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analytical method validation

  1. Analytical Method Validation P. Raja Abhilash, M.pharm (Ph.D.) Assistant professor S.R. college of pharmacy.
  2. Introduction  Method validation is the process of documenting / proving that an analytical method provides analytical data acceptable for the intended use.  A pharmaceutical drug product must meet all its specifications through out its entire shelf-life.  The performance of product characteristics through out the shelf-life must be tested by analytical method for the product’s chemical, physiochemical, microbiological and biological characteristics.  The method of analysis used must be validated. This is required to ensure the product’s safety and efficacy through out all phases of its shelf-life.
  3. Objective  The main objective of analytical validation is to ensure that a selected analytical procedure will give reproducible and reliable results that are adequate for the intended purpose.  This is applicable to all the procedure either pharmacopoeial or non pharmacopoeial.
  4. Steps of method development & validation  The steps of method development & validation depends upon the type of method being developed, however the following steps are common to most types of projects:  Method development plan definition  Back ground information gathering  Laboratory method development  Generation of test procedure  Methods validation protocol definition  Laboratory method validation  Validated test method generation  Validation report
  5. Types of Analytical Procedures to be Validated  The required validation parameters also termed “analytical performance characteristics”, depends upon the type of analytical method.  Pharmaceutical analytical methods are characterized into 5 general types  Identification tests  Potency assays  Limit tests for the control of impurities  Impurity tests- quantitative  Specific tests.
  6. Prerequisites for analytical method validation Man Man Machine Machine Methods Methods qualified qualified calibrated calibrated characterised characterised robust robust documented documented skilled skilled qualified qualified suitable suitable Quality Quality Reference Reference Vibrations Vibrations Time Time analy analy standards standards Analysts´ Irradi- Irradi- Analysts´ support meth meth Tempe- Tempe- ations ations support Quality rature Quality rature Humidity Humidity Supplies Supplies terial terial Milieu Management Milieu Management Six “M”s  
  7. Validation parameter ICH USP Accuracy O O Repeatibility O O Precision Interm. precision O - Reproducibility O - Specificity or Selectivity O O Detection limit O O Quantitation limit O O Linearity O O Range O O Robustness O O Ruggedness - O
  8. Table
  9. Specificity / selectivity Is this analytical Suppose we alter procedure specific test conditions for the drug under test? slightly?
  10. Specificity (1)  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, degradants, matrix, etc.  Lack of specificity of an individual analytical procedure may be compensated by other supporting analytical procedure(s).
  11. Specificity (2)  An investigation of specificity should be conducted during the validation of identification tests, the determination of impurities and the assay.  The procedures used to demonstrate specificity will depend on the intended objective of the analytical procedure.  It is not always possible to demonstrate that an analytical procedure is specific for a particular analyte (complete discrimination).  In this case a combination of two or more analytical procedures is recommended to achieve the necessary level of discrimination.
  12. Identification  Suitable identification tests should be able to discriminate between compounds of closely related structures which are likely to be present.  The discrimination of a procedure may be confirmed by obtaining positive results (perhaps by comparison with a known reference material) from samples containing the analyte, coupled with negative results from samples which do not contain the analyte.  In addition, the identification test may be applied to materials structurally similar to or closely related to the analyte to confirm that a positive response is not obtained.
  13. Assay and Impurity Test(s)  For chromatographic procedures, representative chromatograms should be used to demonstrate specificity and individual components should be appropriately labelled.  Critical separations in chromatography should be investigated at an appropriate level.  For critical separations, specificity can be demonstrated by the resolution of the two components which elute closest to each other.  In cases where a non-specific assay is used, other supporting analytical procedures should be used to demonstrate overall specificity.  For example, where a titration is adopted to assay the drug substance for release, the combination of the assay and a suitable test for impurities can be used.
  14. Impurities are available  For the assay , this should involve demonstration of the discrimination of the analyte in the presence of impurities and/or excipients;  practically, this can be done by spiking pure substances (drug substance or drug product) with appropriate levels of impurities and/or excipients and demonstrating that the assay result is unaffected by the presence of these materials
  15. Impurities are not available  specificity may be demonstrated by comparing the test results of samples containing impurities or degradation products to a second well- characterized procedure e.g.: spharmacopoeial method or other validated analytical procedure (independent procedure).  As appropriate, this should include samples stored under relevant stress conditions:  light, heat, humidity, acid/base hydrolysis and oxidation.
  16. Linearity and Range ‘Know that it’s a straight line’ vs ‘For what concentrations is it a straight line’
  17. Linearity and Range Concentration mg/mL Response  ‘Know that it’s a straight line’ versus ‘For what concentrations is it a straight line’  Is it a straight line between 0.4 & 0.6 mg/mL?  Over what range is it a straight line?  Answer: approx 0.25-0.70 mg/mL
  18. LINEARITY (1)  A linear relationship should be evaluated across the range of the analytical procedure.  It may be demonstrated directly on the drug substance by:  dilution of a standard stock solution and/or  separate weighing of synthetic mixtures of the drug product components using the proposed procedure.
  19. LINEARITY (2)  Linearity should be evaluated by visual inspection of a plot of signals as a function of analyte concentration or content.  If there is a linear relationship, test results should be evaluated by appropriate statistical methods, for example, by calculation of a regression line by the method of least squares.  In some cases, to obtain linearity between assays and sample concentrations, the test data may need to be subjected to a mathematical transformation prior to the regression analysis. Data from the regression line itself may be helpful to provide mathematical estimates of the degree of linearity.  For the establishment of linearity, a minimum of 5 concentrations is recommended.
  20. Example  Seven solutions containing different concentrations (0.280 – 0.520) mg/ml of ketotifen fumarate in tablets were assayed using HPLC  The results were evaluated statistically and the results shown on the following slide
  21. Example (continued) Concentration of ketotifen fumarate Area detected Acceptance mg/ml % criteria 0.280 70 1473566 0.320 80 1677013 0.360 90 1904848 0.400 100 2091215 0.440 110 2293647 0.480 120 2518976 0.520 130 2670144 Regression: y = ax + b 0.998 – 1.002 a = 5055766.964 b = 67608.786 r2 = 0.9984
  22. RANGE  The specified range is normally derived from linearity studies and depends on the intended application of the procedure.  It is established by confirming that the analytical procedure provides an acceptable degree of linearity, accuracy and precision when applied to samples containing amounts of analyte within or at the extremes of the specified range of the analytical procedure.
  23. Minimum Specified Ranges  for the assay of a drug substance or a finished (drug) product: normally from 80 - 120 % of the test concentration  for content uniformity, covering a minimum of 70 - 130 % of the test concentration  for dissolution testing: +/-20 % over the specified range;  e.g., if the specifications for a controlled released product cover a region from 20%, after 1 hour, up to 90%, after 24 hours, the validated range would be 0- 110% of the label claim
  24. Accuracy vs precision What you would like to see!
  25. Accuracy vs precision  Poor accuracy  Good precision
  26. Accuracy vs precision  Poor precision  Good accuracy
  27. Accuracy vs precision What would you call this?  Totally hopeless!  Poor precision  Poor accuracy
  28. So what definitions do these concepts lead us to in the context of assay validation?
  29. ACCURACY (1)  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. This is sometimes termed trueness.
  30. ACCURACY (2) Assay of Drug Product: a) Application of the analytical procedure to synthetic mixtures of the drug product components to which known quantities of the drug substance to be analysed have been added (standard addition method); b) In cases where it is impossible to obtain samples of all drug product components, it may be acceptable either to:  add known quantities of the analyte to the drug product or  to compare the results obtained from a second, well characterized procedure, the accuracy of which is stated and/or defined (independent procedure) c) Accuracy may be inferred once precision, linearity and specificity have been established.
  31. ACCURACY (3) Impurities (Quantitation):  Accuracy should be assessed on samples (drug substance/drug product) spiked with known amounts of impurities.  In cases where it is impossible to obtain samples of certain impurities and/or degradation products, it is considered acceptable to compare results obtained by an independent procedure. The response factor of the drug substance can be used.  It should be clear how the individual or total impurities are to be determined e.g., weight/weight or area percent, in all cases with respect to the major analyte.
  32. Recommended Data  Accuracy should be assessed using a min. of 9 determinations over a min. of 3 concentration levels covering the specified range (e.g. 3 concentrations/3 replicates each of the total analytical procedure).  Accuracy should be reported as:  % recovery by the assay of known added amount of analyte in the sample or as  the difference between the mean and the accepted true value together with the confidence intervals
  33. Example:  Nine solutions containing different concentrations of ketotifen fumarate reference standard added to ketotifen tablet were assayed
  34. Example (continued): Conc. of ketotifen fumarate Area Recovery Acceptance mg/ml % detected (%) Criteria 0.280 70 1473566 99.32 0.320 80 1677013 99.48 0.360 90 1904848 100.94 0.380 95 1905862 100.51 0.400 100 2091215 100.06 0.420 105 2180374 100.03 0.440 110 2293647 100.07 0.480 120 2518976 101.01 0.520 130 2670144 98.99 Mean (recovery) : 100.04 98.0–102.0 % Standard deviation : 0.699 Relative standard deviation (RSD) : 0.699 % <2%
  35. 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 and  reproducibility.  Precision should be investigated using homogeneous, authentic samples. However, if it is not possible to obtain a homogeneous sample it may be investigated using artificially prepared samples or a sample solution.  The precision of an analytical procedure is usually expressed as the variance, standard deviation or coefficient of variation of a series of measurements.
  36. Repeatability (1)  Repeatability expresses the precision under the same operating conditions over a short interval of time.  Repeatability is also termed intra-assay precision.
  37. Repeatability (2)  Repeatability should be assessed using: a) a minimum of 9 determinations covering the specified range for the procedure (e.g. 3 concentrations/3 replicates each) or b) a minimum of 6 determinations at 100% of the test concentration.
  38. Intermediate precision  Intermediate precision expresses within-laboratories variations: different days, different analysts, different equipment, etc.  The extent to which intermediate precision should be established depends on the circumstances under which the procedure is intended to be used.  The applicant should establish the effects of random events on the precision of the analytical procedure.  Typical variations to be studied include days, analysts, equipment, etc. It is not considered necessary to study these effects individually. The use of an experimental design (matrix) is encouraged.
  39. Reproducibility  Reproducibility is assessed by means of an inter-laboratory trial.  Reproducibility should be considered in case of the standardization of an analytical procedure, for instance, for inclusion of procedures in pharmacopoeias.  These data are not part of the marketing authorization dossier.
  40. Recommended Data  The standard deviation, relative standard deviation (coefficient of variation) and confidence interval should be reported for each type of precision investigated.
  41. Example  The active ingredient, ketotifen fumarate, in tablets was assayed seven times using HPLC and the reference standard
  42. Example (continued) Sample no. Concentration (mg/ml) Area detected 1 0.4 1902803 2 0.4 1928083 3 0.4 1911457 4 0.4 1915897 5 0.4 1913312 6 0.4 1897702 7 0.4 1907019 Mean : 1910896 Standard deviation : 9841.78 Relative standard deviation (RSD) : 0.515 % Acceptance criteria: Relative standard deviation (RSD): not more than 2 %
  43. Detection limit vs Quantitation limit ‘Know that it’s there’ vs ‘Know how much is there’
  44. Detection limit (means) Is any of it present? Is it there?
  45. Quantitation limit How much of it is present??? How much of it is there?
  46. DETECTION LIMIT  The detection limit 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  Several approaches for determining the detection limit are possible, depending on whether the procedure is a non- instrumental or instrumental.
  47. Based on Visual Evaluation  Visual evaluation may be used for non- instrumental methods but may also be used with instrumental methods.  The detection limit is determined by the analysis of samples with known concentrations of analyte and by establishing the minimum level at which the analyte can be reliably detected .
  48. Based on Signal-to-Noise  This approach can only be applied to analytical procedures which exhibit baseline noise.  Determination of the signal-to-noise ratio is performed by comparing measured signals from samples with known low concentrations of analyte with those of blank samples and establishing the minimum concentration at which the analyte can be reliably detected.  A signal-to-noise ratio between 3:1 or 2:1 is generally considered acceptable for estimating the detection limit.
  49. Based on the Standard Deviation of the Response and the Slope The detection limit (DL) may be expressed as: DL = 3.3 σ /S where σ = the standard deviation of the response S = the slope of the calibration curve The slope S may be estimated from the calibration curve of the analyte.
  50. Estimate of σ  Based on the Standard Deviation of the Blank  Measurement of the magnitude of analytical background response is performed by analyzing an appropriate number of blank samples and calculating the standard deviation of these responses  Based on the Calibration Curve  A specific calibration curve should be studied using samples containing an analyte in the range of DL.  The residual standard deviation of a regression line or the standard deviation of y-intercepts of regression lines may be used as the standard deviation.
  51. Recommended Data  The detection limit and the method used for determining the detection limit should be presented.  If DL is determined based on visual evaluation or based on signal to noise ratio, the presentation of the relevant chromatograms is considered acceptable for justification.  In cases where an estimated value for the detection limit is obtained by calculation or extrapolation, this estimate may subsequently be validated by the independent analysis of a suitable number of samples known to be near or prepared at the detection limit
  52. QUANTITATION LIMIT  The quantitation limit of an individual analytical procedure is the lowest amount of analyte in a sample which can be quantitatively determined with suitable precision and accuracy.  The quantitation limit is a parameter of quantitative assays for low levels of compounds in sample matrices, and is used particularly for the determination of impurities and/or degradation products.  Several approaches for determining the quantitation limit are possible, depending on whether the procedure is a non-instrumental or instrumental.
  53. Based on Visual Evaluation  Visual evaluation may be used for non- instrumental methods but may also be used with instrumental methods.  The quantitation limit is generally determined by the analysis of samples with known concentrations of analyte and by establishing the minimum level at which the analyte can be quantified with acceptable accuracy and precision.
  54. Based on Signal-to-Noise Approach  This approach can only be applied to analytical procedures that exhibit baseline noise.  Determination of the signal-to-noise ratio is performed by comparing measured signals from samples with known low concentrations of analyte with those of blank samples and by establishing the minimum concentration at which the analyte can be reliably quantified.  A typical signal-to-noise ratio is 10:1.
  55. Based on the Standard Deviation of the Response and the Slope  The quantitation limit (QL) may be expressed as: QL = 10 σ /S where σ = the standard deviation of the response S = the slope of the calibration curve  The slope S may be estimated from the calibration curve of the analyte.
  56. Estimate of σ  Based on Standard Deviation of the Blank  Measurement of the magnitude of analytical background response is performed by analyzing an appropriate number of blank samples and calculating the standard deviation of these responses.  Based on the Calibration Curve  A specific calibration curve should be studied using samples, containing an analyte in the range of QL.  The residual standard deviation of a regression line or the standard deviation of y-intercepts of regression lines may be used as the standard deviation.
  57. Recommended Data  The quantitation limit and the method used for determining the quantitation limit should be presented.  The limit should be subsequently validated by the analysis of a suitable number of samples known to be near or prepared at the quantitation limit.
  58. Robustness Small changes do not affect the parameters of the assay
  59. 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.  The evaluation of robustness should be considered during the development phase and depends on the type of procedure under study.  If measurements are susceptible to variations in analytical conditions, the analytical conditions should be suitably controlled or a precautionary statement should be included in the procedure.  One consequence of the evaluation of robustness should be that a series of system suitability parameters (e.g., resolution test) is established to ensure that the validity of the analytical procedure is maintained whenever used.
  60. Typical Variations  stability of analytical solutions,  extraction time Liquid chromatography:  influence of variations of pH in a mobile phase,  influence of variations in mobile phase composition,  different columns (different lots and/or suppliers),  temperature,  flow rate. Gas chromatography:  different columns (different lots and/or suppliers),  temperature,  flow rate.
  61. SYSTEM SUITABILITY TESTING  System suitability testing 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 test parameters to be established for a particular procedure depend on the type of procedure being validated. They are especially important in the case of chromatographic methods.
  62. System Suitability in Chromatography  To verify that the resolution and reproducibility of the chromatographic system are adequate for the analysis to be done  The resolution, R, is specified to ensure that closely eluting compounds are resolved from each other  Replicate injections of a standard preparation are compared to ascertain whether requirements for precision are met  The tailing factor, T, has to meet a certain requirement, because as peak asymmetry increases, integration, and hence precision, becomes less reliable
  63. Evaluating validation data for an HPLC procedure  Here are some suggestions………  But please note! - The slides that follow do not represent requirements; they are suggestions. - There is more than one way to do this! - Use judgement.  If you are unsure, consult with experienced analysts!!
  64. Specificity (selectivity) Use some or all of these procedures: - Add a synthetic mixture of excipients to the sample & check whether the assay result for the drug is the same - Add some known impurities to the test sample & check whether they are resolved (separated from) the drug - Forcably degrade the active & test whether degradants are separated from the intact drug - Assess peak purity by diode array
  65. Linearity - Minimum of 5 concentrations - r2 >0.99 if possible - Intercept NMT ±2% of response of 100% the working concentration - Confirm accuracy & precision over the required range
  66. Accuracy - Generally within +2% - Recoveries after spiking, or - Comparison with ‘well-established’ methods & by inference - Arguably can be up to +10% for related substances - What is known about the reference standard?
  67. Precision - repeatability  System repeatability %CV (of detector response) <2.0% for 6 injections  Method repeatability %CV <2.0% and accuracy should be within 2%
  68. Precision - intermediate [= ruggedness USP] - Use same complete analytical procedure for comparisons - Compare results across different analysts, days, equipment - Means preferably within 2% - Compare %CV with that for method repeatability
  69. Precision - reproducibility - This is not normally a component of a dossier for an application to register, but if you do have to evaluate these data then…… - For interlab comparisons - Means should preferably be within 2% - Compare the %CV with that for method repeatability - Can use an F test, normally with 95% confidence
  70. Limit of detection - Use some or all of these procedures: - - Visual evaluation: A clear & symmetrical peak is visible - Signal to noise ratio of 3:1 or 2:1 - Based on statistical information: - Detection limit = - 3.3 x (std dev at that concentration) - slope
  71. Limit of quantitation - Use some or all of these procedures: - ‘Visual’ evaluation: A clear & symmetrical peak is visible - Signal to noise ratio of 10:1 - Based on statistical information: - Detection limit = - 10 x (std dev at that concentration) - slope
  72. Robustness - Use some or all of these procedures: - Compare results after altering HPLC parameters, eg mobile phase composition, buffer composition, pH, column type, flow rate: - NMT ± 2% difference in assay - Compare results after storage of test solution, eg for 24h at say 250C - NMT ± 2% difference in assay
  73. Evaluation of analytical validation data The objective of the analytical procedure The analytical technique Item Data provided by applicant Acceptable or not? (add comments if (very briefly) necessary, & reasons if unacceptable) Is a chromatogram, spectrum or similar provided? S Linearity Range Accuracy Precision: Repeatability Precision: Intermediate Precision: Reproducibility Detection limit Quantitation limit Robustness System suitability (if necessary) Are the data concerning analytical validation satisfactory? YES/NO DataIfon therecommended questions to the applicant appear in NO, reference standard …………………………………………………………………… Other evaluator comments: (eg page number below, or draft letter to the company on page……)
  74. Thank you

Editor's Notes

  1. ‘ -’ signifies that this characteristic is not normally evaluated ‘ +’ signifies that this characteristic is normally evaluated (1) In cases where reproducibility has been performed . Intermediate precision is not needed. (2) Lack of specificity of one analytical procedure could be compensated by other supporting analytical procedures (3) May be needed in some cases.
  2. NB From perspective of an evalr, not from perspective of an analyst experienced in HPLC.
  3. Selectivity: Provide representative chromatograms with labelled peaks Suitable acceptance criteria might be: Capacity factor k’ &gt; 1.0 Resolution &gt;1.0 If ref imps not available, can prepare a suitable solution by forced degradation. If degradation &gt;10%, may have to argue relevance. Diode array (suggested by ICH) may not be sensitive to low levels of imps, esp if chromophores similar When validating ID tests, remember to consider other actives on your site, as well as excipients
  4. Linearity: Normally submit plot of detector response vs concentration, plus regression analysis Normally also determine accuracy and precision at extremes of range TGAL usually test across range of 50-150%, especially when test is to be used for CU and/or dissolution testing
  5. Accuracy: When need to determine accuracy over a range of concentrations, normally 3 concentrations sufficient If mixture of excipients not available, may add known quantities of active and determine difference in results Care with reference substance. If a working standard (ie qualified wrt pharmacopoeial ref subst), bear in mind possibility that errors can accumulate. Care with hydration. Watch for time dependent variability, possibly associated with decomposition. If sample is filtered during preparation, specify type of filter and check for losses (soln of ref filtered vs not filtered)
  6. ‘ System’ repeatability: Aka repeatability between injections %CV can be of the order of 0.2%, particularly when automated FDA recommends min of 10 injections with %CV &lt; 1.0% Many EP monographs prescribe %CV &lt; 1% Acceptable %CV depends in part on the acceptance range for the assay in question Method repeatability: Aka repeatability of the complete method In practice, often estimated in conjunction with accuracy Means should be within + 2% of t/c Typically measured by: 6 replicates at 100% t/c OR 3 replicates of 3 concentrations %CV can be of the order of 0.4%, particularly when automated Acceptable %CV may be higher for: Impurities More complex matrices (such as creams) Microdose products
  7. Intermediate precision: FDA uses the term ‘ruggedness’ with same meaning Although slide states means preferably within 2%, criteria are not laid down Acceptability is assessed on case by case basis
  8. Reproducibility: Again: although slide states means preferably within 2%, criteria are not laid down Again: acceptability is assessed on case by case basis
  9. LOD: LOD especially important for imps Submit typical chromatograms at LOD Std dev may be estimated from: Std dev of blank samples Std dev of intercept Residual std dev from regression analysis of calibration plot
  10. LOQ: Again important for imps LOQ must be &lt; acceptance criterion for the imp(s) !! Personally I would not want to rely on ‘visual’ evaluation for limit of quantitation. Submit typical chromatograms at LOQ As for LOD, std dev may be estimated from: Std dev of blank samples Std dev of intercept Residual std dev from regression analysis of calibration plot Confirm the LOQ by determining %CV at that value
  11. Dot point 1: - If difference in assay &gt;2%, describe attempts to improve. If little improvement gained, insert warnings into write-up of method. Dot point 2: - Duration and conditions of storage should represent most stressful situation likely to occur, eg during a 24hour auto-sampling run.
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