Manufacturing process of liposomal Formation: A coarse-grained molecular dynamics simulation.

A method of producing liposomes has been previously developed using a continuous manufacturing technology that involves a co-axial turbulent jet in co-flow. In this study, coarse-grained molecular dynamics (CG-MD) simulations were used to gain a deeper understanding of how the self-assembly process of liposomes is affected by the material attributes (such as the concentration of ethanol) and the process parameters (such as temperature), while also providing detailed information on a nano-scale molecular level. Specifically, the CG-MD simulations yield a comprehensive internal view of the structure and formation mechanisms of liposomes containing DPPC, DPPG, and cholesterol molecules. The importance of this work is that structural details on the molecular level are proposed, and such detail is not possible to obtain through experimental studies alone. The assessment of structural properties, including the area per lipid, diffusion coefficient, and order parameters, indicated that a thicker bilayer was observed at higher ethanol concentrations, while a thinner bilayer was present at higher temperatures. These conditions led to more water penetrating the interior of the bilayer and an unstable structure, as indicated by a larger contact area between lipids and water, and a higher coefficient of lipid lateral diffusion. However, stable liposomes were found through these evaluations at lower ethanol concentrations and/or lower process temperatures. Furthermore, the CG-MD model was further compared and validated with experimental and computational data including liposomal bilayer thickness and area per lipid measurements.

Studying the ssDNA loaded adeno-associated virus aggregation using coarse-grained molecular dynamics simulations.

The aggregation of adeno-associated viral (AAV) capsids in an aqueous environment was investigated via coarse-grained molecular dynamics (CG-MD) simulations. The primary driving force and mechanism of the aggregation were investigated with or without single-strand DNA (ssDNA) loaded at various process temperatures. Capsid aggregation appeared to involve multiple residue interactions (i.e., hydrophobic, polar and charged residues) leading to complex protein aggregation. In addition, two aggregation mechanisms (i.e., the fivefold face-to-face contact and the edge-to-edge contact) were identified from this study. The ssDNA with its asymmetric structure could be the reason for destabilizing protein subunits and enhancing the interaction between the charged residues, and further result in the non-reversible face-to-face contact. At higher temperature, the capsid structure was found to be unstable with the significant size expansion of the loaded ssDNA which could be attributed to reduced number of intramolecular hydrogen bonds, the increased conformational deviations of protein subunits and the higher residue fluctuations. The CG-MD model was further validated with previous experimental and simulation data, including the full capsid size measurement and the capsid internal pressure. Thus, a good understanding of AAV capsid aggregation, instability and the role of ssDNA were revealed by applying the developed computational model.

Numerical study of drop dynamics for inkjet based 3D printing of pharmaceutical tablets.

Interest in 3D printing has been growing rapidly especially in pharmaceutical industry due to its multiple advantages such as manufacturing versatility, personalization of medicine, scalability, and cost effectiveness. Inkjet based 3D printing gained special attention after FDA's approval of Spritam® manufactured by Aprecia pharmaceuticals in 2015. The precision and printing efficiency of 3D printing is strongly influenced by the dynamics of ink/binder jetting, which further depends on the ink's fluid properties. In this study, Computational Fluid Dynamics (CFD) has been utilized to study the drop formation process during inkjet-based 3D printing for piezoelectric and thermal printhead geometries using Volume of Fluid (VOF) method. To develop the CFD model commercial software ANSYS-Fluent was used. The developed CFD model was experimentally validated using drop watcher setup to record drop progression and drop velocity. During the study, water, Fujifilm model fluid, and Amitriptyline drug solutions were evaluated as the ink solutions. The drop properties such as drop volume, drop diameter, and drop velocity were examined in detail in response to change ink solution properties such as surface tension, viscosity, and density. A good agreement was observed between the experimental and simulation data for drop properties such as drop volume and drop velocity.

Head-to-head comparison of in vitro and in vivo efficacy of pHLIP-conjugated anti-seed gamma peptide nucleic acids.

Gamma peptide nucleic acids (γPNAs) have recently garnered attention in diverse therapeutic and diagnostic applications. Serine and diethylene-glycol-containing γPNAs have been tested for numerous RNA-targeting purposes. Here, we comprehensively evaluated the in vitro and in vivo efficacy of pH-low insertion peptide (pHLIP)-conjugated serine and diethylene-based γPNAs. pHLIP targets only the acidic tumor microenvironment and not the normal cells. We synthesized and parallelly tested pHLIP-serine γPNAs and pHLIP-diethylene glycol γPNAs that target the seed region of microRNA-155, a microRNA that is upregulated in various cancers. We performed an all-atom molecular dynamics simulation-based computational study to elucidate the interaction of pHLIP-γPNA constructs with the lipid bilayer. We also determined the biodistribution and efficacy of the pHLIP constructs in the U2932-derived xenograft model. Overall, we established that the pHLIP-serine γPNAs show superior results in vivo compared with the pHLIP-diethylene glycol-based γPNA.

Mitigation of Tribocharging in Pharmaceutical Powders using Surface Modified V-Blenders.

INTRODUCTION: The pharmaceutical industry involves handling of powders on a large scale for manufacturing of solid dosage forms such as tablets and capsules constituting about 85% of the dosage forms. During this manufacturing process, powders get electrostatically charged due to numerous particle-particle and particle-equipment wall collisions. Most of the pharmaceutical powders are insulators in nature and they accumulate charge for longer durations making it difficult to dissipate the generated charge. In this study, a surface modified blender has been used to analyze tribocharging in pharmaceutical powders. METHODS: The surface modified blender has been fabricated using two types of materials, an insulator, and a conductor. The conductor or the metal arm induces charge of opposite polarity to that of the charge induced by the insulator arm and the overall charge on the powder decreases during the tumbling motion of the blender. Ibuprofen was used as the model drug and processed in aluminum, polyvinyl chloride (PVC), stainless steel, surface modified aluminum-PVC (Al-PVC) and surface modified stainless steel- PVC (SS-PVC) blender at 20% RH for different blending times such as 2, 10, 20, 30 and 40 min. To better understand the tribocharging phenomenon in surface modified V blenders, an experimentally validated computational model was developed using Discrete Element Method (DEM) modeling. RESULTS: Significant reduction (> 50%) in electrostatic charge was observed for Ibuprofen using surface modified blenders in comparison to metal only and insulator only V blenders. Additionally, an identical charging trend was observed between the simulation and experimental data.  CONCLUSION: It was established that careful selection of equipment materials could significantly reduce the electrostatic charging of pharmaceutical powders and DEM model could be a really useful tool in assessing the applicability of the modified V blenders.

Large-Scale Freeze-Thaw of Protein Solutions: Study of the Relative Contributions of Freeze-Concentration and Ice Surface Area on Stability of Lactate Dehydrogenase.

Although bulk biotherapeutics are often frozen during fill finish and shipping to improve their stability, they can undergo degradation leading to losses in biological activity during sub-optimal freeze-thaw (F/T) process. Except for a few small-scale studies, the relative contribution of various F/T stresses to the instability of proteins has not been addressed. Thus, the objective of this study was to determine the individual contributions of freeze-concentration, ice surface area, and processing time to protein destabilization at a practical manufacturing-scale. Lactate dehydrogenase (LDH) in histidine buffer solutions were frozen in 1L containers. The frozen solutions were sliced into representative samples and assessed for the ice specific surface area (SSA) and extent of solutes freeze-concentration. For the first time to our knowledge, ice SSA was measured in dried samples from large-volume protein solutions using volumetric nitrogen adsorption isotherms. SSA measurements of the freeze-dried cakes showed that the ice surface area increased with an increase in the freezing rate. The ice SSA was also impacted by the position of the sample within the container: samples closer to the active cooled surface of the container exhibited smaller ice surface area compared to ice-cored samples from the center of the bottle. The freeze-concentrate composition was determined by measuring LDH concentration in the ice-cored samples. The protein distributed more evenly throughout the frozen solution after fast freezing which also correlated with enhanced protein stability compared to slow freezing conditions. Overall, better protein stability parameters correlated with higher ice SSA and lower freeze-concentration extent which was achieved at a faster freezing rate. Thus, extended residence time of the protein at the freeze-concentrated microenvironment is the critical destabilizing factor during freezing of LDH in bulk histidine buffer system. This study expands the understanding of the relative contributions of freezing stresses which, coupled with the knowledge of cryoprotection mechanisms, is imperative to the development of optimized processes and formulations aiming stable frozen protein solutions.

Pilot-scale binder jet 3D printing of sustained release solid dosage forms.

The additive nature and versatility of 3D printing show great promise in the rapid prototyping of solid dosage forms for clinical trials and mass customization for personalized medicine applications. This paper reports the formulation and process development of sustained release solid dosage forms, termed "printlets", using a pilot-scale binder jetting (BJT) 3D printer and acetaminophen (APAP) as the model drug. With the inclusion of hydroxypropyl methylcellulose (HPMC) as a release retardant polymer in the print powder, the drug release time of APAP increased considerably from minutes to hours. However, given the swelling propensity of HPMC, a thicker layer of powder must be laid down during printing to avoid any shape distortion of the printlets. For a fixed print volume, the level of binder saturation (i.e., ratio between the liquid binder and powder in the as-printed sample) is inversely proportional to the thickness of the spread powder layer. An increase in the spread powder layer inadvertently resulted in a lower level of binder saturation and consequently weaker printlets. By increasing the level of binder saturation with jetting from more print heads, the mechanical strength of printlets containing 18% HPMC was successfully restored. The resultant printlets have a drug release time of 3.5 h and a breaking force of 12.5 kgf that is comparable to the fast-disintegrating printlets containing no HPMC and surpasses manually pressed tablets with the same HPMC content.

Molecular Dynamics Modeling Based Investigation of the Effect of Freezing Rate on Lysozyme Stability.

PURPOSE: The stability of protein drug products frozen during fill finish operations is greatly affected by the freezing rate applied. Non-optimal freezing rates may lead to the denaturation of protein's complex macromolecular conformation. However, limited work has been done to address the effect of different freezing rates on protein stability at nano-scale level. METHODS: The stability of a model protein, lysozyme, was investigated at atomic and molecular scale under varying freezing rates and moving ice-water interface. Ice seeding approach was adopted to initiate ice formation in this present simulation. RESULTS: The faster freezing rate (11-12 K/490 ns) applied resulted in overall smaller ice fraction within the simulation box with a larger freeze-concentrated liquid (FCL) region. Consequently, the faster freezing rate better maintained protein stability with less secondary structure deviations, higher hydration level and structural compactness, and less fluctuations at individual residues than observed following slow (5-6 K/490 ns) and medium (7-8 K/490 ns) freezing rates. The present study also identified the residues near and within helices 3, 6, 7, and 8 dominate the structural instability of the lysozyme at 247 K freezing temperature. CONCLUSIONS: For the first time, ice formation in therapeutic protein solution was studied "non-isothermally" at different freezing rates using molecular dynamics simulations. Thus, a good understanding of freezing rates on protein instability was revealed by applying the developed computational model.

On the Applicability of the Coarse Grained Coupled CFD-DEM Model to Predict the Heat Transfer During the Fluidized Bed Drying of Pharmaceutical Granules.

Fluidized bed dryer often used in the pharmaceutical industry for drying of wet granules. Coupled computational fluid dynamics (CFD) - discrete element method (DEM) is frequently used to model the drying process because of its ability to obtain the relevant information at the particle level. However, it becomes almost impossible to model the industrial scale fluidized bed dryer using the coupled CFD-DEM method because of the presence of large number of particles [Formula: see text]. To reduce the number of particles to be tracked in the simulation, coarse grained coupled CFD-DEM method was developed by researchers where a certain number of particles of the original system was represented by a relatively bigger particle in the coarse-grained system. The appropriate scaling of the particle-particle and particle-fluid interaction forces is necessary to make sure that the dynamics of the coarse-grained particles/parcels accurately represent the dynamics of the original particles. The coarse-graining of the drying process of pharmaceutical granules during fluidization needs systematic coarse-graining of the momentum, heat, and solvent vapor transfer process. A coarse grained coupled CFD-DEM method was used to model the momentum and heat transfer during the fluidization of pharmaceutical granules. It was shown that the heat transfer during the fluidization of large number of particles could be predicted by simulating a smaller number of bigger particles with appropriate scaling of particle-particle heat and momentum transfer, and particle-fluid heat and momentum transfer at significantly smaller computational time. This model can be further extended by including a coarse-grained moisture transport model in future.

Coarse-Grained Molecular Dynamics Simulations of Paclitaxel-Loaded Polymeric Micelles.

A continuous manufacturing technology based on coaxial turbulent jet in coflow was previously developed to produce paclitaxel-loaded polymeric micelles. Herein, coarse-grained molecular dynamics (CG-MD) simulations were implemented to better understand the effect of the material attributes (i.e., the drug-polymer ratio and the ethanol concentration) and process parameters (i.e., temperature) on the self-assembly process of polymeric micelles as well as to provide molecular details on micelle instability. An all-atom (AA) poly (ethylene glycol)-poly (lactic acid) (PEG-PLA) polymer model was developed as the reference for parameterizing a coarse-grained (CG) model, and the AA polymer model was further validated with experimental glass transition temperature (Tg). The model transferability was verified by comparing structural properties between the AA and CG models. The CG model was further validated with experimental data, including micelle particle size measurements and drug encapsulation efficiency. Furthermore, the encapsulation of paclitaxel into the polymeric micelles was included in the simulations, taking into consideration the interactions between the paclitaxel and the polymers. The results from various points of view demonstrated a strong dependence of the shape of the micelles on the drug encapsulation, with micelles transitioning from spherical to ellipsoidal structures with an increasing paclitaxel amount. Simulation data were also used to identify the critical aggregation number (i.e., the number of polymer and drug molecules required for transition from one shape to another). Improved micellar structural stability was found with a larger micellar size and less solvent accessibility. Lastly, an evaluation was performed on the micellar dissociation free energy using a steered molecular dynamics simulation over a range of temperatures and ethanol concentrations. These simulations revealed that at higher ethanol and temperature conditions, micelles become destabilized, resulting in greater paclitaxel release. The increased drug release was determined to originate from the solvation of the hydrophobic core, which promoted micellar swelling and an associated reduction in hydrophobic interactions, leading to a loosely packed micellar structure.

Computational Modeling of Drying of Pharmaceutical Wet Granules in a Fluidized Bed Dryer Using Coupled CFD-DEM Approach.

Drying of wet granules in a fluidized bed dryer is an important part of the pharmaceutical tablet manufacturing process. Complicated gas-solid flow patterns appear in the fluidized bed dryer, and interphase momentum, heat, and mass transfer happen during the drying process. A coupled computational fluid dynamics (CFD)-discrete element method (DEM)-based approach was used to model the drying process of pharmaceutical wet granules in a fluidized bed dryer. The evaporation of water from the surfaces of the particles and the cohesion force between the particles due to the formation of liquid bridges between the particles were also considered in this model. The model was validated by comparing the model predictions with the experimental data available from the literatures. The validated model was used to investigate the drying kinetics of the wet granules in the fluidized bed dryer. The results from numerical simulations showed that the dynamics and rate of increase of temperature of wet particles were considerably different from those of dry particles. Finally, the model was used to investigate the effects of inlet air velocity and inlet air temperature on the drying process. The model predicted increase in drying rate with the increase of inlet air velocity and inlet air temperature. This model can help not only to understand the multiphase multicomponent flow in fluidized bed dryer but also to optimize the drying process in the fluidized bed dryer.

Computational Modeling of Fluidized Beds with a Focus on Pharmaceutical Applications: A Review.

The fluidized bed is an essential and standard equipment in the field of process development. It has a wide application in various areas and has been extensively studied. This review paper aims to discuss computational modeling of a fluidized bed with a focus on pharmaceutical applications. Eulerian, Lagrangian, and combined Eulerian-Lagrangian models have been studied for fluid bed applications with the rise of modeling capabilities. Such models assist in optimizing the process parameters and expedite the process development cycle. This paper discusses the background of modeling and then summarizes research papers relevant to pharmaceutical unit operations.

Pharmaceutical applications of powder-based binder jet 3D printing process - A review.

Pharmaceutical applications of the 3D printing process have recently matured, followed by the FDA approval of Spritam, the first commercial 3D printed dosage form. Due to being a new technology in the conventional dosage formulation field, there is still a dearth of understanding in the 3D printing process regarding the effect of the raw materials on the printed dosage forms and the plausibility of using this technology in dosage development beyond the conventional ways. In this review, the powder-based binder jet 3D printing (BJ3DP) process and its pharmaceutical applications have been discussed, along with a perspective of the formulation development step. The recent applications of BJ3DP in pharmaceutical dosage development, the advantages, and limitations have further been discussed here. A discussion of the critical formulation parameters that need to be explored for the preformulation study of the solid oral dosage development using the BJ3DP process is also presented.

Development of a pilot-scale HuskyJet binder jet 3D printer for additive manufacturing of pharmaceutical tablets.

This paper reports a custom-built binder jet 3D printer for pilot-scale manufacturing of pharmaceutical tablets. The printer is equipped with high-throughput piezoelectric inkjet print heads and allows direct control of several key process parameters, including the build layer thickness, amount of jetted liquid binder, and powder spreading rate. The effects of these parameters on the properties of the as-printed tablets were studied using a powder mixture of lactose monohydrate and Kollidon® VA64 (KL) and an aqueous binder containing 5% of KL. The appropriate processing windows for two different powder spreading rates were identified, and the final properties of the printed samples were explained using a dimensionless "degree of overlap" parameter which is defined as the ratio between the penetrating depth of the binder into the powder and the build layer thickness. Lastly, 10% of indomethacin was added to the powder feedstock as a model drug. Drug-loaded tablets were produced at a rate of 32 tablets/min, having an average breaking force of 9.4 kgf, a friability of 2.5%, and an average disintegration time of 8 s. These properties are comparable to commercially available tablets and represent one of the best values reported in the literature of 3D printed tablets thus far.

Use of a Design of Experiments (DoE) Approach to Optimize Large-Scale Freeze-Thaw Process of Biologics.

Large volumes of protein solutions are commonly stored in a frozen state before further drug product fill and finish. This study aimed to establish a design space to perform large-scale freeze-thaw (F/T) processes of biotherapeutics without inducing protein destabilization. A response surface model was designed to evaluate the following main factors and interactions: fill volume of the protein solution in 1-L containers, distance among nine containers during both F/T, freezer set temperature, and a novel forced air flow methodology during thawing. The analysis from 46 experimental runs indicated over 4-fold increase in the freezing rate by lowering the freezing temperature from -20 to -80°C, and the forced air flow at 98 fpm doubled the thawing rate. Furthermore, multivariate linear regression modeling revealed the significant impact of all main factors investigated on lactate dehydrogenase (LDH) quality attributes. The factor that most strongly affected the retention of LDH activity was the loading distance: ≥ 5 cm among containers positively affected the LDH activity response in 50.6%. The factor that most strongly retained the LDH tetramers was the set freezer temperature towards the lower range of -80°C (2.2% higher tetramer retention compared to -20°C freezing, due to faster freezing rate). In summary, this DoE-based systematic analysis increased F/T process understanding at large scale, identified critical F/T process parameters, and confirmed the feasibility of applying faster freezing and forced air thawing procedures to maintain the stability of LDH solutions subject to large-scale F/T.

Artificial neural networks in tandem with molecular descriptors as predictive tools for continuous liposome manufacturing.

The current study utilized an artificial neural network (ANN) to generate computational models to achieve process optimization for a previously developed continuous liposome manufacturing system. The liposome formation was based on a continuous manufacturing system with a co-axial turbulent jet in a co-flow technology. The ethanol phase with lipids and aqueous phase resulted in liposomes of homogeneous sizes. The input features of the ANN included critical material attributes (CMAs) (e.g., hydrocarbon tail length, cholesterol percent, and buffer type) and critical process parameters (CPPs) (e.g., solvent temperature and flow rate), while the ANN outputs included critical quality attributes (CQAs) of liposomes (i.e., particle size and polydispersity index (PDI)). Two common ANN architectures, multiple-input-multiple-output (MIMO) models and multiple-input-single-output (MISO) models, were evaluated in this study, where the MISO outperformed MIMO with improved accuracy. Molecular descriptors, obtained from PaDEL-Descriptor software, were used to capture the physicochemical properties of the lipids and used in training of the ANN. The combination of CMAs, CPPs, and molecular descriptors as inputs to the MISO ANN model reduced the training and testing mean relative error. Additionally, a graphic user interface (GUI) was successfully developed to assist the end-user in performing interactive simulated risk analysis and visualizing model predictions.

Impact of powder-binder interactions on 3D printability of pharmaceutical tablets using drop test methodology.

In this study, a pre-screening test has been developed for the binder-jet 3D printing process (BJ3DP) which has been validated using statistical analysis. The pre-screening test or drop test has been adapted from the wet granulation field and modified later on to be used for tablet manufacturing in BJ3DP. Initially, a total of eight powders and ten water-based binder solutions have been introduced in the preliminary test to understand the powder-binder interactions. Afterward, based on the preliminary test results, three blends were developed which had undergone the same drop test. All these powder and binder combinations were then used for 3D printing. The key parameters such as mechanical strength and shape factors of the drop test agglomerates and 3D printed tablets were then compared using multiple linear regressions. Few dimensionless parameters were introduced in this study such as binding capacity and binding index to capture the printability properties of the powders used in this study. Significant relations (p<0.05) were found between the drop test and the BJ3DP process. Application of drop test was carried out to establish a prescreening test, ii) to develop new blend formulations as well as iii) to develop a fundamental understanding of powder-binder interaction during BJ3DP process.

Molecular Dynamics Simulation to Uncover the Mechanisms of Protein Instability During Freezing.

Freezing is a common process applied in the pharmaceutical industry to store and transport biotherapeutics. Herewith, multi-scale molecular dynamics simulations of Lactate dehydrogenase (LDH) protein in phosphate buffer with/without ice formation performed to uncover the still poorly understood mechanisms and molecular details of protein destabilization upon freezing. Both fast and slow ice growing conditions were simulated at 243 K from one or two-side of the simulation box, respectively. The rate of ice formation at all-atom simulations was crucial to LDH stability, as faster freezing rates resulted in enhanced structural stability maintained by a higher number of intramolecular hydrogen bonds, less flexible protein's residues, lower solvent accessibility and greater structural compactness. Further, protein aggregation investigated by coarse-grained simulations was verified to be initiated by extended protein structures and retained by electrostatic interactions of the salt bridges between charged residues and hydrogen bonds between polar residues of the protein. Lastly, the study of free energy of dissociation through steered molecular dynamics simulation revealed LDH was destabilized by the solvation of the hydrophobic core and the loss of hydrophobic interactions. For the first time, experimentally validated molecular simulations revealed the detailed mechanisms of LDH destabilization upon ice formation and cryoconcentration of solutes.

Discrete Element Modeling (DEM) based investigation of tribocharging in the pharmaceutical powders during hopper discharge.

Triboelectric charging is defined as the phenomenon of charge transfer between two different material surfaces when they are brought into contact and separated. The focus of this research is the development of a Discrete Element Method (DEM) based simulation model to predict tribocharging during hopper discharge. Due to decreased particle-wall interactions and reduced particle wall contact times, net charges generated during hopper discharge are low. The simulation model confirmed this effect and was implemented to predict the triboelectric behavior of glass beads and MCC particles during hopper flow, along with the prediction of percent charged and uncharged particles. Approximately one-third of the particles were predicted to remain uncharged during the hopper discharge simulations for mono-dispersed particles, thus rendering a comparatively high amount of charge distribution into a small concentration of materials. The DEM model acted as a tool to predict charges that can be generated during hopper discharge at a specified geometry, with a potential to mitigate particle charging, when used for appropriate selection of hopper angles, and hopper wall materials.