Preparing your experience...
Preparing your experience...
Capability Domain
Build comprehensive safety profiles from FDA labeling, clinical trial data, post-market surveillance, and pharmacogenomics — all in one structured, auditable view.
A drug safety profile answers: what is known about this drug's harms, and from which sources? AlgoVigilance assembles evidence from four distinct layers — label, trials, surveillance, and genomics — into one coherent profile with source attribution for every finding.
The FDA-approved prescribing information is the regulatory ground truth for drug safety. AlgoVigilance extracts structured data from each section of the label via DailyMed (NIH National Library of Medicine).
| Label Section | What It Contains |
|---|---|
| Boxed Warning (Section 5.x) | Highest-severity FDA safety warnings — black box events requiring prominent labeling |
| Warnings & Precautions (5.x) | Serious risks requiring monitoring, dose adjustment, or contraindication consideration |
| Adverse Reactions (6.1, 6.2) | Clinical trial ADRs (6.1) and post-marketing experience (6.2) with incidence rates |
| Drug Interactions (7) | Pharmacokinetic and pharmacodynamic interactions with clinical consequences |
| Use in Specific Populations (8) | Pregnancy, lactation, pediatric, geriatric, and renal/hepatic impairment data |
| Clinical Pharmacology (12) | Mechanism of action, pharmacokinetics, pharmacodynamics |
Clinical trial registrations include the study design parameters and, for completed trials, results — including Serious Adverse Event (SAE) tables. AlgoVigilance queries ClinicalTrials.gov for trials involving the drug and extracts SAE incidence by system organ class.
SAE Tables
System-organ-class breakdown of serious adverse events from completed trials
Study Design
Phase, population, comparator arm, and dose regimens affecting safety interpretation
Arm Comparison
Drug vs. placebo vs. active comparator SAE rates for absolute and relative risk
PharmGKB (Stanford) curates gene-drug relationships from the published literature. Pharmacogenomic (PGx) annotations explain why some patients experience toxicity at standard doses — due to CYP enzyme polymorphisms, transporter variants, or target sensitivity differences.
CYP Metabolizer Status
Poor/intermediate/normal/ultrarapid metabolizer phenotypes from CYP2D6, CYP2C19, CYP3A4/5 — affects drug exposure by up to 10-fold
FDA PGx Biomarker Labels
FDA-required pharmacogenomic biomarkers in labeling — genotype-based dosing recommendations and contraindications
Open Targets integrates target safety information from toxicology studies, genetic associations, and experimental data. For any drug target (protein), it surfaces safety liability evidence — which tissues express it, what effects genetic perturbation causes, and which safety parameters have been flagged in the literature. This layer is particularly valuable for evaluating mechanism-based toxicity risks early in development.
4 Profile Methods
DailyMed label extraction, ClinicalTrials SAE tables, pharmacogenomic annotations, drug class comparison across all four layers
Post-Market Surveillance
FAERS real-world reporting rates complement label and trial data with actual clinical practice experience
5 Reference Sources
DailyMed, ClinicalTrials.gov, PharmGKB, Open Targets, DrugBank — integrated into a single drug-level view
Data Sources
Connect your AI agent to mcp.nexvigilant.com and assemble a four-layer safety profile in one guided workflow.