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_D) at pH 6 can be used as a composite parameter for effective design of recycling antibodies. For the soluble antigen embodied in the scenario described in this work, a pool of randomly selected antibodies, engineered to undergo recycling, reach half of their maximum antigen reduction capacity at a mean pH 6 K_D of 520 nM and 180 nM for targets with half-lives of 10 and 30 h, respectively.