STRUCTURE OF CHEMICAL COMPOUNDS, METHODS OF ANALYSIS AND PROCESS CONTROL

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1 Pharmaceutical Chemistry Journal Vol. 38, No. 4, 004 STRUCTURE OF CHEMICAL COMPOUNDS, METHODS OF ANALYSIS AND PROCESS CONTROL VALIDATION OF HPLC TECHNIQUES FOR PHARMACEUTICAL ANALYSIS N. A. Épshtein 1 Translated from Khimiko-Farmatsevticheskii Zhurnal, Vol. 38, No. 4, pp , April, 004. Original article submitted June 18, Akrikhin Chemico-Pharmaceutical Joint-Stock Company, Staraya Kupavna, Moscow Region, Russia. Here and below the terms accuracy and precision (repeatability, reproducibility) are treated in accordance with the State Standard GOST R ISO Previously, accuracy had the meaning of correctness, but now correctness is described in terms of trueness. In justifying the suitability of techniques related to the qualitative determination of substances, statistical processing of the experimental results is obligatory [8]. Validation (evaluation of suitability) of an analytical technique is a procedure aimed at obtaining experimentally justified evidence of the ability of this technique to give results characterized by the required accuracy and precision [1 7]. All analytical techniques used for the development of pharmaceuticals and for the determination of their quality characteristics have to be validated. In the case of using methods stipulated and described in the State Pharmacopoeia, it is not necessary to evaluate their suitability, provided that the analyses are conducted with strict observation of the text of each particular article. In most other cases, especially in cases of modification of the drug composition, the scheme of synthesis, or the analytical procedure, it is necessary to re-evaluate the suitability of the analytical techniques. This paper is aimed at (i) considering the peculiarities of validation of HPLC techniques for pharmaceutical analysis, (ii) critically assessing the main approaches to evaluation of the validation characteristics, and (iii) providing practical recommendations and criteria for finding correct solutions. The USSR State Pharmacopoeia (valid in the Russian Federation) introduced the section Statistical Analysis of Biological Test Results in 1968 (Xth Ed.) and the section Statistical Processing of Chemical Experimental Data in 1988 (XIth Ed.). These sections are devoted to problems involved in the metrological attestation of analytical techniques. In 1987, the United States Food and Drug Administration (FDA) issued practical guides on the main principles of validation [5] and on the presentation of samples and analytical data pertaining to the validation of methods [6]. In 1993, the International Conference on Harmonization (ICH) developed generalized recommendations on the validation of analytical procedures; these documents were published in 1994 and treated in more detail in 1995 [1 3]. In 1994, the US FDA Center for Drug Evaluation and Research (CDER) issued a guide on the validation of chromatographic methods [4]. These documents and some review papers and monographs [9 13] provided a basis for extensive implementation of the procedure of validation of analytical methods. The Internet offers the Laboratory Guide to Method Validation and Related Topics at /. In recent years, new guides have become available from CDER [15], Waters Company [16], and Labcompliance [17 19]. Special sections are devoted to these problems in national and international pharmacopoeias and guides on the validation of analytical procedures [7, 0 ]. Also available are computer program packages, such as ELISA Method Validation Templates (Waters) and LaChrom 000 Validation Manager (Merck) representing electronic tables with incorporated functions of statistical processing of the results of measurements and issuing validation certificates, and monographs on the related subjects [3 34]. Tables 1 and summarize the most recent recommendations concerning selection of the validation characteristics depending on the type of analytical procedures. A comparative analysis of these data shows that, according to the United States Pharmacopoeia (USP-6), methods of dissolution testing have to be validated only with respect to precision (repeatability, reproducibility), while the other characteristics may require validation, depending on the specific test nature. In contrast, according to the FDA CDER guidelines [15], procedures used for quantitative analysis and dissolution testing need the same validation characteristics X/04/ Plenum Publishing Corporation

2 Validation of HPLC Techniques for Pharmaceutical Analysis 13 Moreover, according to CDER [15], all methods of quantitative analysis have to be characterized with respect to robustness (see below). Robustness is not included in USP-6 [7] because this characteristic has to be studied at the stage of development of an analytical procedure, rather than in the course of validation. Since any analytical situation poses a multifactor problem, validation has to include at least testing of the analytical system as a whole under the conditions stipulated by the description. 3 The second task is evaluation of the stability (robustness) of the analytical system with respect to small variations of the main factors (for example, the ratio of the mobile phase components, ph, temperature, etc.). This problem is less important than the first one because it is usually solved at the stage of development of a given analytical procedure. For this reason, problems pertaining to robustness are only briefly mentioned in this review. Let us consider the main stages of validation of the HPLC techniques used in pharmacy. 1. TESTING THE ANALYTICAL PROCEDURE AS A UNIFIED SYSTEM UNDER THE CONDITIONS STIPULATED IN THE DESCRIPTION 3 According to this concept, instrumentation, electronics, analytical procedures, and analyzed samples constitute a unified analytical system, which can be considered as a whole [7]. 4 Sometimes, the stability of phases and solutions is considered within the framework of the problem of robustness. Specificity (Section 1.1). Precision (Section 1.).1 Repeatability (Section 1..1). Intermediate precision (Section 1..) 3. Linearity (Section 1.3) 4. Accuracy (Section 1.4) 5. Suitability range (Section 1.5) 6. Limit of detection (Section 1.6) 7. Limit of quantitation (Section 1.7) 8. Stability of solutions (Section 1.8.) 9. Robustness (stability) of HPLC procedures with respect to small variations in the main system factors (ratio of the mobile phase components, ph, temperature, etc.). Robustness is usually studied in the stage of development of the given HPLC tecnique (Section ) Recommended requirements to the repeatability of sample injections (Section 3.3).3 Reproducibility. Checked in special cases (Section 1..3) It is expedient to determine these validation characteristics in the course of proof of the analytical system accuracy (using statistical parameters determined for the calibration graph) (Sections 1.3; 1.4; 1.6.; and 1.7.) Criteria of suitability of a given chromatographic system (Section 3) Fig. 1. The general scheme of validation of HPLC-based analytical procedures. Figure 1 shows the general scheme of evaluation of the suitability of an analytical procedure, which takes into account specific features of HPLC. As can be seen, testing an analytical procedure as a whole in the general case allows the following validation characteristics to be determined [1 7]: (i) specificity; (ii) precision; (iii) linearity; (iv) accuracy; (v) suitability range; (vi) limit of detection; (vii) limit of quantitation; and (viii) stability of solutions. 4 Depending on a particular type of the analytical procedure (HPLC technique) only a part rather than all of the above characteristics may be required (see Tables 1 and ) Confirming the Specificity of a Given Analytical Procedure (Separating Power of a Chromatographic System) By the specificity of a system is meant its ability to detect a given substance unambiguously (reliably) in the presence of other components (including impurities) that may be present in the samples [1 4]. The proof of specificity depends on the task of a given procedure and on the availability of reference samples of the main impurities The specificity of procedures aimed at determination of the content of a parent substance, the parameters of solubility, and the homogeneity of dosage. In order to confirm the specificity of these procedures, it is usually required that peaks of the substances to be determined are sufficiently well resolved between themselves and from peaks of the main impurities, the system components (e.g., of the sample solvent), and the placebo. For this purpose, the separation of peaks is confirmed by a set of chromatograms, at least of (a) the test solution, (b) the reference parent substance solution, (c) the solvent (blank), (d) the placebo (for filled drugs), and (e) the solution used for the evaluation of suitability of the chromatographic system. The degree of peak separation is usually described in terms of the separation coefficient R s. Recommended values of this coefficient are given below in the Section 3.3. It is recommended to confirm the specificity by investigation of the purity of peaks of the parent substance to be determined [4, 7]. This test is usually performed using a diode matrix detector and a special program evaluating spectral homogeneity of the measured peak (e.g., Peak Purity Millennium, Waters). The principle of evaluation of the peak purity is as follows. The sample chromatograms are measured at various detector wavelengths (numbered n ). Each point of the peak is characterized by a spectrum, which is mathematically described by a vector in the n-dimensional space of the values of absorption (in absorption units, AU) at the preset n wavelengths (the length of this vector is proportional to the substance concentration in the solution studied). The difference between the spectra is evaluated by the angle between the corresponding vectors (called the spectral con-

3 14 N. A. Épshtein TABLE 1. Validation Characteristics according to th United States Pharmacopoeia (003) Characteristic I II Category Quantitative tests Limiting tests Accuracy Yes Yes MB MB No Precision Yes Yes No Yes No Specificity Yes Yes Yes MB Yes Limit of detection No No Yes MB No Limit of quantitation No Yes No MB No Linearity Yes Yes No MB No Suitability range Yes Yes MB MB No Notes: Yes = usually studied; No = usually not studied; MB = may be required (depending on a specific test nature). Category I includes analytical methods intended for determination of the content of the main component in parent substances or ready-to-use medicinal forms; category II includes methods of determination of impurities and decomposition products; category III includes methods of determination of the parameters of dissolution, drug release, etc.; category IV includes identification tests; the terms accuracy and precision (repeatability, reproducibility) are treated in accordance with the State Standard GOST R ISO III IV TABLE. Validation Characteristics Recommended for Various Tests by the United States FDA (CDER and CBER) [15] Chatacteristic Identification Type of analytical procedure Tests for impurities quantitative limiting Qualitative determination and dissolution tests Accuracy No Yes No Yes Repeatability No Yes No Yes Intermediate precision No Yes 1 No Yes 1 Specificity Yes Yes Yes Yes 4 Limit of detection No No 3 Yes No Limit of quantitation No Yes No No Linearity No Yes No Yes Suitability range No Yes No Yes Robustness No Yes No 3 Yes Notes: Yes = usually studied; No = usually not studied; 1 in cases where the reproducibility is studied, there is no need to specially determine the intermediate precision; insufficient specificity of a given analytical procedure can be compensated by introducing additional tests; 3 may be required in some cases (e.g., when the limit of detection is close to the rated limiting content of an impurity); 4 insufficient specificity of a given analytical procedure can be compensated by determining the content of impurities. trast angle ). If = 0, the spectra are considered similar (homogeneous). This implies that the value of absorption in one spectrum measured at a given wavelength can be obtained from the value in another spectrum measured at the same wavelength by multiplying by a certain constant factor. In order to evaluate the spectral homogeneity of a chromatographic peak, the spectral contrast angles are calculated for all points of this peak relative to the angle at the peak maximum and then the maximum value p (purity angle) is determined. Two spectra determined for the same substance can differ, for example, because of the influence of the baseline noise. In order to take this into account, a threshold spectral angle th is determined (i) by determining the maximum spectral angle between pints of the baseline with maximum noise levels or (ii) by taking six chromatograms of a standard sample solution, determining the maximum purity angle p for each chromatogram, and considering the maximum of these values as the threshold spectral angle th. This threshold angle characterizes the level below which the difference between two spectra can be considered insignificant. The obtained p values are compared to th. For p < th, the peak is considered spectrally homogeneous; otherwise the peak is influenced by the presence (i.e., additional absorption) of another substance. In practice, it is possible to use a simplified procedure, whereby the chromatograms of the same peak are measured at two or three wavelengths and the chromatograms are checked for the proportionality (see above) at all points. The latter method is less reliable, because the spectrum can be influenced by variations in the mobile phase composition (e.g., under gradient HPLC conditions), or by deviations from the Lambert Beer law at high levels of absorption. Therefore, negative results of evaluation of the spectral homogeneity of peaks in the gradient HPLC should be critically assessed and checked for optical densities not exceeding 1 AU. It should be noted that specificity is rarely checked using chromatomass spectroscopy (HPLC MS) because of the high cost of this procedure and the chemical and other analyses of the eluate fractions corresponding to the parent substance, because of tedious procedures The specificity of procedures aimed at determination of impurities. In evaluating the specificity of such procedures, it is necessary to differentiate between two cases. Case 1. The main impurities are known and available. In order to confirm the specificity of a procedure used for determining the impurities in a parent substance, it is necessary to show that (i) this procedure allows the peaks of the main products of decomposition of the parent substance to be detected and that (ii) the peaks of impurities are sufficiently well separated between themselves and from peaks of the parent substance and the system components (solvents). Developers of the technology of a parent substance have to prove additionally that (iii) the proposed procedure allows determining the main impurities related to the technological process and that (iv) all such impurities present at an amount of 0.1% are identified [7].

4 Validation of HPLC Techniques for Pharmaceutical Analysis 15 In order to confirm the specificity of a procedure used for determining impurities in parent substances, it is necessary to demonstrate that (i) this procedure allows the peaks of the main rated impurities to be detected and that (ii) the peaks of these impurities are sufficiently well separated between themselves and from peaks of the parent substance and the system components (solvents). The specificity is confirmed by a set of chromatograms, including at least those of (a) a model solution of the parent substance and the main impurities (prepared by adding these known impurities or their solutions to the parent compound or its mixture with the placebo), (b) the solvent, (c) the placebo (for filled drugs), (d) the test solution, and (e) the solution used for the evaluation of suitability of the chromatographic system. In addition, it is recommended to confirm the specificity of the given analytical procedure by data on the purity of the main peaks in the chromatograms of test solutions. Case. The main impurities are unknown (unidentified) or absent. In this case, it is expedient to use special experiments involving modification of the parent compound (sometimes called stress testing [, 15, 7]), whereby a solution of the given drug (or of the parent compound) is subjected to factors leading to its partial destruction with the formation of related identifiable compounds. The degree of decomposition can be readily determined from the decrease in the area of the main peak in the chromatogram of the final solution relative to that in the initial solution. The specificity of the given analytical procedure is judged by separation of the peaks of impurities between themselves and from the peak of the main component and by the peak purity of the parent compound. In particular, the specificity of HPLC procedures can be proved using the following methods of chemical modification. (i) Hydrolysis with 0.1 N solutions of HCl or NaOH at room temperature or at elevated temperatures. Example: a granulate was treated with 0.1 N HCl solution for 5 h at 60 C, after which the sample was extracted according to the proposed procedure and analyzed by HPLC. (ii) Oxidation with a 3% hydrogen peroxide solution, 0.05 M iodine solution, etc. Example: captopril was partly oxidized with 0.05 M iodine solution (in order to obtain captopril disulfide the main technological impurity []), extracted according to the proposed procedure, and analyzed by HPLC. (iii) Thermal decomposition by heating to C. Example: a granulate was kept for 7 days at 80 C. The resulting solid products of decomposition can be stored and used as control substances in the tests for suitability of a chromatographic system. (iv) Photochemical decomposition under illumination (e.g., UV irradiation). (v) Chemical addition reactions, for example, drug bromination at multiple bonds. A mixture of the initial substance and the products of its chemical modification can be used for preparing solutions used for the evaluation of suitability of the chromatographic system. The duration of action used for the chemical modification of drugs is selected taking into account the following factors. (i) The peaks of the products of drug modification are to be clearly distinguishable in the chromatogram. Therefore, the treatment duration must be sufficient to provide for a not less than 10% decrease in the main peak height (area), which is proportional to the drug content. (ii) The peaks of the products of drug modification have to be sufficiently well separated from the main peak, but the main peak height (area) must be comparable with that in the initial test solution. According to [7], it is recommended that the main peak intensity would decrease by no more than 30%. However, this requirement is not as critical, since the stronger decomposition of the parent compound can be compensated by adding it in the necessary amount. (iii) It is desired that the percentage content of the products of drug modification determined by the method of internal normalization would be close to the level of maximum permissible content of a single impurity. Further steps in the proof of specificity of the analytical procedure in the case under consideration are the same as in case 1. The validation characteristics additionally include chromatograms obtained in the course of experiments on the chemical modification of the parent compound. Data presentation. The proof of the specificity of an analytical procedure is presented in the form of a set of chromatograms (see above) with discussion of the obtained results. These data are supplemented by the results of calculation of (i) the separation coefficient R s for two peaks of the most closely spaced components, (ii) the column efficiency N, and (iii) the asymmetry parameters (tailing factors) of the main analytical peaks. It is necessary to make the following remark. Solving the problem of detection and separation of impurities by HPLC is still an art, with the results depending on the skill of developers. It is very important to select the optimum chromatographic columns and mobile phases. Moreover, it is known that, depending on the column loading, it is possible (a) to observe no additional peaks of impurities, (b) to find a certain number of such peaks, a part of which cannot be quantitatively characterized, or (c) to reveal a very large number of additional measurable peaks upon overloading the column with respect to the main drug component. Therefore, in developing and validating the methods of impurity determination (especially in the case of parent compounds), it is expedient to check for the possible presence of additional peaks (i.e., impurities) by chromatography of drug solutions with elevated concentrations providing overloading of the column with respect to the main component. However, this approach is usually inapplicable in the case of ready-to-use drugs containing large amounts of auxiliary substances.

5 16 N. A. Épshtein 1.. Confirming the Precision of a Given Analytical Procedure The precision (repeatability, reproducibility) of an analytical procedure characterizes the random scatter (variation) of the results relative to the mean value. It should be emphasized that, in order to obtain reliable results, the sample must have a homogeneous composition. The results have to be statistically treated. Variants leading to rough errors (e.g., using variation range R or the three sigma rule [8]) should be rejected. In evaluating the suitability of HPLC procedures (actually, in determining the metrological characteristics), it is necessary to use measuring vessels of class A or special calibrated measuring vessels and take all other possible measures to increase the reproducibility and accuracy of HPLC measurements [7]. The precision (repeatability, reproducibility) of an analytical procedure is evaluated in terms of the standard deviation (SD) of the relative standard deviation (percentage RSD) determined in a series of measurements and calculated by the formulas m SD ( X i X) ( m1 ), i1 SD RSD(%) 100. (1) X According to the ICH recommendations [4] on the validation of chromatographic procedures, the characteristics of precision are considered at three levels: repeatability, intermediate precision, and reproducibility (Table 3). In [4, 7] and in many other papers, the set of validation characteristics of HPLC procedures includes the injection repeatability. However, the author believes that this is incorrect: this parameter characterizes the quality of injector (e.g., syringe) rather than the suitability of a proposed procedure. TABLE 3. Main Precision Characteristics for the Validation of HPLC Procedures According to ICH [4] Precision characteristic Conditions of determination Repeatability (Rt ) Intermediate precision (Ip ) Reproducibility (Rp ) Injection repeatability Determined for the same sample preparation by the same analyst using the same instrument (chromatograph) during a short period of time Intra-assay precision Determined for the same sample preparation by different analysts using various instruments (chromatographs) during a prolonged period of time (not less than two days) The same, in various laboratories This characteristic is not included in the list of CDER [15] and USP-6 [7]. In HPLC validation, data on the injection repeatability should be provided as additional material required in cases of search for the bottleneck of a proposed method (dispersion analysis) Injection repeatability and intra-assay precision. In the general case, repeatability (R p ) characterizes the reproducibility of a given analytical procedure for the same sample preparation, as performed by the same analyst using the same instrument (chromatograph) during a relatively short period of time. For evaluating the repeatability in a given laboratory, the same analyst prepares samples of a model mixture or the same batch of a parent compound or a drug: (a) not less that nine samples of solutions covering the rated range of concentrations. For example: a homogenized powder of triturated tablets from the same batch is used to prepare drug solutions with concentrations equal to 50, 100, and 150% of the reference sample solution concentration according to the proposed procedure, or (b) not less than six samples of solutions in the region of concentrations close to the nominal value. For example: a homogenized powder of a parent compound or triturated tablets from the same batch is used to prepare six solutions with nominal concentration according to the proposed procedure. Note that each sample solution is (i) prepared independently of the other solutions and (ii) chromatographed at least three times. Each solution is characterized by the drug content X i (i =1,,N ), the average value X X i N, the standard deviation SD, the relative standard deviation RSD of particular measurements, and the confidence interval (for P = 95%) of the average value. It is required to show that the average results are statistically equivalent (e.g., in terms of the Student t-criterion) or, which is more convenient for the practical analysis, that RSD 1.0% for determination of parent compounds, RSD.0% for drugs, or RSD 10.0% for impurities [13, 7] Intermediate precision. This value characterizes the reproducibility of results obtained in the same laboratory by different analysts using various instruments (chromatographs) during a prolonged period of time (not less than two days) for the same homogeneous sample or a model drug mixture according to the proposed analytical procedure. Typically, not less than six solutions are prepared with concentrations close to the nominal value (see the preceding section). Each sample solution is (i) prepared independently of the other solutions and (ii) chromatographed at least three times. 5 For small values of the standard deviation (SD << 1), the t-criterion may give statistically significant differences even for close (almost identical) values of the compared average concentrations. This is related to the fact that this criterion is proportional to the ratio of systematic and random errors.

6 Validation of HPLC Techniques for Pharmaceutical Analysis 17 These solutions are characterized by the average drug content according to the results obtained by each of the analysts, X i and X j (i, j =1,,N ). These data are statistically processed and characterized by generalized average values X1 X i N and X X j N and the corresponding standard deviations (SD i, SD j ) and relative standard deviations (RSD i, RSD j ) of particular measurements. First, it is required to show that the proposed procedure of determination of the drug content and the impurity coincentraiton provides for the statistically equivalent standard deviations SDi and SD j of the results obtained by different analysts (in terms of the Fisher F-criterion). Then, it is necessary to demonstrate that the average results of these (for certainty, two) analysts are statistically reliably (P = 95%) identical in terms of the t-criterion calculated as t X 1 X X 1 X SD1 SD SD SD m m m 1 1, where X 1, X are the average results of analyses performed by analysts 1 and and SD 1,SD are the standard deviations in the particular series of m 1 and m parallel determinations (usually m 1 = m = m ). This t value is compared to tabulated values of the Student criterion t (P = 95%, f = m 1 + m ), where P = 95% is the confidence probability and f = m 1 + m is the number of degrees of freedom. If the calculated parameter t is lower than the tabulated value, the difference of average values can be considered as statistically insignificant with a 95% confidence probability. Otherwise, the average results differ to a greater extent than that admitted by random errors in both series [35]. In pactice, validation of the procedures of determination of the content of impurities is sometimes performed using a less strict method [13], by showing that the scatter (RSD) of the results of one analyst (characterized by a greater standard deviation (SD i or SD j ) relative to the average result of another analyst (with a lower SD i or SD j ) does not exceed a certain preset level, for example, so that RSD 10% for impurities with a rated content up to 1%, RSD 5% for an impurity content within 0.1 1%, and RSD 50% for an impurity level below 0.1%. It should be noted that, according to USP-6 [7], it is in most cases sufficient to determine only the repeatability for proper validation of an analytical procedure, while the intermediate precision and reproducibility characteristics should be determined for procedures included in the pharmacopoeial articles Reproducibility. This characteristic is determined by comparing the results obtained upon analysis of the same samples in different laboratories using a proposed analytical procedure. The necessary statistical methods are described in monograph [35, Chapter 8.4] and in the State Standard GOST R ISO It should be noted that for reliable evaluation of the statistical significance of the difference between the results obtained in such investigation, it is necessary that the round robin tests involve not less than five laborqtories [35]. In practice, however, the reproducibility is usually evaluated using two or three laboratories and characterized by less strict estimates. For example, validation of a procedure proposed for the quantitative determination of a parent compound is performed by demonstrating the statistical equivalence of the standard deviations SD i and SD j of the results obtained in different laboratories (in terms of the Fisher F-criterion). Then, it is demonstrated that the scatter (RSD) of the results of analyses in one laboratory (characterized by the maximum standard deviation (SD i or SD j ) relative to the average results of analyses in other laboratories (with lower SD i or SD j values) does not exceed a certain preset level [13]. The full-scale reproducibility of analytical procedures is rarely validated because (i) it is necessary to involve certified laboratories capable of reproducing the proposed procedure with high precision and (ii) this requires high organizational facilities and expenditures Confirming Linearity of the Response to Drug Concentration Linearity characterizes the ability of a proposed analytical procedure to give (within the suitability range) a response signal with the magnitude Y (e.g., peak height or area) directly proportional to the amount C (concentration) of a drug to be determined: Y = a + bc. According to ICH recommendations [3], the linearity in practice is first visually estimated from the linear appearance of the plot of Y versus C. Ifthe plot appears linear, this relation is studied by methods of regression analysis in terms of the linear equation Y = a + bc. For the analytical procedures for determining the content of a parent compound, CDER recommends establishing the criterion of linearity at a level of the correlation coefficient r not lower than [4]. However, even such a high level of correlation may be accompanied by significant deviations from linearity in the regions of high and low drug concentrations [13]. For this reason, ICH [3] recommends that the linearity be validated by a plot of the difference Y C showing deviations (residuals) of the calculated values y i = a + bc from the measured Y i values as the function of the concentration C i. The outbursts of the points (x i, y i ) relative to the regression model can be determined by calculating the parameter t using the formula [36] t SD 0 y Y i 1 ( Yi y) 1 N ( N 1) SD Here, y i and Y i are the calculated and experimentally measured values of the response, respectively; y = y i /N; N is the total number of experimental points (x i, y i ), and i y,

7 18 N. A. Épshtein ( yi Yi) SD 0 N ( yi y), SD y. N 1 The calculated t value is compared to tabulated values of the Student criterion t (P = 95%, f = N - ). If the calculated parameter is greater than the tabulated value, the given point can be considered as deviating from the adopted regression model with a 95% confidence probability. In practice, validation of the procedures of determination of the content of impurities with respect to linearity is sometimes performed proceeding from a correlation coefficient of r 0.98 [13]. According to our estimates, use of the calibration graphs with such correlation coefficients may lead to RSD values on the order of 0% and above. Therefore, it would be more correct to establish the criterion of linearity at least at the level of r The linearity should be validated based on the analysis of at least five solutions with various concentrations covering the entire suitability range of a proposed analytical procedure [35]. According to ICH recommendations [3], the linearity can be demonstrated directly by using the reference parent substance (dilutions of a standard solution) andor model artificial mixtures including components of the drug studied. The most adequate approach consists in taking thoroughly weighed aliquots of the drug components and preparing solutions according to the proposed procedure, since all operations of the analyst should correspond strictly to those stipulated in the description. In practice, however, an intermediate approach recommended by ICH [3] is frequently employed. According to this, solutions are partly prepared using weighed aliquots of the drug components and the other are obtained by diluting these stock solutions. It should be emphasized that the linearity of a proposed analytical procedure should be confirmed in the course of validation of the accuracy, which reduces expenditures and saves time. The usual procedures are as follows. (a) For the analysis of parent compounds, it is common practice to prepare a reference solution of the compound with a concentration at or above the upper limit of the expected concentration interval (suitability range of the proposed procedure). Then, a series of dilutions is prepared so as to cover the entire range. Each solution is studied in a series of two or three injections. (b) For the analysis of ready-to-use drugs, the linearity is frequently checked in the same way as for the parent compound (i.e., using solutions of the parent compound as described in (a)). However, it is incorrect to ignore the possibility that auxiliary components (placebo) may influence the results. Therefore, it is more correct to validate the linearity using model mixtures of the parent compound and placebo. (c) For the determination of impurities using the method of internal normalization of the peak areas or heights, it is possible to evaluate the linearity by preparing dilutions of the reference sample solution (with a concentration equivalent to the rated value) in the model impurity solution so as to obtain drug concentrations in the range from 0.05% (dilution by a factor of 000!) to.5%. Instead of making some dilutions, it is possible to use a proportional decrease in the volume of applied sample (which saves the mobile phase). Data presentation. The validation characteristics include (i) a regression equation of the S i = a + bc type (for example, S = C [mgml]), (ii) the correlation coefficient (e.g., r = ), and (iii) a plot visually confirming the linearity of relationship between S and C Confirming the Accuracy of a Given Analytical Procedure The accuracy characterizes the proximity of the experimental results, obtained using a proposed analytical procedure, to the true value in the entire suitability range of this procedure. The accuracy represents a combination of the random and systematic error. 6 In order to provide for accurate HPLC determinations, it is recommended to use standard solutions with concentrations close to within 10% of the test solution concentration. The accuracy of analytical procedures should be determined using homogeneous samples with exactly known concentrations of the compounds to be determined. For validation purposes a series of such solutions is prepared using the reference parent compound. According to ICH recommendations and USP-6 [1, 7, 15], the accuracy can be expressed both in the classical form, as the difference X between the average experimental value (X ) and the true value () with the corresponding confidence interval X, 7 ( X ) X, () and in an alternative (and more illustrative) form, in terms of the percentage recovery of the known amount of the compound to be determined, ( found content) R 100 %. (3) ( introduced content) The author believes that the content recovery testing should be preferred for evaluating the accuracy. This approach provides a more illustrative characteristic of the reliability of results obtained using a proposed analytical procedure and reveals the need for additional checks in the case of a significant systematic error (see below). On the other hand, the recovery defined by formula (3) incompletely characterizes the accuracy, since this quantity is also random and requires knowledge of the corresponding confidence interval. Thus, it is recommended to determine both the recovery R (%) and the confidence interval at a preset probability (P = 95%), representing the accuracy in a form analogous to expression (): R R. (4) Obviously, the proposed methods should not involve significant systematic errors. In the absence of systematic er- 6 Accordiong to the State Standard GOST R ISO the systematic error usually characterizes trueness. 7 The value of X characterizes random errors.

8 Validation of HPLC Techniques for Pharmaceutical Analysis 19 rors, the error is determined by the precision. Based on the permissible RSD values (see above), experimental experience, and analysis of the published data [13, 7], it is possible to draw the conclusion that there is no need to verify a proposed analytical procedure in the absence of a significant systematic error, provided that it is established that the recovery with allowance of the confidence interval does not fall outside the following limits: %, for the quantitative analysis of parent substances with a high rated content of the active component (98% and above); %, for the quantitative analysis of parent substances with a lower rated content of the active component (98% and below) and ready-to-use drugs; %, for the quantitative determination of impurities with a rated maximum content of up to 1%; 75 15%, for the quantitative determination of impurities with a rated maximum content from -0.1 to 1%; %, for the quantitative determination of impurities with a rated maximum content below 0.1% The procedure of accuracy evaluation. ICH recommends making three determinations (i.e., analyze three model mixtures) for three different concentrations. However, this approach does not allow the accuracy to be determined together with linearity and other validation characteristics. The author believes that the accuracy should be evaluated using not less than nine determinations at various concentrations covering the entire range of suitability of the proposed procedure. This provides for the possibility of determining this characteristic simultaneously with the calibration graph parameters and their statistical characteristics (for evaluating the linearity according to Section 1.3), the limit of quantitation (Section 1.7.), and the limit of detection (Section 1.6.). It should be emphasized that these determinations should include all stages of the proposed analytical procedure. For parent substances, the accuracy of analysis is usually determined by comparison to a reference sample. According to this, the reference sample (or a high-purity substance) is analyzed using the standard procedure and the results are compared to data in the certificate of the reference sample or to the results of analysis of the high-purity parent substance performed by an alternative method (e.g., titration) with known accuracy and precision. It is recommended that, for parent substances with a high rated content of the active component, the average recovery should be not less than % at each level [13]. For ready-to-use drugs, the accuracy is evaluated through the analysis of mixtures containing known amounts of the parent compounds and placebo; for the quantitative determination of impurities, this characteristic is determined by the analysis of such mixtures containing known amounts of these impurities. These analyses are performed using two principal methods. The method of recovery of a parent compound introduced into the placebo (matrix). This method, used for the analysis of drugs comprising mixtures of parent and auxiliary compounds, is based on determining the recovery of a known amount of the parent substance introduced into the placebo. The placebo is prepared separately and then introduced in a nominal (or proportional) amount into measuring flasks. Then, thoroughly weighed amounts of the parent compound or its concentrated solutions are added so that (upon filling the flasks to the marks) the sample concentrations would cover the entire expected suitability range of the proposed analytical procedure. For example, a parent compound can be introduced into a placebo solution at a level of 80, 100, and 10% of the nominal concentration indicated on the label (or the reference solution concentration). The method of standard additives. This method is generally analogous to that described above but is applied only when it is impossible to prepare a solution of placebo free from the parent compound or when this compound is present in the placebo in an unknown amount (e.g., in biological samples). In these cases, the reference sample of the parent compound is added at an amount of 50, 80, 100, 10, and 150% of its expected content in the analyzed solution. Using the proposed procedure, the amount of the parent compound is determined (found content) and compared to the known additive (introduced content). Alternatively, it is possible to compare the results of analyses performed using the proposed method and the data obtained for the same samples by validated alternative methods. For the validation of analytical procedures intended for the analysis of ready-to-use drugs, it is expedient to use the same reference substance for preparing both model mixtures and standard solutions. This eliminates errors related to the possible uncertainty of the composition indicated on the label of the reference sample and allows using commercial samples instead of special reference compounds. At a low concentration of the parent compound in the mixture (when it is impossible to add a thoroughly weighed amount of this compound), one may add a known amount of concentrated solution and then fill the measuring flask with a solvent stipulated by the proposed analytical procedure. For the quantitative determination of impurities, the accuracy of evaluation has certain peculiarities. In this case, the method of recovery of a parent compound introduced into the placebo and the method of standard additives have limited applicability because these validation procedures require large amounts of identified impurities. In this case, the accuracy is most frequently checked using the method described below. The method of internal normalization with or without response factors. According to this method, identified impurities are characterized by the response factors with respect to the parent compounds determined by the analytical procedure under consideration. These coefficients depend on the mobile phase composition and the analytical wavelength. For reproduction (or modification) of the analytical procedure, the detector wavelength is not changed, while the mobile phase composition can be corrected for the difference in the

9 0 N. A. Épshtein parameters of chromatographic columns. In the case of a considerable change in this composition (see Section 4), it is necessary to re-determine at least the values of the response factors. For determining unidentified and accidental impurities, these factors are conventionally taken equal to unity (assuming that the sensitivity for these impurities is the same as that for the parent compound). If the reference samples of impurities and decomposition products are unavailable, the validation has to be performed using alternative methods Testing for systematic error. The analytical procedure can be checked for the absence of systematic errors by one of the three methods considered below. Method based on the Student t-criterion without regression analysis [8]. Each sample (whose total number is N 5) with known values (introduced content) of the component to be determined is analyzed in m = 3 6 parallel determinations. The total data array is characterized by the dispersion (SD 0 ) and the Student criterion 8 x m t SD 0 This t value is compared to tabulated values of the Student criterion t (P, f = m 1). If the calculated parameter is greater than the tabulated value for P = 95% and f = m 1. t > t (P, f ), the results obtained using the proposed method can be considered as involving a systematic error. This error is calculated by the formula x 100 %. (5) The standard deviation SD 0 in a particular analysis is calculated using the set of all m parallel determinations performed for N (or g in the notation of [8]) samples. This allows the SD 0 value to be reduced and the sensitivity of determination of the systematic error to be increased with a simultaneous decrease in the confidence interval for the results of analysis, X = t SD 0 m, where t is the Student criterion for f = m 1 degrees of freedom. The algorithm of these calculations is as follows. Each k th sample is characterized by the deviation of the experimental value from average, di X i X, and the dispersion m SD k d i ( m 1). Then, the difference between the i1 maximum and minimum values of the dispersion SD k is checked to be insignificant in terms of the Fisher F-criterion. If this difference is actually insignificant, the SD 0 value is calculated as the sum of square deviations for all samples divided by the number of samples, 8 This t value is essentially the ratio of the systematic error x and the random error SD 0 m. SD 0 N SD k 1 N Finally, the Student t-criterion is calculated as k. t ( x m) SD 0 (6) and compared to tabulated values of the Student criterion t (P, f ) for f = N(m 1) degrees of freedom. It should be emphasized that, for small (practically insignificant) systematic error and small random error, the calculated t-criterion can be greater than the tabulated value. However, a small systematic error can be ignored in practice when the analytical problem does not require high accuracy of determination. This approach is also valid for other methods of evaluation of the accuracy of a proposed analytical procedure. Method of regression analysis with the Student t-criterion [35, 38]. This method seems to be the most effective, since it provides for the possibility of using the calibration graph for the accuracy evaluation and determination of some other validation characteristics (see the generalized scheme in Fig. 1). For simultaneous determination of the constant and variable systematic errors, not less than N = 5 samples with known values of the parent compound are studied and the relationship between the introduced content (m t ) and the found content (m f ) is processed by least squares in terms of the equation m f = a + bm i. Using these data, the parameters t a = a SD 0 and t b = 1 bsd 0 are calculated and compared to the critical (tabulated) values of the Student criterion t (P, f ) for the confidence probability P = 95% and f = N degrees of freedom. Using the results of regression analysis, it is possible to judge with 95% probability about the absence of a constant systematic error, provided that t a t (P, f = N ), and the absence of a linear variable systematic error, provided that t b t (P, f = N ). It is expedient to perform validation of the accuracy of an analytical procedure together with checking for the linearity of the system response (area or height of the peak) as a function of the concentration of the parent compound to be determined (in fact, linearity of the calibration graph in terms of the criteria described in Section 1.3) and with finding the limit of detection (Section 1.6.) and the limit of quantitation (Section 1.7.). Method of regression analysis with the Fisher F-criterion. This method is based on the assumption that a linear variable systematic error can be ignored. This assumption is justified because HPLC in pharmacy is used in a relatively narrow range of sample solution concentrations. The measurements are performed for not less than N 5 samples (model mixtures) with known values of the parent compound, after which the relationship between the introduced content (m t ) and found content (m f ) is processed

10 Validation of HPLC Techniques for Pharmaceutical Analysis 1 by least squares in terms of the relation m f = a + bm t. The absence of a constant systematic error is confirmed by the insignificance of the coefficient a [35] at a commonly accepted confidence probability level of P = 95%. For this purpose, the Fisher criterion calculated is as F( P, f1 N 1, f N ) SD 01( N 1) SD 0( N ), SD ( N ) 0 (7), where SD 01 and SD 0 are the standard deviations obtained for the above relations without the free term (m f = bm t ) and with the free term (m f = a + bm t ). If the calculated F value is smaller than the tabulated (critical) values F (P = 95%, f 1, f ), the free term a is in fact insignificant and the error is absent to within a 95% confidence probability Data presentation and evaluation of the systematic error. The final judgment about the accuracy of a proposed analytical procedure can be made upon validation of its specificity, precision (repeatability, reproducibility), and linearity. 9 It is necessary to indicate a particular method of normalization of the content of impurities (weight fractions, percentage of the area under the peak of the main component, etc.). The validation results are presented by data on the recovery of the amount of introduced parent compound with a confidence interval, R R, or the difference between the average experimental value X and the true value with the corresponding confidence interval: ( X ) X. The proposed procedure involves no significant systematic error, provided that the recovery with allowance of the confidence interval does not fall outside the following limits: %, for the quantitative analysis of parent substances with a high rated content of the active component (98% and above); %, for the quantitative analysis of parent substances with a lower rated content of the active component (98% and below) and ready-to-use drugs; %, for the quantitative determination of impurities with a rated maximum content of up to 1%; 75 15%, for the quantitative determination of impurities with a rated maximum content from 0.1 to 1%; %, for the quantitative determination of impurities with a rated maximum content below 0.1%. The numerical result of a particular analysis, X (or R), must contain the last significant digit in the same position as that in the numerical value of the error of determination, X (or R) [37]. The number of significant digits in the latter value is determined as follows. If the first significant digit in the error is 3, then X is expressed by a value with one significant digit; should the first significant digit in the error 9 It is expedient to confirm the linearity together with determining the accuracy. be < 3, then X is expressed by a value with two significant digits Validation of the Suitability Range of a Given Analytical Procedure The range of suitability of a given analytical procedure is the interval between minimum and maximum concentrations (amounts) of a compound to be determined in which (i) the linearity is observed, (ii) the characteristics of repeatability fall within permissible (preset) limits, and (iii) the accuracy is maintained at a sufficiently high level [1 3]. This interval must contain all values of the concentrations (amounts), which can be encountered in the course of routine analyses. The range of suitability of a given analytical procedure is expressed in the same units as the results of analyses. It should be noted that, in practice, it is not necessary to determine the maximum possible range of suitability for an HPLC procedure. If it were necessary, this range could be determined using threshold RSD values obtained in the course of validation of the linearity and precision. For example, RSD must not exceed 3% for HPLC procedures aimed at determination of the parent compounds and 10% for procedures of impurity determination [13]. In practice, it is sufficient to show that a given range of suitability covers with margin the rated limiting concentrations of the substances to be determined, as indicated in the corresponding pharmacopoeial articles. For this reason, it is recommended that the range of suitability of a given analytical procedure be not less than the following intervals [3, 7]. (i) For the quantitative determination of the main component concentration in parent compounds and ready-to-use drugs: from 80 to 10% of the nominal content (i.e., the concentrations of test solutions should range within 80 10% relative to the concentration of a reference sample solution used accordsing to the proposed procedure). (ii) For evaluation of the homogeneity of dosage: from 70 to 130% of the nominal content, provided that a wider interval is not required (in special cases such as aerosols). (iii) For dissolution tests: 0% (absolute percentage) of the rated value of drug release. For example, for monitoring the behavior of a drug with delayed release of a parent compound, for which the release is rated as 0% within the first hour and up to 90% within a 4-h period of time, the suitability range must extend from 0 to 110% of the nominal drug content. (iv) For the quantitative determination of impurities by the method of external standard: from 50 to 10% of the nominal content. It should be noted that, in view of the possibility of RSD values amounting up to 50% (Section 1..), it would be more correct to establish the upper limit at 150% of the nominal content. For impurities exhibiting a very high biological activity, toxicity, or unpredictable behavior, the limits of detection and quantitation must correspond to the level at which these impurities have to be controlled. 10 (v) In cases where the quantitative determination of a parent compound and the detection of impurities are per-