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Modelling Drying of APIs & Formulated Products
Tariq Mahmud School of Chemical & Process Engineering University of Leeds Leeds LS2 9JT iPRD Industrial Club Meeting, 12 May 2016
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Introduction Overview of modelling of drying processes in:
Agitated filter dryer – drying of API powder funded by Pfizer/EPSRC Spray dryers – manufacture of detergent powders funded by P&G and Innovate UK (P&G, PSE, Novozymes & UoL) Drying work packages in ADDoPT project Agitated filter dryer: filtration, washing, drying of APIs Spray drying of APIs/products & fluidised bed drying of granules ADDoPT - Advanced Digital Design of Pharmaceutical Therapeutics − A £20.4m UK Government-Industry-Academia collaboration, part-funded under AMSCI − To Transform UK Pharmaceutical Development and Manufacturing
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Drying of Pharmaceutical Powders in an Agitated Filter Dryer
Wei Li, Tariq Mahmud and Kevin J. Roberts School of Chemical & Process Engineering, University of Leeds Leeds LS2 9JT & D. J. am Ende and M. T. Maloney Chemical Research & Development, Pfizer Inc., Groton, USA EPSRC
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Drying of API in Agitated Filter Dryer (AFD)
Major challenges: preserve initial particle size and morphology by preventing unwanted agglomeration/attrition Agitation in wet state leads to agglomeration and in dry state leads to attrition Agglomerates may be small and hard or large “snowballs” - require special sieving, delumping, contributes to longer drying cycle times, negatively impact downstream unit operations drug product formulation Our goal is to better understand drying rates and effect of operating parameters especially under agitation through experiments in a lab-scale AFD To predict drying behaviour and time, and determine the optimum drying conditions using reliable drying process models So what is the best way to dry, when is the perfect time to stir and when we don’t want to stir too much ?
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5 L Laboratory-scale AFD
Solid: Aspirin powders, D50 = 100 µm Solvent: Water and ethanol
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Through-circulation convective drying
Experimental Conditions Drying mode Conditions Range Vacuum contact drying Jacket temperature 60 – 80 ºC Vacuum level 110 – 170 mbar Initial solvent content 9 – 12 wt. % Agitation speed 10 – 30 rpm Through-circulation convective drying Inlet gas flowrate 0.007 – 0.01 kg/m2·s 8 – 20 wt. %
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Experimental Data – Vacuum Contact Drying
Static bed Agitated bed (20rpm) TC TC-2 TC-3
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Experimental Data – Convective Drying
Static bed Agitated bed (20rpm) TC-1 TC-2 TC-3 TC-4
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Implementation of Models in gPROMPS
Strategy for Drying Model Development Model-1: Lumped-parameter model for vacuum contact drying of static bed State variables (temperature, moisture content) ƒ(time) Model equations: Ordinary differential equations Heating from the side wall and the bottom of the vessel Model-4: Distributed-parameter model for vacuum contact and convective drying of a static bed ƒ(time, space [r, z]) Model equations: Partial differential equations Implementation of Models in gPROMPS Model-2: Distributed-parameter model for vacuum contact drying with agitation State variables ƒ(time, space [r, z]) Extension of Model-1 to an Agitated Bed with intermittent stirring in gSOLIDs Model-3: Lumped-parameter model for convective drying through a static bed State variables ƒ(time)
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Vacuum Contact Drying: Lumped-Parameter Model
Constant-rate period Falling-rate period
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Distributed Parameter Drying Model
Vacuum Contact Drying: Distributed-Parameter Model Variation of solvent content with time in static bed contact drying (▬ simulation, (▬ experimental data)
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Through-Circulation Convective Drying: Distributed Parameter Model
Simulated (—) and experimental moisture profiles (—)
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Modelling of Spray Drying Towers
Muzammil Ali, Tariq Mahmud, Peter Heggs, Mojtaba Ghadiri and Andrew Bayly NOVOZYMES Innovate UK
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Aims and Objectives Development of simplified models for co- and counter-current spray drying towers Develop CFD modelling methodologies for spray drying processes and predict spray dryer performance Propose a multi-zonal approach for modelling spray drying towers based of detail CFD predictions Integrate multi-zonal model in PSE’s gSOLIDS software for optimisation of energy utilization for spray drying processes
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Zoning Strategy of Spray Drying Towers
Zoning strategies were developed at Leeds based on CFD modelling. Scaling functions were developed based on zoning approach with PSE’s collaboration. Scaling functions enabled PSE to develop a tool for optimising energy utilization for spray towers in gSOLIDS. CFD Results Zoning Approach CFD Results Zoning Approach Novozymes Tower P&G Tower
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Spray drying of detergent slurry in a pilot-plant at P&G
Modelling Counter-Current Spray Drying Tower Slurry Atomiser Dried Detergent Powder Drying Gas Slurry Droplet Wet Particle Dried Particle Exhaust gas Spray Drying Tower Spray drying of detergent slurry in a pilot-plant at P&G
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Modelling Approach Numerical Modelling of a Pilot-Scale Counter-Current Spray Drying Tower Single Droplet Drying Model Industrial Pilot-Plant Data Plug Flow Modelling CFD Modelling Velocity Profiles Temperature Profiles Inlet/Outlet Data Isothermal Single Phase CFD Modelling Non-Isothermal Single Phase CFD Modelling Multiphase CFD Modelling Recommended Approach for Zonal Modelling
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Single Droplet Drying Model
The droplet drying kinetics is studied by incorporating a semi-empirical droplet drying model developed by P&G[1]. The model is based on a full numerical model[2]. Drying takes place in three stages: A-B: Saturated surface drying. C: Internal moisture diffusion controlled drying. D: Heat transfer controlled drying at the slurry boiling point followed by particle inflation. 1. Ali et al. (2014). Chem. Eng. Res. Des., vol. 92, pp.826 – 841. 2. Hecht J. P. and King C. J., (2000). Ind. Eng. Chem., vol. 39, pp – 1774.
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Plug Flow Model Cheap compared to detailed CFD approach.
Estimation of the influence of operating conditions on the powder characteristics. Gas and droplets/particles profiles along the tower height. __________________________________________ Ali et al. (2014). Chem. Eng. Res. Des., vol. 92, pp.826 – 841
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CFD Modelling of Spray Drying Process
Sub-Models Slurry Atomiser Dried Detergent Powder Drying Gas Slurry Droplet Wet Particle Dried Particle Exhaust gas Spray Drying Tower Multiphase CFD Model Droplet Drying Model Heat/Mass Transfer, Size and Morphological Changes Particle-Wall Interaction Model Deposition, Drying, Re-entrainment, Attrition, Rebound, Sliding/Rolling and Breakage Droplets and Particles Interaction Model Coalescence, Agglomeration, Rebound and Breakage Heat Loss Through Tower wall & Insulation __________________________________________ Ali et al. (2016). J Drying Technology, available online, March 2016
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CFD Simulation Results
CFD simulation of a Counter-Current Spray Drying Tower Incorporating Droplet Drying Model Diameter (m) Entrained fine particles Sprayed droplets Dried particles exit Small particles swirl Particle Trajectories Slurry Spray Gas Inlets kg/kg oC Droplets/particles trajectories Gas temperature Gas moisture fraction
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Multi-Zonal Modelling Approach
RTD of Particles and Gas Temperature Profiles Zonal Model Gas Outlet Multiphase CFD Coupled with Droplet Drying Model Zone1 CSTR Slurry Zone 2 Plug Flow Drying Kinetics Droplet Drying Model Zone 4 Zone 3 Zone 3 Plug Flow Hot gas Inlets Hot gas Inlets Zone 5 CSTR Dried Particles
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Forward Look 1 2 3 5 4 Droplet Drying Model
Coupled CFD-DEM Modelling to Study Particle-Particle and Particle-Wall Interactions 5 Multiphase CFD Modelling 4 Particle Interaction Models Zonal Modelling
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