Quality assurance valid analytical measurements

In recent years the term qualimetrics has been coined to refer to the use of chemometrics for the purposes of quality control (Massart et al. 1997). ft relates particularly to the use of multivariate analysis of process control measurements. Other texts on quality assurance in chemical laboratories include the latest edition of Garfield s book published by AOAC International (Garfield et al. 2000), material published through the Valid Analytical Measurement program by the LGC (Prichard 1995), and books from the Royal Society of Chemistry (Parkany 1993,1995 Sargent and MacKay 1995). Wenclawiak et al. (2004) have edited a series of Microsoft PowerPoint presentations on aspects of quality assurance. 

Recently, the topic of method development for both routine and non-routine analyses has been the subject of two EURACHEM documents The Fitness for Purpose of Analytical Methods and Quality Assurance for Research and Development and Non-routine Analysis as part of the VAM (Valid Analytical Measurements) programme. These guides provide information and a bibliography for ISO publications. 

This Handbook aims to explain terminology widely used, and sometimes misused, in analytical chemistry. It provides much more information than the definition of each term but it does not explain how to make measurements. Additionally, it does not attempt to provide comprehensive coverage of all terms concerned with chemistry, instrumentation or analytical science. The authors have addressed primarily those terms associated with the quality assurance, validation and reliability of analytical measurements. The Handbook attempts to place each term in context and put over concepts in a way which is useful to analysts in the laboratory, to students and their teachers, and to authors of scientific papers or books. This approach is particularly important because official definitions produced by many international committees and organisations responsible for developing standards are frequently confusing. In a few cases the wording of these definitions completely obscures their meaning from anyone not already familiar with the terms. 

The variety of complex terms used in the Quality Assurance aspect of analytical measurement can be the cause of considerable confusion.This unique handbook explains the most widely-used terminology in language that is readily understood, and attempts to place each term in context. Concepts are described in a way that is useful to all practitioners, particularly those concerned with quality assurance, validation and reliability of analytical measurements. Explanations of terms are always in line with the "official definition", often developed by international committees. 

Keywords Accuracy Analytical procedure Measurement assurance Measurement uncertainty Quality assurance Validation... 

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. 

You have your methodology both verified and validated as required for measurements needing a high level of confidence. But, you must also assure that your analyst Is experienced In performing the type of analysis you need, that you have standards for the analytes available, and that you have a written quality assurance plan that documents good laboratory practice. 

Sampling is just the beginning of the analytical process. On the way from sampling to the test report a lot of different requirements for high quality measurements have to be considered. There are external quality assurance requirements on the quality management system (e.g. accreditation, certification, GLP), internal quality assurance tools (e.g. method validation, the use of certified reference material, control charts) and external quality assurance measures (e.g. interlaboratoiy tests). 

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. 

Analytical method validation forms the first level of QA in the laboratory. Analytical quality assurance (AQA) is the complete set of measures a laboratory must undertake to ensure that it is able to achieve high-quality data continuously. Besides the use of validation and/or standardized methods, these measures are effective IQC procedures (use of reference materials, control charts, etc.), with participation in proficiency testing schemes and accreditation to an international standard, normally ISO/IEC 17025 [4]. Method validation and the different aspects of QA form the subject of Section 8.2.3. 

This update on analytical quahty issues a common understanding on the topics of method validation, traceabihty, and MU of measurements. The interrelationships between method validation and traceability and MU of results have been elucidated. Throughout the landscape of guidelines and standards, the most relevant information was selected, compiled, and summarized. Different approaches are discussed for establishing traceability and assessing MU of analytical methods in general. The importance of both concepts and the link with method validation and analytical quality assurance are highlighted. 

While the provision of suitably validated analytical methods is a necessary requirement for ensuring compliance with MRLs, the method alone is not sufficient to ensure creditable analytical measurements. In addition to selecting suitable methods, the analyst must demonstrate that the method is operating under statistical control in the laboratory and is performed to meet performance specifications as required by the analytical problem. This means that all methods should be applied in an environment with appropriate quality assurance procedures and performance evaluation checks. 

When the analytical laboratory is not responsible for sampling, the quality management system often does not even take these weak links in the analytical process into account. Furthermore, if sample preparation (extraction, cleanup, etc.) has not been carried out carefully, even the most advanced, quality-controlled analytical instruments and sophisticated computer techniques cannot prevent the results of the analysis from being called into question. Finally, unless the interpretation and evaluation of results are underpinned by solid statistical data, the significance of these results is unclear, which in turn greatly undermines their merit. We therefore believe that quality control and quality assurance should involve all the steps of chemical analysis as an integral process, of which the validation of the analytical methods is merely one step, albeit an important one. In laboratory practice, quality criteria should address the rationality of the sampling plan, validation of methods, instruments and laboratory procedures, the reliability of identifications, the accuracy and precision of measured concentrations, and the comparability of laboratory results with relevant information produced earlier or elsewhere. 

Quite obviously, the quality of analytical results strongly depends on the representativeness of the sample examined, the appropriateness of the pretreatment procedures applied for the quantitative conversion of analytes into detectable forms, and the btness for purpose of the laboratory setting. Because of the low concentration and the numerous interferences which affect the various detection systems, measurements methods must be thoroughly validated. Even if values obtained by several laboratories for PGEs concentrations in environmental and biological samples were compliant with the basic requirements of quality assurance (QA) and internal quality control (QC), striking differences have been... 

CRMs are an important tool for quality assurance and quality control in analytical laboratories. They are used for verification of accuracy and precision (i.e., reliability of the results of analysis, validation of analytical procedures, establishing measurement traceability, and calibration of measurement equipment). Use of CRMs is recommended by the ISO/IEC 17025 standard and therefore it is obligatory for those who wish to obtain and maintain accreditation of the laboratory. 

The frequency of the control sample analysis depends on the nature of the analysis. Successful analysis of the control samples assures that the system is performing as expected under the SOP. Validation of HPLC equipment assures that valid measurements are obtained. The quality of the analytical data can be maintained by keeping, in a safe place, records of the actual instrument conditions at the time the measurements were made. Backups should also be maintained. 

This article deals with legal requirements in the European Union on basic principles of laboratory quality assurance for official notification to the EC Commission and on method validation concerning official laboratories. Widespread discussions and activities on measurement uncertainty are in progress, and the European validation standards for official purposes may serve as a basis for world-wide efforts on quality harmonization of analytical results. Although much time has already been spent, definitions and require-... 

Quality issues related to analytical measurements have been described in full detail in several books [1-3] and highlighted several principles, e.g. validation of methods, quality assurance protocols incorporating the use of CRMs, independent assessment of method performance by participation in proficiency testing schemes, and accreditation. Method performance studies also represent a very important aspect to evaluate the state-of-the-art of a particular type of analysis at the development stage e.g. for testing the applicability of a standard method) or to improve the quality of measurements, e.g. prior to the certification of reference materials. 

In the case of compxrsitional data, a lot of analytical techniques can be chosen. Analytical procedures based on these techniques are then selected to be aprplied to the samples. Selected analytical methods have to be fully validated and with an estimation of their uncertainty (Gonzalez Herrador, 2007) and carried out in Quality Assurance conditions (equipment within sp>ecifications, qualified staff, and documentation written as Standard Operational Procedures...). Measurements should be carried out at least duplicate and according to a given experimental design to ensure randomization and avoid systematic trends. 

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