Brinton A. Seashore-Ludlow

A human-supervised multi-agent LLM system covered drug repurposing from knowledge graph building to assay analysis in three case studies; retrospective COVID-19 screen AUC-ROC 0.986 without predefined thresholds.

The paper identifies host-targeting antivirals against SARS-CoV-2 using morphological profiling, finding compounds that reverse infected cell phenotypes and validate host processes hijacked by viruses.

The paper develops a machine learning model to predict drug-induced phospholipidosis using a large dataset of repurposed drugs tested across multiple cell lines.

This paper introduces a method to apply Cell Painting to 3D spheroids for morphological profiling, detecting phenotypic changes in colorectal cancer cells under compound treatments.

The paper develops two annotation pipelines and dashboards to integrate chemical and bioactivity data for drug repurposing, validated on a compound library with over 5000 compounds.

This study identifies novel SETD8 inhibitors and shows their toxicity correlates with ribosome biogenesis regulators, suggesting a biomarker for targeted cancer therapy.

This study shows SMAC mimetics overcome apoptotic resistance in ovarian cancer by targeting the MSLN-TNF alpha axis, enhancing cell death and synergizing with chemotherapy.