# Integrating Large Language Models For Monte Carlo Simulation of Chemical Reaction Networks

Source: [Integrating Large Language Models For Monte Carlo Simulation of Chemical Reaction Networks](<https://www.sota2.com/research/paper/68fa779c1e209131cea74519>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T04:23:33.312Z

Authors: Sadikshya Gyawali, Ashwini Mandal, Manish Dahal, Manish Awale, Sanjay Rijal, Shital Adhikari, Vaghawan Ojha

Published: 2025-03-27T06:01:50.000Z

## Abstract

Chemical reaction network is an important method for modeling and exploring complex biological processes, bio-chemical interactions and the behavior of different dynamics in system biology. But, formulating such reaction kinetics takes considerable time. In this paper, we leverage the efficiency of modern large language models to automate the stochastic monte carlo simulation of chemical reaction networks and enable the simulation through the reaction description provided in the form of natural languages. We also integrate this process into widely used simulation tool Copasi to further give the edge and ease to the modelers and researchers. In this work, we show the efficacy and limitations of the modern large language models to parse and create reaction kinetics for modelling complex chemical reaction processes.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2503.21178>)

[PDF](<https://arxiv.org/pdf/2503.21178.pdf>)