Definition of variables required for comprehensive description of drug dosage and clinical pharmacokinetics.
Eur J Clin Pharmacol
; 73(5): 633-641, 2017 May.
Article
em En
| MEDLINE
| ID: mdl-28197684
ABSTRACT
PURPOSE:
Electronic clinical decision support systems (CDSS) require drug information that can be processed by computers. The goal of this project was to determine and evaluate a compilation of variables that comprehensively capture the information contained in the summary of product characteristic (SmPC) and unequivocally describe the drug, its dosage options, and clinical pharmacokinetics.METHODS:
An expert panel defined and structured a set of variables and drafted a guideline to extract and enter information on dosage and clinical pharmacokinetics from textual SmPCs as published by the European Medicines Agency (EMA). The set of variables was iteratively revised and evaluated by data extraction and variable allocation of roughly 7% of all centrally approved drugs.RESULTS:
The information contained in the SmPC was allocated to three information clusters consisting of 260 variables. The cluster "drug characterization" specifies the nature of the drug. The cluster "dosage" provides information on approved drug dosages and defines corresponding specific conditions. The cluster "clinical pharmacokinetics" includes pharmacokinetic parameters of relevance for dosing in clinical practice. A first evaluation demonstrated that, despite the complexity of the current free text SmPCs, dosage and pharmacokinetic information can be reliably extracted from the SmPCs and comprehensively described by a limited set of variables.CONCLUSION:
By proposing a compilation of variables well describing drug dosage and clinical pharmacokinetics, the project represents a step forward towards the development of a comprehensive database system serving as information source for sophisticated CDSS.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Farmacocinética
/
Sistemas de Registro de Ordens Médicas
Tipo de estudo:
Guideline
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article