We’re seeing a steep rise in the application of nanomedicine, particularly with the use lipid nanoparticles as delivery vectors for nucleic acid-based vaccines and gene therapy therapeutics. While these delivery vectors show great promise, their structural complexity presents significant manufacturing and analytical challenges.

In my recent webinar, Top tips for characterizing lipid nanoparticles attendees submitted lots of great questions about the tools and techniques needed to characterize these vectors for the delivery of mRNA. Keep reading to find my answers to their questions. You’ll also find links to the other webinars in our Vector Analytics Masterclass series.

Light Scattering

What are the pros and cons of nanoparticle tracking analysis (NTA) versus multi-angle dynamic light scattering (MADLS) for lipid nanoparticle analysis?

MADLS is a quick measurement, and it works really nicely when you have a fairly monodisperse sample with few aggregates. There are no clear guidelines on where it would break down, but if there is more light coming from aggregates than the main population of interest, you will struggle to use MADLS to assess your main population. When your samples become very polydisperse, dynamic light scattering techniques become less accurate. MADLS measurements for concentration are based on the size measurement. If your size measurements are not repeatable, your MADLS concentration measurements will not be repeatable.

NTA is a little bit more involved, in that you have to find the concentration range that is good to measure your sample; this is often more dilute than what is required for MADLS concentration measurements. However, it has a real advantage when it comes to polydisperse samples, because it can measure more complex particle compositions. NTA tracks the different particles that you have in your sample and can better resolve close-sized particles.

Which technique you should choose depends on your sample and where you are in your process. I talk more about this in my webinar, Strategies for characterizing size and concentration of viral and non-viral vectors

When MADLS and NTA are applied orthogonally, you extend your insight into your particle’s size distribution and concentration.

When using multi-angle dynamic light scattering, what information about particles do you need to obtain concentration data?

You need to know the refractive index of your buffer and both the refractive index (RI) and the absorbance of your particles. For many buffers, you can either measure RI or you can look it up in tables.

For lipid nanoparticles, they typically show no absorbance – unless you have fluorescently labeled them, and for that, you can use the standard value for liposomes that we provide in our software. In terms of the refractive index of these LNP particles, this will depend on the presence or absence of RNA inside them. Hence, to get accurate concentration values you need to determine the mass fraction of RNA versus the lipid in your particles. When you know that, you can use tabulated values for each to calculate the refractive index for these particles.  I talk more about this in my webinar Strategies for characterizing size and concentration of viral and non-viral vectors

You can determine the mass fraction of RNA versus lipid in a few ways. One of the most commonly used is a fluorescence-based assay, but you can also apply size exclusion chromatography using compositional analysis by a combination of light and concentration detectors. My colleague will describe this in his webinar, How to use SEC-SLS and other detectors to understand mRNA vector composition.

Will multi-angle dynamic light scattering (MADLS) give me the polydispersity index of my lipid nanoparticle sample?

In a word, no. A MADLS measurement provides size distribution analysis, similar to what you get for single angle DLS. It will only give you the peak position, so the size, as well as the peak area, and the peak width. You can assess the MADLS particle size distributions broadness with a parameter called span, which is provided in the software for MADLS measurements.

What are the correct conductivity values to validate zeta potential measurements?

There are no correct conductivity values – it really depends on what you are comparing it with. With the Zetasizer Advance, you can measure across a wide range of conductivity values. If you want to compare different LNP formulations, you need to keep it in the same buffer. If you are studying the effect of the buffer on your particle stability, then you typically use different buffers. If you want to improve your “visibility” of surface charge, then you often use a lower conductivity buffer, such as 10 times diluted PBS buffer. It is all about what question you want to ask of your sample(s).

A good tip is to make up a large volume of a buffer that is enough for all measurements on that day, so that you can use exactly the same buffer for all measurements. That will help in your analysis and comparisons between samples. Small changes in ionic content can significantly affect the zeta potential measurement.

Which type of cells are better for ELS measurement?

It depends a little bit on your sample, of course. I would try to use the semi-disposable cells, mainly because I can do the diffusion barrier method in them. This reduces the sample volume and also limits any potential interaction with the electrodes.

What kind of dispersion could we use for ELS to try to get zeta potential analysis?

Often you can use it as is. Most aqueous buffers work well. Most can be used, but it really depends on your sample. There are some buffers that degrade the electrodes more rapidly, those containing phosphate ions, but this can be reduced by using the diffusion barrier fill method.

Can you explain the Diffusion Barrier Fill Method?

Patented by Malvern Panalytical, the Diffusion Barrier Fill Method is a smarter way of taking zeta potential measurements on the Zetasizer Advance. This method allows you to reduce sample volume from about 750 microliters down to 20-100 microliters (depending on how good you are pipetting!). Using such a small aliquot means the sample never comes into contact with the capillary cell electrodes, preserving the integrity of the sample AND using less of your precious samples.

Differential Scanning Calorimetry (DSC)

How should I prepare my lipid nanoparticle sample for analysis by differential scanning calorimetry (DSC)?

In our study, we did not have to do any sample preparation of our lipid nanoparticles prior to DSC analysis. The important thing is that you have excess buffer that’s the same as the one you have used to suspend your LNPs. This is because you’re doing a comparison compared to the buffer. So that’s what you need. Otherwise, there were no special sample preparations.

You do not need to prepare a sample by centrifuging. In our study we ran our LNP samples from about 2°C up to above 100°C. You can find out more in our peer-reviewed paper from this study here.

Size Exclusion Chromatography (SEC)

How do you obtain information about the loading of the LNP from size exclusion chromatography (SEC) and light scattering techniques?

Size exclusion chromatography only separates the sample. It’s really the detectors that allows you to quantify what’s inside. This is called compositional analysis and it takes into account the concentration measurements from a refractive index (RI) detector and an ultraviolet (UV) detector. The UV detector is sensitive to the mRNA, whereas the RI will see both lipids and mRNA. Using these detectors and static light scattering, we can extract what the fractional mRNA content is, in terms of mass compared to the total content.

Will my lipid nanoparticle remain intact during size exclusion chromatography analysis?

There may be interaction with columns and other components in the system, such as pre-or post-column filters if they are used. This very much depends on the particle.

It’s important to consider this during method development, you can take steps to minimize this, by selecting running buffer conditions and decide which components of your system are critical. A way to assess this is to run your sample through the chromatography tubing, and then compare the recovery after you put in the column and/or any filters you typically used. We have found that it is possible to find columns that do not significantly interact with the sample but gives good recovery. However, some filters may trap the sample. Look out for our upcoming webinar, How to use SEC-SLS and other detectors to understand mRNA vector composition to learn more.

What’s next in this series?

• You can catch up with the first three webinars in this series on-demand:
  • Strategies for characterizing size and concentration of viral and non-viral vectors
  • An expert guide to using zeta potential for the surface characterization of viral and lipid-based vectors
• There’s more to come in this series and you can sign up now for the fourth and fifth webinars in this series:
  • How to use SEC-SLS and other detectors to understand mRNA vector composition
  • Discover how differential scanning calorimetry can help you improve the thermal stability of lipid-based vectors