The Biosafety Challenge: AI Can Now Design Life
Written by: Daniel Uribe, CEO GenoBank.io
🔬 Breakthrough Alert: First AI-Designed Bacteriophages
In January 2025, researchers published a groundbreaking paper in bioRxiv: they used genome language models (Evo 1 and Evo 2) to generate 16 viable bacteriophage genomes from scratch. These weren't modifications of existing viruses—they were genuinely novel organisms with "substantial evolutionary novelty" that had never existed in nature.
This is a watershed moment. AI can now design complete, functional genomes.
The implications are staggering. Some of these AI-generated phages outperformed their natural template ΦX174 and rapidly overcame antibiotic resistance in multiple E. coli strains. This technology could revolutionize phage therapy, synthetic biology, and biotechnology.
But it also raises an urgent question:
⚠️ The Urgent Question
Who ensures these AI-generated genomes are safe? And how do we prove it?
When AI can design life as easily as ChatGPT writes essays, we need infrastructure for accountability that scales with innovation.
Why Current Systems Fail at AI-Scale Biosafety
The Traceability Gap
Traditional biosafety relies on systems designed for the pre-AI era:
❌ Traditional Biosafety Systems
- Institutional Review Boards (IRBs) - Paper reviews, no cryptographic proof
- Laboratory notebooks - Easily altered, lost, or incomplete
- Publication records - Created after the fact, not during design
- Self-reporting - Voluntary and unverifiable
✅ What We Actually Need
- Immutable audit trails - Blockchain-verified assessments
- Real-time documentation - Logged during design, not after
- Cryptographic proof - Verifiable without trust
- Transparent compliance - Public verification of safety
When something goes wrong—a lab leak, an ethical violation, or misuse of synthetic biology—investigators face a maze of incomplete records. There's no chain of custody. No immutable audit trail. No way to prove what safety assessments were actually performed.
The AI Amplification Problem
📈 The Exponential Challenge
AI doesn't just speed up genomic design—it democratizes it. What once required a PhD in molecular biology and months of lab work can now be done by language models in hours.
This means:
- Exponentially more novel genomes being created
- Sequences designed outside traditional institutional oversight
- Difficulty tracking which AI model generated which sequence
- No standard for documenting safety assessments of AI-generated genomes
We need infrastructure that scales with AI—not bureaucracy that collapses under it.
BioNFTs: Immutable Identity for Every Genome
GenoBank's BioNFT system creates a blockchain-based certificate of authenticity and accountability for biological sequences. Here's how it works:
1️⃣ Cryptographic Identity
Every AI-generated genome receives a unique BioNFT token containing:
- Hash of the complete sequence (immutable fingerprint)
- Timestamp of creation
- Creator's cryptographic signature
- AI model used (Evo 2, AlphaFold, etc.)
- Design parameters and training data provenance
2️⃣ Embedded Audit Trail
Unlike paper records, BioNFTs store the complete safety assessment history on-chain:
- Stage 1: Sequence Analysis
- Stage 2: Function Prediction
- Stage 3: Risk Assessment
- Final: Risk score (0-100), approval/rejection
3️⃣ Permissioned Access Control
BioNFTs implement our Biosample Permission Token standard:
- Regulators can verify assessments instantly
- Researchers can prove due diligence
- Institutions can grant/revoke access cryptographically
- Public transparency without compromising sensitive sequences
The Multi-Layer Assessment: From Sequence to Safety
Figure 1: AI Biosafety Sentinel - Multi-layer assessment pipeline with blockchain audit trail
Our biosafety pipeline diagram illustrates the complete workflow from AI-generated sequence to safety certification:
Input: AI-Generated Genome
When a language model like Evo 2 generates a novel genome, it enters our assessment system as a BioNFT candidate.
Stage 1: Sequence Analysis (Low-Risk Filter)
AI Models Used: PathogenBERT, ToxinPredict-XL
- ✓ Screens against databases of known pathogens
- ✓ Identifies toxin-encoding genes
- ✓ Flags antimicrobial resistance markers
- ✓ Result: Green flag for obviously benign sequences
Stage 2: Function Prediction (Medium-Risk Analysis)
AI Models Used: AlphaFold, BioHazardGPT
- ✓ Predicts 3D protein structures
- ✓ Models metabolic pathway interactions
- ✓ Assesses gain-of-function risks
- ✓ Result: Yellow flag for sequences needing deeper review
Stage 3: Risk Assessment (High-Risk Evaluation)
AI Models Used: EcoImpactNet, BioHazardGPT
- ✓ Environmental release modeling
- ✓ Dual-use potential scoring
- ✓ Ecosystem disruption analysis
- ✓ Horizontal gene transfer probability
- ✓ Result: Red flag for sequences requiring human expert review
Decision Engine: Mint or Reject
🎯 Risk Score Decision Matrix
The system calculates a composite risk score (0-100):
- 0-30 (Low Risk): Automatic BioNFT minting ✓
- 31-70 (Medium Risk): Expert panel review required ⚠
- 71-100 (High Risk): Rejection, flagged for regulators ✗
The Critical Difference: Blockchain Logging
🔗 Immutable Audit Trail
"All assessments logged on blockchain for regulatory audit trail"
Every decision—approved or rejected—is permanently recorded. This means:
- ✓ Regulators can audit any genome's safety assessment retroactively
- ✓ Researchers can prove they followed protocols
- ✓ Courts can establish chain of custody in biosafety violations
- ✓ The public can verify compliance without accessing sensitive sequences
Real-World Impact: Lessons from the Phage Paper
Let's return to the 2025 bacteriophage study. The researchers created 16 viable phages with desirable properties. Now imagine this workflow with BioNFTs:
Without BioNFTs (Current State)
- 16 phages documented in a paper (after synthesis)
- Safety assessments described narratively
- No way to verify screening was actually performed
- Future researchers must trust the publication
- If something goes wrong, no audit trail exists
With BioNFTs (GenoBank System)
- ✅ Each phage gets a unique NFT before synthesis
- ✅ All 16 safety assessments cryptographically timestamped
- ✅ Risk scores (e.g., "Phage-7: 23/100, approved") permanently on-chain
- ✅ Future researchers can independently verify screening
- ✅ If misused, complete provenance available for investigation
Case Study: The Resistance-Breaking Cocktail
💊 Phage Therapy Meets Blockchain
The researchers created a phage cocktail that rapidly overcame antibiotic resistance. This is powerful medicine—but also a potential dual-use technology. With BioNFTs:
- Creation: Each phage in the cocktail receives a BioNFT with risk scores
- Distribution: Only institutions with verified Biosample Permission Tokens can access sequences
- Usage Tracking: Every lab that synthesizes the phages logs it on-chain
- Revocation: If new risks emerge, permissions can be revoked cryptographically
- Accountability: Complete trail from AI model → synthesis → deployment
The Future of Biosafety: Privacy Through Ownership
Beyond Surveillance: Empowering Researchers
🔐 Cryptographic Proof, Not Centralized Control
Critics might fear that blockchain-based biosafety creates an Orwellian surveillance system. But BioNFTs do the opposite—they give researchers cryptographic proof of compliance without centralized control.
Consider this scenario:
- A researcher designs a novel phage using Evo 2
- They run it through our multi-layer assessment
- It scores 18/100 (low risk)
- They receive a BioNFT certificate proving the assessment
- When they publish, reviewers can verify the safety screening independently
- No central authority needs to "approve" the work—the blockchain proof stands alone
Aligning Incentives: Responsible Innovation
BioNFTs create positive incentives across the ecosystem:
📰 Journals
Can require BioNFT verification for synthetic biology papers
💰 Funding Agencies
Can prioritize grants with transparent safety records
🧪 Synthesis Companies
Can refuse to synthesize sequences without valid BioNFTs
🏛️ Institutions
Can demonstrate due diligence to regulators and the public
Integration with Story Protocol: IP Protection Meets Biosafety
🎭 Story Protocol Integration
GenoBank's integration with Story Protocol adds another layer:
- Researchers can mint IP for AI-generated genomes
- License tokens enforce biosafety compliance as a usage term
- Commercial applications require valid BioNFT + permission token
- Revenue sharing can fund ongoing safety monitoring
The Technical Implementation
🛠️ Technical Stack
Our system uses established blockchain standards:
- ERC-721 (BioNFTs): Unique identity for each genome
- Biosample Permission Tokens: Granular access control
- IPFS/Arweave: Decentralized sequence storage
- Zero-Knowledge Proofs: Verify assessments without exposing sequences
- Multi-Chain Support: Avalanche (speed), Ethereum (compatibility), Story (IP rights)
Call to Action: Building the Infrastructure Today
AI-generated genomes are here. The 2025 phage paper is just the beginning. Evo 2, AlphaFold 3, and future models will accelerate synthetic biology exponentially.
⚖️ We Have a Choice
- React: Wait for a catastrophic failure, then impose restrictive regulations
- Prepare: Build transparent, decentralized biosafety infrastructure now
GenoBank chose to prepare.
BioNFTs are live today, providing:
- ✓ Immutable audit trails for AI-generated genomes
- ✓ Multi-layer AI safety assessments
- ✓ Cryptographic proof of compliance
- ✓ Permissioned access control
- ✓ Integration with IP protection (Story Protocol)
- ✓ Open standards anyone can implement
Join the Movement
We're calling on:
🤖 AI Researchers
Integrate BioNFT verification into genome language models
🧬 Synthetic Biology Labs
Adopt blockchain-based safety documentation
⚖️ Regulators
Recognize BioNFTs as proof of due diligence
📚 Journals
Require transparent safety assessments for synthetic biology papers
🌍 The Public
Demand accountability in an age of AI-designed life
🧬 Key Principle: Privacy Through Ownership
Privacy is not about hiding data or making it fuzzy. Privacy is about giving researchers complete control over their authentic, high-quality data, with full transparency about its use and fair compensation for its value.
The future of synthetic biology requires traceability without surveillance, accountability without bureaucracy, and innovation without recklessness.
BioNFTs make this possible. The technology exists. The standards are open. The choice is ours.
References & Further Reading
- Samuel H. King et al. (2025). "Generative design of novel bacteriophages with genome language models." bioRxiv. doi: 10.1101/2025.09.12.675911
- Entriken, William; Uribe, Daniel. "Biosample Permission Token with Non-Fungible Tokens." GenoBank.io Technical Documentation, 2020.
- GenoBank.io (2025). "BioFS Deep Dive: PIL-Licensed Genomic Data Downloads." GenoBank.io Blog.
- Story Protocol Documentation
- US Patents: US-11984203-B1, US-11915808-B1 (BioNFTs™ Technology)
About GenoBank.io
GenoBank.io has pioneered blockchain-based genomic data ownership since 2018, with 2 granted US patents for BioNFTs™ technology (US-11984203-B1, US-11915808-B1). We provide the infrastructure for AI-era biosafety, enabling transparent, verifiable, and accountable synthetic biology.
Contact: [email protected] | Learn more: genobank.io
For technical implementation details, see our Biosample Permission Token whitepaper and GitHub repositories.
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