27/02/2017
PURPOSE :
Analytical Method Development
ANALYTICAL METHOD SELECTION:
Many new technologies are now available for bio pharmaceutical development. These analytical advances and their appropriate application are discussed in detail in the literature, Because these technologies are constantly improving—resulting in shorter testing times and increased throughput, ease of use, sensitivity, selectivity, and precision—at some point existing methods will be replaced with better ones. Automating a procedure, resulting in long-term savings and fewer operator errors, is one reason to follow this process. A more sensitive method may increase the likelihood of observing impurities at an upstream-process stage where corrective action is less expensive.
Qualified personnel should carefully select a new test methodology and its appropriate instrumentation. Changing biological assays. Accuracy is a prime consideration, because any bias in results must be reflected in the release specifications. When replacing existing technologies with automated or more sensitive ones, alert and action levels and associated specifications must be adjusted if needed. In-process and product specifications should reflect production process consistency and analytical capabilities, unless otherwise dictated by regulatory authorities.
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Current GMP guidelines state that GMP documentation and the detail of validation activities should increase as the production process progresses. Testing upstream stages may actually be more critical than many final container release tests because it provides evidence of fermentation quality and the efficiency of impurity removal—although the tests are more uncertain and variable. Final container testing attests that active and inactive formulation components remain at predicted levels with little variability.
Science- and risk-based testing should carefully evaluate different product quality attributes that can impact overall product quality. Testing for in-process impurities should emphasize overall measurement sensitivity, selectivity, and precision. In other words, the analytical method should detect batch-to-batch variations; whether the measurements are extremely accurate (100% recovery) is not as important.
Some of the most advanced and innovative analytical technologies may be extremely informative for characterization of product, impurities, or the product matrix, but may not be appropriate for product release testing. When selecting an appropriate quality control (QC) method, the pros and cons should be carefully weighed against each other. Solid evidence that the new method will provide equivalent or better results is necessary when submitting a license change to regulatory authorities. The method's requirements should be similar to instrument requirements and based on the expected capability of the new method, as determined by a careful data review and identification of critical assay characteristics.
ANALYTICAL METHOD DEVELOPMENT:
It is the responsibility of the analytical method development (AMD) Sr Analytical chemist to include the test method's details in the standard operating procedure (SOP), including optimization of assay elements (such as mixing volumes, number of replicates, and statistical data reduction). If practical, all AMD data should ideally be generated in a GMP environment. In other words, we should generate all development data with qualified equipment by qualified personnel, and properly document and summarize the data in an AMD report approved by quality assurance (QA).
Often, methods are not developed from the ground up, but are optimized for a particular product and product matrix. In any case, always follow a thorough optimization process, which includes incorporating the best-fit data reduction function.
A well-planned and controlled experimental design that emphasizes QC release-testing suitability will prevent multiple, unsuccessful trial-and-error efforts. Scientific and regulatory concerns must be balanced with potential economical restrictions.
QA approval is required at many points in method development and validation . Ideally, the process does not continue until it has been approved. Data generated using a final, optimized method may be used to set acceptance criteria for the AMV protocol. All instruments and equipment should be qualified and all relevant software should be validated, ensuring that all AMD data and results (summarized later in the AMV protocol) are valid from a compliance perspective.
Results in and outside the product specifications must be reliable. If the boundaries are fuzzy, it is not possible to clearly differentiate between acceptable and unacceptable (out-of-specification) results, and material may be improperly accepted or rejected.
Accuracy can be estimated by measuring the recovery of various spiked levels of particular analytes. Many critical assays of product purification efficiency and product quality determine product purity and impurities simultaneously (for example, protein composition by capillary zone electrophoresis [CZE] or high performance size exclusion chromatography [HP-SEC]).
Whenever relative percentages of various analytes are estimated using a single assay, response factors must be established and integrated (normalized) in the calculations in order to accurately report purity and impurity levels. Using different detectors to measure analyte signals (for example, HP-SEC with ultraviolet detection to measure protein aggregation versus laser-light scattering or refractive-index detection) affects these relative percentages and should be thoroughly evaluated during AMD. A simple way to directly compare response factors from various detectors during AMD is to connect all detectors in-parallel (or inline).10
SYSTEM SUITABILITY:
The test system must be properly controlled to ensure reliable release-testing results. The system suitability criteria should be established during the AMD and optimization phase. This is usually accomplished by running a set of control points. For each test, system suitability will be satisfied (valid test results generated) if all control points are in established limits. A test system must be able to reproduce measurable results of a homogeneous sample (control) to allow examination of differences between batches. Small differences in batches are normal and acceptable, but the sources of variation should be identified. Ultimately, we will have more certainty when we can separate differences in production batches from assay variability.
SAMPLE SUITABILITY:
Technically, sample suitability is part of system suitability so these parameters can be evaluated together. Sample suitability should be established during AMD and should ideally ensure that samples, controls, and standards are prepared identically and run simultaneously. In addition, sample suitability should include a statistical analysis of the number of replicates needed to generate significant release results. Single measurements may be acceptable if the production-process sampling can deliver truly batch representative samples and the precision of assay repeatability is high compared to the product specifications—and therefore high compared to the batch-to-batch variation on which these specifications are based.
ROBUSTNESS:
Robustness, defined as the lack of a significant effect when small changes are deliberately introduced into the test system, should ideally be addressed during the method optimization phase and not as part of AMV. We should know the degree of robustness of a method before starting the formal AMV phase. Critical test system parameters (for example, the acceptable range of diluting the test sample) must be identified and controlled with appropriate operational limits. These limits should be described in the AMD report and documented in the method SOP. The SOP will then contain operational limits which are in the context of the overall system suitability criteria and which are adhered to during the validation phase. In addition, robustness should be tested in the AMD phase during or after method optimization because significant differences in the AMV results (from challenging the critical operational limits) may be difficult to explain in the AMV report.
We must remember that AMV is the formal evidence that this method is suitable to be used under strictly controlled QC testing conditions. The AMV protocol should be set up to deliver this evidence through appropriate acceptance criteria by varying sample batches and concentrations, operators, instruments, days, and other factors that are expected to vary during routine testing—in established sample and system suitability conditions and operational limits.