Match Patients to Therapies
Mechanism-Based Drug Ranking
S/P/E fusion (Sequence/Pathway/Evidence) matches patients to therapies with 96.6% trial match accuracy. Mechanism-based matching, not just standard of care.
Turn genetics into plain, useful guidance for chemo planning: a ranked drug hypothesis, a confidence hint, and an auditāready summary you can share with your team
Chemo CoāPilot: InāSilico Chemotherapy Guidance
Evidence-backed chemotherapy recommendations with 70-85% confidence. See which drug classes match your patient's tumor biology with transparent S/P/E reasoning. Action-ready dossiers for same-day tumor board discussions.
The Problem: Choosing chemotherapy can be unclear when biology is complex
Choosing chemotherapy can be unclear when biology is complex. We help by turning genetics into a simple, auditable starting point.
Too many options, little clarity on fit to tumor biology.
Too many options, little clarity on fit to tumor biology.
Confidence is hard to communicate without sources and a simple story
Confidence is hard to communicate without sources and a simple story
Data is scattered; assembling a shareable summary takes time
Data is scattered; assembling a shareable summary takes time
The Solution: Transform genetics into plain, useful guidance for chemo planning: a ranked drug hypothesis, a confidence hint, and an auditāready summary you can share with your team
Our live S/P/E + insights pipeline converts variants into a chemo guidance view: top drug classes, confidence, rationale, and citationsāall with provenance (run ID, profile).
Uncertainty Reduction
Dramatically reduced variant uncertainty in chemotherapy applications through advanced AI classification
Classification Improvement
Enhanced variant classification accuracy with 14% consider ā supported upgrades
Confidence Enhancement
Consistent confidence boost across all variants (range +0.05 to +0.12)
Real-World Results
Measurable outcomes from using this capability
Uncertainty Reduction
Dramatically reduced variant uncertainty in chemotherapy applications through advanced AI classification
Classification Improvement
Enhanced variant classification accuracy with 14% consider ā supported upgrades
Confidence Enhancement
Consistent confidence boost across all variants (range +0.05 to +0.12)
See It In Action
Interactive demonstration of this capability
Live Demo Coming Soon
Interactive demonstration for Chemo CoāPilot: InāSilico Chemotherapy Guidance will be available here.
The Chemotherapy Treatment Journey
From genetic testing confusion to precision, biology-aware chemotherapy selection with CrisPRO's Oracle & Forge Engines
Genetic Testing
Patient receives genetic test results with unclear drug response predictions.
Critical Problems
- Limited pharmacogenomic guidance for chemo selection
- Standard protocols ignore patient-specific genetics
- No clear drug ranking based on tumor biology
Clinical Confusion
Oncologist struggles to match chemotherapy drugs to patient's genetic profile.
Critical Problems
- Physicians rely on standard protocols, not personalized biology
- Limited understanding of drug-gene interactions
- Treatment decisions based on incomplete pharmacogenomic data
Trial & Error Treatment
Patient undergoes chemotherapy that may not match their genetic drug response profile.
Critical Problems
- Average 2-3 chemo attempts before finding effective therapy
- Precious time lost during cancer progression
- Unnecessary toxicity from ineffective drug combinations
Treatment Resistance
Without precision drug matching, cancer develops resistance and becomes increasingly difficult to treat.
Critical Problems
- Drug resistance develops from suboptimal initial selection
- Limited treatment options once resistance occurs
- Exponentially higher treatment costs and patient suffering
Biology-Aware Drug Ranking
CrisPRO's Oracle Engine provides MoA-aligned drug class ranking with 95.7% AUROC ClinVar validation and transparent explanations.
AI-Powered Solutions
- 95.7% AUROC ClinVar validation for variant impact prediction
- S/P/E fusion: Sequence, Pathway, Evidence for drug ranking
- Real-time drug class recommendations with confidence scores
Validated Pharmacogenomic Insights
Oracle delivers peer-reviewed variant impact prediction with CrisPRO.ai embeddings and BRCA1 supervised AUROC ā 0.95 for drug-gene interactions.
AI-Powered Solutions
- BRCA1 supervised AUROC ā 0.95 with CrisPRO.ai 40B block-20 embeddings
- Cross-species generalization for drug response pathways
- Transparent explanations with auditable provenance
Precision Chemo Design
Forge Engine generates personalized chemotherapy strategies with 1M token context window and guided epigenomic design.
AI-Powered Solutions
- 1M token context window for comprehensive genomic analysis
- Guided epigenomic design with Enformer+Borzoi scoring
- Configurable beam width for inference-time scaling (beam width ā AUROC)
Research-Validated Chemo Outcomes
End-to-end chemotherapy workflow with validated performance metrics and transparent methodology.
AI-Powered Solutions
- Research-use-only positioning with transparent methodology
- Validated performance metrics with peer-reviewed benchmarks
- Auditable results with complete provenance and run IDs
Journey Visualization
Traditional Approach: The Chemotherapy Treatment Journey
Biology-Aware Drug Ranking
CrisPRO's Oracle Engine provides MoA-aligned drug class ranking with 95.7% AUROC ClinVar validation and transparent explanations.
AI-Powered Solutions
- 95.7% AUROC ClinVar validation for variant impact prediction
- S/P/E fusion: Sequence, Pathway, Evidence for drug ranking
- Real-time drug class recommendations with confidence scores
API Endpoints
/predict_variant_impact/predict_gene_essentiality/generate_therapeutic_protein