ProfhEX

AI-based platform for small molecules liability profiling

Drug off-target interactions are one of the main reasons of candidate failure in the drug discovery process. Anticipating potential drug’s adverse effects in the early stages is a mandatory step to minimize risks of candidate failure.

ProfhEX is an AI-driven suite of 46 OECD-compliant machine learning models able to profile small molecules on 7 liability groups relevant for drug discovery campaigns, including: cardiotoxicity, neurotoxicity, gastrointestinal toxicity, endocrine disruption, renal, pulmonary, and immune system toxicities.

To estimate a liability profile, upload molecule(s) in SMILES format: ProfhEX will provide downloadable target-inhibition activities together with a summary report. Available models can be browsed in the Models section.

AI

Deep Learning

Analysis

Models Selection

Submit Your File

To run ProfhEX, either paste a SMILES string (CCN(CC)CCOC(=O)C(CC1CCCO1)CC2=CC=CC3=CC=CC)
OR
upload a .csv,.txt,.smi file containing one SMILES per row ( for a template)

Once calculations are completed, results can be analyzed and downloaded.

Please note that the maximum number of processed molecules caps at 100 ^(*) (exceeding rows are ignored).

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Available models can be selected in the drop-down list or browsed by liability group in the treemap visualization. The report displays key model quality information:

Training set size and pK property distribution
External validation performance
Internal validation evaluation

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ProfhEX

AI-based platform for small molecules liability profiling

AI

Deep Learning

Analysis

Models Selection

Submit Your File

Contacts

Email

Send us an email

Web Site

www.exscalate.eu