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FALCON: Closed-Loop Multi-Objective Optimization of Lipid Nanoparticles for Cell-Selective mRNA Delivery.

Wu Han Toh, Leonardo Cheng, Brandon Chang

Biorxiv : the Preprint Server for Biology

|June 29, 2026

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This summary is machine-generated.

We developed FALCON, a new AI-driven system that rapidly designs lipid nanoparticles (LNPs) for precise gene delivery. FALCON optimizes LNP composition for enhanced cell targeting and therapeutic efficacy in preclinical models.

Area of Science:

Biotechnology
Nanomedicine
Molecular Biology

Background:

Efficient and cell type-selective delivery of genetic materials is crucial for advancing gene and cell therapies.
Current lipid nanoparticle (LNP) optimization relies on inefficient, brute-force screening methods.
Developing targeted delivery systems requires overcoming challenges in payload delivery and LNP composition design.

Purpose of the Study:

To introduce FALCON (Framework for Active Learning-driven Compositional Optimization of Nanoparticles), an AI-powered pipeline for accelerating LNP design.
To demonstrate FALCON's ability to optimize LNP composition for enhanced gene delivery and cell selectivity.
To validate FALCON's performance in preclinical models for B cell and myeloid cell targeting.

Main Methods:

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Utilized a closed-loop pipeline combining iterative screening, surrogate modeling, and multi-objective optimization.
Employed active learning strategies to guide the compositional design of LNPs.
Performed in vivo validation experiments targeting splenic B cells and myeloid cells in preclinical models.

Main Results:

FALCON-optimized LNPs showed a 1.8-fold increase in splenic B cell transfection in vivo.
Achieved an 84-fold improvement in selective splenic B cell transfection over off-target liver cells.
Demonstrated enhanced myeloid cell-selective delivery and improved vaccine-induced immune responses (higher IgG2c titers, Th1 bias).

Conclusions:

FALCON significantly accelerates the design and optimization of LNP compositions for targeted gene delivery.
The FALCON framework enables data-driven optimization for improved therapeutic efficacy and reduced off-target effects.
FALCON represents a powerful tool for developing precision gene delivery systems for various therapeutic applications.