Analytical Method Validation Approaches

As shown elsewhere (Table 1.15 of ref. [12a]), a validated method is not the only condition for analytical excellence the sample and the experimental implementation (ISO 9000, ISO/IEC Guide 25, GLP) are equally important. The skill of the operator constitutes a critical factor in a measurement process. 

In the ICH guidelines analytical validation relates to test procedures. A test procedure is a more precise and comprehensive term than analytical method as it includes the technique, the sample and standard preparation, the use of apparatus, the formulae for calculation, etc. (cfr. Table 8.1). Validation 

Ideally, validation criteria should be compiled at different stages in the analytical procedure development, but to a different extent. It is a misconception to believe that development of an analytical procedure and validation are independent processes they are interdependent. The actions required to ensure that valid and reliable analytical measurements are being made are not trivial. Development of a procedure and validation is an iterative process. The procedure s suitability must be studied in initial validation experiments. Pre-study validation is a formal validation protocol designed to characterise the method before analysis of real samples. Prerequisite is a detailed description of the method. Acceptance criteria should be established a priori. In the validation stage, it is necessary to demonstrate that the method works with samples of the given analyte, at the expected concentration in the anticipated 

Ensures quality Part of overall quality process Demonstrates performance of method Reduces number of analyses (no duplicates) 

Good scientific practice Makes good business sense A regulatory requirement 

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Method validation, on the other hand, is normally considered part of the study in which the method will subsequently be used or consists of a separate defined study unto itself as such, it is normally required to be accomplished under GLP purview. There is, however, some confusion in some circles as to exactly what is meant by analytical method validation. Some chemists describe it as adaptation of one method from one type of matrix for use with another using basically the same or similar analytical approach. Others take a more strict interpretation and define validation as simply demonstration of the ability to achieve satisfactory results using a published procedure in one s own laboratory setting. Often, validation incorporates both interpretations. 

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... 

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. 

SOURCE J. Vial and A. Jardy, Experimental Comparison of Different Approaches to Estimate LOD and LOQ (fan HPLC Method Anal. Chem. 1999, 71, 2672 and J. M. Green, A Practical Guide to Analytical Method Validation, Anal. Chem. 1996, 68, 305A. 

Validation (policy, documentation, qualifications, approaches to process validation, periodic review of validated systems, cleaning validation, and analytical methods validation)... 

The method development life cycle parallels established approaches to analytical method validation and computer validation.Clearly, analytical... 

There have been various attempts to place the concept of detection limit on a more firm statistical ground. The International Conference on Harmonization (ICH see Chapter 4) of Technical Requirements for Registration of Pharmaceuticals for Human Use has proposed guidelines for analytical method validation (Ref. 18). The ICH Q2B guideline on validation methodology suggests calculation based on the standard deviation, s, of the response and the slope or sensitivity, S, of the calibration curve at levels approaching the limit. For the limit of detection (LOD),... 

When an analytical method is being developed, the ultimate requirement is to be able to determine the analyte(s) of interest with adequate accuracy and precision at appropriate levels. There are many examples in the literature of methodology that allows this to be achieved being developed without the need to use complex experimental design simply by varying individual factors that are thought to affect the experimental outcome until the best performance has been obtained. This simple approach assumes that the optimum value of any factor remains the same however other factors are varied, i.e. there is no interaction between factors, but the analyst must be aware that this fundamental assumption is not always valid. 

LGC - VAM Publications (i) The Fitness for Purpose of Analytical Methods, A Laboratory Guide to Method Validation and Related Topics, (2) Practical Statistics for the Analytical Scientist A Bench Guide By TJ Farrant, (3) Trace Analysis A structured Approach to Obtaining Reliable Results By E Pritchard, (4) Quantifying Uncertainty in Analytical Measurement, and (5) Quality in the Analytical Chemistry Laboratory. LGC/RSC Publications, London, England. 

Validation of the analytical methods for food of animal origin has to be performed with milk, egg, meat, and fat. The latter is required only if log Pqav is >3 and metabolism studies indicate significant residues in fat, because in this case it is likely that an MRL will be set. Other tissues such as kidney or liver must be validated only if an MRL is set or proposed for these tissues. The issue of the general necessity of analytical methods for food of animal origin is not addressed in Directive 96/46/EC or SANCO/825/00. At this moment, the Working Group Pesticide Residues proposes an MRL on a case-by-case basis. However, a pragmatic approach is presented in SANCO/825/00. 

Methods submitted by industry are partly used for implementation in national collections of analytical methods (e.g., in the German Method Collection of 35 LMBG). This activity often involves a modification of the analytical procedure and extended validation. Some examples for this approach are discussed by Lutz Alder in this Handbook. 

General approaches for residue analytical method development and validation... 

This validation typically requires samples with radiolabeled analytes. However, alternative approaches are proposed which involve (i) comparison with extraction of samples using a procedure which has been previously validated rigorously, (ii) comparison with extraction of samples by a very different technique or (iii) analysis of a certified reference material. Generally, this validation should be performed with samples containing analyte incurred by the route by which residues would normally be expected to arise. The simplest option (i) requires fully validated and documented enforcement methods provided by the manufacturer of a pesticide. 

Komit6 for Levnedsmidler (NMKL)]. The standard presents a universal validation approach for chemical analytical methods in the food sector. This includes methods for the main constituents and also for trace components. Therefore, the NMKL procedure focuses on primary validation parameters, such as specificity, calibration, trueness, precision, LOD or LOQ and does not refer to special requirements of pesticide residue analysis. 

The approaches described above give approximate values for the LoD and LoQ. This is sufficient if the analyte levels in test samples are well above the LoD and LoQ. If the detection limits are critical, they should be evaluated by using a more rigorous approach [1, 2, 14]. In addition, the LoD and LoQ sometimes vary with the type of sample and minor variations in measurement conditions. When these parameters are of importance, it is necessary to assess the expected level of change during method validation and build a protocol for checking the parameters, at appropriate intervals, when the method is in routine use. 

This chapter deals with handling the data generated by analytical methods. The first section describes the key statistical parameters used to summarize and describe data sets. These parameters are important, as they are essential for many of the quality assurance activities described in this book. It is impossible to carry out effective method validation, evaluate measurement uncertainty, construct and interpret control charts or evaluate the data from proficiency testing schemes without some knowledge of basic statistics. This chapter also describes the use of control charts in monitoring the performance of measurements over a period of time. Finally, the concept of measurement uncertainty is introduced. The importance of evaluating uncertainty is explained and a systematic approach to evaluating uncertainty is described. 

After five years as an analyst, Vicki moved within LGC to work on the DTI-funded Valid Analytical Measurement (VAM) programme. In this role, she was responsible for providing advice and developing guidance on method validation, measurement uncertainty and statistics. One of her key projects involved the development of approaches for evaluating the uncertainty in results obtained from chemical test methods. During this time, Vicki also became involved with the development and delivery of training courses on topics such as method validation, measurement uncertainty, quality systems and statistics for analytical chemists. 

Partial or complete re-validation is another precedented approach to method transfer. Those variables described in method validation guidance documents (ICH Q2B, 1996 USP, 2012c) that are likely to be impacted by method transfer, should be assessed and documented (transfer or validation protocol). Agut et al. (2011) indicated that, in the changing industry model with the increased outsourcing of R and D activities (alliances, outsourcing, etc.), method re-validation may constitute, in some cases, an efficient approach when the transfer is performed from the Analytical Development Laboratory of an external partner who does not share exactly the same environment (validation standards, analytical culture or traditions , equipment, etc.). ... 

Hoffmann, D., Kringle, R. A Total Error Approach for the Validation of Quantitative Analytical Methods. Pharm. Res., 24, 2007, 1157. 

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