in-situ particle characterization: applications in formulation development · pdf...
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In-Situ Particle Characterization: Applications in Formulation Development and Manufacturing –
Disintegration/Dissolution. Fluid Bed Layering, and High Shear Wet Granulation
Jeffrey W. Sherman, Ph.D.Des O’Grady PhD
The Cortona Conference
- Introduction to FBRM, PVM and the Formulations Workflow
- Case Study 1 – Mapping the Dissolution Design Space
- Case Study 2 – Optimizing Dissolution Through Root Cause Identification
- Case Study 3 – Correlating Upstream Parameters to Dissolution Behavior
- Case Study 4 – Understand Physical Properties to Improve Dissolution
- Conclusion
Executive Summary
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3
Dissolution and PAT
FBRM® is used to understand the impact a formulation step has on tablet disintegration and dissolution mechanisms
FBRM® can identify the root cause of dissolution inconsistency leading to a better understood process
FBRM® can speed process development by providing immediate understanding that allows formulators to make better decisions faster
This can save up to months of development time, target consistent final products, and ensure formulators have answers for regulatory questions
Where does particle size matter?
Wrong sizeMultiple mill passesIncomplete milling
Mill
Optimize
Varying raw materialsSegregation in feedVariable API particle size
API ExcipientsBinder
Fluid bed
High attrition ratesInconsistent endpointIntensive optimization studies
Granulator
Inconsistent endpoint (fine, coarse, bimodal)API agglomeration Form conversionScale-up issues
Poor flow properties SegregationVariable tablet properties
Tablet press
Blender
The significance of particle size and shape
Dr. Zhigang Sun, FDA, Particle Size Specifications for Solid Oral Dosage Forms, AAPS 2008, Atlanta
The significance of particle size and shape
Dr. Zhigang Sun, FDA, Particle Size Specifications for Solid Oral Dosage Forms, AAPS 2008, Atlanta
FDA Stance on Dissolution Testing
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http://www.fda.gov/cder/Offices/ONDQA/presentations/051024-MMN-Dissolution.pdf
FDA Stance on Dissolution Testing
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Moheb Nasr, FDA-CDER, Advisory Committee of Pharmaceutical Science (ACPS)
FDA Stance on Dissolution Testing
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Moheb Nasr, FDA-CDER, Advisory Committee of Pharmaceutical Science (ACPS)
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PVM® TechnologyParticle Video Microscope
Microscope quality image sin-process and in real time
Characterize particle systems from 2µm to 1mm
FBRM® TechnologyFocused Beam Reflectance Measurement
Track the rate and degree of change to particle dimension, count and shape as they naturally exist in process
Characterize particle systems from submicron to 3mm
FBRM® PVM®
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The FBRM® Method of Measurement
FBRM®Probe TubeFBRM®Probe Tube
SapphireWindowSapphireWindow
Beam splitterBeam splitter
Rotating opticsRotating optics
FBRM®Probe TubeFBRM®Probe Tube
SapphireWindowSapphireWindow
Laser source fiberLaser source fiber
Beam splitterBeam splitter
Rotating opticsRotating optics
Focused beamFocused beamFBRM®Probe TubeFBRM®Probe Tube
SapphireWindowSapphireWindow
Detection fiberDetection fiberLaser source fiberLaser source fiber
Beam splitterBeam splitter
Rotating opticsRotating optics
Focused beamFocused beamFBRM®Probe TubeFBRM®Probe Tube
SapphireWindowSapphireWindow
Cutaway view of FBRM® In-process Probe
PVM® image illustrating the view from the FBRM® Probe Window
Probe installed in process stream
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The FBRM® Method of MeasurementPVM® image illustrating the view from the FBRM® Probe Window
Probe detects pulses of Backscattered light
And records measured Chord Lengths
Enlarged view
Path of Focused Beam
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The FBRM® Method of Measurement
Path of Focused Beam
Enlarged view
Thousands of Chord Lengths are measured each second to produce the FBRM® Chord Length Distribution :
Square weighted Distribution
Optimizing Petroleum processing with In Situ Particle Characterization
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FBRM distributions at key points show a decrease in count and an increase in dimension - particle agglomeration
Applying a weighting to the FBRM distribution enhances the resolution to change in different size ranges
Unweighted distribution is sensitive to fine particles and particle population
Square weighted distributions is sensitive to coarse particles and particle dimension
Decrease in population
Increase in dimension
Unweighted Distribution
Decrease in population
Increase in dimension
Optimizing Petroleum processing with In Situ Particle Characterization
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Mean = 75µm
Mean = 82µm
Mean = 141µm
Unweighted Distribution
Square Weighted Distribution
#/s <50 µm
#/s 50-1000 µm
Where does particle size matter?
Wrong sizeMultiple mill passesIncomplete milling
Mill
Optimize
Varying raw materialsSegregation in feedVariable API particle size
API ExcipientsBinder
Fluid bed
High attrition ratesInconsistent endpointIntensive optimization studies
Granulator
Inconsistent endpoint (fine, coarse, bimodal)API agglomeration Form conversionScale-up issues
Poor flow properties SegregationVariable tablet properties
Tablet press
Blender
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Dissolution and PAT
Dissolution testing with in situ particle characterization is a powerful tool for Quality by Design
FBRM® can link tablet disintegration and dissolution mechanisms to upstream formulation process steps and to the initial API and excipient particle size
Other techniques such as UV/VIS or IR to track solute concentration in real time
Speed process development by understanding if dissolution inconsistency it due to the formulation, raw materials or process variability
FBRM®
S400
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MT-Distek – Dissolution inconsistency
In this study dissolution and disintegration kinetics are compared for two acetaminophen based painkillers
A comparison is made between innovator and generic rapid release gel tablets
The innovator API release rate (UV-vis) is significantly faster. Why?
FBRM trends show the innovator tablet breaks apart rapidly into fine particulates
The generic tablet breaks apart slowly into a smaller number of fine particulates
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MT-Distek – Dissolution inconsistency
The initial median dimension of the innovator particulates is ~40µm and it rapidly breaks apart to ~6µm
The initial median dimension of the generic particulates is ~52µm and it slowly breaks apart to ~10µm
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MT-Distek – Dissolution inconsistency
The difference in release rate is clearly NOT a result of a difference in the intrinsic API solubilization rate – (i.e. differences in API PSD or impurity profile)
The difference is clearly a result of the formulation conditionsOver granulation or incomplete milling results in large granules in tablet press?
Difference in formulation components influences the inter and intra granule forces?
Fragmentation and compaction on the tablet press results in granule agglomeration?
Tablet coating retards granule break-up?
Tablet and Granule Release Mechanisms
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Disintegration
Diffusion
Mark Menning, Amgen, FBRM User’s Conference 2000
Innovator
Generic
- Introduction to FBRM, PVM and the Formulations Workflow
- Case Study 1 – Mapping the Dissolution Design Space
- Case Study 2 – Optimizing Dissolution Through Root Cause Identification
- Case Study 3 – Correlating Upstream Parameters to Dissolution Behavior
- Case Study 4 – Understand Physical Properties to Improve Dissolution
- Conclusion
Executive Summary
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Understand Disintegration Kinetics Leads to Risk Assessment
23Novel process Analytical Methodology to Establish Design Space and Real Time Prediction of Dissolution. Jonas Johansson, Staffan Folestad et al, AZ PAT Centre of Excellence, AstraZeneca R&D, Mölndal, Sweden, AAPS Meeting May 2006
Understand Disintegration Kinetics Leads to Risk Assessment
24Novel process Analytical Methodology to Establish Design Space and Real Time Prediction of Dissolution. Jonas Johansson, Staffan Folestad et al, AZ PAT Centre of Excellence, AstraZeneca R&D, Mölndal, Sweden, AAPS Meeting May 2006
CountDisso
CountDisso
Understand Disintegration Kinetics Leads to Risk Assessment
25Novel process Analytical Methodology to Establish Design Space and Real Time Prediction of Dissolution. Jonas Johansson, Staffan Folestad et al, AZ PAT Centre of Excellence, AstraZeneca R&D, Mölndal, Sweden, AAPS Meeting May 2006
- Introduction to FBRM, PVM and the Formulations Workflow
- Case Study 1 – Mapping the Dissolution Design Space
- Case Study 2 – Optimizing Dissolution Through Root Cause Identification
- Case Study 3 – Correlating Upstream Parameters to Dissolution Behavior
- Case Study 4 – Understand Physical Properties to Improve Dissolution
- Conclusion
Executive Summary
26
Understand Disintegration Kinetics Leads to Risk Assessment
27Novel process Analytical Methodology to Establish Design Space and Real Time Prediction of Dissolution. Jonas Johansson, Staffan Folestad et al, AZ PAT Centre of Excellence, AstraZeneca R&D, Mölndal, Sweden, AAPS Meeting May 2006
Understand Disintegration Kinetics Leads to Risk Assessment
28Novel process Analytical Methodology to Establish Design Space and Real Time Prediction of Dissolution. Jonas Johansson, Staffan Folestad et al, AZ PAT Centre of Excellence, AstraZeneca R&D, Mölndal, Sweden, AAPS Meeting May 2006
Understand Disintegration Kinetics Leads to Risk Assessment
29Novel process Analytical Methodology to Establish Design Space and Real Time Prediction of Dissolution. Jonas Johansson, Staffan Folestad et al, AZ PAT Centre of Excellence, AstraZeneca R&D, Mölndal, Sweden, AAPS Meeting May 2006
- Introduction to FBRM, PVM and the Formulations Workflow
- Case Study 1 – Mapping the Dissolution Design Space
- Case Study 2 – Optimizing Dissolution Through Root Cause Identification
- Case Study 3 – Correlating Upstream Parameters to Dissolution Behavior
- Case Study 4 – Understand Physical Properties to Improve Dissolution
- Conclusion
Executive Summary
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Investigating Tablet Properties and Understanding Design Space
Understanding the Correlation Between Drug Dissolution Behavior and Key Formulation Parameters: A Vertex Case Study Kyle Bui Analytical Development Vertex Pharmaceuticals April 28, 2008 Dissolution AAPS Meeting
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Investigation of an Atypical Observation of Harder Tablets Having a Faster Dissolution Rate Zane Arp, GlaxoSmithKline, AAPS November 2007
Investigating Tablet Properties and Understanding Design Space
Statistic particle distribution results during dissolution of tablets at different compression forceTablet dissolution profile by Fiber Optical UV at
different compression force
Low compression tablet
High compression tablet
CompressForce
c50sq wt
c90sq wt
5kN 207µm 371µm
15kN 176µm 315µm
Chord length µmTime (minutes)
In the Vertex example - a higher compression force results in larger granules and a slower dissolution rate
In the GSK example - a higher compression force results in a smaller granules and faster dissolution
Monitoring granule dimension during dissolution helps understandinconsistencies and enables formulators to target consistent dissolution profiles with each new formulations step
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Investigating Tablet Properties and Understanding Design Space
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Conclusion
FBRM® is used to understand the impact a formulation step has on tablet disintegration and dissolution mechanisms
FBRM® can identify the root cause of dissolution inconsistency leading to a better understood process
FBRM® can speed process development by providing immediate understanding that allows formulation scientists to make better decisions faster
This can save up to months of development time, target consistent final products, and ensure formulators have answers for regulatory questions
Optimization of High Shear Wet Granulation using FBRM® and PVM®
Zane Arp, PhDGlaxoSmithKline
Investigator – Process Analytical ChemistryPD-MOST-PUC
Benjamin Smith Mettler Toledo Market Manager
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Agenda
Introduction to high shear wet granulation
DOE Study: Acetaminophen granulation on 6 liter scale- DOE Outline- Ideal batch conditions and process upsets - Extreme process conditions- Varying wet massing time- Optimization and control with varying spray rate
Conclusions
Where do Particles Play a Role?
Fluid bedGranulator
Mill
Tablet press
API ExcipientsBinder
Blender
Why do we Granulate?
Objective is to produce larger, denser agglomerates from fine powders that improve downstream processing
- Improve handling- Improve product appearance- Enhance flow and mixing properties- Control of solubility and porosity- Increase bulk density and storage- Create of non-segregated blends of powder ingredients
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An Overview of Fine-Powder Granulation using a BinderGabriel I. Tardos, City College of New York
Factors Affecting Granule Growth
Binder concentration - Granule strength and tablet strength increase as binder concentration increases
Effects of raw material properties - Packing properties of the solids- Particle shape and surface morphology - Particle size distribution: The smaller the particle size of the raw material, the
more binder liquid required.
Process conditions- Wet massing/densification- High shear vs low shear mixer- Impeller rotation speed - Evaporation of the solvent (Temperature)- Contact angle of the binder liquid to the solids - Solubility of the particles in the binder liquid - Liquid addition: A narrow margin exists between the liquid required to obtain
granule growth and the amount that results in an over-wetted mass.
39Ensuring Better Control of Granulation
Rakesh P. Patel, PhD, and A.M. Suthar,
What is the Granulation Endpoint?
Endpoint can be defined by the formulator as a target particle size distribution, granule density, and rheology
- Wet Granulation: End-Point Determination and Scale-UpBy Michael Levin, Ph. D. “Granulation: End-Point Theory, Instrumentation, and Scale-Up,” AAPS 1999
- Ensuring Better Control of GranulationRakesh P. Patel, PhD, and A.M. Suthar, Gnpat University, India
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Effect of Varying Starting Distribution
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∆ (mean) ~100 µm during blend
Comparing trends highlights differences between the Batch 1 and Batch 2
Batch 1 exhibits a consistently larger granule dimension throughout the batch
The root cause for this appears to be a difference in the size of the raw materials
Effect of Varying Starting Distribution
Batch 1 product is coarser - likely due to larger starting particle distribution
Batch 2Sq Wt Mean = 317.45µm
Batch 1Sq Wt Mean = 476.11µm
Elements of Quality by Design
Process understanding- DOE
Risk management - Root cause analysis
Process analytical tools - NIR, FBRM, PVM, FTIR, UV-vis
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What Process Variables Affect Granulation Endpoint?
Final granule density and particle distribution predicted by: - Binder addition - Moisture addition- Chopper speed - Impeller speed- Spray position- Nozzle type- Spray flux- Product composition- Starting particle distribution
The following are variables based on the above criteria: - Batch time- Bowl type- Temperature
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Wet Granulation: End-Point Determination and Scale-UpMichael Levin, Ph. D. AAPS 1999
Choosing Identical Operating Conditions Does Not Always Lead to Batch to Batch Reproducibility
Three identical Placebo Batches?- Same formulation, same starting materials, same spray rate, same bowl,
same impeller speed, same probe location, same wet mixing time
Process Variability in granulation growth occurs during the wet mass
45Time (2 sec intervals)
Mea
n (s
quar
e w
eigh
t)
Sam
ple S
ampl
e
Batch to Batch Reproducibility at Endpoint?
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Time (2 sec intervals)
Mea
n (s
quar
e w
eigh
t)
Batch 4 EndBatch 4 End Batch 3 EndBatch 3 EndBatch 2 EndBatch 2 End
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Agenda
Introduction to high shear wet granulation
DOE Study: Acetaminophen granulation on 6 liter scale- DOE Outline- Ideal batch conditions and process upsets - Extreme process conditions- Varying wet massing time- Optimization and control with varying spray rate
Conclusions
DOE Characterization and Control of API Granulation
6 liter bowl
12 batch DOE- Vary moisture spray 20%, 25%, 30%- Vary impellor rpm: Low, high- Vary wet mass time 1 min, 2min, 4min
In-Process Understanding
FBRM® associates particle system dynamics with processing conditions in real time
Faster understanding and optimization
No sampling required.
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Consistent Measurements
The FBRM® window stayed clean allowing the system to track particle agglomeration, compaction, and breakage even in the most cohesive API particle conditions.
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FBRM® Probe Installation
Probe location - Near wall, deep install, 0.5-1” above bottom blade
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Formulation:Material Weight (g)
Acetaminophen 625
PVP 20
AC-Di-Sol 20
Lactose Monohydrate 165
Avicel PH-101 135
Total Mass 965
Material Weight (%)
Water 20, 25, 30%
DOE Experimental Setup
DOE # Batch # Water addition (%)
Actual water addition
amount (g)
Addition rate (mg/min)
Wet massing
time (min)
Impeller speed (RPM)
1 15 25 190 90 4 271
2 16 20 190 90 1 542
3 17 20 190 90 4 542
4 6 30 288 90 4 271
5 7 25 240 90 2.5 271
6 8 30 288 90 4 542
7 9 25 240 90 2.5 542
8 10 30 288 90 4 271
9 11 25 240 90 2.5 271
10 12 30 289 90 1 542
11 13 25 243 90 2.5 542
12 14 20 193 90 1 271
13 21 25 246 125 2 542
14 22 25 255 125 2 542
15 23 25 242 25 1 542
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Agenda
Introduction to high shear wet granulation
DOE Study: Acetaminophen granulation on 6 liter scale- DOE Outline- Extreme process conditions- Varying wet massing time- Optimization and control with varying spray rate
Acetaminophen Batch Scale-up and Control in 75 liter vessel
Conclusions
Endpoints from Three Extremes in Water Addition Result in Drastically Different Endpoint Distributions
FBRM® distributions provide immediate target endpoint detection, ensuring consistent downstream particle flow, tableting and dissolution
5422.52575424306
5424203Impeller speed (RPM)Wet massing time (min)Water addition (%)DOE #Color
Endpoints from Three Extremes in Water Addition Result in Drastically Different Endpoint Distributions
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DOE #6
DOE #7
DOE #3
FBRM® distributions provide immediate target endpoint detection, ensuring consistent downstream particle flow, tableting and dissolution
Statistic DOE #3 DOE #7 DOE #6
Mean Lth Wt 120µm 187µm 336µm
DOE #3 Under Granulated
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DOE #7 Ideal
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DOE #6 Over Granulated
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Conclusions
Critical Process ParametersFBRM® helped immediately identify the critical process parameters:- % moisture addition- Wet massing time- Moisture addition rate
Control Batch to Batch Repeatability FBRM® trends were used to troubleshoot unexpected process changes. FBRM® can be used to minimize a-typical batches and improve batch to batch repeatability
Identify Batch EndpointFBRM® distributions provided immediate target endpoint detection, ensuring consistent downstream particle flow, tableting and dissolution
Ensure Consistent Measurements The FBRM® window stayed clean allowing the system to track particle agglomeration, compaction, and breakage even in the most cohesive API particle conditions.
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Acknowledgements/References
Moheb Nasr, CDER, FDA- http://www.fda.gov/cder/Offices/ONDQA/presentations/051024-MMN-Dissolution.pdf
Jonas Johansson, AstraZeneca, Sweden- http://www.aapspharmaceutica.com/meetings/files/63/Johansson.pdf
Kyle Bui Vertex Pharmaceuticals- http://www.aapspharmaceutica.com/meetings/files/126/bui.pdf
Zane Arp, GlaxoSmithKline, AAPS, November 2007
Michael Cheng, Amgen, AAPS, November 2007
Jeff Seely, Distek
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