Mitigation of microtiter plate positioning effects using a block randomization scheme

Abstract

Microtiter plate-based assays are a common tool in biochemical and analytical labs. Despite widespread use, results generated in microtiter plate-based assays are often impacted by positional bias, in which variability in raw signal measurements are not uniform in all regions of the plate. Since small positional effects can disproportionately affect assay results and the reliability of the data, an effective mitigation strategy is critical. Commonly used mitigation strategies include avoiding the use of outer regions of the plate, replicating treatments within and between plates, and randomizing placement of treatments within and between plates. These strategies often introduce complexity while only partially mitigating positional effects and significantly reducing assay throughput. To reduce positional bias more effectively, we developed a novel block-randomized plate layout. Unlike a completely randomized layout, the block randomization scheme coordinates placement of specific curve regions into pre-defined blocks on the plate based on key experimental findings and assumptions about the distribution of assay bias and variability. Using the block-randomized plate layout, we demonstrated a mean bias reduction of relative potency estimates from 6.3 to 1.1 % in a sandwich enzyme-linked immunosorbent assay (ELISA) used for vaccine release. In addition, imprecision in relative potency estimates decreased from 10.2 to 4.5 % CV. Using simulations, we also demonstrated the impact of assay bias on measurement confidence and its relation to replication strategies. We outlined the underlying concepts of the block randomization scheme to potentially apply to other microtiter-based assays.