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Building a Higher-Throughput LNP Screening Workflow
By Joshua Gomes
A higher-throughput LNP screening workflow brings formulation into the automated environment, helping teams evaluate more conditions, conserve valuable inputs, and generate comparable data with fewer handoffs.
Why LNP screening workflows need to evolve
Lipid nanoparticle (LNP) formulation plays a central role in RNA therapeutics, gene editing, vaccines, and advanced delivery research. As programs evaluate more lipid compositions, cargos, process settings, and analytical readouts, the value of a screen increasingly depends on how efficiently teams can generate comparable data across a meaningful design space.
Many teams have already automated the work around formulation, including liquid handling, plate-based assay setup, and downstream characterization. LNP generation, however, often still depends on dedicated instruments, manual transfers, and serial setup, which can narrow what teams choose to test as screens expand and materials become more valuable.
What makes LNP screening difficult to scale?
LNP screening depends on controlled comparison across formulation conditions, process settings, and downstream readouts. Teams need to understand how variables influence particle properties, which formulations merit deeper characterization, and which experimental direction deserves the next round of work.
When particle generation sits outside the automated process, screen design can become shaped by execution constraints rather than the full scientific question. Teams may reduce conditions, limit replicates, delay follow-up work, or spend excessive time coordinating transfers and setup instead of analyzing results and planning the next formulation experiment.
For LNP screening to scale, formulation needs to fit more naturally into the way teams already prepare, organize, and analyze samples.
What changes when formulation moves into automation?
Automated microfluidic screening creates a more direct path from input preparation to particle generation. By keeping formulation inside the automated environment, teams can screen variables such as lipid composition, cargo, flow conditions, and buffer conditions, then evaluate how those inputs affect particle size, PDI, and downstream performance.
This is especially useful in early formulation work, where teams often need broad exploration before narrowing toward a smaller set of candidates. Higher throughput, lower material use, and more consistent execution help each screening round produce data that is easier to compare and faster to act on.
The goal is better formulation data with less operational drag.
How the LNP Screening Array differentiates the workflow
The LNP Screening Array brings microfluidic formulation into one automated liquid handling workflow, allowing teams to generate LNPs on the automation deck instead of routing formulation through a separate dedicated system.
The most important advantages show up in the areas that determine whether a screen can scale efficiently.
| Screening priority | What the LNP Screening Array enables |
|---|---|
| Broader screening capacity | Supports 100+ formulations per hour, helping teams evaluate more conditions per run |
| Faster iteration | Runs up to 10x faster than dedicated instruments, shortening the path from screen design to formulation data |
| Lower material burden | Uses low-volume microfluidic formulation with less than 50 µL dead volume per mixer, helping conserve lipid and RNA inputs |
| Workflow continuity | Keeps formulation inside one automated workflow, reducing handoffs between preparation, particle generation, and sample recovery |
| Process control | Supports instrument-controlled formulation settings, giving teams a practical way to evaluate process variables during screening |
Together, these capabilities help teams ask broader formulation questions, generate more comparable data, and preserve more scientific effort for interpretation and follow-up decisions.
For a closer look at the hardware, components, and liquid handler interface, read How the LNP Screening Array Works.
What does this unlock for LNP screening teams?
- Broader screens become more practical to run.
Automated microfluidic formulation gives teams a more practical way to run structured, DoE-style screens across lipid compositions, cargos, and process parameters. Instead of testing one variable at a time, teams can evaluate multiple inputs in parallel and identify how formulation and process choices influence particle size, PDI, and downstream performance. - Scarce lipid and RNA inputs go further.
Material availability often shapes what teams can test, especially when RNA cargo is limited or lipid inputs are expensive. With less than 50 µL dead volume per mixer, the LNP Screening Array helps teams generate more formulation data from the material they already have. - Scientists spend less time managing execution.
Reducing repetitive setup, transfers, and manual coordination allows scientists to spend more time on experimental design, data interpretation, and the decisions that move a program forward. - Data becomes easier to compare across conditions.
More consistent execution helps teams evaluate formulation outputs with less noise from manual handling, sample movement, or disconnected setup steps, especially when using particle size, PDI, potency, stability, or another downstream readout to decide which formulations move forward.
A more scalable path for LNP screening
The LNP Screening Array gives formulation teams a practical way to increase screening capacity while preserving the control and material efficiency needed for meaningful comparison.
Start screening LNPs on your existing liquid handler
Ready to evaluate automated microfluidic LNP screening?
Contact us to discuss your workflow or get your LNP Screening Array Starter Kit to begin testing.