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Updated: May 28, 2026
Quantifying Antibody-Dependent Cellular Cytotoxicity in a Tumor Spheroid Model: Application for Drug Discovery
Published on: April 26, 2024
Agent-based modeling demonstrates how target-independent processes supplement killing by antibody-drug conjugates in
Melissa C Calopiz1, Jennifer J Linderman1,2, Greg M Thurber1,2,3
1Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.
Abstract:
Antibody-drug conjugates (ADCs) have had remarkable clinical success in recent years with multiple new approvals. However, for some ADCs, the response rates don't closely correlate with clinical target expression. One particular ADC targeting HER2, trastuzumab deruxtecan or T-DXd, is notable due to its success at expression levels ranging from high to low and ultralow. This raises the question of the relative contributions of target-independent mechanisms on ADC efficacy in the clinic, and several such mechanisms have been proposed. However, in vitro and preclinical data have different doses and exposures, making it challenging to quantitatively extrapolate preclinical data to the clinic. In this work, we use our computational hybrid agent-based model, SimADC, to simulate target-dependent and -independent mechanisms, scaling from mice to humans. We first demonstrate that CD8 + T cells can significantly contribute to tumor regression, especially when the ADC further activates the immune cells. Next, we test target-independent payload-driven mechanisms including: 1) Fc-mediated internalization of ADC by intratumoral macrophages and payload release to neighboring cancer cells, 2) free payload circulating in the blood and re-entering the tumor, and 3) extracellular linker cleavage and payload release due to an abundance of proteases in the tumor. We find that free payload in the blood and extracellular linker cleavage had low and moderate impacts, respectively, while macrophage uptake and payload release resulted in high levels of efficacy. This is due to the macrophages' ability to sustain free payload in the tumor. Moderate and high HER2 expression were more efficacious than target-independent mechanisms. Overall, our simulations demonstrate that moderate to high HER2 expression, immune activation, or macrophage uptake and payload release are sufficient for T-DXd tumor regression. Additionally, SimADC provides a robust framework for modeling both target-dependent and target-independent mechanisms for any ADC, providing the opportunity to engineer more effective therapeutic agents.
Insights
Antibody-drug conjugates (ADCs) show efficacy through target-dependent HER2 expression and target-independent mechanisms like macrophage uptake. Computational modeling helps understand these factors for improved ADC development.
Area of Science:
- Oncology
- Pharmacology
- Computational Biology
Background:
- Antibody-drug conjugates (ADCs) have achieved significant clinical success, but response rates sometimes lack correlation with target expression levels.
- Trastuzumab deruxtecan (T-DXd), an ADC targeting HER2, demonstrates efficacy across a wide range of HER2 expression, including low and ultralow levels.
- Preclinical data for ADCs present challenges in quantitative extrapolation to clinical settings due to differing doses and exposures.
Purpose of the Study:
- To investigate the contributions of target-independent mechanisms to ADC efficacy in clinical settings.
- To quantitatively model and compare target-dependent and target-independent mechanisms influencing ADC tumor regression.
- To utilize a computational hybrid agent-based model (SimADC) for simulating ADC mechanisms across species.
Main Methods:
- Development and application of SimADC, a computational hybrid agent-based model, to simulate ADC activity.
- Simulation of target-dependent mechanisms, including HER2 expression levels and immune cell activation (CD8+ T cells).
- Modeling of target-independent payload-driven mechanisms: Fc-mediated macrophage internalization, free payload circulation, and extracellular linker cleavage.
Main Results:
- CD8+ T cell activation significantly contributes to tumor regression, particularly when enhanced by the ADC.
- Macrophage uptake and payload release emerged as a highly efficacious target-independent mechanism, sustaining payload levels in the tumor.
- Free payload in circulation and extracellular linker cleavage showed low and moderate impacts, respectively; moderate to high HER2 expression remained more efficacious than target-independent mechanisms.
Conclusions:
- Moderate to high HER2 expression, immune activation, or macrophage-mediated payload release are sufficient for T-DXd-induced tumor regression.
- SimADC provides a robust framework for modeling both target-dependent and target-independent mechanisms for various ADCs.
- This modeling approach offers opportunities for engineering more effective therapeutic ADCs by dissecting mechanism contributions.
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