Breakage Assessment of Lath-Like Crystals in a Novel Laboratory-Scale Agitated Filter Bed Dryer.

Agitated filter bed dryer is often the equipment of choice in the pharmaceutical industry for the isolation of potent active pharmaceutical ingredients (API) from the mother liquor and subsequent drying through intermittent agitation. The use of an impeller to promote homogeneous drying could lead to undesirable size reduction of the crystal product due to shear deformation induced by the impeller blades during agitation, potentially causing off-specification product and further downstream processing issues. An evaluation of the breakage propensity of crystals during the initial development stage is therefore critical. A new versatile scale-down agitated filter bed dryer (AFBD) has been developed for this purpose. Carbamazepine dihydrate crystals that are prone to breakage have been used as model particles. The extent of particle breakage as a function of impeller rotational speed, size of clearance between the impeller and containing walls and base, and solvent content has been evaluated. A transition of breakage behaviour is observed, where carbamazepine dihydrate crystals undergo fragmentation first along the crystallographic plane [00l]. As the crystals become smaller and more equant, the breakage pattern switches to chipping. Unbound solvent content has a strong influence on the breakage, as particles break more readily at high solvent contents. The laboratory-scale instrument developed here provides a tool for comparative assessment of the propensity of particle attrition under agitated filter bed drying conditions.

A Novel Computational Approach Coupled with Machine Learning to Predict the Extent of Agglomeration in Particulate Processes.

Solid particle agglomeration is a prevalent phenomenon in various processes across the chemical, food, and pharmaceutical industries. In pharmaceutical manufacturing, agglomeration is both desired in unit operations like wet granulation and undesired in unit operations such as agitated filter drying of highly potent active pharmaceutical ingredients (API). Agglomeration needs to be controlled for optimal physical properties of the API powder. Even after decades of work in the field, there is still very limited understanding of how to quantify, predict, and control the extent of agglomeration, owing to the complex interaction between the solvent and the solid particles and stochasticity imparted by mixing. Furthermore, a large size of industrial scale particulate process systems makes it computationally intractable. To overcome these challenges, we present a novel theory and computational methodology to predict the agglomeration extent by coupling the experimental measurements of agglomeration risk zone or "sticky zone" with discrete element method. The proposed model shows good agreement with experiments. Further, a machine learning model was built to predict agglomeration extent as a function of input variables, such as material properties and processing conditions, in order to build a digital twin of the unit operation. While the focus of the present study is the agglomeration of particles during industrial drying processes, the proposed methodology can be readily applied to numerous other particulate processes where agglomeration is either desired or undesired.

Understanding stress-induced disorder and breakage in organic crystals: beyond crystal structure anisotropy.

Crystal engineering has advanced the strategies for design and synthesis of organic solids with the main focus being on customising the properties of the materials. Research in this area has a significant impact on large-scale manufacturing, as industrial processes may lead to the deterioration of such properties due to stress-induced transformations and breakage. In this work, we investigate the mechanical properties of structurally related labile multicomponent solids of carbamazepine (CBZ), namely the dihydrate (CBZ·2H2O), a cocrystal of CBZ with 1,4-benzoquinone (2CBZ·BZQ) and the solvates with formamide and 1,4-dioxane (CBZ·FORM and 2CBZ·DIOX, respectively). The effect of factors that are external (e.g. impact stressing) and/or internal (e.g. phase transformations and thermal motion) to the crystals are evaluated. In comparison to the other CBZ multicomponent crystal forms, CBZ·2H2O crystals tolerate less stress and are more susceptible to breakage. It is shown that this poor resistance to fracture may be a consequence of the packing of CBZ molecules and the orientation of the principal molecular axes in the structure relative to the cleavage plane. It is concluded, however, that the CBZ lattice alone is not accountable for the formation of cracks in the crystals of CBZ·2H2O. The strength and the temperature-dependence of electrostatic interactions, such as hydrogen bonds between CBZ and coformer, appear to influence the levels of stress to which the crystals are subjected that lead to fracture. Our findings show that the appropriate selection of coformer in multicomponent crystal forms, targetting superior mechanical properties, needs to account for the intrinsic stress generated by molecular vibrations and not solely by crystal anisotropy. Structural defects within the crystal lattice, although highly influenced by the crystallisation conditions and which are especially difficult to control in organic solids, may also affect breakage.

A CFD Digital Twin to Understand Miscible Fluid Blending.

The mixing of stratified miscible fluids with widely different material properties is a common step in biopharmaceutical manufacturing processes. Differences between the fluid densities and viscosities, however, can lead to order-of-magnitude increase in blend times relative to the blending of single-fluid systems. Moreover, the mixing performance in two-fluid systems can be strongly dependent on the Richardson number defined as the ratio of fluid buoyancy to fluid inertia. In this work, we combine lattice Boltzmann transport algorithms with graphics card-based computing hardware to build accelerated digital twins of a physical mixing tanks. The digital twins are designed to predict real-time fluid mechanics with a fidelity that rivals experimental characterization at orders-of-magnitude less cost than physical testing. After validating the twins against measured single- and multi-fluid mixing data, we use them to explore the physics governing fluid blending in stratified two-fluid systems. We use output from the twins to provide general guidance on stratified two-fluid mixing processes, as well as guidance for building such models for other types of physical systems.

A machine learning framework for computationally expensive transient models.

Transient simulations of dynamic systems, using physics-based scientific computing tools, are practically limited by availability of computational resources and power. While the promise of machine learning has been explored in a variety of scientific disciplines, its application in creation of a framework for computationally expensive transient models has not been fully explored. Here, we present an ensemble approach where one such computationally expensive tool, discrete element method, is combined with time-series forecasting via auto regressive integrated moving average and machine learning methods to simulate a complex pharmaceutical problem: development of an agitation protocol in an agitated filter dryer to ensure uniform solid bed mixing. This ensemble approach leads to a significant reduction in the computational burden, while retaining model accuracy and performance, practically rendering simulations possible. The developed machine-learning model shows good predictability and agreement with the literature, demonstrating its tremendous potential in scientific computing.

Characterization of the Hydrodynamics in the USP Basket Apparatus Using Computational Fluid Dynamics.

Computational fluid dynamics (CFD) has been extensively used for the USP paddle apparatus II, but limited CFD studies have been conducted on the USP basket apparatus I. We expanded on past CFD basket studies to consider the presence of a tablet inside the basket, compared predictions to in vivo conditions, and confirmed observations around the complexity of nonuniform hydrodynamics. Tablets near the basket perimeter experienced near 5-fold increase in maximum velocity and surface shear stress compared to tablets placed at the center of the basket. At higher basket speeds, the predicted velocities at the center of the basket were closer to in vivo predictions but the surface shear stress was about 2 orders of magnitude lesser. Simulations with a high viscosity fluid (1 Pa-s) showed a 10-fold increase in shear stress on a tablet but a decrease in strain rate compared to low-viscosity medium (0.001 Pa-s) which could impact dissolution rates. Also presented are the insights into turbulent energy dissipation rates that could help in a priori prediction of dissolution rates. Overall, the CFD analysis presented in this work reveals significant differences between the basket and in vivo conditions and will help inform relevant in vitro testing.

Assessment of impact breakage of carbamazepine dihydrate due to aerodynamic dispersion.

Acicular crystals are very common in pharmaceutical manufacturing. They are very prone to breakage, causing unwanted particle size degradation and problems such as segregation and lump formation. We investigate the breakage pattern of carbamazepine dihydrate, an acicular and platy crystal with cleavage planes. It readily undergoes attrition during isolation and drying stage, causing processing difficulties. We use the aerodynamic dispersion of a very small quantity of powder sample to induce breakage by applying a pulse of pressurised air. The dispersion unit of Morphologi G3 is used for this purpose. The broken particles settle in a chamber and are subsequently analysed using the built-in image analysis software. The shift in the particle size and shape distributions is quantified through which the extent of breakage is determined as a function of the dispersion pressure. The analysis reveals a change of breakage mechanism as the dispersion pressure is increased from primarily snapping along the crystal length to one in which chipping has also a notable contribution. The breakage data are analysed using a modified impact-based breakage model and the breakability index of the carbamazepine dihydrate is determined for the two breakage regimes. The method provides a quick and easy testing of particle breakability, a useful tool for assessing attrition in process plant and grindability in milling operations.

Leveraging Lyophilization Modeling for Reliable Development, Scale-up and Technology Transfer.

Modeling of the lyophilization process, based on the steady-state heat and mass transfer, is a useful tool in understanding and optimizing of the process, developing an operating design space following the quality-by-design principle, and justifying occasional process deviations during routine manufacturing. The steady-state model relies on two critical parameters, namely, the vial heat transfer coefficient, Kv, and the cake resistance, Rp. The classical gravimetric method used to measure Kv is tedious, time- and resource-consuming, and can be challenging and costly for commercial scale dryers. This study proposes a new approach to extract both Kv and Rp directly from an experimental run (e.g., temperature and Pirani profiles). The new methodology is demonstrated using 5% w/v mannitol model system. The values of Kv obtained using this method are comparable to those measured using the classic gravimetric method. Application of the proposed approach to process scale-up and technology transfer is illustrated using a case study. The new approach makes the steady-state model a simple and reliable tool for model parameterization, thus maximizes its capability and is particularly beneficial for transfer products from lab/pilot to commercial manufacturing.

Predictive models of lyophilization process for development, scale-up/tech transfer and manufacturing.

Scale-up and technology transfer of lyophilization processes remains a challenge that requires thorough characterization of the laboratory and larger scale lyophilizers. In this study, computational fluid dynamics (CFD) was employed to develop computer-based models of both laboratory and manufacturing scale lyophilizers in order to understand the differences in equipment performance arising from distinct designs. CFD coupled with steady state heat and mass transfer modeling of the vial were then utilized to study and predict independent variables such as shelf temperature and chamber pressure, and response variables such as product resistance, product temperature and primary drying time for a given formulation. The models were then verified experimentally for the different lyophilizers. Additionally, the models were applied to create and evaluate a design space for a lyophilized product in order to provide justification for the flexibility to operate within a certain range of process parameters without the need for validation.

Shape-mediated margination and demargination in flowing multicomponent suspensions of deformable capsules.

We present detailed simulations and theory for flow-induced segregation in suspensions of deformable fluid-filled capsules with different shapes during simple shear flow in a planar slit. This system is an idealized model for transport for blood cells and/or drug carriers in the microcirculation or in microfluidic devices. For the simulations, an accelerated implementation of the boundary integral method was employed. We studied the binary mixtures of spherical and ellipsoidal capsules, varying the aspect ratio κ of the ellipsoid while keeping constant either (a) equatorial radius or (b) volume. Effects of a variety of parameters was studied, including κ, volume fraction and number fraction of the spherical capsules in the mixture. In suspensions where the ellipsoids have the same equatorial radius as the spheres, capsules with lower κ marginate. In suspension where the ellipsoids have the same volume as the spheres, ellipsoidal (both oblate and prolate) capsules are seen to demarginate in a mixture of primarily spherical capsules. To understand these results, a mechanistic framework based on the competition between wall-induced migration and shear-induced collisions is presented. A simplified drift-diffusion theory based on this framework shows excellent qualitative agreement with simulation results.

Dynamics of a single red blood cell in simple shear flow.

This work describes simulations of a red blood cell (RBC) in simple shear flow, focusing on the dependence of the cell dynamics on the spontaneous curvature of the membrane. The results show that an oblate spheroidal spontaneous curvature maintains the dimple of the RBC during tank-treading dynamics as well as exhibits off-shear-plane tumbling consistent with the experimental observations of Dupire et al. [J. Dupire, M. Socol, and A. Viallat, Proc. Natl. Acad. Sci. USA 109, 20808 (2012)] and their hypothesis of an inhomogeneous spontaneous shape. As the flow strength (capillary number Ca) is increased at a particular viscosity ratio between inner and outer fluid, the dynamics undergo transitions in the following sequence: tumbling, kayaking or rolling, tilted tank-treading, oscillating-swinging, swinging, and tank-treading. The tilted tank-treading (or spinning frisbee) regime has been previously observed in experiments but not in simulations. Two distinct classes of regime are identified: a membrane reorientation regime, where the part of membrane that is at the dimple at rest moves to the rim and vice versa, is observed in motions at high Ca such as tilted tank-treading, oscillating-swinging, swinging, and tank-treading, and a nonreorientation regime, where the part of the membrane starting from the dimple stays at the dimple, is observed in motions at low Ca such as rolling, tumbling, kayaking, and flip-flopping.

Margination regimes and drainage transition in confined multicomponent suspensions.

A mechanistic theory is developed to describe segregation in confined multicomponent suspensions such as blood. It incorporates the two key phenomena arising in these systems at low Reynolds number: hydrodynamic pair collisions and wall-induced migration. In simple shear flow, several regimes of segregation arise, depending on the value of a "margination parameter" M. Most importantly, there is a critical value of M below which a sharp "drainage transition" occurs: one component is completely depleted from the bulk flow to the vicinity of the walls. Direct simulations also exhibit this transition as the size or flexibility ratio of the components changes.