PARC is organising the Hackathon for Bioinformatics, a four-day hybrid training event focused on the application of artificial intelligence and computational modelling approaches to toxicology and chemical risk assessment. The Hackathon will take place from 7 to 10 September 2026, with the possibility to participate remotely or in person in Tarragona, Spain. The event is organised into four parallel sessions, each dedicated to a specific application of AI and computational approaches. Participants will select one session and work on it throughout the Hackathon, combining practical activities with guidance from experts in the field, under the scientific coordination of Vikas Kumar (IISPV and BfR), Philip Marx-Stoelting (BfR),  Giles Rivière (ANSES) and Denis Sarigiannis (AUTH). 

What to expect:

Participants can choose one of four parallel sessions:

• LLM-Assisted FAIR PBPK Model Building: exploring how Large Language Models (LLMs) can support the transformation of PBPK model descriptions into FAIR-compliant, standardised, and well-annotated formats, contributing to greater reproducibility in PBPK modelling. 
• Weight of Evidence Assessment for AOP Using Agentic AI: developing an AI-assisted approach to evidence retrieval, evaluation, and structured scoring to improve the transparency and reproducibility of Weight of Evidence assessments for Adverse Outcome Pathways (AOPs). 
• Extending AOP Ontology with Evidence Curation: exploring how AOP Ontology can be extended with structured information on evidence provenance, study design, and evidence type to improve evidence-level queries and computational reasoning. 
• AI-driven QSAR-to-PBPK Pipeline: developing a workflow combining QSAR predictions with AI-assisted database and literature searches to address missing chemical-specific parameters and support more scalable and consistent PBPK model development.

Who should attend:

The Hackathon is intended for Master's students, PhD students, and junior researchers interested in applying bioinformatics, AI, and computational modelling approaches to toxicology and chemical risk assessment. Participants should have knowledge of R or Python, together with basic knowledge relevant to their selected session, such as LLMs, agentic AI, ontology, QSAR, or PBPK modelling.

Practical details:

Participation is free of charge, but attendees are responsible for covering their own travel, accommodation, and other expenses.

How to apply:

Submit your application here ↗ by 7 September.

For additional information about the Hackathon and the application process, please click here.