Feasibility of Singlet Analysis for Ligand Binding Assays: a Retrospective Examination of Data Generated Using the Gyrolab Platform.

There are many sources of analytical variability in ligand binding assays (LBA). One strategy to reduce variability has been duplicate analyses. With recent advances in LBA technologies, it is conceivable that singlet analysis is possible. We retrospectively evaluated singlet analysis using Gyrolab data. Relative precision of duplicates compared to singlets was evaluated using 60 datasets from toxicokinetic (TK) or pharmacokinetic (PK) studies which contained over 23,000 replicate pairs composed of standards, quality control (QC), and animal samples measured with 23 different bioanalytical assays. The comparison was first done with standard curve and QCs followed by PK parameters (i.e., Cmax and AUC). Statistical analyses were performed on combined duplicate versus singlets using a concordance correlation coefficient (CCC), a measurement used to assess agreement. Variance component analyses were conducted on PK estimates to assess the relative analytical and biological variability. Overall, 97.5% of replicate pairs had a %CV of <11% and 50% of the results had a %CV of ≤1.38%. There was no observable bias in concentration comparing the first replicate with the second (CCC of 0.99746 and accuracy value of 1). The comparison of AUC and Cmax showed no observable difference between singlet and duplicate (CCC for AUC and Cmax >0.99999). Analysis of variance indicated an AUC inter-subject variability 35.3-fold greater than replicate variability and 8.5-fold greater for Cmax. Running replicates from the same sample will not significantly reduce variation or change PK parameters. These analyses indicated the majority of variance was inter-subject and supported the use of a singlet strategy.

Automate it: ligand-binding assay productivity in a discovery bioanalytical setting.

In multiple industries, including the biopharmaceutical industry, automation is synonymous with increased productivity. Environments with high-throughput needs commonly employ automation for efficiency. However, in a discovery bioanalytical ligand-binding assay laboratory setting where the focus is not necessarily on sample analysis throughput, but instead on assay development and characterization, is automation applicable? Can automation enhance productivity when tasks are more customized than routine? In this Perspective we review the different categories of automation with ligand-binding assays with these questions in mind. In considering whether automation technology has progressed far enough to result in a positive return in investment in the discovery setting, the resource investment required to operate in this space was contrasted with the gain in productivity. In our opinion, technology advancements in automated technology platforms, and especially personal automation, have allowed these categories to strike the right balance for investment in the discovery laboratory setting.