For Investigational Use Only

Advancing Precision Insights for Pancreatic Cancer

Oncology Copilot leverages RNA-based biology and patent-pending AI interpretation to provide actionable insights into tumor heterogeneity and potential chemotherapy benefit.

Oncology Copilot is currently a patent-pending investigational tool. It has not been FDA approved or validated for diagnostic use nor can it be used as a primary diagnostic tool.

73% Accuracy

Retrospective Analysis Results

In retrospective cohort analyses, our investigative AI model demonstrated a 73% accuracy rate in predicting patient response to standard-of-care chemotherapy regimens.

Initial Decision Support

Predicting the likelihood of chemotherapy benefit

The first treatment choice is a critical inflection point in pancreatic care. Oncology Copilot provides a transcriptomic assay to support treatment planning and personalized regimen selection.

Predict Chemotherapy Benefit
Position the pancreatic test as a primary tool to predict the likelihood of chemotherapy benefit and individualize the therapeutic path
Individualize treatment strategy
Combine tumor biology, RNA-derived signals, and AI interpretation to move beyond generalized assumptions toward patient-specific data
Support provider discussions
Present results in a structured, clear report that helps communicate risk and expected benefit with greater transparency
Investigative Framework
1

Clarify Therapeutic Window

Translate complex transcriptomic data into a structured readout identifying likely responders

2

AI-Assisted Evidence Synthesis

Synthesize genomic context and evidence summaries into an analytical experience

3

Enhanced Informational Dialogue

Equip teams with report findings designed to frame both benefits and options more clearly

Post-Progression Care

Navigating Resistance with Adaptive Strategy

Once pancreatic cancer progresses, the original diagnostic snapshot may no longer be representative. Oncology Copilot re-evaluates current tumor biology to give care teams a foundation for assessing the next approach.

Re-evaluate biology after resistance
Support assessment after resistance by reassessing the tumor’s current biology and identifying meaningful change since the initial diagnosis.
Identify alternate pathways
Surface alternative chemotherapy strategies and off-label options that may become relevant as the disease evolves.
Capture tumor evolution
Use refreshed molecular profiling to detect new signals and guide adaptive, evidence-linked planning for second-line care and beyond.
Adaptive Strategy
1

Reassess Biology After Resistance

Provide a view of tumor biology after progression, replacing generalized assumptions with current insights.

2

Expand Treatment Options

Highlight alternative chemotherapy paths and off-label options that help teams consider the next move.

3

Enable Adaptive Updates

Support data-driven updates to the treatment plan with a structured analytical workflow.

Inquire about your analysis

Empower decision-making with transcriptomic insights grounded in evidence. Contact us to learn about investigative analysis opportunities.