An Automated Sample Preparation Protocol to Determine the Encapsulation Efficiency of RNA-Loaded Lipid Nanoparticles Using Andrew+ Pipetting Robot

Importance of the Topic

Manual determination of lipid nanoparticle (LNP) mRNA encapsulation efficiency is labor-intensive and time-consuming, limiting throughput in pharmaceutical research, development, and quality control. Automating this assay accelerates mRNA vaccine and therapeutic development by delivering consistent, reproducible measurements of critical quality attributes.

Objectives and Study Overview

This work aimed to design, implement, and validate a fully automated RiboGreen fluorescence assay on the Andrew+ Pipetting Robot. The protocol was benchmarked against manual pipetting for throughput, precision, and flexibility, supporting analysis of up to 16 samples within 60 minutes.

Methodology and Instrumentation Used

• RiboGreen Assay: Quant-iT RiboGreen RNA assay performed with TE buffer and Triton X-100–based TX buffer, including five-point calibration and blank correction.
• Sample Preparation: In-house formulated LNPs composed of ionizable lipid, DSPC, cholesterol, and PEGylated lipid, loaded with proprietary mRNA stock and diluted to 417–625 ng/mL for quantitation.
• Automation Platform: Andrew+ Pipetting Robot controlled by OneLab Software, employing 10 µL and 300 µL pipettes, a Heater-Shaker Plate, tip insertion systems, reservoirs, and a 96-well microplate for both 12- and 16-sample dynamic workflows.

Main Results and Discussion

• Throughput Enhancement: Automated protocol compressed total assay time from 120 to 45 minutes (63% reduction) and expanded well-use from 83% to 100% by reconfiguring to a vertical 16-sample layout.
• Performance Metrics: Fresh LNP samples achieved 99.04% encapsulation efficiency (RSD 0.36); after 30 days at –80 °C, efficiency remained high at 98.37% (RSD 0.83), demonstrating stability and comparability to manual results.
• Protocol Innovations: Dynamic processing of 1–16 samples, multivolume dilution mode to adapt to varying concentrations, automated reagent volume calculations, and gentle mixing steps to minimize bubble formation during surfactant handling.

Benefits and Practical Applications

• High-throughput capacity for formulation development, R&D, and CMC laboratories.
• Improved reproducibility and reduced operator error in fluorescence-based RNA quantification.
• Optimized reagent consumption and cost efficiency via software-driven volume calculations.
• Scalable and flexible workflow accommodating variable sample numbers and concentrations without additional manual steps.

Future Trends and Potential Applications

• Implementation of reverse pipetting to further reduce bubble formation and enhance accuracy.
• Extension of dynamic protocols to broader analyte classes and expanded concentration ranges.
• Incorporation of mass spectrometry–based quantification with matrix-matched calibration for improved accuracy.
• Standardization of automated RNA-LNP assays across multi-site networks for consistent quality assessment.

Conclusion

The Andrew+-automated RiboGreen assay delivers manual-comparable encapsulation efficiency measurements with markedly increased throughput, reproducibility, and flexibility. This platform supports streamlined, high-throughput RNA-LNP formulation development and routine quality control, minimizing assay time and resource usage.

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