BiSim Tool: a binding simulation tool to aid and simplify ligand-binding assay design and development.

Ligand-binding assays (LBAs) rely on the reversible, noncovalent binding between the analyte of interest and the assay reagents, and understanding their dynamic equilibrium is key to building robust LBA methods. Although the dynamic interplay of free and bound fractions can be calculated using mathematical models, these are not routinely applied. This approach is costly in terms of both assay development time and reagents, and can result in an under-exploration of the possible parameter combinations. Therefore, we have created a user-friendly simulation tool to facilitate LBA development (the BiSim Tool). We describe the models driving the mathematical simulations and the main features of our software solution by means of case studies, illustrating the tool's value in drug development. To support drug development for all patients worldwide, the BiSim Tool is now available as an open-source code project and as a free web-based tool at https://proteinbindingsimulation.shinyapps.io/BiSim-ProteinBindingSimulation [1].

Use of a mouse model to identify a blood biomarker for IFNγ activity in pediatric secondary hemophagocytic lymphohistiocytosis.

Life-threatening cytokine release syndromes include primary (p) and secondary (s) forms of hemophagocytic lymphohistiocytosis (HLH). Below detection in healthy individuals, interferon γ (IFNγ) levels are elevated to measurable concentrations in these afflictions suggesting a central role for this cytokine in the development and maintenance of HLH. Mimicking an infection-driven model of sHLH in mice, we observed that the tissue-derived levels of IFNγ are actually 500- to 2000-fold higher than those measured in the blood. To identify a blood biomarker, we postulated that the IFNγ gene products, CXCL9 and CXCL10 would correlate with disease parameters in the mouse model. To translate this into a disease relevant biomarker, we investigated whether CXCL9 and CXCL10 levels correlated with disease activity in pediatric sHLH patients. Our data demonstrate that disease control in mice correlates with neutralization of IFNγ activity in tissues and that the 2 chemokines serve as serum biomarkers to reflect disease status. Importantly, CXCL9 and CXCL10 levels in pediatric sHLH were shown to correlate with key disease parameters and severity in these patients. Thus, the translatability of the IFNγ-biomarker correlates from mouse to human, advocating the use of serum CXCL9 or CXCL10 as a means to monitor total IFNγ activity in patients with sHLH.

Evaluation of Multiple Immunoassay Technology Platforms to Select the Anti-Drug Antibody Assay Exhibiting the Most Appropriate Drug and Target Tolerance.

The aim of this study was, at the assay development stage and thus with an appropriate degree of rigor, to select the most appropriate technology platform and sample pretreatment procedure for a clinical ADA assay. Thus, ELISA, MSD, Gyrolab, and AlphaLISA immunoassay platforms were evaluated in association with target depletion and acid dissociation sample pretreatment steps. An acid dissociation step successfully improved the drug tolerance for all 4 technology platforms and the required drug tolerance was achieved with the Gyrolab and MSD platforms. The target tolerance was shown to be better for the ELISA format, where an acid dissociation treatment step alone was sufficient to achieve the desired target tolerance. However, inclusion of a target depletion step in conjunction with the acid treatment raised the target tolerance to the desired level for all of the technologies. A higher sensitivity was observed for the MSD and Gyrolab assays and the ELISA, MSD, and Gyrolab all displayed acceptable interdonor variability. This study highlights the usefulness of evaluating the performance of different assay platforms at an early stage in the assay development process to aid in the selection of the best fit-for-purpose technology platform and sample pretreatment steps.