Current and Near-Future Technologies to Quantify Nanoparticle Therapeutic Loading Efficiency and Surface Coating Efficiency with Targeted Moieties.

Most nanoparticles injected into the body are expected to accumulate at inflamed or cancerous sites through enhanced permeability and retention (EPR) effects, a process known as passive targeting [ 32 ]. However, active targeting nanoparticles, equipped with additional targeting motifs, provide an extra layer of specificity by binding directly to targeted sites. This added precision is crucial when EPR effects are insufficient or absent, ensuring effective delivery and treatment in such cases. Active targeting nanocarriers can be tailored to treat specific diseases where overexpressed biomarkers are detected. There are many proposed benefits for this class of nanoparticles, such as reduced drug side effects, less off-site targeting, and less invasive treatment. In some cases, active targeting drug delivery systems can be paired with minimally invasive delivery systems such as IV injection, which can mitigate possible complications from alternative invasive procedures. Targeted nanoparticles have shown promise in various research applications. Scientists have been discovering biomarkers in various cancers, which have led to the engineering of targeting ligands that can selectively bind to cancer cells. This enables the precise delivery of therapeutic agents directly to the tumor, enhancing treatment effectiveness and reducing side effects compared to traditional chemotherapy strategies. For instance, 5-Fluorouracil was effectively delivered using nanocarriers coated with hyaluronic acid to specifically target the CD44 receptor in breast cancer [ 33 ]. Another targeting molecule for cancer is human epidermal growth factor receptor-2 (HER2) [ 34 , 35 ]. Additionally, a biomimetic macrophage membrane-coated nanoparticle featuring a synthetic D-form oligopeptide exhibits a strong affinity for the insulin-like growth factor 1 receptor (IGF1R), which is notably overexpressed on tumor cells [ 36 ]. Folic acid, a commonly used ligand in cancer therapy, has also been employed in various formulations such as liposomes, chitosan nanoparticles, and silica nanoparticles for cancer treatment [ 37 , 38 , 39 ]. Targeting nanoparticles are also being investigated as a promising strategy to manage cardiovascular diseases and to eliminate the complications of surgical intervention. For example, macrophage mannose receptors (MMRs) and high-density lipoproteins (HDLs) were employed for targeting macrophages at plaque sites and providing a new therapeutic strategy [ 40 ]. Nanoparticles commonly employ targeting moieties such as CD47 and Integrin α4/β1, which effectively target endothelial cells at damaged sites and facilitate successful evasion from macrophages [ 41 , 42 ]. EPR effects with metal particles may have higher side effects and pose a greater risk of off-site targeting. When reaching the vascular bed of an organ, small molecules can diffuse into tissues, whereas the nanoparticles are much larger and must enter cells across tissue barriers through specific uptake mechanisms. Targeting nanoparticles can also be used for osteoporosis to accumulate on bone regions to promote the regeneration of bone and minimize side effects, which is more beneficial compared to current medications or surgical intervention [ 43 ]. In targeting drug delivery for a condition such as osteoporosis in the elderly that does not have a blood–tissue barrier, reducing drug uptake in non-skeletal tissue is crucial [ 44 ]. Iron oxide NPs coated with dextran (Dex) and bisphosphonate (Bis) have been used for thermotherapy as treatment for osteoporosis, successfully targeting bone tissue [ 45 , 46 ]. Additionally, human microvascular endothelial cell (HMEC) membranes overexpressing CXCR4 have been utilized to create stem-cell-mimicking particles with targeting capabilities for osteoporosis [ 47 ]. Moreover, selective phage peptides such as SDSSD were incorporated into polyurethane nano-micelles to target osteoblasts for osteoporosis treatment [ 48 ]. Overall, targeting nanoparticles have been continuously developed as a potential treatment for various diseases to overcome the current treatment limitations. The targeting system, an advanced platform for drug delivery in nanotechnology, offers a diverse array of material and structural designs to efficiently deliver therapeutic payloads to desired locations as needed. The targeting nanocarrier has three main compartments: cargo, payload, and targeting ligands ( Figure 1 ). We discuss each component in detail in the next paragraphs. Cargo carriers . Extensive research in the field of nanomedicine has demonstrated that incorporating cargo to load free drugs can have many superior benefits compared to free drugs by themselves. The advantages include protecting the drug from degradation in the bloodstream, improving the drug solubility, increasing drug stability, and controlling drug release [ 49 ]. There are a variety of choices of materials that make up nanocarriers and altering the material of the nanocarrier can tune the desirability of the nanosystems. These cargos can be made from traditional synthetic materials such as polymers, silica, hydrogels, lipids, and dendrimers, or they can originate from biological sources such as virus capsids or exosomes [ 50 , 51 ]. Synthetic materials allow for ease in modification and optimization of the nanocarriers, while the use of nanoparticles from biological sources can create stealth effects, which can reduce immune responses to the cells. Alternatively, they can be composed of inorganic nanoparticles, such as those based on metals including silver, zinc, gold, iron, or silica [ 52 ]. Tuning these materials to a desired size can also extend the circulation time, improve cellular uptake, and enhance the permeability and retention (EPR) effects [ 53 ]. In addition, the use of nanocarriers can help co-deliver multiple agents for some combination therapies [ 54 ]. Some cargos can be made from smart materials that are responsive to a certain stimulus such as temperature, pH, enzyme, and/or ultrasound [ 55 ], to help to deliver chemotherapy drugs to tumor sites. Payloads . The second component is the drug load encapsulated or carried by the nanocarriers, which can be any therapeutic compound, including small molecules, proteins, or genetic compounds such as ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) for gene therapy. Sometimes the payload cannot be delivered to the target site by traditional delivery methods such as oral delivery or injection; therefore, incorporating nanocarriers into these payloads would provide many benefits. The payloads can be toxic or may not have the capability to reach the site of interest when delivered as a free drug. For example, a chemo drug by itself does not have targeting specificity, is highly toxic, has rapid clearance, and can induce a lot of side effects in other healthy cells [ 56 ]. Currently, gene therapy is a cutting-edge approach in the field of nanomedicine. However, these genetic materials, such as DNA, RNA, ribozymes, and oligonucleotides, and the gene editing tools such as CRISPR cannot deliver themselves to the cytosol or the nuclei for transfection to occur [ 57 ]. Due to the toxicity of certain chemicals and difficulties in targeting certain therapeutics, utilizing nanoparticles as a carrier can eliminate these disadvantages. Targeting ligands. The most important component enabling this class of drug delivery systems to achieve active targeting effects is the ligands on the nanoparticle surface. Antibodies are commonly used as targeting agents incorporated into nanoparticles. For example, CD63 has led to the reduction of myocardial infarction by local delivery of exosomes or targeting CD147 to deliver doxorubicin for hepatoma therapy [ 58 , 59 ]. Peptides, saccharides, and small molecules represent another promising class of ligands for directing drugs to their targets. They offer advantages such as ease of modification, cost-effectiveness, and greater stability compared to antibodies due to their simple structures [ 60 ]. Antibodies are susceptible to denaturation during the conjugation process owing to chemical reactions. Notably, anti-PD-L1 peptide CLQKTPKQC, or the abbreviated D-peptide antagonist of PD-L1 (DPPA), has exhibited promise in targeted cancer immunotherapy [ 61 , 62 ]. Similarly, cyclic peptides such as cRGD have been shown to target integrin αvβ3 for the treatment of cancer or thrombotic diseases [ 63 , 64 , 65 ]. Aptamer, a short single-stranded oligonucleotide, can specifically bind to target molecules by forming three-dimensional structures and has been employed in nanotechnology. Recently, AS1411 aptamer has been used as a cancer targeted therapy and in magnetic resonance imaging using magnetic mesoporous silica nanoparticles [ 66 ]. DNA aptamer AP1153, which exhibits high affinity for the CCK-B receptor (CCKBR) found on pancreatic tumor cells, has been conjugated to nanoparticles [ 67 ]. This bioconjugation has resulted in increased uptake and enhanced specificity in both tumor imaging and therapeutic treatment [ 67 ]. In the new class of drug delivery systems, nanocarriers can also be coated with cell membranes that have been inherently or genetically modified with ligands [ 68 ]. While nanoparticles hold much promise, they can still be perceived as foreign entities by the immune system. To overcome this challenge and avoid immune recognition and nonspecific uptake by immune cells, researchers have shifted their focus to cell-mimicking nanoparticles. These nanoparticles capitalize on either the inherent mechanisms of cells or engineered designs. They often possess natural targeting abilities or a high concentration of adhesion molecules, enabling them to reach the affected or activated tissues more effectively and target specific sites with greater precision. For instance, T-cell membranes engineered with a chimeric antigen receptor (CAR) targeting HER2 or engineered with CD80 have been utilized to coat nanoparticles for cancer treatment, achieving the successful delivery of anticancer agents and fostering anticancer immunity [ 35 , 69 ]. In addition to that, erythrocyte or platelet membranes can be employed to fabricate cell-mimicking nanoparticles [ 70 , 71 , 72 , 73 ]. Furthermore, biomimetic nanoparticles coated with activated macrophage or neutrophil membranes have shown promise in targeting cells in the treatment of various conditions, including osteoarthritis, cancer, infectious diseases, and cardiovascular diseases [ 74 , 75 , 76 ]. Taken together, these three key components for active targeting delivery, that is, the carrier, payload, and targeting ligands, can be combined into a rich variety of possible therapeutic vehicles, as summarized pictorially in Figure 1 . These targeted nanoparticles enhance therapeutic effects locally and specifically to the targeted sites for a wide range of therapeutic applications, including cancer, cardiovascular, and infectious diseases. Although targeting nanoparticles demonstrate superior potential in drug delivery, no targeting nanoparticles have been reported for clinical use due to many possible reasons. One of them is that nanoparticles, especially biological nanoparticles, do not have standardized processing and characterization methods. Quality control of nanomaterials can help to achieve the repeatability, determine progress efficiency, examine the activity, and ensure the safety of the product [ 15 ]. Better quality control of nanoparticles can lead to more homogenous NP formulations that could result in better outcomes in vitro and in vivo [ 16 , 17 ]. However, current quality control for nanoparticles has no standardized physicochemical characterization [ 18 ] and relies on ensemble-average (bulk analysis) studies, which do not provide in-depth information about possible inconsistencies in drug loading and surface coating during NP production. A case study showed that the batch-to-batch inconsistency in the PEGylation coating of gold nanoparticles results in different results in vivo [ 19 ]. Another study showed that different traditional techniques that have been used to record the amounts of drug content are not consistent and can result in inconsistencies in reported data [ 20 ]. In general, the process of generating nanoparticles with adequate drug loading and targeting moiety coating is complicated, and it is still challenging to assess the quality of these nanoparticle formulations. Currently, we do not know how many ligands can be attached per nanoparticle, nor do we know the fractions of coated and uncoated NPs, or even partially coated nanoparticles, per solution. Adequate quality control can help minimize the dosage of materials and drugs used and maximize the efficiency of drug delivery systems, thereby also reducing possible drug side effects. There is a need to strengthen the characterization methods that can push the translation progress of targeted nanoparticles [ 21 ].

The field of nanomedicine is rapidly advancing, and as the complexity of nanoparticles grows, more sophisticated technologies will need to be developed for characterizing these nanoparticles. There are still many gaps in standardizing the characterization of heterogeneous formulations for particle therapeutic loading and targeted moiety coating. Several key shortcomings of bulk solution analysis technologies are summarized in this work. These shortcomings are beginning to be addressed by emerging single-nanoparticle characterization technologies. However, there is still a lot of space for improvement, as well as room for opportunities for new methods to expand into this space. There are currently no methods to quantify both nanoparticle loading and coating at the single-nanoparticle resolution at high throughputs. It is also not clear how this information, once attained, could be actionable for improving nanoparticle preparation heterogeneity. It is also not clear what level of detail needs to be known about preparation before that knowledge results in successful translation into pre-clinical trials and human use. Nevertheless, the value of these new methods is potentially immense and is likely to be crucial for scientists to improve the quality of nanoparticle preparations in a quantifiably reproducible manner. The following are emerging technologies that can help characterize single-nanoparticle characterization. Nanopore-based technologies: Label-free, single-molecule nanopore sensing has been expanding for the sequencing of nucleic acids and protein-based analytes [ 185 , 186 ], but it has recently also shown potential for characterizing nanoparticles [ 187 , 188 ]. In this technique, nanoparticles pass one at a time through a nanopore drilled into a thin dielectric material. The pore diameter is made to be slightly larger than that of the nanoparticles, but not much larger, so that during transit of the nanoparticle through the pore, the pore current is transiently blocked, resulting in a resistive pulse detected by a high-sensitivity voltage clamp system. The recorded fluctuations in current time-series data can be analyzed to provide indirect information on nanoparticle size, shape, surface charge, and other properties. As this technology can detect and analyze individual nanoparticles, it can assess heterogeneity within nanoparticle populations. This information can be beneficial to drug delivery applications, where understanding the uniformity and specific attributes of nanoparticles can significantly impact their therapeutic performance. Additionally, this is a label-free method, avoiding the need for additional chemical modifications that could alter nanoparticle behavior. Therefore, expanding this technology for studying nanomedicine can provide a powerful tool for rapid screening and quality control at a single-nanoparticle resolution. Plasmonic nanopores represent a more recent evolution in nanopore technology, where optical measurements can be collected concurrently with electrical signals during nanoparticle translocation through the pore. Plasmonic enhancement of light intensity can help increase the fluorescence emission of labeled particles, or it can be used for both label-free sensing and optical trapping [ 189 ]. In more recent work, plasmonic optical sensing has been combined with alternating current (AC) electrical sensing [ 188 ]. The premise of the latter is that a nanoparticle is considered as a spherical capacitor that will not conduct DC current through it but will conduct AC current in a frequency-dependent manner. Therefore, AC frequencies can be used to probe the interior of nanoparticles with different levels of sensitivity; DC current mostly probes nanoparticle size and coating. Overall, the integration of AC sensing techniques into single-nanoparticle characterization protocols holds great promise for advancing the development and application of nanoparticle-based drug delivery systems. Mass photometry: Mass photometry, commercialized by Refeyn (Oxford, UK), can be used to measure the molecular mass of single analytes such as proteins, nucleic acids, vesicles, and micelles. It can also be utilized for studying the biomolecular interactions such as protein–protein interactions or protein–DNA interactions [ 23 ]. Furthermore, it can be applied for characterizing AAV gene therapy vectors. Moreover, it has been implemented for SARS-CoV-2 research to study the oligomerization of the SARS-CoV-2 spike protein and the stoichiometry of its generation from the quantified light scattering from single-molecule analytes in solution, revealing the true molecular mass ranging from 30 kDa–5 MDa. For this technique, a beam of light is shone to a single-molecule analyte on the measurement surface, which results in a light scattering signal in which light is scattered by the molecule and light is reflected by the measurement surface, and this signal is proportional to the mass of a molecule. This method is advantageous because it is label-free, can be used in solutions, reveals molecular heterogeneity, and requires only a minimal amount of sample. Real-time NTA: Nanolyze (Mölndal, Sweden) has commercialized label-free image-based real-time NTA with a single-nanoparticle solution that can be used for size estimation and cargo loading of nanoparticles. The mRNA cargo loading heterogeneity of lipid nanoparticles is also a key quality indicator that determines the effectiveness of LNP-based therapy. This technology can also be used to study the interaction and structural changes in many biological and physical processes of liposome–liposome fusion, single-virus infection, nanoparticle aggregation, and protein–lipid interactions. Atomic Force Microscopy-Infrared Spectroscopy (AFM-IR): Bruker Corporation (Billerica, MA, USA) has commercialized an AFM-IR tool for mapping and evaluating drug distribution within individual nanoparticles. This label-free, single-nanoparticle technique has been used to quantify the amount of cancer drug loaded within PLA nanoparticles with high precision [ 190 ]. Specifically, this technique quantified the drug mass fraction with a standard error of 5–6% and was able to quantify the chemical homogeneity at the nanoscale (10–20 nm) level. Importantly, the results of this analysis showed large drug load heterogeneities within nanoparticles, with only a small nanoparticle fraction being fully loaded with drug [ 190 ]. Inductively Coupled Plasma Mass Spectrometry (ICP-MS): Commercialized by PerkinElmer (Waltham, MA, USA) and Thermo Fisher Scientific (St. Bend, OR, USA), ICP-MS is particularly useful for bioassays involving metallic nanoparticles, offering high sensitivity and the ability to quantify drug load without complex signal amplification. Using this technique, one can obtain the nanoparticle size, size distribution, number density, mass concentration, mass agglomeration, and nanoparticle composition at low concentrations [ 191 ]. Biolayer Interferometry-Surface Plasmon Resonance (BLI-SPR): The commercialized Octet System from Sartorius company (Göttingen, Germany) is a label-free biosensor that can be used to characterize various samples such as antibodies, proteins, viruses, DNA/RNA, virus-like nanoparticles, etc., which can aid in studying the interaction between analytes, helping in the exploration of drug discovery and vaccine research. This system combines the technologies of Biolayer Interferometry (BLI) and Surface Plasmon Resonance (SPR), and this system provides real-time label-free measurements, which reveal information about the binding kinetics and affinity and can be used to determine the active concentration of an analyte by measuring the dissociation and dissociation rates. Furthermore, one of the advantages of this system is that it can provide fast quantification of up to 96 samples in 2 min, and there is no need for a pre-analysis purification step compared to current techniques such as HPLC and ELISA. The Octet system was able to distinguish the difference in binding kinetics of different monoclonal antibodies to treat non-Hodgkin’s lymphoma.

Nanoparticles (NPs) are engineered nanosized systems that can capture various therapeutic payloads such as small molecules, proteins, and nucleic acids [ 1 ]. The use of NPs for drug formulations can improve the therapeutic efficacy of the drug due to their capability to control the dosage, deliver site-specific targeting, enhance bioavailability, reduce toxicity, minimize side effects, and improve patient compliance [ 2 , 3 ]. Due to their superior delivery performance compared to free drugs, the field of nanomedicine has been continuously explored since the 1960s [ 3 ]. Doxil, a liposome loaded with doxorubicin, was the first NP to be approved for the treatment of cancer by the Food and Drug Administration (FDA) in 1995 [ 3 , 4 ]. Since then, research on NPs has expanded greatly with many new classes of NPs that are coated and/or loaded with novel agents to improve the efficiency of nanoparticle-mediated therapies. This review focuses on the current status, challenges, and future prospects of drug/gene delivery NPs, especially the characterization of the efficacies of the payload encapsulation and targeted ligand coating, whereas the other aspects of targeted drug delivery are addressed elsewhere [ 5 ]. Active targeting NPs are coated with moieties (peptides, antibodies, aptamers) that bind with high specificity to diseased tissues, which have upregulated expression of the targeted biomarkers [ 6 ], and selectively deliver their payload at the diseased sites. As specific targeting can enhance cellular uptake, this strategy has been investigated for a wide range of applications, such as cancer therapy, cardiovascular disorders, and infectious diseases [ 7 , 8 , 9 ]. Although NP types and their applications continue to expand, this technology remains challenging in its translational aspects. Since 2019, only a few NPs have been officially approved by the FDA or the European Medicines Agency (EMA) [ 10 ]. In addition, despite the proposed advantages, no active targeting NPs have moved past clinical trials [ 11 ]. Due to their more complex design, the production process of active targeting NPs faces more challenges in scale-up production and batch-to-batch consistency [ 11 ]. In order for the products to be more reliable, they require more characterization steps and a longer development timeline, which increases costs [ 11 ]. Incorporating genetic materials with NPs for gene therapy is another strategy of scientists to enhance delivery efficiency, reduce toxicity, and increase the cell targeting. Gene therapy has several advantages compared to other therapies since the main goal of this strategy is to address the root cause of the disease. Genetic materials such as RNA and DNA can be loaded inside viral or non-viral vectors to be delivered specifically to the cytosol or nuclei of cells to transfect the cells. Some notable NPs for gene therapy are mRNA lipid nanoparticles (LNPs) for COVID vaccines from Pfizer and Moderna and Patirisan to treat hereditary transthyretin [ 12 , 13 ]. Extracted exosomes, which naturally carry genetic materials, are also a cutting-edge strategy [ 14 ]. Despite their novelty, not a lot of nanoparticle types for gene delivery have been approved to date, with the main reasons being challenges with scale-up in production, batch-to-batch consistency, and associated costs. These widely used NPs are passive, and there is a lack of targeted commercial NPs. The accurate characterization of nanoparticle formulations can help determine the repeatability and process efficiency, improve therapeutic activity, and ensure the safety of the product [ 15 ]. Better characterization of NPs can lead to more homogenous NP preparations to reduce the risks of dose-dependent cytotoxicity and genotoxicity that have been observed in vitro and in vivo [ 16 , 17 ]. However, current characterization methods for NPs rely on ensemble-average (bulk analysis) studies, which only report average measurements over large numbers of nanoparticles. For example, the commonly used dynamic light scattering (DLS) method is not efficient at analyzing complex, polydisperse nanoparticle suspension [ 15 ]. DLS can create bias because scattered light from large-size particles tends to dominate over the signal of smaller particles in the sample [ 15 ]. Current limitations of targeted nanoparticle characterization are the inconsistency in the drug content loading and surface modification uniformity during production due to a lack of standardized physicochemical characterization procedures [ 18 ]. A case study showed that batch-to-batch inconsistency of PEGylation coating on gold nanoparticles resulted in different results in vivo [ 19 ]. Additionally, a comparison study showed that different traditional techniques that have been used to record the average amount of drug content reported inconsistent data [ 20 ]. Furthermore, quality control methods for nanoparticle coatings with targeted ligands or nanoparticles with payloads have many weaknesses. Currently, we do not know how many ligands are, or can be, attached per nanoparticle, nor do we know the ratio between coated and uncoated nanoparticles. Additionally, we currently do not have any characterization tools to quantify the payload for a single nanoparticle, and direct methods for quantifying the payload are still lacking. Clearly, there is a lack of adequate quality control at the present time to maximize the therapeutic efficiency of drug delivery systems and to minimize drug side effects while also reducing the wastefulness of drugs and targeting ligands used and reducing production costs. Therefore, there is a need to improve quality control for targeted nanoparticles and to help push the translation progress of nanotechnology into the clinic [ 21 ]. A recent positive development is the invention of single-molecule and single-particle characterization assays that can provide far richer information compared to their ensemble-averaged counterparts. For example, Refeyn’s mass photometry or Nanolyze devices are powerful methods for characterizing a variety of analytes, including proteins, nucleic acids, viruses, and the initial drug delivery systems such as vesicles, micelles, and adeno-associated (AAV) vectors [ 22 , 23 , 24 , 25 , 26 , 27 , 28 ]. This label-free technology provides detailed information on the true molecular mass and molecular heterogeneity of the analytes, which may be obscured when using ensemble methods such as DLS. Single-molecule analysis can provide some information that ensemble-average analysis cannot provide such as heterogeneity and stochastic variability [ 29 ] and complex chemical kinetics [ 30 , 31 ]. One of the benefits of single-molecule analysis is that it can detect rare events that can be lost on ensemble-average analysis [ 29 ]. The rare events can be nanoparticles that are too large to be utilized or nanoparticles that do not have any coating or loading. The advantage of having a full distribution rather than just having a mean value measured is that it can reveal the quality of each batch and help improve the scalability, which can potentially help to transition to the clinic better. Therefore, developing new techniques for single-molecule analysis can provide a complementary system to help overcome the limitations of traditional ensemble techniques. In this work, we review both traditional and state-of-the-art methods for characterizing nanoparticles, including quantifying drug contents and surface modification, emphasizing the need for more precise and accurate measurements such as single-molecule characterization. Additionally, we aim to identify the challenges associated with these methods and propose potential solutions for facilitating nanoparticle transitioning into the clinical setting. Lastly, we hope that this review will provide insights that assist scientists in selecting the most suitable characterization technologies for their needs.

There are many methods to modify nanoparticle surfaces to enable targeting for specific applications. Nanoparticles can be functionalized with ligands such as antibodies, peptides, and aptamers through different conjugation chemistries [ 6 , 168 , 169 , 170 ]. Some nanoparticles can be coated with biomimetic membranes that have ligands of interest. Ligand types, conjugation strategies, ligand orientations, and densities are the crucial parameters associated with active targeting nanoparticles [ 171 ]. However, ligand density is the parameter that is usually underestimated [ 171 ]. A higher ligand density per particle can lead to a higher probability of binding to the target [ 171 ]. However, a higher targeting ligand density can also have some disadvantages at the particle, cellular, and systemic levels [ 171 ]. At the particle level, a high ligand density can lead to an increased size, lower diffusion coefficient in biological matrices, and lower colloidal stability. At the cellular level, a high ligand density can lead to steric hindrance that inhibits receptor binding or a high consumption of cellular receptors per binding event. Lastly, at the systemic level, a high ligand density can lead to decreased stealth characteristics, increased opsonization, and increased RES clearance [ 171 ]. Although there are reported methods to help control the number of ligands per nanoparticle, there is no easy method for ligand quantification [ 171 ]. We will discuss more specifically the current methods that rely mostly on bulk detection and the more innovative single-molecule methods have been developed to quantify the density on each single particle. The most common method to quantify the conjugation density is through bulk detection, which will roughly quantify the amount of conjugates/coating, and the average number of ligands per nanoparticle can be estimated. In bulk detection, there are two methods to confirm the conjugation density, through direct or indirect methods. The indirect method quantifies the content of ligand that remained in the byproduct solution during the bioconjugation or coating process. The byproduct solution and the conjugated product will be separated via various separation techniques such as centrifugation. The content of the unbound ligand in the byproduct solution will be quantified and will be subtracted from the initial amount of ligand added. The other method is direct quantification, where the conjugated nanoparticles can be directly measured. Most of the reported research quantifications are based on indirect measurement. Nanoparticles are usually incubated with ligands in a solution that allows the conjugation to happen. The population of nanoparticles and the bound conjugates are separated from the unbound conjugates. The unbound conjugates in the remaining solution will be quantified using quantitative methods such as direct UV/VIS or with colorimetric assays (BCA assay, Bradford assay), HPLC, etc. Indirect quantification of the conjugation, such as with the BCA assay, usually results in an overestimation of conjugates on nanoparticles [ 172 , 173 ]. The traditional method for quantifying targeting ligands may not be suitable for biological nanoparticles such as liposomes, as they cannot withstand harsh separation techniques. Therefore, direct quantification would be a more desirable method for quantifying loading. Fluorescence-based methods have been used to directly quantify antibodies immobilized on gold nanoparticles. Antibody-modified gold nanoparticles were treated with potassium iodide (KI) and iodine (I 2 ) etchant to dissolve the gold nanoparticles. A desalting spin column was used to recover the antibody released from the nanoparticles, and NanoOrange, a fluorescent dye, was used to quantify the antibody. We determined that 309 ± 93 antibodies adsorb onto a 60 nm gold nanoparticle (2.6 × 1010 NP mL) [ 173 ]. Enzyme-mediated assays can be used to quantify the fraction of immobilized antibodies that arcche accessible for antigen binding. Anti-horseradish peroxidase (anti-HRP) antibody is mixed with AuNPs to allow for conjugation, and the unbound, excess antibody is quantified with a modified Bradford assay to determine antibody loading onto AuNPs. The conjugates are then mixed with excess HRP to saturate all accessible binding sites, and bound HRP is quantified based on the enzymatic reaction rate [ 174 ]. NMR spectroscopy can be used to confirm ligand immobilization on nanoparticles [ 175 , 176 ]. It can provide both quantitative and qualitative data that can be used to characterize the successful modification of nanomaterials by ligands, differentiate between bound and unbound ligands, and quantify bound ligands. NMR data can help in understanding the ligand binding mode and dynamics of the bound ligands and in studying the interactions of surface-functionalized nanomaterials with biomolecules to help infer ligand structure [ 175 ]. IR spectroscopy can also be used to infer ligand structure [ 175 ]. In the analysis of nanomaterial surface functionalization, IR spectroscopy is primarily used to confirm the functionalization of nanoparticles by comparing to the spectrum of the free ligand [ 175 ]. There are several other characterization methods that can be used for quantifying ligand structure and confirming its presence on nanoparticles such as Surface Enhanced Raman Spectroscopy (SERS), Scanning Tunneling Microscopy (STM), Small-angle neutron scattering (SANS) microscopy, and X-Ray Diffraction Spectroscopy (XRD) [ 175 ]. XRD can not only analyze ligand structure and conformation but can also map the position of the surface ligand on nanoparticles. Other tools that can be used to determine the ligand density of nanoparticles are Thermogravimetric Analysis (TGA), Quantitative NMR (qNMR) ligand density [ 175 ], and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) [ 175 ]. There is a need to measure nanoparticles in which the numbers of targeting ligands and receptors can specifically be counted with single-molecule resolution to understand their interaction [ 177 ]. TEM and SMLM have been used to quantify the number and map the position of functional sites of proteins on the surface of single nanoparticles [ 178 , 179 , 180 ]. TEM can be used for quantifying the size and the loading; it can also be used for confirming the bioconjugation [ 181 ]. The conjugation between gold nanoparticles (AuNPs) and Cetuximab (antibodies to treat cancer) was visualized by TEM [ 178 ]. 5-Aminolevulinic acid conjugated to AuNPs was observed under TEM due to their slight change in size [ 182 ]. TEM is also helpful for characterizing the orientation of covalently conjugated proteins on nanoparticles [ 178 ]. Specifically, silica nanoparticles were conjugated with transferrin, and antibody fragments (Fabs) conjugated with gold nanoparticles were used as probes to map any available epitopes on transferrin [ 179 ]. TEM has also been used to confirm the coating efficiency of membrane-coated nanoparticles [ 183 , 184 ]. Direct stochastic optical reconstruction microscopy (dSTORM) is an SMLM technique that has a spatial resolution of 20 nm that can also help determine the number of antibody conjugates per nanoparticle [ 177 ]. In one study, silica nanoparticles with different sizes (50, 100, 150 nm) were conjugated with Cetuximab, which is an EGFR antibody conjugated to a dSTORM probe (EGFR-AF647) through incubation. Analysis of the acquired dSTORM images helped quantify differences in the density of antibodies on each nanoparticle [ 177 ]. Additionally, (DNA-PAINT) is another SMLM technique that has been used to map the conjugates attached onto nano- and microparticles [ 180 ] by using a qualitative PAINT (qPAINT) algorithm. Nanoparticles conjugated with Streptavidin and microparticles conjugated with Digoxigenin antibodies have been used to map the ligand distribution on them [ 180 ]. For this procedure, conjugated nanoparticles were incubated with a PAINT probe that has the ligand attached to the conjugate and a DNA docking strand, which allows the probe to bind specifically to the conjugates. Then, the imager DNA strand, which is a complementary DNA strand to the docking strand, was added. The transient binding between the docking strand and the imager strand resulted in the imaging and localization of single ligands. The results of these analyses showed that particles with a similar size can have considerable variability in the number of conjugates [ 180 ].