Syntro is an AI-powered literature review platform designed specifically for pharmacovigilance. It automates the entire research workflow—from search strategy optimization and query formulation to intelligent screening and evidence-based analysis—delivering auditable, verified answers to drug-safety questions in minutes. The platform dynamically generates MeSH-based search queries and provides source-to-data verification through automated citation mapping.
Funding
Funding not disclosed
Founders
Product
Problem
Pharmacovigilance professionals face a time-intensive, manual process when conducting literature reviews to assess drug safety signals. Searching PubMed and other databases requires expert-level query formulation, and screening hundreds of abstracts for relevant adverse event data is laborious and prone to human error, delaying critical safety assessments.
Solution
Syntro provides an AI-powered literature review platform that automates the end-to-end research workflow for pharmacovigilance. Users pose a research question in plain language, and Syntro dynamically generates optimized search queries—including MeSH terms and synonyms—to retrieve relevant publications. The platform then performs smart contextual analysis, extracting and tagging key information such as patient populations, adverse effects, and dosages, while intelligent screening triages high-impact evidence and filters out noise. Each result is anchored to the original source through automated citation mapping, and the system provides direct, evidence-based answers to the research question, complete with full abstract access for verification.
Target Audience
Primary users are pharmacovigilance professionals, drug safety scientists, and medical affairs teams in pharmaceutical companies, regulatory agencies, and clinical research organizations who need to conduct rapid, auditable literature reviews for drug safety assessments.
Features
- Dynamic search query generation that suggests keywords and formulates optimized PubMed queries with MeSH terms, synonyms, and Boolean logic
- Smart contextual analysis that extracts and tags critical information from publications, including population, adverse effects, dosage, and clinical outcomes
- Intelligent screening with automated triage that prioritizes high-impact evidence and categorizes results by key themes
- Source-to-data verification through automated citation mapping, ensuring every AI-generated answer is anchored to the original literature
- Direct research question answering that synthesizes findings from abstracts and indicates whether the evidence supports or refutes the query
- Filtering and sorting capabilities by clinical profile, population, pharmaceutical form, and best-match relevance