DNA Synthesis Screening Cannot Keep Up With AI-Designed Sequences

DNA Synthesis Screening Cannot Keep Up With AI-Designed Sequences
DNA synthesis screening AI biosecurity dual use genomic sequences
Screen
DNA synthesis companies now screen orders for sequences matching select agents
AI bypass
AI protein design can produce functional analogs that evade sequence-similarity screening
IBBIS
International Biosecurity and Biosafety Initiative for Science developing updated screening
Structure
structure-based screening proposed and, per later 2025 work, in early deployment

DNA synthesis companies serve as a critical chokepoint in the biosecurity ecosystem. The argument is straightforward: to create a biological threat agent, an actor needs to obtain its genetic sequence in physical DNA form. DNA synthesis companies, which produce custom DNA sequences on demand for legitimate research, represent the last physical control point before that sequence enters the world. Screening orders against databases of dangerous sequences before synthesizing them should prevent acquisition of threat agents through commercial channels.

How Current Screening Works

The International Gene Synthesis Consortium, representing the major commercial DNA synthesis providers, has maintained a voluntary screening commitment since 2009. The screening approach uses sequence alignment algorithms to compare ordered sequences against databases of select agents and toxins listed under biosafety regulations. Orders matching dangerous sequences above a threshold similarity are flagged for manual review and potential rejection.

The AI Bypass Problem

A 2024 arXiv preprint (arXiv 2406.08027) documented a specific vulnerability. AI protein design tools including ESM3 and RFdiffusion can generate novel sequences with similar three-dimensional structure and function to dangerous proteins but with low sequence similarity to any known protein in screening databases. A viral toxin redesigned by AI to be functionally equivalent but sequentially dissimilar could pass sequence-based screening while retaining biological activity, at least on the computational measures available at the time. The IBBIS proposal for functional screening uses AI models that predict protein function from sequence to flag sequences likely to produce dangerous functional outputs, regardless of their similarity to known threat agents.

What Policy Has Done

The September 2023 Biden Executive Order on AI specifically addressed AI-enabled biosecurity risks and required NIST, NIAID, and other agencies to develop screening requirements for AI-designed genomic sequences. The IBBIS consortium published a technical framework for next-generation screening in 2024. As of early 2026, large commercial synthesis providers have begun piloting AI-augmented functional screening, but the transition from sequence-similarity to function-based screening is not yet complete across the industry.

Update: The 2025 Multistakeholder Response

A multi-institutional research collaboration, including Microsoft and the International Biosecurity and Biosafety Initiative for Science, published a follow-up study in Science in October 2025 (Wittmann et al., “Strengthening nucleic acid biosecurity screening against generative protein design tools,” Science 390, 82-87) that moves this story from vulnerability discovery toward a defensive response. The 2025 work proposes and evaluates function-based screening methods designed specifically to catch AI-generated functional analogs that sequence-similarity screening misses, the same gap the 2024 preprint identified. This does not mean the vulnerability is fully closed: function-based screening is harder to standardize than sequence matching, adoption across the synthesis industry is uneven, and the residual risk from providers that have not yet deployed the newer methods remains real. The accurate framing as of this update is vulnerability identified, defense proposed and being piloted, full industry-wide closure not yet confirmed, rather than an unaddressed open door.

Related coverage: How Protein Language Models Learned to Design Dangerous Proteins | LLMs Give Novice Biologists 4x Uplift on Dangerous Tasks | What ASL-3 Actually Means: Anthropic’s Biorisk Threshold Explained

Primary sources: arXiv preprint on AI bypass of DNA synthesis screening, arXiv 2406.08027 (2024); Wittmann BJ, Alexanian T, Bartling C et al., Science 390, 82-87 (2025), doi:10.1126/science.adu8578. Updated 2026-08-18 to add the 2025 multistakeholder defensive-screening response and to correct the earlier misattribution of the 2024 preprint to Johns Hopkins Center for Health Security alone.

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