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MIT reports automated system for sizing RNA delivery particles

The system measures lipid nanoparticles and adjusts production settings. Separate, older research shows why size matters, but does not validate MIT’s apparatus.

The Great Dome at the Massachusetts Institute of Technology.
The Massachusetts Institute of Technology’s Great Dome, photographed on August 30, 2019. File photo; the lipid nanoparticle production system is not pictured. Web version: converted to WebP and size-optimized without cropping. Mys 721tx / Wikimedia Commons — Great Dome, Massachusetts Institute of Technology, Aug 2019 — CC BY-SA 3.0. CC BY-SA 3.0.
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MIT researchers have automated a process for making lipid nanoparticles at requested sizes, the university announced on September 25. The fatty carriers package RNA and other nucleic acids; controlling their dimensions could help researchers compare options for delivering future therapies.

According to MIT News, the system uses dynamic light scattering to measure particles as they form. If their size misses the target, it adjusts the delay between mixing steps and other production settings.

What the system controls

The automation builds on the team’s work published in 2025. In that process, changing the delay between two mixing steps controls particle growth. Changing the concentration of the buffer added in the second step alters particle shape without changing the lipid formulation, MIT says.

Shape measurement remains outside the automated system. MIT says the researchers also used experimental data to train a machine-learning model to predict settings associated with particular particle sizes or shapes.

Why size matters

An older, independent study by researchers at the Catholic University of Korea and Sungkyunkwan University provides context. Published on November 23, 2025 in the Journal of Nanobiotechnology, it produced particles ranging from 30 to 270 nanometers by changing microfluidic flow conditions while keeping lipid ratios identical.

That team found size-related differences in cellular uptake and gene expression in cultured cells, and in organ-level expression after injections in mice. It used a different production method: the findings support investigating particle size, but do not replicate MIT’s automated system or establish effects in humans.

MIT’s announcement describes a tool for formulation experiments. It does not establish a numerical speed improvement, shorter drug-development timelines or patient benefit from the system.

MIT says the researchers have filed for a patent and are working to commercialize the technology through BIZON Labs. It identifies the U.S. Food and Drug Administration and a National Cancer Institute grant as research funders.

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