Size & morphology

Optimize LNP formulations with super-resolution analysis from whole populations down to single particles. Visualize LNPs with nanometer precision for a quick evaluation of sample integrity, stability, aggregation or fragmentation.

Unlike techniques like flow cytometry and mass-spectrometry, which aggregate data, SMLM methods like dSTORM provide precise nanometer-level details on LNP morphology and size: small particles may indicate degradation, large ones can be aggregates, and high polydispersity suggests instability. With the full information and structural anomalies, scientists can accurately assess their LNP behaviour and optimize the formulation for effective therapeutic applications.

Assess cargo encapsulation

The LNP Profiler kit includes a nucleic acid stain for diffraction-limited imaging to evaluate cargo encapsulation per particle, alongside super-resolution imaging of PanLNP and ligand stains.

By combining SMLM imaging of the PanLNP surface marker, fluorescence imaging of the cargo, and the advanced software tools of AutoLNP, scientists can assess their cargo positivity at a single LNP level. These provide increased sensitivity to determine cargo loaded fraction per sample and cargo positivity with SD of < 5% from chip to chip. This valuable information attests to the loading efficiency without compromising on inaccuracies like signal averaging.

Quantify ligand loading

One of the key challenges in LNP development for therapeutics is to have the cargo encapsulated in as many LNPs as possible. For that, it is essential to assess how many LNPs contain cargo and under what conditions.

By combining SMLM imaging of the LNP surface marker, fluorescence imaging of the cargo, and advanced software tools, scientists can quantify their cargo positivity at a single LNP level. This valuable information attests to the loading efficiency without compromising on inaccuracies like signal averaging. Gaining data on both the fraction of ligand positivity and its abundance, with SD of ligand positivity being < 5% from chip to chip, provides the researcher with information on individual LNPs, as well as on their population.

Figure (left): Size distribution of 3 LNP populations: Top row – empty LNP, middle row – cargo-containing LNP, bottom row – 1:1 mix of empty LNPs and cargo-containing LNPs.
Surface marker is in magenta, RNA cargo is in cyan (diffraction limited images).

Correlate LNP metrics

LNP Profiler’s comprehensive analysis capabilities—ranging from assessing LNP size and integrity to evaluating encapsulation efficiency and ligand abundance—deliver actionable data that drives faster, more informed decisions. Correlate multiple metrics, such as cargo-positive LNPs and the levels of surface ligand concentrations; cargo abundance within each lane (in photon count from diffraction-limited imaging) against ligand abundance (number of localizations per single LNP); LNP size distribution as a function of positivity, and LNP size distribution as a function of cargo loading.

Use morphology and size range of individual LNPs to gain insights into particle uptake and delivery based on ligand abundance and cargo positivity.

Figure (left): LNP sample stained with LNP profiler kit. Imaged using AutoLNP, Nanoimager & analysed by CODI. PanLNP (magenta) was used to calculate the size, ligand (yellow) to measure engineering and diffraction limited RNA stain (cyan) to evaluate cargo encapsulation.