Validation, method linearity

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... 

The trend logio(CV) vs logjo(c) appears reasonably linear (compare this with Ref. 177 some points are from the method validation phase where various impurities were purposely increased in level). A linear regression line B) is used to represent Ae average trend (slope = -0.743). The target level for any given impurity is estimated by a simple model. Because the author-... 

As may be seen from Figure 3, first order plots based on the conversions obtained by both methods were linear with slopes in close agreement. The apparent rate constant is 0.57 h"1 based on H2 evolution and 0.54 h"1 based on the formation of glycine salt thereby indicating that it is valid to use the simpler H2 evolution measurements when measuring the effects of process variables on the reaction. 

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. 

Regarding OQ validation, if one has only an isocratic pump available, it is recommended that one does not perform a detector linearity test at this time. However, this test can be subsequently performed as part of either the PQ validation or individual method validation, both of which typically test the performance of the system as a whole (holistically). 

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. 

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 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. 

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. 

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). 

The method s performance characteristics should be based on the intended use of the method. For example, if the method will be used for qualitative trace-level analysis, there is no need to test and validate the method s linearity over the full dynamic range of the equipment. Initial parameters should be chosen according to the analyst s best judgment. Finally, parameters should be agreed upon between the lab generating the data and the client using the data. 

Method validation is important to ensure that the analytical method is in statistical control. A method may be validated by the so-called method evaluation function (MEF) (Christensen et al., 1993), which is obtained by linear regression analysis of the measured concentrations versus the true concentrations. A true concentration in a solution can be obtained by use of a high purity standard obtained from another manufacturer or batch than the one used for calibration. Both the high purity standard and the solvent are weighed using a traceable calibrated balance. If certified reference material is available this is preferred. The method evaluation includes the most important characteristics of the method as the following elements (see Figure 2.7) ... 

Lin and Wu [137] established a simple capillary zone electrophoresis method for the simultaneous analysis of omeprazole and lansoprazole. Untreated fused-silica capillary was operated using a phosphate buffer (50 mM, pH 9) under 20 kV and detection at 200 nm. Baseline separation was attained within 6 min. In the method validation, calibration curves were linear over a concentration range of 5-100 /iM, with correlation coefficients 0.9990. RSD and relative error were all less than 5% for the intra- and interday analysis, and all recoveries were greater than 95%. The limits of detection for omeprazole and lansoprazole were 2 fiM (S/N = 3, hydroxynamic injection 5 s). The method was applied to determine the quality of commercial capsules. Assay result fell within 94—106%. 

Keywords Traceability Linear calibration Method validation... 

Before a new analytical method or sample preparation technique is to be implemented, it must be validated. The various figures of merit need to be determined during the validation process. Random and systematic errors are measured in terms of precision and bias. The detection limit is established for each analyte. The accuracy and precision are determined at the concentration range where the method is to be used. The linear dynamic range is established and the calibration sensitivity is measured. In general, method validation provides a comprehensive picture of the merits of a new method and provides a basis for comparison with existing methods. 

The absorption of pantoprazole at 295 nm was used for the quantitative determination, and the method validated and used for the analysis of pantoprazole in its tablets. The results of validation study indicated that the method is linear over the range of 1.0 to 3.0 mg/mL (r= 0.9999). The percent recovery and relative standard deviation were 99.3-101.5 (n=9), and less than 1.0%, respectively. This method can be used for quality control and routine analysis [5],... 

Once an analytical method (e.g., LC/MS/MS) is established, it is necessary to qualify or validate the procedure from a regulatory GLP perspective. The desired criteria for method validation/qualification include determining the lower and upper LOQ, inter- and intraday precision, specificity of the method, and linearity of the calibration curves (166). Validation/qualification must be performed in the presence of the representative biological matrix that will be used in reaction phenotyping. For CYP reaction phenotyping studies, the matrix of choice is a pool of human liver microsomes (166). 

Method validation includes determination of performance characteristics such as selectivity (which determines accuracy), linearity, precision, and sensitivity (limit of detection). This work evaluated linearity, precision, and sensitivity for specific CZE separation conditions selectivity was reported previously (15). Factors that contribute to assay imprecision by affecting peak shape (such as the pH of the mobile phase) or migration velocity (pH effects on the electrophoretic velocity) were evaluated also. 

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