Confidential
Quality by Design (QbD) for the Continuous
Manufacturing of Solid Oral Dosage Forms
David Emiabata Smith, 16th September, 2014
©2014 Vertex Pharmaceuticals Incorporated 1
Vertex Continuous
Manufacturing Approach
©2013 Vertex Pharmaceuticals Incorporated 3
Individual unit operations allows manufacture in a “discontinuous” mode
• Wet granulation
• Utilized for process
development, clinical, and formal stability
ConsiGma-25 unit allows for continuous batch manufacture
• Wet granulation, fluidized bed drying & compression
• Utilized for process development, clinical, and formal stability
Development & Launch Rig allows for fully continuous manufacture
• Raw material blending to tablet film coating
• PAT equipped: process monitoring /control & RTRT
• Utilized for process development, clinical, and formal stability
Vertex’s Path to Continuous Manufacturing
4 ©2012 Vertex Pharmaceuticals Incorporated .
Powder In
Sep 16th
Sep 16th Coated Tablets Out
Vertex’s Continuous
Manufacturing Rig
Much Smaller Footprint
• Smaller scale equipment
• All unit ops in one room
Continuous Monitoring, Control & RTRT
©2014 Vertex Pharmaceuticals Incorporated 4 Confidential
Vertex Boston
©2013 Vertex Pharmaceuticals Incorporated 5
Vertex Fan Pier Annex
Drug Product Facility
Boston, MA
©2014 Vertex Pharmaceuticals Incorporated 6
Early finalization of formulation on commercial scale equipment
• Commercial product equivalent to product used for clinical development
“Data rich” commercial design space can be explored with limited API as part of a Quality by Design (QbD) approach
Impact of upstream variables on downstream process and final product quality easier to assess
Highly consistent product quality is produced with continuous monitoring and control
CM facilitates streamlined QbD development and NDA submission
Continuous Manufacturing and PAT are Ideally Suited
for the CMC Development of Breakthrough Therapies
Confidential
Vertex Approach to
Quality by Design (QbD)
Vertex Approach to Quality by Design
8
1. Define Quality Target
Product Profile
2. Identify Potential CQAs
3. Perform Initial Process and
Material Risk Assessment
4. Determine Criticality
5. Establish Design Space and
Control Strategy
6. Perform Process Risk
Assessment
7. Continual Improvement
©2014 Vertex Pharmaceuticals Incorporated Confidential
• Initial risk assessment
– Risk based on SME evaluation and existing
data on probability of occurrence
– Determines which process parameters and
material attributes need to be studied
• Determine criticality
– Set desired manufacturing range and
thresholds for criticality
– Design and execute experiments
– Develop process models and assess
criticality
• Establish Design Space & Control Strategy
– Define Design Space Limits (DSL)
– Material attributes and CPP’s
– Define IPCs
– Finalize specifications
Criticality Determined using Pre-defined Criteria
9
• Desired Manufacturing Range (DMR, ∆X)
– Commercially relevant range of a process
parameter
• Threshold for Criticality
– The minimum change in a CQA considered to be
a significant impact
– Determined by a team of experts
– Generally set as a small fraction of the CQA’s
acceptance range
• Experiments and Process Models
– Multivariate experiments across the DMR
– Statistical analysis of main effects and interactions
result in process models
• Criticality Analysis
– Determine effect on CQA (∆Y) across the DMR
– If ∆Y exceeds the Threshold, the process
parameter is critical
Select Desired Manufacturing range and Thresholds for
Determining Criticality
Design Experiments
Execute Experiments
Finalize Process Models
Criticality Analysis
©2014 Vertex Pharmaceuticals Incorporated Confidential
Example of Criticality Assessment
• IF no statistically significant effect Non-Critical
• IF significant and ΔY < Threshold Non-Critical
• IF significant and ΔY ≥ Threshold Critical
©2014 Vertex Pharmaceuticals Incorporated 10
P ro c e s s P a ra m e te r
CQ
A
2 0 0 3 0 0 4 0 0 5 0 0
8 5
9 0
9 5
D M R
Y
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Approach to Setting Design Space Limits
• The DMR becomes the DSL if a process parameter does not cause a
CQA to fail across the DMR
– DSL is reduced if the parameter can cause failure of a CQA
– Equipment limitations can also limit the DSL
• For materials, if variability of an attribute within the specifications (DMR)
causes a CQA to fail, appropriate specifications will be put in place
©2014 Vertex Pharmaceuticals Incorporated 11
P ro c e s s P a ra m e te r
CQ
A
2 0 0 3 0 0 4 0 0 5 0 0
8 5
9 0
9 5
s p e c if ic a t io n lim it
D M R
D S L = D M R
P ro c e s s P a ra m e te r
CQ
A
2 0 0 3 0 0 4 0 0 5 0 0
8 5
9 0
9 5
s p e c if ic a t io n lim it
D M R
D S L < D M R
D S L
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Example of High Level Approach to QbD Experiments
• Designed experiments with individual unit operations
– All processes, except drying and milling
©2014 Vertex Pharmaceuticals Incorporated 12 Confidential
• Designed experiments with grouped unit operations
– Granulation, drying, and milling
• Process models developed from all unit operation
experiments to assess criticality
• Combined predictive models developed to confirm findings
with continuous experiments across DMR
• Next slides show example of unit op screening
experiments, grouped unit ops experiment, and outcome
of confirmation experiments
• Fully continuous experiments using entire DLR
– Component feeding through film coated tablets
Blending
Example: Screening Study for Wet Granulation
• Initial risk assessment wet granulation
– Potential impact on CQAs of appearance, degradation products, dissolution, content uniformity, and physical form
• 20 experiment design including material attributes and process parameters on commercial scale equipment
©2014 Vertex Pharmaceuticals Incorporated 13
Material Attributes
API A d(0.5) (µm)
API B SDD bulk density (g/cc)
Formulation (1/2)
Process Parameters
Water added during TSWG (%)
Degree of fill (%)
Line rate (kg/hr)
Confidential
Formulation 1
Formulation 2
Water
Added
API B BD
API A d(0.5)
• Summary of results – No impact on CQAs except:
– API A D50 affects milled granule fines, thereby impacting dissolution
– API B SDD bulk density impacts dissolution
Example: Experimental Design Grouped Unit Ops
©2014 Vertex Pharmaceuticals Incorporated 14
• Design includes material attributes, granulation, FB drying and milling
• Initial risk assessment on combined processes
– Potential impact on CQAs of appearance, assay, degradation products, dissolution, content uniformity, physical form, and water content
• 20 experiments on commercial scale equipment
– Separate unit ops to allow sampling between processes
– Incoming material attributes defined as “granule properties”
Confidential
small API A d(0.5)
high API B SDD BD
large API A d(0.5)
low API B SDD BD
Formulation 1
Formulation 2
Example: Experimental Design Grouped Unit Ops
Material Attributes
Granule properties
Formulation (1/2)
Process Parameters
Water added during TSWG (%)
Line rate (kg/hr)
Fluid bed dryer inlet temperature (ºC)
Fluid bed dryer inlet air flow (m3/hr)
Fluid bed dryer fill time (min)
Mill speed (rpm)
©2014 Vertex Pharmaceuticals Incorporated 15
• Summary of Results
– No impact on CQA’s except:
– Drying parameters significantly affect CQA
of water content
– API A dissolution affected by granule
properties, water added during granulation,
and mill speed
– API B dissolution affected by granule
properties, water added during granulation,
& dryer inlet temperature and airflow
Confidential
Drying Time Constrained due to Equipment Limitations
©2014 Vertex Pharmaceuticals Incorporated 16
• Upper drying time limit dependent on fill time of FBD
– Cell has to be empty before next product mass can be charged
– For “short” FB dryer fill time, the max drying time is 16 minutes
– For “long” FB dryer fill time, the max drying time is 22 minutes
• Drying time was regressed against variables studied
– Wet product mass has largest impact on drying time
• Combination of fill time, water added, and line rate
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Wet Mass Wet Mass
API B Dissolution Affected by Material Attributes and
Process Parameters
©2014 Vertex Pharmaceuticals Incorporated 17
• Largest effect from API B SDD bulk density
• Decreased dissolution with water added during granulation
• Increased dissolution with mill speed
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API B Dissolution
Predicted
AP
I B
Granule Property (L)
Granule Property (H)
Midpoint
API A Dissolution Affected by Material Attributes and
Process Parameters
©2014 Vertex Pharmaceuticals Incorporated 18
• Decreased dissolution with water added during granulation
• Increasing dissolution with API A D50
– Consistent with screening study
• Drying parameters showed impact on dissolution when water added
during granulation was high
Confidential
API A Dissolution
Predicted
Granule Property (L)
Granule Property (H)
Midpoint
AP
I A
Confirmation Experiments Spanned DMR
Formula
tion
Granule
Property
Blender
1 Speed
Water
Added
Line
Rate
Inlet air
flow
Inlet air
temp
FBD
Fill time
Mill
speed
Blender
2 Speed
Press
speed
Comp
Force
1 Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
2 Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
2 + + - + + - - + + + +
1 + + - + + - - + + + +
1 - - + - - + + - - - -
2 - - + - - + + - - - -
©2014 Vertex Pharmaceuticals Incorporated 19
• Six development batches were processed continuously on the DLR
• Significant parameters from the unit ops studies were varied
– See table below
• Core tablet samples were tested and projected on the combined unit ops
dissolution models
Confidential
Unit Ops Models Representative for Continuous Runs
©2014 Vertex Pharmaceuticals Incorporated 20
A c tu a l A P I B D is s o lu tio n (% )
Pre
dic
ted
AP
I B
Dis
so
luti
on
(%
)
8 0 8 5 9 0 9 5 1 0 0
8 0
8 5
9 0
9 5
1 0 0
D L R (+ /- 9 5 % C I)
U n ity L in e
Actual API A Dissolution (%)
Pre
dic
ted
AP
I A
Dis
so
luti
on
(%
)
80 85 90 95 10080
85
90
95
100
DLR (+/- 95% CI)
Unity Line
API B API A
Process models appropriate to assess criticality and define DSL
Confidential
• Process models generated from combined data sets
• Predicted dissolution values for API A and API B
• Results show good comparison between unit ops and continuous runs
Process Control Strategy (Summary)
©2014 Vertex Pharmaceuticals Incorporated 21 Confidential
IPC:
− Individual Components Feed Rate
Parameters:
− Line Rate
− Binder Feed Rate
Parameters:
− Line Rate;
− Solution Pump Rate
− Inlet Air Temp. & Flow Rate
− Dryer Fill Time
− Drying Time
IPC:
− Product Temp.
− Moisture Content (NIR)
Parameters:
− Line Rate
− Blender speed
Parameters:
− Mill Speed
IPC:
− Granule Potency (NIR)
Parameters:
− Granule Feed Rate
IPC:
− Individual Components Feed Rate
− Blend Potency (NIR)
Parameters:
− Compression Force
− Press Speed
IPC:
− Weight
− Thickness
− Hardness
Parameters:
− Pan Load
− Spray Rate & Spray Time
− Inlet Air Flow Rate
− Polish Time
Blending (IG
Phase)
Granulation
Drying
Blending (EG
Phase)
Core
Compression
Film-Coating
Milling
Conclusions
• Vertex Approach to CM Development
– CM can provide opportunity for accelerated development - Ideal for
Breakthrough Therapies
– Sequential unit ops and fully continuous experiments can provide
opportunities for streamlined QbD development
– Data rich design space can be developed using commercial scale
equipment with limited API
• Vertex Approach to QbD
– Risk assessment and prior knowledge determines studies needed
– Defining DMR and criticality thresholds up front, before
experiments, eliminates uncertainty in identifying CPP’s
– Process Models (from DoE’s) were used to assess criticality
– Design Space Limits (DSL) were determined by utilizing DoE’s and
resulting process models (across the DMR)
©2014 Vertex Pharmaceuticals Incorporated 22 Confidential
Confidential
Acknowledgements
• Team at Vertex
– Pharmaceutical Development
– Technical Operations
– Supply Chain Management
– Quality
– CMC Regulatory
– GIS
– Facilities
• Equipment manufacturers
• Our CMOs, suppliers, and research collaborators
• FDA, EMA, MHRA
©2014 Vertex Pharmaceuticals Incorporated 23