The rapid advancement of nanomedicine, particularly underscored by the clinical success of lipid nanoparticle (LNP)-based vaccines, has intensified the need for simple, accurate, and widely accessible analytical techniques. A critical yet often overlooked parameter in nanoparticle development is the precise determination of the nanoparticle concentration. Conventional methods such as nanoparticle tracking analysis and electron microscopy are costly, low-throughput, and unavailable in most laboratories, creating a significant bottleneck in nanomedicine research and quality control. We investigated the potential of derived count rate (DCR), a scattered intensity parameter inherent to dynamic light scattering (DLS) when using a Zetasizer Nano ZS (Malvern Panalytical Ltd.)─an instrument available in virtually all nanomedicine laboratories─as a quantitative tool for LNP concentration analysis. A comprehensive DCR-concentration-size map was established using model LNP batches with varying concentrations. This data was used to derive a model correlating DCR, LNP size, and concentration. The model's predictive power was rigorously validated through a double-blind study involving independently formulated LNP batches with randomized compositions and unknown concentrations, done by formulators of varying expertise. The predictive model demonstrated an excellent fit. In the double-blind validation, the model predicted LNP concentrations with an error of only ∼4% compared to the theoretical values. Crucially, the method proved robust and user-independent, showing consistent high precision and accuracy across beginner, junior, and senior formulators. This study establishes DCR from standard DLS measurements as a simple, accurate, and highly accessible method for LNP quantification, bypassing the need for specialized equipment.
mRNA Technology