In this final post regarding bioanalysis, I will review a few of the main ideas related to bioanalytical method validation. The purpose of a method validation is to demonstrate that a specific bioanalytical method can reliably determine the concentration of drug in a study sample with a high degree of confidence. Validation does not mean that a method is perfect, or even adequate for the study. Validation means that the method has met a set of criteria designed to ensure that it is reliable and consistent.
The main areas of assay validation are: selectivity, accuracy, precision, recovery, sensitivity, reproducibility, and stability.
- Selectivity: the detection of the molecule of interest when many other molecules may be present in the sample.
- Accuracy: how close the measured value is to the true value.
- Precision: the spread between successive measurements of the same sample.
- Recovery: the amount of drug in the sample compared to the amount of drug measured.
- Sensitivity: the lowest level at which the molecule of interest can be detected with adequate confidence.
- Reproducibility: the accuracy and precision over multiple days, operators, and other experimental conditions.
- Stability: the amount of degradation of the molecule of interest from the time of sample collection to the time of sample analysis.
The FDA has provided a specific guidance that addresses all of these areas and gives specific requirements to validate a method (link). As a pharmacokineticist, you should familiarize yourself with these method validation topics so that you can effectively communicate with the bioanalyst during the method development and validation effort. Also, your input on sample collection and handling procedures will be critical to determining the stability of the drug (and metabolites) from the time of collection to the time of analysis. I hope this series on bioanalysis methods and techniques is helpful as you interface with your colleagues.
Today, drug development is carried out in human subjects and animals. However, as computing power and the number of sophisticated technology platforms grow exponentially, and our knowledge of human health and disease increases, the virtualization of clinical research and development will grow steadily. Read this article to learn more.