Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome.

ABSTRACT:

Objective

Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models.

Materials and methods

Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from

SUBMITTER: Low YS 

PROVIDER: S-EPMC4997030 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature