

(µg/ml)±SD

(n=3)

%

Recovered of

Spiked amount±

SD (n=3)

80% 40 32 72 2994975.00 71.78±0.30 99.18 ± 0.94

100% 40 40 80 3317019.33 79.52±0.17 98.69 ± 0.42

120% 40 48 88 3664584.00 87.87±0.22 99.64 ± 0.45

Robustness

Table 14: Robustness for Piracetam

Sr.No Parameter Mean SD %RSD

1 Flow Rate+0.2 1661467.00 13699.18 0.82

2 Flow Rate-0.2 1668853.33 9416.95 0.56

3 Mobile Phase+2 1670427.00 10613.30 0.63

4 Mobile Phase-2 1669906.00 4945.17 0.30

LOD and LOQ

Table 15: LOD and LOQ of Piracetam

Parameters Results

Standard deviation of the Y-intercepts of the

calibration 75376.58

Mean slope of the calibration curves; (n=3) 39317.42

LOD (µg/ml) 6.32

LOQ (µg/ml) 19.17

Assay

Table 16: Assay of Piracetam

Sr. No. Label claim

Mg

Result

mg Peak Area % Assay

1 400 mg 400.1 mg 1672752.00 100.02

2 400 mg 399.4 mg 1669906.00 99.85

3 400 mg 401.7 mg 1679532.00 100.40

4 400 mg 399.1 mg 1665264.00 99.74

Mean 100.1

SD 0.28

%RSD 0.30

CONCLUSION

A reversed phase HPLC method development approach using QbD principles has been

described. First, the method goals are clarified based on the process understanding. The

experimental design describes the scouting of the key HPLC method components



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including mobile phase and pH. Their interrelationships are studied and optimized

conditions are obtained for each combination of mobile phase and pH with the help of

design expert 10.0 version. Here a better understanding of the factors influencing

chromatographic separation and greater confidence in the ability of the methods to meet

their intended purposes is done. Moreover, this approach provides an in-depth knowledge

and enables the creation of a chromatographic database that can be utilized to provide

alternative method conditions at a future time should changes to the method be required.

Futhermore, the method development is not considered finished until a thorough risk

assessment and all the necessary robustness and ruggedness studies are carried out. All the

validated parameters were found within acceptance criteria. The validated method is

specific, linear, precise, accurate, robust and rugged for determination based on knowledge

of method obtained through the method development and the results of risk assessment

along with robustness and ruggedness studies, detailed analytical method performance

control strategy can be defined to manage the risk. The approach can be successfully used

in laboratory to develop HPLC method for Piracetam.

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