English

Stochastic Molecular Reaction Queueing Network Modeling for In Vitro Transcription Process

Molecular Networks 2023-06-22 v2

Abstract

To facilitate a rapid response to pandemic threats, this paper focuses on developing a mechanistic simulation model for in vitro transcription (IVT) process, a crucial step in mRNA vaccine manufacturing. To enhance production and support industry 4.0, this model is proposed to improve the prediction and analysis of IVT enzymatic reaction network. It incorporates a novel stochastic molecular reaction queueing network with a regulatory kinetic model characterizing the effect of bioprocess state variables on reaction rates. The empirical study demonstrates that the proposed model has a promising performance under different production conditions and it could offer potential improvements in mRNA product quality and yield.

Keywords

Cite

@article{arxiv.2305.09867,
  title  = {Stochastic Molecular Reaction Queueing Network Modeling for In Vitro Transcription Process},
  author = {Keqi Wang and Wei Xie and Hua Zheng},
  journal= {arXiv preprint arXiv:2305.09867},
  year   = {2023}
}

Comments

11 pages, 3 figures

R2 v1 2026-06-28T10:36:33.841Z