A Quantitative Approach to Guiding Target Antigen Selection and Antibody Optimization in Recycling Antibody Discovery.

Recycling antibodies can enhance therapeutic efficacy by enabling efficient antigen removal through pH-dependent binding mechanisms enabling antibody recycling, but the optimal targets for this strategy remain unclear. This work employs a mathematical modeling approach using a minimal PBPK model, along with global and local sensitivity analyses, to explore how target turnover rates influence the suitability of recycling antibodies. We applied this approach to a scenario featuring a soluble antigen with high baseline levels (1000 nM) that necessitates treatment with an antibody with a high intravenous dosing regimen. Our findings indicate that the recycling strategy is most effective for target antigens expressed at high levels, and particularly for those with half-lives of 10 to 30 h. In contrast, for antigens expressed at sufficiently low levels, where the antibody can be present in significant excess, further optimization of conventional antibodies to achieve higher antigen-binding affinity at neutral pH can be beneficial. While optimizing the off-rate at acidic pH is often the primary focus in the engineering of recycling antibodies, our analysis indicates that the on-rate at pH 6 is also an important parameter, albeit to a lesser extent. Therefore, the equilibrium dissociation constant (K