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Transcript of method validation
Venue: UP Diliman, Institute of Chemistry
Quezon City Quality Measurement in the Analytical Laboratory:
A Hands-on Approach Objectives of Validation Definition of validation What is Method Validation?
Confirmation by examination and provision of objective evidence that the particular requirements for a specified intended use are fulfilled."
There is an increasing concern on the quality of chemical analysis data. The results of chemical analysis are used as the basis for important decisions on the acceptability of materials and products, or on the ensuing measures to be carried out. The soundness of the decision depends on the integrity of the analysis data presented.
It is therefore important that the method for the analysis to be done will yield reliable results. The method has to be validated and proven to fit the purpose of the chemical analysis. Method validation provides a systematic process for establishing and providing guarantee on the quality of the data that will be obtained. METHOD VALIDATION The reliability of analytical data is important as measurement results will be used and or form the basis for decision-making. ISO 8402: 1994 and
ISO/IEC 17025: 2005 cl. 188.8.131.52
to equip the participants with the basic knowledge and skills needed to carry out the process of method validation.
to enable the participants to identify and implement the appropriate type of method validation studies, including the parameters and the acceptability criteria to be considered.
to engender a more meaningful usage of computer methods for the statistical analysis of data and calculation of the method performance characteristics. Objectives Rationale STATISTICS IN MICROBIOLOGICAL ANALYSIS we see from this definition, that we have to: specify the intended use of a method define performance requirements provide data from validation experiments (objective evidence) interpret the validation data (confirmation that requirements have been fulfilled) the inner, hidden, deeper, secret meaning of method validation is = ERROR ASSESSMENT From: J.O. Westgard, Basic method validation, Westgard Quality Corporation 1999, pp 250. www.westgard.com When is Method Validation not required? to minimize analytical and instrumental errors to be assured of the correctness of the results objective evidence for defense against challenges to meet accreditation requirements to ensure the quality of the test results to give reliable and reproducible results in accordance with the given specifications for the test method Standard Methods on condition that: otherwise, required without modifications (including QA plan and reporting) used within their scope of applicability (e.g. matrices, ranges, etc.) > > > > DESCRIPTIVE STATISTICS assessment of data quality
method development and optimization
method validation using built-in functions using Analysis Toolpak -click Formulas, then insert Functions
-select AVERAGE (for the mean) or STDEV (for the standard deviation) [OK]
-highlight data [OK] -click Data, then Data Analysis
-select Descriptive Statistics [OK]
-click Input Range and highlight data
-select Summary statistics [OK] types of microbiological determinations 1) detection of any viable microorganism -
most common examples are the sterility
test and P/A of a particular type of
microorganism in a sample (e.g. coliform
in potable water)
2) quantification of the number of organisms
present-most common example is the plate
count method, others are MFT and MPN
3) identification of the number of
microorganism the limit of detection refers to the number of organisms present in the original sample before any dilution or incubation steps; it does not refer to the number of organisms present at the point of assay A microbiological limit test determines the presence or absence of microorganisms, e.g., absence of Salmonella spp. in 10 g to demonstrate equivalence between the two quantitative methods could be through the use of the Most Probable Number technique. In this method, a 5-tube design in a ten-fold dilution series could be used for both methods. These would then be challenged with equivalent inoculums (for example, a 10–1, 10–2, and 10–3 dilution from a stock suspension of approximately 50 cfu per mL to yield target inocula of 5, 0.5, and 0.05 cfu per tube) and the MPN of the original stock determined by each method. If the 95% confidence intervals overlapped, then the methods would be considered equivalent. an example being an ANOVA analysis of the log10 unit transforms of the data points Measurement Uncertainty. Calculate and document a reasonable, fit-for-purpose estimate of MU. This should form an integral part of method validation. Q1. When are you actually supposed to do the
a) when testing the suitability of the method
b) when testing the sample
c) in both situations Q2. What is the purpose
of the negative
control? Q3. When does negative
control have to be done?
a) every time the sample is tested
b) during the method validation
c) possibly do it periodically Q4. When is it necessary to test the
growth promotion on culture media?
a) check each new batch of received
b) will serve just for
microbiological validation A1.
b) you are suppose to do the
negative control at the same time
as when you are testing the
sample. A2. The purpose of the negative
control is to show that there
is no contamination during
the testing of the sample. If
a positive result is obtained
with a negative control, the
test can be regarded as
invalid and may be repeated. A3.
a) negative control should be
included every time that the
sample is tested. A4.
a) growth promotion must be checked for
each new batch of medium. Growth
promotion must be checked on agar media
and nutritive broth but not on diluted
broth. (Objective evidence can be furnished by observation, measurement, testing or in other ways) Note: the term ‘method’ includes kits, individual reagents, instruments, platforms and software. The laboratory may also verify performance characteristics for a method of analysis via participation in a performance testing programme provided that the tested material is representative of the method in terms of matrix, analytical parameters, concentration level(s), etc. This concern is adequately addressed by growth promotion of the media for qualitative methods that rely upon growth to demonstrate presence or absence of microorganisms. the limit of detection of an assay is determined from a number of replicates (not less than 5). The measure of robustness is not necessarily a comparison between the alternate method and the traditional, but rather a necessary component of validation of the alternate method so that the user knows the operating parameters of the method. Ruggedness is a validation parameter best suited to determination by the supplier of the test method who has easy access to multiple instruments and batches of components. Raw counts can be transformed to normally distributed data either by taking the log10 unit value for that count, or by taking the square root of count +1. colony-forming units follow a Poisson distribution Accuracy is usually expressed as the percentage of recovery of microorganisms by the assay method. The precision of a microbiological method is usually expressed as the standard deviation or relative standard deviation (coefficient of variation). Irrespective of the specific results, the alternate method should have a coefficient of variation that is not larger than that of the traditional method. For example, a plate count method might have the RSD ranges as shown: The limit of quantification should not be a number greater than that of the traditional method. The alternate method should not have an r2 value less than 0.95. An appropriate measure would be to calculate the square of the correlation coefficient, r2, from a linear regression analysis of the data generated False Positive Rate
False Negative Rate Validation can be classified as primary validation and secondary validation according to its purpose. Optimization involves the identification of specific factors employed in the method such as procedures, environmental conditions, and reagents most likely to introduce variability in results and the subsequent iterative testing of modifications to the method that minimize this variability. Examples of generally unavoidable sources of variability can include different analysts, lots or preparations of reagents, and calibration of instruments. Ruggedness is also defined as the ability of a method to provide acceptable results in the presence of variable factors that are unavoidable. Robustness is also defined as the ability of a method to provide acceptable results in the presence of variable factors that are avoidable. Examples of potentially avoidable sources of variability could include the use of reagents and/or instruments from different sources. ISO/IEC 17025 requires that facilities estimate and, where applicable, report the MU associated with results. Therefore the estimation of MU may be considered an essential requirement of method validation. Sensitivity
Exclusivity are the shellfish contaminated with the red tide toxin? is the glucose in a blood sample within the allowable limits? is the waste water clean enough for discharge into the river? do the products meet specifications?
related to regulatory and legal matters
used for improving the environment and community health and safety
of considerable economic significance
Data obtained from laboratory analyses are often used for making decisions. These decisions could be: Q5. For the validation of a
batch of Lauryl Sulphate
Tryptose broth, what
positive reference culture
will be used? A5.
E. coli When should a Method be Validated? new method...no previous performance history
revised or established method adopted to a new problem
when an established method is used in a different laboratory, with different analysts or with different equipment
to demonstration of the equivalence between two methods, e.g. a new method vs. a standard method Qualitative and Quantitative tests Qualitative and Quantitative tests Qualitative and Quantitative tests Quantitative and Identification tests Qualitative and Quantitative tests Quantitative and Identification tests Quantitative and Identification tests Quantitative test Quantitative test Quantitative test Quantitative and Identification tests Quantitative and Identification tests Quantitative and Identification tests Quantitative and Identification tests Qualitative, Quantitative and Identification tests