R&D teams struggle to connect scattered evidence—chemical structures, assay results, omics readouts, ELN notes, public databases (ChEMBL/DrugBank/PubMed), and internal discovery reports—into a single, defensible view of “which molecule should we advance, and why.” The Molecule-Target Pathfinder agent unifies these sources into a searchable knowledge graph and analysis workspace. It answers small, targeted questions (e.g., “Does a higher literature hit count correlate with genomic similarity score—any supporting papers?”) and bigger portfolio ones (e.g., “Rank the top-10 molecules by predicted likelihood of success and plot them”).

Using Corvic’s multi-space retrieval and analytics, the agent links molecules to proteins/targets, aligns assay and PK/PD signals, cross-checks literature claims, and surfaces explainable features behind each recommendation. It can match drugs to proteins based on structural/sequence similarity and prior evidence, quantify correlations (e.g., literature hit count vs. genomic similarity), and produce ranked shortlists with citations and visualizations—accelerating triage, reducing false positives, and improving confidence in go/no-go decisions.