Navigating Lipid Nanostructure Design Space Through Continuous Microfluidic Automation

Area of Science:

• Nanotechnology and Materials Science
• Biomedical Engineering
• Chemical Engineering

Background:

• Lipid nanoparticles are versatile scaffolds for biomedical delivery, membrane engineering, and biophysical studies.
• Rational design of lipid nanoparticles is challenging due to the vast, high-dimensional parameter space (composition, size, morphology, etc.).
• Conventional optimization methods are slow and limited, necessitating high-throughput screening for efficient exploration.

Purpose of the Study:

• To introduce a high-throughput microfluidic platform for rapid screening of lipid nanoparticles.
• To enable precise, programmable control over lipid nanoparticle composition and morphology.
• To accelerate the discovery of optimal lipid formulations for various applications.

Main Methods:

• Development of an integrated microfluidic system for on-chip lipid stock metering and continuous particle self-assembly.
• Robotic collection of generated lipid nanoparticles into 96-well plates for automated screening.
• High-throughput generation of over 200 unique lipid nanoparticle formulations per hour.

Main Results:

• The platform demonstrated a several-orders-of-magnitude increase in throughput compared to conventional methods.
• Systematic mapping of lipid nanoparticle biophysical space at unprecedented resolution was achieved.
• Validated compositional trends influencing transfection efficiency and identified optimal non-lamellar formulations.

Conclusions:

• The microfluidic platform offers scalable synthesis and automated screening for lipid nanoparticle discovery.
• This approach facilitates data-driven and AI-integrated discovery of self-assembled nanomaterials.
• The platform is expected to accelerate advancements in biomedical delivery and materials science.