D. Lee
University of Pennsylvania,
United States
Summary:
Conventional particle engineering follows a fragmented workflow: milligram‑scale discovery in bench reactors, followed by a complete process redesign for kilogram‑scale manufacturing. This hand‑off is slow, expensive, and frequently compromises the very attributes that made the original particles attractive. Microfluidics enables precise control over nanoscale and microscale particle synthesis, allowing tuning of size, structure, and composition. However, widespread use has been limited by surface fouling, low production rates, and reproducibility issues. In this presentation, I will present our work to address these challenges using automation, surface lubrication, and scalable device architectures. Our platform integrates real-time AI-augmented image-based feedback with adjustable flow control to reliably produce emulsions, microcapsules, and lipid nanoparticles at high throughput and with excellent consistency. I will focus on examples involving the microfluidic production of polymeric microparticles and lipid nanoparticles (LNPs), demonstrating how parallelization and surface-lubrication strategies enable seamless scaling from discovery to manufacturing. Together, these efforts highlight microfluidics as a versatile platform for designing and producing functional particulate systems with applications in drug delivery, soft robotics, and environmental sensing. I will also highlight ongoing research and development at the NSF AI-driven RNA BioFoundry, which seeks to expand and democratize the use of RNA technologies throughout bioscience and biotechnology.