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PreprintCC BY-NCbioRxiv

Scaling Network Medicine with LLMs for Combinatorial Drug Repurposing in ER+ Breast Cancer

  • A. A. Hamed1
  • T. E. Fandy
  • L. M. Rocha
  1. 1University of Nebraska-Lincoln
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Abstract

Drug repurposing can accelerate therapy discovery for ER+ breast cancer, but combination selection remains difficult. We developed an LLM-driven network medicine framework that extracts drug--target relationships from 595,122 PubMed abstracts, builds a cross-model consensus network, overlays it onto the KEGG estrogen signaling pathway, and enumerates complementary drug pairs. Candidate combinations are ranked by ComboRank, which aggregates pathway coverage, LLM consensus, RAG validation, cross-method agreement, and ClinicalTrials.gov precedent. The framework identified 166 significant pairs at FDR <= 0.05, including 31 with clinical-trial precedent, with 393 shared drug--target pairs across extraction strategies and 11 exact pairs additionally supported by the pathway overlay.

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Cite

BibTeXRIS
BibTeX
@misc{hamed2026scaling,
  title = {{Scaling Network Medicine with LLMs for Combinatorial Drug Repurposing in ER+ Breast Cancer}},
  author = {A. A. Hamed and T. E. Fandy and L. M. Rocha},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.14.728753},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.14.728753v1},
  note = {CC BY-NC},
}
RIS
TY  - UNPB
TI  - Scaling Network Medicine with LLMs for Combinatorial Drug Repurposing in ER+ Breast Cancer
AU  - A. A. Hamed
AU  - T. E. Fandy
AU  - L. M. Rocha
PY  - 2026
DA  - 2026/09/14
PB  - bioRxiv
DO  - 10.64898/2026.09.14.728753
UR  - https://www.biorxiv.org/content/10.64898/2026.09.14.728753v1
AB  - Drug repurposing can accelerate therapy discovery for ER+ breast cancer, but combination selection remains difficult. We developed an LLM-driven network medicine framework that extracts drug--target relationships from 595,122 PubMed abstracts, builds a cross-model consensus network, overlays it onto the KEGG estrogen signaling pathway, and enumerates complementary drug pairs. Candidate combinations are ranked by ComboRank, which aggregates pathway coverage, LLM consensus, RAG validation, cross-method agreement, and ClinicalTrials.gov precedent. The framework identified 166 significant pairs at FDR <= 0.05, including 31 with clinical-trial precedent, with 393 shared drug--target pairs across extraction strategies and 11 exact pairs additionally supported by the pathway overlay.
ER  -