Custom carbohydrate-conjugated LNP development services covering glycan selection, carbohydrate-lipid synthesis, surface functionalization, payload formulation, receptor binding, and functional delivery evaluation.
Carbohydrate-conjugated lipid nanoparticles combine lipid-based delivery with carbohydrate ligands selected for a defined biological interaction. These ligands can range from individual sugars to oligosaccharides, branched glycan clusters, and polysaccharides. They may be covalently attached to a lipid anchor for incorporation during or after particle assembly, or coupled to reactive groups on an existing LNP. This differs from adding soluble sugars solely as formulation excipients.
BOC Sciences helps pharmaceutical and biotechnology teams connect carbohydrate chemistry with practical LNP development. We select the ligand, attachment position, spacer, lipid anchor, and formulation around your target cell and payload. Projects can begin with a new glycan design, an existing carbohydrate-lipid conjugate, or an established LNP that needs an additional targeting feature.
Carbohydrate-Modified LNP Structure IllustrationOur service portfolio covers ligand chemistry, particle engineering, analytical development, and biological evaluation. Each project is organized around a specific delivery objective and agreed comparison criteria, rather than a fixed carbohydrate formulation.
We develop carbohydrate-lipid structures that preserve the glycan features needed for recognition while providing a suitable anchor for LNP incorporation.
We coordinate the incorporation route with ligand presentation so that added carbohydrate does not simply become an inaccessible formulation component.
Carbohydrate modification is developed alongside the core lipid nanoparticle formulation, with the loading strategy selected for the actual payload.
Our LNP characterization strategy connects particle attributes with the amount, accessibility, and retention of the carbohydrate component.
We design biological comparisons that distinguish receptor engagement, internalization, and payload activity.
We develop repeatable preparation and post-processing conditions through coordinated LNP process optimization.
Every sugar addresses a different receptor set, and those receptors sit on different cells. Choosing the ligand before confirming the receptor is the most common reason a carbohydrate-LNP project stalls, so we work in the opposite direction: start from the receptor, then match the glycan. The table below is the working map we use at the start of a project, with the receptors each ligand is normally used for and the applications it tends to serve.
| Carbohydrate-LNP Type | Main Receptor Targets | Typical Applications and Target Cells | Request Information |
|---|---|---|---|
Mannose-Conjugated LNPs | CD206 / mannose receptor (MRC1), DC-SIGN | Used for macrophage, dendritic cell and Kupffer cell delivery studies, CD206+ tumor-associated macrophage work, and antigen delivery in immune activation research, where clustered Man3 or Man4 display at moderate density usually outperforms single mannose at high density. | Inquiry |
Galactose-Conjugated LNPs | ASGPR on hepatocytes, MGL / CLEC10A on macrophages and dendritic cells | Chosen for hepatocyte-directed siRNA and mRNA delivery through ASGPR, for ASGPR-dependence testing against matched unmodified controls, and for macrophage or dendritic cell studies routed through MGL, with lactose often used as the presenting unit because the glucose ring acts as a built-in spacer. | Inquiry |
GalNAc-Conjugated LNPs | ASGPR, MGL / CLEC10A | Applied to hepatocyte gene silencing and hepatic mRNA expression studies, Kupffer cell and monocyte-derived dendritic cell delivery, and head-to-head comparison against galactose formats, most often as trivalent clusters whose spacer length decides whether ASGPR or MGL dominates uptake. | Inquiry |
Glucose-Conjugated LNPs | GLUT-family transporters, with cross-recognition by the mannose receptor | Selected where transport is meant to run through transporters rather than lectins, including brain endothelium transport studies, metabolically active tumor models, and control arms that separate GLUT-driven uptake from mannose receptor recognition. | Inquiry |
Fucose-Conjugated LNPs | DC-SIGN, selectins through Lewis-type epitopes, fucose-recognizing sites on sinusoidal macrophages | Used for dendritic cell-directed antigen delivery, inflamed endothelium models, and liver studies aimed at non-parenchymal cells, with L-fucose presented terminal and α-linked inside a defined epitope so the lectin reads the structure it expects. | Inquiry |
Sialic Acid-Conjugated LNPs | Siglecs on B cells, macrophages and neutrophils; selectins within sialyl LewisX | Applied to Siglec-directed delivery to B cells, macrophages and neutrophils, to leukocyte trafficking models, and to surface designs meant to read as self and lower scavenger clearance, with the α2,3 and α2,6 linkage content specified before synthesis since the two recruit different lectins. | Inquiry |
Hyaluronic Acid-Conjugated LNPs | CD44, HARE / stabilin receptors on liver sinusoidal endothelium | Used for CD44-positive tumor models, tumor stroma work and macrophage phenotype studies, and wherever a hydrated polymer corona is preferred over a PEG shell, with chain length screened deliberately because it shifts both CD44 avidity and sinusoidal clearance. It also fits within tumor-targeted LNP development programs. | Inquiry |
Custom Oligosaccharide- and Glycopolymer-Conjugated LNPs | Set by the epitope displayed, since the motif is built to order | Chosen when a single monosaccharide cannot provide enough affinity, for multi-epitope display across mixed cell populations, and for cases where valency has to be raised along a polymer or dendrimer backbone without pushing particle size up. | Inquiry |
Send us the target cell, the receptor you expect to address, and the payload type. We will propose two or three realistic ligand options with the trade-offs written out.
We select a conjugation route based on four inputs: how much glycan the receptor actually needs, how fragile the payload is, whether the glyco-lipid can survive the self-assembly step, and what happens to the particle over storage. Routes are compared side by side in early screening rather than committed to in advance.
The glyco-lipid joins the organic lipid phase and becomes part of the particle as it forms, using our lipid nanoparticles synthesis workflow. It is a single step with no residual reagents, and the ligand distributes evenly.
Where it fits: Moderate to high target density, uncharged glycans, and projects where the glyco-lipid tolerates the low-pH ethanol or aqueous mixing environment.
Preformed glyco-PEG-lipid micelles are incubated with already-assembled LNPs, typically between room temperature and 65 °C, and insert into the outer layer. Density is set by the incubation ratio, temperature, and time, and is supported by LNP PEG-lipid optimization services.
Where it fits: Projects where a loading process is already established and you want to test several densities without disturbing encapsulation.
Carbodiimide chemistry activates a carboxylate or presents an activated ester such as NHS toward an amine on the particle surface. It runs in water or mixed aqueous buffer with no metal catalyst, available through our nanoparticle conjugation services.
Where it fits: Carboxylated glycans such as sialic acid derivatives and glucuronic acid containing structures, and particles already displaying amine groups.
A thiolated carbohydrate reacts with maleimide-functionalized PEG-lipid already in the particle. The reaction is fast and selective near pH 6.5 to 7.0, Available through our nanoparticle functionalization services.
Where it fits: Quantitative, site-defined coupling where you need to know exactly how many glycans sit on the surface.
Azide-modified sugars react with DBCO-functionalized lipids through strain-promoted cycloaddition, or tetrazine and trans-cyclooctene pairs react through inverse electron demand Diels-Alder chemistry. Both run without copper, which matters for RNA-loaded particles since copper ions accelerate strand breakage.
Where it fits: Post-loading decoration of particles already carrying intact nucleic acid, and projects needing orthogonal control over two different surface features.
Polysaccharides such as hyaluronan, dextran, or pullulan are grafted onto an amine- or carboxyl-displaying shell, or introduced as preformed glycopolymers. The resulting layer behaves more like a hydrated brush than a display layer, which brings it close to the design space covered by our PEGylated lipid nanoparticles.
Where it fits: CD44 targeting with hyaluronan, or cases where a thick hydrophilic shell helps the biological interface more than a short ligand would.
Standard four-component LNPs already deliver reasonably well to the liver after intravenous administration. Adding a carbohydrate is worthwhile when you need more precision than that default distribution gives you, and the four advantages below are where the added chemistry earns its keep.
Enhanced Receptor-Mediated Cellular Targeting
An unmodified LNP reaches hepatocytes largely because adsorbed apolipoprotein E hands the particle to low-density lipoprotein receptors. That route works, but it depends on a protein corona you do not control, and it stops wherever the corona stops. Displaying a glycan adds a second entry route that operates on receptor expression instead of adsorbed protein, so the particle can enter cells that the default pathway ignores, including macrophages and dendritic cells outside the liver sinusoid.
Improved Target Cell Selectivity and Uptake
Selectivity here is a ratio, not an absolute. We measure it as uptake in a receptor-high model against uptake in a receptor-low model, always against an unmodified particle made from the same lipid stock. When a client's first glyco-LNP shows a wide gap between those two conditions, usually combined with a clear drop under calcium chelation or free sugar competition, the increase is genuinely ligand driven rather than a charge artifact.
Tunable Glycan Density and Multivalent Binding
Because each individual sugar-lectin contact is weak, the practical lever is avidity. Clustering three or four copies on a scaffold, then tuning the spacer so they can all reach the receptor, commonly raises apparent affinity by two to four orders of magnitude relative to a monovalent ligand. Density is the same lever from another direction: it lets a single platform cover both low-sensitivity targets and receptors that need crosslinking to internalize.
Expanded Tissue and Cell Targeting Possibilities
Swapping the displayed carbohydrate changes the address without rebuilding the core formulation or redeveloping the loading process. Teams working on several indications can keep one RNA-lipid system and vary only the glyco-lipid component, which keeps formulation knowledge intact across programs and shortens the comparison between targets. This is the practical reason many clients start with a carbohydrate approach before considering larger targeting proteins.
Payload chemistry drives how much surface modification the particle can absorb before loading suffers. We match the conjugation route and glycan density to the payload, then confirm both the particle attributes and the biological readout before any comparison between candidates.
| Payload Type | Carbohydrate-LNP Development Considerations | Request Information |
|---|---|---|
| siRNA | The most common pairing with glycan targeting, since knockdown is a clean readout of receptor-driven entry. Work focuses on encapsulation efficiency, free RNA removal, glycan density, matched unmodified controls, and target transcript reduction in receptor-high and receptor-low models. See our lipid nanoparticles for siRNA delivery capabilities. | Inquiry |
| mRNA and Reporter RNA | Used for receptor-routed expression studies, antigen delivery to dendritic cells, and platform comparisons. RNA integrity after the conjugation step is checked explicitly, because some coupling chemistries nick longer transcripts. Our lipid nanoparticles for mRNA delivery experience informs N/P ratio selection here. | Inquiry |
| circRNA and saRNA | Longer or more structured RNA needs gentler surface chemistry and tighter control of particle growth, since both payload types are sensitive to processing conditions. Supported within lipid nanoparticles for circRNA delivery and lipid nanoparticles for saRNA delivery, with glycan density screened second. | Inquiry |
| miRNA and Antisense Oligonucleotides | Shorter oligonucleotides allow higher glycan input without the same encapsulation penalty seen with long RNA, which suits high-density presentations aimed at lectin crosslinking. Duplex stability and loading are handled alongside lipid nanoparticles for ASO delivery. | Inquiry |
| pDNA and CRISPR RNP Complexes | Large cargoes leave less surface area for ligands, so glycan density per particle needs recalculating rather than transferring from an siRNA project. Cas9 protein and guide RNA combinations are developed through lipid nanoparticles for CRISPR RNP delivery, with pDNA options available separately. | Inquiry |
| Proteins, Peptides, and Antigens | Loading conditions stay mild to preserve conformation, and aggregation during coupling is monitored. Immune-cell directed projects often route through dendritic cell lectins, supported by our work on lipid nanoparticles for antigen delivery. | Inquiry |
| Small Molecules | Hydrophobic and amphiphilic compounds change the assembly balance in ways that interact with glyco-lipid content, so the two are optimized together with attention to leakage and release profile. Development draws on our lipid nanoparticles for small molecule delivery experience. | Inquiry |
| Co-Loaded Payload Systems | Two payloads in one particle complicate both loading order and surface crowding. We evaluate ratio control, particle uniformity, and how each payload responds to the glycan layer, following the approaches used in lipid nanoparticles for co-delivery. | Inquiry |
| Fluorescent and Imaging Labels | Labeling strategy matters here because dyes can compete with the glycan for surface space or alter zeta potential. Once balanced, labeled particles give usable data on uptake, intracellular routing, and distribution trends, supported by our fluorescent-labeled lipid nanoparticles service. | Inquiry |
| Custom or Feasibility-Stage Payloads | For unusual chemistries, conjugates, or early exploratory work we start with a short feasibility study covering payload compatibility, loading route, and whether a glycan layer is likely to survive the process before wider screening begins. | Inquiry |
Carbohydrate-LNP projects rarely fail because of one large mistake. They usually stall because ligand presentation, particle stability, payload loading, and receptor biology pull against each other, and each was optimized in isolation.
✔ Insufficient Glycan Exposure and Receptor Binding
When a glyco-LNP performs no better than the unmodified control, the ligand is usually present but unreachable. Common causes are a PEG layer too long relative to the glycan spacer, a glyco-lipid buried inside the lipid phase, or the wrong anomeric configuration. We lengthen or restructure the spacer, adjust PEG-lipid content, and confirm the change with a lectin accessibility readout, not just with increased input.
✔ Weak Targeting Specificity and Off-Target Uptake
Uptake that is high everywhere means the glycan is not doing the work. Because the default apolipoprotein E route can dominate, we raise accessible glycan density, then verify through nanoparticle in vivo distribution analysis or comparative cell panels whether the ligand, rather than the corona, is driving distribution.
✔ Particle Aggregation After Carbohydrate Modification
Charged glycans are frequent offenders, with hyaluronan and sialic acid both altering the surface enough to change inter-particle repulsion. We track zeta potential through each modification. For a deeper look at the failure mode, our colleagues also support nanoparticle zeta potential analysis and lipid nanoparticle stability assessment.
✔ Reduced Payload Encapsulation and Stability
Surface components competing with the payload for space inside the particle is a structural problem, not a reagent problem. We re-balance the core rather than lowering the glycan level straight away, and work the issue through LNP encapsulation efficiency optimization until both attributes sit in an acceptable range.
✔ Unstable Glycan Linkages and Surface Retention
Two separate losses happen here. The glycosidic bond itself can be cleaved by glycosidases, which argues for thio-linked or C-linked analogues, while post-inserted glycolipids can simply leave the particle during storage. We address the second with payload retention testing for LNP encapsulation and surface glycan measurement taken at several time points.
✔ High Cellular Uptake but Limited Payload Activity
A particle can enter efficiently and still fail if it is trapped and degraded in the endosome, or if the payload was damaged during conjugation. Both are diagnosed rather than guessed at, using LNP endosomal escape evaluation, intracellular localization work, and payload integrity checks on material recovered from cells.
Describe what your current formulation does and does not do. Our team will point to the few measurements that usually explain it, and propose what to screen next.
The conversation starts with the cell population you need to reach, the receptor you believe is available there, and the payload you are carrying, since those three together narrow the ligand field immediately. We also ask what readout you plan to use, because an uptake-only endpoint supports far weaker conclusions than a functional one. That input shapes a practical development plan under our broader targeted LNP development framework.
We then fix the design variables: monosaccharide or cluster, anomeric configuration, spacer length, lipid anchor, incorporation route, and the density range worth screening. Where prior experience predicts a narrow useful window, we say so at this stage and plan variants around it instead of running a wide, unfocused grid.
Candidates are prepared under controlled mixing conditions, drawing on microfluidic LNP production services, staggered herringbone micromixer LNP production, and Dean flow LNP production services depending on batch size. Lipid composition, payload loading, ligand density, and buffer exchange are adjusted against matched unmodified control batches prepared in parallel.
Every candidate is reported on size, PDI, zeta potential, payload loading, and quantified surface glycan, with quality attributes checked through LNP critical quality attributes and QC testing. Biology follows through nanoparticle in vitro evaluation, covering uptake, localization, expression or knockdown, and the control arms needed to attribute the effect to the carbohydrate.
Carbohydrate-conjugated LNPs appear wherever a defined cell population, rather than an organ, is the delivery target. The four areas below account for most projects we receive.
BOC Sciences can help translate your application into a carbohydrate-LNP development plan, from ligand design and conjugate synthesis to formulation, characterization, and model-specific delivery evaluation.
Challenge: A research group working on hepatocyte gene silencing asked us to improve a lactosylated LNP that had stalled. The formulation showed only about 1.4-fold higher uptake than their unmodified control, and adding ligand had cost them encapsulation, which fell from roughly 82% to 61% along with a rise in PDI to 0.28. They needed hepatocyte selectivity without rebuilding their siRNA program.
Diagnosis: Three issues were identified. The galactose head group sat too close to the particle surface to reach the receptor's binding pocket; total glyco-lipid input at 5 mol% was disrupting assembly; and the assay was run in serum, so apolipoprotein E driven uptake masked whatever the lactose was contributing.
Solution: We ran a focused screen rather than a wide one. Twelve variants were prepared covering lactose, galactose, and GalNAc head groups; PEG12, PEG24, and PEG1000 spacers; and inputs of 1, 2.5, and 5 mol%. Each was evaluated for particle attributes, encapsulation, and surface accessibility using a galactose-specific lectin probe, then tested in ASGPR-positive hepatocyte models under both serum-free and serum-containing conditions with free galactose competition as the mechanistic control.
Result: Lactose on a PEG24 spacer at 2.5 mol% was the strongest candidate. The selected formulation measured around 82 nm with PDI near 0.14, and encapsulation recovered to approximately 88%, confirmed through efficiency testing for LNP encapsulation. Uptake reached roughly 4.2-fold over the unmodified control under serum-free conditions, fell by about 65% when free galactose competed for ASGPR, and produced around 78% knockdown against 31% for the unmodified particle. In serum, advantage narrowed noticeably, and we reported that explicitly so the client could plan their next model accordingly.
Challenge: A team studying inflammatory signaling in the liver needed siRNA delivered to Kupffer cells rather than hepatocytes. Their first-generation galactose LNP behaved like a hepatocyte particle, and a mannose version they tried went to both myeloid populations and hepatocytes, so the two uptake routes were impossible to separate in their readouts.
Diagnosis: Two problems, one chemical and one biological. The monovalent galactose ligand was too weak and too sparsely displayed at 1 mol% to compete with default clearance routes. Biologically, the relevant macrophage receptor in this setting is MGL rather than ASGPR, and MGL prefers terminal GalNAc held on an extended spacer.
Solution: We synthesized trivalent galactose and trivalent GalNAc clusters on lysine scaffolds with PEG24 spacers, then compared them with the original monovalent ligand at 1, 3, and 6 mol%. Candidates were assessed through nanoparticle cellular uptake testing in Kupffer and hepatocyte models, alongside MGL blocking antibody, excess mannose competition, EDTA chelation to check lectin dependence, and nanoparticle intracellular localization detection to confirm routing after internalization.
Result: The trivalent GalNAc variant at 3 mol% was the one worth keeping. It measured roughly 88 nm with PDI near 0.16 and encapsulation around 85%. Uptake in the Kupffer model reached about 3.6-fold over unmodified LNP, dropped by 58% when MGL was blocked, and barely responded to mannose competition, indicating the two route claims were genuine rather than overlapping. Target transcript knockdown was around 62% versus 24% for the unmodified control, while hepatocyte uptake stayed low. We also flagged that this variant showed a narrower storage window than their original formulation, which they took into account for downstream work.
Extensive Carbohydrate and Lipid Raw Material PortfolioBOC Sciences connects carbohydrate building blocks, lipid components, spacers, and coupling reagents with custom development. This material selection supports comparisons across ligand structures and lipid anchors, with sourcing reviewed against each project's structural requirements.
Tailored Glycan Structures and Precise Surface Density ControlWe coordinate glycan identity, linkage, valency, spacer, and anchor selection with formulation screening. Surface-density development includes analytical verification of incorporation and accessible presentation, rather than relying only on the amount added during preparation.
Versatile LNP Formulation Expertise Across Payload TypesWe adapt development to the payload instead of applying one formulation to every project. Loading conditions, processing, analytical methods, and functional assays are selected around the characteristics of the RNA, protein, peptide, small molecule, or custom cargo.
Comprehensive Receptor-Targeting and Functional Delivery EvaluationOur evaluation strategy links receptor binding with cellular internalization and payload activity. Matched formulations, relevant nontarget cells, and mechanism controls help clients distinguish a useful targeting contribution from nonspecific particle uptake.
Flexible Formulation Screening and Process OptimizationProjects can address a single bottleneck or connect ligand synthesis, formulation, characterization, and biological evaluation. Screening breadth and follow-up work are adjusted to the results, providing a practical basis for candidate selection and repeat preparation.
Carbohydrate ligands for LNP surface engineering can include mannose, galactose, GalNAc, glucose, fucose, sialic acid, hyaluronic acid, defined oligosaccharides, and glycopolymers. Selection should not rely on the sugar name alone. Receptor expression, glycosidic linkage, ligand valency, attachment position, spacer length, and surface presentation can all influence recognition. For example, GalNAc and selected galactose structures are often investigated for ASGPR-related hepatocyte targeting, whereas mannose-containing ligands may be explored in selected macrophage or dendritic cell models. For new projects, comparing several ligand architectures and surface densities is usually more informative than committing to one carbohydrate structure at the beginning.
No. Increasing carbohydrate density can enhance multivalent receptor interactions, but excessive ligand loading may also create steric crowding, alter PEG shielding, increase particle size, promote aggregation, or reduce payload delivery. Ligand density is therefore best treated as an optimization variable rather than a parameter that should be maximized. A useful development study compares several carbohydrate densities while measuring total ligand incorporation, receptor-accessible surface display, particle properties, receptor binding, cellular uptake, and payload function. In some systems, an intermediate ligand density can outperform a highly decorated surface because it preserves both receptor accessibility and favorable LNP physicochemical properties.
Increased cellular fluorescence or particle uptake alone does not establish carbohydrate-mediated targeting. A more informative study includes matched unmodified LNPs, several carbohydrate densities, receptor-high and receptor-low cell models, and competition or receptor-blocking controls where appropriate. Functional delivery should also be measured, such as siRNA-mediated knockdown, mRNA expression, or another payload-specific response. Combining glycan surface-accessibility data with receptor-binding measurements, cellular internalization, intracellular localization, and payload activity helps determine whether the carbohydrate ligand contributes meaningfully to delivery rather than simply increasing nonspecific nanoparticle association with cells.
Yes. BOC Sciences can design a carbohydrate-ligand screening strategy around the client's target receptor, cell model, payload type, and existing LNP formulation. Supported options can include mannose, galactose, GalNAc, sialic acid, hyaluronic acid, custom oligosaccharides, and glycopolymers. We can also compare co-assembly, carbohydrate-PEG-lipid post-insertion, amide coupling, thiol-maleimide coupling, and copper-free click conjugation. Spacer length, lipid anchor, ligand valency, and surface density can be screened in parallel so that ligand chemistry and particle performance are optimized together rather than as separate development steps.
BOC Sciences provides integrated carbohydrate-LNP development from ligand design through functional delivery evaluation. Services can include carbohydrate and lipid raw material selection, custom carbohydrate-lipid conjugate synthesis, LNP surface functionalization, ligand-density optimization, payload encapsulation, formulation screening, and physicochemical characterization. We can also evaluate carbohydrate incorporation, receptor-accessible surface display, receptor binding, cellular uptake, intracellular localization, and payload-specific function. When projects encounter issues such as aggregation, poor glycan exposure, reduced encapsulation, unstable surface retention, or high uptake with limited activity, our team can investigate the bottleneck and adjust conjugation, formulation, or process parameters accordingly.
