(M-071) Mechanistic mathematical model of emicizumab

Dougald Monroe, PhD – Professor, UNC Chapel Hill; Suzanne Sindi, PhD – Professor, Applied Mathematics, University of California, Merced; Karin Leiderman, PhD – Associate Professor, Mathematics/Biochemistry and Biophysics/Computational Medicine/BRC, UNC Chapel Hill

A mechanistic mathematical model of emicizumab

Emicizumab is a bispecific antibody that brings together activated Factor IX and Factor X, replacing the missing Factor VIII in hemophilia A patients. Although widely used as an FDA approved therapeutic, the lipid-surface dependence of emicizumab is not well understood. A key mechanistic difference between emicizumab and FVIII is that emicizumab does not bind directly to the lipid surface, while FVIII does. In biochemical assays, emicizumab has been shown to inhibit FX activation by TF:VIIa – a lipid-surface dependent reaction.

Previously, we developed and validated a mathematical model that uniquely captured the lipid-surface dependence of TF:VIIa activation of FX. In this work, we expand the model to include emicizumab and consider all plausible biochemical mechanisms. As emicizumab does not bind TF:VIIa, this tests interaction of emicizumab and FX alone, a one arm interaction. We calibrate the model with experimental data under several conditions. We then take knowledge from the one arm interaction and apply it to a model for FIXa activation of FX, a two arm interaction.

Results agree with experiments and capture the inhibitory effect of high concentrations of emicizumab on FX activation by TF:VIIa. The results imply that emicizumab inhibits the binding of FX to the lipid-surface. Through this assumption, the model is able to capture FIXa activation of FX under several experimental conditions.

The results have implications for the design of second generation bifunctional antibodies. Future directions include further exploration of the off-target effects of emicizumab, specifically the effect of emicizumab on the lipid-binding of FIXa.

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