Scaling up LNP formulation using a Reynolds number-based methodology

Scaling up LNP formulation using a Reynolds number-based methodology — Technical summary

Significance of the topic:

The manufacture of lipid nanoparticles (LNPs) underpins modern mRNA therapeutics and advanced drug delivery. Reliable scale-up from laboratory to production scales is essential to preserve critical quality attributes (CQAs) such as particle size, polydispersity index (PDI), encapsulation efficiency and API integrity. Because LNP self-assembly occurs on timescales comparable to mixing, hydrodynamic control during formulation is a decisive factor for reproducible product quality.

Objectives and study overview:

The study demonstrates a dimensionless, Reynolds-number-driven strategy to transfer LNP production from an R&D-scale Impinging Jets Mixer (IJM NanoScaler) to a production-scale Benchtop NanoProducer. The aim was to identify a critical Reynolds number above which particle size and PDI stabilize and to use that hydrodynamic condition to preserve CQAs while increasing throughput during scale-up.

Methodology and experimental approach:

- Formulation principle: rapid mixing of an ethanol lipid phase with an aqueous citrate buffer (FRR 1:3) to trigger solvent-exchange-driven lipid self-assembly. Lipid composition (example used: ALC-0315, PhytoChol, DSPC, ALC-0159) and buffer pH were controlled.
- Hydrodynamic framework: Reynolds number (Re) used to characterize flow regime and mixing intensity; Damköhler number (Da) considered conceptually to indicate mixing-controlled assembly (Da >> 1).
- Experimental design: systematic variation of total flow rate (TFR) and flow rate ratio (FRR) on the IJM NanoScaler across multiple IJM sizes to map particle size and PDI as functions of Re. Selected Re conditions were then reproduced on the Benchtop NanoProducer to evaluate scale-up fidelity. DLS (DynaPro ZetaStar) was used for immediate post-formulation particle sizing.

Used instrumentation:

• Impingement Jets Mixers: KNAUER IJM NanoScaler (R&D scale) and IJM Benchtop NanoProducer (production/benchtop scale).
• Pumping and flow hardware: multi-pump configurations; example configurations included 3 pumps (50 ml) on NanoScaler and 2×250 ml + 1×500 ml on Benchtop NanoProducer, with appropriate IJM cartridge sizes (IJM No. 1–7 depending on scale).
• Analytical sizing: Dynamic Light Scattering — DynaPro ZetaStar (Wyatt Technology).

Key results and discussion:

- Critical Re and plateau behavior: On the NanoScaler, particle diameter decreased with increasing Re and reached a plateau (~52 nm) above a critical Reynolds number of approximately 750. Below Re ~500, mixing was insufficient, yielding larger particles (>100 nm) and heterogeneous supersaturation.
- Cross-scale hydrodynamic matching: Operating at Re = 1120 (selected above the critical threshold) across five differently sized IJM geometries produced consistent particle diameters and low PDI on the NanoScaler, demonstrating hydrodynamic similarity across mixer sizes.
- Scale-up to benchtop: Replicating the Reynolds-number conditions on the Benchtop NanoProducer yielded comparable CQAs (particle diameters ≈ 50 nm, PDI < 0.05) across multiple IJM cartridges (3–7) and TFR ranges, confirming successful transfer of formulation conditions.
- Throughput expansion: On the benchtop system, increasing TFR and Re (tested up to Re ≈ 8400 and TFR up to ~200 ml/min on IJM 5) retained particle size and low PDI within the established plateau, indicating that shear/mixing intensity rather than absolute flow rate governs LNP assembly in this regime.

Practical benefits and applications of the method:

- Predictable scale-up: Using Re as a scale-agnostic control variable enables direct transfer of mixing-controlled formulations from lab to production while preserving CQAs.
- Robustness and flexibility: Operating above the identified critical Re yields a plateau region where variations in flow rate and minor equipment differences have limited impact on particle attributes, supporting routine manufacturing and process robustness.
- Throughput gains: Maintaining the hydrodynamic regime allows substantial increases in production rate without compromising particle quality, facilitating rapid scale-up for development and early manufacturing needs.

Summary of analytical observations (figures and tables summarized):

- Particle size vs. Re: monotonic decrease in mean diameter with increasing Re until a plateau near 52 nm above critical Re ≈ 750.
- Multi-IJM comparison at matched Re: consistent diameters and PDIs across IJM geometries when Re = 1120, confirming hydrodynamic similarity as a valid scale-up criterion.
- Throughput window: particle size and PDI stable across a wide Re range (252–8400) on benchtop, emphasizing a broad operational window above the critical Re.

Future trends and potential applications:

- Integration with quality-by-design frameworks: Dimensionless-parameter scaling (Re, Da) can be embedded in QbD strategies to define design spaces and control strategies for LNP manufacturing.
- Online monitoring and PAT: Coupling hydrodynamic setpoints with real-time analytics (e.g., inline DLS, FFF, Raman) can further reduce risk and enable automated control of CQAs during scale-up and continuous production.
- Wider applicability: The Re-based approach is relevant to other rapid self-assembly or precipitation processes where assembly timescales are comparable to mixing timescales, including polymer nanoparticles and certain inorganic colloids.

Conclusions:

The study shows that identifying and maintaining a hydrodynamic regime defined by a critical Reynolds number provides a practical and robust route to scale LNP production using impinging-jet mixers. Operating above the critical Re places formulation in a plateau region where particle size and PDI are minimally sensitive to further increases in flow rate, enabling reproducible transfer from R&D to benchtop production and scalable throughput expansion while preserving predefined CQAs.

References:

1. Zhou W., Jiang L., Liao S., Wu F., Yang G., Hou L., Liu L., Pan X., Jia W., Zhang Y. Vaccines’ New Era — RNA Vaccine. Viruses. 2023;15.
2. Hou X., Zaks T., Langer R., et al. Lipid nanoparticles for mRNA delivery. Nature Reviews Materials. 2021;6:1078–1094.
3. Devos C., Mukherjee S., Inguva P., et al. Impinging jet mixers: A review of their mixing characteristics, performance considerations, and applications. AIChE Journal. 2025;71(1):e18595.