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Apostol et al. Apostol, Kelner et al. The model allows for real-time assessment of all performance characteristics using the results of the specific separation of interest. A fundamental, underlying principle of this approach recognizes that the execution of a purity method is always associated with specific circumstances; therefore, uncertainty about the generated results needs to account for both the operational conditions of the method and the hardware.
The authors demonstrated that noise levels, instrument and software settings can be linked directly to all method performance characteristics. The UBCI model approximates the maximal uncertainty of the measurement associated with the actual conditions of analysis test. The obtained precision corresponds to the uncertainty under the most unfavorable conditions, including the highest variability of injection, maximal numeric integration error, expected variability of the peak width, and the most unfavorable contribution of the noise.
UBCI shows that the uncertainty of results is not only a function of the method composition of the mobile phase, gradient, flow rate, temperature , but also is influenced by the hardware associated with the execution of the method pump pulsation, detector range, status of the lamp, etc. Application of historical validation data always begs a question about the relevance of these data to the current experimental situation, and sometimes requires investigation, which can delay the approval of results.
The UBCI approach, therefore, has the capability of providing not only simplicity, but also a greater level of assessment of the data validity relative to current practices. The determination of accuracy for protein purity methods presents significant challenges. Since it is difficult to establish orthogonal methods for proteins to measure the same quality attribute, it is hard to assess the truthfulness of the accuracy measurements. For example, although SEC-HPLC results can be verified by analytical ultra centrifugation AUC techniques, these techniques are based on very different first principles, and may not provide comparable results Carpenter, Randolph et al.
Pharmaceutical method development and validation
Therefore, in most cases, the accuracy of purity methods for proteins is inferred when other performance characteristics meet expectations, which is consistent with the principles of ICH Q2R1 ICH Linearity and range are typically assessed in a complex experiment demonstrating a linear change of peak area with analyte concentration. Since most of the methods use UV detection, such linearity experiments can be considered as re-confirmation of the Beer-Lambert law for the particular hardware configuration.
The specificity of analytical methods is typically assessed by examining system interference with the detection and quantification of analytes. Part of this evaluation is the determination of protein recovery from the column Rossi, Pacholec et al. The recovery determination requires the knowledge of the extinction coefficient for the protein, which can be calculated from its amino acid composition Pace, Vajdos et al.
It should be noted that the extinction coefficient of a protein may change as a function of pH Eberlein ; Kendrick, Chang et al. Therefore, direct comparison of the recovery in the neutral pH, size exclusion method with the recovery in an acidic reversed-phase separation may not be valid due to differences in the operating pHs of the methods. The difference may not necessarily reflect the actual recovery, but rather shows pH dependent changes of spectroscopic properties of the protein.
With such an approach, the specificity of the method can be assessed in every assay, and reflects dynamically the change in status of consumables columns and mobile phases and hardware.
Practical application of LOD is related to the decision about integration of chromatograms, electropherograms or spectra, while LOQ is related to the decision on whether to report the results of tests on official documents, such as the Certificate of Analysis CoA for the lot. ICH Q2R1 suggests three different approaches: visual inspection, signal-to-noise-ratio, or variability of the slope of the calibration curve statistical approach.
Vial and Jardy, andApostol et al. If those values are not within the same order of magnitude, then the integrity of the source data should be investigated.
The statistical approach is most commonly practiced, and is associated with the use of well known equations:. The SD can be easily obtained from linear regression of the data used to create the calibration curves. The most common way to present calibration data for the purpose of linear regression is to graph the expected analyte concentration spiked, blended vs.
This type of plot is characteristic of analytical methods for which the response is a linear function of the concentration e. UV detection that follows the Beer-Lambert law. In cases where the measured response does not follow a linear dependency with respect to concentration e.
Since the LOD and LOQ are functions of instrument sensitivity, these values, when defined this way, are not universal properties of the method transferable from instrument to instrument, or from analyte to analyte. Considering LOD from the perspective of the decision to include or disregard a peak for integration purposes, stresses the importance of signal-to-noise ratio as a key parameter governing peak detection.
Analytical Instrument Qualification and USP Compliance
Defining LOD as 3. LOD expressed in this format is a dynamic property due to the dependency on the type of instrument, status of the instrument, and quality of the consumables. LOD determined this way will be expressed in units of peak height, e. The decision about reporting a specific analyte on the CoA is typically linked to specifications.
After the decision about integration has been made for all analytes resolved defined by the method, the results are recorded in the database e. When all analytical tests are completed, the manufacturer creates the CoA by extracting the relevant information from the database. Only a subset of the results, which are defined by specifications, will be listed on the CoA. The specifications will depend on the extent of peak characterization and the clinical significance of the various peaks Apostol, Schofield et al.
Therefore, the list will change evolve with the stage of drug development. In such a context, LOQ should be considered as the analyte specific value expressed in units of protein concentration, a calculation for which instrument sensitivity cannot be disregarded in contrast to LOD estimation. The signal created by the analyte may vary with the load, while the relative percentage of the analyte does not change.
This creates a situation where the analyte of interest can be hidden within the noise or, alternatively, can be significantly above the noise for the same sample analyzed at two different load levels within the range allowed by the method. The above equation expresses LOQ as a function of signal-to-noise ratio and the observed purity of the analyte.
Both parameters can change from test-to-test, due to equipment variability and sample purity variability. Therefore this equation should be viewed as the dynamic live assessment of LOQ. 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. 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 maintaining operational efficiency is a significant challenge for industry.
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.
Practical Approaches to Method Validation and Essential Instrument Qualification / Edition 1
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 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 established.
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 purpose of system suitability is to ensure appropriate system performance including standards and controls , not to try to differentiate individual sample results from historical trends e.
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In practice, setting system suitability parameters that are inappropriately stringent can result in the rejection of assay results with acceptable precision and accuracy. 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. It is a good practice to prospectively establish a general design outline for such studies.
The studies may be carried out using the one-factor-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. 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 ; Horwitz and Albert ; Horwitz and Albert Recently a number of software packages have become available to assist with the design and data analysis Turpin, Lukulay et al.
Remediation of validated analytical methods is typically triggered by the need to improve existing methods used for disposition of commercial products.
The improvement may be required due to an unacceptable rate of method failures in the GMP environment, lengthy run times, obsolete instruments or consumables, the changing regulatory environment for specifications or stability testing, or for other business reasons.
We anticipate that technological advances will continue to drive analytical methods toward increasing throughput. In this context, it appears that many release methods are destined for change as soon as the product has been approved for commercial use Apostol and Kelner ; Apostol and Kelner This is due to the fact that it takes more than 10 years to commercialize a biotechnology drug, resulting in significant aging of the methods developed at the conception of the project. Therefore, the industry and regulators will need to continuously adjust strategies to address the issue of old vs.
Frequently, old methods have to be replaced by methods using newer technologies, creating a significant challenge for the industry in providing demonstration of method equivalency and a corresponding level of validation for the methods. When we consider the critical role that analytical method development, qualification and validation play in the biopharmaceutical industry, the importance of a well designed strategy for the myriad analytical activities involved in the development and commercial production of biotechnology products becomes evident.
The method qualification activities provide a strong scientific foundation during which the performance characteristics of the method can be assessed relative to pre-established target expectations. This strong scientific foundation is key to long-term high performance in a Quality environment, following the method validation, which serves as a critical pivotal point in the product development lifecycle.
As noted previously, the method validation often serves as the point at which the Quality organization assumes full ownership of analytical activities. If done properly, these activities contribute to operational excellence, as evidenced by low method failure rates, a key expectation that must be met to guarantee organizational success.
Without the strong scientific foundation provided by successful method development and qualification, it is unlikely that operational excellence in the 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. It can further help to avoid costly and time consuming exercises.
Analytical Chemistry is the branch of Science that uses advance technologies in determining the composition by analytical technique. We can achieve both qualitative as well as quantitative results. Analytical instruments play a major role in the process to achieve high quality and reliable analytical data. Thus everyone in the analytical laboratory should be concerned about the quality assurance of equipment.
Analytical method could be spectral, chromatographic, electrochemical, hyphenated or miscellaneous.