{Reference Type}: Journal Article
{Title}: Best Practices in mAb and Soluble Target Assay Selection for Quantitative Modelling and Qualitative Interpretation.
{Author}: Fairman D;Tang H;
{Journal}: AAPS J
{Volume}: 25
{Issue}: 1
{Year}: 02 2023 9
{Factor}: 3.603
{DOI}: 10.1208/s12248-023-00788-4
{Abstract}: Biologics, especially monoclonal antibodies (mAbs), are an increasingly important part of the drug discovery and development portfolio across the pharmaceutical industry. To enable robust demonstration of pillars 1 and 2 [1] for mAbs, specialised assays are required to measure the complex interactions between mAb and target. This is especially important for the interpretation of soluble target interactions. In some instances, multiple assays with overlapping purposes (e.g., developing both complex and total assays) have been developed. In retrospect, these efforts may have led to excessive time and resources spent in assay development and the generation of data that is contradictory or misleading. Our recommendation is to invest resources early into the development of total assays for both mAb and target. Free target assay data may be inaccurate and report higher levels of free target than are present in the sample at collection due to re-equilibrium during measurement. Total assay formats are inherently less sensitive to the effects of sample preparation, assay conditions, and re-equilibration than free or complex assays. It is acknowledged that pathology/pharmacology is ultimately driven by the free target and knowledge of its dynamics are critical. However, generation of appropriate total target data and using model-based estimation of free target concentrations is a more robust approach than utilisation of direct assay derived estimates. Where free data are utilised, the potential biases should be prospectively considered when developing the assay and utilising the data for quantitative analyses.