### Validation my ppt

1. Promila thakur M pharma 1 st year (p’ceutics)
2. What is Validation? Validation is defined as establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product specifications and quality attributes. Identification meeting its pre-determined    Determination Assay of impurities Analytical Method Validation 2
3. Why Validation? • The objective of any analytical measurement is to obtain consistent, reliable and accurate data. Validated analytical methods play a major role in achieving this goal. • Validation of analytical methods is also required by most regulations. Analytical Method Validation 3
4. Typical Analytical Procedures Be Validated To • Four most common types of analytical procedures to validated: be • • • • Identification tests Quantitative tests for impurities content Limit tests for the control of impurities Quantitative tests of the active moiety Analytical Method Validation 4
5. Parameters 1. Linearity and Range 2. Specificity 3. Precision 4. Accuracy 5. Limit of Detection 6. Limit of Quantitation 7. Robustness 8. System Suitability Analytical Method Validation 6
6. -signifies that this characteristic is not normally evaluated + signifies that this characteristic is normally evaluated Analytical Method Validation 7 Characteristic Identification Impurities Testing Assay Quantitative Limit Accuracy _ + _ + Precision a. Repeatability _ + _ + b. Intermediate precision _ + _ + Specificity + + + + LOD _ _ + _ LOQ _ + _ _ Linearity _ + _ + Range _ + _ +
7. 1. Linearity and Range LINEARITY Ability to obtain test results that are directly (or by a well-defined mathematical transformation) proportional to the concentration of analyte in samples within a given range. (y = mx + c) • •    The following parameters should be correlation coefficient y-intercept(c) determined: slope of the regression line(m) Analytical Method Validation 8
8. Determination of Linearity • For establishment of linearity, minimum recommended. 5 concentrations are • Linearity results methods. should be established by appropriate statistical = 0.9988 Analytical Method Validation 9 R² 1 0.8 0.6 0.4 y = 0.0868x + 0.019 0.2 0 0 2 4 6 8 10 12
9. • Transformations are also acceptable and may include log, square root, or reciprocal (other transformations are acceptable) 1.2 0.8 0 2 4 6-0.2 Analytical Method Validation 10 y = 0.3671x - 0.4296 1.8 1.6 1.4 1 R² = 0.9515 0.6 0.4 0.2 0 Conc. Response (µg/ml) 1 0.0625 2 0.25 3 0.562 4 0.922 5 1.562
10. 0 1.2 0.4 • If linearity is not attainable, a nonlinear model may be used. The goal is to have a model (whether linear or nonlinear) that describes closely the concentration-response relationship. • r2Acceptance criteria: Linear regression > 0.95 Analytical Method Validation 11 1.4 1 0.8 0.6 y = 0.246x + 0.004 R² = 0.9982 0.2 0 2 4 6 Conc. √Response (µg/ml) 1 0.25 2 0.5 3 0.75 4 0.96 5 1.25
11. RANGE • The range of an analytical procedure is the interval between the upper and lower levels of analyte(including these levels) that have been demonstrated with a suitable level of precision, accuracy, and linearity. For assay tests, ICH requires the minimum specified range to be 80 to 120 percent of the test concentration. • Analytical Method Validation 12
12. • • Acceptable range having linearity, accuracy, precision. For Drug Substance & Drug product Assay – 80 to 120% of test Concentration For Content Uniformity Assay – 70 to 130% of test Concentration For Dissolution Test Method – +/- 20% over entire Specification Range For Impurity Assays • • • – From Reporting Level to 120% of Impurity Impurity Assays – From Reporting Level to 120% of Assay Specification for Impurity/Assay Methods Specification for Analytical Method Validation 13
13. 2. 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. • Sample prepared in six replicates as per the method. on the same day and analysed • The precision is reportedin terms of %RSD Analytical Method Validation 14
14. Less Variation High Precision More Variation Low Precision Analytical Method Validation 15 Concentration Absorbance 10 µg/ml Mean 0.22 0.35 0.39 0.53 0.36 Concentration Absorbance 10 µg/ml Mean 0.28 0.31 0.29 0.30 0.29
15. • Precision maybe considered at three levels: Precision Intermediate Precision Repeatability Reproducibility Analytical Method Validation 16
16. 1. • Repeatability Repeatability expresses the precision under the same operating conditions over a short interval of time. Repeatability should be assessed using a minimum of 9 determinations covering the specified range. • 2. • Intermediate Precision Intermediate precision expresses variations within laboratories, such as different days, different analysts, different equipment, and so forth. 3. • Reproducibility Reproducibility laboratories. It laboratory trial. 17025) expresses the precision between an inter- USP, ISO is assessed by means of (Defined as ruggedness in Analytical Method Validation 17
17. 0. • Following parameters should be reported: a. b. Standard deviation Relative standard deviation (coefficient of variation) 1 0 Analytical Method Validation 18 12 20 1.2 8 8 0.8 8 0.6 12 4 12 0.2 20 20 4 8 12 16 20 24 Concentration Absorbance SD & % RSD µg/ml 8 0.337 0.00041, 1.223%0.348 0.341 12 0.575 0.0106, 1.815%0.583 0.596 20 0.967 0.0091, 0.933% 0.985 0.978
18. 3. Accuracy Closeness of agreement between the conventional true• value / an accepted reference value and the value found. High Accuracy Less Accuracy Analytical Method Validation 19
19. Determination of Accuracy 1. Assay Drug Substance Drug Product a)application of the analyticala) application procedure Material. of to analytical reference procedure to synthetica mixtures quantities to which of the known drug addedsubstance have been b) to compare the results. b) to compare the results c) accuracy may be concluded once precision, linearity and specificity have been established. c) accuracy may be concluded once precision, linearity and specificity have been established. Analytical Method Validation 20
20. 2. Impurities (Quantitation)  Assessed on samples (drug substance/drug product) spiked with known amounts of impurities.  Accuracy should be assessed using a minimum of 9 determinations over a minimum 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 percent 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. Analytical Method Validation 21
21. 4. Limit of Detection & Quantitation Limit of Detection: It is the lowest amount of analyte in a sample detected but not necessarily quantitated. Limit of • • which can be • • Limit of Quantitation: It is the lowest amount of analyte in a sample which can be quantitatively determined with suitable precision and accuracy. Analytical Method Validation 23
22. 4. Limit of Detection & Limit of Quantitation LOQLOD  Lowest amount of analyte in a sample that can be Lowest amount of analyte in a sample that can be detected but not necessarily quantified with suitable quantitated. accuracy and precision.  Estimated by Signal to Noise Ratio of 10:1. Estimated by Signal to Noise Ratio of 3:1. Analytical Method Validation 22
23. Signal to noise ratio 10:1 Signal to noise ratio 2:1 or 3:1 Determination of LOD & LOQ Limit of Detection  Method Limit of Quantitation  Method  Based on visual evaluation Based on visual evaluation  Based on standard deviation of response and slope Based on standard deviation of response and slope LOD = 3.3 σ / Slope LOD = 10 σ / Slope  Analytical Method Validation 24
24. Analytical Method Validation 25
25. 6. Specificity • The ability to detect the analyte of interest in the presence of interfering substances (typically impurities, degradants, ). 1. 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 from samples containing the analyte, coupled with negative results from samples which do not contain the analyte. 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. • Analytical Method Validation 26
26. 2. Assay and impurity test: a. • Impurities are available For the assay , this discrimination of the and/or excipients. should involve demonstration of the analyte in the presence of impurities • This can be done by spiking pure substances with appropriate levels of impurities and/or excipients and demonstrating that the assay result is unaffected by the presence of these materials. • For the impurity test, the discrimination may be established by spiking drug substance or drug product with appropriate levels of impurities and demonstrating these impurities individually and/or from in the sample matrix. the separation of other components Analytical Method Validation 27
27. 7. 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. • • If measurements are susceptible to variations in analytical conditions, the analytical conditions should should be suitably controlled or a precautionary statement the procedure, such as: Use solution within 24 hours be included in • • Maintain temperature below 25 degrees Analytical Method Validation 29
28. • In the case of liquid chromatography, examples of typical variations are: 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      • In the case of gas-chromatography, examples of typical variations are: different columns (different lots and/or suppliers) temperature flow rate    Analytical Method Validation 30
29. 8. System Suitability • 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. • Determination: repeatability, tailing factor (T), capacity factor (k’), resolution (R), and theoretical Plates (N) Analytical Method Validation 31
30. System Suitability Requirements Analytical Method Validation 32 Parameters Recommendations K’ In general k’ ≥ 2.0 R >2, between the peak of interest and R the closest potential interferent (degradant, internal STD, impurity, excipient, etc…) T T ≤ 2 N In general N > 2000 Repeatability RSD ≤ 2.0% (n ≥ 5)
31. Conclusion When the method is properly validated consistent, reliable• and accurate results are obtained. Also, Validation of analytical methods is also required by regulations. Hence it is very important to validate any analytical method that has been developed. Analytical Method Validation 33
32. 15 nov 2018 Analytical Method Validation 34

### Notas del editor

1. correlation coefficient : statistical relationship between two variables  y-intercept is the point where a line crosses the y-axis. The slope of regression line (b) represents the rate of change in y as x changes. Because y is dependent on x, the slope describes the predicted values of y given x.
2. In reproducibility : the same analysis is performed in different laboratory or place by same methods.