MCP server for PBPK modeling workflows (simulation control + PK analytics).
Evidence federation MCP server for the EPA CompTox API
MCP server for Adverse Outcome Pathway (AOP) discovery, semantics, and draft authoring.
MCP server for OECD QSAR Toolbox workflows with structured outputs and PDF reports.
MCP server for ADMETlab 3.0 (washing, ADMET prediction, rendering, CSV retrieval).
OECD Test Guidelines-based toxicity prediction using machine learning. Comprehensive computational toxicology framework with pre-trained models for genotoxicity, carcinogenicity, acute toxicity, DART, and ecotoxicity endpoints.
A repo for the EWC artifical Neural network model for predicting EC3 Values For Skin Sensitization
Auditable dietary exposure screening and evidence handoffs over MCP
Jupyter notebook and tabular data files to support the publication "Combined In vitro and In silico Workflow to Deliver Robust, Transparent, and Contextually Rigorous Models of Bioactivity" (Charest et al. 2025)
4-compartment PBPK model with hepatic Michaelis-Menten metabolism and Monte Carlo uncertainty analysis (Python + R)
EPA data on 1,800 chemicals across 700+ assay endpoints
Script that associates with: ‘Comparing the Predictivity of Human Placental Gene, microRNA, and CpG Methylation Signatures in Relation to Perinatal Outcomes’, published in 2021 by Clark et al. (PMID: 34255065).
An open-source, regulatory-grade neuro-symbolic platform for molecular toxicity prediction, hERG cardiotoxicity screening, and 21 CFR Part 11 drug safety triage.
A machine learning project estimating the effect of data splitting strategies across different similarity gradients on calibration and discrimination in hERG liability predictions.
49k chemicals categorized by usage or function in 16k consumer products (e.g. shampoo, soap)
MCP server reproducing Nikitin et al. 2025 (Pharmaceutics 17, 1573): antitarget-LD50 computational toxicology, inverse docking, hERG/safety panel. Turns every figure/statistic of the paper into MCP tools over the public ld50-antitargets dataset.
Computational toxicology analysis and machine-learning prediction of Ames mutagenicity using molecular descriptors.
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