This research demonstrates how large language models can automate and accelerate the simulation of complex chemical reaction networks in biological systems.

• Automates stochastic monte carlo simulations through natural language descriptions
• Reduces time-consuming manual formulation of reaction kinetics
• Enables faster modeling of complex biological processes and biochemical interactions
• Provides a more accessible approach to system biology simulation

For biology, this integration creates opportunities to model and understand intricate biological mechanisms more efficiently, potentially accelerating research in drug development, cellular behavior, and disease modeling.

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