Method Validation of HPLC

Method Validation of HPLC Customer Support Centre Shimadzu (Asia Pacific) Pte Ltd 1 Materials required to establish an analytical method Analytical Methods Analytical Procedure Controlling procedure of standard Controlling procedure of test sample Explanations of the instruments and apparatus System suitability test Calculating formula and measurement number Specification of standards Materials of validation Test methods and evaluation methods to get results Analytical results Calculating results 2

Consideration in method development Separation Mobile phase Select of buffer solution ph Buffer concentration Select of organic solvent polarity Detection does not interrupt ETC Ionpair methods Derivatized methods Column Small subsidiary work High theoretical plate number Small dispersion for the lot Detector Sensitivity Selectivity Applied with SPDM10A VP 3 DOCUMENTS AVAILABLE ON VALIDATION OF ANALYTICAL PROCEDURES ICH Text on Validation of Analytical Procedures (October 1994) Extension of the ICH Text "Validation of Analytical Procedures (November 1994) FDA(CDER) Validation of Chromatographic Methods (November 1994) USP23 <1225> Validation of Compendial Methods Others Pharmaceutical Technology, LCGC, etc.

Evaluation of Parameters for Analytical Capability Parameters for analytical capability are evaluated by analytical results using statistical method. Estimation and test Regression analysis and Variance analysis 5 VALIDATION CHARACTERISTICS Validation of an analytical procedure is the process by which it is established that the validation characteristics of the analytical procedure meet proper standards of validation characteristics. [Typical Validation Characteristics] Accuracy Precision Repeatability Intermediate Precision Specificity Detection Limit Quantitation Limit Linearity Range (ICH Q2A,October 1994)

VALIDATION CHARACTERISTICS The table lists the validation characteristics regarded as the most important for the validation of different types of analytical procedures. IDENTIFICATION TESTING FOR IMPURITIES ASSAY characteristics quantitat. limit Accuracy Precision Repeatability Interm.Precision Specificity Detection Limit Quantitation Limit Linearity Range signifies that this characteristic is not normally evaluated signifies that this characteristic is normally evaluated Validation example(1) Test Confirmation test for acetylsalicylic acid in acetylsalicylic acid raw drug using HPLC. Analytical capability parameter to evaluate Specificity Data for evaluation Acetylsalicylic acid drug and standard of their impurity compound are analyzed. And, acetylsalicylic acid drug is analyzed on hard conditions. Get the chromatograms and spectrum of each peaks 8

SPECIFICITY Specificity is the ability to assess unequivocally the analyte in the presence of components which may be expected to be present. Typically these might include impurities, degradant, matrix, etc. Lack of specificity of an individual analytical procedure may be compensated by other supporting analytical procedure(s). [Determination] Specificity can be determined for instance by spiking pure substances with excipients and/or impurities and/or degradation products and to compare the test results with those of pure substances. Specificity test for acetylsalicylic acid(1) Acetylsalicylic acid phydroxybenzoic acid Salicylic acid A B 0 5 10 15(min) Resolution between target and impurity is more than 1.5 and each impurity resolution is more than 1.2. Spectrum of drug substance(b) is similar to one of standard acetylsalicylic acid(a). 10

Specificity test for acetylsalicylic acid(2) Acetylsalicylic Acid Salicylic Acid A B C D 0 5 10 15 min Chromatogaram of raw drug A: 10mMHCl 25 darkness 1hr B: 10mMNaOH 25 darkness 1hr C: White light5000 Neutral buffer 25 1hr D: 80 Neutral buffer darkness 1hr 11 Specificity test for acetylsalicylic acid(3) Method(peak purity) The spectrum of upslope, peaktop, downslope correspond each other. And theoretical plate number and symmetry factor are calculated by the chromatograms of different wavelength. Acetylsalicylic Acid 200 nm N=12804, Tf =1.20 220 nm N=12970, Tf =1.20 240 nm N=12924, Tf =1.20 260 nm N=12887, Tf =1.20 280 nm N=12924, Tf =1.20 0 5 10 15 min Chromatogarams of raw drug 12

Validation example(2) Test Quantitative testing for acetylsalicylic acid in their drug using HPLC Evaluation of Parameters Specificity Accuracy Repeatability Intermediate Precision Linearity Range Data 5 concentration level sample are analyzed 5 times. It is analyzed on different date, operator, instrument, column and reagent. Conc. 80 % 90 % 100 % 110 % 120 % 1st run 79.2 % 90.8 % 99.3 % 109.0 % 120.9 % 2nd run 79.7 % 90.2 % 100.8 % 109.7 % 120.1 % 3rd run 80.6 % 89.7 % 100.4 % 110.6 % 119.4 % 4th run 80.0 % 89.3 % 99.1 % 110.5 % 120.7 % 5th run 80.4 % 90.5 % 99.9 % 109.1 % 119.2 % Test 1 Test 2 1st run 99.3 % 99.6 % 2nd run 100.8 % 98.9 % 3rd run 100.4 % 100.5 % 4th run 99.1 % 99.7 % 5th run 99.9 % 99.2 % 13 LINEARITY The linearity of an analytical procedure is its ability (within a given range) to obtain test results which are directly proportional to the concentration (amount) of analyte in the sample. For those analytical procedures which are not linear, another mathematical relationship (proportionality) must be demonstrated. [Determination] The linearity is determined by calculating a regression line by the method of least squares of test results versus analyte concentrations. Five points in the range of standard value±20% for an assay method and in the range from 20% of target concentration down to the limit of quantitation of the drug substance or impurity for an assay/impurities combination method based on area % (for impurities) are recommended. It is often combined with accuracy, precision and range, and carried out as a single study. Under most circumstances, regression coefficient (r) is 0.999. Intercept and slope should be indicated.

Linearity test for acetylsalicylic acid Conc. 80% 90% 100% 110% 120% 1st run 79.2 90.8 99.3 109.0 120.9 2nd run 79.7 90.2 100.8 109.7 120.1 3rd run 80.6 89.7 100.4 110.6 119.4 4th run 80.0 89.3 99.1 110.5 120.7 5th run 80.4 90.5 99.9 109.1 119.2 140.0 120.0 100.0 80.0 60.0 40.0 20.0 0.0 0% 20% 40% 60% 80% 100% 120% 140% 6 4 2 0 0 20 40 60 80 100 120 140 2 4 6 15 Evaluation of linearity for acetylsalicylic acid Regression coefficient :r = Slope : b = Σ{(x i Σx i /n) (y i Σy i /n)} {[Σ(x i Σx i /n)][σ(y i Σy i /n) 2 ]} 1/2 Σ{(x i Σx i /n) (y i Σy i /n)} Σ(x i Σx i /n) 2 Intercept : a = Σy i /n bσx i /n r = 0.999034, a = 0.124, b = 0.9984 More than 0.999 of regression coefficient is obtained. 16

ACCURACY The accuracy of an analytical procedure expresses the closeness of agreement between the value which is accepted either as a conventional true value or an accepted reference value and the value found. [Determination] Accuracy studies are performed, at least in triplicate, by the addition of known amounts of drug (80, 100 and 120% levels of label claim) to the placebo formulation working in the linear range of detection of the analyte. The mean of the replicates, expressed as % label claim, is an estimate of accuracy. It is often combined with precision, linearity and range, and carried out as a single study. Accuracy Method After the results of 5 level concentration, 5 numbers repeat was normalized, it is calculated with the accuracy and 95% confidence interval of their variance by 1Dvariance analysis. Variance analysis Factor Square sum Freedom Square mean Fvalue Sample S I = 0.300494 I ν= 4 V I = 0.075123 F= 0.16193 Erroer S e = 9.27852 e ν= 20 V e = 0.463926 Total S T = 9.57901 T ν = 24 S I = Σ(Σy i) 2 j /m (ΣΣy ij) 2 /n I ν= l 1 V I = S I/ν I F= V I/V e S e = S T S I e ν= T ν ν I V e = S e/ν e S T = ΣΣy 2 ij (ΣΣy ij) 2 /n T ν = lm 1 Trueness(each step) dj = Σ{yji(100/xj)}/m 100 d80 = 0.02500 d90 = 0.11111 d100 = 0.10000 d110 = 0.20000 d120 = 0.05000 Trueness( Total) d = ΣΣ{yij(100/xj)}/n 100 d = 0.03278 Confidence interval d 1.96(VI /n) 1/2 D d1.96(vi /n) 1/2 0.14022 D 0.074664] or d t0.025(l 1)(VI /n) 1/2 D dt0.025(l 1)(VI /n) 1/2 0.18495 D 0.11940 ( l = 5: step number m = 5: repeat number n = lm = 25: total number of analysis) It does not deviate as 0 is contained in confidence interval of accuracy. 18

PRECISION The precision of an analytical procedure expresses the closeness of agreement (degree of scatter) between a series of measurements obtained from multiple sampling of the same homogeneous sample under the prescribed conditions. Precision may be considered at three levels: Repeatability Intermediate Precision Reproducibility Reproducibility is not normally expected if intermediate precision is accomplished. Repeatability Repeatability expresses the precision under the same operating conditions over a short interval of time. Repeatability is also termed intraassay precision. Repeatability is considered at two levels: Injection Repeatability and Analysis Repeatability. Injection Repeatability Injection repeatability, expressed as the RSD, is determined by multiple injections of a homogeneous sample (prepared solution) under the analytical conditions. A minimum of 10 injections with an RSD of 1% is recommended. For low level impurities, higher variations may be acceptable. Analysis Repeatability Analysis repeatability, expressed as the RSD, is determined by multiple measurements of a sample by the same analyst under the same analytical conditions. It is often combined with accuracy, linearity and range, and carried out as a single study.

SCL10A::::::: SIL10A:::::: SAMPLE COOLER......... 0.0 LC10AD ::::::: 000 0 000 0 7 8 9 4 5 6 1 2 3 0 7 8 9 4 5 6 1 2 3 0 SPD10A ::::::: 000 0000 00000 0 7 8 9 4 5 6 1 2 3 CTO10A:::::: 000 0 0 LC10AD ::::::: 000 0 000 0 7 8 9 4 5 6 1 2 3 0 SCL10A::::::: SIL10A:::::: LC10AD ::::::: 000 0 000 0 7 8 9 4 5 6 1 2 3 0 7 8 9 4 5 6 1 2 3 0 SPD10A ::::::: 000 0000 00000 0 7 8 9 4 5 6 1 2 3 CTO10A:::::: 000 0 0 Repeatability Method After the results of 5 level concentration, 5 numbers repeat was normalized, it is calculated with the accuracy and 95% confidence interval of their variance by 1Dvariance analysis. Standard deviation( each level) sj = {Σ(yji Σyji/m) 2 /(m 1)} 1/2 Variance analysis Factor Square sum Freedom Square mean F value Sample SI = 0.300494 νi = 4 VI = 0.075123 F = 0.16193 Error Se = 9.27852 νe = 20 Ve = 0.463926 Total ST = 9.57901 νt = 24 SI = Σ(Σyi)j 2 /m (ΣΣyij) 2 /n νi = l 1 VI = SI/νI F = VI/Ve Se = ST SI νe = νt νi Ve = Se/νe ST = ΣΣyij 2 (ΣΣyij) 2 /n νt = lm 1 s80 = 0.558570 s90 = 0.604152 s100 = 0.717635 s110 = 0.752994 s120 = 0.756968 Relative standard deviation( each level) RSDj = sj/(σyji/m) RSD80 = 0.70 (%) RSD90 = 0.67 (%) RSD100 = 0.72 (%) RSD110 = 0.69 (%) RSD120 = 0.63 (%) Standrd deviation( total) s = Ve 1/2 s = 0.681121 Confidence interval Se /χ 2 0.025(n l) σ 2 Se /χ 2 0.975(n l) 0.271543 σ 0.967441 ( l = 5: level, m = 5: repeat n = lm = 25: total number of analysis) 21 Intermediate precision Intermediate precision expresses withinlaboratories variations: different days, different analysis, different equipment. [Determination] Intermediate precision, expressed as the RSD, is determined by multiple measurements, as a minimum, for two separate occasions. It is often combined with accuracy, linearity and range, and carried out as a single study.

Intermediate precision Method To use two analytical results, the difference of population mean and 95% confidence interval of the ratio of population variance. mean( each test) Avej = Σyji/mj Ave1 = 99.90 Ave2 = 99.58 standard deviation( each test) sj = {Σ(yji Σyji/mj) 2 /(mj 1)} 1/2 s1 = 0.717635 s2 = 0.605805 relative standard deviation( each test) RSDj = sj/(σyji/mj) RSD1 = 0.72 (%) RSD2 = 0.61 (%) ( m = 5: Repeat number of Test1 n = 5: Repeat number of Test2) Degree of freedom ν = (s1 2 /m1s2 2 /m2) 2 /{(s1 2 /m1) 2 /(m1 1)(s2 2 /m2) 2 /(m2 1)} ν = 4.0 ν* = 4 Difference of population mean d = Σy1i/m1 Σy2i/m2 d = 0.32 Confidence of difference of population mean d t0.025(ν*)(s1 2 /m1s2 2 /m2) 1/2 D d t0.025(ν*)(s1 2 /m1s2 2 /m2) 1/2 0.84592 D 1.48592 Variance ratio F = s1 2 /s2 2 F = 1.4033 Confidence interval of variance ratio F0.975(m1 1, m2 1)s2 2 /s1 2 F F0.025(m1 1, m2 1)s2 2 /s1 2 0.074193 F 6.8447 It does not signify as 0 is contained in the confidence interval of difference of population mean and 1 is contained in the confidence in the ratio of population variance. 23 Validation example(3) Test Limitation test of impurities in acetylsalicylic acid drug using HPLC Evaluation of Parameters Specificity Limit of detection Data 5 level (lower) concentration sample, 5 number of repeat Conc. 0.04 % 0.06 % 0.08 % 0.10 % 1.20 % 1st run 3551 4446 6182 7963 9405 2nd run 3282 5089 6294 8154 9226 3rd run 3013 5050 6418 8078 9084 4th run 3635 4907 6793 7668 9780 5th run 3119 4686 6109 7525 9591 24

LIMIT OF DETECTION The limit of detection of an individual analytical procedure is the lowest amount of analyte in a sample which can be detected but not necessarily quantitated as an exact value. [Determination] The limit of detection may be determined from the signaltonoise ratio (S/N) by comparing test results from samples with known concentrations of analyte with those of blank samples and by establishing the minimum concentration at which the analyte can be reliably detected. S/N 3:1 is generally accepted. Standard deviation and slope of calibration curve method Limit of detection Method The slope for regression curve and standard deviation were calculated by regression analysis using the results of 5 concentration,5times repeats. Then the limit of quantitation was calculated from these results. SD of redisual sy/x = {Σ{yi (bxia)} 2 /(n 2)} 1/2 sy/x = 252.857 SD of y intercept sy = sy/x{(σxi 2 /nσ(xi Σxi/n) 2 } 1/2 sy = 151.7139 or SD of y intercept sy = sy/x{11/n(σxi/n) 2 /Σ(xi Σxi/n) 2 } 1/2 sy = 294.879 Limit of detection DL = 3.3s y/x/a DL = 0.011 (%) ( From SD of redisual) or DL = 0.0066 (%) ( From SD of y intercept) or DL = 0.013 (%) ( From SD of y intercept) ( a = 76182: Slope of regression curve b = 267.36: y intercept n = 25: total number of analysis) 26

Signal to Noise ratio Limit of detection : S/N= 3 Limit of quantitation : S/N=10 Signal to Noise ratio 50ppm : S/N=200mm/1mm=200? ppm : S/N=2 Concentration=50 ppm (N = 1mm) (S = 200mm)? =0.5ppm

Standard deviation and slope of calibration curve method Limit of detection : 3.3 σ/s Limit of quantitation : 10 σ/s σ : standard deviation of response signal S : slope value of calibration curve σ slope [resp.] [conc.] Limit of Detection test for acetylsalicylic acid Conc. 0.04% 0.06% 0.08% 0.10% 1.20% 1st run 3551 4446 6182 7963 9405 2nd run 3282 5089 6294 8154 9226 3rd run 3013 5050 6418 8078 9084 4th run 3635 4907 6793 7668 9780 5th run 3119 4686 6109 7525 9591 s y/x = {Σ(y i (bx i a)} 2 /(n2)} 1/2 = 252.857 a = 76182 : slop of regression line b = 267.36 : y intercept n = 25 : total run number DL = 3.3s y/x /a = 0.011(%) 30

Validation example(4) Test Quantitative test of salicylic acid which is impurity, in acetylsalicylic acid raw drug using HPLC Evaluation of Parameters Data Specificity Accuracy Repeatability Intermediate precision Limit of quantitation Linearity Range 5 concentration level(50%~120%) sample, 5 times repeat. Conc 0.04 % 0.06 % 0.08 % 0.10 % 1.20 % 1st run 2454 3300 4316 5401 6791 2nd run 2538 3762 4496 5825 6488 3rd run 2081 3859 4581 5739 6560 4th run 2669 3504 4852 5334 6943 5th run 2312 3697 4378 5518 7005 31 LIMIT OF QUANTITATION The limit of quantitation of an individual analytical procedure is the lowest amount of analyte in a sample which can be quantitatively determined with suitable precision and accuracy. [Determination] The limit of quantitation may be determined from the signaltonoise ratio (S/N) by comparing test results from samples with known concentrations of analyte with those of blank samples and by establishing the minimum concentration at which the analyte can be detected with suitable precision and accuracy. S/N 10:1 is generally accepted.

Limit of quantitation Method The slope for regression curve and standard deviation were calculated by regression analysis using the results of 5 concentration,5times repeats. Then the limit of quantitation was calculated from these results. Standard deviation sy/x = {Σ{yi (bxia)} 2 /(n 2)} 1/2 Quantitative limit QL = 10 sy/x/a sy/x = 218.097 DL = 0.041 (%) ( From SD of redisual) or Standard deviation of y intercept sy = sy/x{(σxi 2 /nσ(xi Σxi/n) 2 } 1/2 DL = 0.025 (%) ( From SD of y intercept) sy = 130.858 or Standard deviation of y intercept sy = sy/x{11/n(σxi/n) 2 /Σ(xi Σxi/n) 2 } 1/2 or DL = 0.048 (%) ( From SD of y intercept) sy = 254.343 ( a = 53161: Slope of regression line b = 323.24: y intercept n = 25: Total number of analysis) 33 Quantitation Limit test for salicylic acid as a impurity Conc. 0.04% 0.06% 0.08% 0.10% 1.20% 1st run 2454 3300 4316 5401 6791 2nd run 2538 2762 4496 5825 6488 3rd run 2081 3859 4581 5739 6560 4th run 2669 3504 4852 5334 6943 5th run 2312 3697 4378 5518 7005 s y/x = {Σ(y i (bx i a)} 2 /(n2)} 1/2 = 218.097 a = 53161 : slop of regression line b = 323.24 : y intercept n = 25 : total run number DL = 10s y/x /a = 0.041(%) 34

RANGE The range of an analytical procedure is the interval between the upper and lower concentration (amounts) of analyte in the sample (including these concentrations) for which it has been demonstrated that the analytical procedure has a suitable level of precision, accuracy and linearity. [Determination] The range is validated by verifying that the analytical procedure provides acceptable precision, accuracy and linearity when applied to samples containing analyte at the extremes of the range as well as within the range. The recommended range is NLT±20% for an assay method and is20% of target concentration down to the limit of quantitation of the drug substance or impurity for an assay/impurities combination method based on area % (for imputies). It is often combined with accuracy, precision and linearity, and carried out as a single study. REFERRENCE STANDARDS A reference standard is a highly purified compound that is well characterized. USP/NF reference standard that does not need characterization. Noncompendial standard that should be of the highest purity that can be obtained by reasonable effort and should be thoroughly characterized to assure its identity, strength, quality and purity. The working concentration is the target concentration of the compound of interest. Keeping the concentrations of the sample and the standard close to each other for the external standard method improves the accuracy of the method. Include the purity correction factor, if known, of the reference standard in the calculation. State the working concentrations of the standard and sample in the method.

OTHER VALIDATION CHARACTERISTICS Recovery Recovery is expressed as the amount/weight of the compound of interest analyzed as a percentage to the theoretical amount present in the medium. Accuracy may be expressed as percent recovery by the assay of known, added amounts of analyte. Sample Solution Stability Solution stability of the drug substance or drug product after preparation according to the test method should be evaluated. Data to support the sample solution stability under normal laboratory conditions for the duration of the test procedure, e.g., 24 hours, should be generated. Robustness The robustness of an analytical procedure is a measure of its capacity to remain unaffected by small, but deliberate variations in method parameters and provides an indication of its reliability during normal usage. Testing varying some or all conditions, e.g., age of columns, column type, column temperature, ph of buffer in mobile phase, reagents, is normally performed. SYSTEM SUITABILITY TESTS System suitability is an integral part of many analytical procedures. The tests are based on the concept, that the equipment, electronics, analytical operations and samples to be analyzed constitute an integral system that can be evaluated as such. [ System Suitability Parameters ] [ System Suitability Parameters ] Capacity Factor ( k' ) Precision/Injection Repeatability ( RSD ) Relative Retention (α) Resolution ( Rs ) Tailing Factor ( T ) Theoretical Plate Number ( N )

SYSTEM SUITABILITY PARAMETERS [Determination and Standards of Parameters] Capacity Factors ( k' ) k' = (t R t 0 ) /t 0 k'>2 Precision/Injection Repeatability ( RSD ) n 5 RSD 1% Relative Retention (α ) t α = k' 1 / k' 0 2 There is not an essential parameter as long as the resolution( Rs ) is stated. Resolution ( Rs ) Rs = (t R2 t R1 ) / (1/2)(t W1 t W2 ) Rs 2 Tailing Factor ( T ) T = Wx / 2f T 2 Theoretical Plate Number ( N ) N =16(t R /t W ) 2 = L/H N>2000 Injection Air peak t R1 Solvent peak f Solvent tail t R2 Wx t W1 t W2 0.05h h Thank you 40