Abstract
Background:
Recent advances in synthetic biology have raised new challenges in biosecurity and biorisk management (BRM), particularly in high-containment laboratories and other critical research settings.
Objective:
This article explores the use of artificial intelligence (AI) agents to automate BRM tasks, thus enhancing both safety and efficiency in these sensitive environments.
Methods:
We propose an integrated system combining machine learning models for risk assessment with embodied AI agents capable of executing physical containment and other tasks. Specifically, AI algorithms can be employed for predictive risk modeling, anomaly detection, and real-time decision-making, while embodied AI agents can serve to carry out operations that would otherwise expose humans to hazardous biological agents and other hazards.
Results:
Combined, these two technologies are known as a specialized AI agent for BRM. This dual approach aims to reduce the cognitive and physical burdens on human personnel, minimize human error, and ensure consistent adherence to BRM protocols. This combination optimizes laboratory workflows and introduces a robust layer of redundancy in managing biological risks. Conclusions: Here we present a novel and promising step forward in augmenting the safety of high-containment laboratories through implementation of specialized AI agents; thus, contributing to more resilient BRM frameworks.
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