Validation, method accuracy

Method validation Accuracy three levels in triplicate (70,100, and 130% of... 

FIGURE 6.7 Total error (TE) and precision of validation samples. Data from inter day method validation accuracy and precision runs. The standards were in buffer. Five levels of VS were prepared in buffer and in sample matrix. Open squares TE% in buffer solid squares CV% in buffer open circles TE% in matrix solid circles CV% in matrix. 

Swartz, M. and Krull, I., Analytical method validation Accuracy in quantitation. LC-GC, 23, 46 (2005). 

In this article, an analytical method is defined as series of procedures from receipt of a sample to final determination of the residue. Validation is the process of verifying that a method is fit for purpose. Typically, validation follows completion of the development of a method. Validated analytical data are essential for monitoring of pesticide residues and control of legal residue limits. Analysts must provide information to demonstrate that a method intended for these purposes is capable of providing adequate specificity, accuracy and precision, at relevant analyte concentrations and in all matrices analyzed. 

Once the determinative or confirmatory method has been developed to take full advantage of the chemical properties of the analyte molecule, a study is necessary to prove that the method is valid. Criteria for method validation are outlined in guidelines from the US FDA, US EPA, and EU. A summary of the differences in regulatory requirements for method validation is provided in Table 3. The parameters addressed by all of the regulatory guidelines include accuracy, precision, sensitivity, specificity, and practicability. 

Once you have confidence that your method is adequate from the preliminary work in the method tryout, you are ready to begin the method validation. The method validation provides additional data on accuracy and precision, and confirms that there are no problems due to interference. Method validation must be completed before beginning the analysis of the treated samples from the field. The validation should test the detector s response over the expected range of concentrations from the field. 

For non-compendial procedures, the performance parameters that should be determined in validation studies include specificity/selectivity, linearity, accuracy, precision (repeatability and intermediate precision), detection limit (DL), quantitation limit (QL), range, ruggedness, and robustness [6]. Other method validation information, such as the stability of analytical sample preparations, degradation/ stress studies, legible reproductions of representative instrumental output, identification and characterization of possible impurities, should be included [7], The parameters that are required to be validated depend on the type of analyses, so therefore different test methods require different validation schemes. 

The near-IR technique has been used very successfully for moisture determination, whole tablet assay, and blending validation [23]. These methods are typically easy to develop and validate, and far easier to run than more traditional assay methods. Using the overtone and combination bands of water, it was possible to develop near-IR methods whose accuracy was equivalent to that obtained using Karl-Fischer titration. The distinction among tablets of differing potencies could be performed very easily and, unlike HPLC methods, did not require destruction of the analyte materials to obtain a result. 

Also, according to these regulations [21 CFR 211.194(a)(2)], users of analytical methods described in the USP and the NF are not required to validate accuracy and reliability of these methods, but merely verify their suitability under actual conditions of use... ... 

Rozet, E., Wascotte, V., Lecouturier, N., Preat, V., Dewe, W., Boulanger, B., Hubert, P. Improvement of the decision efficiency of the accuracy profile by means of a desirability function for analytical methods validation application to a diacetyl-monoxime colorimetric assay used for the... 

Method validation is the process of proving that an analytical method is acceptable for its intended purpose. Many organizations provide a framework for performing such validations (ASTM, 2004). In general, methods for product specifications and regulatory submission must include studies on specificity, linearity, accuracy, precision, range, detection limit, and quantitation limit. 

Further discussion of method validation can be found in Chapter 7. However, it should be noted from Table 11 that it is frequently desirable to perform validation experiments beyond ICH requirements. While ICH addresses specificity, accuracy, precision, detection limit, quantitation limit, linearity, and range, we have found it useful to additionally examine stability of solutions, reporting threshold, robustness (as detailed above), filtration, relative response factors (RRF), system suitability tests, and where applicable method comparison tests. 

Analytical data generated in a testing laboratory are generally used for development, release, stability, or pharmacokinetic studies. Regardless of what the data are required for, the analytical method must be able to provide reliable data. Method validation (Chapter 7) is the demonstration that an analytical procedure is suitable for its intended use. During the validation, data are collected to show that the method meets requirements for accuracy, precision, specificity, detection limit, quantitation limit, linearity, range, and robustness. These characteristics are those recommended by the ICH and will be discussed first. 

Apart from the qualification dossiers provided by vendors there seems, at present, to be very little information published on the performance of an operational qualification for capillary electrophoresis (CE) instruments other than a chapter in Analytical Method Validation and Instrument Performance. The chapter, written by Nichole E. Baryla of Eli Lilly Canada, Inc, discusses the various functions (injection, separation, and detection) within the instrument and provides guidance on the type of tests, including suggested acceptance criteria, that may be performed to ensure the correct working of the instrument. These include injection reproducibility and linearity, temperature and voltage stability, detector accuracy, linearity, and noise. 

HPLC methods can usually be transferred without many modifications, since most commercially available HPLC instruments behave similarly. This is certainly true when the columns applied have a similar selectivity. One adaptation, sometimes needed, concerns the gradient profiles, because of different instrumental or pump dead-volumes. However, larger differences exist between CE instruments, e.g., in hydrodynamic injection procedures, in minimum capillary lengths, in capillary distances to the detector, in cooling mechanisms, and in the injected sample volumes. This makes CE method transfers more difficult. Since robustness tests are performed to avoid transfer problems, these tests seem even more important for CE method validation, than for HPLC method validation. However, in the literature, a robustness test only rarely is included in the validation process of a CE method, and usually only linearity, precision, accuracy, specificity, range, and/or limits of detection and quantification are evaluated. Robustness tests are described in references 20 and 59-92. Given the instrumental transfer problems for CE methods, a robustness test guaranteeing to some extent a successful transfer should include besides the instrument on which the method was developed at least one alternative instrument. 

Step 5 Off-line method or analyzer development and validation This step is simply standard analytical chemistry method development. For an analyzer that is to be used off-line, the method development work is generally done in an R D or analytical lab and then the analyzer is moved to where it will be used (QA/ QC lab, at-line manufacturing lab, etc.). For an analyzer that is to be used on-line, it may be possible to calibrate the analyzer off-line in a lab, or in situ in a lab reactor or a semiworks unit, and then move the analyzer to its on-line process location. Often, however, the on-line analyzer will need to be calibrated (or recalibrated) once it is in place (see Step 7). Off-line method development and validation generally includes method development and optimization, identification of appropriate check samples, method validation, and written documentation. Again, the form of the documentation (often called the method or the procedure ) is company-specific, but it typically includes principles behind the method, equipment needed, safety precautions, procedure steps, and validation results (method accuracy, precision, etc.). It is also useful to document here which approaches did not work, for the benefit of future workers. 

While methods validation and accuracy testing considerations presented here have been frequently discussed in the literature, they have been included here to emphasize their importance in the design of a total quality control protocol. The Youden two sample quality control scheme has been adapted for continuous analytical performance surveillance. Methods for graphical display of systematic and random error patterns have been presented with simulated performance data. Daily examination of the T, D, and Q quality control plots may be used to assess analytical performance. Once identified, patterns in the quality control plots can be used to assist in the diagnosis of a problem. Patterns of behavior in the systematic error contribution are more frequent and easy to diagnose. However, pattern complications in both error domains are observed and simultaneous events in both T and D plots can help to isolate the problems. Point-by-point comparisons of T and D plots should be made daily (immediately after the data are generated). Early detection of abnormal behavior reduces the possibility that large numbers of samples will require reanalysis. 

Accuracy expresses the closeness of a result to the true value. Accuracy = trueness + precision. Under specific conditions it is quantified by the measurement uncertainty. Measurement uncertainty may vary under changing conditions and method validation determines the degree. 

Method validation seeks to quantify the likely accuracy of results by assessing both systematic and random effects on results. The properly related to systematic errors is the trueness, i.e. the closeness of agreement between the average value obtained from a large set of test results and an accepted reference value. The properly related to random errors is precision, i.e. the closeness of agreement between independent test results obtained under stipulated conditions. Accnracy is therefore, normally studied as tmeness and precision. 

Figure 5.1 shows the various characteristics and stages in a method validation program. For most quantitative methods of analysis, the method characteristics that require evaluation are accuracy, sensitivity, selectivity, precision and method limitations. Each of these characteristics have contributions from various effects, all of which require consideration within a method validation study. 

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. 

The precision and accuracy of the overall method was assessed by collecting and analyzing three sets of samples from test atmospheres of known concentration. An overall coefficient of variation of 10% for all analytical data and accuracy of 10% was required for method validation. 

Execution of the method validation protocol should be carefully planned to optimize the resources and time required to complete the full validation study. For example, in the validation of an assay method, linearity and accuracy may be validated at the same time as both experiments can use the same standard solutions. A normal validation protocol should contain the following contents at a minimum ... 

The roles of method validation in the achievement of reliable results are (1) to include all possible effects or factors of influence on the final result, (2) to make them traceable to stated references [reference methods, reference materials, or International System of Units (SI)], and (3) to know the uncertainties associated with each of these effects and with the references. Validation is thus a tool to establish traceability to these references [2,4]. In this context, it is important to see the difference between traceability and accuracy. A method which is accurate, in terms of true (i.e., approximating the true value), is always traceable to what is considered to be the true value. The opposite however is not correct. A method that is traceable to a stated reference is not necessarely true (accurate). Errors can still occur in this method, depending on the reference [12]. 

The error of an analytical result is related to the (in)accuracy of an analytical method and consists of a systematic component and a random component [14]. Precision and bias studies form the basis for evaluation of the accuracy of an analytical method [18]. The accuracy of results only relates to the fitness for purpose of an analytical system assessed by method validation. Reliability of results however has to do with more than method validation alone. MU is more than just a singlefigure expression of accuracy. It covers all sources of errors which are relevant for all analyte concentration levels. MU is a key indicator of both fitness for purpose and reliability of results, binding together the ideas of fitness for purpose and quality control (QC) and thus covering the whole QA system [4,37]. 

The ISO definition of validation is confirmation by examination and provision of objective evidence that the particular requirements of a specified intended use are fulfilled [15]. Method validation is needed to confirm the fitness for purpose of a particular analytical method, that is, to demonstrate that a defined method protocol, applicable to a specified type of test material and to a defined concentration rate of the analyte —the whole is called the analytical system — is fit for a particular analytical purpose [4]. This analytical purpose reflects the achievement of analytical results with an acceptable standard of accuracy. An analytical result must always be accompanied by an uncertainty statement, which determines the interpretation of the result (Figure 6). In other words, the interpretation and use of any measurement fully depend on the uncertainty (at a stated level of confidence) associated with it [8]. Validation is thus the tool used to demonstrate that a specific analytical method actually measures what it is intended to measure and thus is suitable for its intended purpose [11,55,56]. 

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