metadata
language: en
license: mit
tags:
- drug-repurposing
- biomedical-nlp
- bert
- text-classification
- twas
TRACE Classifier
This is the fine-tuned BiomedBERT classifier for TRACE — TWAS-driven Repurposing through AI-assisted Curation of Evidence.
Model Description
The classifier is built on BiomedBERT and fine-tuned to classify PubMed abstracts for drug-gene relationships across three simultaneous tasks:
- Relationship detection — does this abstract support a direct drug-gene interaction?
- Mechanism classification — inhibitor, agonist, activator, antagonist, downregulator, upregulator, etc.
- Direction classification — does the drug increase or decrease gene expression or activity?
Held-out macro F1: 0.809 across all three tasks.
Intended Use
This model is used as part of the TRACE pipeline. It is not intended to be used as a standalone model outside of that context. See the TRACE GitHub repository for full usage instructions.
Citation
Otieno CO, Seagle HM, Akerele AT, Jaworski J, Guare L, Setia-Verma S, Velez Edwards DR, Edwards TL. TRACE: A fine-tuned biomedical language model for directionally informed drug repurposing from transcriptome-wide association studies. 2026. Preprint.