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ADAPT: a programme for the advanced detection of AI-enabled pathogenic threats.

Hanna Palya1,2, Cassidy Nelson2

  • 1Institute for Global Pandemic Planning, University of Warwick, Coventry, United Kingdom.

Frontiers in Bioengineering and Biotechnology
|June 25, 2026
PubMed
Summary

New AI-enabled biological threats require advanced screening. The proposed Advanced Detection of AI-enabled Pathogenic Threats (ADAPT) program will develop functional definitions and tools to detect novel, AI-generated pathogens beyond sequence similarity.

Keywords:
Biodefense policybiological AI modelsdual-use research of concern (DURC)function-based screeninggene ontology (GO)protein language modelssequences of concern (SOC)synthetic nucleic acid screening

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Area of Science:

  • Biosecurity
  • Synthetic Biology
  • Bioinformatics

Background:

  • Artificial intelligence (AI) advances biological engineering, creating novel biosecurity threats.
  • Existing synthetic nucleic acid screening methods are insufficient for AI-generated threats.
  • The Functional Genomic and Computational Assessment of Threats (FunGCAT) program improved sequence screening but left critical gaps.

Purpose of the Study:

  • To propose the Advanced Detection of AI-enabled Pathogenic Threats (ADAPT) program as a successor to FunGCAT.
  • To address limitations in defining and detecting AI-driven biological threats.
  • To develop next-generation screening tools for biosecurity.

Main Methods:

  • Phase I: Develop a function-based definition for sequences of concern and create benchmark datasets.
  • Phase II: Develop and validate screening tools for known threats, AI-functional homologues, and novel AI-designed threats.
  • Integrate continuous governance for regulatory translation and secure infrastructure.

Main Results:

  • The study outlines a two-phase program (ADAPT) to bridge current detection gaps.
  • It proposes a shift from sequence similarity to function-based threat detection.
  • It aims to create tools capable of identifying AI-generated biological threats.

Conclusions:

  • ADAPT is crucial for adapting biosecurity screening to the era of AI-driven biological engineering.
  • The program will enhance detection capabilities against novel and evolving biological threats.
  • It builds upon previous efforts while addressing the unique challenges posed by AI in synthetic biology.