Mechanistic Model Research Articles

Implementation of filtration models for filter performance prediction in bioprocess dead-end membrane filtration

Mechanistic modeling is frequently applied during process development and scale-up in bioprocessing. For normal flow filtration (NFF, also called dead-end filtration) processes, such as aseptic filtration, harvest clarification, and virus removal etc., the modeling based on a theoretical fouling law has long been used to assess filter performance and filtration area requirements. This case study describes how an appropriate fouling model is selected and provides guidance for using the fouling model for bioprocess application. There is general agreement that the modeling and process simulation enables accurate filter size calculations for scale-up. Their predictions can then be used to identify optimal filter formats for each unit operation. However, because feed characteristics and conditions vary between processes, fouling models need to consider several filter fouling mechanisms for different bioprocess applications and unit operations. This study reviewed several fouling models and considered various bioprocess filter fouling scenarios, as well as the accuracy of filtration area predictions from the models. It was determined that filtration runs in small scale sizing studies should be run to at least 40% flux decay to minimize the risk of prediction error due to extrapolation.

Effects of carbon to nitrogen ratio on nitrogen removal in a single-stage microaerobic system: A model-based evaluation

Single-stage microaerobic systems have been proven to be effective for concurrent removal of ammonium and organic carbon from sewage. While mechanistic models derived from activated sludge models (ASMs) have simulated nutrients removal under microaerobic conditions, classic ASMs exhibit limitations in capturing the intricate effects of carbon to nitrogen (C/N) ratio on nitrogen removal performance. To address this issue, a mechanistic model modified from the classic ASMs was proposed to capture the combined inhibitory effects of carbon and ammonium on microaerobic systems. This modified model was established based on experimental data from a single-stage microaerobic reactor encompassing simultaneous nitrification-denitrification and anammox processes. The inhibition coefficient of C/N ratio was integrated into the process rate equations, and its effectiveness was validated through model performance evaluation. Compared to the classic models, the modified one achieved superior predictions for nitrite and nitrate nitrogen concentrations. Simulations revealed that under optimized conditions with a C/N of 4.57 and a dissolved oxygen (DO) of 0.41 mg/L, the system could achieve up to 95.5% of total nitrogen (TN) removal efficiency. Based on the simulation of substrate uptake/production rate, increasing the nitrogen loading rate (NLR) rather than organic loading rate (OLR) was crucial for efficient nitrogen removal. The proposed modified model served as a valuable tool for designing and optimizing similar biological wastewater treatment systems.

Mechanistic model for hydrogen accelerated fatigue crack growth in a low carbon steel

Fracture by hydrogen accelerated fatigue crack growth is a severe type of environmental failure. Although fatigue crack growth has been the subject of intense investigation over several decades, a complete mechanistic and predictive model is still lacking. Such a crack growth model is even more rare in the case of hydrogen in view of the lack also of constitutive models for material deformation under cycling loading that account for the hydrogen effect. In this study, we present a model for fatigue crack propagation induced by alternating crack tip plastic blunting and re-sharpening, which in the presence of hydrogen can be accelerated by hydrogen enhanced dislocation motion and generation. The Chaboche constitutive model, which is a nonlinear kinematic hardening model capable of capturing many features of material behavior under cyclic loading, is used for the calculation of the stress and strain fields at the propagating crack tip. The Chaboche model is calibrated using a sequence of experimental data from uniaxial strain-controlled cyclic loading tests and uniaxial stress-controlled ratcheting tests with a low carbon steel, JIS SM490YB, in the absence and presence of hydrogen. The numerical simulation results indicate that the proposed crack propagation model can predict Paris law behavior and can successfully demonstrate acceleration of fatigue crack growth in the presence of hydrogen. Significantly, the profiles of the steady-state opening stress and strain ahead of the fatigue crack tip in a compact tension (C(T)) specimen were found to have sections over which they vary as ln(1/r) with distance r from the crack tip, consistent with the crack-tip strain field for a non-stationary crack.

Single and multiphase flow leak detection in onshore/offshore pipelines and subsurface sequestration sites: An overview

Leaks may occur in existing pipelines, even when designed with quality construction and appropriate regulations. The economic impact of oil spills and natural gas dispersion from leaks can be huge. Failure to detect pipeline leaks promptly will have an adverse impact on life, the economy, the environment, and corporate reputation. Therefore, early detection of leaks, their location, and their size with high sensitivity and reliability are important for efficient hydrocarbon transportation through a pipeline, both in onshore and offshore applications. Although several studies have been conducted on leak detection using various techniques, recent literature that comprehensively investigates and summarizes the different multiphase leak detection techniques could not be found. Therefore, this paper provides a comprehensive review of the different leak detection techniques in pipelines, wellbores, and subsurface sequestration wells. This is done by studying the different multiphase flow leak detection techniques using various Computational Fluid Dynamics (CFD), Mechanistic, Machine Learning models, and digital twin techniques in the pipeline as well as in sub-surface sequestration sites. A comprehensive investigation revealed that a few studies have been conducted related to integrated multiphase flow leak experiments, computational fluid dynamics, mechanistic models, and implementing extended real-time transient monitoring using machine learning. This type of systematic investigation is deemed to be more useful for field applications. Furthermore, a new set of recommendations is provided in the last section which shows how experimental, mechanistic, and CFD simulation data can be used to drive a statistical approach based on modern deep learning and digital twin techniques. This allows for the precise understanding of the leak events such as size, location, and orientation of the leak, without sending a remotely operated underwater vehicle or aircraft to scan the whole pipeline and ocean.

Quantitative assessment of microstructural damage for interior crack initiation and high cycle fatigue life modeling

Axially loaded cyclic tests of a nickel-based alloy were conducted at 550°C, 630°C and 650°C and stress ratios of -1, -0.3 and 0.5 up to high cycle fatigue regime. Multiscale characterizations and quantitative analyses of microstructural damage were carried out to illustrate the physics and mechanics of interior microstructure induced fatigue strength degradation and cracking. Results showed that the fatigue strength increased with the decreases of twin spacing, the size and aspect ratio of carbide, and γ′ phase size. Twin collapse due to slip band-twin interaction was found for the first time and confirmed as a form of crack initiation process, followed by short crack growth forming facets with significant contribution from shear stress. A new mechanistic fatigue life model of interior microstructure induced cracking was established with sound agreement with experimental data. All these combined into a design-manufacturing integrated approach which are capable of ensuring the safe operation and maintenance of service structures in long-life regime.

Field monitoring and modelling of sediment transport, hydraulics and hydroabrasion at Sediment Bypass Tunnels

Sediment Bypass Tunnels (SBTs) are proven to be an effective measure to reduce or even stop reservoir sedimentation by bypassing sediment laden flows around reservoir dams to the downstream river reach. They are mostly used in Switzerland, Japan, and Taiwan. However, hydraulic and sedimentological operating conditions and the resistance of the invert materials against hydroabrasive erosion affect their cost-effectiveness. Hydroabrasion is a pressing issue at SBTs, other hydraulic structures and steep bedrock rivers exposed to high sediment transport rates under supercritical flow conditions. The present study was therefore conducted to address this issue by aiming at improving knowledge on abrasion mechanics and calibrating a mechanistic saltation abrasion model enhanced by Demiral-Yüzügüllü (2021). To this end, the abrasion resistance of fourteen different invert materials installed at Solis, Pfaffensprung and Runcahez SBTs in Switzerland was quantified by annual 3D laser scanning and the hydraulic conditions and sediment transport rates were regularly monitored between 2017 and 2021. The analysis of invert scans and hydraulic conditions revealed that Prandtl’s first and second kinds of secondary currents occurring in the bends and straight sections of the SBTs, respectively, and the observed abrasion patterns were strongly interrelated. The tested potassium aluminate cement and steel fibre concretes, granite, cast basalt and steel plates had better abrasion resistance against impact of sediment-laden flows compared to other materials. Sediment mineralogical composition i.e., bulk hardness relative to the invert material properties significantly affected hydroabrasion. The enhanced abrasion prediction model was calibrated with the present data and a quasi-constant abrasion coefficient of kv = (4.8 ± 2.2) × 104 was obtained. The enhanced model is well-suited for both laboratory and field scales. The present findings will contribute to the sustainable utilization and operational safety of hydraulic structures, optimization of SBT and reservoir operations regarding bypassing efficiency and reservoir lifetime and modelling of bedrock river erosion.

Transient Mechanism Analysis of Three-Dimensional Zinc-Nickel Single Flow Battery Based on Different Negative Electrode Structures

On the basis of the mass, momentum, charge conservation equations, in addition to coupled with the global reaction kinetic equations, a transient three-dimensional mechanistic analytical model of zinc-nickel single flow batteries (ZNBs), which comprehensively takes into account the hydrogen and oxygen evolution side reactions, the polarization distribution, as well as the structural effects of the pole lugs, is developed in this paper. After grid independence validation and experimental verification, the polarization distribution, side-reaction current density, and battery efficiency of ZNBs at high current density and multiple cycles of charging and discharging were comparatively analyzed based on this model with different anode materials of nickel sheet (NS) and porous nickel foam (NF). Subsequently, the effects of changes in negative electrode porous nickel foam thickness and porosity on battery polarization, side-reaction current density and battery efficiency were further investigated. Finally, the performance of the battery under the optimal battery state was studied. The results showed that the NF negative electrode effectively reduced the battery polarization, suppressed the battery side reactions as well as improved the battery efficiency under high current density and multiple cycles of charging and discharging, which improved the efficiency and stability of the battery.

Atmospheric drought dominates changes in global water use efficiency

Water use efficiency (defined as the ratio of gross primary productivity to plant transpiration, WUET) describes the tradeoff between ecosystem carbon uptake and water loss. However, a comprehensive understanding of the impact of soil and atmospheric moisture deficits on WUET across large regions remains incomplete. Solar-induced chlorophyll fluorescence (SIF) serves as an effective signal for measuring both terrestrial vegetation photosynthesis and transpiration, thereby enabling a rapid response to changes in the physiological status of plants under water stress. The objectives of this study were to: 1) mechanistically calculate WUET using top-of-canopy SIF data and meteorological information by using the revised mechanistic light response model and the Penman-Monteith equation; 2) analyze the effects of atmospheric and soil water deficits on SIF-based WUET by using decoupled soil water content (SWC) and vapor pressure deficit (VPD); 3) evaluate estimated SIF-based WUET against data from 28 eddy covariance (EC) flux sites representing eight different vegetation types. Results indicated that the model performed well in ecosystems with dense canopies, explaining 56 % of the daily variability in EC tower-based WUET. For the years 2019–2020, the global average WUET derived from SIF was 3.49 g C/kg H2O. Notably, this value exceeded 4 g C/kg H2O in tropical rainforest regions near the equator and went beyond 5 g C/kg H2O in the high-latitude regions of the Northern Hemisphere. We found that SIF-based WUET was primarily influenced by VPD rather than SWC in over 90 % of the global vegetated area. The model used in this study increased our ability to mechanistically estimate WUET with SIF at the global scale, thereby highlighting the significance of the global response of SIF-based WUET to water stress, and also enhancing our understanding of the water‑carbon cycle in terrestrial ecosystems.

Time-dependent interaction modification generated from plant-soil feedback.

Pairwise interactions between species can be modified by other community members, leading to emergent dynamics contingent on community composition. Despite the prevalence of such higher-order interactions, little is known about how they are linked to the timing and order of species' arrival. We generate population dynamics from a mechanistic plant-soil feedback model, then apply a general theoretical framework to show that the modification of a pairwise interaction by a third plant depends on its germination phenology. These time-dependent interaction modifications emerge from concurrent changes in plant and microbe populations and are strengthened by higher overlap between plants' associated microbiomes. The interaction between this overlap and the specificity of microbiomes further determines plant coexistence. Our framework is widely applicable to mechanisms in other systems from which similar time-dependent interaction modifications can emerge, highlighting the need to integrate temporal shifts of species interactions to predict the emergent dynamics of natural communities.

Meta-analysis reveals that the effects of precipitation change on soil and litter fauna in forests depend on body size.

Anthropogenic climate change is altering precipitation regimes at a global scale. While precipitation changes have been linked to changes in the abundance and diversity of soil and litter invertebrate fauna in forests, general trends have remained elusive due to mixed results from primary studies. We used a meta-analysis based on 430 comparisons from 38 primary studies to address associated knowledge gaps, (i) quantifying impacts of precipitation change on forest soil and litter fauna abundance and diversity, (ii) exploring reasons for variation in impacts and (iii) examining biases affecting the realism and accuracy of experimental studies. Precipitation reductions led to a decrease of 39% in soil and litter fauna abundance, with a 35% increase in abundance under precipitation increases, while diversity impacts were smaller. A statistical model containing an interaction between body size and the magnitude of precipitation change showed that mesofauna (e.g. mites, collembola) responded most to changes in precipitation. Changes in taxonomic richness were related solely to the magnitude of precipitation change. Our results suggest that body size is related to the ability of a taxon to survive under drought conditions, or to benefit from high precipitation. We also found that most experiments manipulated precipitation in a way that aligns better with predicted extreme climatic events than with predicted average annual changes in precipitation and that the experimental plots used in experiments were likely too small to accurately capture changes for mobile taxa. The relationship between body size and response to precipitation found here has far-reaching implications for our ability to predict future responses of soil biodiversity to climate change and will help to produce more realistic mechanistic soil models which aim to simulate the responses of soils to global change.

Modeling the larval growth and survival of Pacific cod (Gadus macrocephalus) in the eastern Bering Sea

The eastern Bering Sea (EBS) is a highly productive ecosystem that supports several important commercial species such as the Pacific cod (Gadus macrocephalus). Climate variability affects the population dynamics of this stock throughout its life stages, especially early life stages, since they are particularly susceptible to environmental changes. In recent decades, warm and cold stanzas (i.e., 3–5 year periods) have been observed in the EBS, and there is evidence that they can modulate the recruitment of this stock, causing important socioeconomic impacts. Using a mechanistic individual-based model, this study investigates the spatial and temporal variability of growth and survival of Pacific cod's early life stages during 2000–2020. We examined changes by year and over space and compared our results with published literature to validate our model. We found that temperature played a key role in modulating the survival of fish larvae, observing an increase in starvation events in warmer years or locations. Periods or areas with low prey density, especially small-bodied copepods, also contributed to increased starvation. The average temperature in the fish habitat was negatively correlated with recruitment estimates from the stock assessment model. Growth was primarily temperature-driven; however, food-limited growth became more frequent when larvae were smaller during cold years. Spatially, we found that the environmental conditions in the southeastern Bering Sea may favor larval survival but reduce growth, and higher mortality may be persistent on the middle and outer shelf. Our model produces results that agree with previous field studies, and it offers a valuable tool to investigate other ecological questions on the impact of the environment on early life stages of fishes.

Bioequivalence prediction with small-scale biphasic dissolution and simultaneous dissolution-permeation apparatus—An aripiprazole case study

Both biphasic dissolution and simultaneous dissolution-permeation (D-P) systems have great potential to improve the in vitro-in vivo correlation compared to simple dissolution assays, but the assay conditions, and the evaluation methods still need to be refined in order to effectively use these apparatuses in drug development.Therefore, this comprehensive study aimed to compare the predictive accuracy of small-volume (16–20 mL) D-P system and small-volume (40–80 mL) biphasic dissolution apparatus in bioequivalence prediction of five aripiprazole (ARP) containing marketed drug products.Assay conditions, specifically dose dependence were studied to overcome the limitations of both small-scale systems. In case of biphasic dissolution the in vivo maximum plasma concentration (Cmax) prediction greatly improved with the dose reduction of ARP, while in case of the D-P setup the use of whole tablet gave just as accurate prediction as the scaled dose. With the dose reduction strategy both equipment was able to reach 100 % accuracy in bioequivalence prediction for Cmax ratio. In case of the in vivo area under the curve (AUC) prediction the predictive accuracy for the AUC ratio was not dependent on the dose, and both apparatus had a 100 % accuracy predicting bioequivalence based on AUC results.This paper presents for the first time that not only selected parameters of flux assays (like permeability, initial flux, AUC value) were used as an input parameter of a mechanistic model (gastrointestinal unified theory) to predict absorption rate but the whole in vitro flux profile was used. All fraction absorbed values estimated by Predictor Software fell within the ±15 % acceptance range during the comparison with the in vivo data.

Reprint of: Prelude to molecularization: The double gradient model of Sulo Toivonen and Lauri Saxén

The present molecular investigations of Organizer phenomena show a remarkable connection to the earlier classical embryological studies that used transplantation as a method for making mechanistic models of induction. One of the most prominent of these connections is the dual gradient model for anterior-posterior and dorsal-ventral polarity. This paper will discuss some of the history of how transplantation experiments provided data that could be interpreted in terms of two gradients of biologically active materials. It will highlight how the attempts to discover the elusive Induktionsstoffen gave rise to the double gradient model of Sulo Toivonen and Lauri Saxén in the 1950s and 1960s. This paper will also document how this research into the identity of these molecules gave rise to the developmental genetics that eventually would find the molecules responsible for primary embryonic induction.

Spatiotemporal Patterns and Environmental Drivers of Particulate Inorganic Carbon (PIC) Variability in the Southern Waters of Sumatra‐Java Islands

AbstractThe southern waters of the Sumatra‐Java Islands, within the Indo‐Pacific Warm Pool, are highly susceptible to global climate change impacts. Understanding particulate inorganic carbon (PIC) dynamics and environmental responses in this region is critical for assessing climate change effects on marine ecosystems. Utilizing two decades of remote sensing PIC data (2003–2022), we identified five sub‐regions via K‐means clustering: the Sunda Strait, southern coastal/offshore waters of Sumatra Island, and southern coastal/offshore waters of Java Island. Self‐Organizing Map explored interannual PIC variations, while Generalized Additive Models delineated driving factors. In the Sunda Strait, PIC dynamics are influenced by water exchanges between the Indonesian Seas (ISs) and eastern Indian Ocean (EIO). Seasonally, PIC concentrations peak during the east monsoon (boreal summer); decreasing during positive Indian Ocean Dipole (+IOD) and El Niño events. Along the southern Sumatra, PIC variations positively correlate with rainfall and photosynthetically active radiation (PAR). Along the southern Sumatra, upwelling drives PIC variations, with higher concentrations during mature summer monsoon induced upwelling periods. PIC increases during +IOD and decreases during El Niño. Our study highlights the nexus between nutrients, physical factors (e.g., rainfall), and climatic events (e.g., El Niño) on PIC concentrations. Climate‐induced changes in oceanic physical processes modulate nutrient concentrations, thereby governing PIC variations. We propose a mechanistic model to elucidate PIC variations in upwelling areas. Findings suggest that prospective climate variability, encompassing alterations in climate events, rainfall, and temperature, may escalate PIC concentrations within the study area, advocating PIC as a forward‐looking climate change indicator.

Predicting gastric emptying of drug substances taken under postprandial conditions by combination of biorelevant dissolution and mechanistic in silico modeling

Physiologically based pharmacokinetic (PBPK) models can help to understand the effects of gastric emptying on pharmacokinetics and in particular also provide a platform for understanding mechanisms of food effects, as well as extrapolation between different postprandial conditions, whether standardized clinical or patient-oriented, non-clinical conditions. By integrating biorelevant dissolution data from the GastroDuo dissolution model into a previously described mechanistic model of fed-state gastric emptying, we simulated the effects of a high-calorie high-fat meal on the pharmacokinetics of sildenafil, febuxostat, acetylsalicylic acid, theobromine and caffeine. The model was able to simulate the variability in Cmax and tmax caused by the presence of the stomach road. The main influences investigated to affect the gastric emptying process were drug solubility (theobromine and caffeine), tablet dissolution rate (acetylsalicylic acid) and sensitivity to gastric motility (sildenafil and febuxostat). Finally, we showed how PBPK models can be used to extrapolate pharmacokinetics between different prandial states using theobromine as an example with results from a clinical study being presented.

Longevity of subtidal mussel beds (Mytilus edulis) in eutrophic coastal areas

Mussel populations (Mytilus edulis) around the coasts of Europe and the North Atlantic are often ephemeral and have notably experienced a large decline in abundance. Since 1993, annual blue mussel stock surveys have been carried out in the Limfjorden, Denmark. We used the stock survey data combined with electronic monitoring fishing data and Mechanistic Models for the Limfjorden, providing environmental data to investigate the impact of various stressors. Multiple factors were found to affect the longevity of subtidal mussel beds in Limfjorden. Predation by starfish, fishing activities, shell length of the mussels, amplitude in summer temperature and consecutive days of oxygen depletion decreased the longevity of the beds. Conversely, increased biomass, multiple cohorts and increasing water depth demonstrate stabilizing effects. Water column stratification had both a negative and positive impact on bed longevity depending on the duration. These analyses can help inform environmental, conservation, and fisheries managers on the long-term trends of population dynamics and gain a deeper understanding of what factors can affect mussel bed longevity in the context of declining stocks.

Improved size effect law (SEL) considering size-dependent fracture process zone (FPZ) for quasi-brittle materials

Establishing a mechanistic model to simultaneously capture the descending size effect (DSE) and the change from DSE to the ascending size effect (ASE) remains a challenging issue for quasi-brittle materials. A size-dependent fracture process zone (FPZ) model is proposed and verified by experimental and simulative results. Subsequently, the size effect law (SEL) of unnotched specimens is improved by considering the size-dependent FPZ model, which is termed the improved SEL in this paper. Parametric studies are conducted for a better understanding of the improved SEL. It is found that the underlying mechanism of the DSE and the change from DSE to ASE is the competition between the relative rates of FPZ and specimen size change with respect to specimen size. The ASE is obtained when the relative rate of FPZ change is higher than that of specimen size. Conversely, the DSE is observed. No size effect exists when the relative rate of FPZ change is equal to that of specimen size. Experimental and simulative results are adopted to validate the improved SEL of unnotched specimens. The validation of the improved SEL indicates that the improved SEL not only accurately predicts the DSE, but also correctly captures the change from DSE to ASE. In addition, the size effect of nominal strength with different maximum aggregate size is well captured by the improved SEL. The fitting parameters of the improved SEL lie in the given interval. By comparing the determination coefficients R2 of the SEL, unified size effect law (USEL), and improved SEL, it is found that the R2 of the improved SEL is higher than that of the SEL for the DSE and is close to that of the IUSEL for the change from DSE to ASE. Therefore, it is recommended that engineers and researchers use the improved SEL to describe the DSE and the change from DSE to ASE of unnotched specimens.

Towards a mechanistic model of oxidase deactivation in a bubble column

Despite the many advantages of biocatalysis, enzyme stability remains an issue. This work investigates the long-term kinetic stability of a water-forming NAD(P)H-oxidase (NOX2), an enzyme of potential industrial interest for NAD(P)H regeneration, in a bubble column sparged with air, which enables reasonable oxygen transfer but without drastic enzyme deactivation. Experiments have been performed with the particular goal of explaining the observed two-stage deactivation trend. We show evidence supporting the hypothesis that the first stage is related to the adsorption of enzymes to the interface, followed by a subsequent deactivation stage at the interface.The characterization of NOX deactivation in the bubble column setup, complemented by additional’quiescent’ experiments, has enabled the development of a first principles model as the first step towards a complete mechanistic model of oxidase deactivation at gas–liquid interfaces.

Mechanistic regulation of planarian shape during growth and degrowth.

Adult planarians can grow when fed and degrow (shrink) when starved while maintaining their whole-body shape. It is unknown how the morphogens patterning the planarian axes are coordinated during feeding and starvation or how they modulate the necessary differential tissue growth or degrowth. Here, we investigate the dynamics of planarian shape together with a theoretical study of the mechanisms regulating whole-body proportions and shape. We found that the planarian body proportions scale isometrically following similar linear rates during growth and degrowth, but that fed worms are significantly wider than starved worms. By combining a descriptive model of planarian shape and size with a mechanistic model of anterior-posterior and medio-lateral signaling calibrated with a novel parameter optimization methodology, we theoretically demonstrate that the feedback loop between these positional information signals and the shape they control can regulate the planarian whole-body shape during growth. Furthermore, the computational model produced the correct shape and size dynamics during degrowth as a result of a predicted increase in apoptosis rate and pole signal during starvation. These results offer mechanistic insights into the dynamic regulation of whole-body morphologies.

Mechanistic modeling of twin screw wet granulation for pharmaceutical formulations: Calibration, sensitivity analysis, and model-driven workflow

Wet granulation, a particle size enlargement process, can significantly enhance the critical quality attributes of powders and improve the ability to form tablets in pharmaceutical manufacturing. In this study, a mechanistic-based population balance model is applied to twin screw wet granulation. This model incorporated a recently developed breakage kernel specifically designed for twin screw granulation, along with nucleation, layering, and consolidation. Calibration and validation were performed on Hydrochlorothiazide and Acetaminophen formulations, which exhibit different particle size and wettability characteristics. Utilizing a compartmental experimental dataset, a comprehensive global sensitivity analysis identified critical inputs impacting quality attributes. The study revealed that the nucleation rate process model, effectively represented particle size distributions for both formulations. Adjustments to nucleation and breakage rate parameters, influenced by material properties and screw configuration, improved the model’s accuracy. A model-driven workflow was proposed, offering step-by-step guidelines and facilitating PBM model usage, providing essential details for future active pharmaceutical ingredient (API) formulations.