Send to

Choose Destination

Automatic Extraction of Drug Adverse Effects from Product Characteristics (SPCs): A Text Versus Table Comparison.

Author information

LIMICS, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France, INSERM UMRS 1142, UPMC Université Paris 6, Sorbonne Universités, Paris.



Potential adverse effects (AEs) of drugs are described in their summary of product characteristics (SPCs), a textual document. Automatic extraction of AEs from SPCs is useful for detecting AEs and for building drug databases. However, this task is difficult because each AE is associated with a frequency that must be extracted and the presentation of AEs in SPCs is heterogeneous, consisting of plain text and tables in many different formats.


We propose a taxonomy for the presentation of AEs in SPCs. We set up natural language processing (NLP) and table parsing methods for extracting AEs from texts and tables of any format, and evaluate them on 10 SPCs.


Automatic extraction performed better on tables than on texts.


Tables should be recommended for the presentation of the AEs section of the SPCs.

[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for IOS Press
Loading ...
Support Center