Enabling formulations of aprepitant: in vitro and in vivo comparison of nanocrystalline, amorphous and deep eutectic solvent based formulations

A deep eutectic solvent (DES) is a eutectic system consisting of hydrogen bond donor and acceptor has been suggested as a promising formulation strategy for poorly soluble drugs. A DES consisting of choline chloride and levulinic acid in a 1:2  molar ratio was used to formulate a liquid solution of the model drug aprepitant. This formulation was tested in vitro (drug release and permeability) and in vivo (rat model) and compared with the performance of amorphous aprepitant and the commercial aprepitant nanocrystalline formulation. In this study a DES formulation is compared for the first time directly to other established enabling formulations. The in vitro drug release study demonstrated that the DES formulation and the amorphous form both were able to induce an apparent supersaturation followed by subsequent drug precipitation. To mitigate the risk of precipitation, HPMC was predissolved in the dissolution medium, which successfully reduced the degree of precipitation. In line with the results from the release study, an in vitro permeation study showed superior permeation of the drug from the DES formulation and from the amorphous form compared to the nanocrystalline formulation. However, the promising in vitro findings could not be directly translated into an increased in vivo performance in rats compared to the nanocrystalline formulation. Whilst the DES formulation (34 ± 4%) showed a higher oral bioavailability compared to amorphous aprepitant (20 ± 4%), it was on par with the oral bioavailability obtained from the nanocrystalline formulation (36 ± 2%).

Rapid Prototyping of Miniaturized Powder Mixing Geometries

Continuous manufacturing is an important element of future manufacturing solutions enabling for both high product quality and streamlined development process. The increasing possibilities with computer simulations allow for innovating novel mixing principles applicable for continuous manufacturing. However, these innovative ideas based on simulations need experimental validation. The use of rapid prototyping based on additive manufacturing opens a possibility to evaluate these ideas at a low cost. In this study, a novel powder mixing geometry was prototyped using additive manufacturing and further, interfaced with an in-line near-IR spectrometer allowing for investigating the residence time distribution (RTD) in this geometry.

Automated digital design for 3D-printed individualized therapies

Customization of pharmaceutical products is a central requirement for personalized medicines. However, the existing processing and supply chain solutions do not support such manufacturing-on-demand approaches. In order to solve this challenge, three-dimensional (3D) printing has been applied for customization of not only the dose and release characteristics, but also appearance of the product (e.g., size and shape). A solution for customization can be realized via non-expert-guided processing of digital designs and drug dose. This study presents a proof-of-concept computational algorithm which calculates the optimal dimensions of grid-like orodispersible films (ODFs), considering the recommended dose. Further, the algorithm exports a digital design file which contains the required ODF configuration. Cannabidiol (CBD) was incorporated in the ODFs, considering the simple correspondence between the recommended dose and the patient's weight. The ODFs were 3D-printed and characterized for their physicochemical, mechanical, disintegration and drug release properties. The algorithm was evaluated for its accuracy on dose estimation, highlighting the reproducibility of individualized ODFs. The in vitro performance was principally affected by the thickness and volume of the grid-like structures. The concept provides an alternative approach that promotes automation in the manufacturing of personalized medications in distributed points of care, such as hospitals and local pharmacies.

Monitoring the Isothermal Dehydration of Crystalline Hydrates Using Low-Frequency Raman Spectroscopy

Detection of the solid-state forms of pharmaceutical compounds is important from the drug performance point of view. Low-frequency Raman (LFR) spectroscopy has been demonstrated to be very sensitive in detecting the different solid-state forms of pharmaceutically relevant compounds. The potential of LFR spectroscopy to probe the in situ isothermal dehydration was studied using piroxicam monohydrate (PXM) and theophylline monohydrate (TPMH) as the model drugs. The dehydration of PXM and TPMH at four different temperatures (95, 100, 105, and 110 °C and 50, 60, 70, and 80 °C, respectively) was monitored in both the low- (20-300 cm^-1) and mid-frequency (335-1800 cm^-1) regions of the Raman spectra. Principal component analysis and multivariate curve resolution were applied for the analysis of the Raman data. Spectral differences observed in both regions highlighted the formation of specific anhydrous forms of piroxicam and theophylline from their respective monohydrates. The formation of the anhydrous forms was detected on different timescales (approx. 2 min) between the low and mid-frequency Raman regions. This finding highlights the differing nature of the vibrations being detected between these two spectral regions. Computational simulations performed were also in agreement with the experimental results, and allowed elucidating the origin of different spectral features.

In situ nanoscale visualization of solvent effects on molecular crystal surfaces

Atomic force microscopy and molecular dynamics simulations probed the crystallinity and hydrophobicity of a paracetamol crystal surface in water–ethanol mixtures. We observe the formation of a dynamic heterogenous disordered surface (DHDS) layer.

Effect of dehydration pathway on the surface properties of molecular crystals

Atomic force microscopy was used to determine roughness, elastic modulus and work function after thermally-induced and solvent-induced dehydration. These properties correlated with electric charging to provide insight into behaviour of bulk powders.

Determination of Residence Time Distribution in a Continuous Powder Mixing Process With Supervised and Unsupervised Modeling of In-line Near Infrared (NIR) Spectroscopic Data

Successful implementation of continuous manufacturing processes requires robust methods to assess and control product quality in a real-time mode. In this study, the residence time distribution of a continuous powder mixing process was investigated via pulse tracer experiments using near infrared spectroscopy for tracer detection in an in-line mode. The residence time distribution was modeled by applying the continuous stirred tank reactor in series model for achieving the tracer (paracetamol) concentration profiles. Partial least squares discriminant analysis and principal component analysis of the near infrared spectroscopy data were applied to investigate both supervised and unsupervised chemometric modeling approaches. Additionally, the mean residence time for three powder systems was measured with different process settings. It was found that a significant change in the mean residence time occurred when comparing powder systems with different flowability and mixing process settings. This study also confirmed that the partial least squares discriminant analysis applied as a supervised chemometric model enabled an efficient and fast estimate of the mean residence time based on pulse tracer experiments.

Simultaneous automated image analysis and Raman spectroscopy of powders at an individual particle level

Solid form diversity of raw materials can be critical for the performance of the final drug product. In this study, Raman spectroscopy, image analysis and combined Raman and image analysis were utilized to characterize the solid form composition of a particulate raw material. Raman spectroscopy provides chemical information and is complementary to the physical information provided by image analysis. To demonstrate this approach, binary mixtures of two solid forms of carbamazepine with a distinct shape, an anhydrate (prism shaped) and a dihydrate (needle shaped), were characterized at an individual particle level. Partial least squares discriminant analysis classification models were developed and tested with known, gravimetrically mixed test samples, followed by analysis of unknown, commercially supplied carbamazepine raw material samples. Classification of several thousands of particles was performed, and it was observed that with the known binary mixtures, the minimum number of particles needed for the combined Raman spectroscopy - image analysis classification model was approximately 100 particles per solid form. The carbamazepine anhydrate and dihydrate particles were detected and classified with a classification error of 1 % using the combined model. Further, this approach allowed the identification of raw material solid form impurity in unknown raw material samples. Simultaneous automated image analysis and Raman spectroscopy of powders at an individual particle level has its potential in accurate detection of low amounts of unwanted solid forms in particulate raw material samples.

Image-Based Artificial Intelligence Methods for Product Control of Tablet Coating Quality

Mimicking the human decision-making process is challenging. Especially, many process control situations during the manufacturing of pharmaceuticals are based on visual observations and related experience-based actions. The aim of the present work was to investigate the use of image analysis to classify the quality of coated tablets. Tablets with an increasing amount of coating solution were imaged by fast scanning using a conventional office scanner. A segmentation routine was implemented to the images, allowing the extraction of numeric image-based information from individual tablets. The image preprocessing was performed prior to utilization of four different classification techniques for the individual tablet images. The support vector machine (SVM) technique performed superior compared to a convolutional neural network (CNN) in relation to computational time, and this approach was also slightly better at classifying the tablets correctly. The fastest multivariate method was partial least squares (PLS) regression, but this method was hampered by the inferior classification accuracy of the tablets. Finally, it was possible to create a numerical threshold classification model with an accuracy comparable to the SVM approach, so it is evident that there exist multiple valid options for classifying coated tablets.

Non-destructive quantification of fragmentation within tablets after compression from scattering analysis of terahertz transmission measurements

Material deformation behaviour has a critical impact on tablet formation. Fragmentation is one of the key mechanisms affecting the strength of a final compact, however, quantitative methods for estimating fragmentation are often complex, destructive and time-consuming. The purpose of this study was to investigate the applicability of terahertz time-domain spectroscopy (THz-TDS) to quantify fragmentation upon tableting. Up to five size fractions of microcrystalline cellulose (MCC), dibasic calcium phosphate (DCP), and lactose monohydrate (lactose) in the range of <125 µm up to the range of 355-500 µm were compressed into tablets and analysed with THz-TDS. The effective refractive index and absorbance spectra of whole tablets were measured in transmission, and the optical properties were clearly affected by fragmentation upon compression. The scattering observed from the absorbance spectra was fitted into a power law equation (y = Aν^B). It was observed that up to pressures of 50 MPa the values of parameter A that were extracted from the power law fit decreased exponentially with increasing compression pressure. For higher compression pressures the value of A remained constant. This observation was more pronounced for DCP, followed by lactose and then MCC and the effect was more pronounced for larger compared to smaller initial particles. The non-destructive measurements correlated with previously obtained results based on particle size distribution measurements of the particles before compression and those obtained from destructive analysis of tablets. The terahertz method can resolve similar differences in fragmentation behaviour upon compression compared to the particle size analysis but requires no sample preparation.

Effect of particle size and deformation behaviour on water ingress into tablets

Drug release performance of tablets is often highly dependent on disintegration, and water ingress is typically the rate-limiting step of the disintegration process. Water ingress into tablets is known to be highly influenced by the microstructure of the tablet, particularly tablet porosity. Initial particle size distribution of the formulation and the predominant powder deformation behaviour during compression are expected to impact such microstructure, making both factors important to investigate in relation to water ingress into tablets. Two size fractions (<125 and 355-500 µm) of plastically deforming microcrystalline cellulose (MCC) and fragmenting di-calcium phosphate (DCP) were compressed into tablets with porosities ranging from 5 to 30% (with 5% increments). The total porosity of the tablets was measured using terahertz time-domain spectroscopy and liquid transport into these tablets was quantified using a flow cell coupled to terahertz pulsed imaging. It was found that tablets compressed from large MCC particles resulted in slower water ingress compared to tablets prepared from small MCC particles. In contrast, no difference in liquid transport kinetics was observed for tablets prepared across both size fractions of DCP particles. These results highlight the complex interplay between material characteristics, the process induced microstructure, and the liquid transport process that ultimately determines the drug release performance of the tablets.

Fabrication of Mucoadhesive Buccal Films for Local Administration of Ketoprofen and Lidocaine Hydrochloride by Combining Fused Deposition Modeling and Inkjet Printing

In the area of developing oromucosal drug delivery systems, mucoadhesive buccal films are the most promising formulations for either systemic or local drug delivery. The current study presents the fabrication of buccal films, by combining fused deposition modeling (FDM) and inkjet printing. Hydroxypropyl methylcellulose-based films were fabricated via FDM, containing the non-steroidal anti-inflammatory drug ketoprofen. Unidirectional release properties were achieved, by incorporating an ethyl cellulose-based backing layer. The local anesthetic lidocaine hydrochloride, combined with the permeation enhancer l-menthol, was deposited onto the film by inkjet printing. Physicochemical analysis showed alterations in the characteristics of the films, and the mucoadhesive and mechanical properties were effectively modified, due to the ink deposition on the substrates. The in vitro release data of the active pharmaceutical compounds, as well as the permeation profiles across ex vivo porcine buccal mucosa and filter-grown TR146 cells of human buccal origin, were associated with the presence of the permeation enhancer and the backing layer. The lack of any toxicity of the fabricated films was demonstrated by the MTT viability assay. This proof-of-concept study provides an alternative formulation approach of mucoadhesive buccal films, intended for the treatment of local oromucosal diseases or systemic drug delivery.

Continuous Manufacturing of a Polymer Stabilized Emulsion Monitored with Process Analytical Technology

Moving from batch to continuous manufacturing (CM) requires implementation of process analytical technology (PAT), as it is crucial to monitor and control these processes. CM of semi-solids has been demonstrated but implementation of a broader range of PAT tools with in- or on-line process interfacing at the end of the CM line has not been demonstrated. The goal of this work was to continuously manufacture creams and to investigate whether in- and on-line measurement of viscosity, changes in the concentration of active pharmaceutical ingredient (API), and pH could be used to support optimization of a model cream product. Additionally, the torque of the mixers was assessed for determination of the physical properties of the cream. Two Raman probes with different probe optics were compared for characterization of the API concentration. The API concentration, amount of neutralizer, and mixing speed of the CM line were systematically varied. Both the PhAT probe with a larger sampling volume and immersion Raman probe with a smaller sampling volume could detect the step changes in the API concentration. The torque from the mixer was compared with the viscosity measurements, but the torque signal could not be correlated with the viscosity due to the dynamic nature of the polymer conformation and the time-dependency of this property. Adjustment of pH of the cream could be monitored with the current installation. The investigated PAT tools could be implemented into a continuous line and, further, be used to support the optimization of a model cream composition and related process parameters.

Quality by design thinking in the development of long-acting injectable PLGA/PLA-based microspheres for peptide and protein drug delivery

Adopting the Quality by Design (QbD) approach in the drug development process has transformed from "nice-to-do" into a crucial and required part of the development, ensuring the quality of pharmaceutical products throughout their whole life cycles. This review is discussing the implementation of the QbD thinking into the production of long-acting injectable (LAI) PLGA/PLA-based microspheres for the therapeutic peptide and protein drug delivery. Various key elements of the QbD approaches are initially elaborated using Bydureon®, a commercial product of LAI PLGA/PLA-based microspheres, as a classical example. Subsequently, the factors influencing the release patterns and the stability of the peptide and protein drugs are discussed. This is followed by a summary of the state-of-the-art of manufacturing LAI PLGA/PLA-based microspheres and the related critical process parameters (CPPs). Finally, a landscape of generic product development of LAI PLGA/PLA-based microspheres is reviewed including some major challenges in the field.

In silico design and 3D printing of microfluidic chips for the preparation of size-controllable siRNA nanocomplexes

Small interfering RNA (siRNA) is regarded as one of the most powerful tools for the treatment of various diseases by downregulating the expression of aberrant proteins. Delivery vehicle is often necessary for getting siRNA into the cells. Nanocomplex using polyamidoamine (PAMAM) is regarded a promising approach for the delivery of siRNA. The size of siRNA nanocomplexes is a critical attribute in order to achieve high gene silencing efficiency in vivo. Microfluidics provides advantages in the preparation of siRNA nanocomplexes due to better reproducibility and a potential for more robust process control. The mixing efficiency of siRNA and PAMAM is different in microfluidics systems with different geometries, therefore, resulting in nanocomplexes with varying size attributes. In this study, hydrodynamic flow focusing microfluidic chips with different channel designs, i.e. diameters/widths, channel shapes (cylindrical/rectangular) and inter-channel spacings were optimized in silico and rapidly prototyped using 3D printing and finally, used for production of siRNA nanocomplexes. The fluid mixing inside the microfluidic chips was simulated using the finite element method (FEM) with the single-phase laminar flow interface in connection with the transport of diluted species interface. The digital design and optimization of microfluidic chips showed consistency with experimental results. It was concluded that the size of siRNA nanocomplexes can be controlled by adjusting the channel geometry of the microfluidic chips and the simulation with FEM could be used to facilitate the design and optimization of microfluidic chips in order to produce nanocomplexes with desirable attributes.

Near infrared analysis of pharmaceutical powders with empirical target distribution optimization (ETDO)

Near infrared (NIR) spectroscopy is a well-established method for analysis of pharmaceutical products, and especially useful for process monitoring and control of continuous production due to high sample throughput. In this work, a previously established method called empirical target distribution optimization (ETDO) wherein reference sample values using information from model prediction of the calibration data was used as a tool to improve the performance of NIR partial least squares (PLS) models. Model performance was assessed using root mean square error (R²), bias and accuracy in prediction of test samples. A target value selection threshold was tested to assess the ETDO procedure for NIR analysis of powder samples. The amount of specific variation captured by the model was examined and compared for models calibrated with and without ETDO. The results reported in this work suggests that PLS models optimized with ETDO of reference values can provide more specific PLS models for NIR analysis for complex powder mixtures. In addition, the model optimization method could also be applied as a tool to verify the necessary amount of PLS components to produce robust models. The ETDO method presented in this work is an approach that could be applied in the development of continuous blending or tableting processes where robust in-line quantitative analysis of powder samples is needed.

Single particles as resonators for thermomechanical analysis

Thermal methods are indispensable for the characterization of most materials. However, the existing methods require bulk amounts for analysis and give an averaged response of a material. This can be especially challenging in a biomedical setting, where only very limited amounts of material are initially available. Nano- and microelectromechanical systems (NEMS/MEMS) offer the possibility of conducting thermal analysis on small amounts of materials in the nano-microgram range, but cleanroom fabricated resonators are required. Here, we report the use of single drug and collagen particles as micro mechanical resonators, thereby eliminating the need for cleanroom fabrication. Furthermore, the proposed method reveals additional thermal transitions that are undetected by standard thermal methods and provide the possibility of understanding fundamental changes in the mechanical properties of the materials during thermal cycling. This method is applicable to a variety of different materials and opens the door to fundamental mechanistic insights.

Temperature-Modulated Micromechanical Thermal Analysis with Microstring Resonators Detects Multiple Coherent Features of Small Molecule Glass Transition

Micromechanical Thermal Analysis utilizes microstring resonators to analyze a minimum amount of sample to obtain both the thermal and mechanical responses of the sample during a heating ramp. We introduce a modulated setup by superimposing a sinusoidal heating on the linear heating and implementing a post-measurement data deconvolution process. This setup is utilized to take a closer look at the glass transition as an important fundamental feature of amorphous matter with relations to the processing and physical stability of small molecule drugs. With an additionally developed image and qualitative mode shape analysis, we are able to separate distinct features of the glass transition process and explain a previously observed two-fold change in resonance frequency. The results from this setup indicate the detection of initial relaxation to viscous flow onset as well as differences in mode responsivity and possible changes in the primary resonance mode of the string resonators. The modulated setup is helpful to distinguish these processes during the glass transition with varying responses in the frequency and quality factor domain and offers a more robust way to detect the glass transition compared to previously developed methods. Furthermore, practical and theoretical considerations are discussed when performing measurements on string resonators (and comparable emerging analytical techniques) for physicochemical characterization.

Medication Tracking: Design and Fabrication of a Dry Powder Inhaler with Integrated Acoustic Element by 3D Printing

PURPOSE

Asthma is a prevalent lung disorder that cause heavy burdens globally. Inhalation medicaments can relieve symptoms, improve lung function and, thus, the quality of life. However, it is well-documented that patients often do not get the prescribed dose out of an inhaler and the deposition of drug is suboptimal, due to incorrect handling of the device and wrong inhalation technique. This study aims to design and fabricate an acoustic dry powder inhaler (ADPI) for monitoring inhalation flow and related drug administration in order to evaluate whether the patient receives the complete dose out of the inhaler.

METHODS

The devices were fabricated using 3D printing and the impact of the acoustic element geometry and printing resolution on the acoustic signal was investigated. Commercial Foradil (formoterol fumarate) capsules were used to validate the availability of the ADPI for medication dose tracking. The acoustic signal was analysed with Partial-Least-Squares (PLS) regression.

RESULTS

Indicate that specific acoustic signals could be generated at different air flow rates using a passive acoustic element with specific design features. This acoustic signal could be correlated with the PLS model to the air flow rate. A more distinct sound spectra could be acquired at higher printing resolution. The sound spectra from the ADPI with no capsule, a full capsule and an empty capsule are different which could be used for medication tracking.

CONCLUSIONS

This study shows that it is possible to evaluate the medication quality of inhaled medicaments by monitoring the acoustic signal generated during the inhalation process.

Investigation of the effects of particle size on fragmentation during tableting

Particle size is a critical parameter during tablet production as it can impact tabletability, flowability, and dissolution rate of the final product. The purpose of this study was to investigate the effect of initial particle size on fragmentation of pharmaceutical materials during tableting. Initial particle size fractions ranging from 0-125 to 355-500 µm of dibasic calcium phosphate (DCP), lactose monohydrate, and agglomerated and non-agglomerated microcrystalline cellulose (MCC) were blended with magnesium stearate and compressed into tablets. Larger initial particle sizes were found to fragment more extensively than smaller initial particle sizes for all materials based on the particle size distributions determined by laser diffraction. DCP was found to fragment most extensively followed by lactose and both MCCs. The fragmentation degrees of DCP, lactose, agglomerated and non-agglomerated MCC reached 95, 81, 32, and 29%, respectively. These findings were further supported by an increase in specific surface area with increasing compression pressure of compressed particles. The NIR spectral baseline offset from tablets was found to increase with increasing compression pressure up to 50 MPa for all materials, which was the same compression pressure range where fragmentation was observed. The NIR spectral slope from tablets as a function of compression pressure furthermore showed a similar trend as the tabletability profiles. NIR spectroscopy can thereby potentially be used as a surrogate control strategy for assessing compression related particle size changes and possibly tablet density and deformation behavior during tablet production.