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Related Experiment Video

Updated: May 19, 2026

A Workflow for Lipid Nanoparticle (LNP) Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models (SVEM)
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Understanding Size Distributions during Lipid Nanoparticle Manufacturing through Mechanistic Modeling.

Saikat Mukherjee1, Sunkyu Shin1, Cedric Devos1

  • 1Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.

ACS Omega
|May 18, 2026
PubMed
Summary
This summary is machine-generated.

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A new model predicts lipid nanoparticle (LNP) size during manufacturing by simulating lipid crystallization in turbulent mixing. This enables better control over LNP production for mRNA therapeutics.

Area of Science:

  • Biotechnology
  • Chemical Engineering
  • Materials Science

Background:

  • Lipid nanoparticles (LNPs) are crucial for delivering messenger RNA (mRNA) therapeutics.
  • Current LNP manufacturing methods lack a first-principles model for predicting particle size distribution.
  • This limits process control and optimization for consistent LNP production.

Purpose of the Study:

  • To develop a mechanistic model for predicting LNP size and distribution during manufacturing.
  • To understand the fundamental mechanisms governing LNP formation via lipid crystallization.
  • To enable predictive process control for scalable LNP production.

Main Methods:

  • A model based on lipid crystallization during turbulent water-ethanol mixing was developed.

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Constant Pressure-controlled Extrusion Method for the Preparation of Nano-sized Lipid Vesicles

Published on: June 22, 2012

Related Experiment Videos

Last Updated: May 19, 2026

A Workflow for Lipid Nanoparticle (LNP) Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models (SVEM)
13:54

A Workflow for Lipid Nanoparticle (LNP) Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models (SVEM)

Published on: August 18, 2023

Formulating and Characterizing Lipid Nanoparticles for Gene Delivery using a Microfluidic Mixing Platform
09:41

Formulating and Characterizing Lipid Nanoparticles for Gene Delivery using a Microfluidic Mixing Platform

Published on: February 25, 2021

Constant Pressure-controlled Extrusion Method for the Preparation of Nano-sized Lipid Vesicles
11:35

Constant Pressure-controlled Extrusion Method for the Preparation of Nano-sized Lipid Vesicles

Published on: June 22, 2012

  • Population balance equations were employed to predict particle size distributions.
  • The model's predictions were validated against experimental results.

    • Main Results:

    • The model successfully predicted the influence of key parameters like flow rate and lipid concentration.
    • Favorable comparison between model predictions and experimental data was achieved.
    • The model demonstrates the capability for predictive manufacturing of LNPs.

    Conclusions:

    • A mechanistic model for LNP size prediction during turbulent mixing has been established.
    • This understanding is foundational for optimizing LNP manufacturing processes.
    • The findings support the development of consistent LNP production for mRNA vaccines and nucleic acid therapeutics.