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Updated: Aug 10, 2025
Non-Viral Engineering of Primary Human T Cells via Homology-Mediated End-Joining Targeted Integration of Large DNA Templates
Published on: May 9, 2025
A next generation mathematical model for the in vitro to clinical translation of T-cell engagers
David Flowers1, David Bassen1, Georgi I Kapitanov1
1Applied BioMath, Concord, MA, USA.
Abstract:
T-cell engager (TCE) molecules activate the immune system and direct it to kill tumor cells. The key mechanism of action of TCEs is to crosslink CD3 on T cells and tumor associated antigens (TAAs) on tumor cells. The formation of this trimolecular complex (i.e. trimer) mimics the immune synapse, leading to therapeutic-dependent T-cell activation and killing of tumor cells. Computational models supporting TCE development must predict trimer formation accurately. Here, we present a next-generation two-step binding mathematical model for TCEs to describe trimer formation. Specifically, we propose to model the second binding step with trans-avidity and as a two-dimensional (2D) process where the reactants are modeled as the cell-surface density. Compared to the 3D binding model where the reactants are described in terms of concentration, the 2D model predicts less sensitivity of trimer formation to varying cell densities, which better matches changes in EC50 from in vitro cytotoxicity assay data with varying E:T ratios. In addition, when translating in vitro cytotoxicity data to predict in vivo active clinical dose for blinatumomab, the choice of model leads to a notable difference in dose prediction. The dose predicted by the 2D model aligns better with the approved clinical dose and the prediction is robust under variations in the in vitro to in vivo translation assumptions. In conclusion, the 2D model with trans-avidity to describe trimer formation is an improved approach for TCEs and is likely to produce more accurate predictions to support TCE development.
Insights
A new 2D mathematical model accurately predicts T-cell engager (TCE) trimer formation. This model improves predictions of in vivo active clinical dose for TCEs, aiding in their development.
Area of Science:
- Immunology
- Computational Biology
- Pharmacology
Background:
- T-cell engagers (TCEs) activate T cells to kill tumor cells by crosslinking CD3 on T cells and tumor-associated antigens (TAAs) on tumor cells.
- Accurate computational models are crucial for predicting the trimolecular complex (trimer) formation essential for TCE efficacy.
Purpose of the Study:
- To present a next-generation two-step binding mathematical model for TCEs that accurately describes trimer formation.
- To model the second binding step using trans-avidity as a two-dimensional (2D) process based on cell-surface density.
Main Methods:
- Developed a 2D mathematical model for TCE trimer formation, considering trans-avidity and cell-surface density.
- Compared the 2D model with traditional 3D binding models (concentration-based).
- Validated the model using in vitro cytotoxicity assay data and predicted in vivo active clinical dose for blinatumomab.
Main Results:
- The 2D model shows less sensitivity to varying cell densities compared to the 3D model, aligning better with in vitro EC50 data across different effector-to-target (E:T) ratios.
- The 2D model's prediction for blinatumomab's in vivo active clinical dose closely matched the approved dose.
- The dose prediction using the 2D model remained robust despite variations in in vitro to in vivo translation assumptions.
Conclusions:
- The 2D model incorporating trans-avidity offers an improved approach for predicting TCE trimer formation.
- This enhanced modeling strategy is likely to yield more accurate predictions, significantly supporting the development of novel TCE therapeutics.
