Toxometris.ai

Accelerate your drug design process with cutting-edge in silico toxicity assessment

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Available for

Version

1.3.0

Resources

Integration Documentation Management

Predict chemical toxicity early with AI-powered insights

The Toxometris.ai add-on enables in silico toxicity assessment directly within the SciSure platform. Using advanced AI-based models, it helps researchers evaluate the potential toxicity of chemicals and substances early in the R&D process before committing to costly and time-consuming wet-lab testing.

By identifying risk sooner, teams can prioritize safer, more promising compounds and make more informed development decisions.

Key Features & Benefits

Early toxicity screening
Predict toxicological risks at an early stage of drug discovery or chemical development.
Resource-efficient decision-making
Focus experimental efforts on compounds with the highest potential, reducing unnecessary testing.
AI-powered prediction models
Leverage validated machine-learning models for reliable in silico toxicity assessments.
Fast, accessible results
View prediction outcomes in a clear dashboard and download detailed PDF reports within minutes.

Supported Prediction Endpoints

Toxometris.ai currently supports predictions for:

Genotoxicity (AMES)
Genotoxicity (Micronucleus, in vitro)
Genotoxicity (Micronucleus, in vivo)
Aqueous solubility
hERG cardiotoxicity
Rodent carcinogenicity
Hepatotoxicity

The list of endpoints is continuously expanding and will increasingly cover ADME and toxicity-related properties.

Ideal For

Drug discovery and early-stage R&D teams
Pharma and biotech companies screening chemical libraries
Research groups looking to reduce wet-lab testing costs
Scientists prioritizing compound safety earlier in development

Seamless Integration with SciSure

With the Toxometris.ai add-on installed, researchers can assess the physicochemical, biological, and toxicological properties of compounds in just a few clicks—bringing predictive toxicology directly into their digital lab workflow.

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