Building and evaluation of a structured representation of pharmacokinetics information presented in SPCs: from existing conceptual views of pharmacokinetics associated with natural language processing to object-oriented design.
OBJECTIVE
Develop a detailed representation of pharmacokinetics (PK), derived from the information in Summaries of Product Characteristics (SPCs), for use in computerized systems to help practitioners in pharmaco-therapeutic reasoning.


METHODS
Available knowledge about PK was studied to identify main PK concepts and organize them in a preliminary generic model. The information from 1950 PK SPC-texts in the French language was studied using a morpho-syntactic analyzer. It produced a list of candidate terms (CTs) from which those describing main PK concepts were selected. The contexts in which they occurred were explored to discover co-occurring CTs. The regrouping according to CT semantic types led to a detailed object-oriented model of PK. The model was evaluated. A random sample of 100 PK texts structured according to the model was judged for completeness and semantic accuracy by 8 experts who were blinded to other experts' responses.


RESULTS
The PK text file contained about 300000 words, and the morpho-syntactic analysis extracted 17520 different CTs. The context of 592 CTs was studied and used to deduce the PK model. It consists of four entities: the information about the real PK process, the experimental protocol, the mathematical modeling, and the influence of factors causing variation. Experts judged that the PK model represented the information in 100 sample PK texts completely in 89% of cases and nearly completely in the other 11%. There was no distortion of meaning in 98% of cases and little distortion in the remainder.


CONCLUSIONS
The PK model seems to be applicable to all SPCs and can be used to retranscribe legal information from PK sections of SPCs into structured databases.
Duclos-Cartolano
Catherine
C
LIM&BIO, UFR de Santé, Médecine, Biologie Humaine, Université, Bobigny, France.
Venot
Alain
A
D001185:Artificial Intelligence; D016208:Databases, Factual; D004346:Drug Information Services; D016247:Information Storage and Retrieval; D008962:Models, Theoretical; D009323:Natural Language Processing; D004364:Pharmaceutical Preparations; D010599:Pharmacokinetics; D010602:Pharmacopoeias as Topic; D012984:Software; D012985:Software Design
D004364:Pharmaceutical Preparations