Test methods robustness

Expert opinion is a source, frequently elicited by survey, that is used to obtain information where no or few data are available. For example, in our experience with a multicountry evaluation of health care resource utilization in atrial fibrillation, very few country-specific published data were available on this subject. Thus the decision-analytic model was supplemented with data from a physician expert panel survey to determine initial management approach (rate control vs. cardioversion) first-, second-, and third-line agents doses and durations of therapy type and frequency of studies that would be performed to initiate and monitor therapy type and frequency of adverse events, by body system and the resources used to manage them place of treatment and adverse consequences of lack of atrial fibrillation control and cost of these consequences, for example, stroke, congestive heart failure. This method may also be used in testing the robustness of the analysis [30]. 

In spite of the great effort and advances made on in vitro testing, we are still far to have alternative methods robust enough to cover developmental, neurotoxic, reproductive, or carcinogenic potential for the substances evaluated. However the use of some distinct approaches may cover a great part of the potential toxic effects of some environmental pollutants. 

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. 

Some important parameters for testing the robustness of TLC methods include the stability of analyte in the solution being analyzed and on the plate before and... 

If the validated test method requires 1 g of material but only 100 mg is available, you must find out if the method is sufficiently robust to stand this amount of scaling down. This has to be checked before the analysis starts, i.e. the method must be validated for analysis of 100 mg of material. Even if the method of analysis is found to be robust, scaling down is only a viable option if the smaller test portion size remains representative, within acceptable limits. This will depend on the homogeneity of the material. 

Test methods used in the laboratory are generally derived from pharmacopoeias such as the US Pharmacopoeia, British Pharmacopoeia, or European Pharmacopoeia. For test methods that are not from recognized pharmacopoeias, validation of the analytical methods is required. The validation includes testing for accuracy, specificity, ruggedness, robustness, precision, detection limit, quantitation hmit, and range. A discussion of analytical methods vahda-tion is presented in Section 9.6.5. 

As an alternative, SST limits can be determined from the results of a robustness as recommended by the ICH. It can be done using the worst-case results for the response, derived from the experimental design results. This allows defining SST limits for responses such as resolution or peak asymmetry. The main idea behind the approach is that the most extreme results are considered, obtained under experimental conditions resulting in acceptable quantitative determinations. SST limits can thus only be meaningfully derived when the tested method is considered robust concerning its quantitative aspect. Then, nowhere in the domain, described by the experimental design, a problematic quantitation occurs, even not at the conditions where the SST responses are worst. 

In reference 88, response surfaces from optimization were used to obtain an initial idea about the method robustness and about the interval of the factors to be examined in a later robustness test. In the latter, regression analysis was applied and a full quadratic model was fitted to the data for each response. The method was considered robust concerning its quantitative aspect, since no statistically significant coefficients occurred. However, for qualitative responses, e.g., resolution, significant factors were found and the results were further used to calculate system suitability values. In reference 89, first a second-order polynomial model was fitted to the data and validated. Then response surfaces were drawn for... 

As an identity (ID) test, per ICH guidelines, only selectivity is required in method qualification and validation. Repeatability and intermediate precision are often included to ensure reliability of p7 determinations. Additionally, method robustness should be tested to assure that the assay performance is suitable for QC environment. Quantitative parameters such as LOD/LOQ are not required for an ID assay. If a cIEF method is used for purity determination, then all the purity parameters shown in Section 4 should be qualified. The following sections illustrate an example of method development and qualification procedures for cIEF. 

The first two points are best dealt with as part of the process for developing vahdated analytical methods. Vafidation should include testing the robustness of a method in repeated use over a period of time determining the precision and accuracy and study of potential interferences. As an example, it would be expected that in the capillary GC—TEA method for organic explosives, a peak should be at least three times the basefine noise to be counted as a real signal, and that the relative retention time should be within 1.0% of the standard for volatile compounds and within 0.5% for the rest. The relative retention time is simply the ratio of the analyte s retention time compared with that of an internal standard. Use of relative retention times significantly improves the repeatabdity of GC analysis... 

KoCVAM was announced in 2009 and established in 2010. In March 2011, KoCVAM joined the 2009 agreement known as the International Cooperation on Alternative Test Methods (ICATM) that had previously been formed with Europe, Canada, the USA, and Japan (33). This agreement will promote international cooperation on the validation of new test methods. It is envisioned that this cooperative effort will result in the most vigorous and robust science, thereby promoting regulatory acceptance. 

This book consists of eight chapters. Chapters 2, 3 and 4 give methodological background and reviews. Chapters 5 to 8 carry the applications both in the field of analytical chemistry and pharmaceutical formulations. Since the field of which this book tries to give an overview is still under active research, this book is by no means a monograph with well established and tested methods. There are still a lot of questions and open ends. This book, however, does give some ideas how to tackle the problems of robustness. 

A review of ruggedness testing methods is presented in Chapter 3 and in Chapter 5 examples are given. In these chapters procedures are described that test the robustness or ruggedness of existing methods. Hence, incorporating robustness explicitly in analytical techniques (see Section 1.1) is not discussed. 

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. 

Data can be obtained from tests in uniaxial tension, uniaxial compression, equibiaxial tension, pure shear and simple shear. Relevant test methods are described in subsequent sections. In principle, the coefficients for a model can be obtained from a single test, for example uniaxial tension. However, the coefficients are not fully independent and more than one set of values can be found to describe the tension stress strain curve. A difficulty will arise if these coefficients are applied to another mode of deformation, for example shear or compression, because the different sets of values may not be equivalent in these cases. To obtain more robust coefficients it is necessary to carry out tests using more than one geometry and to combine the data to optimize the coefficients. 

To satisfactorily meet and address these regulatory and market needs, standard methods for emissions testing need to be both robust and repeatable for competent laboratories to carry out, and practical and affordable for manufacturing industry. Uniformity of test methods, between countries and markets is also important if manufacturers are to avoid having to submit the same products for emissions testing by multiple different emissions certification protocols. 

For emissions testing to be accepted as a meaningful and necessary part of product quality assessment, relevant test methods must ensure acceptable uncertainty. Any associated products standards, incorporating pass/fail criteria, must also take into account the actual uncertainty of the standard methods specified. A relatively detailed summary of some of the major potential causes of error in the multistep materials emissions testing process is presented later in this chapter (see Section 6.6.2). For an emissions test standard/protocol to be robust and useful, it must take into account all of these issues and include sufficient guidance to ensure that a competent laboratory can achieve results within the expected uncertainty limits. 

The outcome of the different exercises should be discussed among all participants in technical meetings, in particular to identify random and/or systematic errors in the procedures. Whereas random errors can be detected and minimised by intralaboratory measures, systematic errors can only be identified and eliminated by comparing results with other laboratories/techniques. When all steps have been successfully evaluated, i.e. all possible sources of systematic errors have been removed and the random errors have been minimised, the methods can be considered as valid. This does not imply that the technique(s) can directly be used routinely and further work is likely to be needed to test the robustness and ruggedness of the method before being used by technicians for daily routine measurements . 

The method of choice is dependent upon the analyte, the assay performance required to meet the intended application, the timeline, and cost-effectiveness. The assay requirements include sensitivity, selectivity, linearity, accuracy, precision, and method robustness. Assay sensitivity in general is in the order of IA > LC-MS/MS > HPLC, while selectivity is IA LC-MS/MS > HPLC. However, IA is an indirect method which measures the binding action instead of relying directly on the physico-chemical properties of the analyte. The IA response versus concentration curve follows a curvilinear relationship, and the results are inherently less precise than for the other two methods with linear concentration-response relationships. The method development time for IA is usually longer than that for LC/MS-MS, mainly because of the time required for the production and characterization of unique antibody reagents. Combinatorial tests to optimize multiple factors in several steps of some IA formats are more complicated, and also result in a longer method refinement time. The nature of IAs versus that of LC-MS/MS methods are compared in Table 6.1. However, once established, IA methods are sensitive, consistent, and very cost-effective for the analysis of large volumes of samples. The more expensive FTMS or TOF-MS methods can be used to complement IA on selectivity confirmation. 

In order to use commercial reagents in a drug development program, it was important to negotiate and plan with the kit supplier to assure consistency of the Ab reagents, and that sufficient quantities would be reserved. Method robustness included the pre-study validation tests with a second lot of the capture Ab, three analysts, and three batches of radioiodinated detector Ab. Method robustness was further demonstrated by in-study validation, with four additional analysts performing sample analysis using 12 batches of radioiodinated detector Ab over a time span of approximately three years. 

Ruggedness is measured by imposing small variations on the experimental parameters and recording the results. Let us suppose we have developed an. AAS method and we want to test its robustness. The following seven parameters have been identified as possible sources of variation amount of water, reaction time, distillation rate, distillation time, n-Heptane, Aniline, and status of the reagent. For short, we will call these 7 variables or factors as AoW, Rt, Dr, Dt, n-H, Anl, SoR and perform a partial factorial experiment consisting of 8 experiments. The partial factorial experiment is described in Table 2.2. 

Once the data are collected and a topology constructed, it is necessary to evaluate the reliability of those data and the supported tree. It is important to keep in mind that even randomly generated data can lead to a single, best result. Therefore, several methods exist for testing the robustness of the final topology using analytical and resampling procedures (Table V). 

Ruggedness/robustness Defined based on an experimental design and data (sensitive parameters and a range for each parameter in the final test method)... 

HPLC method development has already been covered in Chapter 8. The focus of this chapter is to utilize HPLC and the data generated by this technique to help in developing a robust formulation for a drug product. However, the current section will discuss sample preparation solvent since it becomes an integral part of HPLC when we are discussing HPLC methods for a particular formulation. Any sample preparation solvent that is chosen for any HPLC method must be compatible with the HPLC solvents utilized for that particular test method. The current section will assume that a new molecular entity (NME) is utilized for a particular drug product. 

P. Sajonz, T. K. Natishan, Y. Wu, N. T. McGachy, and D. DeTora, Development and validation of a sensitive and robust wipe-test method for the detection and quantification of the antibiotic Ertapenem and its primary degradates in a pharmaceutical manufacturing environment, /. Liq. Chromatogr. Relat. Technol. 28 (2005), 713-725. 

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