Implementing Fundamental Pharmaceutical Science and Materials/Engineer Expertise in Scale-up

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1 Implementing Fundamental Pharmaceutical Science and Materials/Engineer Expertise in Scale-up 2 nd FDA/PQRI Conference on Advancing Product Quality Session: The Science of Tech Transfer/Scale-up North Bethesda, Maryland, October 05-07, 2015 Ecevit Bilgili ( bilgece@njit.edu, Phone: ) Associate Professor & Associate Chair Department of Chemical, Biological, & Pharmaceutical Engineering New Jersey Institute of Technology Newark, NJ

2 Outline A chemical engineering perspective to unit ops. scale-up Art or science/engineering or maybe both? Scale-up or down? What to scale-up? Fundamental, first-principle-based models (DEM/PBM/CFD) Criticality of understanding the key physical transformations, measuring relevant response variables and using scale-up rules/heuristics & PAT/simulators Case Study with Fluidized Bed Granulation (FBG) Scale-up Brief intro to FBG Demonstration of scale-up Do scaling rules/pat/surrogate tools work? Conclusions and Outlook

3 The Concept of (FBG) Scale-up in Batch Processes (~100 g) (10-15 kg) ( kg) Product volume, batch size, and capacity increase with scale.

4 Elements of a QbD Program D. Ventura, American Association of Pharmaceutical Scientists Workshop, Sept Robust Product Formulation & Materials Equipment Process The same elements are needed for successful scale-up! Scale-up/down is an integral part of product (process/formulation) development.

5 Fact: Scale-up still entails a marriage between science/engineering and the art of making! Unit ops. scale-up has evolved from traditional trial-error approach to a creative activity involving scientific/engineering principles More use of scale-up rules based on fundamental dimensionless #s and empirical studies More use of first-principle-based models based on continuum theories or discrete particle interactions (DEM/PBM/CFD/FEM) & their combination More use of PAT and data-driven process models But the art of making/manufacturing did not disappear: Scale-up: a creative process also requiring skills based on experience (personal skills, company internal knowhow/culture) and observation of process, equipment, and operational aspects as well as economics Upon more use of scientific/engineering principles, the involvement of the art component will be less significant.

6 Scale-up or down? What to scale-up? Scale-up is an integral part of product development. Process development at small/pilot scale equipment must consider eventual scale-up. In the selection of smaller scale equipment/process, we use Scale-up rules for approximate scale-down In-house experience/expertise, equipment knowledge, etc. Retrospective studies of prior development activities We cannot perform DOEs at every scale. Hence, understanding the key physical transformations and considering equipmentindependent, key response variables for scale-up/down is critical. Design space grows automatically if extensive process variables vs. dimensionless or key response variables are used. Scale-up Commercial Scale Lab Scale Pilot Scale

$fraction of powder$ Modeling Approach

7 On Various Process Modeling Approaches DEM Simulation: a milling ball on particles CFD Simulation of Multiphase Flow in an FBG: Volume fraction of powder DEM-PBM Multi-Scale Modeling Approach for Dry Milling (Capece et al., 2015, Chem. Eng. Sci.)

8 Case Study: Scale-up of Fluidized Bed Granulation (FBG) Process ABC of FBG

9 What is Fluid Bed Granulation? Definition: A wet granulation process in which API(s) and excipient powders, which are set in fluidization by a heated gas, are bound together by binder droplets originating from a two-fluid nozzle Objective: Form granules that allow or improve successful down-stream processing of pharmaceutical materials (from blending to tabletting) Materials: API(s), excipients, binder (usually dissolved in a solvent prior to atomization) Equipment: An FBG processer equipped with an air handling unit (AHU), two-fluid atomizing nozzle, and spray pump

10 How does FBG Work? Exhaust Air Exhaust Fan Police Filters Filter Bags Two-fluid Nozzle Assembly Powder Bed Expansion Chamber Conical binder spray (droplets) Product Bowl Pump Binder Solution Inlet Plenum Air Handling Unit (AHU) Ambient Air Sucked In Air Filters

11 Fluid Bed Granulation Parameters Equipment Process Formulation Gas Distributor Plate: type, nominal & open Area Bowl-Expansion Chamber: diameter, height, cone angle Two-fluid Nozzle: location on the column number of nozzle heads liquid tip, air cap size relative position of tip/air cap Air Handling Unit (AHU) Filter Bag/Cartridge: type, pore size, permeability one-side vs. two-side shake, Pulsation pressure Hydrodynamic Behavior: Inlet air flow rate Binder Soln. Dispersion & Droplet Size Distribution: dimensionless flux number, spray rate, atomization air pressure and flow rate Product Bed Moisture Content & Temperature: Spray rate, excess air velocity, inlet air flow rate, temperature, and humidity Bed height: batch size Fines Incorporation: shake duration & frequency, inlet air flowrate Particle: Density, size, shape, surface characteristics, porosity, friction, terminal velocity, initial moisture, dissolution, hydrophilicity, wettability, mechanical properties Bulk/Powder: Bulk/tap density, cohesion, minimum fluidization and bubbling velocity Binder and Binder Solution: Level, concentration, viscosity, surface tension 11

12 What is Fluidization? Fundamentals (I) Fluidization Regimes as Determined by Superficial Air Velocity & Material Characteristics Vigorous bubbling/turbulent fluidization is key to a successful FBG process. Schematic from a Lecture by Prof. J. Werther, 5 th World Cong. on Particle Technol. 2006

13 What is Fluidization? Fundamentals (II) Geldart s Classification of Powders Lecture by Prof. J. Werther, 5 th World Cong. on Particle Technol. 2006

14 Case Study: Scale-up of Fluidized Bed Granulation Process Scale-up to Ensure Key Response Variables Remain Scale-Invariant

15 Process Scale-up (I): What to Maintain? Key Input Variables Air Flow Rate, Q Distributor Plate Area, A Spray Rate, S Inlet Air Temperature/RH Atomization Air Pressure, P Number of nozzle heads, N Spray foot-print area, A f Scaling rules based on theory/modeling/heuristics/ experiments are needed!!! Key Response (Output) Variables Hydrodynamic Behavior Bed moisture and temperature Droplet size distribution Binder/saturation distribution Product Characteristics PSD Drying-end-point moisture Granule Morphology Granule porosity

16 Process Scale-up (II): Scaling Rules for FBG Key Input Variables Air Flow Rate, Q Distributor Plate Area, A Spray Rate, S Inlet Air Temperature and Humidity, T in &RH Atomization Air Flow or Pressure, M a or P a Number of nozzle heads, N Spray foot-print area, A f Scaling Rules (Connecting Input to Response) u e = u u Mehta (1988), Rambali (2003) ψ = 3S 2Px Q = A mf u mf S NM d S Q, T, in RH S NP or 2 a a2 ρ pue Af FN = log 10 S Key Response (Output) Variables Hydrodynamic Behavior Bed moisture and temperature Droplet size distribution Dimensionless Spray Flux (Litster, 2001) or Akkermans Flux #, FN (1988)

17 Granule PSD upon Scale-up Cumulative Mass Percent Retained (%) Sieve Opening Size (µm) Peak LOD 45 L, :0042, 2.1% 45 L, :0043, 5.2% 45 L, :0044, 1.3% 420 L Scale Batch A, 1.6% 420 L Scale Batch B, 2.2% Similar granule PSD achieved at 420L scale in Batch B, after slightly adjusting the spray rate from that in Batch A (Basis for scale-up: Batch 0042 at 45 L scale).

18 Conclusions & Outlook More science/engineering vs. the art More scale-up rules and modeling for process scale-up; no more trial-error A fundamental understanding of the underlying physical transformations as opposed to black-box treatment of processes To DesignOE or not to DesignOE upon scale-up? Too expensive, impractical, Not needed with establishment of good process understanding at smal/pilot scales. Design space in terms of scale-independent parameters May provide regulatory flexibility for tech transfer Instead of reestablishing the design space at each scale, confirm the relatively fixed design space at larger scales

MULTI-SCALE SIMULATION APPROACH FOR THE FLUIDISED BED SPRAY GRANULATION PROCESS

MULTI-SCALE SIMULATION APPROACH FOR THE FLUIDISED BED SPRAY GRANULATION PROCESS STEFAN HEINRICH HAMBURG UNIVERSITY OF TECHNOLOGY, Germany NIELS DEEN & HANS KUIPERS EINDHOVEN UNIVERSITY OF TECHNOLOGY, The