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End-to-end digital twin software for continuous mRNA manufacturing.

Mohammed Aatif Shahab1, Nathan Merica Stover1, Hasan Al-Mahayni1

  • 1Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA.

International Journal of Pharmaceutics
|October 24, 2025
PubMed
Summary
This summary is machine-generated.

A new digital twin software enables continuous manufacturing of messenger RNA (mRNA) therapeutics by simulating key production steps. This accelerates process optimization and supports scalable, reliable, data-driven production for global health demands.

Keywords:
Continuous biomanufacturingDigital twinOpen-source softwareProcess simulationmRNA

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Area of Science:

  • Biotechnology
  • Pharmaceutical Manufacturing
  • Computational Modeling

Background:

  • Messenger RNA (mRNA) therapeutics offer rapid development and broad applications but face manufacturing scalability and consistency issues with traditional batch processes.
  • Continuous manufacturing presents a promising alternative for enhancing mRNA production efficiency and reliability.

Purpose of the Study:

  • To develop and present a novel digital twin software for end-to-end continuous manufacturing of mRNA therapeutics.
  • To integrate key unit operations into a modular, user-friendly platform for process simulation and optimization.

Main Methods:

  • The software integrates In Vitro Transcription (IVT), Tangential Flow Filtration (TFF), Continuous Chromatography (CCTC), Lipid Nanoparticle (LNP) formulation, and Freeze-Drying modules.
  • A graphical interface allows engineers to manipulate modules without coding, supported by mechanistic models and a database for data storage.
  • Morris-based global sensitivity analysis was employed for process optimization and model validation.

Main Results:

  • The software successfully simulated all five unit operations in silico for a representative mRNA production scenario.
  • Generated time series and 3D plots provided insights into process dynamics and product characteristics.
  • Sensitivity analysis identified critical input factors for process optimization.

Conclusions:

  • The digital twin software accelerates process optimization and promotes Quality-by-Design (QbD) principles for mRNA manufacturing.
  • It provides a platform for closed-loop control and operator training, supporting data-driven continuous manufacturing.
  • This technology enhances scalability, reliability, and responsiveness for mRNA therapeutics production.