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Biomedical Engineering Education

Biomedical Engineering Education - Poster Session D

Poster R2 - Developing an Open-Source High-Throughput Lipid Nanoparticle Synthesis Workflow for Multi-Formulation Screening Using an Automated Liquid Handler

Friday, October 25, 2024
3:30 PM - 4:30 PM EST
Location: Exhibit Hall E, F & G

Introduction:  The advent of lipid nanoparticles (LNPs) as delivery vectors has significantly revolutionized the field of gene therapy and personalized medicine. LNP formulation optimization of lipid and cargo components using conventional LNP synthesis methods is labor – intensive and time consuming. In our study, we introduce a high-throughput method utilizing the next-generation open-source automated liquid handling robot – Opentrons Flex, which is capable of synthesizing up to 96 or 384 distinct LNP formulations simultaneously. This approach aims to democratize and streamline the screening and optimization of multiple formulations, thereby accelerating the discovery of effective LNP therapeutic agents.

Materials and

Methods:  Our high-throughput workflow employs the Opentrons Flex, an open-source automated liquid handling robot, to perform precise pipetting operations for lipid mixing for the synthesis of lipid nanoparticles. To benchmark our developed protocol and workflow, we first tested the synthesis of LNP formulations consisting of 2 sets of FDA approved ionizable cationic lipids – SM-102 and ALC-0315, along with other helper lipids which include 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), cholesterol, and a polyethylene glycol (PEG)-lipid conjugate. The experimental setup included varying the types of lipids, their molar ratios, and protocol parameters to investigate their effects on nanoparticle size and polydispersity index (PDI). The synthesised lipid nanoparticle library was characterized on Malvern Zetasizer Ultra for size and PDI.

Results, Conclusions, and Discussions: RESULTS
The Opentrons Flex demonstrated good precision in producing LNPs with consistent size distribution within the therapeutic range of 106–170 nm. The polydispersity index of the individual formulations was within an acceptable range of 0.08-0.18, comparable to conventional microfluidic synthesis. The LNPs were synthesized in triplicates and the reproducibility of nanoparticle sizes and PDIs across different formulations underscores the reliability of the automated approach. This high-throughput method facilitated rapid screening and optimization of LNP formulations within a time frame of 60-minutes for a 96-well formulation, identifying key parameters such as the pipetting speed varying from 1x-3x, mixing volume, dispensing speed ranging from 480 µL/s to 850 µL/s and number of mixes influencing nanoparticle characteristics. Our data showed that specific molar percentages of the lipid significantly affect the size and uniformity of the LNPs, offering valuable insights for tailoring the appropriate formulations for specific therapeutic needs.
CONCLUSION
This study presents a scalable, efficient, and open-source solution for high-throughput LNP synthesis using the Opentrons Flex automated liquid handling robot. The developed protocol enhances the ability to perform extensive formulation studies, which are impractical with conventional methods. Our protocol can also be shared to the Opentrons open-source protocol library for other research groups to use, adapt, and reproduce in support of the FAIR (Findability, Accessibility, Interoperability, and Reuse) principles. The platform’s precision and reproducibility make it an invaluable tool for the rapid development of LNP–based therapeutics. Future work will focus on further optimization, encapsulation of various nucleic acids, and extending the application of this technology to other therapeutic agents, thereby advancing the field of nanomedicine.
IMPACT
The implementation of an automated liquid handling system for high-throughput LNP-synthesis represents a significant advancement in the field of nanomedicine. The open-source nature of our developed workflow can also enable democratization of this approach. This technology not only accelerates the discovery and optimization of lipid-based delivery systems, but also opens new avenues for the development of personalized therapeutics. By enabling large-scale, reproducible synthesis of diverse formulations, this developed platform supports the rapid translation of research findings into clinical applications, potentially transforming therapeutic delivery and improving patient outcomes.

Acknowledgements (Optional):  I would like to acknowledge the University of Texas System STARs Program (E210292976), the Trauma Research and Combat Casualty Care Collaborative (TRC4) (226420284A) and the Research Foundation for the State University of New York along with the School of Engineering & Applied Sciences at the University of Buffalo for funding and providing interdisciplinary expansion for this project.