2025/07/23 by Charles Tapley Hoyt, Hoyt, Charles Tapley
Business, Management and Accounting · Computer Science · Decision Sciences · #Big Data and Business Intelligence #Data Mining Algorithms and Applications #FOS: Biological sciences #Quantitative Methods (q-bio.QM) #Scientific Computing and Data Management
paper · pdf · doi:10.48550/arxiv.2507.17783
openalex publication_date 2025/07/23 · openalex created_date 2025/10/16 · openalex updated_date 2026/07/28
Many modern cheminformatics workflows derive datasets from ChEMBL, but few of these datasets are published with accompanying code for their generation. Consequently, their methodologies (e.g., selection, filtering, aggregation) are opaque, reproduction is difficult, and interpretation of results therefore lacks important context. Further, such static datasets quickly become out-of-date. For example, the current version of ChEMBL is v35 (as of December 2024), but ExCAPE-DB uses v20, Deep Confidence uses v23, the consensus dataset from Isigkeit et al._ (2022) uses v28, and Papyrus uses v30. Therefore, there is a need for tools that provide reproducible bulk access to the latest (or a given) version of ChEMBL in order to enable researchers to make their derived datasets more transparent, updatable, and trustworthy. This article introduces `chembl-downloader`, a Python package for the reproducible acquisition, access, and manipulation of ChEMBL data through its FTP server. It can be downloaded under the MIT license from https://github.com/cthoyt/chembl-downloader and installed from PyPI with `pip install chembl-downloader.`