# Mapping the effector response space of antibody combinations

> **NIH NIH U01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $314,929

## Abstract

Antibodies are crucial, central regulators of the immune response. They are particularly versatile
therapeutic agents due to their ability to both bind to a target with high affinity and direct the
immune system. Indeed, antibodies comprise a broad range of approved therapies across
disease indications, many of which are known to rely in large part on effector cell (immune)
response. Antibodies of the IgG isotype interact with FcγRs on effector cells and elicit effector
function through multiple cell types (e.g., macrophages, monocytes) and through multiple
processes, including phagocytosis and killing of diseased cells. The many possible design
parameters—constant region composition, FcγRs, cell populations, and antigen binding in
combination—have made precisely understanding, measuring, and manipulating effector
function an elusive goal. Our proposed work is centered around the hypothesis that two IgGs
can elicit distinct responses when present in combination from what would be suggested by the
response to either on its own. Using a computational model of antibody-FcγR interaction, we will
identify predicted cases of this emergent behavior. These combinations will be tested for their
binding and effector response in vitro and then in two models of antibody-targeted cell killing.
Finally, we will use the computational model of effector regulation to map how human and
mouse IgGs are related according to their effector response. In total, these efforts will provide
critical information for designing more effective antibodies with the goal of targeted cell killing
and provide a clearer view of how existing therapeutic antibodies function.

## Key facts

- **NIH application ID:** 10529268
- **Project number:** 5U01AI148119-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Aaron Samuel Meyer
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $314,929
- **Award type:** 5
- **Project period:** 2019-12-18 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10529268

## Citation

> US National Institutes of Health, RePORTER application 10529268, Mapping the effector response space of antibody combinations (5U01AI148119-04). Retrieved via AI Analytics 2026-06-14 from https://api.ai-analytics.org/grant/nih/10529268. Licensed CC0.

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