Transcript Case Studies in QbD with DOE From Pharmaceutical Tech

Case Studies in Quality by
Design with Design of
Experiments From
Pharmaceutical Technology
Lynn Torbeck
19 August 2008
19 August 2008
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Overview
A little, very little, history
3 types of controlled experiments
Key literature and dates
Today’s driving force behind QbD
“Show me an example in my area of
interest”
Case Studies from Pharm Tech
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A Short Bit of History
Sir Ronald A. Fisher
Born 1890, England
Died 1962, Australia
Graduated college in 1913, math,
genetics
1919 joined Rothamsted Experimental
Station in Harpenden, England
The right person in the right place.
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Three Controlled Experiments
John S. Mill, System of Logic, 1843
1. Success / Failure



One run, no factors varied, one outcome, yes/no
Easy to design, easy to analyze
Lack of comparison, inefficient
2. OFAT, One-Factor-at-a-Time




We all learned this in school
Several runs, one factor varied, two outcomes
Easy to Design, has comparison of outcomes
Can’t find interactions and is inefficient
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Fisher’s Experiments
Multiple runs, multiple factors varied
Multiple outcomes
Will find interactions
Is much more efficient
Comparison of outcomes
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Key Literature
1926, “The Arrangements of Field
Experiments.” Journal of the Ministry of
Agriculture of Great Britain. Fisher.
1935, The Design of Experiments,
Oliver & Boyd, London. Fisher.
1951, “On the Experimental Attainment
of Optimum Conditions,” Box and
Wilson. The original source for QbD !
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Today’s Driving Force
FDA / PAT guidance
ICH Q8 – Quality by Design
ICH Q8 _ Annex with DOE example
The freedom of Design Space
Ability to change within Design Space
Economics and cost savings
Product / Process Knowledge
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State of the Topic
While there is more to Quality by
Design than DOE, it seems to be the
part that most people have the most
trouble with.
Chemometrics is many times more
complicated than DOE but yet it seems
to be more readily accepted than DOE.
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Show Me an Example
Many people have taken a DOE class at
some time, but still have difficulty in
getting started.
The most common request is for
examples in specific areas.
Examples here show that it is not all
that difficult to get started.
QbD was being done before ICH Q8
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Six Steps to Designing
1.
2.
3.
4.
5.
6.
Do your homework
Define the measured responses (CQA)
Brainstorm factors (CPP)
Select 2-7 factors to be treatments
Select levels or values for treatments
Select a design
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A Short List of Designs
Number of Runs
4
8
22
23
23-1III
Number
of
2
3
Factors
4
24-1IV
5
25-2III
6
7
8
9
10
11
8
9
3*3, 32
12
16
PB9
24
PB8
PB9
25-1V
26-3III
PB8
PB9
26-2IV
27-4III
PB8
PB9
27-3IV
PB9
28-4IV
PB12
PB12
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PB12
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Pharm Tech Yearbook, 1999
“Functionality Testing of a Co-processed
Diluent Containing Lactose and
Microcrystalline Cellulose”
Gohel, M., et all
Pre-formulation development of
excipients
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Objective
“The objective of the present study was
to prepare the directly compressible
adjuvant by using a simpler process
that could be adopted by any
pharmaceutical company.
Product is a tablet
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Treatments
A: Ratio of lactose to MCC

75:25, 85:15
Binding Agent

Dextrin, HPMC
% binding agent

1.0%, 1.5%
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Held Constant
Stirring speed at 35 rpm
Stirring time at 90 minutes
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Agglomerate Responses
Bulk Density, Tapped Density
Angle of Repose, Flow Rate
Hausner ratio
Carr’s Index
Friability Index
Moisture uptake
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Statistical Design
Three treatments
Each at two levels
Eight sets of conditions or runs
A 23 full factorial design
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Results
This is a complicated set of data with
many two factor interactions, but it can
be understood by looking at a
geometric presentation of the factors
and the responses for flow rate.
Ratio is on the horizontal, A, axis
Agent is on the vertical, B, axis
Percent is on the third, C, axis
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Agent
B
HPMC
16.00
16.00
19.00
14.00
Dextrin
14.80
18.00
75/25%
Ratio
A
85/25%
1.0%
15.00
C
1.5%
14.60
Percent
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Observations for Flow Rate
1. Within these bounds, flow is 14.0 to
19.0 g/s
2. Slowest is 85/15, HPMC, 1.5%.
3. Fastest is 75/25, HPMC, 1.5%
4. Fast is 85/15, Dextrin, 1.0%
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Pharm Tech, November 1999
This is a related example.
“An Investigation of the DirectCompression Characteristics of Coprocessed Lactose-Microcrystalline
Cellulose Using Statistical Design.”
Gohel, M., and Jogami, P.
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Pharm Tech, June, 1993
A bottle packaging example.
“The Effect of Rayon Coiler on the
Dissolution of Hard-Shell Gelatin
Capsules.
Hartauer, K.; Bucko, J.; Cooke, G;
Mayer, R.; Schwier, J. and Sullivan, G.
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BioPharm, October 1997
“Demonstrating Process Robustness for
Chromatographic Purification of a
Recombinant Protein.”
Kelly, B.; Jennings, P.; Wright, R. and
Briasco, C.
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Objective
“Control is achieved by setting
operating ranges for manipulated
process variables. Those ranges should
ensure that a process does not fail
within the multidimensional operating
space defined by those limits.”
That is, the Design Space !
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Treatments
1.
2.
3.
4.
5.
6.
7.
Load Mass
Load Conductivity
% Cleavage
Wash pH
Wash volume
Elution pH
Elution conductivity
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2.4 – 15.5
2.5 – 4.2
63 – 75
9.4 – 9.6
9.7 – 11.6
9.4 – 9.6
8.6 – 14.4
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Responses
1.
2.
3.
4.
5.
Recovery %
Purity %
rhIL-11 mass
Product pool volume
Elution pool concentration
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Statistical Design
Wash pH / Wash volume confounded
Elution pH / Elution conductivity
confounded
1. Five factors each at two levels
2. 16 runs will still find the two factor
interactions
3. Design is a 25-1 fractional factorial
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A:Elution pH B:Conductivity C:Cleavage D:Load Mass E:Wash pH Recovery % Purity %
-1
-1
-1
-1
1
112.6
96.3
1
-1
-1
-1
-1
90.7
96.9
-1
1
-1
-1
-1
104.9
97.1
1
1
-1
-1
1
72.8
97.3
-1
-1
1
-1
-1
99.6
96.1
1
-1
1
-1
1
84.2
97.1
-1
1
1
-1
1
98.4
97.3
1
1
1
-1
-1
104.2
97.8
-1
-1
-1
1
-1
104.3
91.8
1
-1
-1
1
1
79.0
94.9
-1
1
-1
1
1
94.8
96.6
1
1
-1
1
-1
93.7
96.0
-1
-1
1
1
1
95.5
94.4
1
-1
1
1
-1
88.5
93.9
-1
1
1
1
-1
78.7
96.5
1
1
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1
1
58.7 29 98.4
Design Space
Independent
Factor
Space
?
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Dependent
Response
Space
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Conceptual Design Space
Operation
Space
Opt
Region of Interest
Region of operability
Uncertain space
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Statistical Design Space
“The mathematically and statistically
defined combination of Factor Space
and Response Space that results in a
system, product or process that
consistently meets its quality
characteristics, SSQuIP, with a high
degree of assurance.” LDT
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Analysis
Analysis is done by fitting a
mathematical model to the factors
(CPP) and the responses (CQA) that
includes the factor main effects and the
significant two factor interactions
The model is then used to find contour
plots for recovery and purity.
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Recovery
Design-Expert® Software
1.00
Recovery
112.6
58.7
0.50
Actual Factors
C: Cleavage = -1.00
D: Load Mass = 0.00
E: Wash pH = 0.00
B: Conductivity
X1 = A: Elution pH
X2 = B: Conductivity
99.8417
95.4875
91.1333
86.7792
0.00
104.196
-0.50
-1.00
-1.00
-0.50
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0.00
A: Elution pH
0.50
1.00
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Purity
Design-Expert® Software
1.00
Purity
98.4
96.6333
91.8
0.50
X1 = A: Elution pH
X2 = B: Conductivity
B: Conductivity
Actual Factors
C: Cleavage = -1.00
D: Load Mass = 0.00
E: Wash pH = 0.00
96.1792
0.00
95.725
-0.50
95.2708
94.8167
-1.00
-1.00
-0.50
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0.00
A: Elution pH
0.50
1.00
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Overlay Plot
Design-Expert® Software
1.00
Overlay Plot
Recovery
Purity
X1 = A: Elution pH
X2 = B: Conductivity
Actual Factors
C: Cleavage = -1.00
D: Load Mass = 0.00
E: Wash pH = 0.00
B : C onductivity
0.50
Recovery: 100
Recovery: 90
0.00
-0.50
-1.00
-1.00
-0.50
0.00
0.50
1.00
A: Elution pH
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Pharm Tech, February 1999
“Blow-Fill-Seal Technology: Part II,
Design Optimization of a Particulate
Control System.”
Price, J.
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Objectives
1. Optimize the particulate control
system
2. Find cause and effect relationships
3. Alter the system settings to improve
performance
4. Find interactions between factors
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Treatments
1.
2.
3.
4.
5.
6.
HEPA flow rate %
Damper % open
Chimney air ft/min
HEPA height in
Isolation plate
Knife cut
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20 50 80
30 55 80
300 550 800
0 0.375
Slotted – Hole
Double Single
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Response
Particulate level.
Three measurements at each of the 24
conditions
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Statistical Design
Six factors


Three at two levels
Three at three levels
16 combinations
8 center points
Design is a 26-2 fractional factorial
Design is resolution IV
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Analysis
Analysis of Variance, ANOVA, was used.
15 effects were included
5 were statistically significant





Damper
HEPA height
Knife cur
Isolation plate
HEPA flow * HEPA height
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OR {damper*knife cut}
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Conclusions
“The study met the design objective of
minimizing the particulate levels while
the particulate control system operated
in the dynamic state. … a more
thorough understanding of the cause
and effect relationships between the
critical input factors and the particulate
levels was obtained using the DOE.”
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Pharm Tech, Analytical
Validation, 1999
Robustness Testing of an HPLC Method
Using Experimental Design.”
Peters, P. and Paino, T.
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Objective
“This article describes an experimental
design that challenged an analytical
method that assays two components in
a solid dosage drug product.”
Confirm the robustness of an HPLC
method.
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Treatments
HPLC system
HPLC column
Wavelength


A
B
Flow rate
A, B
Y, X
270, 290
215, 235
0.7, 1.3
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Treatments
Injection volume
Column temp
Mobile phase


TFA
MeCN
10, 30
Ambient, 30
85, 75
15, 25
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Responses
1.
2.
3.
4.
Resolution of component A and B
Theoretical plates for A and B
Tailing factor for A and B
%RSD of the peaks for A and B
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Statistical Design
7 factors each at two levels
Wavelength A and B are confounded
Mobile phase TFA and MeCN are
confounded
8 runs done in triplicate for 24 total
Design is a 27-4 fractional factorial
Design is resolution III.
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Analysis and Results
Visual inspection of an overlay of the 8
chromatograms shows that the method
is robust within the tolerance limits of
the parameters tested. They have
acceptable resolution and peak shape.
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Compare Chromatograms
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Pharm Tech, May 1998
“A Systematic Formulation Optimization
Process for a Generic Pharmaceutical
Tablet.”
Hwang, R.; Gemoules, M; Ramlose, D.
and Thomasson, C.
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Objective
“ … optimizing an immediate release
tablet formulation for a generic
pharmaceutical product.”
Develop a generic tablet with a
disintegration time of 6-12 minutes, 5
minute dissolution of 40-60% and 45
minute dissolution of greater than 90%.
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Treatments
API particle size
API %
Lactose MCC ratio
MCC particle size
MCC density
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small large
5% 10%
1:3 3:1
small large
low high
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Treatments
Disintegrant
Disintegrant %
Talc
Mag Sterate
cornstarch, glycolate
1% 5%
0
5%
0.5% 1%
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Responses
Blend homogeneity
Compression force %RSD
Ejection force
Tablet weight %RSD
Tablet hardness
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Responses
Tablet
Tablet
Tablet
Tablet
friability
disintegration time
dissolution at 5 minutes
dissolution at 45 minutes
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Statistical Design
9 factors each at two levels
16 runs
Design is a 29-5 fractional factorial
Resolution III
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The best formulation:
API
Fast-Flo lactose
Avicel PH-302
Talc
Mag Stearate
7.14%
60.74%
30.37%
1%
0.75%
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Conclusion
“The formulation was successfully
scaled up to a 120 kg batch size and
the manufacturability and product
quality were confirmed.”
“This study has demonstrated the
efficiency and effectiveness of using a
systematic formulation optimization
process … “
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Pharm Tech, March 1994
“Evaluation of a Cartridge and a Bag
Filer System in Fluid-Bed Drying.
Bolyard, K. and McCurdy, V.
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Pharm Tech Europe, April 2000
“Response Surface Methodology Applied
to Fluid Bed Granulation.”
Wehrle, P. et all
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Pharm Tech
March 1992 and May 1992
“A Compaction Study of Directly
Compressible Vitamin Preparations for
the Development of a Chewable Tablet,
Parts I and II.
Konkel, P. and Mielck, B.
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Pharm Tech, March 1994
“Computer Assisted Experimental
Design in Pharmaceutical Formulation.”
Dobberstein, R. et all.
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Pharm Tech, April 1998
“A Unique Application of Extrusion for
the Preparation of Water Soluble
Tablets.”
Murphy, M. and Hollenbeck, R.
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Pharm Tech, June 2000
“Artificial Neural Network and Simplex
Optimization for Mixing of Aqueous
Coated Beads to Obtain Controlled
Release Formulations.”
Vaithiyalingam, S. et all.
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Summary
Looked at 13 Case studies
Shown 3 types of analysis
Shown several areas of application
Illustrated how to get started
Shown that Q8 QbD has a precedent
DOE has been used for a long time
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Acknowledgements
The University of Adelaide Library is the
owner of the image of Sir R. A. Fisher.
Pharmaceutical Technology holds the
copyright for the journal articles used in
this presentation.
Opinions in this presentation are that of
Lynn Torbeck alone.
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