Analytic practices validation studies

Interlaboratory Quality Control. In addition to the mandatory quality control practices just outlined, the laboratory is encouraged to participate in interlaboratory programs such as relevant performance evaluation (PE) studies, analysis of standard reference materials, and split sample analyses. Participation in interlaboratory analytical method validation studies is also encouraged. 

Until 1991, manufacturers seeking authorizations for pesticides had to fulfil country-specific requirements of validation of enforcement methods. The term enforcement method means analytical methods which are developed for post-registration control and monitoring purposes. The harmonization of these requirements was initiated with the European Economic Community (EEC) Council Directive 91/414/EEC and temporarily finalized with the Guidance Document on Residue Analytical Methods SANCO/825/00 rev. 6, dated 20 June 2000 [Santd et Protection des Consommateurs (SANCO)]. The evaluation of validation studies by the competent authority is conducted by comparison of these European Union (EU) requirements with the study results and most often without any practical experience of the method. Some details of this evaluation are discussed below. 

If analytical methods are validated in inter-laboratory validation studies, documentation should follow the requirements of the harmonized protocol of lUPAC. " However, multi-matrix/multi-residue methods are applicable to hundreds of pesticides in dozens of commodities and have to be validated at several concentration levels. Any complete documentation of validation results is impossible in that case. Some performance characteristics, e.g., the specificity of analyte detection, an appropriate calibration range and sufficient detection sensitivity, are prerequisites for the determination of acceptable trueness and precision and their publication is less important. The LOD and LOQ depend on special instmmentation, analysts involved, time, batches of chemicals, etc., and cannot easily be reproduced. Therefore, these characteristics are less important. A practical, frequently applied alternative is the publication only of trueness (most often in terms of recovery) and precision for each analyte at each level. No consensus seems to exist as to whether these analyte-parameter sets should be documented, e.g., separately for each commodity or accumulated for all experiments done with the same analyte. In the latter case, the applicability of methods with regard to commodities can be documented in separate tables without performance characteristics. 

Once the determinative or confirmatory method has been developed to take full advantage of the chemical properties of the analyte molecule, a study is necessary to prove that the method is valid. Criteria for method validation are outlined in guidelines from the US FDA, US EPA, and EU. A summary of the differences in regulatory requirements for method validation is provided in Table 3. The parameters addressed by all of the regulatory guidelines include accuracy, precision, sensitivity, specificity, and practicability. 

In analytical practice, they are best recognized by the determination of xtest as a function of the true value xtrue, and thus, by analysis of certified reference materials (CRMs). If such standards are not available the use of an independent analytical method or a balancing study may provide information on systematic errors (Doerffel et al. [1994] Kaiser [1971]). In simple cases, it may be possible, to estimate the parameters a, / , and y, in Eq. (4.5) by eliminating the unknown true value through appropriate variation of the weight of the test portions or standard additions to the test sample. But in the framework of quality assurance, the use of reference materials is indispensable for validation of analytical methods. 

Methods can only usefully applied in analytical practice when they are sufficiently robust and therefore insensitive to small variations in method conditions and equipment (replacement of a part), operator skill, environment (temperature, humidity), aging processes (GC- or LC columns, reagents), and sample composition. This demand makes robustness (ruggedness) to an important validation criterion that has to be proved by experimental studies. The concepts of robustness and ruggedness mostly have been described verbally where it must be stated that their use is frequently interchangeably and synonymously (e.g., Hendricks et al. [1996] Kellner et al. [1998] EURACHEM [1998] ICH [1994, 1996] Wunsch [1994] Wildner and Wunsch [1997] Valcarcel [2000] Kateman and Buydens [1993]). 

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. 

The process of method validation (i.e., evaluation of the assay) affects the quality of the quantitative data directly [9 A Guide to Analytical Method Validation, Waters Corporation]. Through method validation, it is assured that the method developed is acceptable. Issues involved in the validation of a mass spectrometry method for quantitative analysis are similar to those in any other analytical technique. The validation involves undertaking a series of studies to demonstrate the limit of detection G OD) limit of quantitation (LOQ) linear range specificity within-day precision and accuracy and day-to-day precision and accuracy, specificity, and robustness of the method. All of these parameters must be determined with those commonly accepted good laboratory practices criteria that are applicable in the vafidation of analytical methods. 

In summary, the purpose of any validated analytic method is to obtain consistent, reliable, and accurate measurements. The results from method validation can be used to judge the quality, reliability, and consistency of analytic results, which is an integral part of any good analytic practice and the base of which is supported by the identification and quantification of active substances, studies of their fate and behavior, and studies of their residue. Validation of analytic methods is required by actual EU legislative framework and has received considerable attention in the literature from industrial committees and regulatory agencies. 

The workhorses in national monitoring programs are multi-residue methods. Any official method collection of any EU Member State contains at least one multi-residue method. For multi-analyte and/or multi-matrix methods, it is likely to be impractical to validate a method for all possible combinations of analyte, concentration and type of sample matrix that may be encountered in subsequent use of the method. Therefore, initial validation should incorporate as many of the target analytes and matrices as practicable. For practical reasons this validation and the evaluation of other methods with limited scope often cannot be conducted in inter-laboratory studies. Other concepts based on independent laboratory validation or validation in a single laboratory have been developed and can provide a practical and cost-effective alternative (or intermediate) approach. 

The fourth and final need is for doctmentation and education. The validation and standardization will go for naught if the practice of receptor modeling cannot be established at the state implementation plan level where it is most sorely needed. Major reviews of model applications, analytical methods, source characterization and field study design need to be prepared and communicated to those most likely to make use of them. 

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]. 

A validation report is a written document that cross-references the validation protocol, summarizes the results obtained, describes any deviations observed, and draws the necessary conclusions, including recommending changes required to correct deficiencies for the qualification and validation performed [5]. In this report it is required to present both the results and conclusions and the secure approval of the study. The report should include a summary of the procedures used to clean, sample, and test as well as the physical and analytical test results or references for the same. The conclusions regarding the acceptability of the results should also be included. Other information would be the status of the procedures being validated, any recommendations based on the results, or any relevant information obtained during the study. These include, re validation practices (if applicable), the approved conclusions, and any deviations of the protocol that might have occurred. In cases where it is unlikely that further batches of the product will be manufactured for a period... 

Method validation covers a number of aspects of an analytical method that have already been evaluated in the course of development and use. The values of the calibration parameters must be known to use the method to analyze a particular sample, and any serious deviations from the measurement model should have been discovered. In addition, however, every method should undergo a robustness study as the practicality of the method may ultimately depend on how rugged it is. 

Recently, major developments in statistical methods have been made particularly in the areas of collaborative studies and method validation and robustness testing. In addition, analytical method development and validation have assumed a new importance. However, this handbook is not intended to be a list of statistical procedures but rather a framework of approaches and an indication of where detailed statistical methods may be found. Whilst it is recognised that much of the information required is available in the scientific literature, it is scattered and not in a readily accessible format. In addition, many of the requirements are written in the language of the statistician and it was felt that a clear concise collation was needed which has been specifically written for the practising analytical chemist. This garnering of existing information is intended to provide an indication of current best practices in these areas. Where examples are given the intent is to illustrate important points of principle and best practice. 

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