Implementing Fundamental Pharmaceutical Science and ... · Scale-up or down? What to scale-up?...
Transcript of Implementing Fundamental Pharmaceutical Science and ... · Scale-up or down? What to scale-up?...
Implementing Fundamental Pharmaceutical Science and Materials/Engineer Expertise
in Scale -up
2nd FDA/PQRI Conference on Advancing Product Quality Session: The Science of Tech Transfer/Scale- up
North Bethesda, Maryland, October 05-07, 2015
Ecevit Bilgili(E-mail: [email protected], Phone: 973-596-2998)
Associate Professor & Associate Chair
Department of Chemical, Biological, & Pharmaceutical Engineering
New Jersey Institute of TechnologyNewark, NJ
OutlineA 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
The Concept of (FBG) Scale-up in Batch Processes
(100-150 kg)(10-15 kg)
(~100 g)
Product volume, batch size, and capacity increase with scale.
Robust Product
Process
Formulation & Materials
Equipment
D. Ventura, American Association of Pharmaceutical Scientists Workshop, Sept. 2006
Elements of a QbD Program
The same elements are needed for successful scale-up! Scale-up/down is an integral part of product (process/formulation) development.
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.
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 equipment-
independent, “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.
Lab Scale Pilot Scale
Commercial ScaleScale-up
On Various Process Modeling Approaches
CFD Simulation of Multiphase Flow in an FBG: Volume fraction of powder
DEM Simulation: a milling ball on
particles
DEM-PBM Multi-Scale Modeling Approach for Dry Milling (Capece et al., 2015, Chem. Eng. Sci.)
Case Study: Scale -up of Fluidized Bed Granulation (FBG) Process
ABC of FBG
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
How does FBG Work?
Ambient AirSucked In
Exhaust Air
Air Handling
Unit(AHU)
Binder Solution
Exhaust Fan
Police Filters
Expansion Chamber
Product BowlTwo-fluid Nozzle Assembly
Pump
Inlet Plenum
Air Filters
Filter Bags
Powder Bed
Conical binder spray (droplets)
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 columnnumber of nozzle headsliquid tip, air cap sizerelative 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
What is Fluidization? Fundamentals (I)
Schematic from a Lecture by Prof. J. Werther, 5th World Cong. on Particle Technol. 2006
Fluidization Regimes as Determined by Superficial A ir Velocity & Material Characteristics
Vigorous bubbling/turbulent fluidization is key to a successful FBG process.
What is Fluidization? Fundamentals (II)
Lecture by Prof. J. Werther, 5th World Cong. on Particle Technol. 2006
Geldart’s Classification of Powders
Case Study: Scale -up of Fluidized Bed Granulation Process
Scale-up to Ensure Key Response Variables Remain Scale -Invariant
Process Scale-up (I): What to Maintain?
Key Input Variables
Key Response (Output) Variables
Product Characteristics
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
Hydrodynamic Behavior
Bed moisture and temperature
Droplet size distribution
Binder/saturation distribution
PSD
Drying-end-point moisture
Granule Morphology
Granule porosity
Scaling rules based on theory/modeling/heuristics/experiments are needed!!!
Process Scale-up (II): Scaling Rules for FBG
Key Input Variables
Key Response (Output) Variables
Air Flow Rate, Q
Distributor Plate Area, A
Spray Rate, S
Inlet Air Temperature and Humidity, Tin&RH
Atomization Air Flow or Pressure, Ma or Pa
Number of nozzle heads, N
Spray foot-print area, Af
Hydrodynamic Behavior
Bed moisture and temperature
Droplet size distribution
Dimensionless Spray Flux (Litster, 2001) or
Akkermans Flux #, FN (1988)
Scaling Rules (Connecting Input
to Response)
mfmf uA
Quuue −=−=
RHTQ
S,, in
22or
aa NP
S
NM
S
=
=
S
AuFN
Px
S
fep
d
ρ
ψ
10log
2
3
Mehta (1988), Rambali (2003)
Granule PSD upon Scale-up
Similar granule PSD achieved at 420L scale in Batch B, after slightly adjusting the spray rate from that in Batc h A (Basis for
scale-up: Batch 0042 at 45 L scale).
Sieve Opening Size (µm)
0 200 400 600 800 1000
Cum
ulat
ive
Mas
s P
erce
nt R
etai
ned
(%)
0
20
40
60
80
100
45 L, 0219151:0042, 2.1%45 L, 0219151:0043, 5.2%45 L, 0219151:0044, 1.3%420 L Scale Batch A, 1.6%420 L Scale Batch B, 2.2%
Peak LOD
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 physi cal transformations as opposed to “black-box” treatment of processes
To DesignOE or not to DesignOE upon scale-up? Too e xpensive, impractical, …Not needed with establishment of good process understanding at smal/pilot scales.
Design space in terms of scale-independent paramete rsMay provide regulatory flexibility for tech transfe r Instead of reestablishing the design space at each scale, confirm the “relatively fixed design” space at larg er scales