Developing reliable bioanalytical assay methods is vital at every step of drug discovery and development. A bioanalytical assay must be developed and validated in the intended matrix of choice to determine assay parameters for supporting toxicokinetic, pharmacokinetic, bioavailability, and bioequivalence studies. Bioanalytical assays employed in these studies are crucial / in assessing pharmacological drug products. Hence, sensitive and selective bioanalytical assays are critical for the success of preclinical and clinical pharmacological studies. Robust assay development and validation ensure that the bioanalytical assay will yield accurate, reliable, and reproducible results.
Bioanalytical assays are continually developed and improved. In many cases, they are the leading cutting-edge technology in pharmaceutical sciences. Each bioanalytical assay will have unique features, depending on the analyte of interest. Therefore, each assay may need specific validation standards for the analyte of interest. Moreover, assay validation approaches impact the ultimate objective of the study. Hence, the current article highlights common approaches and criteria for bioanalytical assay validation.
Bioanalytical Assay Validation
As a drug development project moves from early discovery and preclinical studies toward clinical development, bioanalytical assays will undergo numerous modifications. These changes will require a series of demonstrations to validate assay performance. Hence, there are three levels of assay validation: full validation, partial validation, and cross-validation.
Full assay validation is needed when developing a novel drug entity. If an assay quantifies additional metabolites, then the revised assay must be fully validated for all analytes present in the sample.
Partial validation is required for assays that do not need full revalidation. Although, partial assay validation may range from testing for a single parameter, such as precision or accuracy, to conducting a nearly full assay validation. Some situations when partial assay validation is needed include assay transfer between laboratories, change in species, change in the matrix, change in methodology, change in instrument or software, and change in sample processing protocols.
On the other hand, cross-validation compares two bioanalytical methods. They are necessary when two or more assays are used to generate study results. For instance, the original assay can serve as a reference to the revised version. Besides, this comparison should be both ways. Some examples of cross-validation include when different analytical techniques are used to generate regulatory submission data and when samples within the same study are tested at different laboratories and study sites. For sample analysis at different sites, one must conduct cross-validation with spiked matrix and study samples at each testing site or laboratory.
Moreover, specific parameters are assessed in the validation of bioanalytical assays. However, these validation parameters will vary from analyte to analyte and the intended application of the assays. Generally, the parameters assessed during bioanalytical assay validation include:
- Linearity
- Specificity
- Sensitivity
- Calibration model
- Accuracy
- Bias
- Precision and repeatability
- Reproducibility
- Limits (lower limit of quantification and upper limit of quantification)
- Stability (long-term stability, freeze/thaw stability, in-process stability, and processed sample stability)
- Recovery
- Robustness
In Conclusion
Robust validation results are crucial for demonstrating the reliability of bioanalytical assays and the successful conduct of preclinical and clinical studies.
Must Read: Inside the Bioanalytical Laboratory: Where Cutting-Edge Science Meets Real-World Applications!
