A cytotoxicity dataset for data-driven design of ionizable lipid nanoparticles

Ionizable lipid nanoparticles (LNPs) are widely used to deliver nucleic acid therapeutics, but the design of safe LNPs remains challenging due to the complex activity relationships among structure, composition, and physicochemical properties. Here, we present a curated dataset, the Lipid Nanoparticle Cytotoxicity Database (LNPCD), which aggregates 1,413 LNP cytotoxicity measurements across 1,288 unique ionizable lipids drawn from 11 high-throughput combinatorial studies. Lipid structures were generated computationally from the published libraries and manually verified against the original publications. Each record pairs a machine-readable SMILES representation of the ionizable lipid with its measured viability endpoint and the associated experimental descriptors, including cell line, dose, and cargo type. The dataset provides a traceable resource for examining how ionizable lipid structure and experimental conditions relate to in vitro cell viability, and for developing and evaluating computational models of lipid nanoparticle cytotoxicity.