Datasheet Dataset URL Responsibility and statement of license Hosting/maintenance plan Data format Structured metadata UniTox Datasheet Motivation For what purpose was the dataset created? UniTox was created as a unified toxicity dataset across eight types of drug toxicities (cardiotoxicity, liver toxicity, renal toxicity, pulmonary toxicity, hematological toxicity, dermatological toxicity, ototoxicity, and infertility). We generated information across all toxicities for the same set of 2,418 drugs with the same methodology of applying LLMs. For each drug, for each toxicity, we provide an LLM-generated summary of the relevant portions of the drug label, as well as ternary (No/Less/Most) predictions and binary (No/Yes) predictions for that toxicity. Who created the dataset (e.g., which team, research group) and on behalf of which entity (e.g., company, institution, organization)?

Reliable drug safety reference databases are essential for pharmacovigilance, yet existing resources like SIDER are outdated and static. We introduce PVLens, an automated system that extracts labeled safety information from FDA Structured Product Labels (SPLs) and maps terms to MedDRA. In validation against 97 drug labels, PVLens achieved an F1 score of 0.882, with high recall (0.983) and moderate precision (0.799). By offering a scalable, more accurate and continuously updated alternative to SIDER, PVLens enhances real-time pharamcovigilance with improved accuracy and contemporaneous insights. Keywords: Pharmacovigilance, Natural Language Processing (NLP), Drug Safety, ADR 1 Introduction A clear understanding of known adverse effects, along with continuous surveillance for emerging safety concerns, is essential for patients, healthcare professionals, and pharmacovigilance (PV) scientists.