Bioanalytical method validation is crucial for the success of bioanalytical studies supporting different phases of drug development. Validating a bioanalytical method ensures the data generated is safe and effective for the intended applications. However, researchers must address specific critical questions around bioanalysis method validation. These questions include assessing assay specificity, variability with measurements, quantification range, and sample handling and storage.
Today, recommendations such as FDA bioanalytical method validation (BMV) guidance and ICH guidelines for method validation talk about the fit-for-purpose concept. This concept states that the level of method validation must be adequate to fulfill the intended application of the assay. This notion means that the level of method validation will change at different phases of drug development. For example, studies like BA/BE supporting regulatory approval require full assay development and validation. In contrast, early exploratory studies may not need such stringent requirements. Hence, the current article discusses critical concepts that bioanalysis services must comply with during bioanalytical method validation.
Concepts to comply with during method validation
A validated bioanalytical technique proves the method is suitable for the intended analysis of study samples. FDA GLP guidance has specific recommendations for bioanalytical method validation. Following are some guidelines.
- Sponsors must perform a full method validation for a new method that analyzes a new drug entity
- Sponsors must conduct a full method validation if revisions are made to an already validated bioanalytical method
- Each bioanalytical method must have a detailed standard operating procedure before method validation. The description must include procedures for controlling method parameters
- All experiments conducted during method validation must be documented and reported
- Moreover, the drug product must be validated in the intended biological matrix.
Bioanalytical method validation has specific acceptance criteria for different parameters. These parameters include:
- Reference standards and critical reagents
- Calibration curve
- Quality Control samples
- Selectivity and Specificity
- Sensitivity
- Accuracy
- Precision and Recovery
- Stability
- Dilution effects
Depending on the ultimate objectives, sponsors may conduct partial or cross-validations. Generally, partial validations are conducted to assess an already validated method. Partial method validation can range from a single element, such as intra-assay precision, to nearly a full method validation. Some specific categories for partial method validation include:
- Method transfer between different labs
- Change in methodology
- Changes in sample processing
- Changes in platform or instruments
- Changes in matrices
- Expanding assay range
- Changes in critical reagents
- Demonstrating assay selectivity in the presence of other medications
Also Read: CRO Diaries: A Quick Guide To Clinical Biomarkers
On the other hand, cross-validation compares method validation parameters between two or more methods or techniques. These methods generate data across separate studies or within the same study. Moreover, cross-validation is crucial when samples within a single study are evaluated at different laboratories or experimental sites. In these types of validation, researchers must conduct cross-validation using shared matrix quality controls and non-pooled samples at each study site. These initiations help demonstrate interlaboratory reliability. Besides, when the study sample volume is insufficient, researchers can use pooled incurred samples for analysis. Notably, a validation plan or standard operating procedure must include these specifications.
