CRC-Screen: Certified DNA-Synthesis Hazard Screening Under Taxonomic Shift

TL;DR

This paper introduces CRC-Screen, a hazard screening method for DNA synthesis that remains reliable under taxonomic shifts by using calibrated signals and conformal risk control.

Contribution

It presents a novel hazard screening approach that certifies low false-negative rates despite taxonomic gaps, leveraging multiple signals and conformal risk control.

Findings

Achieves 0% test miss rate on most folds at α=0.05

Certifies a maximum 1.77% false-negative rate with finite-sample guarantees

Requires larger calibration sets for more stringent thresholds

Abstract

DNA-synthesis providers screen incoming orders by searching the requested sequence against curated hazard lists. We show that this baseline collapses to a 100% false-flag rate when the hazardous sequence comes from a taxonomic family absent from the reference set: under Conformal Risk Control's certified miss-rate constraint, a low-discrimination signal forces the threshold below the entire test-benign mass. We compose three signals derived from a synthesis order's public annotation: $k$-mer Jaccard similarity to known toxins, the trimmed-mean score of a five-LLM judge panel, and cosine similarity to clustered embedding centroids. Fused under a monotone logistic aggregator and calibrated by Conformal Risk Control, the resulting screener certifies $\mathbb{E}[\mathrm{FNR}] \le \alpha$. Across ten leave-one-taxonomic-family-out folds at $\alpha=0.05$ on UniProt KW-0800 reviewed toxins, the calibrated screener achieves 0% test miss rate on every fold and 0% test false-flag rate on nine of ten folds. The bound's finite-sample slack $1/(n_{\mathrm{cal}}+1)$ caps the certifiable miss rate at 1.77% on our 200-hazard subsample; reaching procurement-grade $\alpha=10^{-3}$ requires an $18\times$ larger calibration set, which the full reviewed UniProt KW-0800 corpus is large enough to deliver. The binding constraint on certifiable DNA-synthesis screening is calibration data, not algorithms. Code: https://github.com/najmulhasan-code/crc-screen