Automating Biosecurity Screening with ORCID and TAXID Mapping

Automating Biosecurity Screening with ORCID and TAXID Mapping

Summary: DNA synthesis faces slow, error-prone biosecurity screening due to manual researcher and organism validation. Automating this by linking ORCID publications to standardized organism IDs (TAXIDs) would streamline approvals, maintain security, and accelerate research without biosecurity gaps.

DNA synthesis companies currently face a cumbersome and error-prone process when screening orders for sequences of concern, such as pathogens. Manual verification of researchers' credentials and their history of working with specific organisms slows down legitimate research while creating biosecurity gaps. One way to address this could be by automating the link between researchers' publication histories and the organisms they've studied.

How the Tool Would Work

The core idea involves mapping researchers' ORCID identifiers to taxonomic IDs (TAXIDs) of organisms mentioned in their publications. Here's how it could function:

  • Input a researcher's ORCID ID to retrieve their publication history via ORCID's API
  • Parse publications for organism mentions and map these to standardized TAXIDs using databases like NCBI Taxonomy
  • Output a list of organisms the researcher has worked with, potentially with confidence scores based on publication frequency

More advanced versions might analyze co-author networks or calculate risk scores based on the researcher's history with high-risk pathogens.

Potential Benefits and Implementation

This approach could benefit multiple stakeholders:

  • DNA synthesis companies would reduce manual screening work while improving compliance
  • Legitimate researchers would experience fewer order processing delays
  • Biosecurity organizations would gain a standardized screening tool

For implementation, one could start with a basic web tool or API that performs the core ORCID-to-TAXID mapping, then gradually add features like collaborator network analysis. Initial testing could verify whether publication metadata contains sufficient organism information and whether researchers consistently use standard organism names.

Addressing Potential Challenges

Some challenges might include ambiguous organism names in publications, which could potentially be resolved using natural language processing techniques. Privacy concerns could be addressed through transparent data usage policies and opt-out options. The system would need regular updates to maintain accurate TAXID mappings from reference databases.

This approach differs from existing solutions like ORCID profiles or NCBI Taxonomy by specifically bridging the gap between researcher identities and their organism-specific research history, creating a novel tool for biosecurity screening.

Source of Idea:
Skills Needed to Execute This Idea:
API IntegrationTaxonomic ClassificationNatural Language ProcessingData Privacy ComplianceBiosecurity StandardsAlgorithm DesignDatabase ManagementWeb DevelopmentPublication AnalysisRisk Assessment
Resources Needed to Execute This Idea:
ORCID API AccessNCBI Taxonomy DatabaseNatural Language Processing Software
Categories:BiosecurityDNA SynthesisResearch ComplianceTaxonomic IdentificationPublication AnalysisAutomated Screening

Hours To Execute (basic)

500 hours to execute minimal version ()

Hours to Execute (full)

250 hours to execute full idea ()

Estd No of Collaborators

1-10 Collaborators ()

Financial Potential

$1M–10M Potential ()

Impact Breadth

Affects 1K-100K people ()

Impact Depth

Significant Impact ()

Impact Positivity

Probably Helpful ()

Impact Duration

Impacts Lasts 3-10 Years ()

Uniqueness

Moderately Unique ()

Implementability

Moderately Difficult to Implement ()

Plausibility

Logically Sound ()

Replicability

Easy to Replicate ()

Market Timing

Good Timing ()

Project Type

Digital Product

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