Agentic Causal Graph Learning for Drug Target Discovery
Causal graph methods for mapping mechanism relationships — applied to nutrition pathway analysis.
Our work begins with a defined scientific question. We then assess fit, scope the brief, review relevant literature, and apply computational or mechanism-focused methods where they add value.
Define the question
Assess fit and scope
Run literature and computational analysis where relevant
Deliver a written brief or dossier
Not every project requires every method. The method depends on the question. The deliverable is always a written scientific asset.
The computational approaches we may use have been validated through peer-reviewed publications at AAAI, ICLR, NeurIPS, and other top AI and bio venues.
Causal graph methods for mapping mechanism relationships — applied to nutrition pathway analysis.
ADMET screening methods adapted for ingredient safety and bioavailability assessment.
Validated causal hypothesis testing methods applied to bioactive compound analysis.
Multi-scale safety screening of compounds — the same approach for ingredient-level analysis.