From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generation

• URL: http://arxiv.org/abs/2603.00612v1
• Date: Sat, 28 Feb 2026 12:14:37 GMT
• Title: From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generation
• Authors: Raneen Younis, Suvinava Basak, Lukas Chavez, Zahra Ahmadi,
• Abstract summary: CoDHy is an interactive, human-in-the-loop system for biomarker-guided drug combination hypothesis generation in cancer research.<n>It integrates structured biomedical databases and unstructured literature evidence into a task-specific knowledge graph.<n>Users can configure the scientific context, inspect intermediate results, and iteratively refine hypotheses.
• Score: 4.281508114645598
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The rapid growth of biomedical literature and curated databases has made it increasingly difficult for researchers to systematically connect biomarker mechanisms to actionable drug combination hypotheses. We present AI Co-Scientist (CoDHy), an interactive, human-in-the-loop system for biomarker-guided drug combination hypothesis generation in cancer research. CoDHy integrates structured biomedical databases and unstructured literature evidence into a task-specific knowledge graph, which serves as the basis for graph-based reasoning and hypothesis construction. The system combines knowledge graph embeddings with agent-based reasoning to generate, validate, and rank candidate drug combinations, while explicitly grounding each hypothesis in retrievable evidence. Through a web-based interface, users can configure the scientific context, inspect intermediate results, and iteratively refine hypotheses, enabling transparent and researcher-steerable exploration rather than automated decision-making. We demonstrate CoDHy as a system for exploratory hypothesis generation and decision support in translational oncology, highlighting its design, interaction workflow, and practical use cases.

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