Uncover Hidden Mechanisms in Drug Lead Optimization With a Multi-Axis Workflow
Drug lead optimization teams face a critical challenge: identifying metabolic liabilities, cytotoxic effects, and immune-related risks early enough to guide compound selection before costly preclinical studies. Traditional single-modality assays often leave blind spots—allowing safety and efficacy risks to emerge only in late-stage development, where attrition is significantly more expensive.
An integrated workflow overcomes these gaps by combining real-time cellular metabolomics, functional cytotoxicity analysis, and lipidomics—all from the same in vitro sample set. This unified approach enables a systems-level understanding of compound effects, revealing mechanistic insights that remain inaccessible to isolated assays.
This application note demonstrates:
- How multi-axis data integration uncovers metabolic and lipidomic changes missed by standalone assays
- Detection of immune-related signaling alongside functional cytotoxicity —from the same sample set
- How connected LC/MS omics workflows support earlier de-risking and more confident lead advancement decisions
For Research Use Only. Not for use in diagnostic procedures.
PR7004-1454
