Affinity defines the attractive force between antibody (Ab) and antigen (Ag) and represents a key feature of strong immune response. The study of affinity maturation of antibodies following vaccination or infection is a growing field of interest for vaccine discovery. Nevertheless the affinity characterization of human sera is still precluded due to the complexity of polyclonal antibodies, being the sera a mixture of different Abs clones (mAb) of unknown concentration and affinity.
We developed a high-throughput methodology, based on mathematical modeling of the Ag-Ab capture profile in the Gyrolab^® miniaturized immunoassay platform, to define an affinity score and to de-convolute polyclonal sera in monoclonal-like sub-populations. The mAb-Ag profile in a hydro-dynamical system can be modeled as a Lévy process and it is described by an approximated Landau distribution. The estimation of optimal parameters from the de-convolution of non-Gaussian mixtures allows to measure affinity and quantity in each Ab sub-population.
This approach has been validated on four artificial mixtures, each composed by two fully characterized monoclonal antibodies with different affinity and run at different concentrations.  Nevertheless, capture profiles from certain mixtures of mAbs elude our analysis.
The next step is to extend the approach by investigating the microscopic dynamics in the Gyrolab^® experimental set-up and by developing a model to explain all observed capture profiles in polyclonal sera.
This method can be successfully used in human sera from subject immunized with different vaccines to study the maturation of Ab affinity, also in relationship with other serological measurements, including cellular responses and correlates of protection, and therefore to select the best vaccine formulation.