Mission
OpenCure Labs exists to make computational biology research more open, reproducible, and accessible. We run autonomous AI-driven research pipelines across genomics, drug discovery, and protein science โ then publish every result as a signed, inspectable artifact that anyone can download and verify.
The platform generates research tasks from public biomedical datasets (TCGA, ClinVar, ChEMBL, GEO), executes them on GPU compute via specialist agents, and publishes the outputs with full provenance metadata. Every artifact carries an Ed25519 integrity signature for auditability.
How the System Works
1. Task Generation
Research tasks derived from public biomedical datasets exploring open problems in oncology, rare disease, and pharmacology.
2. Agent Execution
Specialist agents run computational pipelines on GPU clusters โ neoantigen binding, variant scoring, molecular docking, QSAR.
3. Two-Tier Grok Review
Grok independently critiques each result: methodology, confidence scoring, and literature overlap. Below-threshold results are blocked.
4. Signed Artifact Publication
Approved artifacts stored in Cloudflare R2/D1 with Ed25519 signatures, provenance metadata, and validation warnings.
Research Skills
Neoantigen Prediction
Tumor-specific peptide-MHC binding for personalized cancer immunotherapy targets.
Variant Pathogenicity
Genetic variant scoring for disease-causing potential using ensemble ML models.
Molecular Docking
Protein-ligand interaction simulation to identify drug binding candidates.
QSAR Modeling
Structure-activity models predicting compound bioactivity from molecular features.
Structure Prediction
Protein 3D structure prediction for downstream docking and analysis.
Sequencing QC
Quality control โ coverage, error rates, and contamination checks.
Literature Review
AI-powered analysis of scientific literature to identify gaps and validate hypotheses.
The Review Process
Every result passes through a two-tier review before publication:
Tier 1: Automated Validation
A local critique step checks methodology, input data quality, and statistical validity. Results that fail local validation are withheld.
Tier 2: Independent Critique (Grok)
Grok (xAI) independently evaluates each result โ critiquing methodology, checking literature overlap, and assigning a confidence-oriented review score. Below-threshold results are blocked with a written explanation.
Multi-Species Support
Human
HLA-based neoantigen prediction, variant pathogenicity, and drug response across TCGA cancer types.
Dog (Canine)
DLA-88 MHC allele support for canine neoantigen prediction and variant analysis.
Cat (Feline)
FLA MHC allele support for feline neoantigen prediction and variant analysis.
Why the Public Artifact Browser?
We built the public browser at opencurelabs.ai because open science means more than open-source code โ it means open data. Every computational result we generate is published with integrity signatures, provenance metadata, and explicit validation warnings so anyone can inspect, reproduce, and build on the work.
With 25,000+ published artifacts and growing, the browser gives researchers instant access to AI-generated hypotheses across oncology, rare disease, and drug discovery โ no account required.
Responsible AI Disclaimer
All outputs are AI-generated computational predictions. They carry explicit validation warnings and have not been experimentally validated. Each artifact includes provenance metadata and an Ed25519 integrity signature for auditability. Outputs are open for inspection and reuse, but should be independently validated before scientific or clinical use.
Open Source
The full platform โ agents, pipelines, coordinator, reviewer โ is open source on GitHub. Contributions are welcome via pull requests.