Analytical procedure robustness

The robustness of an analytical procedure is a measure of its capacity to remain unaffected by small, but deliberate, variations in method parameters this provides an indication of its reliability during normal usage. 

Thompson, M., Robust Statistics and Functional Relationship Estimation for Comparing the Bias of Analytical Procedures over Extended Concentration Ranges, Anal. Chem. 61, 1989, 1942-1945. 

Analytical methods, particularly those used by accredited laboratories, have to be validated according to official rules and regulations to characterize objectively their reliability in any special field of application (Wegscheider [1996] EURACHEM/WELAC [1993]). Validation has to control the performance characteristics of analytical procedures (see Chap. 7) such as accuracy, precision, sensitivity, selectivity, specificity, robustness, ruggedness, and limit values (e.g., limit of detection, limit of quantitation). 

Multifactorial experiments are used in analytical chemistry for diverse applications, e.g., checking up significant influences before optimization procedures, recognizing matrix effects, and testing the robustness of analytical procedures (Wegscheider [1996]). 

As a measuring science, analytical chemistry has to guarantee the quality of its results. Each kind of measurement is objectively affected by uncertainties which can be composed of random scattering and systematic deviations. Therefore, the measured results have to be characterized with regard to their quality, namely both the precision and accuracy and - if relevant - their information content (see Sect. 9.1). Also analytical procedures need characteristics that express their potential power regarding precision, accuracy, sensitivity, selectivity, specificity, robustness, and detection limit. 

Consequently, it was proposed to define (Burns et al. [2005]) Robustness of an analytical procedure is the property that indicates insensitivity against changes of known operational parameters on the results of the method and hence its suitability for its defined purpose and Ruggedness of an analytical procedure is the property that indicates insensitivity against changes of known operational variables and in addition any variations (not discovered in intra-laboratory experiments) which may be revealed by inter-laboratory studies (Burns et al. [2005]). 

The robustness of an analytical procedure for the determination of the analyte A in presence of some accompanying species i = B,...,N under influence of various factors fj(j = l,...,m) according to Eq. (4.30) is in reciprocal proportion to the sum of all their cross sensitivities, SA multiplied by the actual amounts, x and the specific influencing strengths, hjy of the factors multiplied by their actual values (in relation to xA) see Danzer (2004). Because of the way measurements are obtained, the range of their values is range = (0... oo), so it makes sense to calculate the relative robustness which includes the analyte sensitivity and amount itself, SAA xA, as follows ... 

Relative robustness will have values between 0 (no robustness) and 1 (ideal robustness). Burns et al. [2005] defines the relative robustness of an analytical procedure as the ratio of the ideal signal for an uninfluenced method compared to the signal for a method subject to known operational parameters determined in an intra-laboratory experiment (Burns et al. [2005]). 

Burns DT, Danzer K, Townshend A (2005) IUPAC, Analytical Chemistry Division Use of the terms Robust and Rugged and the associated characteristics of Robustness and Ruggedness in descriptions of analytical procedures. Draft 2005... 

Based on the examination of analytical data from polychlorinated biphenyls (PCBs), OCPs and PAHs spiked into SPMDs, which have subsequently been subjected to the entire SPMD analytical procedure described herein, recoveries are generally >75% with good precision (i.e., C.Fs < 20%). Surprisingly, the C. Vis for the analysis of contaminants present in replicate SPMDs deployed contiguously at the same sites and treated identically during analysis are often equivalent to C.Fs of SPMD spikes. This observation suggests that the variability of analyte sampling rates of replicate SPMDs in the field is small and that the analytical methods used for field-deployed SPMDs are robust. 

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. 

Reliable quality control in the field of pharmaceutical analysis is based on the use of valid analytical methods. For this reason, any analytical procedures proposed for a particular active pharmaceutical ingredient and its corresponding dosage forms shonld be validated to demonstrate that they are scientifically sonnd nnder the experimental conditions intended to be used. Since dissolntion data reflect drng prod-net stability and quality, the HPLC method used in snch tests shonld be validated in terms of accuracy, precision, sensitivity, specificity, rngged-ness, and robustness as per ICH guidelines. 

The ICH guidelines define robustness as The robusmess of an analytical procedure is a measure of its capacity to remain unaffected by small, but deliberate variations in method parameters and provides an indication of its reliability during normal usage.Thus, the robustness of a method is a measure of its capacity to be transferred to another laboratory without affecting the analytical result. A robustness test is the experimental setup applied to evaluate the robustness of the method. The ICH guidelines also state that One consequence... 

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. 

The evaluation of robustness should be considered in the development of the assay and will depend on the type of procedure under development. It must show the reliability of a method with respect to deliberate variations in method parameters. If measurements are susceptible to variations in analytical conditions, the analytical conditions should be suitably controlled or a precautionary statement might be included in the procedure. One consequence of the evaluation of robustness may be that a series of system suitability parameters is established to ensure that the validity of the analytical procedure is maintained whenever used. Typical parameters to be tested would be the following sample concentration, sample stability, labeling variability (if applicable), injection variability, reagent lot-to-lot variability, and capillary vendor. 

MDOE embraces a number of tools which permit experiments to be conducted in the most efficient possible way, achieving several interesting results such as screening of the important factors, optimization of manufacturing and analytical procedures, minimization of costs and pollution, and robustness testing of products and processes. 

The evaluation of robustness is normally considered during the development phase and depends on the type of procedure under study. Experimental design (e.g., fractional factorial design or Plackett-Burman design) is common and useful to investigate multiple parameters simultaneously. The result will help to identify critical parameters that will affect the performance of the method. Common method parameters that can affect the analytical procedure should be considered based on the analytical technique and properties of the samples ... 

Other robustness considerations for ruggedness of the analytical procedure during validation include the following ... 

The objective for any analytical procedure is to enable consistent and reliable data of the appropriate quality to be generated by laboratories. Such procedures should be sufficiently well-defined and robust to ensure the best use of resources and to minimise the possibility of expensive large-scale collaborative trials yielding unsatisfactory results through lack of application of best practices. As part of achieving the objectives of the AMC it was felt that such a handbook would enable a consistency of approach to the work of the sub-committees. 

A simple example, focusing on the analytical procedure, will illustrate the type of experimental design used to investigate three key factors in an HPLC method. Detailed discussion of experimental designs for robustness testing can be found in Morgan and Hendriks et Riley and Rosanske provide an... 

---