Analytical method validation robustness

The majority of 21 CFR 211.160 (laboratory controls) and subsections can be applied in the same manner for clinical supplies as for commercial products. An exception, in many cases, is the time by which analytical methods validation is required. For new chemical entities or significant formulation changes, new analytical methods may need to be developed. As with manufacturing processes, until such methods are robust it is difficult (or impossible) to validate them to the full extent that is expected for commercial products. 

Test methods used in the laboratory are generally derived from pharmacopeias 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 limit and range. A discussion of analytical methods validation is presented in Section 9.6.5. 

The process of method validation (i.e., evaluation of the assay) affects the quality of the quantitative data directly [9 A Guide to Analytical Method Validation, Waters Corporation]. Through method validation, it is assured that the method developed is acceptable. Issues involved in the validation of a mass spectrometry method for quantitative analysis are similar to those in any other analytical technique. The validation involves undertaking a series of studies to demonstrate the limit of detection G OD) limit of quantitation (LOQ) linear range specificity within-day precision and accuracy and day-to-day precision and accuracy, specificity, and robustness of the method. All of these parameters must be determined with those commonly accepted good laboratory practices criteria that are applicable in the vafidation of analytical methods. 

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. 

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). 

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. 

Final methods are developed for transfer to operational quality control (QC) laboratories for the release testing of production batches. Additionally, the methods are intended to be applied during Registration Stability studies and for the release of the DP or DS validation batches during the pre-approval development stage. The analytical methods should last for the entire product lifetime therefore, the aim of final method development is to generate fast, robust, reliable, and transferable HPLC methods (preferably isocratic and at low cost). 

As shown in Figure 11, before extensive validation, the performance of the method is evaluated appropriately. Column durability tests, robustness testing for the chromatographic and sample preparation conditions, analytical method evaluation ring tests (AMERTs), method capability assessments, and pre-validation studies are applied to... 

System suitability test characteristics and limits are recommended as a component of any analytical method. This ensures that both methodology and instrumentation are performing within expectations prior to the analysis of test samples. The test characteristics are inferred from robustness studies and evaluated during the validation experiments. 

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. 

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. 

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. 

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. 

In analytical chemistry, validation of the analytical methods is of utmost importance [4,5]. One of the aspects of this validation is the robustness of analytical methods against variations in experimental circumstances. The term experimental circumstances is very broad it might even include inter-laboratory variation. In this book, only intra-laboratory experimental conditions are considered. No explicit attention is given to inter-laboratory variations, although some of the presented methodology might be useful in that area. 

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. 

The key to successful integration of automation into the modem analytical laboratory is a sound approach to method development and validation. The end result of a well-developed and validated automated method will be a robust analytical method that should pay dividends by being able routinely to produce sound analytical data to support crucial regulatory submissions. 

Typical parameters that are generally considered most important for validation of analytical methods are specificity, selectivity, precision, accuracy, extraction recovery, calibration curve, linearity, working range, detection limit, quantification limit, sensitivity, and robustness. 

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. 

Analytical testing (preformulation, stability, product release) is a core component of pharmaceutical operations from early R D through manufacturing of the commercial product. The original analytical methods are usually developed by the pioneer pharmaceutical firm and transferred to the provider. In some cases, the early methods are only preliminary methods and are not sufficiently robust to test the quality of downstream (clinical, commercial, and line extension) products and facility quality practices (cleaning validation). In those situations, the supplier is often asked to develop new methods, and in some cases those methods are transferred back to the client. In either scenario, the transfer of validated analytical methodology consists of the following four main tasks [52] ... 

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