PK-DB: pharmacokinetics database for individualized and stratified computational modeling.


A multitude of pharmacokinetics studies have been published. However, due to the lack of an open database, pharmacokinetics data, as well as the corresponding meta-information, have been difficult to access. We present PK-DB (, an open database for pharmacokinetics information from clinical trials. PK-DB provides curated information on (i) characteristics of studied patient cohorts and subjects (e.g. age, bodyweight, smoking status, genetic variants); (ii) applied interventions (e.g. dosing, substance, route of application); (iii) pharmacokinetic parameters (e.g. clearance, half-life, area under the curve) and (iv) measured pharmacokinetic time-courses. Key features are the representation of experimental errors, the normalization of measurement units, annotation of information to biological ontologies, calculation of pharmacokinetic parameters from concentration-time profiles, a workflow for collaborative data curation, strong validation rules on the data, computational access via a REST API as well as human access via a web interface. PK-DB enables meta-analysis based on data from multiple studies and data integration with computational models. A special focus lies on meta-data relevant for individualized and stratified computational modeling with methods like physiologically based pharmacokinetic (PBPK), pharmacokinetic/pharmacodynamic (PK/PD), or population pharmacokinetic (pop PK) modeling.


PubMed ID: 33151297

Projects: Multi-Scale Models for Personalized Liver Function Tests (LiSyM-MM-PLF)

Publication type: Journal

Journal: Nucleic Acids Res

Citation: Nucleic Acids Res. 2020 Nov 5. pii: 5957165. doi: 10.1093/nar/gkaa990.

Date Published: 5th Nov 2020

Registered Mode: by PubMed ID

Authors: J. Grzegorzewski, J. Brandhorst, K. Green, D. Eleftheriadou, Y. Duport, F. Barthorscht, A. Koller, D. Y. J. Ke, S. De Angelis, M. Konig

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Created: 18th Dec 2020 at 18:53

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