The use of biomarkers in clinical development for decision making is predicated on confidence in the data and the assay used. Parallelism is a critical experimental assessment that may or may not have been robustly determined and may be challenging to interpret. Without conducting this work for LBA and many LC/MS biomarkers assay there is uncertainty in the assay's reliability and utility. Parallelism demonstrates that both the calibrator, often a surrogate analyte (eg rh protein), and the surrogate matrix are suitable for the quantitative measurement of the biomarker analyte in biological matrix and clinical samples. During method development it may inform assay selection/design. It may also identify potential binding partners or disease/subject specific interferences. The presentation will provide a high-level update on from the AAPS Parallelism team’s draft best practices in execution and interpretation of parallelism data over the life cycle of biomarker assays.
Learning Objectives:
Understand the rational and importance of parallelism experiments for biomarker assay validation.