Introduction

Generative AI in synthetic biology uses AI models to design novel DNA, RNA and protein sequences. Recent AI-designed bacteriophages demonstrate its potential to generate functional biological entities.

Opportunities

• AMR: Design customised phages against drug-resistant bacteria.
• Drug & vaccine discovery: Faster development of therapeutic proteins and vaccines.
• Gene therapy: Design targeted viral vectors for CRISPR-based therapies.
• Precision oncology: Development of viruses targeting cancer cells.

Concerns

• Dual-use risk: Same technology could potentially facilitate harmful biological-agent design.
• Biosecurity gaps: Novel AI-generated sequences may bypass conventional pathogen-based DNA screening.
• Ecological uncertainty: Unintended mutations, ecosystem disruption or zoonotic effects.
• Acceleration risk: AI can rapidly expand biological design possibilities and shorten experimentation cycles.
• Regulatory ambiguity: Existing laws and intellectual-property frameworks may not adequately cover AI-generated biological designs.

Way Forward

• Function-based DNA synthesis screening and KYC norms.
• Strengthen biosafety and biosecurity across laboratories, databases and computing infrastructure.
• Update the Biological Weapons Convention (BWC) for AI-enabled biological threats.
• Promote red-teaming and responsible AI access.
• Strengthen international cooperation and risk-based governance.

Conclusion

India should pursue “innovation with safeguards”, balancing AI leadership in biotechnology with robust biosafety, biosecurity and ethical oversight.