Surface characterization of carbohydrate microarrays

Improvement of Lipid Detection in Mouse Brain and Human Uterine Tissue Sections Using In Situ Matrix Enhanced Secondary Ion Mass Spectrometry

The potential of mass spectrometry imaging, and especially ToF-SIMS 2D and 3D imaging, for submicrometer-scale, label-free molecular localization in biological tissues is undisputable. Nevertheless, sensitivity issues remain, especially when one wants to achieve the best lateral and vertical (nanometer-scale) resolution. In this study, the interest of in situ matrix transfer for tissue analysis with cluster ion beams (Bin+, Arn+) is explored in detail, using a series of six low molecular weight acidic (MALDI) matrices. After estimating the sensitivity enhancements for phosphatidylcholine (PC), an abundant lipid type present in almost any kind of cell membrane, the most promising matrices were softly transferred in situ on mouse brain and human uterine tissue samples using a 10 keV Ar3000+ cluster beam. Signal enhancements up to 1 order of magnitude for intact lipid signals were observed in both tissues under Bi5+ and Ar3000+ bombardment. The main findings of this study lie in the in-depth characterization of uterine tissue samples, the demonstration that the transferred matrices also improve signal efficiency in the negative ion polarity and that they perform as well when using Bin+ and Arn+ primary ions for analysis and imaging.

Identification of Pseudomonas aeruginosa exopolysaccharide Psl in biofilms using 3D OrbiSIMS

Secondary ion mass spectrometry (SIMS) offers advantages over both liquid extraction mass spectrometry and matrix assisted laser desorption mass spectrometry in that it provides the direct in situ analysis of molecules and has the potential to preserve the 3D location of an analyte in a sample. Polysaccharides are recognized as challenging analytes in the mass spectrometry of liquids and are also difficult to identify and assign using SIMS. Psl is an exopolysaccharide produced by Pseudomonas aeruginosa, which plays a key role in biofilm formation and maturation. In this Letter, we describe the use of the OrbiTrap analyzer with SIMS (3D OrbiSIMS) for the label-free mass spectrometry of Psl, taking advantage of its high mass resolving power for accurate secondary ion assignment. We study a P. aeruginosa biofilm and compare it with purified Psl to enable the assignment of secondary ions specific to the Psl structure. This resulted in the identification of 17 peaks that could confidently be ascribed to Psl fragments within the biofilm matrix. The complementary approach of the following neutral loss sequences is also shown to identify multiple oligosaccharide fragments without the requirement of a biological reference sample.

Applications of multivariate analysis and unsupervised machine learning to ToF-SIMS images of organic, bioorganic, and biological systems

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging offers a powerful, label-free method for exploring organic, bioorganic, and biological systems. The technique is capable of very high spatial resolution, while also producing an enormous amount of information about the chemical and molecular composition of a surface. However, this information is inherently complex, making interpretation and analysis of the vast amount of data produced by a single ToF-SIMS experiment a considerable challenge. Much research over the past few decades has focused on the application and development of multivariate analysis (MVA) and machine learning (ML) techniques that find meaningful patterns and relationships in these datasets. Here, we review the unsupervised algorithms—that is, algorithms that do not require ground truth labels—that have been applied to ToF-SIMS images, as well as other algorithms and approaches that have been used in the broader family of mass spectrometry imaging (MSI) techniques. We first give a nontechnical overview of several commonly used classes of unsupervised algorithms, such as matrix factorization, clustering, and nonlinear dimensionality reduction. We then review the application of unsupervised algorithms to various organic, bioorganic, and biological systems including cells and tissues, organic films, residues and coatings, and spatially structured systems such as polymer microarrays. We then cover several novel algorithms employed for other MSI techniques that have received little attention from ToF-SIMS imaging researchers. We conclude with a brief outline of potential future directions for the application of MVA and ML algorithms to ToF-SIMS images.

Preparation and structural properties of starch phosphate modified by alkaline phosphatase

In this study, a method for the synthesis of starch phosphate using the transferase properties of alkaline phosphatase was explored. Maize starch was treated with a pyrophosphate solution containing alkaline phosphatase and catalytic ions under pH 8 at 37 °C. The synthesis of starch phosphate was evaluated and compared with untreated and treated starch controls. The phosphorus content of the samples increased up to 8500% with the catalytic ion concentration, whereas the peak viscosity by up to 41.4% decreased. The crystallinity and enthalpy of the phosphorylated samples were reduced by up to 26.8% and 23.3%, respectively; however, no significant was observed by Fourier-transform infrared spectrometer. The roughness of the starch surface and the distribution of elemental phosphorus were observed by scanning electron microscopy and energy dispersive Spectrometry. X-ray photoelectron spectroscopy and time of flight secondary ion mass spectrometry results further indicated the grafting of the phosphate radical.

High sensitivity analysis of nanogram quantities of glycosaminoglycans using ToF-SIMS

Glycosaminoglycans (GAGs) are important biopolymers that differ in the sequence of saccharide units and in post polymerisation alterations at various positions, making these complex molecules challenging to analyse. Here we describe an approach that enables small quantities (<200 ng) of over 400 different GAGs to be analysed within a short time frame (3-4 h). Time of flight secondary ion mass spectrometry (ToF-SIMS) together with multivariate analysis is used to analyse the entire set of GAG samples. Resultant spectra are derived from the whole molecules and do not require pre-digestion. All 6 possible GAG types are successfully discriminated, both alone and in the presence of fibronectin. We also distinguish between pharmaceutical grade heparin, derived from different animal species and from different suppliers, to a sensitivity as low as 0.001 wt%. This approach is likely to be highly beneficial in the quality control of GAGs produced for therapeutic applications and for characterising GAGs within biomaterials or from in vitro cell culture.

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

Understanding mass spectrometry images: complexity to clarity with machine learning

The application of artificial intelligence and machine learning to hyperspectral mass spectrometry imaging (MSI) data has received considerable attention over recent years. Various methodologies have shown great promise in their ability to handle the complexity and size of MSI data sets. Advances in this area have been particularly appealing for MSI of biological samples, which typically produce highly complicated data with often subtle relationships between features. There are many different machine learning approaches that have been applied to MSI data over the past two decades. In this review, we focus on a subset of non-linear machine learning techniques that have mostly only been applied in the past 5 years. Specifically, we review the use of the self-organizing map (SOM), SOM with relational perspective mapping (SOM-RPM), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). While not their only functionality, we have grouped these techniques based on their ability to produce what we refer to as similarity maps. Similarity maps are color representations of hyperspectral data, in which spectral similarity between pixels-that is, their distance in high-dimensional space-is represented by relative color similarity. In discussing these techniques, we describe, briefly, their associated algorithms and functionalities, and also outline applications in MSI research with a strong focus on biological sample types. The aim of this review is therefore to introduce this relatively recent paradigm for visualizing and exploring hyperspectral MSI, while also providing a comparison between each technique discussed.

Improved spot morphology for printed glycan arrays

Despite considerable success studying glycan-binding proteins using printed glycan arrays (PGAs), unambiguous quantitation of spot intensities by fluorescent readers remains a challenge. The main obstacles are the varying spot shape and size and in-spot fluorescence distribution caused by uneven drying of the printed drops. Two methods have been suggested for solving this problem: using polymeric glycoconjugates, which makes it possible to equalize the physicochemical properties (hydrophobicity, charge, and size) of different glycans, and applying a glycan solution on a slide coated with a thin oil mask, which hinders evaporation of the drop. Both approaches yield spots with similar sizes and an even distribution of the signal across the spot and are likely to be useful for improving the prints of other classes of molecules.

Chemo-enzymatic Synthesis of N-glycans for Array Development and HIV Antibody Profiling

We present a highly efficient way for the rapid preparation of a wide range of N-linked oligosaccharides (estimated to exceed 20,000 structures) that are commonly found on human glycoproteins. To achieve the desired structural diversity, the strategy began with the chemo-enzymatic synthesis of three kinds of oligosaccharyl fluoride modules, followed by their stepwise α-selective glycosylations at the 3-O and 6-O positions of the mannose residue of the common core trisaccharide having a crucial β-mannoside linkage. We further attached the N-glycans to the surface of an aluminum oxide-coated glass (ACG) slide to create a covalent mixed array for the analysis of hetero-ligand interaction with an HIV antibody. In particular, the binding behavior of a newly isolated HIV-1 broadly neutralizing antibody (bNAb), PG9, to the mixture of closely spaced Man5GlcNAc2 (Man5) and 2,6-di-sialylated bi-antennary complex type N-glycan (SCT) on an ACG array, opens a new avenue to guide the effective immunogen design for HIV vaccine development. In addition, our ACG array embodies a powerful tool to study other HIV antibodies for hetero-ligand binding behavior.

The physicochemical fingerprint of Necator americanus

Necator americanus, a haematophagous hookworm parasite, infects ~10% of the world's population and is considered to be a significant public health risk. Its lifecycle has distinct stages, permitting its successful transit from the skin via the lungs (L3) to the intestinal tract (L4 maturing to adult). It has been hypothesised that the L3 larval sheath, which is shed during percutaneous infection (exsheathment), diverts the immune system to allow successful infection and reinfection in endemic areas. However, the physicochemical properties of the L3 larval cuticle and sheath, which are in direct contact with the skin and its immune defences, are unknown. In the present study, we controlled exsheathment, to characterise the sheath and underlying cuticle surfaces in situ, using atomic force microscopy (AFM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). AFM revealed previously unseen surface area enhancing nano-annuli exclusive to the sheath surface and confirmed greater adhesion forces exist between cationic surfaces and the sheath, when compared to the emergent L3 cuticle. Furthermore, ToF-SIMS elucidated different chemistries between the surfaces of the cuticle and sheath which could be of biological significance. For example, the phosphatidylglycerol rich cuticle surface may support the onward migration of a lubricated infective stage, while the anionic and potentially immunologically active heparan sulphate rich deposited sheath could result in the diversion of immune defences to an inanimate antigenic nidus. We propose that our initial studies into the surface analysis of this hookworm provides a timely insight into the physicochemical properties of a globally important human pathogen at its infective stage and anticipate that the development and application of this analytical methodology will support translation of these findings into a biological context.

Glycan Arrays: From Basic Biochemical Research to Bioanalytical and Biomedical Applications

A major branch of glycobiology and glycan-focused biomedicine studies the interaction between carbohydrates and other biopolymers, most importantly, glycan-binding proteins. Today, this research into glycan-biopolymer interaction is unthinkable without glycan arrays, tools that enable high-throughput analysis of carbohydrate interaction partners. Glycan arrays offer many applications in basic biochemical research, for example, defining the specificity of glycosyltransferases and lectins such as immune receptors. Biomedical applications include the characterization and surveillance of influenza strains, identification of biomarkers for cancer and infection, and profiling of immune responses to vaccines. Here, we review major applications of glycan arrays both in basic and applied research. Given the dynamic nature of this rapidly developing field, we focus on recent findings.

Modular synthesis of N-glycans and arrays for the hetero-ligand binding analysis of HIV antibodies

A new class of broadly neutralizing antibodies (bNAbs) from HIV donors has been reported to target the glycans on gp120--a glycoprotein found on the surface of the virus envelope--thus renewing hope of developing carbohydrate-based HIV vaccines. However, the version of gp120 used in previous studies was not from human T cells and so the glycosylation pattern could be somewhat different to that found in the native system. Moreover, some antibodies recognized two different glycans simultaneously and this cannot be detected with the commonly used glycan microarrays on glass slides. Here, we have developed a glycan microarray on an aluminium-oxide-coated glass slide containing a diverse set of glycans, including homo- and mixed N-glycans (high-mannose, hybrid and complex types) that were prepared by modular chemo-enzymatic methods to detect the presence of hetero-glycan binding behaviours. This new approach allows rapid screening and identification of optimal glycans recognized by neutralizing antibodies, and could speed up the development of HIV-1 vaccines targeting cell surface glycans.

ToF-SIMS analysis of a polymer microarray composed of poly(meth)acrylates with C6 derivative pendant groups

Surface analysis plays a key role in understanding the function of materials, particularly in biological environments. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) provides highly surface sensitive chemical information that can readily be acquired over large areas and has, thus, become an important surface analysis tool. However, the information‐rich nature of ToF‐SIMS complicates the interpretation and comparison of spectra, particularly in cases where multicomponent samples are being assessed. In this study, a method is presented to assess the chemical variance across 16 poly(meth)acrylates. Materials are selected to contain C₆ pendant groups, and ten replicates of each are printed as a polymer microarray. SIMS spectra are acquired for each material with the most intense and unique ions assessed for each material to identify the predominant and distinctive fragmentation pathways within the materials studied. Differentiating acrylate/methacrylate pairs is readily achieved using secondary ions derived from both the polymer backbone and pendant groups. Principal component analysis (PCA) is performed on the SIMS spectra of the 16 polymers, whereby the resulting principal components are able to distinguish phenyl from benzyl groups, mono‐functional from multi‐functional monomers and acrylates from methacrylates. The principal components are applied to copolymer series to assess the predictive capabilities of the PCA. Beyond being able to predict the copolymer ratio, in some cases, the SIMS analysis is able to provide insight into the molecular sequence of a copolymer. The insight gained in this study will be beneficial for developing structure–function relationships based upon ToF‐SIMS data of polymer libraries. © 2016 The Authors Surface and Interface Analysis Published by John Wiley & Sons Ltd.

Visualization of acetaminophen-induced liver injury by time-of-flight secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (MS) provides secondary ion images that reflect distributions of substances with sub-micrometer spatial resolution. To evaluate the use of time-of-flight secondary ion MS to capture subcellular chemical changes in a tissue specimen, we visualized cellular damage showing a three-zone distribution in mouse liver tissue injured by acetaminophen overdose. First, we selected two types of ion peaks related to the hepatocyte nucleus and cytoplasm using control mouse liver. Acetaminophen-overdosed mouse liver was then classified into three areas using the time-of-flight secondary ion MS image of the two types of peaks, which roughly corresponded to established histopathological features. The ion peaks related to the cytoplasm decreased as the injury became more severe, and their origin was assumed to be mostly glycogen based on comparison with periodic acid-Schiff staining images and reference compound spectra. This indicated that the time-of-flight secondary ion MS image of the acetaminophen-overdosed mouse liver represented the chemical changes mainly corresponding to glycogen depletion on a subcellular scale. In addition, this technique also provided information on lipid species related to the injury. These results suggest that time-of-flight secondary ion MS has potential utility in histopathological applications.

3D ToF-SIMS imaging of polymer multilayer films using argon cluster sputter depth profiling

ToF-SIMS imaging with argon cluster sputter depth profiling has provided detailed insight into the three-dimensional (3D) chemical composition of a series of polymer multilayer structures. Depths of more than 15 μm were profiled in these samples while maintaining uniform sputter rates. The 3D chemical images provide information regarding the structure of the multilayer systems that could be used to inform future systems manufacturing and development. This also includes measuring the layer homogeneity, thickness, and interface widths. The systems analyzed were spin-cast multilayers comprising alternating polystyrene (PS) and polyvinylpyrrolidone (PVP) layers. These included samples where the PVP and PS layer thickness values were kept constant throughout and samples where the layer thickness was varied as a function of depth in the multilayer. The depth profile data obtained was observed to be superior to that obtained for the same materials using alternative ion sources such as C60(n+). The data closely reflected the "as manufactured" sample specification, exhibiting good agreement with ellipsometry measurements of layer thickness, while also maintaining secondary ion intensities throughout the profiling regime. The unprecedented quality of the data allowed a detailed analysis of the chemical structure of these systems, revealing some minor imperfections within the polymer layers and demonstrating the enhanced capabilities of the argon cluster depth profiling technique.

Tunable aggregation by competing biomolecular interactions

Measurements and models are reported for Concanavalin A (ConA) mediated aggregation of dextran coated colloids that is tunable via a competing ConA-glucose interaction. Video and confocal scanning laser microscopy were used to characterize ConA adsorption to dextran colloids and quasi-2D dextran coated colloid aggregation kinetics vs [ConA] and [glucose]. ConA adsorption to, and aggregation rates of, dextran coated colloids increased from negligible values to high coverage and rapid rates for increasing [ConA] in the range 0.1-10 mM and decreasing [glucose] in the range 1-100 mM, consistent with dissociation constant estimates. Analysis of colloidal aggregation kinetics indicates ConA bridge formation is the rate-limiting step controlling the transition from slow to rapid aggregation. Our findings reveal a mechanism for tuning colloidal interactions and aggregation kinetics through specific, competitive biomolecular interactions, which lends insights into aggregation phenomena in mixed synthetic-biomaterial and biological systems.

Synthesis of conjugation-ready zwitterionic oligosaccharides by chemoselective thioglycoside activation

A method to chemoselectively activate thioglycosides in the presence of thioethers is developed and applied in the total synthesis of repeating units of S. pneumoniae Sp1 and B. fragilis PS A1. Biochemical evaluation of these glycans is performed after conjugation to reporter moieties.

Strategies for MCR image analysis of large hyperspectral data-sets

Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data 'binning'). Copyright © 2012 John Wiley & Sons, Ltd.

Multivariate curve resolution: a review of advanced and tailored applications and challenges

Multivariate curve resolution (MCR) is a widespread methodology for the analysis of process data in many different application fields. This article intends to propose a critical review of the recently published works. Particular attention will be paid to situations requiring advanced and tailored applications of multivariate curve resolution, dealing with improvements in preprocessing methods, multi-set data arrangements, tailored constraints, issues related to non-ideal noise structure and deviation to linearity. These analytical issues are tackling the limits of applicability of MCR methods and, therefore, they can be considered as the most challenging ones.

High-resolution epifluorescence and time-of-flight secondary ion mass spectrometry chemical imaging comparisons of single DNA microarray spots

DNA microarray assay performance is commonly compromised by spot-spot probe and signal variations as well as heterogeneity within printed microspots. Accurate metrics for captured DNA target signal rely upon uniform spot distribution of both probe and target DNA to yield reliable hybridized signal. While often presumed, this is neither easily achieved nor often proven experimentally. High-resolution imaging techniques were used to determine spot heterogeneity in identical DNA array microspots comprising varied ratios of unlabeled and dye-labeled DNA probes contact-printed onto commercial arraying surfaces. Epifluorescence imaging data for individual array microspots were correlated with time-of-flight secondary ion mass spectrometry (TOF-SIMS) chemical state imaging of the same spots. Epifluorescence imaging intensity distinguished varying DNA density distributed both within a given spot and from spot to spot. TOF-SIMS chemical analysis confirmed these heterogeneous printed DNA distributions by tracking bound Cy3 dye, DNA base, and phosphate specific ion fragments often correlating to fluorescence patterns within identical spots. TOF-SIMS ion fragments originating from probe DNA and Cy3 dye are enriched in microspot centers, correlating with high fluorescence intensity regions. Both TOF-SIMS and epifluorescence support Marangoni flow effects on spot drying, with high-density DNA-Cy3 located in spot centers and nonhomogeneous DNA distribution within printed spots. Microspot image dimensional analysis results for DNA droplet spreading show differing DNA densities across printed spots. The study directly supports different DNA probe chemical and spatial microenvironments within spots that yield spot-spot signal variations known to affect DNA target hybridization efficiencies and kinetics. These variations critically affect probe-target duplex formation and DNA array signal generation.

Multivariate analysis of ToF-SIMS data from multicomponent systems: the why, when, and how

The use of multivariate analysis (MVA) methods in the processing of time-of-flight secondary ion mass spectrometry (ToF-SIMS) data has become increasingly more common. MVA presents a powerful set of tools to aid the user in processing data from complex, multicomponent surfaces such as biological materials and biosensors. When properly used, MVA can help the user identify the major sources of differences within a sample or between samples, determine where certain compounds exist on a sample, or verify the presence of compounds that have been engineered into the surface. Of all the MVA methods, principal component analysis (PCA) is the most commonly used and forms an excellent starting point for the application of many of the other methods employed to process ToF-SIMS data. Herein we discuss the application of PCA and other MVA methods to multicomponent ToF-SIMS data and provide guidelines on their application and use.

Use of imaging multivariate analysis to improve biochemical and anatomical discrimination in desorption electrospray ionisation mass spectrometry imaging

Desorption electrospray ionisation (DESI) mass spectrometry images usually contain a large amount of information that can be difficult to interpret in an objective manner. We explore the use of imaging multivariate analysis (MVA) on DESI images of protein spots and rat brain sections to automatically assign peaks and improve discrimination of spatially important features. DESI parameters were optimised on an ion trap mass spectrometer for (a) consistent imaging of dried single and mixture spots of insulin, myoglobin and BSA from a Permanox slide, and (b) to produce a MS image of rat brain coronal section at 100 μm resolution. Multivariate curve resolution (MCR), an imaging MVA technique was applied to these images after appropriate data binning. MCR analysis on DESI images of protein mixture spots allowed the multiply charged peaks of a number of proteins to be distinctly separated. Application of MCR to a DESI image of a rat brain coronal section deconvoluted the image into components that showed biologically important features. Further application of MCR to a subsection of the image produced a component that clearly separated out the substantia nigra region, which allowed us to produce a biochemical anatomy for this area of the brain. We have demonstrated the ability of imaging MVA to automatically and objectively analyse DESI images of standardised and complex biological samples, and have shown its capacity for detailed spatial profiling of biomolecules in specific morphological regions. We propose the routine use of this technique for future DESI imaging experiments.

Characterizing the surface quality and droplet interface shape for microarray plates

The variation in the surface quality of microarray plates was examined by measuring the contact angles of 480 droplets on five microarray plates. It was found that the measured contact angle did not accurately predict the droplet shape for moderate Bond numbers (~0.5 ≤ N(B) ≤ 5). By defining an apparent contact angle using the ratio of the contact radius to the height, the variance in the predicted interface shape decreased by greater than a factor of 3 for both local and globally averaged characteristics. The error in the predicted droplet height was also reduced by 3 orders of magnitude.

ToF-SIMS analysis of chemical heterogenities in inkjet micro-array printed drug/polymer formulations

Three different formulations comprising two drugs, felodipine and hydrochlorothiazide (HCT) and two polymers, poly(vinyl pyrolidone) (PVP) and poly(lactic-co-glycolic acid) (PLGA) were inkjet printed as micro-dot arrays and analysed on an individual micro-spot basis by time-of-flight secondary ion mass spectrometry (ToF-SIMS). For the HCT/PLGA formulation, the spots showed heterogeneity of the drug and other chemical constituents. To further investigate these heterogeneities, multivariate curve resolution was applied to the ToF-SIMS hyperspectral image datasets. This approach successfully identified distinct chemical components elucidating the HCT, PLGA, substrate material, and contaminants based on sulphur, phosphorous and sodium chloride. Spots printed using either of the drugs with PVP exhibited full substrate coverage and a uniform distribution of the active ingredient along with all other constituents within the printed spot area. This represents the preferred situation in terms of stability and controlling the release of a drug from a polymer matrix.