Effect of molecular size on interstitial pharmacokinetics and tissue catabolism of antibodies

Hanine Rafidi1, Sharmila Rajan1, Konnie Urban2

  • 1Departments of Preclinical and Translational Pharmacokinetics and Pharmacodynamics, Research and Early Development, Genentech, Inc, South San Francisco, CA, USA.

Mabs
|July 22, 2022
PubMed

Advances in antibody engineering have enabled the construction of novel molecular formats in diverse shapes and sizes, providing new opportunities for biologic therapies and expanding the need to understand how various structural aspects affect their distribution properties. To assess the effect of antibody size on systemic pharmacokinetics (PK) and tissue distribution with or without neonatal Fc receptor (FcRn) binding, we evaluated a series of non-mouse-binding anti-glycoprotein D monoclonal antibody formats, including IgG [~150 kDa], one-armed IgG [~100 kDa], IgG-HAHQ (attenuated FcRn binding) [~150 kDa], F(ab')2 [~100 kDa], and F(ab) [~50 kDa]. Tissue-specific concentration-time profiles were corrected for blood content based on vascular volumes and normalized based on interstitial volumes to allow estimation of interstitial concentrations and interstitial:serum concentration ratios. Blood correction demonstrated that the contribution of circulating antibody on total uptake was greatest at early time points and for highly vascularized tissues. Tissue interstitial PK largely mirrored serum exposure profiles. Similar interstitial:serum ratios were obtained for the two FcRn-binding molecules, IgG and one-armed IgG, which reached pseudo-steady-state kinetics in most tissues. For non-FcRn-binding molecules, interstitial:serum ratios changed over time, suggesting that these molecules did not reach steady-state kinetics during the study. Furthermore, concentration-time profiles of both intact and catabolized molecule were measured by a dual tracer approach, enabling quantification of tissue catabolism and demonstrating that catabolism levels were highest for IgG-HAHQ. Overall, these data sets provide insight into factors affecting preclinical distribution and may be useful in estimating interstitial concentrations and/or catabolism in human tissues.

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