Category: Biologics Discovery
Immunoassay technique is one of the most efficient and reliable tools for in vitro diagnostics. It mainly relies on the specific recognition between an antigen and an antibody. When designing immunoassays, sensitivity, specificity and time-to-result can be optimized with the choice of a dedicated ligand to specifically capture the analyte of interest as well as the solid support (material and form) or the flow-rate of the liquid which contains the molecules to be detected,... Until now, these choices have usually been made empirically which is very time and money consuming. Using a predictive model to at least focus the empirical tests on a limited set of critical parameters could improve the efficiency of immunoassays design. A kinetic model of antibody/antigen interactions could be useful to simplify and speed-up the identification of the best immunoassays conditions or to improve the existing immunoassays. More and more, the characterization of antigen/antibody interactions kinetics plays a major role for the selection of the best molecules for immunoassays.
The global aim of this work is to improve the performance level of immunoassay diagnostic tests in a rational and effective way (compared to the fastidious empirical approaches used today) by better understanding and predicting the complex molecular interactions that occur in the different steps of a diagnostic immunoassay. To do so, it is proposed to build a predictive model of antigen/antibody interaction processes. This model will then serve i) to refine our knowledge of the mechanisms involved in the capture of antigens by antibodies immobilized on surfaces and ii) to identify the critical parameters of the diagnostic systems.
An experimental tool based on affinity chromatography has been built to study physical and chemical phenomena involved in molecular recognition processes between antigens and antibodies. Antibodies are immobilized on a particle bed in a chromatography column while antigens are injected at the inlet of the column. Hydrodynamics has been characterized through Residence Time Distribution (RTD) measurements with sodium chloride as a tracer. In parallel, a kinetic model of the experimental system that takes into account mass transfer processes has been developed and implemented in Matlab. Parameters of the model have been estimated by minimizing the difference between experimental and simulated data. The next step is to adapt the model to a diagnostic system.
This work is part of a collaboration between the bioMérieux company and the LAGEP (Chemical Engineering and Process Control Laboratory). It is a unique opportunity to make the link between the deductive approaches of physics-based modeling and the empirical knowledge of biology/biochemistry settings, with a clear potential impact in the field of diagnostics and, ultimately, public health.
Maelenn Robin– PhD student, Univ Lyon, Université Claude Bernard Lyon 1, CNRS, LAGEP UMR 5007 and bioMerieux SA, Villeurbanne, France
Univ Lyon, Université Claude Bernard Lyon 1, CNRS, LAGEP UMR 5007 and bioMerieux SA
Maelenn Robin is graduated from a French engineering school Grenoble INP – Phelma with a major in systems and microsystems for physics and biotechnologies. She is now a PhD student in LAGEP (Chemical Engineering and Process Control Laboratory) working on modeling and simulations of complex biological processes involved in in vitro diagnostic systems. Her project is in collaboration with the French company bioMerieux SA.