il

n

t

g

te

g

e

q

s

Among all of the parameters, the robustness is oen considereda verication step and plays a kment of an analytical method.1,2 Rthrough traditional approachessuch as inability to determinbetween method variables like prate, buer concentration, mobilare time-consuming processes whdata as a single variable is changapproach is optimization using QICH Q8 guidelines, with Designensures success in nal methoDOE dates back to 1920 whenRonald A. Fischer, a British scienknowledge gained from experproposed by him overcomes t

chemicals (response surface designs for process optimization),

AnalyticalMethods

PAPER

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. approaches by considering all variables simultaneously andaDepartment of Pharmaceutical Analysis,

Education and Research (NIPER), Balana

E-mail: satish@niperhyd.ac.inbUnited States Pharmacopeia India Pvt. Lt

Knowledge Park, Genome Valley, Turkapall

India. E-mail: gs1738@yahoo.com

This journal is The Royal Society ofey role in successful develop-obustness is generally studiedwhich suer major drawbackse complex interactive eectsH, column temperature, owe phase composition etc. Thereich take several runs to obtained for each run; while anotheruality by Design (QbD), as perof Experiments (DOE), whichd validation.35 The history ofit was originally proposed bytist, in order to maximize theimental data. The approachhe limitations of traditional

the pharmaceutical eld and various elds which are concernedwith quality improvement.8,9

Christine Ye et al.10 have reported the applicability of DOEand data treatment using JMP and Brynn Hibbert D11 hasreviewed the use of DOE in chromatography. In recent years theapplicability of DOE and statistical data treatment to HPLCmethods have greatly increased.1216 JMP@ (SAS Institute) so-ware provides dual advantages like ecient data collection andscientic data interpretation with statistical evaluation of datafrom chromatographic analysis. The main aim of the presentpaper is to study the robustness parameter in the method vali-dation ofHPLC for simultaneous estimation of a combination oftwo anti-diabetic drugs sitagliptin (SIT) and pioglitazone (PIO)by application of the statistical method through DOE andanalyzing the data in JMP@ (SAS Institute) soware using theanalysis of variance method. SIT (Fig. 1a) is (R)-4-oxo-4-[3-(tri-Design and studysimultaneous estusing a statistica

Shantikumar Saladi,a Sreekaand N. Satheeshkumar*a

Application of design of experimen

factors were selected: the percenta

detector wavelength, the column

are examined in two-level screenin

system suitability parameters like th

using the ANOVAmethod by least s

the method is robust within the e

sitagliptin and pioglitazone.

Introduction

Developing chromatographic methods involves the utilizationof various approaches such as trial and error with dierentcolumns, dierent mobile phases and soware based methods.The subsequent step aer method development is methodvalidation which includes several sensitive analytical parame-ters to ensure that the method is accurate, precise and robust.

Cite this: DOI: 10.1039/c3ay42330a

Received 31st December 2013Accepted 10th February 2014

DOI: 10.1039/c3ay42330a

www.rsc.org/methodsNational Institute of Pharmaceutical

gar, Hyderabad 500 037, A.P, India.

d, Reference Standards Laboratory, ICICI

y, Shameerpet, Hyderabad 500 078, A.P,

Chemistry 2014of a HPLC method for themation of two anti-diabetic drugsapproach

th Gutala,*b Krishnaveni Yadiki,a M. V. N. Kumar Talluria

s to study the robustness of a HPLC method was carried out, where six

e of acetonitrile (ACN) in themobile phase, the pH of mobile phase, the

mperature, the ow rate and the strength of the buer. These factors

experimental designs created using JMP@ (SAS Institute) software. The

capacity factor, tailing factor, resolution were calculated and analyzed

uares tting. The results are within the acceptance criteria showing that

tablished limits. Forced degradation studies were also conducted for

obtaining the most relevant data with minimal eort.6,7

Generally, DOE is a systematic, rigorous approach that appliesprinciples and techniques at the data collection stage so as toensure the generation of valid, supportable conclusions andwhich can be carried out under the constraint of a minimalamount of runs, time and money. This approach nds itsapplication in a broad range of elds such as agriculture(factorial and fractional designs), defense (sequential designs),

View Article OnlineView Journaluoromethyl)-5,6-dihydro[1,2,4]triazolo[4,3-a]pyrazin-7(8H)-yl]-1-(2,4,5-triuorophenyl)butan-2-amine and is an anti-diabeticdrug of the dipeptidyl peptidase-4 (DPP-4) inhibitor class. Itworks by inhibiting the dipeptidyl peptidase 4 (DPP-4) enzymecompetitively.17 PIO (Fig. 1b) is [()-5-[[4-[2-(5-ethyl-2-pyridinyl)ethoxy]phenyl]methyl]2,4]thiazolidinedione mono hydrochlo-ride. It is a potent agonist for the peroxisome proliferator-

Anal. Methods

pill was administered to subjects, results showed that there is

Empower soware. The thermal stability study was performedin a dry air oven (Mack Pharmatech Pvt. Ltd., Mumbai, India). Aphotostability chamber (Osworld, Mumbai, India) was used forthe photodegradation study. All pH measurements were doneusing a pH-meter (Metrohm SchweizAG, 780 pH-meter, Ger-many) and weighing was done using a Sartorius balance(CD225D, 22308105 Germany).

Chromatographic conditions and solution preparation

Chromatographic analysis was carried out at a temperature of30 C. The compounds were separated isocratically using aHypersil BDS column (C18, 250 4.6 mm i.d.; particle size, 5m)using a mobile phase consisting of acetonitrile : 25 mMammonium acetate buer with the pH adjusted to 4.5 withacetic acid (45 : 55, v/v), at a ow rate of 1 mL min1. The eluentwas monitored using UV detection at a wavelength of 267 nmand an injection volume of 10 mL was used. Sample solutionswere prepared by dissolving appropriate amounts of SIT andPIO in the ratio (10 : 3) initially in 10 mL of 0.1 N HCl and thevolume was made up to 50 mL with acetonitrile. The analyticalconcentrations of SIT and PIO in the stock solution were 2 mgmL1 and 0.6 mgmL1 respectively. For linearity determination

Analytical Methods Paper

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article OnlineExperimentalMaterials

SIT and PIO were kindly provided by Dr. Reddys Ltd. India.HPLC grade acetonitrile, methanol, acetic acid, hydrochloricacid and ammonium acetate-GR were purchased from Merck.Milli-Q water (16.2 MU cm) was obtained using a Milli-Q system(Millipore, Billerica, MA).

Instrumentation

The HPLC system used for the method development andsignicant greater reduction in A1c compared tomonotherapy.19

Pharmaceutical formulation for this product is under researchand in our lab we have studied the excipient compatibility withSIT for a few excipients,20 which aid in the formulation devel-opment of this combination. In the present study we haveevaluated the placebomixtures of SIT and PIO. Among these twocompounds, SIT is soluble in water while PIO is insoluble.activated receptor gamma (PPARg).18 SIT and PIO in a combi-nation pill have complementary eects, when this combination

Fig. 1 (a) Structure of sitagliptin. (b) Structure of pioglitazone.degradation study was an Agilent 1100 series consisting of aquaternary pump plus an auto sampler and diode array detector(DAD). The output signal was monitored and processed using

Table 1 PlackettBurman design for the robustness study

Run PatternFlow rate (mLmin1) pH

Bu(mM

1 ++++++ 1.1 4.7 302 ++ 0.9 4.3 303 ++ 0.9 4.3 204 +++ 0.9 4.7 205 +++ 0.9 4.7 306 +++ 1.1 4.3 207 +++ 1.1 4.3 308 ++ 1.1 4.7 20

Anal. Methods269 40 47269 30 43265 40 47269 30 47265 40 43269 40 43265 30 47265 30 43er strength)

Wavelength(nm)

Temperature(C) %ACN

Fig. 2 Chromatogram of standard sitagliptin (Rt: 3.61) and pioglita-zone (Rt 9.38), in a ratio of (10 : 3) measured at 267 nm with a mobilephase of acetonitrile : 25 mM ammonium acetate buer with pH 4.5(45 : 55, v/v). The inset shows the overlaid spectra of both compounds(each 10 mg mL1) produced on a UV-Vis spectrophotometer.This journal is The Royal Society of Chemistry 2014

triplicate samples of the compounds were prepared at 20%,40%, 60%, 80%, 100%, 120% and 140% of the stock solutionresulting in concentrations between 2001400 mg mL1 and 60420 mg mL1 for SIT and PIO respectively. The detection limitwas 0.2% and 0.38% for SIT and PIO of the analyticalconcentration.

Design of the forced degradation study

A forced degradation study was carried out by transferring 50mg of SIT and 15mg of PIO into a 250mL round bottomed ask.These proportions were employed under acidic, alkaline,oxidative, thermal and photolytic conditions. Aer degradationwas complete the samples were collected and allowed toequilibrate at room temperature, quenching was carried out in

Table 2 Summary of validation parameters: statistical data for thecalibration graphs

Parameter Sitagliptin Pioglitazone

Linearity range (mg mL1) 2001400 60420Correlation coecient 0.9997 0.002 0.9998 0.002Limit of detection (mg mL1) 2.0 1.1Limit of quantitation (mg mL1) 6.5 3.8Recovery 99.05 2.13 99.5 1.44

Precision (%RSD)Inter-day (n 6) 1.11 1.12Intra-day (n 6) 0.21 0.10

Fig. 3 Chromatograms of the forced degradation study, which include (stressed samples treated with 1 N NaOH at room temperature for 6 h, (cphoto stressed samples and (e) thermally stressed samples.

This journal is The Royal Society of Chemistry 2014

Paper Analytical Methods

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article Onlinea) acid stressed samples treated with 1 N HCl at 80 C for 3 h, (b) alkali) peroxide stressed samples treated with 5% H2O2 at 80 C for 3 h, (d)Anal. Methods

the cases of the acid and alkaline samples and nally dilutedwith acetonitrile to attain the target concentration. The acidstressed samples were treated with 1 N HCl at 80 C for 3 h,alkali stressed samples were treated with 1 N NaOH at roomtemperature for 6 h, peroxide stressed samples were treatedwith 5% H2O2 at 80 C for 3 h, the photo stressed sample wasexposed as per ICH recommendations and the thermal stressedsample was kept in a hot air oven at 70 C for 48 h.

Robustness study

Robustness of an analytical procedure is a measure of itscapacity to remain unaected by small, but deliberate variationsin method parameters and it provides an indication of reli-ability during normal usage. In the present study, six factorswere selected, namely the acetonitrile (ACN) percentage in themobile phase, the pH of the mobile phase, the detectionwavelength, the column temperature, the ow rate and thestrength of the buer. Prior knowledge of the physiochemicalproperties and chromatographic behaviour of the compoundssuggested that these six factors would not be highly interactive.Therefore using JMP soware, a fractional factorial design wasgenerated (Table 1). The eects of variations in the chromato-graphic parameters were evaluated using system suitability testresults.

sample and its solubility. As mentioned earlier, the challenge

with these two compounds is their solubility. The compoundsare soluble in 0.1 N HCl, therefore samples were initially solu-bilized in 0.1 N HCl and the nal volume was made up withacetonitrile in the composition of 0.1 N HCl and acetonitrile(1 : 4, v/v). The best results were obtained with this composition.Aer selecting the proper diluent, preliminary trials were carriedout with a mobile phase consisting of water and methanol oracetonitrile, but they were lacking in peak characteristics, sobuers like KH2PO4 and ammonium acetate were preferredinstead of water. The best results were obtained withacetonitrile : 25 mM ammonium acetate buer with the pHadjusted to 4.5 with acetic acid (45 : 55, v/v). In the present studyforceddegradationwas also included,wherein a specic stabilityindicating assay method was established. Stability indicatingassay methods are useful for determining the integrity of a drugsubstance anddrug product during accelerated shelf life studies.It provides information about the drugquality. Therefore there isa need to develop a stability indicating HPLC method.

System suitability

System suitability shows the suitability of a system for thatparticular analysis. Five replicate injections of standard prepa-ration were injected and the tailing factor, capacity factortheoretical plate, resolution and %RSD of the peak area were

Analytical validation

,

d

S. no ExcipientAa

22

2222

Analytical Methods Paper

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article Online1 Micro crystalline cellulose2 Calcium hydrogen

phosphate3 Cross carmellose4 Magnesium stearate5 Sodium stearate6 Lactose monohydrateTable 3 Summary of the results from the forced degradation study

SamplesNo. of degradation products(Rt values)

Acid (Fig. 3a) 3 (2.72, 3.07, 7.22)Base (Fig. 3b) 4 (2.55, 2.71, 4.38, 6.88)H2O2 (Fig. 3c) 10 (2.62, 2.92, 3.50, 4.33, 4.55Photolytic-UV (Fig. 3d) 4 (1.27, 2.29, 3.32, 7.18)

Table 4 Evaluation data for the recovery studies using commonly useResults and discussionDevelopment and optimization of the HPLC method

Thequality of anyHPLCmethoddepends on theproper selectionof stationary andmobile phases which relies on the nature of theAnal. Methods25.12 19.3615.29 10.20

5.10, 6.16, 7.26, 7.54) 30.50 46.5214.63 20.38

excipients

mountdded

Percentage recovery

Sitagliptin Pioglitazone

0 mg 99.9 100.10 mg 95.2 98.8

0 mg 100.2 97.50 mg 98.2 101.40 mg 101.3 98.60 mg 99.5 100.6

99.05 2.13 99.5 1.44Linearity. Calibration curves for both compounds in thelaboratory mixture solutions were found to be linear with

%degraded

SIT PIOdetermined. All parameters were within the expected range.Fig. 2 shows neat separation of compounds along with theirrespective UV spectra.This journal is The Royal Society of Chemistry 2014

correlation coecients of 0.9997 and 0.9998 respectively; Table2 lists a summary of the validation parameters.

Specicity and selectivity. Selectivity was determined by

Robustness

System suitability tests were performed, according to thedesign, across eight chromatographic runs. Results wereobtained (Table 5) for the area response, retention time, tailingfactors, capacity factor and resolution of the peak of interest,and the %RSD was calculated and examined for robustness.

Table 5 Results of system suitability parameters

Run Compound

Capacity factor(mean S.D)

Tailing factor(mean S.D) Resolution (mean S.D)

1 SIT 2.47 0.008 1.42 0.006 1.62 0.004PIO 7.94 0.071 1.03 0.010

2 SIT 2.53 0.005 1.42 0.004 1.64 0.005PIO 8.21 0.000 1.02 0.008

3 SIT 2.72 0.024 1.53 0.190 2.05 0.012PIO 10.6 0.098 1.00 0.008

4 SIT 2.42 0.016 1.50 0.010 2.05 0.000PIO 9.94 0.004 1.04 0.004

5 SIT 2.65 0.012 1.52 0.012 1.75 0.005PIO 9.01 0.006 1.02 0.016

6 SIT 2.76 0.011 1.56 0.008 2.02 0.005PIO 10.52 0.024 1.04 0.013

7 SIT 2.73 0.008 1.54 0.008 1.75 0.080PIO 9.55 0.012 1.02 0.019

8 SIT 2.22 0.022 1.49 0.004 1.86 0.030PIO 7.62 0.019 1.02 0.005

Paper Analytical Methods

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article Onlinechecking the interference of excipients with the analytes. Thespecicity of the proposed method was determined by checkingthe peak purity of SIT and PIO during the forced degradationstudy. Fig. 3 shows the chromatograms of the acid, alkali,peroxide, photolytically and thermally stressed samples wherethe method is being used to separate SIT and PIO from theirdegradation products. There is no interference from any of thedegradants with the main peak. Thus the proposed HPLCmethod is selective for both of the compounds. The results aretabulated in Tables 3 and 4.

Table 6 Results for the variation in retention times and area responseParameter Rt of C1 Area of C1 Rt of C2 Area of C2

Mean 3.58 2 108 923.00 9.45 2 559 697.00Std dev. 0.16 32 420.67 0.31 33 726.59%RSD 4.66 1.53 3.31 1.31Std error mean 0.06 11 462.44 0.11 11 924.1595% condence level 0.11 22 465.90 0.21 23 370.91

Table 7 Parameter estimates for the capacity factor, tailing factor and r

Parameter

Std error t ratio

T K0RS

T

SIT PIO SIT PIO SIT

Flow rate (0.9, 1.1) 0.016 0.008 0.018 0.024 0.011 1.31pH (4.3, 4.7) 0.016 0.008 0.018 0.024 0.011 0.38Strength of buer (20, 30) 0.016 0.008 0.018 0.024 0.011 0.23Wavelength (265, 269) 0.016 0.008 0.018 0.024 0.011 0.38Column temperature (30, 40) 0.016 0.008 0.018 0.024 0.011 1.15%ACN (43, 47) 0.016 0.008 0.018 0.024 0.011 1.46

This journal is The Royal Society of Chemistry 2014JMP soware enables application of the screening design i.e. thePlackettBurman design through which the main eects can beconfounded and by running the model with data, statistical

Table 8 Summary of t for the capacity factor, tailing factor andresolution

Summary of t

0esolution

Prob > [t]

K0RS

T K0RS

PIO SIT PIO SIT PIO SIT PIO

0.43 6.68 22.42 1.89 0.415 0.742 0.094 0.028 0.3100.14 1.23 13.80 2.11 0.766 0.909 0.435 0.056 0.2810.14 1.07 0.04 3.89 0.855 0.909 0.479 0.972 0.1600.43 4.84 3.22 5 0.766 0.742 0.129 0.191 0.122

0.71 1.66 9.53 6.78 0.454 0.605 0.345 0.066 0.0930.14 3.98 34.61 11.22 0.382 0.909 0.156 0.058 0.056

T KRS

SIT PIO SIT PIO

R square 0.8467 0.4842 0.9889 0.9994 0.9954Root mean square error 0.0459 0.0247 0.0518 0.0689 0.0318Mean of response 1.50 1.02 2.56 9.17 1.84Observation 48 48 48 48 48

Anal. Methods

evaluation of the data can be done through which the signi-cant and non-signicant factors can be ascertained.

The factors selected in the robustness test were related to theanalytical procedure like the pH of the mobile phase, the %ACN, the detection wavelength, the strength of the buer and

the ow rate (operational factors), and to the environmentalconditions like the column temperature (environmentalfactors). The operational factors are selected from the descrip-tion of the analytical method (operating procedure), whereasthe environmental factors are not necessarily specied explicitly

)

Analytical Methods Paper

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article OnlineFig. 4 Prediction proler for the capacity factor (a), the tailing factor (bbecause of its acceptance limits.Anal. Methodsand the resolution (c). The desirability was shown for resolution aloneThis journal is The Royal Society of Chemistry 2014

in the analytical method. The levels for these factors wereselected based on systematic determination of the uncer-tainties.21 The pH varies with a condence level of 95% in theinterval pH 0.02. The column temperature, %ACN, detectionwavelength, strength of the buer and ow rate low and highlevels were based on the uncertainty. The factors were examinedin an experimental design, which was selected as a function ofthe number of factors investigated. The design applied was atwo-level screening design which allowed the screening of arelatively large number of factors in a relatively small number ofexperiments. The design applied was fractional factorial. In thisrobustness test we have focused mostly on the main eects ofthe factors.

Regarding the screening design, the parameters to beconsidered should be selected based on the purpose of themethod and its performance characteristics, and tolerances arexed by considering the tolerance of the HPLC system. Byapplication of the design the number of experiments forrobustness testing were decreased as it gives a better under-standing of the process, rather than studying extremities likewhich factors are more or less inuential on the results.

Variation in the retention time and area response. The %RSD for the retention time of eight experimental runs for bothof the compounds was between 3.33 and 4.66% on average,which is within the proposed criterion of 5%. The %RSD for thearea response was between 1.3 and 1.5%, for which theproposed acceptance criterion of [t] was greater than 0.05 for the ow rate,the pH of the mobile phase, the strength of the buer, thedetection wavelength, the column temperature and the ACNpercentage. It demonstrated that no signicant dierences wereobserved when changing the above factors within the testedranges. The prediction prole on the 95% condence intervalshowed that all T values would be within the acceptance crite-rion, 1.0 # T # 1.56, if parameters were changed within theirtesting ranges. Therefore, the conclusion was made that thetailing factor was acceptable when chromatographic parameterswere changed within the experimental range. These results areshown in Tables 7 and 8.

Capacity factor. The capacity factor (K0) for each of the 8injections for both of the compounds was also analyzed usingthe ANOVAmethods by least squares tting. The tting revealedthat each of the six factors showed no signicant dierencesbetween the two levels tested. However, parameter estimates forthe ow rate, the pH of the mobile phase, the strength of the

ip

Paper Analytical Methods

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article OnlineFig. 5 Contour proles of the retention times and peak areas of sitaglThis journal is The Royal Society of Chemistry 2014tin (C1) and pioglitazone (C2).Anal. Methods

buer, the detection wavelength, the column temperature andthe ACN percentage were 0.122, 0.022, 0.019, 0.088, 0.0304and 0.0729 respectively, which were very small compared withthe mean value of 2.56, therefore these factors will not beconsidered as primary factors in changing the capacity factor.The results are shown in Tables 7 and 8.

Resolution. The resolution (RS) is the separation between twochromatographic peaks. It is not only the measure of theseparation of peaks but also the eciency of the column. Forreliable quantication, well-separated peaks are essential. Aresolution of >1.5 between the peaks of interest is desirable. Theresolution (RS) for each of the 8 injections was also analyzedusing the ANOVA methods by least squares tting. The tting

revealed that each of the six factors showed no signicantdierences with the set minimum. However, parameter esti-mates for the ow rate, the pH of the mobile phase, the strengthof the buer, the detection wavelength, the column temperatureand the ACN percentage were 0.02125, 0.02375, 0.04375,0.05625,0.07625 and0.12625 respectively, which were verysmall compared with the mean value of 1.84, therefore thesefactors will not be considered as primary factors in changing theresolution and method parameters. These results are shown inTables 7 and 8. Fig. 4 is the prediction proler for all of thesystem suitability parameters, where parameter estimates andthe respective proles of each run with respect to all of theselected factors are depicted.

pdo

Analytical Methods Paper

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article OnlineFig. 6 Contour proler with response surface plots which show the imcapacity factor, the tailing factor and the resolution for both sitagliptin anwavelength, (c) ow rate vs. pH, (d) ow rate vs. temperature and (e) Anal. Methodsact of various parameters, against a xed ow rate as a variable, on thepioglitazone. (a) Flow rate vs. buer strength, (b) ow rate vs. detectionw rate vs. %ACN.This journal is The Royal Society of Chemistry 2014

Contour proler and the impact of various factors

The contour proler is useful for studying the responsesurfaces graphically, the shaded regions show the unaccept-able regions and the unshaded regions (white) represent theacceptable regions in the contour plots. Contour plots wereplotted for responses like the tailing factor, the resolution, the

Pharmacopeia (USP)-India Private Limited for supporting thiswork. The authors are indebted to NIPER-Hyderabad, forproviding the support and encouragement to carry out this workand S. Shanti Kumar is grateful to NIPER for providingfellowship.

1998, http://www. eurachem. org.

Paper Analytical Methods

Publ

ished

on

10 F

ebru

ary

2014

. Dow

nloa

ded

by U

nive

rsity

of S

outh

ern

Calif

orni

a on

04/

04/2

014

08:0

7:07

. View Article Onlinecapacity factor and the eects of the various variables selectedfor the robustness study were evaluated. Fig. 6ae show thecontour proles. Flow rate was xed as a horizontal factoragainst which vertical factors like pH (X 4.5), buerstrength (X 25 mM), wavelength (X 267 nm), temperature(X 35 C) and %ACN (X 45), were plotted. Within thetested ranges the method didn't show any unacceptable areas.The lines on the graphs are contours for responses set by Yslider controls; there are separately coloured contours for eachresponse.

Desirability function

These are smooth piecewise functions which are designed to tcontrol points. In Fig. 4 the minimum desirability function isshown; this associates high response values with low desir-ability and low response values with high desirability. The topfunction handle is positioned at the minimum desirability i.e.Y 2.1 with a desirability of 0 and Y 1.6 with a desirability of1. The desirability traces are also shown for each factor.

Conclusion

A new HPLC method has been developed to be routinely appliedto determine SIT and PIO in pharmaceutical dosage form. Themethod was validated by employing ICH recommended stressconditions. The method has been proven to be specic, linear,precise, accurate, robust and an indicator of stability. Hence themethod can be recommended for routine quality control anal-ysis. The proposedmethodwas robust within the specied limitswhich can be assured by the statistical data provided. Theacceptance criteria for the system suitability were %RSD for Rt#5.0% and %RSD for area #2.0%, 1.0 # T # 1.56, K0 $ 1.5. Thecontrol limits for the HPLC method parameters tested in thisrobustness study are as follows:ow rate 1 0.1mLmin1, pHof the mobile phase 4.5 0.2, buer strength 25 5 mM,detectionwavelength 267 2 nm, temperature 35 5 Cand%ACN 45 2. To conclude, approaches like DOE ts well withthese applications which is economical and reduces the totalnumberof experiments tobe carriedoutwhich in turnsaves time.

Acknowledgements

The authors wish to thank Dr K. V. Surendranath, Sr VicePresident and other scientic sta of United StatesThis journal is The Royal Society of Chemistry 2014References

1 K. D. Altria and S. D. Filbey, Chromatographia, 1994, 39, 306310.

2 J. N. Miller, Analyst, 1991, 116, 314.3 I. Molnar and K. E. Monks, Chromatographia, 2011, 73, 514.4 B. Julicher, P. Gowik and S. Uhlig, Analyst, 1999, 124, 537545.

5 J. C. Berridge, Analyst, 1987, 112, 385389.6 M. J. Anderson and P. J. Whitcomb, Design of experiments,Wiley Online Library, 1974.

7 D. R. Cox and N. Reid, The theory of the design of experiments,CRC Press, 2002.

8 R. L. Mason, R. F. Gunst and J. L. Hess, Statistical design andanalysis of experiments: with applications to engineering andscience, Wiley, 2003.

9 G. Vicente, A. Coteron, M. Martinez and J. Aracil, Ind. CropsProd., 1998, 8, 2935.

10 C. Ye, J. Liu, F. Ren and N. Okafo, J. Pharm. Biomed. Anal.,2000, 23, 581589.

11 D. B. Hibbert, J. Chromatogr. B: Anal. Technol. Biomed. LifeSci., 2012, 910, 213.

12 Y. AlSalka, F. O. Karabet and S. Hashem, Anal. Methods,2010, 2, 10261035.

13 S. Gorji and M. Bahram, Anal. Methods, 2010, 2, 948953.14 Y. Guo, S. Srinivasan and S. Gaiki, Chromatographia, 2007,

66, 223229.15 V. R. Harang and D. Westerlund, Chromatographia, 1999, 50,

525531.16 G. Srinubabu, K. Jaganbabu, B. Sudharani, K. Venugopal,

G. Girizasankar and J. Rao, Chromatographia, 2006, 64, 95100.

17 B. Gallwitz, Vasc. Health Risk Manage., 2007, 3, 203.18 U. Smith, Int. J. Clin. Pract. Suppl., 2001, 13.19 R. R. Henry, B. Staels, V. A. Fonseca, M. Z. Chou, R. Teng,

G. T. Golm, R. B. Langdon, K. D. Kaufman, H. Steinbergand B. J. Goldstein, Diabetes Obes. Metab., 2014, 16, 223230.

20 S. Shantikumar, G. Sreekanth, K. V. SurendraNath,S. JaferValli and N. Satheeshkumar, J. Therm. Anal.Calorim., 2014, 115, 24232428.

21 E. Guide, The Fitness for Purpose of Analytical Methods: ALaboratory Guide to Method Validation and Related Topics,Anal. Methods

Design and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approach

Design and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approach

Design and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approachDesign and study of a HPLC method for the simultaneous estimation of two anti-diabetic drugs using a statistical approach