Abstract
<jats:p>Background: Messenger RNA (mRNA)-loaded lipid nanoparticles (LNPs) are a major therapeutic delivery platform, popularized by mRNA COVID-19 vaccines and under active development for vaccination, protein replacement, and gene-editing applications. Reported formulation and characterization data remain scattered across a fast-growing and heterogeneous literature. Objective: To build a transparent, traceable, literature-derived dataset of in vitro-tested mRNA-LNP formulations and explore associations between formulation parameters, physicochemical characteristics, delivery performance, and cell viability. Methods: Twenty-one peer-reviewed articles and preprints (2018-2026) meeting predefined inclusion criteria were screened and manually extracted, yielding 59 formulations (53 conventional mRNA, 6 self-amplifying RNA analyzed as a separate subgroup). Data were cleaned in Python (pandas) and analyzed descriptively; exploratory associations between numeric variables were tested using Spearman rank correlation. Results: Data completeness varied substantially across variables (64% for particle size, 45% for encapsulation efficiency, versus 4-6% for delivery performance and cell viability). A moderate, statistically significant negative correlation was observed between particle size and encapsulation efficiency (r = -0.50, p = 0.018, n = 22), which persisted after exclusion of one outlier (r = -0.44, p = 0.048, n = 21). A second significant negative association was found between N/P ratio and encapsulation efficiency (r = -0.47, p = 0.040, n = 19). Conclusion: Within the limits of a small, heterogeneous, literature-derived sample, this exploratory analysis suggests a reproducible pattern linking particle size to encapsulation efficiency across independently published mRNA-LNP formulations. These associations do not establish causality and should be interpreted as hypothesis-generating rather than confirmatory.</jats:p>