Valid analytical measurements system

The UK Government has, for more than six years, funded the Valid Analytical Measurement (VAM) Programme, which is aimed at improving the quality and comparability of analytical measurements. The work undertaken within VAM is key to the underpinning of a modern physico-chemical and biochemical National Measurement System, By disseminating the activities of VAM across international boundaries and linking with other national measurement system VAM also aims to ensure the comparability of data worldwide. Thus VAM provides an infrastructure under which reliable measurements can be made for trade, regulation and health and safety provision. 

LGC has a strong interest in the quality of analytical measurements and played a lead role in the development of the UK s initiative on Valid Analytical Measurement (VAM). This is a programme supported by the UK government as part of the DTI programmes supporting the national measurement system. 

The preparation of this book was supported under contract with the Department of Trade and Industry (DTI) as part of the National Measurement System (NMS) Valid Analytical Measurement (VAM) Programme. The latter aims to improve the quality of analytical measurement in the UK. 

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. 

We are grateful for financial support from the Department of Trade and Industry as part of the National Measurement System Valid Analytical Measurement programme. 

Abstract The Valid Analytical Measurement (VAM) programme was set up by the Department of Trade and Industry as part of its support for the UK National Measurement System. This paper gives an overview of the VAM programme together with a description of the principles on which valid analytical measurement should be based. This is followed by a... 

Can you imagine going to court with results that you are not completely sure about in terms of validity and reliability Imagine the situation where you have been asked to attend the coroner s court in relation to a suspected drug overdose You are in the witness box and you are asked to confirm that your results indicate that John Doe may have died from an overdose of heroin. His family is in court and your answer is, I think so, but I can t really be sure it was heroin and I can t be sure about the amount exactly . Clearly, this answer is not acceptable and it would not take many appearances at court of this type for you to lose any credibility as an expert witness and to bring your laboratory into disrepute. In order to avoid these types of situations, it is normal for forensic laboratories to implement a set of principles that ensure that results are valid, reliable, and repeatable. This forms part of the company s overarching quality system (see Chapter 9). One of the ways in which a laboratory can ensure that measurement is valid and fit for purpose is to adopt the valid analytical measurement (VAM) system. 

Certified reference materials are used to provide reference values to facilitate the development and validation of analytical methods, and for the calibration, verification, and quality control of analytical measurement systems. 

Similar to quantitative methods, qualitative tests should also undergo a method validation. The measuring system of a qualitative test usually transforms a quantitative result into a negative or positive report or in some cases a semi-quantitative outcome however, the absolute numerical concentration of the analyte itself is not reported. Qualitative tests can be validated by using a series of samples with known concentrations of analyte that fall either side of the positive-negative cut-off. These known values may be assigned by an alternative method, or may be reference material. It is particularly important to assess reproducibility of results around a concentration of the analyte of interest that is clinically important such as around a diagnostic cut-off. A method comparison study can also be undertaken with a comparator. The new method can usually be implemented when predefined criteria are fulfilled. 

Seah et al. [20,32] have addressed the calibration of the intensity/energy response function for valid analytical measurements with electron spectrometers used in XPS and AES. Both techniques have matured to a sufficient level that calibration systems are now available which allow spectral intensities to be related from instrument to instrument. The KE axis is usually calibrated with reference to a signal belonging to an internal calibrant, e.g. the Cl - level of adventitious carbon due to pump oil or the Au4/7/2 level of gold vacuum-deposited on the sample. 

In general, only valid studies were used to derive predicted no effect concentrations (PNECs). Because in some cases only a few valid data were available, studies valid with restrictions have been used based on expert judgement. Invalid or non-assignable studies have not been used. In instances of volatile compounds, valid studies were generally those using closed, flow-through systems, preferably with analytical measurements. 

New biomarkers will be useful in hepatotoxicity risk assessment if the data quality and validity can be established. The FDA defines a valid biomarker as one that can be measured in an analytical test system with well-established performance characteristics and has an established scientific framework or body of evidence that elucidates the significance of the test results [160]. Although there is no formerly agreed upon path, biomarker validation should include appropriate end-points for study (i.e., toxicology, histopathology, bioanalytical chemistry, etc.) and dose- and time-dependent measurements. An assessment of species, sex and strain susceptibility is also important to evaluate across species differences. More specific considerations for validation of gene and protein expression technologies are reviewed by Corvi et al. and Rifai et al. [144, 147]. 

FIGURE 2 Role of method validation in quality of analytical measurements. Validation is the process to demonstrate the fitness for purpose of the analytical system [4,8,14,15]. 

If there is any doubt about whether 100% of the analyte is presented to the measuring system or that the response of the calibrated system leads to no bias, then the assumptions must be tested during method validation and appropriate actions taken. If a series of measurements of a CRM (not used for calibration) leads to the conclusion that there is significant bias in the observed measurement result, the result should be corrected, and the measurement uncertainty should include the uncertainty of the measurement of the bias. If the bias is considered insignificant, no correction need be made, but measuring the bias and concluding that it is zero adds uncertainty (perhaps the bias was not really zero but is less than the uncertainty of its measurement). One approach to measurement uncertainty is therefore to include CRMs in the batch to be used to correct for bias, and then the uncertainty of estimation of bias, which includes the uncertainty of the quantity value of the CRM, is combined with the within-laboratory reproducibility. In some fields of analysis it is held that routine measurement and correction for bias... 

The information in this chapter applies specifically to the first element sample preparation. The sample preparation steps are usually the most tedious and labor-intensive part of an analysis. By automating the sample preparation, a significant improvement in efficiency can be achieved. It is important to make sure that (1) suitable instrument qualification has been concluded successfully before initiation of automated sample preparation validation [2], (2) the operational reliability of the automated workstation is acceptable, (3) the analyte measurement procedure has been optimized (e.g., LC run conditions), and (4) appropriate training in use of the instrument has been provided to the operator(s). The equipment used to perform automated sample preparation can be purchased as off-the-shelf units that are precustomized, or it can be built by the laboratory in conjunction with a vendor (custom-designed system). Off-the-shelf workstations for fully automated dissolution testing, automated assay, and content uniformity testing are available from a variety of suppliers, such as Zymark (www.zymark.com) and Sotax (www.sotax.com). These workstations are very well represented in the pharmaceutical industry and are all based on the same functional requirements and basic principles. 

The term chemical measurement can cover all these determinations, including identification [6], Identification defines the so called analyte by means of chemical, electrochemical, spectroscopical and other physical properties. In most cases identification is done by measurements. Identification is valid only in a reference system. The terms describing the analytical problem (see Fig. 4), the measuring system used, the reference methods and the reference materials, belong together as the reference system. 

If analytical measurements are susceptible to variations in the analysis parameters or sample preparation conditions, the method must be suitably controlled or a precautionary statement must be included in the written procedure that alerts the chemist to the susceptibility. The method s system suitability parameters should be defined in such a way that meeting all system suitability criteria would ensure that the method is currently being performed within the acceptance window provided by validation robustness testing. 

Before assessing the other validation parameters (trueness, recovery, precision, selectivity, specificity, detection capability, stability, and applicability/mgged-ness), the appropriateness of the calibration model should be evaluated. The correctness of the analytical determination of elements in food and food products depends indeed on the choice and the evaluation of the calibration model. The calibration model gives the mathematical relationship between the signal of the measuring system and the concentration in the sample. Several authors have published guidelines concerning calibration in analytical chemistry [5-7]. 

Generally, the analysis of environmental pollutants is considered as a necessary expense that is performed solely if stated by law. With less expensive screening methods and automated modern equipment to analyze suspect samples, the cost of analysis will become much lower. Hence, the attitude towards QA would most probably be more positive and the analytical work much more reliable for the customers. This also strengthens the international competitiveness of European producers. The credibility of the entire monitoring chain (screening methods, reference and standardized methods, as well as CRMs for the quality control of these methods) lies in the adequacy and integration of all three levels of the system. The adequate development and validation of methods is a prerequisite for a harmonized measurement system [80]. 

Ion-selective electrodes (ISEs) represent the current primary methodology in the quantification of S-Li [11-13], Moreover, ISE modules are parts of large and fully automated clinical chemistry analysers. In practice, the validation parameters are most often chosen in terms of judging the acceptability of the new measurement system for daily use. For this reason, the first approach was to study whether the detected imprecision fulfilled the desired analytical quality specifications. Secondly, proficiency testing (PT) results from past samples were of great value in predicting future bias. The identity of the three ISE methods was evaluated using patient samples. The analytical performance was checked after 6 months routine use. Without any exception, method validations always mean an extra economical burden. Therefore, the validation parameters chosen and processed have to be considered carefully. 

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