PK-DB
PK-DB aggregates pharmacokinetic (PK) data from clinical trials and pre-clinical studies to centralize concentration-time profiles, cohort and intervention metadata, and derived PK parameters for quantitative analysis.
Key Features:
- Comprehensive Data Curation: Curates cohort and subject characteristics (age, body weight, smoking status), intervention details (dosing regimens, substances, routes of application), measured concentration-time courses, and PK parameters such as clearance, half-life, and area under the curve.
- Experimental Error Representation: Represents experimental errors associated with measurements and reported parameters.
- Normalization and Annotation: Normalizes measurement units across datasets and annotates entities using biological ontologies.
- Pharmacokinetic Parameter Calculation: Calculates pharmacokinetic parameters directly from concentration-time profiles.
- Collaborative Data Curation Workflow: Implements a structured workflow to support collaborative curation and high-quality data entry.
- Robust Validation Rules: Enforces validation rules to maintain data integrity and accuracy.
- Computational Access: Provides programmatic access via a REST API for computational retrieval and integration.
Scientific Applications:
- Meta-analysis: Enables meta-analyses across multiple studies by consolidating comparable PK measurements and metadata.
- Integration with Computational Models: Facilitates integration with physiologically based pharmacokinetic (PBPK), pharmacokinetic/pharmacodynamic (PK/PD), and population pharmacokinetic (pop PK) modeling workflows.
- Individualized and Stratified Modeling: Supports individualized and stratified computational modeling by supplying patient-level metadata relevant to personalized analyses.
Methodology:
Normalization of measurement units, ontology-based annotation, calculation of PK parameters from concentration-time profiles, representation of experimental errors, implementation of validation rules, and provision of a REST API for programmatic access.
Topics
Details
- Programming Languages:
- Python
- Added:
- 11/14/2019
- Last Updated:
- 1/10/2021
Operations
Publications
Grzegorzewski J, Brandhorst J, Eleftheriadou D, Green K, König M. PK-DB: PharmacoKinetics DataBase for Individualized and Stratified Computational Modeling. Unknown Journal. 2019. doi:10.1101/760884.
DOI: 10.1101/760884
Links
Repository
https://github.com/matthiaskoenig/pkdb