Bayesian Estimation of the Active Concentration and Affinity Constants Using Surface Plasmon Resonance Technology

Maximizing the Accuracy of Equilibrium Dissociation Constants for Affinity Complexes: From Theory to Practical Recommendations

The equilibrium dissociation constant (Kd) is a major characteristic of affinity complexes and one of the most frequently determined physicochemical parameters. Despite its significance, the values of Kd obtained for the same complex under similar conditions often exhibit considerable discrepancies and sometimes vary by orders of magnitude. These inconsistencies highlight the susceptibility of Kd determination to large systematic errors, even when random errors are small. It is imperative to both minimize and quantitatively assess the systematic errors inherent in Kd determination. Traditionally, Kd values are determined through nonlinear regression of binding isotherms. This analysis utilizes three variables: concentrations of two reactants and a fraction R of unbound limiting reactant. The systematic errors in Kd arise directly from systematic errors in these variables. Therefore, to maximize the accuracy of Kd, this study thoroughly analyzes the sources of systematic errors within the three variables, including (i) non-additive signals to calculate R, (ii) mis-calibrated experimental instruments, (iii) inaccurate calibration parameters, (iv) insufficient incubation time, (v) unsaturated binding isotherm, (vi) impurities in the reactants, and (vii) solute adsorption onto surfaces. Through this analysis, we illustrate how each source contributes to inaccuracies in the determination of Kd and propose strategies to minimize these contributions. Additionally, we introduce a method for quantitatively assessing the confidence intervals of systematic errors in concentrations, a crucial step toward quantitatively evaluating the accuracy of Kd. While presenting original findings, this paper also reiterates the fundamentals of Kd determination, hence guiding researchers across all proficiency levels. By shedding light on the sources of systematic errors and offering strategies for their mitigation, our work will help researchers enhance the accuracy of Kd determination, thereby making binding studies more reliable and the conclusions drawn from such studies more robust.

Monitoring bioactive and total antibody concentrations for continuous process control by surface plasmon resonance spectroscopy

Monoclonal antibodies have become an increasingly important part of fundamental research and medical applications. To meet the high market demand for monoclonal antibodies in the biopharmaceutical sector, industrial manufacturing needs to be achieved by large scale, highly productive and consistent production processes. These are subject to international guidelines and have to be monitored intensely due to high safety standards for medical applications. Surface plasmon resonance spectroscopy - a fast, real-time, and label-free bio-sensing method - represents an interesting alternative to the quantification of monoclonal antibody concentrations by enzyme-linked immunosorbent assay during monoclonal antibody production. For the application of monitoring bioactive and total monoclonal antibody concentrations in cell culture samples, a surface plasmon resonance assay using a target-monoclonal antibody model system was developed. In order to ensure the subsequent detection of bioactive monoclonal antibody concentrations, suitable immobilization strategies of the target were identified. A significant decrease of the limit of detection was achieved by using an adapted affinity method compared to the commonly used amine coupling. Furthermore, the system showed limit of detection in the low ng/mL range similar to control quantifications by enzyme-linked immunosorbent assay. Moreover, the comparison of total to bioactive monoclonal antibody concentrations allows analysis of antibody production efficiency. The development of an alternative quantification system to monitor monoclonal antibody production was accomplished using surface plasmon resonance with the advantage of low analyte volume, shorter assay time, and biosensor reusability by target-layer regeneration. The established method provides the basis for the technical development of a surface plasmon resonance-based system for continuous process monitoring.