Validation, method robustness

Method validation Basic method validation (short-term use, fit for purpose, little robustness), data will see expert eye prior to release Extended method validation, robustness and ruggedness tests important for unsupervised operation... 

For non-compendial procedures, the performance parameters that should be determined in validation studies include specificity/selectivity, linearity, accuracy, precision (repeatability and intermediate precision), detection limit (DL), quantitation limit (QL), range, ruggedness, and robustness [6]. Other method validation information, such as the stability of analytical sample preparations, degradation/ stress studies, legible reproductions of representative instrumental output, identification and characterization of possible impurities, should be included [7], The parameters that are required to be validated depend on the type of analyses, so therefore different test methods require different validation schemes. 

Certification using at least two independent methods. At least two validated, robust, and independent methods are employed to produce the true value of the analyte. 

Further discussion of method validation can be found in Chapter 7. However, it should be noted from Table 11 that it is frequently desirable to perform validation experiments beyond ICH requirements. While ICH addresses specificity, accuracy, precision, detection limit, quantitation limit, linearity, and range, we have found it useful to additionally examine stability of solutions, reporting threshold, robustness (as detailed above), filtration, relative response factors (RRF), system suitability tests, and where applicable method comparison tests. 

Analytical data generated in a testing laboratory are generally used for development, release, stability, or pharmacokinetic studies. Regardless of what the data are required for, the analytical method must be able to provide reliable data. Method validation (Chapter 7) is the demonstration that an analytical procedure is suitable for its intended use. During the validation, data are collected to show that the method meets requirements for accuracy, precision, specificity, detection limit, quantitation limit, linearity, range, and robustness. These characteristics are those recommended by the ICH and will be discussed first. 

In biomedical and pharmaceutical analysis, and particularly in the pharmaceutical industry, much attention is paid to the quality of the obtained analytical results because of the strict regulations set by regulatory bodies. Proper method validation demonstrates the fit of an analytical method for a given purpose. In this context, robustness testing has become increasingly important. 

Initially, robustness testing was performed to identify potentially important factors, which could affect the results of an interlaboratory study.Therefore, the robustness test was executed at the end of the method validation procedure, just before the interlaboratory study. Flowever, a method found to be non-robust should be redeveloped and revalidated, leading to a waste of time and money. For these economical reasons, nowadays, method robusmess is verified at an earlier stage in the lifetime of the method, i.e., at the end of method development or at the beginning of the validation procedure. ... 

HPLC methods can usually be transferred without many modifications, since most commercially available HPLC instruments behave similarly. This is certainly true when the columns applied have a similar selectivity. One adaptation, sometimes needed, concerns the gradient profiles, because of different instrumental or pump dead-volumes. However, larger differences exist between CE instruments, e.g., in hydrodynamic injection procedures, in minimum capillary lengths, in capillary distances to the detector, in cooling mechanisms, and in the injected sample volumes. This makes CE method transfers more difficult. Since robustness tests are performed to avoid transfer problems, these tests seem even more important for CE method validation, than for HPLC method validation. However, in the literature, a robustness test only rarely is included in the validation process of a CE method, and usually only linearity, precision, accuracy, specificity, range, and/or limits of detection and quantification are evaluated. Robustness tests are described in references 20 and 59-92. Given the instrumental transfer problems for CE methods, a robustness test guaranteeing to some extent a successful transfer should include besides the instrument on which the method was developed at least one alternative instrument. 

Guidance for robustness/mggedness tests in method validation. J. Pharm. Biomed. Anal. 24, 723-753. 

Jimidar, M., Van Ael, W., De Smet, M., and Cockaerts, R (2002). Method validation and robustness testing of an enantioselective CE method for chemical quality control. LC-GC Europe (April), 230-241. 

Method qualification is based on ICH method validation guidelines. Method type (purity or identity) will dictate the level of qualification testing necessary. Several strategies for method qualification and validation exist and are based on needs, resources available, and the project timeframe. One approach is to perform minimal development and qualification, which may be necessary for projects with shorter timelines, but it may place more burden and risk on future validation activities for robustness testing, and can result in failure. As discussed in Chapter 4, an alternate approach would invest more time and resources into method development, followed by extensive qualification and robusmess testing to determine if further development is... 

Not all of the mentioned parameters will be required for validation of every method. Validation of some methods may require consideration of other parameters and should be justified. It should also be noted that robustness is not listed here but should be considered at an appropriate stage in the development of the analytical procedure. 

This review describes the determination of robustness and ruggedness in analytical chemistry. The terms ruggedness and robustness as used in method validation are sometimes considered to be equivalent [1,2], In other publications a difference is made between the two terms [3]. In the following only the term ruggedness will be used. 

An example of the minimum requirement for potency assay of the drug substance and drug product is tabulated in Table 4. Note that the postponement of intermediate precision is aligned with previous discussion that the use of early phase analytical method resides mainly in one laboratory and is used only by a very limited number of analysts. Each individual company s phased method validation procedures and processes will vary, but the overall philosophy is the same. The extent of and expectations from early phase method validation are lower than the requirements in the later stages of development. The validation exercise becomes larger and more detailed and collects a larger body of data to ensure that the method is robust and appropriate for use at the commercial site. 

The purpose of an analytical method is the deliverance of a qualitative and/or quantitative result with an acceptable uncertainty level. Therefore, theoretically, validation boils down to measuring uncertainty . In practice, method validation is done by evaluating a series of method performance characteristics, such as precision, trueness, selectivity/specificity, linearity, operating range, recovery, LOD, limit of quantification (LOQ), sensitivity, ruggedness/robustness, and applicability. Calibration and traceability have been mentioned also as performance characteristics of a method [2, 4]. To these performance parameters, MU can be added, although MU is a key indicator for both fitness for purpose of a method and constant reliability of analytical results achieved in a laboratory (IQC). MU is a comprehensive parameter covering all sources of error and thus more than method validation alone. 

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. 

System suitability. During the robustness testing of method validation, critical method parameters such as mobile phase composition and column temperature are varied to mimic the day-to-day variability. Therefore, the system suitability results from these robustness experiments should reflect the expected range for the system suitability results. As a result, system suitability results in these method validation experiments are very useful in determining the system suitability... 

Rotational Speed. The rotational speed of a basket or paddle is an important consideration in the development and validation of the dissolution test. A speed of 100 rpm is commonly used with the basket apparatus and a speed of 50 rpm is used with paddles. In method validation, one needs to ensure that slight variations in rotational speed will not affect the outcome of the dissolution test. The compendial limit for variations in rotational speed is 4%, but a wider variation (e.g., 10%) may be considered in testing the robustness of the method. 

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. 

Method validation is the process of proving that an analytical method is acceptable for its intended purpose.3 In pharmaceutical chemistry, method validation requirements for regulatory submission include studies of method specificity, linearity, accuracy, precision, range, limit of detection, limit of quantitation, and robustness. 

The phrase related to implies that the relationship is known and valid. This will only be realized if the relationship at every step of the process is clearly defined and valid. Hence the requirement for an unbroken chain of comparisons. The parallel between these issues and those addressed by method validation is worth noting. Validation is the process of establishing that a method is capable of measuring the desired measurand (analyte), with appropriate performance characteristics, such as level of uncertainty, robustness, etc. It should also address systematic effects, such as incomplete recovery of the analyte, interferences, etc. These latter issues can be dealt with by designing a method to eliminate any bias, at a given level of uncertainty, or if that is not possible, to provide a means of correcting for the bias. This may be done at the method level, by applying a correction factor to all results, or at the individual measurement level. 

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. 

The benefit to this unconventional approach to method validation is that many of the standard method-development experiments lend themselves to the validation. For example, the method changes that normally surround the optimization of a method provide important robustness data for the validation. 

Once the analytical parameters have been determined from the method development and the method has proven suitable for routine measurements, internal quality control (IQC) procedures must be established to maintain the validity of the analytical scheme and to better monitor potential sources of errors. The IQC used includes pre- and post-digestion controls, blank determination, half range of the calibration graph checking, and recovery rate of the samples. The stability of the recovery rate with time (Fig. 1.4) shows that the method is robust after using... 

A rapid, robust ICP-MS method was described for the determination of I in food for human consumption as well as for pets [34], The sample preparation was made by alkaline hydrolysis with TMAH using either MW heating or the high-pressure asher. Method validation was carried out using seven food CRMs with certiPed I content and by cross-validation with GC, neutron activation analysis (NAA) and colorimetry. The method has been proven to give accurate and repeatable results for a range of fortiPed food commodities for human and animal consumption. 

The use of HPLC for the separation of organo-Sn compounds has been scarce. The technique allows for the baseline separation of the butyl- and phenyl-Sn compounds although the LoDs obtained by HPLC-ICP-MS are much worse than with GC-ICP-MS. Therefore, despite the need for a prior derivatization of organo-Sn compounds, GC has been accepted as the separation method of choice because of its robustness and high sample throughput. HPLC-ICP-MS, however, should be considered as a valuable independent technique to be used for method validation and production of CRMs. 

Consider now robustness. If the estimators A are computed from independent response variables then, as noted in Section 1, the estimators have equal variances and are usually at least approximately normal. Thus the usual assumptions, that estimators are normally distributed with equal variances, are approximately valid and we say that there is inherent robustness to these assumptions. However, the notion of robust methods of analysis for orthogonal saturated designs refers to something more. When making inferences about any effect A, all of the other effects At (k i) are regarded as nuisance parameters and robust means that the inference procedures work well, even when several of the effects ft are large in absolute value. Lenth s method is robust because the pseudo standard error is based on the median absolute estimate and hence is not affected by a few large absolute effect estimates. The method would still be robust even if one used the initial estimate 6 of op, rather than the adaptive estimator 6L, for the same reason. 

Harmonization of methods is important for the laboratories given the task of monitoring products for compliance with specifications, especially where they have to monitor pesticides for both public health and agricultural use. It would also enable the wider use of robust methods, validated by international collaborative studies. 

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