ADMETlab models for evaluation of drug candidates

A series of models for the systematic ADMET evaluation of drug candidate molecules. Models include blood-brain barrier penetration; inhibition and substrate affinity for CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and pgp; F 20% and F 30% bioavailability; human intestinal absorption; Ames mutagenicity; skin sensitization; plasma protein binding; volume distribution; LD50 of acute toxicity; human hepatotoxicity; hERG blocking; clearance; half-life; Papp (caco-2 permeability); LogD distribution coefficient; and LogS solubility.

Identifiers

• EOS model ID: eos2re5
• Slug: admetlab

Characteristics

• Input: Compound
• Input Shape: Single
• Task: Classification, Regression
• Output: Experimental value
• Output Type: Float
• Output Shape: List
• Interpretation: Regression models provide a numerical result (LogS (log mol/L), LogP (distribution coefficient), Papp (Caco-2 permeability in cm/s), PPB (%)). Classifications provide the probability of activity according to ADMETlab thresholds.

References

• Publication
• Source Code
• Ersilia contributor: svolk19-stanford

Ersilia model URLs

• GitHub
• AWS S3
• DockerHub (AMD64)

Citation

If you use this model, please cite the original authors of the model and the Ersilia Model Hub.

License

This package is licensed under a GPL-3.0 license. The model contained within this package is licensed under a GPL-3.0 license.

Notice: Ersilia grants access to these models 'as is' provided by the original authors, please refer to the original code repository and/or publication if you use the model in your research.

About Us

The Ersilia Open Source Initiative is a Non Profit Organization (1192266) with the mission is to equip labs, universities and clinics in LMIC with AI/ML tools for infectious disease research.

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