Single Particle Analyzer for high-throughput and high-content characterization of Nanoparticle-based RNA Therapy

This project develops a high-throughput single-particle analyzer using fluorescence and microfluidics to characterize RNA-loaded lipid nanoparticles, enabling precise analysis of RNA payload and empty particles to improve RNA drug development and safety.
Categories
Proteins/ Antibodies

Industry Need

Current lipid nanoparticle (LNP) methods primarily rely on bulk measurements, failing to provide critical insights into individual particles. Two emerging quality attributes, the fraction of empty particles and RNA payload quantity and its distribution in LNPs, remain challenging to quantify with existing technologies, leading to challenges in process development, quality control, and regulatory compliance.

Approach

Our team has developed a novel single particle analyzer based on Cylindrical Illumination Confocal Spectroscopy (CICS) technology that achieves single-molecule sensitivity, enabling the accurate quantification of the unaddressed properties at single-particle resolution. This analytical platform has demonstrated the potential to accelerate product development, improve manufacturing consistency, and enhance regulatory compliance and address key challenges in RNA-LNP research and development, and manufacturing settings.

Impacts

Technical innovation with better analytical methods for product and process understanding to facilitate the improvement of product quality and manufacturing consistency

Economic and market impact by advancing analytical instruments for cell and gene therapy specifically for LNP characterization for competitive pricing for instruments and consumables

Outputs/Deliverables

  • Microfluidic system development and validation
  • Optical platform integration and performance optimization
  • Analytical method development for manufacturing quality control
  • LNP property structure-function correlation and quality system implementation
  • Biophysical database with biological attribute correlation and predictive models for defined quality metrics

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Project Lead

Johns Hopkins University

Johns Hopkins University

Participating Organizations

CICS Analytics Corporation

CICS Analytics Corporation

Federal Stakeholder:  National Institute of Standards and Technology

Federal Stakeholder: National Institute of Standards and Technology

Sartorius Stedim

Sartorius Stedim