Method validation range

Typically, linearity and accuracy determination covers a wide concentration range (e.g., 50% of the ICH reporting limit to 150% of specification). However, the concentration range for precision will be limited by the availability of sample of different related substance levels. Therefore, to ensure an appropriate method validation range with respect to precision, it is critical to use samples of low and high levels of related substance in precision experiments (e.g., fresh and stressed samples). 

Validation is the determination of the attributes, or figures of merit, of an analytical method for one or more analytes in one or more sample matrices by one or more analysts in one or more analytical laboratories and the acceptance of the attributes as reasonable and useful by the users of the data. There are many levels of analytical method validation ranging from the validation of a method for a single analyte in a single matrix by a single analyst in a single laboratory to a multi-analyte, multi-matrix, multi-analyst, and multi-laboratory validation. 

During the method validation phase, the calibration, using the CS solutions, is repeated each day over at least one week to establish both the within-day and the day-to-day components of the variability. To this end, at least 6 CS, evenly spread over the concentration range, must be repeatedly run (m = 8-10 is usual), to yield n 50 measurements per day. If there are no problems with linearity and heteroscedacity, and if the precision is high (say, CV < 2-5%, depending on the context), the number of repeats m per concentration may be reduced from the second day onwards (m = 2 - 3 is reasonable). The reasoning behind... 

For multi-analyte and/or multi-matrix methods, it is not possible to validate a method for all combinations of analyte, concentration and type of sample matrix that may be encountered in subsequent use of the method. On the other hand, the standards EN1528 andEN 12393 consist of a range of old multi-residue methods. The working principles of these methods are accepted not only in Europe, but all over the world. Most often these methods are based on extractions with acetone, acetonitrile, ethyl acetate or n-hexane. Subsequent cleanup steps are based on solvent partition steps and size exclusion or adsorption chromatography on Florisil, silica gel or alumina. Each solvent and each cleanup step has been successfully applied to hundreds of pesticides and tested in countless method validation studies. The selectivity and sensitivity of GC combined with electron capture, nitrogen-phosphorus, flame photometric or mass spectrometric detectors for a large number of pesticides are acceptable. 

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. 

Method validation is needed to demonstrate the acceptability of the analytical method. A recovery test on a chemical being determined should be performed in order to verify the reliability of the series of analyses. Recovery studies are usually conducted by spiking untreated sediment with the target chemical at the deteetion limit, quantitation limit and in the range of 10-50 times the detection limit. The method is considered acceptable when the recoveries typically are greater than 70%. When the recovery is less than 70%, an improvement in the analytical methods is needed. Where this is not possible for technical reasons, then lower recovery levels may be acceptable provided that method validation has demonstrated that reproducible recoveries are obtained at a lower level of recovery. Analysis is usually done in duplicate or more, and the coefficient of variation (CV) should be less than 10% to ensure that recoveries will be consistently within the range 70-110%. 

For method tryout, run a control sample and two fortifications from each site. One fortification should be done at the LOQ and the other at the highest expected residue level, perhaps 1000 x LOQ. If the recoveries are within the acceptable range of 70-120% and there are no interferences, proceed with the method validation. If interferences are present which prevent quantitation of the analyte, try additional cleanup steps with SPE or use a more selective detection method such as liquid chromatography/mass spectrometry (LC/MS). 

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. 

Method validation is defined in the international standard, ISO/IEC 17025 as, the confirmation by examination and provision of objective evidence that the particular requirements for a specific intended use are fulfilled. This means that a validated method, if used correctly, will produce results that will be suitable for the person making decisions based on them. This requires a detailed understanding of why the results are required and the quality of the result needed, i.e. its uncertainty. This is what determines the values that have to be achieved for the performance parameters. Method validation is a planned set of experiments to determine these values. The method performance parameters that are typically studied during method validation are selectivity, precision, bias, linearity working range, limit of detection, limit of quantitation, calibration and ruggedness. The validation process is illustrated in Figure 4.2. 

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. 

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. 

Resorcinol Water solution Non-destructive quantitation method. Precision lower than 0.15% in a temperature range of 9-35 °C. Method validated using ICH-adapted guidelines 151... 

Before any method validation is started, the scope of validation must be fixed, comprising both the analytical system and the analytical requirement. A description of the analytical system includes the purpose and type of method, the type and concentration range of analyte(s) being measured, the types of material or matrices for which the method is applied, and a method protocol. On the basis of a good analysis lies a clear specification of the analytical requirement. The latter reflects the minimum fitness-for-purpose criteria or the different performance criteria the method must meet in order to solve the particular problem. For example, a minimum precision (RSD, see below) of 5% may be required or a limit of detection (LOD) of 0.1% (w/w) [2,4,15,58]. The established criteria for performance characteristics form the basis of the final acceptability of analytical data and of the validated method [58]. 

The purpose of an analytical method is the deliverance of a qualitative and/or quantitative result with an acceptable uncertainty level. Therefore, theoretically, validation boils down to measuring uncertainty . In practice, method validation is done by evaluating a series of method performance characteristics, such as precision, trueness, selectivity/specificity, linearity, operating range, recovery, LOD, limit of quantification (LOQ), sensitivity, ruggedness/robustness, and applicability. Calibration and traceability have been mentioned also as performance characteristics of a method [2, 4]. To these performance parameters, MU can be added, although MU is a key indicator for both fitness for purpose of a method and constant reliability of analytical results achieved in a laboratory (IQC). MU is a comprehensive parameter covering all sources of error and thus more than method validation alone. 

An important aspect of a full method validation is estimating bias components attributable to the method itself and to the laboratory carrying out the analysis. This step is required to estimate measurement uncertainty with a reasonable range that covers results that would be obtained in another laboratory of similar experience and standing. In chapter 5 I discussed these approaches at length. ISO (1994b) has a procedure for such interlaboratory... 

Not all methods require each parameter detailed in table 8.2 to be established. For example, a method that only measures the active ingredient in a 100-mg cold cure as part of a quality control protocol is not concerned with limit of detection, the matrix is fixed, and the calibration range might only need to be established between 80 and 120 mg. An analysis that determines the presence or absence of the target analyte needs only to establish its selectivity, limit of detection, and ruggedness. Table 8.3 details some common analytical systems with their critical method validation parameters. 

A discussion about calibration must also include consideration of singlepoint calibration and direct comparison of responses to samples of known and unknown quantities. In each case the linearity of the calibration (i.e., the correctness of taking a ratio of instrument responses) is accepted in routine work. In method validation this assumption must be verified by making a series of measurements in a concentration range near to the range used, and the linear model must be demonstrated to be correct. 

In traditional method validation, assessment of the calibration has been discussed in terms of linear calibration models for univariate systems, with an emphasis on the range of concentrations that conform to a linear model (linearity and the linear range). With modern methods of analysis that may use nonlinear models or may be multivariate, it is better to look at the wider picture of calibration and decide what needs to be validated. Of course, if the analysis uses a method that does conform to a linear calibration model and is univariate, then describing the linearity and linear range is entirely appropriate. Below I describe the linear case, as this is still the most prevalent mode of calibration, but where different approaches are required this is indicated. 

Method validation must demonstrate that the calibration model (i.e., the equation by which the instrument response is related to a known value of a standard) holds for the system under investigation, and over what range of concentrations. 

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