Sentinel™ safeguards
Our Sentinel™ safeguard screens molecular outputs inside scientific AI workflows and identifies latent risk in novel structures.
Identify risk before it becomes a threat.
BioSymetrics combines biological risk intelligence, machine learning, toxicology data, and validation in living systems to assess chemical threats and support countermeasure development.
Bring the risk signal and the biological response together.
As AI-enabled molecular design accelerates, fragmented detection and testing workflows can struggle to keep pace with emerging threats. Chemical, toxicological, and biological signals also need context before they can guide a response.
We connect computational analysis with experimental evidence so partners can identify risk, understand biological effects, and decide what to assess next.
Move from molecular signal to biological evidence.
We integrate chemical, toxicological, biological, and phenotypic data, then use machine learning to identify risk and predict mechanisms. Partners can screen candidate structures or submitted compounds before moving priority questions into automated zebrafish assays.
Our computer vision workflow measures behaviour, physiology, and other phenotypic responses in living systems. The result is connected biological evidence for threat assessment, mechanism analysis, and countermeasure prioritization.
Build biosecurity into prevention, assessment, and response.
Threat assessment
We combine AI-based mechanism prediction with zebrafish phenotypic screening to classify neuroactive and neurotoxic compounds and prioritize follow-up.
Pathfinder consortium
As part of the Pathfinder consortium, we bring together academic, government, defence, and biotechnology resources to move threat identification toward countermeasure development and preparedness.
Put biosecurity controls inside scientific AI.
Sentinel™ is an embedded transformer-based safeguard for scientific foundation models and large language models. It screens molecular outputs in real time and uses molecular representations alongside biological, toxicological, and phenotypic data to identify potentially hazardous compounds.
This approach gives AI developers, life sciences platforms, and government partners a way to build biosecurity controls into high-risk scientific systems rather than relying only on keyword filters.
See how predicted risk appears in biology.
Our chemical threat workflow identifies compounds associated with neurotoxic mechanisms, then uses zebrafish behaviour and physiology to observe their effects in living systems.
The combination of molecular screening, mechanism-of-action prediction, and high-content phenotypic readouts helps partners prioritize compounds for additional assessment and countermeasure work at scale.
Coordinate the response around the next decision.
Pathfinder is a national academic and industry consortium that BioSymetrics participates in. It brings together academic toxicology, military research, federal preparedness, and AI-enabled biotechnology resources in a shared countermeasure development workflow.
The consortium connects early efficacy work with zebrafish validation, animal studies, safety testing, government procurement, and preparedness planning. It gives partners a route from threat characterization to candidate selection and stockpiling decisions.
Looking for a clearer way to assess biological risk?
We work with government, defence, AI, life-sciences, pharmaceutical, biotechnology, and research partners on molecular safety, threat assessment, biosurveillance, and countermeasure questions.
Partner with us