(T-073) Bispecific T-cell engagers and cytokine release syndrome: Modeling molecule, indication and patient-specific aspects

Luis David Jimenez Franco, PhD – Principal Scientist & Lead Radioharmaceuticals Platform, ESQLabs; Venetia Karamitsou, PhD – Scientist, ESQlabs GmbH; Wilbert De Witte, PhD – Principal Scientist & Lead Large Molecule Platform, ESQLabs; Carla Troisi, PhD – Scientist, ESQLabs; Stephan Schaller, PhD – CEO and Lead Scientist, ESQlabs

Harnessing the power of T-cells to enhance anti-tumor activities has become a promising strategy in clinical management of cancer. Bispecific antibodies (BsAbs), which recruit T cells to tumor sites (also termed T-cell engagers, TCEs or BiTEs), have facilitated the development of tumor immunotherapy and have led to successful approval for non-solid oncology indications. Especially immune related adverse events require a conservative dosing strategy in early clinical development, that can profit from comprehensive mathematical modeling. For this purpose, mechanistic (quantitative systems pharmacology, QSP) models are coming of age, that typically quantify complex formation of the antibody, linking receptors with various levels of detail as well as downstream T-cell activation kinetics, cytokine release and tumor effects.

The main objective of this work is to elaborate on the use of mechanistic models for deciphering the expected variability of cytokine release by breaking it down into three contributions: 1. molecular (affinities, mutations) and regimen design translating into the extent of functional T-cell -> Tumor cell crosslinking 2. differences in indication, notably solid vs. nonsolid indications 3. between-patient variability in pharmacokinetics, T-cell response and cytokine release.
As the methods for this work, we employ the open-source large molecule physiologically-based pharmacokinetics (PBPK) model [1] offered by PK-Sim® and expand it with a dedicated with T-cell redistribution and crosslinking in MoBi® (both software packages are part of the open systems pharmacology suite [2]) and as evaluated on the example of HER2xCD3 [3]. We additionally implement both a structured tumor compartment versus systemic circulation of tumor cells. Additionally, we set up an explicit IL-6-centric signaling model (integrating immunological knowledge from other modalities and indications) to integrate between-patient immunological variability.

As the main results we detail the model building workflow, explain the model structure and conduct example simulations for selected approved T-cell engagers including an assessment of the model’s sensitivity to factors 1-3.

In conclusion, we expanded a widely used open-source large molecule PBPK model with custom modules to become a QSP tool that explores the therapeutic window of T-cell engagers that can be used to support early clinical development of these modalities.

Citations: [1] Niederalt C, Kuepfer L, Solodenko J, Eissing T, Siegmund HU, Block M, Willmann S, Lippert J. A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim. J Pharmacokinet Pharmacodyn. 2018 Apr;45(2):235-257. doi: 10.1007/s10928-017-9559-4. Epub 2017 Dec 12. PMID: 29234936; PMCID: PMC5845054.

[2] Lippert J, Burghaus R, Edginton A, Frechen S, Karlsson M, Kovar A, Lehr T, Milligan P, Nock V, Ramusovic S, Riggs M, Schaller S, Schlender J, Schmidt S, Sevestre M, Sjögren E, Solodenko J, Staab A, Teutonico D. Open Systems Pharmacology Community-An Open Access, Open Source, Open Science Approach to Modeling and Simulation in Pharmaceutical Sciences. CPT Pharmacometrics Syst Pharmacol. 2019 Dec;8(12):878-882. doi: 10.1002/psp4.12473. Epub 2019 Nov 12. PMID: 31671256; PMCID: PMC6930856.

[3] Susilo M, Li C, Chen C, Gadkar K, Mandikian D, Boswel A, Jimenez L, Schaller S, "A PB-QSP platform model for T-cell-dependent bispecific antibodies", PAGE 30 (2022) Abstr 10024 [www.page-meeting.org/?abstract=10024]