How to Measure Reproducibility in an LNP Screening Workflow

By Joshua Gomes

Measure reproducibility in an LNP screening workflow by comparing independent preparations within and across runs under matched handling, so differences between candidates can be separated from workflow variation.

Look for consistent results within and across runs

When lipid nanoparticle (LNP) candidates are prepared on different days, a shift in the workflow can look like a difference between candidates. Preparing the same formulation again, both within a run and in a separate run, shows whether a difference comes from the formulations or from the workflow.

An independent preparation is a new formulation of the same composition that goes through every formulation and handling step again, unlike repeat measurements of a single sample.

Type of repeat	What it tells you
Repeat measurements of one sample	Whether the measurement itself is repeatable
Independent preparations within one run	Whether the workflow produces the same particles under one setup
Independent preparations across runs	Whether results hold when the workflow runs again on another day

No single size or %CV threshold defines reproducibility, because the variation your screen can tolerate depends on how small a difference between candidates it needs to detect.

Read particle size, PDI, and %CV together

Z-average diameter is the average hydrodynamic size measured by dynamic light scattering (DLS). Polydispersity index (PDI) describes how broad the size distribution is within a sample. Particle-size percent coefficient of variation (%CV) expresses the standard deviation of Z-average across independent preparations as a percentage of the mean.

Result	What to look for across independent preparations
Z-average diameter	The same formulation returns to a similar size within and across runs
PDI	The size distribution stays comparably narrow
Particle-size %CV	Size variation stays low, with the number of preparations and runs stated

Each preparation can have a low PDI while its average size still shifts between runs, so no single result confirms reproducibility on its own. A %CV from a single run leaves out run-to-run variation. None of these results measure encapsulation or biological activity, which need their own assays.

Match formulation and handling conditions across runs

A shift in particle size between runs often comes from differences in preparation, mixing, or post-processing, rather than from the formulation itself. A sample measured right after collection and one measured after buffer exchange cannot be compared directly.

Comparison point	What to keep consistent
Formulation inputs	Composition, concentrations, buffers, and how inputs were prepared
Formulation method	Platform, device, and protocol settings
Processing and sample age	Processing stage, storage, and hold times
Characterization	Sample preparation, measurement timing, and analytical method

Record these conditions with every result. When they differ, repeat the comparison under matched conditions before drawing a conclusion.

Decide which differences support advancing a candidate

Reading the results together shows which differences between candidates are worth acting on.

What you see	What it means	Next step
Preparations agree within a run but shift between runs	Something in the workflow changes between days	Compare candidates within the same run, or repeat one formulation in every run as a reference
PDI stays low while Z-average shifts	Distributions are tight, but average size is not reproducing	Treat small size differences between candidates as unconfirmed
Candidates differ by about as much as repeat preparations	The difference may come from the workflow	Confirm in another independent run
The difference holds across runs under matched conditions	The difference reflects the formulations	Advance, and confirm with encapsulation and biological assays
Samples were processed or measured differently	The comparison is not on the same basis	Repeat under matched conditions

Most of these patterns resolve with another independent preparation.

Make independent preparations practical in routine screening

Every independent preparation uses instrument time, operator time, and material that could go toward new candidates. How much effort it takes to prepare a formulation again decides how often your team can afford to confirm a result.

Routine task	What to assess
Preparing another formulation	Setup and operator time repeated for each preparation
Moving samples between steps	Manual transfers and waiting between instruments
Collecting material for analysis	Enough recovered volume for characterization and follow-up assays
Repeating the workflow on another day	Whether others on the team can run the method the same way

For teams already preparing reagents on a liquid handler, integrating formulation and collection removes transfers to a separate instrument. Less time per formulation leaves room for more independent preparations and more candidates.

Bring controlled LNP formulation onto your liquid handler

The LNP Screening Array runs microfluidic formulation on your liquid handler, with reagent delivery, mixing, and collection in one automated sequence. Every independent preparation follows the same protocol and is collected separately for characterization.

Screening requirement	How the LNP Screening Array addresses it
A consistent mixing path	Every formulation runs through the same microfluidic mixer design
Defined liquid delivery	A platform-specific automation protocol sets the volumes and flow rates for every sample
Fewer transfers between instruments	Formulation and collection stay on the liquid handler deck
Matched timing after mixing	Every sample follows the same schedule from mixing to collection

Evaluate reproducibility with your own formulations

Run an evaluation in your lab with your own formulations on your liquid handler.

Our applications team is on site for the first run, runs DLS with you, and reviews results against your current method.

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