# Molecular characterization and modeling efficient antibody effector function

> **NIH AI R01** · DARTMOUTH COLLEGE · 2026 · $442,024

## Abstract

ABSTRACT
Antibody effector functions represent a nexus linking innate and adaptive arms of the immune system and also
have direct clinical implications for antibody therapeutics and antibody-mediated pathologies. However, the
potency of Ab-dependent effector responses depends on numerous antigen, antibody and effector cell
properties. Variable antigen expression levels, accessibility and context on different targets influence not only
Ab binding but also the ability of the effector cell to kill or engulf its target. Based on the extensive diversity of
natural and engineered antibody forms and formats, both B cells and immunologists can engineer antibodies
with different flexibility, affinity, and avidity to manipulate the effector response. The complexity of these
interactions makes in vivo experimental testing of all combinations impractical, but the significance of these
activities to antibody-based protection and pathology and the opportunity to design agents with a high
probability of success once the fundamental cellular presentation mechanisms are understood makes
quantitative analysis of this complex biological landscape of high significance. This proposal will elucidate our
basic understanding of the cellular mechanisms that can drive advancements in the practical development of
immune therapeutics and the parameters by which both B cells and effectors can drive variation in the
outcome of antibody recognition. Overall, this work seeks to distill quantitative relationships between antigen,
antibody, and effector biology to establish “rules” that enable the generation of antibody design criteria that
encapsulate key landmarks in the antibody effector function landscape and enable robust prediction of this
critical aspect of antibody activity.

## Key facts

- **NIH application ID:** 11248347
- **Project number:** 5R01AI186995-02
- **Recipient organization:** DARTMOUTH COLLEGE
- **Principal Investigator:** Margaret E Ackerman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AI
- **Fiscal year:** 2026
- **Award amount:** $442,024
- **Award type:** 5
- **Project period:** 2024-12-16T00:00:00 → 2029-11-30T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11248347

## Citation

> US National Institutes of Health, RePORTER application 11248347, Molecular characterization and modeling efficient antibody effector function (5R01AI186995-02). Retrieved via AI Analytics 2026-06-24 from https://api.ai-analytics.org/grant/nih/11248347. Licensed CC0.

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