dbparser
dbparser package aims to parse different public drugs databases into a single and unified format R object called dvobject (stands for drugverse object). Also, dbparser has evolved into an integration engine, allowing you to merge mechanistic data (DrugBank) with real-world phenotypic data (OnSIDES) and drug-drug interaction risks (TWOSIDES).
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Peer-reviewed publication
rOpenSci
Peer-reviewed practices
Need more than the open-source package?
dbparser at a glance
dbparser is a production-ready R package for parsing and integrating major drug knowledge sources into one analysis-friendly structure called dvobject.
Instead of working with multiple raw database formats, teams can standardize data into a single object and move directly into pharmacovigilance and translational workflows.
What dbparser solves
- •Converts complex source formats (including DrugBank XML) into tidy, explorable R tables.
- •Bridges mechanistic and phenotypic evidence by integrating DrugBank, OnSIDES, and TWOSIDES.
- •Preserves provenance and metadata so downstream analyses remain auditable.
Integration workflow
dbparser supports an end-to-end pipeline:
- 1.Parse each source database.
- 2.Merge datasets into one integrated knowledge object.
- 3.Query enriched tables for adverse events and drug-drug interaction patterns.
This workflow is especially useful for teams building explainable pharmacovigilance analyses, drug safety research pipelines, and reusable internal data products.
Why teams adopt it
- •One unified object instead of fragmented files.
- •Easier collaboration and handoff across research teams.
- •Strong open-source quality signals through active maintenance and peer-reviewed ecosystem practices.