Method validation case study

Once a method has been developed and validated, it should be transferred to each site that intends to use the method. A typical method transfer would take place between the research group that developed and validated the method and the QC group that will use the method to release the finished commercial product, although method transfer may occur at any point where knowledge moves from one group to another. As in the case of method validation, method transfer should be performed under the control of a protocol that details the steps required for the study. 

ABSTRACT This paper will present the HuDeM (Human Dependability Model) project financed by the European Space Agency (ESA). The project has focused on developing a Human Dependability Model to be applicable for space activities and projects. The project is based on relevant perspectives from other industries like aviation, petroleum, nuclear and railways. Human Dependability is described as the contribution of the human in a space system to safety and reliability, a subject to reduce the incidence of human error and minimize its effects. Existing literature suggests that there is a trend towards an understanding and acknowledgement of the importance of humans in accidents and recoveries. In addition to propose a Human Dependability Model, the project validated the implementation of one proposed method. The initial validation is based on a case study. The validation method focuses primarily on the use of scenarios and checklists. This paper will outline and discuss some experiences and key challenges. 

This chapter discusses research methods. The multiple case study method is reviewed and is followed by an assessment of the appropriateness of a case study approach. The data collection methods in general and the rationale for using interview and observation in this study to collect primary data are addressed. Archived data are outlined and the issues of reliability and validity are considered. Finally, simulation and simulation-based optimisation methods are introduced. 

The integration of analytical methods in European standards requires their acceptance by several national experts within special working groups and in a final weighted vote of National Standards Bodies. Therefore, there needs to be very high confidence in the performance of methods. Consequently, methods should be tested in inter-laboratory method validation studies, with the exception of those multiresidue methods which are widely used throughout Europe. In the case of CEN methods there is no doubt about residue definition but detailed requirements about the number of matrices and concentration levels in validation experiments do not exist. Eor this reason it may be that CEN methods are validated for important crops only. 

In this section, we will discuss some examples from the literature, in which the approximation methods derived in this chapter have been used. In several cases, the approximations have been compared with more-accurate path integral simulations to assess their validity. This is not meant as a full review rather, several case studies have been chosen to illustrate the tools we have developed. We will first look at simpler examples and then discuss water models and applications in enzyme kinetics. 

Basak, S. C., Mills, D., Hawkins, D. M., Kraker, J. J. Proper statistical modeling and validation in QSAR A case study in the prediction of rat fat air partitioning. In Computation in Modem Science and Engineering, Proceedings of the International Conference on Computational Methods in Science and Engineering 2007 (ICCMSE 2007), Simos, T. E., Maroulis, G., Eds., American Institute of Physics, Melville, New York, 2007, pp. 548-551. 

Briefly, to assure quality assurance and quality control, samples are analyzed using standard analytical procedures. A continuing program of analytical laboratory quality control verifies data quality and involves participation in interlaboratory crosschecks, and replicate sampling and analysis. When applicable, it is advisable, even insisted upon by the EPA, that analytical labs be certified to complete the analysis requested. However, in many cases, time constraints often do not allow for sufficient method validation. Many researchers have experienced the consequences of invalid methods and realized that the amount of time and resources required to solve problems discovered later exceeds what would have been expended initially if the validation studies had been performed properly. 

The primary object of this book is to provide the HPLC practitioner with a handy guide to the use of HPLC for analyzing pharmaceutical compounds of interest. This means familiarizing the practitioner with the theory, instrumentation, regulations, and numerous applications of HPLC. This handbook provides practical guidelines using case studies on sample preparation, column or instrument selection, and summaries of best practices in method development and validation, as well as tricks... 

Validation is the process of proving that a method is acceptable for its intended purpose. It is important to note that it is the method not the results that is validated. The most important aspect of any analytical method is the quality of the data it ultimately produces. The development and validation of a new analytical method may therefore be an iterative process. Results of validation studies may indicate that a change in the procedure is necessary, which may then require revalidation. Before a method is routinely used, it must be validated. There are a number of criteria for validating an analytical method, as different performance characteristics will require different validation criteria. Therefore, it is necessary to understand what the general definitions and schemes mean in the case of the validation of CE methods (Table 1). Validation in CE has been reviewed in references 1 and 2. The validation of calibrations for analytical separation techniques in general has been outlined in reference 3. The approach to the validation of CE method is similar to that employed for HPLC methods. Individual differences will be discussed under each validation characteristic. 

The case study of the tetranuclear manganese complex presented above and the specific examples of structure/spectroscopy correlations have established the validity of the proposed methods and set the stage for more ambitious applications. The first such application has been the recent evaluation of several structural models of the OEC in the S2 state ( 1 3) of the Kok cycle (107). Twelve structural models were considered, 10 of which were based on Mn405Ca core topologies derived by polarized EXAFS spectra. Figure 19 shows one of the models included in the set. 

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]. 

The top-down approach is often used when there are method validation data from properly conducted interlaboratory studies, and when the laboratory using reproducibility as the measurement uncertainty can demonstrate that such data are applicable to its operations. Chapter 5 describes these types of studies in greater detail. In assigning the reproducibility standard deviation, sR, to the measurement uncertainty from method validation of a standard method, it is assumed that usual laboratory variables (mass, volume, temperature, times, pH) are within normal limits (e.g., 2°C for temperature, 5% for timing of steps, 0.05 for pH). Clause 5.4.6.2 in ISO/ 17025 (ISO/IEC 2005) reads, In those cases where a well-recognized test method specifies limits to the values of the major sources of uncertainty of measurement and specifies the form of presentation of the calculated results, the laboratory is considered to have satisfied this clause by following the test method and reporting instructions. ... 

It may be important to consider the variability of the matrix due to the physiological nature of the sample. In the case of LC-M/MS-based procedures, appropriate steps should be taken to ensure the lack of matrix effects throughout application of the method, especially if the nature of the matrix changes from the matrix used during method validation. For Microbiological and immunoassay, if separation is used prior to assay for study samples but not for standards, it is important to establish recovery and use it in determining results. In this case, possible approaches to assess efficiency and reproducibility of recovery are ... 

Many case studies have been described for pharmacophore models. The second section will report some success stories in which pharmacophore models have been used. The validation methods to which the authors have to resort will be particularly emphasized. Undeniably, the ultimate validation method for a model is to demonstrate its practical usefulness for drug discovery ... 

This section will underline the importance of some of the above-described validation methods depending on the planned use for the pharmacophore model to be determined. It will be illustrated by several case studies. Successful applications are undoubtedly the best way to validate a pharmacophore hypothesis they bring a straightforward answer to the practical question Was the model useful ... 

In case there are doubts in data quality, request from the laboratory the SOPs, the MDL studies, and method validation documentation. Have them examined by a qualified chemist to determine if they are acceptable. 

The objective of improvement schemes is to study and validate each step of different analytical procedures applied by different laboratories in a collaborative manner. Such programmes usually involve groups of 20-50 laboratories. In the best case, each critical step of the procedure should be evaluated in an adapted exercise. The individual steps may be studied with a series of different materials in a stepwise manner. In principle the strategy consists of starting from the simplest matrix, e.g. pure solutions and/or mixtures of compounds in solution, for testing the performance of the detector. The analysis of more complex matrices (e.g. raw extract, purified extract) enables the separation and/or clean-up steps to be tested, whereas solid samples are used to test the entire procedure. Spiked samples can be analysed to evaluate the extraction procedure, within the limits of this evaluation (as commented in Section 2.3.1). Such an approach is actually similar to the steps that should be followed when developing and validating a new method in a laboratory. 

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