Analytical validation method performance

Insufficient testing is one of the major causes of method failure. The amount of data needed to publish a new procedure in a peer-reviewed journal and the procedural detail supplied therein are often insufficient to allow a different user to validate a method rapidly. The developer should evaluate if the method will work using chemicals, reagents, solid-phase extraction columns, analytical columns, and equipment from various vendors. Separate lots of specific supplies within a vendor should be evaluated to determine if lot-to-lot variation significantly impacts method performance. Sufficient numbers of samples should be assayed to estimate the lifetime of the analytical column and to determine the effects of long-term use on the equipment. 

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). 

To reduce the effort, another validation procedure is used for extension of the German multi-residue method to a new analyte. Actually, more than 200 pesticides can be analyzed officially with this method, which is the up-to-date version of the better known method DFG SI9. A typical validation is performed by at least three laboratories, which conduct fortification experiments at the same three levels with at least four representative matrices. These representative matrices are commodities with high water content (e.g., tomato), fruits with high acid content (e.g., lemon), dry crops (e.g., cereals) and commodities with high fat content (e.g., avocado). 

In a widely accepted definition, an analytical method can be defined as the series of procedures from receipt of a sample to the production of the final result. Often, not all procedures can be validated in an adequate way. However, even in such cases, where all procedures of a method are validated, the performance characteristics obtained do not reflect all sources of error. In a recent paper,the complete ladder of errors is described in the following way ... 

A final point is the value of earlier (old) validation data for actual measurements. In a study about the source of error in trace analysis, Horwitz et al. showed that systematic errors are rare and the majority of errors are random. In other words, the performance of a laboratory will vary with time, because time is related to other instruments, staff, chemicals, etc., and these are the main sources of performance variation. Subsequently, actual performance verification data must be generated to establish method performance for all analytes and matrices for which results will be reported. 

In the OPMBS, the lead laboratory developed the analytical method for all analytes in ah commodities. The same laboratory validated the method for each commodity, to demonstrate that all the specific analytes for the commodity could be determined in accordance with analytical quality specifications. The method was then provided to the other three laboratories, each of which validated the method for its assigned commodities, to ensure that the method performed properly using the laboratory s equipment and personnel. 

Few well characterized, validated methods are available for the determination of w-hexane in blood. A purge-and-trap method for volatiles has been developed and validated by researchers at the Centers for Disease Control and Prevention (CDC) (Ashley et al. 1992, 1994). Extension of the method to include /7-hexane should be possible. Current analytical methods utilize capillary GC columns and MS detection to provide the sensitivity and selectivity required for the analysis. Detection limits are in the low ppb range (Brugnone et al. 1991 Schuberth 1994). Headspace extraction followed by GC analysis has also been utilized for the determination of /7-hexanc in blood (Brugnone et al. 1991 Michael et al. 1980 Schuberth 1994) however, very little performance data are available. 

The ability to provide accurate and reliable data is central to the role of analytical chemists, not only in areas like the development and manufacture of drugs, food control or drinking water analysis, but also in the field of environmental chemistry, where there is an increasing need for certified laboratories (ISO 9000 standards). The quality of analytical data is a key factor in successfully identifying and monitoring contamination of environmental compartments. In this context, a large collection of methods applied to the routine analysis of prime environmental pollutants has been developed and validated, and adapted in nationally or internationally harmonised protocols (DIN, EPA). Information on method performance generally provides data on specificity, accuracy, precision (repeatability and reproducibility), limit of detection, sensitivity, applicability and practicability, as appropriate. 

By using the combination of specific method accreditation and generic accreditation it will be possible for laboratories to be accredited for all the analyses of which they are capable and competent to undertake. Method performance validation data demonstrating that the method was fit-for-purpose shall be demonstrated before the test result is released and method performance shall be monitored by on-going quality-control techniques where applicable. It will be necessary for laboratories to be able to demonstrate quality-control procedures to ensure compliance with the EN 45001 Standard,3 an example of which would be compliance with the ISO/AOAC/IUPAC Guidelines on Internal Quality Control in Analytical Chemistry Laboratories.12... 

QC tests are carried out according to validated analytical methods or established methods from pharmacopoeias US Pharmacopoeia and British Pharmacopoeia. Exhibit 10.2 lists some of the QC analytical methods performed on drug intermediates and products. 

As shown in Figure 11, before extensive validation, the performance of the method is evaluated appropriately. Column durability tests, robustness testing for the chromatographic and sample preparation conditions, analytical method evaluation ring tests (AMERTs), method capability assessments, and pre-validation studies are applied to... 

A validation protocol adapted from the experiences during the method development defines the scope of the validation study (goal of the study, regulating guidelines, key method parameters, etc.). To investigate the adequate method performance, these features (e.g., range of analyte concentration), together with a statement of any fitness-for-purpose criteria, have to be specified in the validation protocol. A basic check has to provide that the reasonable assumptions about the principles of the method are not seriously flawed. In this process, sources of error in analysis have to be listed (Table 4) and their effects have to be checked. The validation should, as far as possible, be conducted to provide a realistic survey of the number... 

It is required for quantitative purity assays, and it must be established across the specified range of the analytical procedure. This can be done, by establishing the recovery rate over the range of the method. Alternatively, a method comparison between a validated method and a new method can be performed. Accuracy can be determined by spiking degraded, aggregated, pure or impure material into a known amount of sample. A theoretical recovery would then be calculated and the spike material analyzed using the chosen method. The actual recovery should then be compared to the theoretical recovery to calculate the accuracy of the method. Accuracy in this case would be reported as percent recovery. 

Quantitative CE—MS studies were scarcely reported. " This subject is however of prime importance, particularly for the pharmaceutical industry where the reliability of analytical data is essential. For this reason, method development is generally followed by an evaluation of quantitative performance using an appropriate validation procedure performed in agreement with criteria established by the International Conference on Harmonisation of technical requirements for registration of pharmaceuticals for human use (ICH) and the Food and Drug Administraction (FDA) guidelines, or Societe Franqaise des Sciences et Techniques Pharmaceutiques (SFSTP) commissions. ... 

A method should be validated when it is necessary to verify that the performance parameters are adequate for use for a particular analytical problem. Method validation is required in circumstances such as those indicated in this slide. 

Quality Assurance/Quality Control. QA/QC measures included field blanks, solvent blanks, method blanks, matrix spikes, and surrogates. Percent recovery was determined using three surrogate compounds (nitrobenzene-d5, 2-fluorobiphenyl, d-terphenyl-diQ and matrix spikes (naphthalene, pyrene, benzo[ghi]perylene) the recoveries ranged from 80 to 102%. Separate calibration models were built for each of the 16 PAHs using internal standards (naphthalene-dg, phenanthrene-dio, perylene-di2). Validation was performed using a contaminated river sediment (SRM 1944) obtained from NIST (Gaithersburg, MD) accuracy was <20% for each of the 16 analytes. 

Traceability and MU both form parts of the purpose of an analytical method. Validation plays an important role here, in the sense that it confirms the fitness-for-purpose of a particular analytical method [4]. 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 [7]. Validation is 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 [2,11]. In Section 8.2.3, the classical method validation approach is described based on the evaluation of a number of method performance parameters. Summarized, the cri-teria-based validation process consists of precision and bias studies, a check for... 

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]. 

Validation of a new analytical method is typically done at two levels. The first is the level of prevalidation, aiming at fixing the scope of the validation. The second level is an extensive, full validation performed through a collaborative trial or interlaboratory study. The objective of full validation, involving a minimum number of laboratories, is to demonstrate that the method performs as was stated after the prevalidation. 

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. 

In practice, data from method validation and collaborative studies form the basis for but are only a part of MU estimation. MU is thus more than just a method performance parameter, as described extensively in Section 8.2.2. Over the years, the concept of MU has won attention in all analytical areas and this has led to two different approaches currently accepted and used for analytical method validation. 

Extent of Validation Depends on Type of Method On the one hand, the extent of validation and the choice of performance parameters to be evaluated depend on the status and experience of the analytical method. On the other hand, the validation plan is determined by the analytical requirement(s) as defined on the basis of customer needs or as laid down in regulations. When the method has been fully validated according to an international protocol [63,68] before, the laboratory does not need to conduct extensive in-house validation studies. It must only verify that it can achieve the same performance characteristics as outlined in the collaborative study. As a minimum, precision, bias, linearity, and ruggedness studies should be undertaken. Similar limited vahdation is required in cases where it concerns a fully validated method which is apphed to a new matrix, a well-established but noncol-laboratively studied method, and a scientifically pubhshed method with characteristics given. More profound validation is needed for methods pubhshed as such in the literature, without any characteristic given, and for methods developed in-house [84]. 

One or more of these bias components are encountered when analyzing RMs. In general, RMs are divided into certified RMs (CRMs, either pure substances/solu-tions or matrix CRMs) and (noncertified) laboratory RMs (LRMs), also called QC samples [89]. CRMs can address all aspects of bias (method, laboratory, and run bias) they are defined with a statement of uncertainty and traceable to international standards. Therefore, CRMs are considered useful tools to achieve traceability in analytical measurements, to calibrat equipment and methods (in certain cases), to monitor laboratory performance, to validate methods, and to allow comparison of methods [4, 15, 30]. However, the use of CRMs does not necessarely guarantee trueness of the results. The best way to assess bias practically is by replicate analysis of samples with known concentrations such as reference materials (see also Section 8.2.2). The ideal reference material is a matrix CRM, as this is very similar to the samples of interest (the latter is called matrix matching). A correct result obtained with a matrix CRM, however, does not guarantee that the results of unknown samples with other matrix compositions will be correct [4, 89]. 

Use of Validated Methods In-Home Versus Interlaboratory Validation Wherever possible or practically achievable, a laboratory should use methods which have been fully validated through a collaborative trial, also called interlaboratory study or method performance study. Validation in collaborative studies is required for any new analytical method before it can be published as a standard method (see below). However, single-laboratory validation is a valuable source of data usable to demonstrate the fitness for purpose of an analytical method. In-house validation is of particular interest in cases where it is inconvenient or impossible for a laboratory to enter into or to organize itself a collaborative study [4,5]. 

Use of Standardized Methods The first level of AQA is the use of validated or standardized methods. The terms validated and standardized here refer to the fact that the method performance characteristics have been evaluated and have proven to meet certain requirements. At least, precision data are documented, giving an idea of the uncertainty and thus of the error of the analytical result. In both validated and standardized methods, the performance of the method is known. 

Together with the fast development of analytical methodologies, great importance is nowadays attached to the quality of the measurement data. Besides the necessary reporting of any result with its MU and traceability of the results to stated standards or references (Section 8.2.2), a third crucial aspect of analytical methods of whichever type is their status of validation. It is internationally recognized that validation is necessary in analytical laboratories. However, less is known about what is validation and what should be validated, why validation is important, when and by whom validation is performed, and finally, how it is carried out practically. This Chapter has tried to answer these questions. 

Analytical potency method development should be performed to the extent that it is sufficient for its intended purpose. It is important to understand and know the molecular structure of the analyte during the method development process, as this will facilitate the identification of potential degradation impurities. For example, an impurity of M + 16 in the mass spectrum of a sample may indicate the probability of a nitrogen oxide formation. Upon successful completion of method development, the potency method will then be validated to show proof that it is suitable for its intended purpose. Finally, the method validated will be transferred to the quality control laboratory in preparation for the launch of the drug substance or drug product. 

Performance characteristics of residue methods are often only determined for major food animal species. The Joint FAO/IAEA Expert Consultation on Validation of Analytical Methods for Food Control (17) has discussed the issue of the availability of suitable analytical methods for determining compliance of residues in tissues of the so-called minor species with established MRLs. The Consultation has concluded that if metabolism and related pharmacokinetic data are similar in minor species to those in major species, only the recovery of the analytes in the minor species needs to be determined. If the recovery remains stable, there is no need to study the method performance any further. If the recovery is not stable the full set of performance data should be determined. 

Although a thorough validation cannot rule out all potential problems, the process of method development and validation would address the most common ones. Examples of typical problems that can be minimized or avoided include interferences that coelute with the analyte in liquid chromatography (LC), a particular type of column that no longer produces the separation needed because the supplier of the column has changed the manufacturing process, an assay method that is unable to achieve the same detection limit after a few weeks, or a quality assurance audit of a validation report that finds no documentation on how the validation was performed. 

Apart from establishing analytical validation parameters, other activities should include experimental optimization of each procedural step or method manipulation to determine the critical control steps that have a substantial impact on method performance. The ruggedness or process variability that may be employed in any particular method step, without reducing method performance, should be determined. It should be identified, for example, whether an analytical method may be stopped without adversely affecting the result. 

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