Measurement method validation

Where you devise original solutions to the measurement of characteristics the theory and development of the method should be documented and retained as evidence of the validity of the measurement method. Any new measurement methods should be proven by rigorous experiment to detect the measurement uncertainty and cumulative effect of the errors in each measurement process. The samples used for proving the method should also be retained so as to provide a means of repeating the measurements should it prove necessary. 

Reproducibility of experiments indicates whether measurements are reliable or not under GMP regulations this is used in the systems suitability and the method validation settings. 

During the method validation phase, the calibration, using the CS solutions, is repeated each day over at least one week to establish both the within-day and the day-to-day components of the variability. To this end, at least 6 CS, evenly spread over the concentration range, must be repeatedly run (m = 8-10 is usual), to yield n 50 measurements per day. If there are no problems with linearity and heteroscedacity, and if the precision is high (say, CV < 2-5%, depending on the context), the number of repeats m per concentration may be reduced from the second day onwards (m = 2 - 3 is reasonable). The reasoning behind... 

The term definitive method is applied to an analytical or measurement method that has a valid and well described theoretical foundation, is based on sound theoretical principles ( first principles ), and has been experimentally demonstrated to have negligible systematic errors and a high level of precision. While a technique may be conceptually definitive, a complete method based on such a technique must be properly applied and must be demonstrated to deserve such a status for each individual application. A definitive method is one in which all major significant parameters have been related by a direct chain of evidence to the base or derived SI units. The property in question is either directly measured in terms of base units of... 

Christensen JM (1996) Correcting measurement errors using reference materials in method validation. Mikrochim Acta 123 231-240. 

The use of reference samples for method calibration and development/validation occurred hand-in-hand with the development of all modern instrumental methods of analysis. In fact, the two developments are intimately linked with one another. As already noted, G-i and W-i (Fairbaim et al. 1951 Stevens i960) illustrate first instance of reference samples specifically developed for calibration purposes. Following that, the use of BCR-i as a reference sample throughout the lunar program (Science 1970) is a prime illustration of the quality assurance and method validation applications in large-scale inter-laboratory measurement programs. 

Identification of sources of analytical bias in method development and method validation is another very important application of reference materials in geochemical laboratories. USGS applied simplex optimization in establishing the best measurement conditions when the ICP-AES method was introduced as a substitute for AAS in the rapid rock procedure for major oxide determinations (Leary et al. 1982). The optimized measurement parameters were then validated by analyzing a number of USGS rock reference samples for which reference values had been established first by classical analyses. Similar optimization of an ICP-AES procedure for a number of trace elements was validated by the analysis of U S G S manganese nodule P-i (Montaser et al. 1984). 

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. 

Established in 1894, AOAC International is an independent association of scientists and organizations in the public and private sectors devoted to promoting methods validation and quality measurements in the analytical sciences. AOAC has a mission to ensure the development, testing, validation, and publication of reliable chemical and biological methods of analysis for foods, drugs, feed-stuffs, fertilizers, pesticides, water, forensic materials and other substances affecting public health and safety and the environment. 

The sensitivity achieved (LOD) is not normally presented. It is recognized that different laboratories determine dissimilar values for this parameter and even within a laboratory the repeatability of the LOD is low. Most often, the lowest validated concentration gives an impression about the lowest levels that can be analyzed generally with acceptable results. A measure of selectivity is the intensity of blank results. This intensity is discussed by the participants of inter-laboratory validation studies. However, results are not reported and limits are not defined by CEN TC 275. The results of method validations of the several multi-residue/multi-matrix methods are not reported in the same way, but newer methods with limited scope generate analogous tables with validation results (as an example, see Table 7). 

Untreated (control) soil is collected to determine the presence of substances that may interfere with the measurement of target analytes. Control soil is also necessary for analytical recovery determinations made using laboratory-fortified samples. Thus, basic field study design divides the test area into one or more treated plots and an untreated control plot. Unlike the treated plots, the untreated control is typically not replicated but must be sufficiently large to provide soil for characterization, analytical method validation, and quality control. To prevent spray drift on to the control area and other potential forms of contamination, the control area is positioned > 15 m away and upwind of the treated plot, relative to prevailing wind patterns. 

Measurements in living things, e.g. patients, is occasionally done by sampling in a non-invasive way. Because no standard patients are available which can be selected for calibration, another principle of calibration must be applied, e.g., by a reference method that measures parallel to the actual measuring method. So, the calibration consists in a comparison of the measured results with that of the reference method which are considered to be true (that have been validated beforehand). An example of a reference calibration is represented by non-invasive blood glucose determination by means of NIR spectroscopy (Muller et al. [1997] Fischbacher et al. [1997] Danzer et al. [1998], see Sect. 6.2.6). 

Due to the possible change in retention time and peak profile that may take place during day-to-day operation, it is necessary to measure peak characteristics every day to verify the status of the method validation. A blank sample should be evaluated for an analysis run, where the resolution is determined. For asymmetric peaks, the Gaussian equation cannot be used, so the modified equation, using an exponentially modified Gaussian (EMG) method has been proposed [21]. 

Ashton and Chan [ 1 ] have reviewed the techniques for the collection of seawater samples preservation, storage, and prevention of contamination are all discussed. The most appropriate measurement techniques, preconcentration and extraction, method validation, and analytical control are all covered. The apparent aluminium content of seawater stored in ordinary containers such as glass and polyethylene bottles decreases gradually, e.g., to half in 2.5 h. But if the samples are acidified with 0.5ml/l concentrated sulfuric acid the aluminium content remains constant for at least one month. Accordingly, samples should be acidified immediately after collection. However, the aluminium could be recovered by acidifying the stored samples and leaving them for at least five hours. 

This approximation is probably adequate during method validation as it provides an indication of the concentration below which detection becomes problematic. It indicates that a signal more than 3 bi above the sample blank value could have arisen just from the blank in fewer than 5% of the measurements... 

Associated with method validation, but not part of it, are two properties of results that have been previously mentioned. These parameters are measurement uncertainty and metrological traceability. Measurement uncertainty is covered in Chapter 6 and metrological traceability in Chapter 5. If considered at the planning stage of method validation, the information obtained during validation is a valuable input into measurement uncertainty evaluation. Traceability depends on the method s operating procedures and the materials being used. 

Precision estimates are key method performance parameters and are also required in order to carry out other aspects of method validation, such as bias and ruggedness studies. Precision is also a component of measurement uncertainty, as detailed in Chapter 6. The statistics that are applied refer to random variation and therefore it is important that the measurements are made to comply with this requirement, e.g. if change of precision with concentration is being investigated, the samples should be measured in a random order. 

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. 

Method validation is carried out to provide objective evidence that a method is suitable for a given application. A formal assessment of the validation information against the measurement requirements specification and other important method performance parameters is therefore required. Although validation is described as a sequential process, in reality it can involve more than one iteration to optimize some performance parameters, e.g. if a performance parameter is outside the required limits, method improvement followed by revalidation is needed. 

Method validation provides information concerning the method s performance capabilities and limitations, when applied under routine circumstances and when it is within statistical control, and can be used to set the QC limits. The warning and action limits are commonly set at twice and three times the within-laboratory reproducibility, respectively. When the method is used on a regular basis, periodic measurement of QC samples and the plotting of these data on QC charts is required to ensure that the method is still within statistical control. The frequency of QC checks should not normally be set at less than 5% of the sample throughput. When the method is new, it may be set much higher. Quality control charts are discussed in Chapter 6. 

The fundamental unit in chemical measurement is the mole - amount of substance. A mole is the amount of a substance that contains as many atoms, molecules, ions or other elementary units as the number of atoms in 0.012 kg of carbon 12 (12C). It is the only dimensionless SI unit. In practical terms, it is almost impossible to isolate a mole of pure substance. Substances with a purity of better than 99.9% are rare one exception is silver, which can be obtained with a purity of 99.9995% which is referred to as five nines silver . Another problem is that it is not always possible to isolate all of the analyte from the sample matrix, and the performance of the chemical measurement may be matrix-dependent - a given response to a certain amount of a chemical in isolation may be different from the response to the same amount of the chemical when other chemicals are present. If it is possible to isolate quantitatively all of the analyte of interest from the accompanying sample matrix, then a pure chemical substance may be used for calibration. The extent to which the analyte can be recovered from the sample matrix will have been determined as part of the method validation process (see Chapter 4, Section 4.6.3). 

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. 

This chapter has considered two key aspects related to quality assurance - the use of control charts and the evaluation of measurement uncertainty. These activities, along with method validation, require some knowledge of basic statistics. The chapter therefore started with an introduction to the most important statistical terms. 

Many of the technical requirements of the Standard are covered in Chapters 4 to 7. The analytical requirements, including choosing a method and method validation, are covered in Chapter 4. The other measurement requirements, such as calibration, traceability and equipment qualification, are dealt with in Chapter 5. Some of the general issues not covered elsewhere are mentioned in the following sections. It has already been mentioned that staff should be trained and proven to be competent to carry out the testing. This applies to permanent and contracted staff. The laboratory should have a job description for all members of staff. There are more stringent requirements on staff who are also able to provide customers with opinions or interpretation of the results. 

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. 

The manufacture of flexible PU foam (PUF) results in the emission of a variety of compounds, including TDI. There have been several concerted efforts to quantify TDI emissions from PUF manufacturing processes. While many measurement methods have been used to quantify TDI emissions, most of these methods have not been validated to establish their suitability for the quantification of TDI emissions from PUF processes. To properly address the global concern about the health effects of TDI emissions, reliable emission data, based on validated measurement techniques, are required. TDI emission measurements are typically made using adaptations of... 

To this author s knowledge, Rogers is the only one who has developed a measurement method based on a mass-balance approach, similar to the method developed by this author. However, it is hard to conclude anything regarding the validity of Rogers method, since he only applied it two times. 

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