Official Python client for accessing ChEMBL API

Access to Biological Web Services from Python.

Automatic extraction of interacting compound-target pairs from ChEMBL.

Structured Multi-task Learning for Molecular Property Prediction, AISTATS'22 (https://proceedings.mlr.press/v151/liu22e.html)

Fetch pharmacological knowledge on chemical compounds and squeeze it into semantic triples. For analysis of chemical screens and training and evaluation of algorithms.

AI Agent wrappers for Life Sciences APIs (Open Targets, ChEMBL, UniProt). Accelerating drug discovery with Model Context Protocol (MCP) and FastMCP.

Machine learning project to evaluate machine learning approaches in drug discovery.

Module of the DrugDesign project responsible for loading and pre-processing data from ChEMBL and PubChem, necessary for further modeling and analysis in drug development

A Python package to process & model ChEMBL data.

Prescribing genes, not just drugs. ETL + dashboard pipeline that cross-references Open Targets, ChEMBL and UniProt to rank therapeutic targets by disease.

Code to retrieve drugs against a desired target using the ChEMBL database API

Scientific data enrichment tool for Open WebUI - Chemistry and materials science integration with PubChem, ChEMBL, Materials Project, and RDKit

Drug discovery data platform with curated catalogs, API ingestion, smart caching, and incremental parquet materialization.

A reproducible pipeline for extracting, harmonizing, and merging large-scale drug–disease associations from major public biomedical resources including AACT (ClinicalTrials.gov), CTD, ChEMBL, DrugCentral, OpenTargets, and SIDER.

Auditable ChEMBL-derived benchmark for coumarin bioactivity with organism-aware target-family mapping, QSAR-readiness assessment, activity-landscape analysis, and reproducible release materials.

This project demonstrates how to integrate two public REST APIs (ChEMBL and UniProt) into an end‑to‑end data workflow, with caching, progress reporting, and clean, reusable code

MINDPROT: Markov Inside for Drugs and Proteins

Parkinson's disease target, compound, omics, stem-cell validation and knowledge-graph benchmark dashboard

Modular cheminformatics ML pipeline for target-specific bioactivity prediction using ChEMBL data.