A Beginner’s Guide to Lipid Nanoparticle Preparation: Key Steps from Design to Characterization

Lipid nanoparticles (LNPs) have become the leading non-viral delivery platform for nucleic acid therapeutics, with validated performance in mRNA vaccines, saRNA-delivered therapeutics, siRNA, gene editing, and an expanding range of small molecule and protein payloads. For researchers entering this field, the path from a new cargo to a usable LNP can feel fragmented: there are many lipid components to choose from, several preparation methods to evaluate, and a growing list of characterization assays whose targets must be met before in vitro or in vivo work begins. This guide walks through the full workflow in seven practical steps — defining the payload, designing a starting formulation, selecting a preparation method, preparing stocks and buffers, mixing the components, purifying the product, and characterizing the result — with troubleshooting guidance for the most common issues encountered in early LNP development.

Step 1: Define Your Payload and Research Requirements

A clear payload and project definition sits at the start of every successful LNP program because nearly every downstream decision — lipid composition, buffer choice, mixing method, and characterization depth — is shaped by what is being delivered and how the formulation will be used. Before touching the first tube of lipid stock, take a step back and map the requirements of the project.

Identify Payload Properties That Affect Encapsulation

Different cargo classes interact with the ionizable lipid core in different ways, and they tolerate different ranges of pH, ethanol, and shear during mixing.

Nucleic acid size and charge density matter: mRNA (typically a few hundred to a few thousand nucleotides) is a long, flexible polyanion that needs an acidic mixing environment (around pH 4.0) and an ionizable lipid with sufficient amine content; saRNA is even longer and places more demand on the encapsulation chemistry; siRNA is small (~21 bp duplex) and is usually encapsulated more easily with lower N/P ratios; plasmid DNA is large and supercoiled, which requires stronger mixing and a higher ionizable lipid fraction; antisense oligonucleotides and Cas9 ribonucleoproteins fall between these extremes and may require tailored compositions.

Small molecule and biologic payloads behave differently: hydrophobic small molecules partition into the lipid bilayer or core and often do not need electrostatic association, while proteins and peptides may be encapsulated as a co-solution, surface-displayed, or anchor-assisted depending on their isoelectric point and stability. A project focused on lipid nanoparticle synthesis for a particular cargo should always start from a payload-specific design rather than a generic mRNA recipe.

Define the Target Cells, Delivery Route, and Functional Readout

The intended biology shapes both the formulation and the acceptance criteria. Liver delivery via intravenous injection is the easiest case to design for, while extrahepatic targets (lung, tumor, brain, lymphoid tissue) typically require either selective organ targeting (SORT) strategies, modified lipid chemistries, or active targeting ligands.

Route of administration also matters. Intramuscular and subcutaneous routes generally tolerate larger LNPs and broader size distributions than intravenous routes, while inhaled or local routes may impose additional buffer and sterility requirements. The functional readout — whether a luciferase assay, a GFP reporter, a knockdown of an endogenous transcript, an editing event, or an antigen-specific immune response — determines how sensitive the characterization panel must be and how reproducible the formulation needs to be across batches.

Plan Batch Size, Final Concentration, and Sample Requirements

Early feasibility work usually needs only a few hundred microliters per condition, while animal studies may require several milliliters at therapeutically meaningful concentrations. Defining these volumes up front prevents costly re-runs and dictates whether parallel microfluidic cartridges, a single syringe pump, or bulk mixing is appropriate.

Concentration targets drive buffer choice: if the assay requires 0.5–1.0 mg/mL mRNA, the formulation needs to be concentrated after preparation, which adds a tangential flow filtration (TFF) step and an additional recovery check. If the downstream use is a single-cell transfection screen, lower concentrations and direct use of the preparation buffer may be sufficient. Lipid nanoparticle formulation projects scale much more smoothly when the team agrees on batch size, target concentration, and the minimum characterization panel before the first LNP is made.

Step 2: Select Lipid Components and Design a Starting Formulation

Once the payload and project requirements are defined, the next decision is the lipid composition. Most modern LNPs are built from four functional lipid components, and the molar ratio between them controls almost every downstream property — size, encapsulation efficiency, stability, biodistribution, and potency. Beginners benefit from starting with a published reference formulation and adjusting one variable at a time.

Choose an Ionizable Lipid for Payload Association and Delivery

The ionizable lipid is the functional core of the LNP. It carries a tertiary amine head group with a pK_a between roughly 6.0 and 7.0, which means it is positively charged in the acidic mixing buffer (around pH 4.0), neutral at physiological pH (~7.4), and re-protonated in the late endosome (around pH 5.5). This reversible protonation enables three things at once: electrostatic binding to the nucleic acid cargo during self-assembly, low surface charge and reduced toxicity in circulation, and disruption of the endosomal membrane that releases the cargo into the cytosol.

Established choices include DLin-MC3-DMA (used in the first approved siRNA-LNP, patisiran), SM-102, and ALC-0315. Each has its own apparent pK_a, biodegradability profile, and tolerability profile. For a new program, it is often pragmatic to start with a well-characterized reference ionizable lipid and explore alternatives through systematic LNP ionizable lipid optimization once the workflow is established.

Select the Helper Phospholipid, Cholesterol, and PEG-Lipid

The helper phospholipid — most commonly 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) — provides structural support to the lipid bilayer and stabilizes the particle during and after mixing. Phosphatidylethanolamines such as DOPE can be substituted in formulations that favor endosomal escape, at the cost of slightly reduced stability. Cholesterol fills gaps in the lipid monolayer, promotes membrane fusion, and limits cargo leakage, and is typically included at 30–45 mol%.

PEG-lipid is the smallest but most consequential component. PEG-lipid density controls the colloidal stability of the LNP, the particle size, and the rate of cellular uptake. Too little PEG-lipid (below ~1.0 mol%) leads to fusion and aggregation; too much (above ~3.0 mol%) blocks cellular uptake and reduces potency. The anchor length (C14 vs C18) and PEG molecular weight (commonly 1–5 kDa) further tune how quickly the PEG-lipid sheds from the surface after injection, which influences both circulation time and intracellular delivery.

Set Lipid Molar Ratios and the Lipid-to-Payload Ratio

Most clinical-stage LNP formulations sit within a fairly narrow compositional envelope. The molar ratio of ionizable lipid : helper lipid : cholesterol : PEG-lipid in approved products is close to 50 : 10 : 38.5 : 1.5 (for example, the patisiran and mRNA-1273 formulations), with BNT162b2 close to 46.3 : 9.4 : 42.7 : 1.6. This is a reasonable starting point for a beginner; small adjustments can then be made as the formulation is screened.

The lipid-to-payload weight ratio (most often 10:1 to 30:1) controls encapsulation efficiency. The N/P ratio — the molar ratio of ionizable lipid amines to nucleic acid phosphates — controls the charge balance and is most often set between 3 and 8, with 6 as a common baseline for mRNA. These two parameters together set the payload loading and the dose per particle, and they are usually the first variables explored in any LNP lipid ratio optimization campaign.

Step 3: Choose a Preparation Method That Fits Your Project

Preparation method matters as much as lipid composition in determining whether an LNP program moves forward. The three families of methods most beginners encounter — manual mixing, microfluidic mixing, and bulk techniques such as T-mixers or impingement jet mixers — differ dramatically in reproducibility, sample consumption, scalability, and the equipment investment required.

Manual Mixing for Small-Scale Feasibility Studies

Manual methods include thin-film hydration (in which a lipid film is hydrated with an aqueous cargo solution) and ethanol injection (in which the ethanolic lipid mixture is rapidly pipetted into the aqueous cargo solution). Both require only basic laboratory equipment and a small reagent budget, which makes them appealing for early feasibility studies.

The trade-off is reproducibility. Manual mixing tends to produce heterogeneous particle populations with polydispersity indices above 0.3 and encapsulation efficiencies well below what microfluidic methods can achieve. For most nucleic acid programs, manual mixing is best confined to the very first "does it work at all?" screen, with the understanding that any positive result must be confirmed under more controlled mixing before drawing biological conclusions.

Microfluidic Mixing for Controlled Formulation Screening

Microfluidic mixing has become the default method for LNP formulation development because it enables rapid, controlled, and reproducible mixing at low volumes. In the typical setup, the ethanolic lipid phase and the aqueous payload phase are pushed through a micromixer with defined geometry (T-junction, Y-junction, serpentine, toroidal, or staggered herringbone) where they mix on the millisecond timescale. The lipid solubility drops sharply as ethanol is diluted, triggering nanoprecipitation and LNP self-assembly in a single, well-controlled step.

The most common chip architecture for LNP work is the staggered herringbone micromixer (SHM), which uses chaotic advection to produce very uniform mixing across the channel. Specialized geometries such as hydrodynamic flow focusing and Dean flow mixers offer different mixing dynamics and are sometimes preferred for difficult encapsulation cases. For routine screening, an entry-level cartridge-based instrument can deliver reproducible 50–120 nm LNPs with polydispersity indices below 0.2 and encapsulation efficiencies above 90% in volumes as small as a few hundred microliters.

Compare Equipment Needs, Sample Consumption, and Reproducibility

Choosing a method is partly a scientific question and partly an operational one. Manual mixing has the lowest equipment cost but the worst reproducibility; bulk impingement jet mixing has been used for COVID-19 vaccine manufacturing but requires significant volumes to operate within its narrow design space; microfluidic mixing offers the best combination of reproducibility and material efficiency for R&D work, with options ranging from disposable cartridges to parallelized high-throughput platforms.

Sample consumption should also be considered carefully. Methods that require several milliliters per condition quickly become prohibitive when a screening campaign explores dozens of lipid compositions. Methods that operate in the 100–500 µL range make it practical to run design-of-experiments studies across ionizable lipids, helper lipids, PEG-lipids, and ratios in a single day.

Step 4: Prepare Lipid Stocks, Payload Solutions, and Buffers

The fourth step — preparing stocks and buffers — is where most first-time LNP experiments are won or lost. Most reproducibility failures are not caused by the lipid design itself, but by misprepared stocks, miscalculated volumes, pH drift, or trace contaminants that disturb the self-assembly. A short checklist before each campaign pays for itself many times over.

Prepare Lipid Stocks with Verified Concentrations and Solubility

Each lipid should be dissolved in absolute ethanol (or, for some lipids, chloroform followed by solvent exchange) at a verified stock concentration. Stock concentrations in the 10–25 mM range are convenient because they allow simple volumetric mixing when assembling the working lipid solution. Stocks should be stored tightly capped, protected from moisture, and checked visually for precipitation before each use; any lipid stock that shows turbidity, color change, or precipitation should be discarded and replaced.

Lipid concentration should be verified by an appropriate method (for example, a colorimetric assay or HPLC against a standard) before scale-up. For custom or novel lipid chemistries, partnering with a custom synthesis provider during the stock preparation step reduces the risk of working with inaccurately characterized material.

Check Payload Concentration, Integrity, and Handling Requirements

Payload concentration must be confirmed by absorbance (for example, A₂₆₀ for nucleic acids) and ideally cross-checked by a fluorescence-based assay. Integrity should be assessed by capillary electrophoresis, agarose or acrylamide gel electrophoresis, or bioanalyzer trace — a degraded mRNA or fragmented plasmid will produce a "successful" encapsulation measurement that delivers very little functional cargo.

RNase-free handling is non-negotiable for RNA payloads: gloves should be fresh, work surfaces should be cleaned with an RNase decontamination solution, plastic consumables should be certified RNase-free, and stocks should be kept on ice and used within a few hours of thawing. For ASO, siRNA, or mRNA work, the difference between a 90% and a 30% encapsulation efficiency often comes down to payload handling rather than formulation chemistry.

Select Mixing Buffers and Calculate Input Volumes

The most common mixing buffer for nucleic acid LNPs is 10–25 mM sodium citrate (or sodium acetate) at pH 4.0, which protonates the ionizable lipid and enables electrostatic complexation. The aqueous phase volume is typically three times the ethanol phase volume, giving a flow rate ratio of 3:1 and a final ethanol concentration around 25% (v/v) immediately after mixing. Working volumes, lipid concentrations, and payload concentrations should be tabulated before the run so that no volumetric mistake is made at the bench.

For screening campaigns, a well-designed LNP buffer screening study spanning pH 4.0–5.5 and ionic strengths of 0–150 mM often reveals that a seemingly minor change in buffering can shift encapsulation efficiency by 10–20 percentage points, especially for highly structured RNAs.

Step 5: Mix the Components and Control LNP Formation

LNP formation is a kinetically controlled self-assembly process: lipids dissolved in ethanol and payload dissolved in an acidic aqueous buffer meet at a controlled interface, the polarity drops, and the lipid precipitates around the payload on the millisecond timescale. The faster and more uniform the mixing, the smaller and more homogeneous the resulting particles.

Control Phase Volumes, Mixing Rate, and Addition Sequence

For manual mixing, the most important control is the addition sequence. The ethanolic lipid solution should be added rapidly to the stirred aqueous payload solution (not the reverse), at a volume ratio of about 1:3, and the resulting dispersion should be allowed to equilibrate for 10–15 minutes at room temperature before purification. Stirring should be vigorous but not vortexing — a magnetic stirrer at 600–1000 rpm in a round-bottom vial is typical.

For microfluidic mixing, the addition sequence is replaced by simultaneous pumping of both phases through a micromixer. Phase volumes, mixing rates, and the chip geometry together determine the mixing time, which in turn determines particle size and encapsulation efficiency.

Set Flow Rate Ratio and Total Flow Rate for Microfluidic Mixing

The two key process parameters in microfluidic mixing are the flow rate ratio (FRR, aqueous : ethanol) and the total flow rate (TFR). A starting point of 3:1 FRR and 12 mL/min TFR is widely used for nucleic acid LNPs and produces particles in the 60–100 nm window with low PDI. Increasing the aqueous fraction (FRR 4:1 or 5:1) generally produces smaller particles by accelerating the polarity shift; increasing the total flow rate increases Reynolds number, which speeds mixing and tightens the size distribution.

Both parameters are easy to vary and have a large effect, so a small design-of-experiments screen around FRR and TFR is often the most cost-effective optimization step in early development. Specialized geometries such as Dean flow LNP production offer additional mixing dynamics that can be useful when standard SHM designs plateau.

Manage Temperature, Collection, and Post-Mixing Dilution

Mixing is usually performed at room temperature (20–25 °C), which keeps all four lipid components above their phase transition temperatures and ensures consistent bilayer fluidity. After collection, the LNP dispersion should be diluted promptly — typically 1:1 with PBS or another neutral buffer — to bring the ethanol concentration below ~10% and prevent fusion during the early minutes when the PEG-lipid has not yet fully equilibrated on the particle surface.

The collected dispersion should be held at room temperature for 10–15 minutes before further processing. This "maturation" step allows any loosely associated PEG-lipid to redistribute, which improves both colloidal stability and downstream reproducibility. Beginning LNP researchers often skip this step and end up with misleadingly variable size measurements between batches.

Step 6: Purify, Concentrate, and Store the Prepared LNPs

Immediately after mixing, the LNP dispersion still contains ethanol, unencapsulated payload, and excess buffer ions that should be removed before the formulation is used in biological experiments. Purification also has a substantial effect on apparent encapsulation efficiency, so a consistent purification step is essential for reproducible characterization.

Remove Solvent and Exchange into a Suitable Final Buffer

The most common purification methods are dialysis (using a 10–20 kDa molecular weight cutoff membrane against a large excess of PBS), tangential flow filtration (TFF, using a similar cutoff membrane in a crossflow setup), and desalting columns such as desalting column for rapid buffer exchange. All three methods remove ethanol, exchange the buffer from acidic mixing conditions to a neutral storage buffer (typically PBS pH 7.4), and reduce the concentration of free lipid and free payload.

TFF is preferred when the formulation needs to be concentrated at the same time, while dialysis is easier to set up at small scale. The choice of method affects recovery — TFF typically gives 80–95% recovery with proper membrane selection, while dialysis may give 60–80% recovery depending on volume and membrane area. For consistency, the same purification method should be used throughout a screening study.

Assess Free Payload Removal and Concentrate with Recovery Checks

After purification, a sample should be analyzed for free payload to confirm that the purification has done its job. For RNA LNPs, this is conveniently measured as part of the fluorescence-based RNA encapsulation assay, by comparing the fluorescence of the LNP sample (with encapsulated RNA inaccessible to the dye) to that of a detergent-disrupted sample (with all RNA accessible). A small free payload fraction is acceptable; a large free fraction is usually a sign that the encapsulation step needs to be revisited rather than that the purification step failed.

Concentration should be tracked with mass balance: measure the payload concentration (by absorbance or RiboGreen) and the lipid concentration (by a cholesterol assay or HPLC) before and after concentration to calculate recovery. A sudden drop in recovery is a strong signal that the formulation is aggregating, sticking to the membrane, or being lost during the buffer exchange.

Select Storage Conditions and Establish Initial Stability

For short-term working stocks, LNPs are typically stored at 2–8 °C in PBS for up to one week. For longer-term storage, lyophilization with an appropriate cryoprotectant (commonly sucrose or trehalose at a 5:1 to 20:1 sugar-to-lipid mass ratio) or freezing at −80 °C is required. Each storage path should be qualified with a stability study that tracks particle size, PDI, zeta potential, encapsulation efficiency, and payload integrity over the intended storage interval.

Specialized LNP cryoprotectant screening can identify the cryoprotectant type and concentration that minimizes post-thaw size and EE% shifts, and is often the difference between a formulation that survives a single freeze-thaw cycle and one that can be stored for months at a time.

Step 7: Characterize LNPs Before Further Experiments

Characterization is what closes the loop between formulation and biology. Before an LNP is taken into in vitro or in vivo studies, a small panel of physicochemical measurements confirms that the formulation is what it is supposed to be, and a brief functional test confirms that it actually delivers.

Measure Particle Size, Size Distribution, and Surface Charge

Dynamic light scattering (DLS) is the workhorse technique for particle size and polydispersity index. For therapeutic LNPs, a Z-average of 50–150 nm and a PDI below 0.2 are typical targets. Zeta potential — measured by electrophoretic light scattering — is usually in the −5 to −10 mV range at neutral pH, because the ionizable lipid is uncharged at physiological pH; a much more negative value suggests surface adsorption of anionic payload or a degradation of the PEG-lipid coating.

When DLS reports an unexpectedly large size, the first checks are: sample dilution, the refractive index settings, and the absence of bubbles. A genuine increase in size with time is more concerning than a single high reading and usually indicates aggregation or fusion. Complementary techniques such as nanoparticle tracking analysis (NTA) or cryo-TEM can help distinguish between a few large particles skewing the DLS average and a genuinely broader size distribution.

Determine Encapsulation Efficiency, Payload Recovery, and Integrity

Encapsulation efficiency is most often measured by the RiboGreen assay (for nucleic acid payloads) or by HPLC (for small molecule payloads). The assay compares the dye-accessible (free) payload to the total payload after LNP disruption, giving an EE% that should exceed 85% for a well-optimized nucleic acid LNP. Payload recovery — the fraction of input payload recovered in the final product — should also be tracked, because low recovery can mask a reasonable encapsulation percentage.

Payload integrity is independently checked by gel or capillary electrophoresis for nucleic acids, by HPLC peak shape for small molecules, and by SDS-PAGE or size-exclusion chromatography for proteins. The assay confirms that the purification step has not damaged the cargo and that the measured EE% reflects functional material.

Check Lipid Composition and Particle Morphology Where Needed

Lipid composition is confirmed by LC-MS or HPLC against authentic standards, particularly when working with custom or novel ionizable lipids. Morphology is assessed by cryo-transmission electron microscopy, which preserves the native state of the LNP in vitreous ice and reveals the characteristic electron-dense core, the amorphous bilayer organization, and the absence or presence of payload-containing vesicles. SAXS or SANS can provide complementary information about internal lipid packing, especially when studying new lipid chemistries.

Evaluate Cellular Delivery, Payload Function, and Cell Viability

A brief cell-based functional readout confirms that the formulation actually delivers its cargo. Common readouts include a luciferase assay (for mRNA translation), a GFP or mCherry reporter (for mRNA expression), a probe-based qPCR or bDNA assay (for knockdown in siRNA experiments), or a flow cytometry readout for surface marker expression. Cell viability should be measured in parallel (for example, by ATP-based cell viability assay or a similar assay) at the doses planned for the downstream experiment, because some lipid compositions become toxic at the higher dose ranges used for in vivo work.

How to Troubleshoot Common Problems in LNP Preparation?

Even with careful preparation, most LNP development programs encounter at least one of the following issues during early work. Each is best diagnosed by combining a single physicochemical measurement with a single process change, rather than by changing everything at once.

Large or Variable Particle Size: Check Mixing and Solution Conditions

Particle sizes above the 50–150 nm target usually point to insufficient mixing, too much ethanol in the final dispersion, or excessive lipid concentration. The first check is the mixing parameters — increasing the total flow rate, switching from a Y-mixer to a staggered herringbone mixer, or reducing the lipid concentration in the organic phase will often bring the size down. The second check is the aqueous-to-ethanol phase ratio: lowering the FRR shifts the mean upward, while raising it brings the mean down. The third check is the post-mixing dilution timing — extending the time before dilution typically allows the PEG-lipid to equilibrate and produces tighter distributions.

Low Encapsulation Efficiency: Check Input Ratios and Payload Compatibility

Low encapsulation efficiency is most often caused by an N/P ratio that is too low, an aqueous phase pH that has drifted above 4.5, or a payload that is partially degraded. The first diagnostic is a RiboGreen assay: a low EE% in the presence of a high fluorescence in the free-RNA channel confirms that the cargo is genuinely outside the particle. The corrective action is usually to adjust the N/P upward (by increasing the ionizable lipid fraction or by decreasing the payload concentration), to verify the buffer pH at the time of mixing, and to confirm payload integrity by gel electrophoresis before the next run. For cargo classes that are harder to encapsulate (for example, certain saRNAs, circRNAs, or proteins), a wider ionizable lipid screen via LNP lipid library screening is faster than chasing the same few compositions.

Low Recovery or Aggregation: Check Purification and Handling

A drop in payload recovery, especially after concentration, usually indicates aggregation, sticking to the membrane, or premature cargo leakage. The first check is a visual inspection of the formulation — turbidity that develops over hours or visible particulates indicate aggregation. The second check is the DLS trace over time — a single time-point PDI above 0.3 immediately after preparation is a different problem from a PDI that drifts upward over 24 hours. PEG-lipid density can be increased (for example, from 1.5 to 2.0 mol%) to improve colloidal stability; the anchor length can be switched from C14 to C18 if PEG-lipid shedding is suspected; and the purification conditions can be adjusted to use a buffer with a small amount of sucrose or trehalose to reduce membrane sticking.

Weak Functional Delivery: Check Payload Integrity and Intracellular Delivery

A formulation with good physicochemical attributes and good EE% can still underperform in cells. The most common reasons are payload degradation (despite good EE%), inadequate endosomal escape, or a payload–ionizable lipid mismatch. The first check is payload integrity by gel or capillary electrophoresis — a smear rather than a band signals degradation. The second is a comparison of delivery in the presence and absence of a functional endosomal escape assay, or screening of a small panel of alternative ionizable lipids for the same payload. A specialized LNP endosomal escape evaluation can localize the bottleneck and identify the most promising next lipid to test.

BOC Sciences Support for LNP Preparation and Characterization

A first LNP campaign benefits greatly from working alongside an experienced formulation team. BOC Sciences offers end-to-end support across lipid design, preparation process development, and physicochemical characterization, with services tailored to nucleic acid LNPs (mRNA, saRNA, siRNA, ASO, circRNA, CRISPR RNP), small molecule LNPs, protein and peptide LNPs, and antigen-loaded vaccine LNPs.

Payload-Specific Formulation Design and Lipid Selection

BOC Sciences provides payload-specific formulation design, beginning with a clear understanding of the cargo and target, followed by a rational choice of ionizable lipid, helper lipid, cholesterol, and PEG-lipid. Lipid nanoparticle synthesis is supported by an in-house lipid library, custom synthesis for non-standard chemistries, and excipient screening to identify robust buffers and cryoprotectants. The team's expertise covers the full range of lipid nanoparticles, including ionizable lipid nanoparticles, cationic lipid nanoparticles, and solid lipid nanoparticles for payloads that prefer a hydrophobic matrix.

Preparation Process Development and Encapsulation Optimization

For projects that need controlled, reproducible mixing, BOC Sciences operates a range of microfluidic platforms including SHM, hydrodynamic flow focusing, and Dean flow designs, alongside TFF-based purification and concentration. Lipid nanoparticle manufacturing is supported by design-of-experiments studies that map encapsulation efficiency, particle size, and process parameters across the relevant design space, with options for scale-up as the program matures.

Physicochemical Characterization and Stability Evaluation

The lipid nanoparticle characterization service panel covers particle size and PDI by DLS, zeta potential by ELS, encapsulation efficiency by RiboGreen and HPLC, lipid composition by LC-MS and GC-MS, morphology by cryo-TEM, and short- and long-term stability under defined storage conditions. The LNP critical quality attributes and QC testing workflow aligns the characterization panel with the decision points of the program and supports projects that need to qualify formulations for downstream in vivo studies or for further development.

For programs that have encountered specific bottlenecks, focused services such as LNP transfection troubleshooting and LNP process scale-up can be engaged independently, and nanoparticle functionalization services are available for programs that need targeting ligands, antibody conjugates, or stimulus-responsive coatings beyond the standard PEG surface.