Method validation

Method Validation

1. METHOD VALIDATION Kanchan K. Nayak Senior Divisional chemist 2/24/2021 2

2. Definitions 2/24/2021 K.K. Nayak 3 Method validation is basically the process of defining an analytical requirement, and confirming that the method under consideration has capabilities consistent with what the application requires. confirmation, through the provision of objective evidence, that the requirements for a specific intended use are fulfilled [ISO/IEC 17025] confirmation by examination and provision of objective evidence that the particular requirements for a specific intended use or application have been fulfilled [ISO 9000]

3. Why Method Validation? 2/24/2021 K.K. Nayak 4 To minimize analytical and instrumental errors To give reliable and reproducible results in accordance with the given specifications of the test method To ensure the quality of the test results To meet accreditation requirement Objective evidence for defense against challenges To be assured of the correctness of results

4. When should methods be validated? 2/24/2021 K.K. Nayak 5 A method should be validated when it is necessary to verify that its performance parameters are adequate for use for a particular analytical problem. For example: non-standard methods; laboratory-designed/developed methods; standard methods used outside their intended scope amplifications and modifications of standard methods. to demonstrate the equivalence between two methods, e.g. a new method and a standard. when quality control indicates an established method is changing with time;

5. When Method Validation Not Required? Standard methods on condition that – used within their scope of applicability (e.g. matrices, ranges, etc) – without modifications 2/24/2021 K.K. Nayak 6

6. Who carries out method validation? The laboratory using a method is responsible for ensuring that it is adequately validated, and if necessary for carrying out further work to supplement existing data. For example, where a method has been validated by a standards approving organisation, such as AOAC International, the user will normally need only to establish performance data for their own use of the method. 2/24/2021 K.K. Nayak 7

7. EXTENT OF VALIDATION STUDIES Suggestions as to the extent of validation and verification measures for different circumstances are: The laboratory is to use a “fully” validated method Verify by precision and linearity The laboratory is to use a fully validated method, but a new matrix is to be used Verify by precision and linearity, bias and LoD The laboratory is to use a well-established, but not collaboratively studied, method. laboratory should verify and undertake precision studies, bias studies, reproducibility and possibly linearity studies, LoD & LoQ 2/24/2021 K.K. Nayak 8

8. EXTENT OF VALIDATION STUDIES The method has been published in the scientific literature together with some analytical characteristics. The laboratory should undertake precision studies, bias studies, ruggedness, and linearity studies, LoD & LoQ 2/24/2021 K.K. Nayak 9 Validation is always a balance between costs, risks and technical possibilities.

9. EXTENT OF VALIDATION STUDIES 2/24/2021 K.K. Nayak 10 Extent of validation work for four types of analytical applications. Example from the pharmaceutical sector

10. Deciding what degree of validation is required The laboratory has to decide which method performance parameters need to be characterised in order to validate the method. 2/24/2021 K.K. Nayak 11 Validation requirements may be specified in guidelines within a particular sector of measurement relevant to the method and it is recommended that where these are available they are followed. For example validation of a method for food analysis should be consistent with the validation strategy used by AOAC International.

11. Ask yourself What analytes should be detected? What are the expected concentration levels? What are the sample matrices? Are there interfering substances expected, and, if so, should they be detected and quantified? Are there any specific legislative or regulatory requirements? Should information be qualitative or quantitative? What are the required detection and quantitation limits? What is the expected concentration range? What precision and accuracy is expected? How robust should the method be? Which type of equipment should be used? Is the method for one specific instrument, or should it be used by all instruments of the same type? Will the method be used in one specific laboratory or should it be applicable in all laboratories at one side or around the globe? What skills do the anticipated users of the method have? 2/24/2021 K.K. Nayak 12 Before start to validate a method

12. VAM Principles 2/24/2021 K.K. Nayak 13 There are six VAM principles : Analytical measurements should be made to satisfy an agreed requirement Analytical measurements should be made using methods and equipment which have been tested to ensure they are fit for their purpose Staff making analytical measurements should be both qualified and competent to undertake the task There should be a regular independent assessment of the technical performance of the laboratory Analytical measurements made in one location should be consistent with those elsewhere Organisations making analytical measurements should have well defined quality control and quality assurance procedures

13. Method development and validation 2/24/2021 K.K. Nayak 14 ‘ Never attempt to re-invent the wheel!’ Before embarking on the development of a new method, always research the chemical literature to see if a suitable one already exists. If a suitable one is found, it will still be necessary however to perform some method validation to prove that the method can be successfully adapted to your laboratory, equipment and personnel . More extensive validation is required for a brand new method. Methods in any field of analysis may be defined in terms ‘ Method performance characteristics’ and it is these parameters plus a few others, that are quantified during a method validation exercise.

14. Method validation 2/24/2021 K.K. Nayak 15 Validation, is the proof needed to ensure that an analytical method can produce results which are reliable and reproducible and which are fit for the purpose intended. The parameters that need to be demonstrated are those associated with the ‘ Performance characteristics’ together with robustness, repeatability and reproducibility. Many analytical methods appearing in the literature have not been through a thorough validation exercise and thus should be treated with caution until full validation has been carried out. Validation of a new method (new to your laboratory), is a costly and time-consuming exercise, however the result of not carrying out method validation could result in litigation, failure to get product approval, costly repeat analysis and loss of business and prestige. You can now consider in more detail how validation is carried out

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16. Method performance characteristics 2/24/2021 17 A method’s performance is defined by a number of important individual characteristics. There are: Sensitivity Precision Accuracy Limit of Detection ( LoD ) Limit of Determination Measurement Uncertainty Bias Selectivity Linearity Range K.K. Nayak

17. Accuracy and precision 2/24/2021 K.K. Nayak 18 The dictionary definition of both ‘ accuracy ’ and ‘ precision ’ are roughly the same, indicating that these words may be used synonymously. However in ‘Analytical Science’ they have two separate meanings, the difference between them is best illustrated by using target diagrams Poor precision poor accuracy Good precision poor accuracy Good mean accuracy poor precision Good accuracy good precision

18. Accuracy and precision (2) 2/24/2021 K.K. Nayak 19 You saw from the previous slide, a set of results can be either accurate and/or precise or can be neither accurate nor precise . Thus accuracy may be defined as: The closeness of the mean value from a replicate set of results to the true or accepted value Precision may be defined as: The spread of results from a replicate set of measurements The difference between the true value and the mean measured value is termed bias . The spread of replicate data is measured in terms of standard deviation (s) or variance (s 2 )

19. Bias and variance 2/24/2021 K.K. Nayak 20 A solution containing copper was analysed 10 times using atomic absorption spectroscopy. The results obtained in ppm were: 10.08, 9.80, 10.10, 10.21, 10.14, 9.88, 10.02, 10.12, 10.11, 10.09 We can now calculate the precision of the data as standard deviation If the true value is known to be 10.00 ppm, we can also calculate the bias Bias = Mean value - true value = 10.06 - 10.00 = 0.06 ppm Standard deviation (SD) = 0.12 Conclusion - the method gives both good accuracy (low bias) and acceptable precision (RSD of 1.2%) Relative SD = 100 X SD/10.00 = 1.2%

20. Sensitivity and selectivity 2/24/2021 K.K. Nayak 21 Sensitivity is the change in measured signal for unit change in concentration and can be obtained from the calibration graph Sensitivity = dy/dx dy dx Selectivity is the ability of a method to discriminate between the target analyte and other constituents of the sample. In many instances selectivity is achieved by high performance separation using chromatographic or electrophoretic techniques. “ the extent to which the method can be used to determine particular analytes in mixtures or matrices without interferences from other components of similar behaviour ” Hplc chromatogram

21. Limits of detection ( LoD ) and determination 2/24/2021 K.K. Nayak 22 These values refer to the statistical limits below which results of detection or accurate quantitative measurements (determination) should not be reported. The levels of both are dependent upon the variability of the signal when a blank containing none of the analyte is being measured. The signal generated under these conditions is mostly signal noise and is assumed to exhibit a normal distribution pattern. Both the blank signal and the standard deviation of the blank signal need to be measured. From this data we can calculate both limits. Example: In an analysis of trace Cd by plasma emission spectrometry the following data were obtained: mean blank (Bl) signal 4 SD of blank signal 12 500 ppb Cd 2000 LoD = Bl signal + 3(SD of Bl) = 4 + 3(12) = 40 This equates to: [40/2000] X 500 ppb = 10 ppb Cd The limit of determination uses a similar formula, replacing the 3 SD’s by 10. This gives the limit of determination as 31 ppb Cd

22. Method validation - detection & quantitation limits 2/24/2021 K.K. Nayak 23 A method is not acceptable for accurate detection or quantitation if the analyte level is likely be fall beneath the limit(s) calculated based upon the blank signal and its standard deviation . Analyte pre-concentration then becomes necessary. Variation in blank signal Mean blank signal Variation in sample signal Mean sample signal Mean sample signal must be sufficiently larger than the blank so that positive detection or accurate quantitation is possible

23. Method validation - linearity 2/24/2021 K.K. Nayak 24 Linearity Most analytical methods are of a comparative type and thus require calibration against accurately known standards to generate quantitative data. Where possible calibration data should show a linear relationship between analyte concentration and measured signal, however it is acceptable under some circumstances, to use a non-linear relationship up to the limit of the dynamic range. Check linearity between 50 - 150% of the expected analyte concentration

24. Method validation - specificity 2/24/2021 K.K. Nayak 25 Loss of specificity can be due to interferences and matrix effects. All likely interferences should be investigated and their effects on analyte response determined over a range of concentrations. Measures can then be put into place to mask , eliminate or separate them from the analyte. Standard addition procedures can be used to identify matrix effects no yes

25. Method validation - precision 2/24/2021 K.K. Nayak 26 You have seen already that, precision is measured in terms of standard deviation (SD) . Assuming that the variability of the measurements is totally random (obeys a normal distribution curve) then a formula derived from this distribution may be used to calculate standard deviation. SD = [ Σ(x i - x) 2 /(n - 1)] 1/2 where: x i = individual data point x = mean value of the data n = the total number of data points Σ = the sum of Estimation of true mean In practice around 8 - 10 data points are used normally to calculate the SD, although statisticians would recommend 50

26. Method Validation - repeatability & reproducibility 2/24/2021 K.K. Nayak 27 Methods need to be shown to be both repeatable and reproducible. A replicate set of data produced at a particular time point by an operator working with a particular set of equipment in a given laboratory will verify repeatability . To show reproducibility , the method must produce similar results when any of these parameters are changed. The most likely changes are to time and operator. Two different operators analysing milk using different pieces of equipment at different times. The laboratory is the same.

27. Method validation - reliability 2/24/2021 K.K. Nayak 28 The reliability of a method can be tested in a number of ways Test results from the new method against an existing method which is known to be accurate Add a known quantity of pure analyte (spike) to a real sample or real sample matrix and check that all of the added substance can be measured (recovered) The best way of demonstrating accuracy is to analyse a reference material or certified reference material (CRM) if one is available Selection of reference materials from LGC

28. Method validation - robustness 2/24/2021 K.K. Nayak 29 Robustness of an analytical method refers to it’s ability to remain unaffected when subjected to small changes in method parameters. For example In an hplc analysis the mobile phase is defined in terms of % organic modifier, pH of the mobile phase, buffer composition, temperature etc. A perfect mobile phase is one which allows small changes in the composition without affecting the selectivity or the quantitation of the method. Alter all major parameters in order to ascertain when the method ceases to function in accordance with specifications

29. Validation Plan& Report validation plan and validation report may consist of the following sections: Title Planning Performance Characteristics Summary 2/24/2021 K.K. Nayak 30

30. Title: 2/24/2021 K.K. Nayak 31 Identify the method When and who is performing Method scope and a short description of method The Analyte Measurement Unit Types of Sample

31. Planning This section should outline the purpose, e.g. full validation of a new method, verification of performance of a standardised method, extension to method scope, 2/24/2021 K.K. Nayak 32

32. Performance characteristics: This section should give a brief explanation of the performance characteristic, Outline the experiments which will be done and How the results are to be evaluated? Results and conclusions from the experiments should be stated. 2/24/2021 K.K. Nayak 33

33. Summary The last section should summarize the validation work and the results A concluding statement as to whether the method is fit for purpose 2/24/2021 K.K. Nayak 34

34. Documentation of method validation Foreword Introduction Title Warnings Scope References Definitions Principle Reaction Reagent and materials Apparatus & Equipments Sampling Procedure Acceptance criteria Calculations Precision QA/QC Special Cases Test Report Annexes Bibliography 2/24/2021 K.K. Nayak 35

35. कभी कभी हमने अपने दिल को यु बहलाया है । जिन बातो को हम नही समझे औरो को समझाया है ।। 2/24/2021 K.K. Nayak 36

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