Robustness method validation elements

Assay validation characterizes the assay performance so that the significance of the measured assay values obtained is readily understood [75]. Test methods should be validated when important decisions are to be based on the data generated [30]. Thus, the extent of method validation depends on the stage of clinical supply manufacture. The key elements of assay validation for a method are to establish reliability, the intra- and interlaboratory test variation, and relevance, the meaning of the results for a specific purpose [19]. The robustness of an analytical procedure (according to the ICH-Validation of Analytical Methods, 1993) is its measured capacity to be unaffected by small variations in controlled parameters and reliability under normal usage [35]. 

Verification implies that the laboratory investigates trueness and precision in particular. Elements which should be included in a full validation of an analytical method are specificity, calibration curve, precision between laboratories and/or precision within laboratories, trueness, measuring range, LOD, LOQ, robustness and sensitivity. The numbers of analyses required by the NMKL standard and the criteria for the adoption of quantitative methods are summarized in Table 10. 

Finally, process analytics methods can be used in commercial manufacturing, either as temporary methods for gaining process information or troubleshooting, or as permanent installations for process monitoring and control. The scope of these applications is often more narrowly defined than those in development scenarios. It will be most relevant for manufacturing operations to maintain process robustness and/or reduce variability. Whereas the scientific scope is typically much more limited in permanent installations in production, the practical implementation aspects are typically much more complex than in an R D environment. The elements of safety, convenience, reliability, validation and maintenance are of equal importance for the success of the application in a permanent installation. Some typical attributes of process analytics applications and how they are applied differently in R D and manufacturing are listed in Table 2.1. 

For the manufacture of clinical material, an IND-enabling method must be established under current Good Manufacturing Practice (cGMP) with validation of some critical elements. The whole process should be designed for robustness and scalability very early on. 

The analytical procedures to assess stability must encompass the elements common to validating analytical assays. The methods must be validated according to the parameters of accuracy, precision, robustness and specificity, limits of detection and quantitation, linearity of active ingredient assays, degradants, and other reaction products. More information on how to develop stability indicating methods is discussed in Chapter 7. Validation of these methods is discussed in Chapter 8. 

For validating analytical methods for testing stability samples, the following elements need to be considered accuracy, precision, linearity, range, specificity, robustness, and detection and quantitation limits. Each of these terms is defined and discussed below. 

At present the real strength of LA lies in the measurement of distribution patterns of minor and trace elements in solid samples with high spatial resolution. Homogeneity testing is an application of LA-ICP-MS. There is an increasing demand for the development and validation of accurate and robust analytical technologies for the determination of the chemical characteristics of polymeric products in support of industrial needs, EC regulations (e.g. Directive on toy safety) or research. Needs are particularly acute for techniques able to determine trace element contents in solids with a minimum sample preparation. For this purpose, laser ablation-based methods, such as LA-ICP-AES/MS and laser-induced plasma atomic emission spectrometry (LIP-AES, LA-AES or LIBS) have already... 

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