This website is using cookies
We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. By browsing our website, you consent to our use of cookies and other tracking technologies.
×
AFM Workshop

Pharmaceutical Applications of AFM

 

AFM and the Pharma Industry - Download

 

Table of Contents


1. The Current State of the Pharmaceutical Industry
2. Introduction to AFM
3. Advantages of AFM in the Pharmaceutical Industry
4. Relevant Applications of AFM in the Pharmaceutical Industry
Analysis of Drug Properties
Nanoparticle Characterization for Drug Delivery
Mechanical Characterization of Drugs and Biological Entities
Characterization of Coatings and Surfaces
Drug Discovery Studies
Histopathological Characterization
Disease Marker Discovery
Characterization of Antimicrobial Effects of Drugs
REFERENCES

 

1. The Current State of the Pharmaceutical Industry

There is an increasing need for state-of-the-art tools that will bring innovation to the pharmaceutical industry and help in expanding drug pipelines. The research and development (R&D) costs of developing a new drug are at its highest, and the number of new molecules developed per $1B budget has steadily fallen to less than one over the past decades.1 Many pharmaceutical companies mainly rely on ‘blockbuster drugs’ for profit, which is a precarious strategy regarding patent-related challenges.2 Moreover, standard drug treatments are beneficial only to a limited percentage of the patients.

The response rates of patients to a primary drug from given group of therapeutic areas show limitations of standard drug treatment.
Figure 1. The response rates of patients to a primary drug from given group of therapeutic areas show limitations of standard drug treatment.2

 

The pharmaceutical industry demands for novel paradigms that will revolutionize many aspects of drug development, diagnostics, and treatment design. Nanotechnology, an emerging field of knowledge, is a significant impact on the major areas of pharmaceutical R&D – process development, product development, and personalized medicine.2

Nanoscale design of pharmaceuticals and biomedical devices is an increasing demand by the pharmaceutical industry.3 Such levels of precision endow drugs with new features that enable them to interact with molecular structures and improve drug delivery to desired sites in the body.

Nanoscale processing and design of the pharmaceuticals require imaging, analysis, and measurement also at the nanoscale. As we will see throughout this document, nanoscale analysis, among other contributions, informs pharmaceutical formulation, facilitates drug discovery, and detects otherwise indiscernible differences between tissues that are relevant to diagnostics.

 

2. Introduction to AFM

Traditional nanoscale imaging techniques such as electron microscopy provide high resolution images at the nanoscale level, but they generally require painstaking sample preparation, perform imaging in a vacuum, and give a 2D image of the surface as an output. Atomic Force Microscopy (AFM) can readily image any surface in an ambient condition and provide 3D topography of the surface. Moreover, AFM allows measuring other properties of the surface, such as elasticity and adhesiveness, which are relevant to pharmaceutical applications. Current scientific literature is consistently studded with pharma-related applications of AFM. The data lead us to claim that AFM deserves a space in the R&D toolbox of pharmaceutical industry game-changers.

 

The working principle of Atomic Force Microscopy
Figure 2. The working principle of Atomic Force Microscopy

 

The working principle of the Atomic Force Microscope (AFM) is based on the forces that arise when a sample surface is scanned with a nanometer-sized tip (a few 10s of nm) attached to a cantilever.

The edge of the AFM over traditional stylus surface profilers is that the former uses a feedback loop to control the forces between the surface and probe. Because the forces are controlled, very small probes may be used without being broken while capturing an image. There are two primary modes used for measuring the topography of a sample, which are contact mode and vibrating mode.

 

Visualization of the two primary modes for topography imaging
Figure 3. Visualization of the two primary modes for topography imaging

 

Contact Mode

The probing tip is in contact with the surface throughout the imaging in contact mode. The short-range forces between the surface and tip cause the deflection of the cantilever, which is recorded to generate the topographical image of the surface. However, the tip-surface contact in this mode can potentially damage the surface or wear the tip. Hence, this mode may not be suitable for imaging of soft surfaces. On the other hand, continuous contact with the surface allows identifying other features such as friction (lateral force imaging) or stiffness/elasticity map of the surface (force modulation imaging). In lateral force (or frictional force) microscopy, the rising lateral deflections of the cantilever are measured due to forces parallel to the plane of the sample surface.4 This allows the detection of inhomogeneities on the material which gives rise to variations in surface friction. Force modulation microscopy, on the other hand, works by periodically pushing the tip into the sample determined through oscillating the Z position of the sample at a known amplitude.

Vibrating Mode

In vibrating mode, a probe at the end of a cantilever is vibrated up and down. As the vibrating probe begins to interact with a surface, the vibration amplitude is dampened. The amount of damping is proportional to the amount of force placed on the surface by the probe on each oscillation of the vibrating probe. A feedback loop is used to maintain a fixed vibration amplitude as the probe is scanned across a surface. Forces between the probe and surface in vibrating mode can be as low as a few 10's of piconewtons.

Although AFM is widely known for mapping surface topography, that alone does not always provide the answers that researchers need to understand the material.5 Fortunately, as a result of its capability to measure varying forces arising between the tip and sample, AFM can characterize a wide array of mechanical properties (e.g. adhesion, stiffness, friction, dissipation, viscoelasticity), electrical properties (e.g. capacitance, electrostatic forces, work function, electrical current, conductivity, surface potential, resistance), magnetic properties, optical/spectroscopic properties, thermal properties, and solvent effects (via imaging at liquid environment) in almost real-time.6

 

PHASE IMAGING

A phase difference between oscillation of the cantilever and of the signal that drives cantilever oscillation (i.e., piezoelectric crystal) is measured and visualized in phase imaging.7 There is no phase contrast when the surface is homogenous, or when there is no interaction between the tip and surface (i.e., the cantilever is well above the surface). However, if specific regions of the surface have distinct mechanical properties, it could be captured with phase imaging. This is because cantilever loses a different amount of energy as probe taps to surface areas with differing mechanical properties. Hence, phase imaging could be helpful to detect variations in mechanical properties on surfaces. It could as well be used to detect patterns of various materials such as polymers on the surface or to identify contaminants that cannot be distinguished with topography imaging.

 

3. Advantages of AFM in the Pharmaceutical Industry

Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) techniques are traditionally used for measuring nanoscale images of samples in the pharmaceutical industry, and these techniques can be costly. The AFM offers an alternative to these traditional imaging techniques by its inherent properties: 3

  • Three-dimensional topography is measured with the AFM, directly revealing surface textures
  • AFM provides nanoscale resolution in surface imaging
  • AFM requires only minimal sample preparation
  • AFM obtains images in ambient air or liquids and does not require large vacuum chambers. This could be critical for testing the effects of an environmental condition to a drug or delineating the behavior of the sample, such as a cell or a therapeutic, under physiological conditions.
  • Images of very smooth, flat materials are readily determined with AFM
  • AFM is the only imaging technique to provide mechanical information on the surface.8
  • The cost of acquisition and ownership of an AFM is a fraction of an SEM

What roles can AFM play in the pharmaceutical industry? 8, 9, 10

  • Analysis of crystal structure and growth for drug compounds
  • Characterization of biological materials at nanoscale
  • Measurement of molecular interaction parameters at nanometer spatial resolution
  • Obtaining tertiary and quaternary structural information from proteins
  • Evaluation of morphological characteristics of polymers, nanoparticles, and other materials used in drug delivery
  • Quantification of the individual active pharmaceutical ingredient (API)-excipient interaction across different conditions
  • Identification of the surface properties of powdered excipients, colloids, microbiological systems and implants
  • Visualization of homogeneity of dispersions at a molecular level
  • Monitoring structural changes in any living & non-living material

 

4. Relevant Applications of AFM in the Pharmaceutical Industry

 

ANALYSIS OF DRUG PROPERTIES

As soon as a biologically active molecule is selected to be a candidate drug, its solid-state properties gain the utmost importance.11 Drug molecules exist in a particulate, generally crystalline, form in more than 90% of all pharmaceutical products, such as tablets, capsules, and inhalable powders.3, 12 Their production involves the transformation of the drug into particles having a size range of 0.1-10 microns.13 Characterization of these particles will guide the optimization of the process parameters and thus has the potential to save the costs of the manufacturing process.8 For example, the shape and roughness of the particles influence the flow properties of the powder.10 Particle size is also known to affect various drug properties such as dissolution rate, bioavailability, content uniformity, stability, texture, flow characteristics, and sedimentation rates.13 Mechanical properties of the particles, including the forces between them, similarly determine processability and formulation stability. 3 Respirable particles highly depend on adhesive and cohesive forces.8 Understanding the broad properties of a candidate drug is important for solid dosage formulation.

Using AFM in analyzing the size, shape, and other properties of a drug crystal can help in predicting the drug’s behavior in large scale production.14 AFM has been successfully used in characterizing the morphology, roughness, and mechanical properties of powdered and granulated particles, in which these data are used to correlate with their physicochemical properties.15

Typical qualities attributed to drug crystals are classified under four classes: purity, form (solid), particle attributes, and stability.16 AFM can be used to evaluate a variety of qualities from each of these classes. For example, impurities could be detected via topographic analysis of crystal structure. Regarding the solid form, it could be used to differentiate various polymorphic forms of the crystal or distinguish crystalline regions from amorphous ones. It could as well be exploited to understand various particle attributes such as particle size and shape. Lastly, it could be used to assess the stability of the drug crystals via employing mechanical analysis mode.

 

Crystal Growth

There is a variety of crystal growth parameters (e.g. temperature, pH, concentration, and additive levels) that should be optimized to tailor the growth process. There will be endless combinations of these parameters if the aim is to optimize crystal growth. Testing these conditions in real-time would increase efficiency while decreasing costs. Since AFM is capable to operate under varying conditions such as temperature, humidity, and liquid medium, it allows studying the kinetics of a range of phenomena.14 It is used for in situ imaging of crystallization to see the effects of growth conditions on the growth process, as well as to study growth mechanisms and defect formation.

Crystal growth initiated on the surface of amorphous drugs by environmental conditions could have unwanted effects on their solubility and bioavailability.17 Miyazaki et al. studied the crystal growth at the surface of amorphous nifedipine under ambient temperature and relative humidity (<50%).17 The researchers used tapping mode AFM to observe the effects of the exposure to ambient temperature and humidity on crystal growth in real-time. They observed significant crystal growth on the amorphous surface as time passed. This kind of study can be helpful in testing the effects of potential inhibitors on crystal growth.

 

Characterization of Polymorphism in Crystals

The polymorphism in drug compounds indicates their potential to exist in more than one crystalline form. Polymorphs can become a significant obstacle to the pharmaceutical industry.18 It is because different polymorphs have different physicochemical properties, such as solubility, dissolution rate, and stability.13, 19 Therefore, characterization and detection of different polymorphs are critical for achieving consistent quality in pharmaceutical products.

Danesh et al. employed the phase imaging technique to analyze and differentiate two different polymorphic forms of the drug cimetidine, both of which are in pharmaceutical use.18 While polymorph A has better flow properties, and a lack of adherence, which suits it for manufacturing tablets, polymorph B is more suitable for suspension form. AFM images delineated the nanoscale features of both crystal forms (the one with spindle-shaped features, the other with a relatively flat surface), which can be a standard for routine industrial characterization

 

Crystal Dissolution Studies

Studying the dynamics of crystal dissolution process is critical because it is related to in vivo drug absorption.20 AFM has been successfully utilized by several studies to investigate the dissolution of drugs under varying environmental stress and contributed to our understanding of this process.15

Danesh et al. used AFM techniques to measure and compare the dissolution rates of two different crystal planes ((001) and (100)) of aspirin.21 They observed that the plane (100) dissolves 6 times faster than the (001) with an average dissolution rate of 2.93 nm/s. The dissolution mechanisms of the two crystal planes were different as well. While (100) displayed crystal terrace sinking, (001) dissolved by receding step edges. Measured dissolution rates predict the difference between the rate of flux of material from two different crystal planes. They might as well be related to already reported variations in the dissolution behavior of commercial aspirin products.

 

Characterization of Amorphous vs. Crystalline Domains

Pressurized metered-dose inhalers (pMDIs) is a standard application for the treatment of various lung disorders, such as asthma and chronic obstructive pulmonary disease (COPD).15 Milling of drug materials is necessary to produce the dry powder (micronized particles) included in pMDIs. However, the milling process induces the formation of amorphous regions on the surface of particles, which may cause high dose variability and poor aerosolization.22 Alterations in environmental conditions may also result in the mobility of amorphous regions, recrystallization and potential fusion of particles.

The general strategy employed to induce controlled recrystallization of amorphous regions is to expose the particles to organic vapor, particularly ethanol vapor. To characterize the effectiveness of this strategy, a surface analysis technique that can distinguish the crystallized regions from the amorphous ones is required. Jones et al. employed AFM phase imaging techniques to visualize the contrast between surface regions of different mechanical properties for the same goal.22 Phase imaging of unmilled budesonide particles displayed almost no variation on the surface, indicating ordered crystalline surface. On the other hand, milled budesonide particles displayed an immense variation on the surface mechanical properties, confirming the presence of amorphous regions. Exposure to ethanol flattened this variation suggesting the recrystallization of the amorphous regions.

 

Drug Interaction Studies

Drug-drug, drug-excipient, and drug-device interactions influence the parameters of pharmaceutical formulation such as tablet strength, blending uniformity, flow characteristics and granulation.15 These interactions are controlled by intrinsic factors such as the chemical nature of materials or the polymorphism type, and by extrinsic factors such as environmental storage conditions.23 For example, micronization, a process that generates an optimal particle size for dry powder delivery, causes an increase in the surface area of particles, producing a higher number of interaction sites. This can lead to particle agglomeration or adherence to unwanted sites. Knowledge in particle interaction at the nanoscale can help in the reassessment of formulations and guide in particle modification and optimization.24

AFM is the only technique that allows measuring such interactions in the pN (piconewton) range, which makes it an indispensable tool for biomedicine.25 To carry out these measurements, a drug particle is attached to a blank cantilever to create a “colloid probe” (Fig. 4).10 These studies aim to compare “drug- drug” cohesion forces to “drug-carrier particle” and “drug-device component” adhesion forces, and to evaluate the balance between these forces with potential contribution to select a suitable carrier particle and device material for the drug molecule.3, 25

Drug Interaction Studies
Figure 4. (a) Scanning electron micrograph of a “colloid probe”, that is a drug particle attached to a cantilever; (b) The graph shows drug particle (probe) - surface distance vs cantilever deflection (adhesion force).10

 

Adhesion force measurements with AFM can also help in understanding the powder behavior and in choosing the right excipient materials for increased powder stability. Begat et al. evaluated the cohesive and adhesive force balance within dry powder inhaler formulations quantitatively.26 They probed the surfaces of lactose, budesonide, and salbutamol with an AFM tip carrying either of the budesonide or salbutamol particle. Their findings showed that budesonide has strong cohesive forces while its affinity to lactose excipient is weak. On the other hand, salbutamol exhibited weak cohesive forces while having strong adherence to lactose. As a result, they concluded that the salbutamol/lactose blend would be more uniform and stable during processing than the budesonide/lactose blend.26

Bringing together the adhesion and the imaging data would be helpful in characterizing the heterogeneity on the surface of a particle. In this way, it would be possible to distinguish the adhesion behaviors of crystalline and amorphous regions.24 The micronization process leads to amorphous regions on the surface of the otherwise crystalline particles. Moreover, the relative humidity of the environment can change the size of these amorphous regions which may cause significant effects on adhesion forces between particles. To investigate the phenomenon, Berard et al. measured the interaction strength between crystal or amorphous zanamivir and lactose.23 Tapping mode AFM images displayed ordered structures on the surfaces of lactose and zanamivir crystals, with aligned structures and terraces, respectively. As expected, the amorphous zanamivir did not show any ordered structure. The interaction forces between the lactose crystal particle (attached to a cantilever) and the zanamivir surface were measured. The measurements indicated that amorphous zanamivir shows higher adhesion to lactose than crystalline zanamivir. Also, both micronized and amorphous zanamivir showed a similar affinity to lactose. These data indicate the significance of gradual amorphization of the particle surfaces upon micronization. It was also discovered that the elevation of humidity increased adhesion in all cases. Hence, both effects (amorphization and change in humidity) might have severe consequences in the batch quality. As a result, storage conditions should be considered carefully for dry powder inhalers.

Apart from the mentioned applications, AFM has also been used to investigate biomolecular interactions such as DNA-protein, drug-enzyme, and antigen-antibody interactions.15 Several studies also probed cell surface molecule organizations and their alterations due to changing environmental conditions.25 Single molecule force spectroscopy (SMFS) allows identifying the nature of interaction between ligands and receptors.25

 

NANOPARTICLE CHARACTERIZATION FOR DRUG DELIVERY

The use of nanoparticles as a drug delivery system has been proposed as a strategy to fight cancer. Nanoparticles could potentially increase the therapeutic window of anticancer drugs by controlling their bioavailability, minimizing adverse effects, and target them to the tumor site. Morphological characterization of nanoparticles is crucial since their size and shape affect various parameters related to their efficacy such as plasma clearance rate, target site accumulation, and susceptibility to attack by immune cells. AFM is a commonly used technique to characterize nanoparticles.

Batista et al. developed a drug delivery system based on Poly(methyl methacrylate) (PMMA) nanoparticles for the delivery of the natural anticancer drug, α-terpineol.27 The researchers synthesized PMMA nanoparticles using the mini-emulsion technique, and encapsulated varying concentrations of α-terpineol into nanoparticles. Samples of PMMA nanoparticles that were either unloaded or loaded with ranging amounts of the drug α-terpineol (20-400 mg) were prepared. For this, the suspension of nanoparticles was deposited on mica surfaces and washed after 15 min of incubation at 40 °C. Dried samples were imaged with AFMWorkshop™ ™ TT-AFM under intermittent contact mode (vibrating). In all cases, the researchers observed PMMA nanoparticles to have spherical shapes (Fig. 5). However, the size measurements showed that drug encapsulation enlarged the diameter of nanoparticles in a concentration-dependent way. The average size of the nanoparticles increased from ~50 nm for the unloaded PMMA nanoparticles to ~120 nm for the PMMA nanoparticles encapsulating 400 mg of α- terpineol (Fig. 5). The data could be used to select the most optimal nanoparticle-drug combination for in vivo/clinical studies based on the current knowledge of how nanoparticle size affects therapeutic efficacy.

Nanoparticle Characterization for Drug Delivery
Figure 5. AFM analysis of polymeric nanoparticles loaded with an anticancer drug. (a) PMMA nanoparticles loaded with 400 mg of α-terpineol (PMMA/α-terpineol 400); (b) the graph showing average sizes of PMMA/α-terpineol combinations.27

 

MECHANICAL CHARACTERIZATION OF DRUGS AND BIOLOGICAL ENTITIES

Mechanical properties of active pharmaceutical ingredients (API) and excipients determine how their blends will behave during subsequent processing steps such as tableting, milling, roller compaction, and coating.28 Understanding these properties also play an important role in particle size control and excipient selection.15

AFM nanoindentation is a technique that allows measuring certain mechanical properties such as particle hardness, stiffness, and creep, at the nanoscale.25 With the help of this technique, Masterson & Cao (2008) measured and compared the hardness of individual particles of several pharmaceutical solids such as sucrose, ascorbic acid, lactose, and ibuprofen. 29 They measured the contact depth and the peak loads to estimate the hardness values (5.6, 2.0, 0.5, and 0.5 GPa, respectively) for these pharmaceuticals. Since smaller indentation depth would be expected for harder material, the ordering of materials in terms of contact depth was similar with that of hardness. Quantitative analysis of surface mechanical properties in this approach facilitates the selection of the right combination of drug and carrier molecules.

Another way of evaluating the micromechanical properties of the surface is by pressing the probe into the surface to determine its hardness and stickiness. 10 This could be done under controlled temperature and humidity with minimal sample preparation to measure the dynamic responses of the pharmaceutical to environmental conditions.

AFM could also be used to measure the mechanical properties of biological materials and even living cells. This area of research is already paving the way to understanding disease mechanisms and potentially evaluating the effects of drugs on cellular behavior. Studying the aortic stiffening that comes with aging, Canugovi et al. relied on AFM-based measurement of cell stiffness in the way to discover the disease mechanism.30 The researchers suspected a gene (Nox4) that is involved in cellular oxidative stress and has increased expression on older ages. They speculated whether aortic cells of young mice with increased expression of the gene will have increased stiffness. For this purpose, they generated transgenic mice which overexpressed Nox4. The researchers then measured the elastic modulus of aortic vascular smooth muscle cells from both transgenic and wild-type mice (Fig. 6) using the AFMWorkshop™ TT-AFM. Aortic vascular smooth muscle cells (VSMCs) from mice with different genetic backgrounds were compared according to the elastic modulus. They observed that aortic vascular smooth muscle cells from transgenic mice had significantly higher stiffness than wild-type mice, despite both groups of mice being young.

Mechanical Characterization of Drugs and Biological Entities
Figure 6. Measurement of cell stiffness (elastic modulus) using TT-AFM in contact mode to obtain the force-distance (F-D) curves for each cell and derive elastic modulus. The histogram shows elastic modulus for at least 10 VSMCs and 100 observations per each genotype. AFM measurements were carried out in cell buffer, where 5-15 F-D curves were obtained from many regions of each cell.30

 

In the described example, the measurement of the cellular mechanical property using AFM helped in identifying the evidence to disease mechanism. The question to whether overexpression of a gene causes stiffening of aortic cells has been answered. In this light, AFM can be used to further lead this line of research into drug discovery. Potential drugs that reduce the expression of a gene involved in the disease progression or interfere with the physiology of disease (e.g. bringing cellular stiffness to acceptable levels) could be tested on cells, and their effectiveness could be inferred based on AFM measurement outputs.

 

CHARACTERIZATION OF COATINGS AND SURFACES

Characterization of surfaces and coatings is vital to keep their quality near to standard. AFM can be used to determine various parameters of surface characterization such as pore structure, roughness, and surface area.13 The nanoscale surface morphology of material surfaces, coatings, and thin films can be associated with composition, fabrication parameters, and performance.15

A noteworthy application is the characterization of nanocoatings for cardiovascular implants.20 Biocompatible polymers, which are increasingly becoming a standard tool for drug delivery, are used in coating stents. It is essential to understand whether they retain their morphological and mechanical features when loaded with drugs. Wu et al. used AFM to study structural and mechanical differences between polylactic acid (PLA) coated stents and PLA/everolimus drug-eluting stents (DES).31 The researchers studied two different PLA/everolimus ratios (1:1 and 1:3). While the 1:1 PLA/everolimus coating was similar to PLA coating in both topography and phase imaging, the 1:3 PLA/everolimus coating had significant differences. The data suggested that the 1:3 polymer/drug ratio is not suitable for implant coating since the polymer loses its morphological and mechanical features at this ratio.

In another surface characterization application, AFM has been used to measure the nanoscale surface roughness of electrode materials used in neuroprosthetics and to discover how they are related to material processing conditions.32 The neuroprosthetics field requires microelectrodes with increased electrochemical stability as they will serve as neural implants. First, they have to endure the corrosive biochemical environment that compromises their functionality. They also need to withstand billions of cycles of electrical stimulation, thus, to be applicable in clinics. In this context, Huynh et al. evaluated the surface properties of two materials, glassy carbon and platinum, by using AFM as they changed microfabrication processing parameters.

Characterization of Coatings and Surfaces
Figure 7. AFM images of glassy carbon and platinum electrode surfaces exposed to varying fabrication process conditions. Glassy carbon surfaces were treated with N 2 of varying flow rates (a. 7.5 sccm, b. 15 sccm, c. 22.5 sccm). On the other hand, platinum surfaces were processed with argon gas of varying pressures (d. 0.7 Pa, e. 1.1 Pa, c. 1.5 Pa). Next, the electrode surfaces were scanned with AFMWorkshop™ TT-AFM equipment in tapping mode. Insets exhibit images with higher resolutions. The average roughness value was calculated for each surface-treatment combination and given at the top of the image.32

 

Glassy carbon surfaces are treated with nitrogen (N2) flow as part of their processing as an electrode material. The researchers aimed to investigate how the N2 flow rate affects glassy carbon surface roughness (Fig. 7a-7c). It is observed that as the flow rate increases, the roughness increases as well. They used thin-film platinum as a second electrode material. Here, they altered the pressure parameter to argon gas treatment and studied its effect on surface roughness (Fig. 7d-7f). The surface roughness decreases as the pressure increases. The researchers related the surface roughness data and processing parameters to the performance parameters such as the corrosion rate. Their general conclusion was that processing conditions determine surface roughness, which in turn affects the performance and stability of microelectrodes.

 

DRUG DISCOVERY STUDIES

Pathological aggregation of proteins caused by their misfolding is known to lead to metabolic diseases, such as Type II Diabetes, besides neurodegenerative diseases. Insulin is a protein hormone that is used as a therapeutic drug to regulate glucose homeostasis in diabetic patients. However, its high aggregation and fibrillation capacity not only limits its activity but can also have unwanted systemic side effects (amyloidosis).33 The development of inhibitors of insulin aggregation for utilization in pharmaceutical formulations of insulin is vital to counter this effect.

AFM has been widely used to monitor protein aggregation and understand its mechanism. It is possible to evaluate the effect of environmental conditions in real-time, such as the presence of drugs, by using AFM techniques. Ratha et al. used AFMWorkshop™ equipment to discover a drug that can inhibit the insulin fibrillation process.33 The researchers tested two candidate peptide molecules for their potential in the inhibition of fibrillation. Insulin molecules were incubated either alone or with one of the peptides for specified periods at suitable conditions that favor aggregation. AFM images indicated that while insulin alone proceed to form fibrils when incubated sufficiently long (8 hours), fibrillation gets hampered with the use of one of the peptide molecules (Fig. 8). However, the other peptide molecule was not effective. In conclusion, AFM images helped the researchers in selecting the potent drug among the candidates.

Drug Discovery Studies
Figure 8. AFM images at various stages of insulin fibrillation. Insulin was incubated in appropriate conditions to induce fibrillation in the presence and absence of the peptides (indicated on the figure). AFM images were acquired in vibrating mode by using AFMWorkshop™ TT-AFM equipment.33

 

HISTOPATHOLOGICAL CHARACTERIZATION

Currently, biochemical staining of tissue sections succeeded by light microscopy analysis is the method commonly used for histological analysis. With this method, it is possible to identify the tissue-level changes that occur in pathological conditions or upon drug action. These changes may involve deformations in tissue layers, cellular infiltration, and destruction of the extracellular matrix. AFM can facilitate this analysis by simplifying sample preparation while providing a high-resolution image of tissue structures.

In a recent study by Nol to et al., AFM has been employed for histopathological characterization of rat gastric tissue.34 The researchers intended to observe the damaging effects to the stomach of the drug alendronate, commonly used to treat osteoporosis, and the possible protective effects of the drug metformin from this damage. Four groups of rats received either of the following protocols: Saline solution (negative control), Alendronate (ALD), ALD + Metformin, ALD + Metformin + Compound C (the latter interferes with metformin activity). AFM images of the gastric tissue sections showed the destruction of the submucosal layers and collagen fibers, and also the loss of epithelium and fold in the ALD-treated group when compared to the negative control (Fig. 9A, 9C). On the other hand, metformin treatment protected against the damage, as the epithelium, the folds, and the collagen fibers of the gastric mucosa preserved their integrity (Fig. 9B). Also, the darker areas representing the lesions were reduced in metformin treated group. In the fourth group, Compound C reversed some of the beneficial effects of metformin by damaging the integrity of epithelium and collagen fibers (Fig. 9D).

Histopathological Characterization
Figure 9. AFM-based histological analysis of rat gastric mucosal tissue. AFMWorkshop ™ TT-AFM instrument was used in vibrating mode to analyze the protective effect of metformin on gastric damage induced by the drug alendronate. Rat treatment protocols were as follows: (a) Saline solution (negative control); (b) Metformin and Alendronate; (c) Alendronate (positive control); and (d) Compound C, Metformin, and Alendronate.34

 

In this study, AFM allowed eliminating the staining procedure from the histological analysis. Sectioned tissue slides were directly used for analysis by AFM after deparaffinization and without going through H&E staining, which is performed in the conventional method. AFM analysis also allowed to visualize the thinner structures, such as collagen fibers, than what is possible with light microscopy.

 

DISEASE MARKER DISCOVERY

Early diagnosis is critical to prevent disease progression. However, slight phenotypic alterations at the early stages are usually not detectable with conventional diagnostic tools. Nanometer-size precision of AFM allows detecting such small structural and mechanical changes that are involved in the pathology of various diseases.25

Eaton et al. utilized AFM imaging to visualize the morphological changes in eosinophils of acute asthma patients.35 Eosinophils are leukocytes with wide-ranging functions as a part of innate and adaptive responses. These cells have been implicated in the pathophysiology of many diseases, from inflammatory and allergic diseases to skin and gastrointestinal disorders. The researchers relied on previous works that showed how eosinophil activation and the accompanying increase in their number and morphological changes correlated with the progression of inflammatory diseases. As a result, they hypothesized that AFM could capture the minute details at an early stage of their activation that could not be detected with conventional imaging, serving as an early biomarker of the disease.

Disease Marker Discovery
Figure 10. AFM and light microscopy images of eosinophils from healthy individuals and acute asthma patients. AFMWorkshop ™ TT-AFM instrument was used in vibrating mode to obtain the height images (first column) and amplitude images (second column). A-F shows images of normal eosinophils from healthy individuals, while G-L shows the morphological changes in activated eosinophils from patients, respectively. The scale bars represent a length of 5 μm. Globular features indicated by arrows might be a sign of granulation.35

 

The researchers compared the eosinophils from healthy subjects with the eosinophils from acute asthma patients. Both AFM and light microscope images showed that eosinophils from healthy individuals have a rounded morphology with minimal spreading (Fig. 10a-10f). On the other hand, individuals with asthma symptoms had activated eosinophils with irregular, spreading morphology (Fig. 10g-10l). Losing their rounded shape, activated cells displayed separate granules in the vicinity, indicating the degranulation process. These phenotypes can be observed also by a light microscope, nevertheless, AFM revealed higher details. Activated cells also presented pseudopods, fiber-like structures, that could be discerned better with the help of AFM. The higher resolution of AFM allowed detecting smaller and thinner pseudopods. Consequently, a higher number of pseudopods could be counted from an AFM image of the same eosinophil than its light microscope image (Fig. 10g-10l).

These data show that AFM enables visualization of the subtle morphological changes related to eosinophils and thus provides higher sensitivity than optical microscopy. Such small eosinophilic alterations should be investigated for their biomarker role at early stages of several diseases besides asthma, including allergic and infectious diseases and possibly cancer. As it needs only minimal sample preparation, AFM can be employed both in the discovery of biomarkers and as a diagnostic tool.

Mechanical changes associated with the disease could also be detected by AFM and serve as a biomarker. Stolz et al. employed AFM to monitor morphological and biomechanical changes in mouse and human cartilage tissue according to the progression of age or osteoarthritis.36 Topographical images of mice cartilage revealed thickening of collagen fibrils depending on age or disease stage.

Stiffness measurements appeared to be even more promising for diagnostic purposes. The researchers measured microscale and nanoscale stiffness in articular cartilage samples, which represented various disease stages (grades 0–3) from the 77-year-old osteoarthritis patient. The results show that while mentioned disease stages (especially early stages) are not distinguishable by micro-stiffness analysis, that is not the case by nano-stiffness measurements carried out by AFM. Regarding the lack of requirement for specific sample preparation or ambient condition, AFM can be integrated easily into histopathology laboratories for measuring tissue-level biomarkers.

 

CHARACTERIZATION OF ANTIMICROBIAL EFFECTS OF DRUGS

Characterization of prokaryotic or eukaryotic cells at the nanoscale brings remarkable advantages. It is possible to determine the adhesion of microorganisms onto various surfaces and identify bacteria- resistant surfaces.20 The most commonly reported usage is investigating the effect of antimicrobial agents at a single cell level that became possible with the use of AFM without the need for complicated sample preparation procedures.

Intestinal tract infections due to bacteria such as E. coli are the most common cause of diarrhea, especially in developing countries. Overusing conventional antibiotics renders them ineffective as bacteria develop resistance to these agents. Hence, the development of antibacterial agents that use a novel mechanism to inhibit bacterial growth is critical.

Characterization of Antimicrobial Effects of Drugs
Figure 11. Representative AFM images showing the morphological effect of antibacterial peptide treatment on E. coli bacteria: (A) untreated; (B) after 24 h of peptide treatment at the minimum inhibitory concentration (MIC). Imaging was carried out in tapping mode by using the TT-AFM (AFMWorkshop) instrument (Taken from ref. 37).

 

Placido et al. developed a peptide-based antibacterial agent and tested its effect against bacterial growth.37 AFMWorkshop™ TT-AFM instrument was used to study the action mechanism of antibacterial peptides. AFM images indicated that bacterial membranes lose their integrity when treated with the peptide at its minimal inhibitory concentration (Fig. 11). The flat and smooth structure of the intact membrane in the control bacteria deformed into blistered morphology in peptide-treated bacteria. The damage to the membrane was demonstrated further by the increase in the surface roughness (3.03 to 16.33 nm).

 

 

REFERENCES


 

  1. 1 https://www.economist.com/technology-quarterly/2020/03/12/new-drugs-are-costly-and-unmet-need-is-growing

  2. 2 https://doi.org/10.1016/S1369-7021(10)70142-5

  3. 3 https://microscopy-analysis.com/sites/default/files/magazine_pdfs/mag%202009_April_Roberts.pdf

  4. 4 https://pubweb.eng.utah.edu/~lzang/images/Lecture_10_AFM.pdf

  5. 5 https://www.nanoscience.com/techniques/atomic-force-microscopy/

  6. 6 https://www.nanosurf.com/en/how-afm-works

  7. 7 https://www.sciencedirect.com/science/article/abs/pii/S0304399199001643

  8. 8 http://pmbrc.org/files/9013/8738/5149/Marc%20Kelly%20AFM%20in%20Pharmaceutical%20Characterisation.pdf

  9. 9 https://doi.org/10.1017/S1431927606066402

  10. 10 http://www.pharmtech.com/atomic-force-microscopy-0

  11. 11 http://nanoscaleworld.bruker-axs.com/nanoscaleworld/forums/p/353/509.aspx

  12. 12 https://doi.org/10.1016/S0022-0248(99)00819-2

  13. 13 https://www.azom.com/article.aspx?ArticleID=3282

  14. 14 https://doi.org/10.4172/2153-2435.1000e131

  15. 15 https://doi.org/10.2174/157341209788922020

  16. 16 https://www.lifescienceintegrates.com/wp-content/uploads/2019/02/JStar_API_Crystallization_WP.pdf

  17. 17 https://doi.org/10.1002/jps.22603

  18. 18 https://doi.org/10.1023/A:1007524729146

  19. 19 https://doi.org/10.1016/j.ajps.2014.05.002

  20. 20 https://doi.org/10.1007/978-1-4939-4029-5_20

  21. 21 https://doi.org/10.1023/A:1011046728622

  22. 22 https://doi.org/10.1016/j.ijpharm.2008.01.042

  23. 23 https://doi.org/10.1016/S0378-5173(02)00400-3

  24. 24 https://doi.org/10.1016/j.ejps.2004.11.002

  25. 25 https://doi.org/10.1016/j.trac.2016.03.014

  26. 26 https://doi.org/10.1023/B:PHAM.0000041453.24419.8a

  27. 27 https://doi.org/10.1016/j.mtcomm.2019.100762

  28. 28 https://doi.org/10.1515/acph-2016-0032

  29. 29 https://doi.org/10.1016/j.ijpharm.2008.06.015

  30. 30 https://doi.org/10.1016/j.redox.2019.101288

  31. 31 https://doi.org/10.1016/j.ejps.2008.12.001

  32. 32 https://doi.org/10.1007/s00542-019-04618-6

  33. 33 https://doi.org/10.1016/j.bbapap.2019.01.007

  34. 34 https://doi.org/10.1016/j.ejphar.2019.172410

  35. 35 https://doi.org/10.3389/fphys.2019.01261

  36. 36 https://doi.org/10.1038/nnano.2008.410

  37. 37 https://doi.org/10.1016/j.msec.2017.02.027

 

 

×

Search for mobile


TOP