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

• Published in: Nucleic acids research Vol. 49; no. D1; pp. D1358 - D1364
• Main Authors: Grzegorzewski, Jan, Brandhorst, Janosch, Green, Kathleen, Eleftheriadou, Dimitra, Duport, Yannick, Barthorscht, Florian, Köller, Adrian, Ke, Danny Yu Jia, De Angelis, Sara, König, Matthias
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 08.01.2021
• Subjects: Area Under Curve; Body Weight; Caffeine - pharmacokinetics; Clinical Trials as Topic; Contraceptives, Oral - administration & dosage; Database Issue; Databases, Factual; Dose-Response Relationship, Drug; Drug Administration Routes; Drug Administration Schedule; Drug Dosage Calculations; Gene Ontology; Half-Life; Humans; Models, Statistical; Molecular Sequence Annotation; Prescription Drugs - pharmacokinetics; Smoking - physiopathology
• ISSN: 0305-1048; 1362-4962; 1362-4962
• DOI: 10.1093/nar/gkaa990

Abstract 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 (https://pk-db.com), 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.