The granular Bond number, estimated using Chen's multi-asperity particle adhesion model, has been shown as a basis for powder flowability prediction for both as-received and dry-coated powders. Here, the prediction model calibrated solely using as-received powders is tested by estimating the expected flowability enhancement after dry coating with two different nano-silicas. Prediction accuracy for 9 APIs and 18 excipients is compared for three characteristic particle size parameters for the Bond number; median particle size (d50), Sauter mean diameter (d3,2), and the size class-dependent (SCD) metric utilizing entire particle size distribution (PSD). A new sigmoid-function based flowability prediction model is proposed and fitted for as-received powders. Both d3,2 and SCD lead to better predictive accuracy with narrower prediction intervals as compared to d50, suggesting d3,2 captures the same surface-area-dependent PSD effects as SCD without added computational burden. The model could accurately predict flow category for all but one as-received powder. The model calibrated through as-received uncoated powders can predict enhancement of one to three flow categories for most dry coated powders with high accuracy. Notable exceptions are materials with SSA above ∼2 m2/g whose experimental SSA deviates significantly from PSD-estimated theoretical SSA (high ΔSSA), indicating surface roughness or adherent debris that restricts dry coating effectiveness. Materials with high SSA but low ΔSSA, where high surface area is simply a consequence of fine particle size, respond well to dry coating as predicted. In summary, the proposed unifying model can be calibrated using small samples of as-received powders to estimate expected flowability improvements after dry coating and, importantly, to identify dry coated powders likely to underperform.

Segregation behavior of binary blends of free-flowing powders was systematically investigated to develop a quantitative model for predicting segregation tendencies as a function of key particle properties. Binary blends, eight training and two testing, were prepared from seven materials, spanning a range of ratios of particle size, bulk density, and aspect ratios. A novel tape test sample preparation technique, developed to enhance the accuracy of blend uniformity measurements, reduce material usage, and minimize sampling errors, helps validate the use of a Near-Infrared (NIR) probe-based SPECTester to assess segregation intensity (SI) of those binary blends. Cumulative segregation area (CSA), defined as the integrated absolute deviation area between the cumulative concentration profile and the no-segregation baseline, was introduced as a novel measure of segregation that better captured the segregation tendency across a range of variables. A multi-variate power-law model, capturing the combined influence of these properties on segregation behavior, was developed. For the segregation intensity (SI)-based model, predictions closely matched experimental measurements for the training dataset (R2 ≈ 0.98) and maintained good accuracy for unseen test blends (R2 ≈ 0.85). When evaluated using CSA, the model exhibited strong generalization, achieving R2 = 0.92 for the training dataset and R2 = 0.96 for the test blends. Heatmap visualizations overlaid with experimental data confirmed that higher D50 × bulk density ratios increased segregation intensity, whereas larger ratios of aspect ratio mitigated segregation. Overall, a robust quantitative framework was established for understanding and predicting segregation in free-flowing powder systems, potentially enabling improved blend uniformity.

A mechanistic powder compaction equation for binary blends is proposed, extending author's previous singlecomponent framework (Powder Technology 464, (2025) 121285) to predict tablet tensile strength from physical particle properties and two fitting parameters: the corrected contact number c and the brittle property number k. Novel mixing rules are developed for c(mix )and k(mix) based on three dimensionless quantities: the surface area fraction lambda, particle number fraction chi, and weighted surface area fraction omega, which capture the relative contributions of particle size, density, and composition. The model is validated against two binary blend systems: a ductile-ductile blend (Ibuprofen (IBU)-microcrystalline cellulose (MCC)) and a brittle-ductile blend (Mannitol-MCC), spanning six loading levels. Ductile-ductile systems where k = 0 for both components is determined by c(mix )for blend predictions and captures the nonlinear decay of tensile strength of intermediate IBU blends. Brittle-ductile systems, where one component k =/ 0 is governed by both c(mix) and k(mix )capturing the more gradual decline in strength and wider porosity sensitivity at high Mannitol loadings. The novelty of this framework is that it provides quantitative formulation guidance, without having to prepare and test blends, yet can predict that the IBU-MCC system could achieve similar to 60% IBU loading while the Mannitol-MCC system could achieve higher, similar to 70% Mannitol loading before falling below a 2 MPa tensile strength threshold.

As predicted by the multi-asperity particle contact model, powder cohesion can be significantly reduced through dry coating of silica using a high-intensity vibratory mixer (HIVM). To promote industry adoption of dry coating, industry-relevant devices, a low-intensity V-blender and a medium-intensity comil, were evaluated against HIVM as a benchmarking control. Since low/medium intensity devices could lead to less effective silica dispersion, the contact model was extended to account for silica agglomeration. Three model APIs, belonging to very cohesive and cohesive flow category, were coated with two silica types (A200 and R972P) for enhancing flow (flow function coefficient - FFC) and conditioned bulk density (CBD). The V-blender exhibited least improvements in FFC and CBD. Corresponding SEM images revealed poor silica dispersion and presence of large porous agglomerates on coated API surfaces. Comil, at one and five passes with different-sized screens, performed better than V-blender. While FFC and CBD improved, some silica agglomeration on API surfaces was evident. HIVM, due to well-dispersed silica coating, achieved the most significant, 2-3 category enhancements in FFC and CBD at higher intensities. These results, in line with the extended model predictions, indicated that whereas V-blender would be unsuitable for dry coating due to excessive silica agglomeration, comil with finer screens would be a promising continuous manufacturing option for enhancing fine powder flowability. Device equivalence analysis identified lower intensity HIVM operating conditions that could achieve performance comparable to best outcomes from V-blender or comil; potentially enabling HIVM as a surrogate material sparing screening device.

Dry coating fine pharmaceutical powders with nano-silica has been shown to enhance their bulk properties and their blend processability at lab-scale, potentially facilitating tablet manufacturing. This study critically investigates key aspects of dry coating from industrial applicability perspective: (1) evaluating the selection of silica amount based on the host particle surface area coverage (SAC) against the industry standard 1 wt% addition, (2) assessing the feasibility of continuous dry coating using a pilot-scale conical screen mill (comil-U10) compared to the lab-scale batch high-intensity vibratory mixer (HIVM), and (3) investigating downstream processing improvements from dry coating via feedability and tabletability studies. Results from six different pharmaceutical powders (d50 ∼ 3-35 μm) demonstrated that SAC-based silica wt.% selection outperformed 1 wt% silica for bulk properties enhancements. Multi-faceted characterization revealed that FFC was the most reliable amongst Hausner's ratio, compressibility, and permeability tests. Three selected materials (d50 ∼ 16-26 μm) for comil processing showed remarkable one-flow category improvement, though two finer materials fell short of the HIVM performance. The dry coated materials demonstrated superior feed rate stability, demonstrating reduced flow variability, attributed to enhanced flowability and lower compressibility. Tablets of formulations containing dry-coated API using either comil or HIVM outperformed formulations with blended silica at three drug loads, 10 %, 30 %, and 60 %, likely due to better silica dispersion. These outcomes demonstrate the benefits of potentially scalable comil-based dry coating to continuous manufacturing of tableting, potentially eliminating the need for granulation.

Dry coating of fine pharmaceutical powders with nano-sized flow aids has been shown to enhance their bulk properties and processability, greatly facilitating direct compression tablet manufacturing. Here, a model-based understanding of cohesion reduction due to dry coating is presented to provide industrial adoption guidelines. It is shown that, unlike existing single-asperity contact models, our multi-asperity particle contact model explains the effect of the amount of silica, the predominant role of the particle surface roughness, and insufficient flowability enhancements through conventional blending. Our model, coupled with two other models, is used for the determination of the amount and type of guest particles. These models provide an estimate of reduced cohesion as a function of particle size, particle density, asperity size, surface area coverage, and dispersive surface energy. Cohesion is nondimensionalized by using the granular Bond number with the hope of linking the particle scale properties with bulk-scale properties such as flowability, bulk density, and powder agglomeration. Experimental results show that when done properly, dry coating led to significant bulk property enhancements such that 10μm powders attained flowability, fluidizability, and dispersibility as good as 100μm powders; qualitatively agreeing with the model-predicted dramatic reduction in Bond number.

A mechanistic powder compaction equation is proposed to incorporate physical particle properties into the prediction of tablet tensile strength based on the bonding strength and bonding number. This investigation aims to establish insights between the interplay of particle and material properties including primary particle size, Sauter mean diameter, surface energy, Young's modulus, and Poisson's ratio to calculate the bonding strength and bonding number with tablet porosity and compaction pressure. There are two fitting parameters, brittle parameter k and corrected contact number c are related to powder ductility tendency and contact area after compression, respectively. The predicted tablet tensile strength is driven by two terms: bonding number and bonding strength. The model is tested with three sizes of microcrystalline cellulose by characterizing compacted tablets for a range of compaction pressures. The main novelty of this framework is that it can provide a mechanistic insight into the interplay of physical particle properties to predict tablet strength. Ultimately, this model aims to provide guidelines for excipient selection and tablet formulation development.

PURPOSE:Predicting powder blend flowability is necessary for pharmaceutical manufacturing but challenging and resource-intensive. The purpose was to develop machine learning (ML) models to help predict flowability across multiple flow categories, identify key predictive features, and arrive at formulations with improved flow properties. METHODS:A dataset of 410 blends, composed of 9 active pharmaceutical ingredients (APIs) and 18 excipients with varying silica dry-coating parameters, was analyzed. Supervised ML models were trained to predict various flowability categories (very cohesive, cohesive, semi-cohesive, well-flowing, and free-flowing). Particle size, morphology, surface properties, and coating parameters were used as features. Classification algorithms, including Random Forest (RF) and Extreme Gradient Boosting (XGBoost), were evaluated. Unsupervised clustering identified natural groupings within flowability data. RESULTS:The best-performing models achieved up to 85% accuracy for predicting flowability regimes of individual components and 87% for blends. Individual components generally showed higher accuracy than blends, except in the uncoated scenario with 2 flow regimes, where blends outperformed with 94.67%. SHapley Additive exPlanations (SHAP) and Feature Importance analysis indicated dry coating parameters as the most influential factors, followed by particle size and morphology. ML models effectively identified category transitions between flow regimes, offering insights into blend optimization. CONCLUSION:Integrating ML with mechanistic approaches effectively predicted powder blend flowability across diverse categories and elucidated feature-property relationships. These outcomes can facilitate the rational design of blends having enhanced flow properties at reduced experimental effort through judiciously selected dry coating of a blend constituent; making this approach promising for advancing pharmaceutical process and product development.

Predictive selection of silica size, type (hydrophobic/hydrophilic), and amount is addressed for achieving significant property enhancements of fine active pharmaceutical ingredients (APIs). Four models, Chen's multiasperity particle-adhesion, total surface energy-based guest-host compatibility, dispersive surface energy-based tablet tensile strength, and stick-bounce-based silica aggregation on coated particles, are invoked. The impact on the bulk properties of four APIs cohesive API powders (similar to 10 mu m) and 40 wt% (wt%) blends of one API, drycoated at 50% and 100% surface area coverage (SAC) of four nano-silicas (7-20 nm), hydrophobic (R972P), hydrophilic (M5P, A200, A300) is assessed. Significant enhancements in flowability, bulk density, compactability, agglomeration reduction, and dissolution for API or blend are achieved with all silicas. The experimental and model-based outcomes demonstrate that silica performance is impacted by multiple factors, silica size and coating effectiveness being most critical. In conclusion, R972P and A200 at lower 50% SAC present two excellent choices.

The possibility of attaining direct compression (DC) tableting using silica coated fine particle sized excipients was examined for high drug loaded (DL) binary blends of APIs. Three APIs, very-cohesive micronized acetaminophen (mAPAP, 7 mu m), cohesive acetaminophen (cAPAP, 23 mu m), and easy-flowing ibuprofen (IBU, 53 mu m), were selected. High DL (60 wt%) binary blends were prepared with different fine-milled MCC-based excipients (ranging 20- 37 mu m) with or without A200 silica coating during milling. The blend flowability (flow function coefficient -FFC) and bulk density (BD) of the blends for all three APIs were significantly improved by 1 wt% A200 dry coated MCCs; reaching FFC of 4.28 from 2.14, 7.82 from 2.96, and > 10 from 5.57, for mAPAP, cAPAP, and IBU blends, respectively, compared to the uncoated MCC blends. No negative impact was observed on the tablet tensile strength (TS) by using dry coated MCCs despite lower surface energy of silica. Instead, the desired tablet TS levels were reached or exceeded, even above that for the blends with uncoated milled MCCs. The novelty here is that milled and silica coated fine MCCs could promote DC tableting for cAPAP and IBU blends at 60 wt% DL through adequate flowability and tensile strength, without having to dry coat the APIs. The effect of the silica amount was investigated, indicating lesser had a positive impact on TS, whereas the higher amount had a positive impact on flowability. Thus, the finer excipient size and silica amounts may be adjusted to potentially attain blend DC processability for high DL blends of fine APIs.

Previous work demonstrated the benefits of dry coating fine-grade microcrystalline cellulose (MCC) for enabling direct compression (DC), a favored tablet manufacturing method, due to enhanced flowability while retaining good compactability of placebo and binary blends of cohesive APIs. Here, fine brittle excipients, Pharmatose 450 (P450, 19 μm) and Pharmatose 350 (P350, 29 μm), having both poor flowability and compactability are dry coated with silica A200 or R972P to assess DC capability of multi-component cohesive API (coarse acetaminophen, 22 μm, and ibuprofen50, 47 μm) blends. Dry coated P450 and P350 not only attained excellent flowability and high bulk density but also heightened tensile strength hence processability, which contrasts with reported reduction for dry coated ductile MCC. Although hydrophobic R972P imparted better flowability, hydrophilic A200 better enhanced tensile strength, hence selected for dry coating P450 in multi-component blends that included fine Avicel PH-105. For coarse acetaminophen blends, substantial bulk density and flowability increase without any detrimental effect on tensile strength were observed; a lesser amount of dry coated P450 was better. Increased flowability, bulk density, and tensile strength, hence enhanced processability by reaching DC capability, were observed for 60 wt% ibuprofen50, using only 18 wt% of the dry coated P450, i.e. 0.18 wt% silica in the blend.

The downstream processability of Hot Melt Extrusion (HME) Amorphous Solid Dispersions (ASD), an underexplored topic of importance, was assessed through a multi-faceted particle engineering approach. Extrudates, comprised of griseofulvin (GF), a model poorly water-soluble drug, and hydroxypropyl cellulose (HPC), were prepared at four drug concentrations and three HME temperature profiles to yield cases with and without residual crystallinity and subsequently milled to five sieve cuts ranging from < 45 mu m to 355 - 500 mu m. Solid state characterization was performed with XRPD, FT-IR, and TGA. Particle scale properties of the milled extrudates were evaluated including particle size, density, surface energy, and morphologies imaged via SEM. It was observed that regardless of sieve cut size, drug concentration and HME conditions impacted the flowability trends, quantified via Flow Function Coefficient (FFC) and bulk density. As a novelty, the effects of various process parameters and drug loadings were consolidated into a dimensionless interparticle cohesion measure, granular Bond Number (Bog), to better correlate them with bulk powder properties. The significant contrast in particle morphologies, particle size, and densities among selected cases demonstrated that particle size alone should not be the sole consideration when correlating particle scale to bulk powder scale properties of milled extrudates. Instead, the HME temperature profile and ASD drug loading may be more suitable parameters affecting the bulk powder properties of the milled extrudates.

A true unsteady-state simulator (TUSSIM) for ball milling was integrated with a variable Tromp curve for classification to simulate and optimize closed-circuit, multi-compartment cement ball milling. Using representative model-operational parameters from available literature, we first investigated the system dynamics for a two-compartment mill. Then, various simulations examined the impacts of closedcircuit vs. open-circuit operation, number of compartments, and various ball size distributions. Our results suggest that integrating an air classifier into an open-circuit ball mill can increase the production rate by 15% or increase the cement-specific surface area by 13%. A single-compartment mill entails a pre milled feed for proper operation, whereas a two-compartment mill yields a finer cement product than a three-compartment mill. Uniform mass distribution of balls led to slightly finer product than uniform surface area or number distributions, while the impact of a classifying liner was negligibly small. Finally, we identified optimal ball mixtures in a two-compartment mill using a combined global optimizer-DAE solver, which suggests 14% capacity increase with desirable cement quality. Overall, TUSSIM's results are not only in line with limited, full-scale experimental studies and industry best practices, but also provide fundamental process insights, while enabling process optimization with tailored ball mixtures in different compartments. & COPY; 2023 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.

A highly porous additive, Neusilin^®, with high adsorption capability is investigated to improve bulk properties, hence processability of spray-dried amorphous solid dispersions (ASDs). Griseofulvin (GF) is applied as a model BCS class 2 drug in ASDs. Two grades of Neusilin^®, US2 (coarser) and UFL2 (finer), were used as additives to produce spray-dried amorphous composite (AC) powders, and their performance was compared with the resulting ASDs without added Neusilin^®. The resulting AC powders that included Neusilin^® had greatly enhanced flowability (flow function coefficient (FFC) > 10) comparable to larger particles (100 μm) yet had finer particle size (< 50 μm), hence retaining the advantage of fast dissolution rate of finer sizes. Dissolution results demonstrated that achieved GF supersaturation for AC powders with Neusilin^® was as high as 3 times that of crystalline GF concentration and was achieved within 30 min. In addition, 80% of drug was released within 4 min. The flowability improvement for AC powders with Neusilin^® was more significant as compared to spray-dried ASDs without Neusilin^®. Thus, the role of Neusilin^® in flowability improvement was evident, considering that spray-dried AC with Neusilin^® UFL2 has higher FFC than ASDs having a similar size. Lastly, the AC powders retained a fully amorphous state of GF after 3-month ambient storage. The overall results conveyed that the improved flowability and dissolution rate could outweigh the loss of drug loading resulted by addition of Neusilin^®. Graphical Abstract

This paper considers two fine-sized (d50 ∼10 µm) model drugs, acetaminophen (mAPAP) and ibuprofen (Ibu), to examine the effect of API dry coprocessing on their multi-component medium DL (30 wt%) blends with fine excipients. The impact of blend mixing time on the bulk properties such as flowability, bulk density, and agglomeration was studied. The hypothesis tested is that blends with fine APIs at medium DL require good blend flowability to have good blend uniformity (BU). Moreover, the good flowability could be achieved through dry coating with hydrophobic (R972P) silica, which reduces agglomeration of not only fine API, but also of its blends while using fine excipients. For uncoated APIs, the blend flowability was poor, i.e. cohesive regime at all mixing times, and the blends failed to achieve acceptable BU. In contrast, for dry coated APIs, their blend flowability improved to easy-flow regime or better, improving with mixing time, and as hypothesized, all blends consequently achieved desired BU. All dry coated API blends exhibited improved bulk density and reduced agglomeration, attributed to mixing induced synergistic property enhancements, likely due to silica transfer. Despite coating with hydrophobic silica, tablet dissolution was improved, attributed to the reduced agglomeration of fine API.

This study explored the breakage kinetics of cement clinker in a lab-scale ball mill loaded with steel or alumina balls of 20, 30, and 40 mm sizes and their mixtures. The temporal evolution of the particle size distribution (PSD) was measured by sieving and laser diffraction. A global optimizer-based back-calculation method, based on a population balance model (PBM), was developed to estimate the breakage parameters. The ball motion in the mill was simulated via discrete element method (DEM). Our results show that steel balls achieved faster breakage of clinker into finer particles than alumina balls, which was explained by the higher total-mean energy dissi-pation rates of the steel balls. The PSD became finer as smaller balls were used. This study suggests that replacement of steel balls with alumina balls in continuous ball mills could provide significant energy savings if one accounts for the slower breakage with the alumina balls.

Purpose To investigate the effect of dry coating the amount and type of silica on powder flowability enhancement using a comprehensive set of 19 pharmaceutical powders having different sizes, surface roughness, morphology, and aspect ratios, as well as assess flow predictability via Bond number estimated using a mechanistic multi-asperity particle contact model. Method Particle size, shape, density, surface energy and area, SEM-based morphology, and FFC were assessed for all powders. Hydrophobic (R972P) or hydrophilic (A200) nano-silica were dry coated for each powder at 25%, 50%, and 100% surface area coverage ( SAC). Flow predictability was assessed via particle size and Bond number. Results Nearly maximal flow enhancement, one or more flow category, was observed for all powders at 50% SAC of either type of silica, equivalent to 1 wt% or less for both the hydrophobic R972P or hydrophilic A200, while R972P generally performed slightly better. Silica amount as SAC better helped understand the relative performance. The power-law relation between FFC and Bond number was observed. Conclusion Significant flow enhancements were achieved at 50% SAC, validating previous models. Most uncoated very cohesive powders improved by two flow categories, attaining easy flow. Flowability could not be predicted for both the uncoated and dry coated powders via particle size alone. Prediction was significantly better using Bond number computed via the mechanistic multi-asperity particle contact model accounting for the particle size, surface energy, roughness, and the amount and type of silica. The widely accepted 200 nm surface roughness was not valid for most pharmaceutical powders.

A true unsteady-state simulator (TUSSIM), based on a cell-based Population Balance Model (PBM) with a dif-ferential algebraic equation (DAE) solver, was used for modeling a full-scale open-circuit cement ball mill for better understanding the industry best practices of employing number of mill compartments, classifying liners, and ball mixtures. Model parameters for the particle breakage and classification action with/without the clas-sifying liner were obtained from the available literature for cement clinker. Experimental residence time dis-tribution data for a full-scale cement ball mill was fitted by the cell-based PBM to determine the number of cells and axial back-mixing ratio. Dynamic simulations, conducted to determine the temporal evolution of the particle size distribution and mass hold-up, demonstrate that milling with a ball mixture outperforms milling with a single ball size. Single-compartment milling can achieve desirable product fineness if the feed is pre-milled. Having the same length, a two-compartment mill obviates the need for pre-milling and performs similarly or better than a three-compartment mill, depending on the ball sizes used. For a given set of ball sizes, a distribution with uniform mass of balls, as opposed to that with a uniform number of balls, achieves 8% increase in cement specific surface area. The use of a classifying liner achieves a negligibly finer cement product compared to uniformly mixed balls. Overall, these results agree with experimental observations, lending credence to TUSSIM, while providing rationale to best practices in the cement industry, offering various process insights and a toolbox to optimize existing open-circuit continuous ball mills.

This theoretical study examined the impact of the degree of mixing, nonlinear particle breakage, and screen opening size on the particle size distribution (PSD) and mass hold-up in continuous dry mills with internal classification. A cell-based population balance model (PBM) incorporating a non-ideal screen model was formulated, wherein the back-mixing ratio and number of cells modulated the extent of axial mixing. The set of differential- algebraic equations (DAEs) was solved for the spatio-temporal evolution of the PSD in the mill and the product stream. The simulation results suggest that a smaller screen opening delayed the attainment of the steady state, increased the hold-up, and yielded a finer product PSD. The cushioning action of fines resulted in a coarser product PSD; however, a screen with a smaller opening mitigated this effect. The cell-based PBM predicted various features of experimental milling observations while providing insights into the mixing-nonlinear breakage- classification interplay. (c) 2022 Elsevier B.V. All rights reserved.

This paper presents a review of our key advances in model-guided dry coating-based enhancements of poor flow and packing of fine cohesive powders. The existing van der Waals force-based particle -contact models are reviewed to elucidate the main mechanism of flow enhancement through silica dry coating. Our multi-asperity model explains the effect of the amount of silica, insufficient flowability enhancements through conventional blending, and the predominant effect of particle surface roughness on cohesion reduction. Models are presented for the determination of the amount and type of guest par-ticles, and estimation of the granular Bond number, used for cohesion nondimensionalization, based on particle size, particle density, asperity size, surface area coverage, and dispersive surface energy. Selection of the processing conditions for LabRAM, a benchmarking device, is presented followed by key examples of enhancements of flow, packing, agglomeration, and dissolution through the dry coating. Powder agglomeration is shown as a screening indicator of powder flowability. The mixing synergy is identified as a cause for enhanced blend flowability with a minor dry coated constituent at silica < 0.01%. The anal-ysis and outcomes presented in this paper are intended to demonstrate the importance of dry coating as an essential tool for industry practitioners.(c) 2022 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.