Method robustness

With respect to method robustness. Table 11-4 shows results obtained on several different days during which a variety of buffer conditions were used. As can be seen from the table, the vial corresponding to the maximum concentration of the individual enantiomers as well as the number of vials containing piperoxan is fairly constant. 

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. 

The method(s), supporting validation reports, related knowledge and target specifications are critical inputs into risk assessment process. A review is performed jointly by a transfer team from both sites. There is an assessment of complexity (simple vs. complex) and prior knowledge (similar methods/API/products already transferred vs. no experience), method robustness (low vs. high concern), which can affect quality post transfer (low vs. high risk). 

Method robustness may be evaluated during method development. 

TABLE 7 Typical Parameters and Ranges Evaluated During Method Robustness... 

TABLE 8 Example of a Plackett-Burman Experimental Design to Evaluate the Effect of varying Seven Conditions on Method Robustness... 

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... 

Most frequently, the design results, or more specifically the factor effects, are analyzed graphically and/or statistically, to decide on method robustness. A method is considered robust when no significant effects are found on responses describing the quantitative aspects. When significant effects are found on quantitative responses, non-significance intervals for the significant quantitative factors can be defined, to obtain a robust response. However, no case studies were found in CE where such intervals actually were determined. 

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. 

T. Kourti, Abnormal situation detection, three-way data and projection methods robust data archiving and modeling for industrial applications, Ann. Rev. Control, 27, 131-139 (2003). 

Built-in Robustness in Method Procedure. The following are some suggestions to improve method robustness ... 

For many method development problems, three or four factors are often the norm. The message is clearly that a simple approach to experimental design can be a crucial tool in ascertaining those factors which need to be controlled in order to maximise method robustness. In this example, the level of citric acid will have to be tightly controlled, as well as the methanol concentration, if consistent and high values of CRF are to be regularly obtained. 

J. A. Day, M. Montes-Baydn, A. P. Vonderheide, and J. A. Caruso, A Study of Method Robustness for Arsenic Speciation in Drinking Water Samples by Anion Exchange HPLC-ICP-MS, Anal. Bioanal. Chem. 2002,373, 664. 

The main purpose of this paper is to explore the robustness of SFE as an analytical technique. To do this, we have used guidelines published by the AOAC (14), Association of Official Analytical Chemists, as a way to define and measure contributors to method robustness. In particular, method robustness can be characterized by the reliability of the analytical instrumentation employed and the precision (variability) of the results. In the "Results and Discussion" section, anecdotal information will be presented as an indication of instrumentation reliability and many studies will be summarized to provide precision data for the factors of replicability, repeatability, and reproducibility. 

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. 

Method robustness was established to show assay consistency with various supplies of the reference standards and two other critical reagents ... 

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. 

The remaining chapters of the book introduce some of the advanced topics of chemometrics. The coverage is fairly comprehensive, in that these chapters cover some of the most important advanced topics. Chapter 6 presents the concept of robust multivariate methods. Robust methods are insensitive to the presence of outliers. Most of the methods described in Chapter 6 can tolerate data sets contaminated with up to 50% outliers without detrimental effects. Descriptions of algorithms and examples are provided for robust estimators of the multivariate normal distribution, robust PC A, and robust multivariate calibration, including robust PLS. As such, Chapter 6 provides an excellent follow-up to Chapters 3, 4, and 5. 

We now illustrate some recent examples of chemometrical modeling of IPC systems for the sake of clarity. In the framework of a quality by design approach, statistically designed experiments were used to optimize the IPC condition for the analysis of atomoxetine and impurities and demonstrate method robustness. 

Day, J.A., Montes-Bayon, M., Vonderheide, A.P., Caruso, J.A. A study of method robustness for arsenic speciation in drinking water samples by anion exchange HPLC-ICP-MS. Anal. Bioanal. Chem. 373, 664-668 (2002)... 

Step B. Once spT a is determined, the spH at which the analyte would be in its fully neutral form (>99%) needs to be determined. This corresponds to that is 2 pH units greater than the IpKa of 4.7 (calculated above). Note that if one wanted to determine the IpH in which the analyte would be >90% of its neutral form, this would correspond to working spH 1 unit greater than the IpKa of 4.7. (This is also acceptable from a method robustness point of view.)... 

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