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Biosecurity for Synthetic Nucleic Acid Sequences


Balancing the growth of the bioeconomy with the inherent risks associated with the potential misuse of artificial intelligence (AI) related to nucleic acid synthesis will require comprehensive and sustainable nucleic acid synthesis screening practices and risk mitigation strategies including standards, databases, tools and capacities to identify, track and defend against evolving sequences of concern (SOCs).  NIST is working with key stakeholders to develop standards and best practices related to nucleic acid synthesis and screening, including underpinning bioinformatics, machine learning (ML), predictive AI, and cybersecurity capabilities.


Genetic codes
Credit: Sergei Drozd/Shutterstock

Emerging biotechnology, enabled by the ability to genetically engineer biological systems similar to the way we write software and program computers, can provide solutions to many pressing societal needs related to health, food security, supply chain resilience, and job growth for economic and national security.

Synthetic DNA (and RNA) technology is fundamental to U.S. biotechnology and biomanufacturing innovation.  However, as with other transformative technologies, synthetic DNA can be used for good, but also unintentionally or deliberately, to engineer biological systems that can cause harm.  With increased convergence of biotechnology and AI, the possibility also exists that AI could be used to design entirely novel DNA sequences, undetectable by current sequence screening tools, that may increase harm.

Under the recent AI Executive Order, NIST was assigned the responsibility of engaging industry and relevant stakeholders to initiate an effort to develop and refine a systematic sequence screening approach towards the development of standards and conformity assessment schemes for commercial synthetic DNA manufacturers.  In response, NIST is enabling a preliminary assessment by the stakeholder community through a grant awarded to the Engineering Biology Research Consortium (EBRC) aimed to better coordinate existing efforts towards the development of more robust tools, capabilities, and best practices.  NIST will also leverage this program to support emerging measurement needs and challenges associated with safety and security in the synthesis of nucleic acids.

Selected Programs and Accomplishments

International Documentary Standards and Implementation Guides

NIST will expand its work within Standards Development Organizations including the International Organization for Standardization (ISO) to harmonize global nucleic acid sequence screening practices.  Documentary Standards efforts include a two-part ISO standard on Nucleic Acid Synthesis: 


NIST is working with the EBRC and other relevant stakeholders to develop a framework for the development of screening and safety tools, standards, and best practices for possible use by synthetic nucleic acid sequence providers.  These include: 

  • Specifications for effective nucleic acid synthesis procurement screening
  • Best practices, including security and access controls, for managing sequence-of-concern databases to support such screening
  • Technical implementation guides for effective screening
  • Conformity assessment best practices and mechanisms
SOC Databases and Screening Tools

NIST and EBRC are engaging with industry to jointly develop the necessary features of SOC databases and screening tools, including:

  • Database access and control
  • Standardized metadata and proper annotations
  • Scalability and flexibility
  • Maintenance of entries

NIST and EBRC will hold a series of workshops to develop high-level requirements to be captured in a white paper serving as current industry best practice, in support of meeting global standards and eventual conformity assessment.  Concurrently, NIST will leverage its existing expertise in biosurveillance and microbial genomics to develop test datasets and benchmarking tools to assess and maintain the performance of nucleic acid screening tools.

Emerging Predictive Capabilities

To safeguard from emerging threats from sophisticated synthetic biology tools, NIST will leverage its predictive Engineering Biology program to further advance AI capabilities to enable the prediction of sequence to function.  Specifically, NIST will develop standard methods for the collection of large, high-quality datasets for training and testing of AI tools.  NIST will continue to develop interpretable AI tools such as LANTERN to understand the physics behind sequence-to-function modulation.

To reduce emerging threats, NIST must develop new capabilities to predict sequences for host–pathogen interactions.  Based on stakeholder input and for well-defined host–pathogen interactions, NIST will generate large protein–protein datasets will be generated using non-pathogenic surrogate systems as proxies.  These data will support developing AI tools for the prediction of sequent mutation effects on host-dependent pathogenicity.

Cybersecurity needs of SOC Dataset

Leveraging the NIST Cybersecurity and Privacy of Genomic Data effort and the testbeds underdevelopment, NIST will test and validate secure data transfer of sequence screening.  The transmission process will be documented and areas of cybersecurity requirements against the draft Genomic CSF will be highlighted.

Created March 25, 2024, Updated April 11, 2024