An Accessible and Scalable Pipette-Driven Microfluidic Platform for Lipid Nanoparticle Formulation
Advances in lipid nanoparticle (LNP) technology have increased the need for accessible and scalable methods that accelerate low-volume formulation screening. Here, we describe a disposable microfluidic mixer actuated by a positive-displacement pipette equipped with dual-chamber pipette tip, providing volumetric control at a fixed flow rate ratio without external microfluidic pumps. Computational fluid dynamics analysis predicted shorter micromixing times in the high-shear spiral channel than in the low-shear design. Across three benchmark lipid formulations, the high-shear mixer reproducibly generated smaller LNPs with higher mRNA encapsulation efficiency than the low-shear mixer or manual pipetting. Orthogonal characterization further revealed higher particle concentrations, structural features consistent with compact particles, more uniform mRNA loading, and a lower empty-particle fraction. LNPs prepared using the selected high-shear mixer mediated functional mRNA delivery in 2D cell cultures, a 3D human liver tissue model, and mice. Integration with a liquid-handling robot enabled automated screening of formulation parameters. Dimensionless mixing-time analysis guided enlargement of the mixer geometry for a separate production system, which produced 75 mL preparations at 150 mL/min with particle size and mRNA encapsulation efficiency comparable to those obtained with the small-scale mixer. This platform provides an accessible, automation-compatible approach to LNP formulation screening and a route to larger-scale production.
Authors
- Mehdi Dehghani (ORCID: https://orcid.org/0000-0003-4295-4390)
- Hai‐Quan Mao (ORCID: https://orcid.org/0000-0002-4262-9988)
- Samin Akbari (ORCID: https://orcid.org/0000-0003-2244-8941)
- Sixuan Li (ORCID: https://orcid.org/0000-0002-0116-8812)
- Yuji S. Takeda (ORCID: https://orcid.org/0000-0002-0065-2063)
- Martha Mayo
- Yuriy Kim (ORCID: https://orcid.org/0000-0001-8658-6863)
- Joseph F. Finelli
- Sabrina I. Apel (ORCID: https://orcid.org/0009-0001-0407-3464)
- James Forster (ORCID: https://orcid.org/0000-0002-3164-5819)
- Tza‐Huei Wang (ORCID: https://orcid.org/0000-0002-3540-9354)
- Shayan Shafiee (ORCID: https://orcid.org/0000-0002-2679-764X)
- Parsa Molaei (ORCID: https://orcid.org/0000-0002-5595-1327)
- Seyoum Ayehunie (ORCID: https://orcid.org/0000-0002-4365-5504)
- Parnian Hemmati (ORCID: https://orcid.org/0000-0003-0142-3278)
- Behnam Partopour (ORCID: https://orcid.org/0000-0003-0809-0824)
- Fujun Wang (ORCID: https://orcid.org/0000-0002-4283-4631)
- Jinghan Lin (ORCID: https://orcid.org/0009-0002-1475-1895)
- Haoyi Hou
- Ryan Norton
- Xin Gu
- Laura Maugeri
- Chen-wei Chiang
Institutions
- Johns Hopkins University (US)
- Johns Hopkins University Applied Physics Laboratory (US)
- MatTek (Slovakia) (SK)
- Sartorius (United States) (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-11-09
- DOI
- https://doi.org/10.64898/2026.11.06.757988
- Primary Topic
- RNA Interference and Gene Delivery
- Type
- preprint