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A next generation mathematical model for the in vitro to clinical translation of T-cell engagers

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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.

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Acknowledgements

We would like to thank many colleagues at Applied BioMath who have contributed to the discussion of this work, including Victor Chang, Marc Presler, Saheli Sakar, Fereshteh Nazari. We would also like to thank Sarah A. Head and Max Nowak for performing the literature search for parameter values.

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  1. David Flowers and David Bassen are co-first author.

Authors and Affiliations

  1. Applied BioMath, Concord, MA, USA

    David Flowers, David Bassen, Georgi I. Kapitanov, Diana Marcantonio, John M. Burke, Joshua F. Apgar & Fei Hua

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  1. David Flowers
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  2. David Bassen
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  3. Georgi I. Kapitanov
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  4. Diana Marcantonio
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  7. Alison Betts
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  8. Fei Hua
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Contributions

All authors contributed to the design of the work and interpretation of results. DF and DB prepared all figures. DF, DB, GK, AΒ and FH wrote the main manuscript text. All authors reviewed the manuscript.

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Correspondence to Fei Hua.

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Flowers, D., Bassen, D., Kapitanov, G.I. et al. A next generation mathematical model for the in vitro to clinical translation of T-cell engagers. J Pharmacokinet Pharmacodyn 50, 215–227 (2023). https://doi.org/10.1007/s10928-023-09846-y

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