Evo 2 AlphaFold3 Cancer Classifier

I built a variant-to-therapy guidance system by chaining Evo 2 (40B genomic foundation model) with AlphaFold3 for structural validation. The pipeline takes a cancer mutation as input and outputs a tiered therapeutic recommendation with mechanistic rationale, multi-modal biological scoring, and 3D protein-drug interaction validation.

The technical demo will walk through:

1. How I fine-tuned Evo 2 embeddings for multi-class variant classification (essentiality, functionality, chromatin, regulatory impact)
2. My custom scoring layer that converts sequence likelihoods into actionable therapeutic guidance
3. The AlphaFold3 integration that validates every guide/drug-target pair at atomic resolution
4. Live code walkthrough of the inference pipeline: VCF → Evo 2 → scoring → AlphaFold3 → JSON output

I’ll show the actual Python code, the model architecture, and walk through a real BRCA1 ovarian cancer case where the system correctly identified synthetic lethality despite low essentiality scores.