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Talk2Biomodels: AI agent-based open-source LLM initiative for kinetic biological models.

Lilija Wehling1, Gurdeep Singh2, Ahmad Wisnu Mulyadi2

  • 1BioMed X Institute, Heidelberg, Germany. wehling@bmedx.com.

BMC Bioinformatics
|November 19, 2025
PubMed
Summary
This summary is machine-generated.

Talk2Biomodels (T2B) is a new AI platform that simplifies accessing and analyzing biological models using natural language conversations. This tool makes complex systems biology models more accessible to both experts and non-experts, promoting FAIR data principles.

Keywords:
Agentic AIFoundational modelsOrdinary differential equation modelsSystems biology

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Quantitative kinetic models are crucial for understanding disease mechanisms but require specialized expertise for simulation and analysis.
  • Accessing and interpreting complex biological models presents a significant barrier for researchers without extensive computational training.

Purpose of the Study:

  • To introduce Talk2Biomodels (T2B), an AI platform designed to democratize access to computational models of biological systems.
  • To promote the FAIRification (Findability, Accessibility, Interoperability, Reusability) principles within systems biology research.
  • To enable users to interact with and analyze biological models through natural language conversations.

Main Methods:

  • Development of an open-source, user-friendly, large language model-based agentic AI platform (Talk2Biomodels).
  • Integration with the BioModels database for retrieval, simulation, and analysis of curated systems biology models.
  • Support for models encoded in the Systems Biology Markup Language (SBML).

Main Results:

  • Talk2Biomodels allows natural language interaction, lowering the entry barrier for model interpretation and hypothesis-driven exploration.
  • The platform successfully demonstrated its capabilities in use cases related to precision medicine, infectious disease epidemiology, and cellular systems.
  • Both computational experts and domain scientists without prior modeling training can derive actionable insights from complex biological models using T2B.

Conclusions:

  • Talk2Biomodels significantly lowers the barrier for non-experts to engage with computational biological models.
  • The platform offers a streamlined interface for experts to analyze models, enhancing efficiency.
  • T2B contributes to the overall FAIRification of biological models, improving their accessibility and reusability.