Testing, in method validation

Many experts in Europe have tested the methods of both standards with various pesticide-matrix combinations in their own laboratories. Consequently, the responsible working groups of CEN TC 275 concluded that these are the best methods available. Nevertheless, there is no complete validation of all possible pesticide-matrix combinations. However, for most multi-residue methods within the standards all those pesticides which had been successfully tested in method validation trials and/or proficiency tests are listed. Also, matrices which had been examined in ring tests are listed. 

Guidance for robustness/mggedness tests in method validation. J. Pharm. Biomed. Anal. 24, 723-753. 

Y.V. Heyden, A. Nijhuis, J. Smeyers-Verbeke, B.G.M. Vandeginste, D.L. Massart, Guidance for robustness/ruggedness tests in method validation, J. Pharm. Biomed. Anal. 24 (2001) 723. 

Vander Heyden, Y., Nijhuis, A., Smeyers-Verbeke, J., Vandeginste, B. G. M. and Massart, D. L. Guidance for robustness/ru edness tests in method validation.. Pharm. Biomed. Anal. 24 723-754, 2001. 

Even if most examples and procedures presented apply to in-house validation, the procedure does not distinguish between validations conducted in a single laboratory and those carried out within inter-laboratory method performance studies. A preference for inter-laboratory studies can be concluded from the statement that laboratories should always give priority to methods which have been tested in method performance studies. Within the procedure a profound overview of different categories of analytical methods according to the available documentation and previous external validation is given. For example, if a method is externally validated in a method performance study, it should be tested for trueness and precision only. On the other hand, a full validation is recommended for those methods which are published in the scientific literature without complete presentation of essential performance characteristics (Table 9). 

Table 14 can be regarded as providing a reasonable overall picture, even if the results cannot applied to any particular case. However, if the underlying principle is accepted, it becomes clear that improvements in a single stage, for example the reduction of instrument variation, has a negligible beneficial effect (if this variation was not outside the normal range ). Even if the contribution of repeatability is re-duced to zero, the cumulative uncertainty is reduced by 10% only, i.e. from 2.2 to y(0.0)2 (0.8)2 (1.0)2 + (1.5)2 = 2.0. This statistical view of errors should help to avoid some unnecessary efforts to improve, e.g., calibration. Additionally, this broad view on all sources of error may help to detect the most important ones. Consequently, without participation in proficiency tests, any method validation will remain incomplete. 

The basic criterion for successful validation was that a method should come within 25% of the "true value" at the 95% confidence level. To meet this criterion, the protocol for experimental testing and method validation was established with a firm statistical basis. A statistical protocol provided methods of data analysis that allowed the accuracy criterion to be evaluated with statistical parameters estimated from the laboratory test data. It also gave a means to evaluate precision and bias, independently and in combination, to determine the accuracy of sampling and analytical methods. The substances studied in the second phase of the study are summarized in Table I. 

Any or all of these conditions can be varied. To provide some guidance, intralaboratory reproducibility is used to express changes only within a laboratory, and interlaboratory reproducibility" is used to refer to the changes that occur between laboratories, for example in proficiency testing, interlaboratory method validation studies, and the like. Interlaboratory reproducibility is usually two to three times the repeatability. 

If there is any doubt about whether 100% of the analyte is presented to the measuring system or that the response of the calibrated system leads to no bias, then the assumptions must be tested during method validation and appropriate actions taken. If a series of measurements of a CRM (not used for calibration) leads to the conclusion that there is significant bias in the observed measurement result, the result should be corrected, and the measurement uncertainty should include the uncertainty of the measurement of the bias. If the bias is considered insignificant, no correction need be made, but measuring the bias and concluding that it is zero adds uncertainty (perhaps the bias was not really zero but is less than the uncertainty of its measurement). One approach to measurement uncertainty is therefore to include CRMs in the batch to be used to correct for bias, and then the uncertainty of estimation of bias, which includes the uncertainty of the quantity value of the CRM, is combined with the within-laboratory reproducibility. In some fields of analysis it is held that routine measurement and correction for bias... 

System suitability. During the robustness testing of method validation, critical method parameters such as mobile phase composition and column temperature are varied to mimic the day-to-day variability. Therefore, the system suitability results from these robustness experiments should reflect the expected range for the system suitability results. As a result, system suitability results in these method validation experiments are very useful in determining the system suitability... 

Rotational Speed. The rotational speed of a basket or paddle is an important consideration in the development and validation of the dissolution test. A speed of 100 rpm is commonly used with the basket apparatus and a speed of 50 rpm is used with paddles. In method validation, one needs to ensure that slight variations in rotational speed will not affect the outcome of the dissolution test. The compendial limit for variations in rotational speed is 4%, but a wider variation (e.g., 10%) may be considered in testing the robustness of the method. 

NARL test methods include details of how traceability was established at the time the method was validated. Provided that the documented test method is followed, and all critical control points are addressed, measurements made using the test method will correctly identify and selectively and accurately measure the analyte of interest. Such measurements are traceable to the standards used in method validation and the calibration processes. For the test methods used in homogeneity testing of study samples, traceability of chemical measurements is maintained by ... 

Once the method is vahdated, any modification requires revalidation to demonstrate that it still works as defined. If the new parameter is within the tolerance range of the method as specified during the ruggedness test of method validation, the method does not need to be revalidated. In other cases, it should go through revalidation. With the system suitability software frequently offered by analytical equipment vendors, methods can be automatically revalidated with little operator interaction. The validation can be performed overnight. 

Establishment of Common Protocols and Standard Operating Procedures It is essential that all factors relevant to the conduct of the alternative method that may affect the results, the collection of data, and interpretation of the alternative method results be clearly defined before the study begins. These are best documented in the study protocol and SOPs that define the alternative methods. In order to assess the adequacy of the SOPs, they should be examined to determine if they contain three key elements. First, each SOP must have a detailed step-by-step description of how to conduct the assay. Enough details need to be provided such that any appropriately trained and competent laboratory technician need use only this document as the guide to run the assay. Second, the SOP must indicate the steps used to calculate the endpoint of the assay and the number of replicates necessary. Any data transformation or algorithms applied to the data should be clearly documented and consistently applied across all laboratories conducting a particular assay. Third, the protocol must specifically describe the prediction model being tested in the validation study. 

Validation of a method involves running assays on aliquots from the same sample a number of times and ideally is done over a well-balanced design of all the external factors effecting performance. If, for example, more than one machine could be used for the method in question then, ideally, all machines should be tested in the validation. In a similar manner, the validation should be run over a number of days... 

Experiment 39 provides practice in method validation and quality control, and Experiment 40 is an exercise in proficiency testing. These are class team experiments. Read these, even if they are not part of your assigned laboratory exercises. 

An interesting and useful classification of steps used to assure quality of analytical data (Bansal 2004) has drawn a clear distinction between quahfication of apparatus used to obtain the data and validation of the methods developed to use the apparatus to obtain the data pertinent to a particular analytical problem. Overlaid on this distinction is another, that between tests that must be completed satisfactorily before acquisition of the desired analytical data can begin (instrument quahfication and method vah-dation) on the one hand, and those that are conducted immediately before or simultaneously with data acquisition (system suitability and quahty control checks) on the other. The original paper (Bansal 2004) represented the outcome of a workshop intended to fiU a need for a more detailed scientific approach to what was termed Analytical Instrument Quahfication (AIQ) , particularly in the context of applications in the pharmaceutical industry. Note in particular that qualification of both hardware and software plays an important role in method validation. 

The purpose of method validation is to demonstrate that an analytical method is suitable for its intended purpose and, for a quantative method, provides a reasonable estimate of the true value of the sample tested. Appropriate performance characteristics, such as accuracy and precision, must be demonstrated before making decisions based on test data. Method validation involves assessing method performance against predefined criteria, established based on the sample specifications and the type of measurement to be performed, for example, assay, identification, or limit test. A rigorous assessment of method performance versus predefined criteria provides assurance that the method will consistently provide a fit for purpose performance. Method characteristics to be evaluated during method validation are described by several guidelines [1,2] some of which are shown in Tables 3.1 and 3.2. 

By proceeding this way, it is very probable that the result of the integration of the chromatographic peak will be compatible with the use of the validated response function. Proceeding in this manner is legitimate only if one has previously performed tests during method validation to verify that dilution of the sample does not alter the result of the dosage. 

The last step in establishing a standard method is to validate its transferability to other laboratories. An important step in the process of validating a method is collaborative testing, in which a common set of samples is analyzed by different laboratories. In a well-designed collaborative test, it is possible to establish limits for the method s precision and accuracy. 

Many of the better known shortcut equipment design methods have been derived by informed assumptions and mathematical analysis. Testing in the laboratory or field was classically used to validate these methods but computers now help by providing easy access to rigorous design calculations. 

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