**12. Method robustness**

128 Analytical Chemistry

established.

**11. System suitability** 

System suitability is intended to demonstrate that all constituents of the analytical system, including hardware, software, consumables, controls, and samples, are functioning as required to assure the integrity of the test results. System suitability testing is an integral part of any analytical method, as specified by ICH Q2R1. However, guidance is vague and reference is often made to Pharmacopeias for additional information. The USP, EP and JP contain guidance for a broad scope of HPLC assays, including assays of the active substance or related substances assays, assays quantified by standards (external or internal) or by normalization procedures, and quantitative or limit tests. While each type of assay is described in the compendia, the specific system suitability parameters to be applied for each type of assay, is not included with the description. Thus, some interpretation is required. The interpretation of how to best meet the requirements of the various compendia while still

Existing guidance for system suitability was developed for pharmaceutical compounds and may not be directly applicable for proteins which, due to their structural complexity and inherent heterogeneity, require additional considerations beyond those typically required for small molecules. For example, appraisal of resolution by measuring the number of theoretical plates (commonly done for small molecules), may not be the best way to assess the system readiness to resolve charge isoforms of a protein on an ion exchange column. This may be due to the relatively poor resolution of protein peaks resulting from inherent product microheterogeneity, when compared to the resolution typically seen with small molecules. However, this methodology (the number of theoretical plates) may be a very good indicator to measure the system performance for size exclusion chromatography (SEC), which does not typically resolve product isoforms resulting from microheterogeneity.

To appropriately establish system suitability, we need to consider both the parameter that will be assessed and the numerical or logical value(s), generally articulated as acceptance criteria, associated with each parameter. System suitability parameters are the operating parameters that are the critical identifiers of an analytical method's performance. System suitability should be demonstrated throughout an assay by the analysis of appropriate controls at appropriate intervals. It is a good practice to establish the system suitability parameters during method development, and to demonstrate during qualification that these parameters adequately evaluate the operational readiness of the system with regard to such factors as resolution, reproducibility, calibration and overall assay performance. Prior to validation, the system suitability parameters and acceptance criteria should be reviewed in order to verify that the previously selected parameters are still meaningful, and to establish limits of those parameters, such that meaningful system suitability for validation is firmly

One important issue that merits consideration is that the setting of appropriate system suitability parameters is a major contribution to operational performance in a Quality environment, as measured by metrics such as invalid assay rates. A key concept is that the

maintaining operational efficiency is a significant challenge for industry.

ICH Q2R1 prescribes that the evaluation of robustness should be considered during the development phase. The robustness studies should demonstrate that the output of an analytical procedure is unaffected by small but deliberate variations in method parameters. Robustness studies are key elements of the analytical method progression and are connected to the corresponding qualification studies.

Method robustness experiments cannot start before the final conditions of the method are established. It is a good practice to identify operational parameters for the method and to divide them in the order of importance into subcategories according to their relative importance, which are exemplified below:


It is highly impractical to evaluate the impact of all possible parameters on the output of the method. Therefore, robustness studies could be limited to the demonstration that the reported assay values are not affected by small variations of "essential" operational parameters. It is a good practice to prospectively establish a general design (outline) for such studies. Typically, in these types of studies a reference standard and/or other appropriate samples are analyzed at the nominal load. The studies may be carried out using the onefactor-at-a-time approach or a Design of Experiment (DOE) approach. The selection of assay parameters can vary according to the method type and capabilities of the factorial design, if applicable. It is essential to study the impact of all essential factors, and it is important to establish prospectively "target expectations" for acceptable changes in the output, to ensure that these robustness studies do not repeat the development work. The maximum allowable

change in the output of the analytical method can be linked to the target expectations for the precision of the method, which are derived from the Horwitz equation (Horwitz 1982; Horwitz and Albert 1997; Horwitz and Albert 1997). Recently a number of software packages have become available to assist with the design and data analysis (Turpin, Lukulay et al. 2009; Jones and Sall 2011; Karmarkar, Garber et al. 2011).

Analytical Method Validation for Biopharmaceuticals 131

Quality environment can be achieved. As analytical technologies continue to evolve, both the biotechnology industry and the regulatory authorities will need to continuously develop concepts and strategies to address how new technologies impact the way in which the Quality by Design principles inherent in the analytical lifecycle approach are applied to the development of biopharmaceutical products. The basic concepts are described in ICH

The ICH Q2 guideline requires that an analytical method be validated for commercial pharmaceutical and bio-pharmaceutical applications. Frequently, validation is done only once in the method's lifetime. This is particularly of concern when the future testing is performed on an instrument with different technical characteristics, in different geographic locations within the company and/or at contract laboratories around the world, using different consumables, different analysts, etc. This concern is exacerbated by the requirement for modern pharmaceutical and biopharmaceutical companies to seek regulatory approval in multiple jurisdictions, where the instrumentation, consumables, and scientific staff experience at the testing location may be very different than that present in the place where the drug was developed. These considerations raise questions about the value of the current format of the validation studies conducted by the industry. Moreover, it is not clear how the validation data obtained using existing methodologies should or even could be used toward the assessment of the uncertainty of the future results, given the many

Perhaps the time is right for the industry to consider the use of a combination of sound science and reasonable risk assessment to change the current practice of the retrospective use of method validation to the new paradigm of live validation of purity methods based on the current information embedded in the chromatogram. Laboratories that work in a GMP environment are required to produce extensive documentation to show that the methods are suitable. Pharmaceutical and biopharmaceutical companies thoroughly adhere to these requirements, inundating industry with an avalanche of validation work that has questionable value toward the future assessment of uncertainty. The predication of uncertainty provides an alternative that has the potential to reduce the work required to demonstrate method suitability and, in turn, provide greater assurance of the validity of the

The establishment of qualification target expectations can be considered as a form of Quality by Design (QbD), since this methodology establishes quality expectations for the method in advance of the completion of method development. Also, the analytical lifecycle described here covers all aspects of method progression, starting with method development, the establishment of system suitability parameters, and qualification and robustness activities, culminating in method validation, which confirms that the method is of suitable quality for testing in Quality laboratories. The entire analytical lifecycle framework can be considered as a QbD process, consistent with evolving regulatory expectations for pharmaceutical and

guidelines Q8, Q9 and Q10 (ICH 2005; ICH 2008).

factors that contribute to the uncertainty.

results from the specific analysis in real time.

biopharmaceutical process and product development.
