Method validation approach

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... 

Additional examples of method validation were published by M. Blanco et al. [32] in the implementation of a NIR model for active prediction across pharmaceutical processes or by Peinado et al. [33], who proposed a method validation approach for in-line measurements. 

FIGURE 3 Staged method validation approach during the drug development process. 

This approach enables also to substantiate acceptance criteria for detection and qualification limits in impurity control method validation. 

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. 

Method validation guidelines for use in trace analysis have been proposed by various authors, but there is little consistency in the recommended approaches. The general validation guidelines proposed by standards organizations such as ISO (International Organization for Standardization), DIN (Deutsches Institut fUr Normung German Institute for Standardization) and others are often not well defined and consequently... 

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. 

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. 

The list will probably contain a mixture of processes that lead to values of the performance parameters and quality control checks. A more structured approach will now be taken to method validation. The important performance characteristics are shown in Table 4.6. 

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.). ... 

The novel concept of High-Throughput Screening (HTS) assay, that has gained widespread popularity over the last two decades, is a valid approach to drug discovery and has become a standard method for drug discovery in the pharmaceutical industry [34],... 

A pharmaceutical company has to adopt a proactive policy of validation for its facilities, production processes, production equipment and support systems, analytical methods, and computerized systems. A properly validated approach will help to assure drug product quality, optimize the processes, and reduce manufacturing cost. 

This chapter focuses on approaches to the validation of high-performance liquid chromatography methods based on regulatory guidance documents and accepted industry practices. The information in this chapter gives a brief review of the reasons for performing method validation and the regulations that describe this activity. Individual validation parameters are discussed in relation to the type of method to be validated. Examples of typical validation conditions are presented with references to additional information on individual topics. This chapter was written to help analysts responsible for method validation. 

In Table 1, the typical validation parameters required for the different types of analytical procedures are listed. For all these analytical procedures CE might be an appropriate analytical technique. In fact numerous validated CE methods for pharmaceutical analysis have been described in literature during the last decade.In Table 2, an overview is listed of the ICH validation parameters included in several reported CE validation studies. Since chiral purity determination is an important application area of CE methods, this test is listed separately as a specific analytical procedure. In addition, the determination of drug counterions has been included as a separate application. This overview illustrates that in general the required validation parameters are addressed in reported CE validation studies. It should be noted, however, that the validation parameters included in Table 2 are not necessarily evaluated exactly according ICH requirements in the reported references. Many pharmaceutical companies apply a phase-related validation approach in which the depth of validation depends on the clinical phase of development of the product involved. 

Method qualification is based on ICH method validation guidelines. Method type (purity or identity) will dictate the level of qualification testing necessary. Several strategies for method qualification and validation exist and are based on needs, resources available, and the project timeframe. One approach is to perform minimal development and qualification, which may be necessary for projects with shorter timelines, but it may place more burden and risk on future validation activities for robustness testing, and can result in failure. As discussed in Chapter 4, an alternate approach would invest more time and resources into method development, followed by extensive qualification and robusmess testing to determine if further development is... 

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. 

Feinberg M, Laurentie M (2006) A global approach to method validation and measmement uncertainty, Accred (Jiral Assur 11, 3-9... 

Quantitation of synthetic, conjugated bilirubin, after its direct separation from the incubation mixtures, offers the most valid approach to the determination of conjugation rates. However, for the present, such methods are unlikely to find wide application because of instability of... 

ECVAM is the leading international center for alternative test method validation. Hartung et al. (29) summarized the modular steps necessary to accomplish stage 3 (test validation). The seven modular steps are (I) test definition, (2) within-laboratory variability, (3) transferability, (4) between-laboratory variability, (5) predictive capacity, (6) applicability domain, and (7) performance standards (29). Steps 2-4 evaluate the test s reliability steps 5 and 6 evaluate the relevance of the test. Successful completion of all seven steps is necessary to proceed to stage 4 (independent assessment or peer review). This modular approach allows flexibility for the validation process where information on the test method can be gathered either prospectively or retrospectively. The approach is applicable not only to in vitro test methods but also to in silico approaches (e.g., computer-based approaches such as quantitative structure-activity relationships or QSAR) and pattern-based systems (e.g., genomics and proteomics). 

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