Helene Kenter 1,2, Farshid Alemdehy 1, Jeroen Elassaiss-Schaap 3, Esther van Leeuwen 1, Nasrin Afzal 1, Samira Anbari Meybodi 1, Wenyi Wang 1, Sieto Bosgra 1
1 Genmab (Utrecht, The Netherlands), 2 LACDR, Leiden University (, The Netherlands), 3 PD-Value (Utrecht, The Netherlands)
Introduction: In vitro trimer formation modeling is commonly used to predict the dose at which pharmacological activity is observed for bispecific T cell engagers (TCE). The prevailing assumption is that the number of trimers formed drives pharmacological activity; however, this quantity is typically not measured experimentally but instead inferred using relatively simple crosslinking models that describe interactions between the bispecific antibody and its two targets [1]. In in vitro cytotoxicity experiments, cells are not maintained in suspension and therefore tend to settle at the bottom of the well, substantially influencing cell–cell proximity and, consequently, trimer formation. This effect is not always explicitly accounted for in the interpretation of such data using mechanistic models. To more accurately describe trimer formation in vitro, cell settling may therefore need to be incorporated into the modeling framework. Here, we performed different model simulations to quantify the effect of cell settling on trimer formation modeling. The model results were validated with simultaneous binding experiments in vitro quantifying T cell-tumor cell conjugate by flow cytometry following coincubation with TCE. Validation was defined as concordance between predicted trimers per T cell and experimentally observed T cell–tumor cell conjugate formation across various concentrations and time points.
Objectives:
– Examine the effect of cells settling at the bottom of the well on trimer formation modeling
– Validate the model with results from the simultaneous binding experiments in vitro
Data: Simultaneous binding experiments were conducted with two B7H4 targeting TCE with low and high CD3 affinity. Three tumor cell lines were used with varying B7H4 expression, with E:T ratios of 1:2, 2:1 and 8:1. T cells and tumor cells were incubated with a range of TCE concentrations, starting at 100 µg/mL and followed by four-fold serial dilutions across 8 concentration points, for 30 min. The numbers of target cells and T cells under different settings were each plated per well in 100 µL in a U-bottom 96 Greiner well plate. After centrifugation, the supernatant was removed, and 50 µL of antibody dilution was added to each well, yielding a final working volume during incubation of 50 µL. After extensive washing T cell-tumor cell conjugate events were counted by flow cytometry.
Methods: The binding and trimer formation model considered the association and the dissociation of the antibody with CD3 on T cells and the tumor associated antigen (TAA) on tumor cells, cross-linking and complex internalization. Cells were considered to settle to the bottom from the initial suspension in the course of 10 min by an exponential decay function, consistent with visual inspection, affecting receptor and complex concentrations, but not unbound antibody concentrations. The effective volume was assumed to be 82% of the cellular volume, consistent with loose random sphere packing (packing fraction ≈0.55), corresponding to a void-to-cell volume ratio of ~0.82 [2]. Simulations were performed reflecting antibody properties including binding kinetics towards CD3 and in vitro experimental conditions including T cell and tumor cell counts, effector-to-target (E:T) ratios, antigen cell surface densities, antibody concentrations and incubation time. RxODE was used to develop a mechanistic trimer formation model. Simulations were performed for three bispecific antibodies:
– CD3xB7H4, high affinity for CD3
– CD3xB7H4, low affinity for CD3
– CD3x5T4, low affinity for CD3
Results: Simulations comparing cells in suspension to cells settling at the bottom suggested that cell settling increases the number of trimers per T-cell by 2-3 orders of magnitude depending on antibody properties and experimental conditions. The model accounting for the cell settling explained the cross-linking observed in the simultaneous binding experiments much more accurately.
Conclusion: These findings confirm that cell settling at the bottom effectively increases the concentration of receptors and antibody-receptor complexes, enhancing trimer formation, highlighting the importance of incorporating this process into the model to better describe the data. Simultaneous binding experiments, counting T cell-tumor cell conjugate events by flow cytometry after coincubation of T cells, tumor cells and TCE, can be used to reveal trimer formation in vitro and validate mechanistic trimer formation models. Combined, these results show that integrating the experimental findings into a model that incorporates cell settling may strengthen the in vitro to in vivo translational framework for TCE.
References:
[1] Wang, T., Wang, Y., & Sun, Q. (2025). Clinical Pharmacology Characterization of Bispecific T-cell engagers: A Summary Based on FDA Approvals. Clinical Pharmacology & Therapeutics. https://doi.org/10.1002/cpt.70020.
[2] Onoda, G. Y. & Liniger, E. G. (1990). Random loose packings of uniform spheres and the dilatancy onset. Physical Review Letters 64, 2727–2730.
Reference: PAGE 34 (2026) Abstr 12011 [www.page-meeting.org/?abstract=12011]
Poster: Drug/Disease Modelling - Absorption & PBPK