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๐Ÿš€ Innovations & IP Portfolio

10 patent families. 364K lines. Self-improving daily.

10
Patent Families
150
Targets
14
A+/A Leads
+23%
Strategy Uplift
94%
Validity
37
Nightly Phases

Innovation Families

1. NPEAD Learn-to-Learn Scoring

Meta-learning (MAML) inside drug scoring. Adapts to new target classes in 1 gradient step. 28-dim dual scorer. Self-corrects from outcomes. Governed self-modification.

2. Regulatory Activity Layer NEW

TF activity inference โ†’ discordance detection โ†’ EGAO authority scoring โ†’ therapeutic hypothesis generation โ†’ strategy-conditioned molecules. +21% NPEAD uplift.

3. Closed-Loop Generative Learning NEW

Every docking result feeds back. Transformer fine-tuned on positives. Active learning (2 iter/job). Daily RL from Vina scores. Known actives seeding (enzalutamide, osimertinib, dabrafenib scaffolds). Confidence-weighted temperature. Model improves without human.

4. Pocket-Aware Generation NEW

3D CNN pocket encoder. Real PDB profiles (16 targets). 16-dim conditioning = pocket shape + regulatory intent + NPEAD knowledge. 94% validity.

5. Monotone Cost Escalation

8 gates cheapest-first. External grade gate. Authority only decreases. 95% cost reduction vs naive pipelines.

6. Governed Self-Improvement NEW

Level 1: Autonomous config (bounds/delta/cooldown). Level 2: Self-generated PRs with evidence bundles. Never touches main.

7. Multi-Cancer End-to-End Discovery

145 genes from TCGA. De novo + repurposing + CDx + cross-cancer scan. 4 revenue streams. RO-Crate evidence.

8. 3D Failure Reasoning NEW

Diagnoses WHY molecules fail: steric clash, missing H-bonds, shape mismatch. Generates fix suggestions for next cycle.

9. CIFOG Knowledge Graph

276 nodes, 608 edges. Qdrant vectors. GCN driver/passenger (87.5%). Fused embeddings for cross-entity reasoning.

10. Quantum-Gated Validation

VQE binding confirmation (local/sv1/IonQ). Quantum only after classical gates pass. Cost-ordered.

7 Differentiators

#DifferentiatorWhy It Matters
1NPEAD learn-to-learnAdapts instantly to new targets โ€” no retraining
2Governed self-improvementAutonomous but safe โ€” regulated environments need this
3Closed-loop generationGets better every day without human intervention
4Monotone cost escalation95% cheaper than brute-force approaches
5Full evidence chainEvery decision traceable โ€” patent and regulatory ready
6End-to-end multi-cancer4 revenue streams from one system
7Strategy-conditioned generationMolecules have therapeutic intent from first atom