Development of mPBPK model to support translation decision-making for novel bispecific therapeutics
Anuraag Saini, Seshasai Pallikonda Chakravarthy, Goutam Nair, Kartikeya Raman, Bhairav Paleja, Mrittika Roy, Rukmini Kumar
Vantage Research Inc, USA
Background
Bispecific therapeutics have emerged as a promising class due to their ability to target two distinct antigens simultaneously, resulting in unique properties such as redirecting immune cells to attack cancer cells. Bispecific T cell engagers (BiTEs) engage T cells to kill cancer cells, while NK cell engagers (NKE) activate natural killer cells to target tumor cells. Further, such therapeutics can be engineered to have Half-life extended (HLE) by manipulating the Fc domain or adding chemical linkers to the engager protein. The pharmacokinetics (PK) of bispecifics can thus be complex, with nonlinear clearance and target-mediated disposition. Mechanistic [1] and semi-empirical models [2] have been proposed to describe efficacy and safety specifically for BiTEs. Here, we propose an mPBPK model which is parameterized for various complex bi-specific modalities to support decision-making in translational PK and predict clinical PK for varying dosing regimens.
Objectives
The objective of this study is to develop a mPBPK model that is designed to support translational decision-making in the development of bispecific therapeutics such as T cell engagers and NK cell engagers, including BiTEs, HLE BiTEs, and NKEs. This model aims to provide accurate predictions of dosing regimens of these agents in humans, using available preclinical and early clinical PK data.
Methods
This mPBPK model was developed by extending an established mPBPK model as a starting point [3]. Further, the model from [4]was expanded to include the receptor dynamics in addition to the cell dynamics module. Our extended model comprises 3 aspects: (a) Cell dynamics of cell type relevant to the bi-specific therapeutics (one of more of T cells, NK cells, Neutrophils and Bcells) (b) Relevant Receptor dynamics (one of CD3 for T cells, CD16 for NK cells neutrophils) and (c) PK. These modules are designed to account for the unique PK properties of bispecifics, including nonlinear clearance due to target-mediated disposition via various effector cells. Specifically, to capture HLE BiTE, an endosomal compartment captures the dynamics of endosomal recycling and lysosomal degradation of the molecule.
Results
The developed mPBPK model was calibrated to reproduce preclinical and clinical PK using each modality - BiTE, HLE BiTE and NKE
- BiTE: Multiple dose plasma PK data in Cynomolgus monkeys for mosunetuzumab [5] was used for calibration, followed by translation to humans for capturing single dose human PK data[4]. The cell types involved are T Cells along with CD3 receptor dynamics to account for the specific clearance of the drug from plasma.
- HLE BiTE: HLE BiTE has a higher half-life in plasma relative to non-HLE mAbs/BiTEs due to recycling of a significant fraction of the drug. The model was calibrated to a single dose plasma PK data of AMG160 in cynomolgus monkeys [6]. The model was able to capture the difference in PK for non HLE and HLE BiTE.
- NKE: The model was calibrated to capture antiCD16xCD30 NKE plasma PK in humans [7]. Apart from NK cells, other cell types which express CD16 are lumped together under neutrophils. It is important to capture the dynamics of these cells expressing CD16 as the specific clearance of the NKE through its binding to CD16 on these cell types significantly affects PK.
Conclusion
Our mPBPK model provides the ability to support translational decision-making for complex modalities, including bispecific T cell engagers and NK cell engagers. The model can be extended to optimize dose and dosing regimens, inform clinical trial designs, and aid in the selection of lead candidates for further development.
References:
[1] Susilo ME, Li CC, Gadkar K, Hernandez G, Huw LY, Jin JY, Yin S, Wei MC, Ramanujan S, Hosseini I. Systems‐based Digital Twins to Help Characterize Clinical Dose‐Response and Propose Predictive Biomarkers in a Phase I Study of Bispecific Antibody, Mosunetuzumab, in NHL. Clinical and Translational Science. 2023 Mar 13.
[2] Betts A, van der Graaf PH. Mechanistic quantitative pharmacology strategies for the early clinical development of bispecific antibodies in oncology. Clinical Pharmacology & Therapeutics. 2020 Sep;108(3):528-41.
[3] Cao Y, Balthasar JP, Jusko WJ. Second-generation minimal physiologically based pharmacokinetic model for monoclonal antibodies. J Pharmacokinet Pharmacodyn. 2013 Oct;40(5):597-607.
[4] Hosseini I, Gadkar K, Stefanich E, Li CC, Sun LL, Chu YW, Ramanujan S. Mitigating the risk of cytokine release syndrome in a Phase I trial of CD20/CD3 bispecific antibody mosunetuzumab in NHL: impact of translational system modeling. NPJ systems biology and applications. 2020 Aug 28;6(1):28.
[5] Ferl GZ, Reyes A, Sun LL, Cheu M, Oldendorp A, Ramanujan S, Stefanich EG. A preclinical population pharmacokinetic model for anti‐CD20/CD3 T‐cell‐dependent bispecific antibodies. Clinical and Translational Science. 2018 May;11(3):296-304.
[6] Deegen P, Thomas O, Nolan-Stevaux O, Li S, Wahl J, Bogner P, Aeffner F, Friedrich M, Liao MZ, Matthes K, Rau D. The PSMA-targeting Half-life Extended BiTE Therapy AMG 160 has Potent Antitumor Activity in Preclinical Models of Metastatic Castration-resistant Prostate CancerPreclinical Evaluation of AMG 160 in mCRPC Models. Clinical Cancer Research. 2021 May 15;27(10):2928-37.
[7] Rothe A, Sasse S, Topp MS, Eichenauer DA, Hummel H, Reiners KS, Dietlein M, Kuhnert G, Kessler J, Buerkle C, Ravic M. A phase 1 study of the bispecific anti-CD30/CD16A antibody construct AFM13 in patients with relapsed or refractory Hodgkin lymphoma. Blood, The Journal of the American Society of Hematology. 2015 Jun 25;125(26):4024-31.
