Use of Exposure Data to Establish Causality in Drug-Adverse Event Relationships: An Example with Desvenlafaxine.

ABSTRACT: Causality algorithms help establish relationships between drug use and adverse event (AE) occurrence. High drug exposure leads to a higher likelihood of an AE being classified as an adverse drug reaction (ADR). However, there is a knowledge gap regarding what concentrations are predictive of ADRs, as this has not been systematically studied. In this work, the Spanish Pharmacovigilance System (SEFV) algorithm was used to define the relationship between the AE occurrence and drug administration in 178 healthy volunteers participating in five desvenlafaxine single-dose clinical trials, a selective serotonin and norepinephrine reuptake inhibitor that may cause dizziness, headache, nausea, dry mouth, constipation and hyperhidrosis. Eighty-three subjects presented 172 AEs that were classified as

SUBMITTER: Rodriguez-Lopez A 

PROVIDER: S-EPMC10819155 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature