Dataset Information

Target-Adverse Event Profiles to Augment Pharmacovigilance: A Pilot Study With Six New Molecular Entities.

ABSTRACT: Clinical trials can fail to detect rare adverse events (AEs). We assessed the ability of pharmacological target adverse-event (TAE) profiles to predict AEs on US Food and Drug Administration (FDA) drug labels at least 4 years after approval. TAE profiles were generated by aggregating AEs from the FDA adverse event reporting system (FAERS) reports and the FDA drug labels for drugs that hit a common target. A genetic algorithm (GA) was used to choose the adverse event (AE) case count (N), disproportionality score in FAERS (proportional reporting ratio (PRR)), and percent of comparator drug labels with an AE to maximize F-measure. With FAERS data alone, precision, recall, and specificity were 0.57, 0.78, and 0.61, respectively. After including FDA drug label data, precision, recall, and specificity improved to 0.67, 0.81, and 0.71, respectively. Eighteen of 23 (78%) postmarket label changes were identified correctly. TAE analysis shows promise as a method to predict AEs at the time of drug approval.

SUBMITTER: Schotland P

PROVIDER: S-EPMC6310867 | biostudies-other | 2018 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Target-Adverse Event Profiles to Augment Pharmacovigilance: A Pilot Study With Six New Molecular Entities.

Schotland Peter P Racz Rebecca R Jackson David D Levin Robert R Strauss David G DG Burkhart Keith K

CPT: pharmacometrics & systems pharmacology 20181024 12

Clinical trials can fail to detect rare adverse events (AEs). We assessed the ability of pharmacological target adverse-event (TAE) profiles to predict AEs on US Food and Drug Administration (FDA) drug labels at least 4 years after approval. TAE profiles were generated by aggregating AEs from the FDA adverse event reporting system (FAERS) reports and the FDA drug labels for drugs that hit a common target. A genetic algorithm (GA) was used to choose the adverse event (AE) case count (N), dispropo ...[more]

PMID: 30354029

Similar Datasets

Project description:BackgroundRisankizumab, a humanized IgG1 monoclonal antibody that selectively inhibits IL-23, is currently approved for the treatment of moderate-to-severe plaque psoriasis and Crohn's disease. The real-world safety study of risankizumab in a large- sample population is currently lacking. The aim of this study was to evaluate risankizumab-associated adverse events (AEs) and characterize the clinical priority through the data mining of the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS).MethodsDisproportionality analyses were performed by calculating the reporting odds ratios (RORs), deemed significant when the lower limit of the 95% confidence interval was greater than 1, to quantify the signals of risankizumab-related AEs from the second quarter (Q2) of 2019 to 2022 Q3. Serious and non-serious cases were compared, and signals were prioritized using a rating scale.ResultsRisankizumab was recorded in 10,235 reports, with 161 AEs associated with significant disproportionality. Of note, 37 PTs in at least 30 cases were classified as unexpected AEs, which were uncovered in the drug label, such as myocardial infarction, cataract, pancreatitis, diabetes mellitus, stress, and nephrolithiasis. 74.68%, 25.32%, and 0% PTs were graded as weak, moderate, and strong clinical priorities, respectively. A total of 48 risankizumab-related AEs such as pneumonia, cerebrovascular accident, cataract, loss of consciousness, cardiac disorder, hepatic cirrhosis, and thrombosis, were more likely to be reported as serious AEs. The median TTO of moderate and weak signals related to risankizumab was 115 (IQR 16.75-305) and 124 (IQR 29-301) days, respectively. All of the disproportionality signals had early failure type features, indicating that risankizumab-associated AEs gradually decreased over time.ConclusionOur study found potential new AE signals and provided valuable evidence for clinicians to mitigate the risk of risankizumab-associated AEs based on an extensive analysis of a large-scale postmarketing international safety database.

Dataset Information

Target-Adverse Event Profiles to Augment Pharmacovigilance: A Pilot Study With Six New Molecular Entities.

Publications

Target-Adverse Event Profiles to Augment Pharmacovigilance: A Pilot Study With Six New Molecular Entities.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets