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Time*Temp Interaction Plot
Time*Temp Interaction Plot
Time* Moisture Interaction Plot
Time* Moisture Interaction Plot
Temp*Moisture Interaction Plot
Temp*Moisture Interaction Plot
Time*Temp Contour Plot
Time*Temp Contour Plot
Time*Moisture Contour Plot
Time*Moisture Contour Plot
Temp*Moisture Contour Plot
Temp*Moisture Contour Plot
Time*Temp Surface
Time*Temp Surface
Time*Moisture Surface
Time*Moisture Surface
Temp*Moisture Surface
Temp*Moisture Surface
Design Space
Design Space
Design Space
Design Space
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How to Define Design Space

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1How to Define Design Space. Lynn 23Mechanistic Models: A physical or chemical
Torbeck. equation.
2Overview. Why is a definition 24Model Prediction. Equations for
important? Definitions of Design Space. critical factors and the mechanistic
Deconstructing Q8 Definition. Basic connection with the critical responses
science, Cause and Effect SIPOC Process allow for the prediction of the quality
Analysis Three Levels of Application. Case characteristics in quantitative terms.
Study with Example. Multidimensional in factors and responses.
3Why is this Important? ICH Q8 is in 25S.I.P.O.C. Model.
its final version. Design Space is defined 26Macro View. Product Process Design.
in Q8. Many presenters are using the term. The Whole New Product Development Cycle.
All are repeating the same definition. Unknown. Controllable Factors. Controlled
Many presenters don’t understand the Responses. Uncontrolled Responses.
statistical implications of the issue. Concomitant. Uncontrollable Factors.
Need for a detailed ‘Operational 27Mid-Level View. Pre-formulation /
Definition’. formulation studies Pharmacology /
4Regulatory Impact. “Design space is toxicology Animal studies Product
proposed by the applicant and is subject development Process development Clinical
to regulatory assessment and approval.” trials Validation and process improvement.
“Working within the design space is not 28Micro Level View: Design Space.
considered a change.” “Movement out of the Independent Factor Space. Dependent
design space is considered to be a change Response space.
and would normally initiate a regulatory 29Existing Products. Design Space can be
post approval change process.” This is a inferred by using existing information and
big deal, it needs to be done correctly ! historical data . Retrospective process
The economic impact of this can be huge. capability studies. Annual Product Review
5Potential Benefits. Real process analysis Comparison of historical data to
understanding and knowledge, not just specs Risk management and assessment, Q9.
tables of raw data. Reduced rejects, 30Factor Space. ASTM E1325-2002 “That
deviations, discrepancies, lost time, portion of the experiment space restricted
scrap and rework. Fewer 483 citations and to the range of levels of the factors to
warning letters. Fewer investigations and be studied in the experiment …” AKA,
CAPA. Freedom to operate with design “Design Regions” The Cambridge Dictionary
space. of Statistics. B. S. Everitt, Cambridge
6ICH Q8 Definition. “The University Press.
multidimensional combination and 31Quick Dry Example. Five batches of
interaction of input variables and process product had been lost to an impurity
parameters that have been demonstrated to exceeding the criteria The criteria for
provide assurance of quality.” This is not impurity 1 was NMT 1.0% Four factors
universally understood by all parties studied. Four responses.
involved. We need to harmonize several 32Quick Dry Example. FACTOR SPACE Drying
viewpoints, statistical, scientific, time 3-9 mins Drying Temperature 40-100
engineering and regulatory. Excipients Moisture 1.2-5 % %Solvent 1-14
7Deconstructing the Definition. Need to %. RESPONSE SPACE Impurity-1 % Impurity-2
deconstruct the definition to get to a day % Intact drug % Final moisture %.
to day working Operational Definition that 33Factor Space.
can be implemented. Need enough detail to 34Design Space. f(x)=? Independent
write a Standard Operating Procedure or Factor Space. Dependent Response space.
SOP. Need to see an example of what it Process understanding is cause and effect
looks like. quantitated. We find a mathematical and
8Multidimensional. Also called statistical formula that describes the
multivariable or multivariate More than relationship between factor space and
one variable at a time is considered. The response space.
practice of holding the world constant 352 Factor Interaction Effects to
while only considering Consider. Time * Temperature Time *
one-factor-at-a-time has been shown to be Moisture Time * Solvent Temperature *
grossly inefficient and ineffective. Moisture Temperature * Solvent Moisture *
9Interaction. Defined in the PAT Solvent.
guidance “Interactions essentially are the 36Time*Temp Interaction Plot.
inability of one factor to produce the 37Time* Moisture Interaction Plot.
same effect on the response at different 38Temp*Moisture Interaction Plot.
levels of another factor.” Interactions 39Time*Temp Contour Plot. Temp. Time.
are the joint action of two or more 40Time*Moisture Contour Plot. Moisture.
factors working together. Time.
10Example Interaction. 41Temp*Moisture Contour Plot. Moisture.
11“Input” Variables. Input Variables: Temp.
The “cause” Independent variable Factor 42Time*Temp Surface.
Output Variables The “effect” Dependent 43Time*Moisture Surface.
variable Responses. 44Temp*Moisture Surface.
12Assurance of Quality. Assurance is a 45Quick Dry Example. FACTOR SPACE Drying
high probability of meeting: Safety time 3-9 mins Drying Temperature 40-100
Strength Quality Identity Purity For all Excipients Moisture 1.2-5 % %Solvent 1-14
measured quality characteristics. %. RESPONSE SPACE Impurity-1 % Impurity-2
13Cause Effect. ? Basic Science. % Intact drug % Final moisture %.
14Critical Cause and Effect. Multiple 46Conclusions. FACTOR SPACE Solvent, no
Causes. Effects. Dependent. Independent. effect Time, decrease Temp, decrease
Responses. Factors. Moisture, decrease. RESPONSE SPACE
15Design Space. ? Dependent Response Impurity 1 Less than 1% R2 = 0.95.
Space. Independent Factor Space. 47f(Xi) Design Space. Impurity = +0.6079
16Design Space. FACTOR SPACE N dimension +Time * -0.0057 +Temperature * -0.0058
X’s X1 X2 X3 X4 X5 XN. RESPONSE SPACE M +Moisture * +0.1994 +Time*Temp * +0.00061
dimension Y’s Y1 Y2 Y3 Y4 Y5 YM. +Time*Moist * -0.29386 +Temp*Moist *
17Factor Space. “Potential Space” Areas -0.00502 +T*T*M * +0.00713.
that could be investigated “Uncertain 48Goal. Find a set of levels for Time,
Space” Insufficient data for a decision. Temperature, and Moisture that will
“Unacceptable Space” Factors and ranges predict impurity of less than 1 percent.
have been shown to not provide assurance (Solvent doesn’t matter.) The combination
of SSQuIP. “Acceptable Space” Data to of levels is the design space for impurity
demonstrate assurance of SSQuIP. 1.
“Production Space” Factors and ranges that 49Predictive Equation.
are selected for routine use. 50Predictive Equation.
18Response Space. “Potential space” or 51Design Space.
“Region of Interest” “Uncertain Space”, 52Design Space.
unknown responses “Unacceptable Space” 53Multidimensional Specifications.
unacceptable responses “Region of Specifications should not be set one
Operability,” acceptable responses factor at a time. We need to consider all
“Production Space” for manufacturing responses together. We need to do the same
Optimal Conditions or Control Space. analysis for impurity 2, intact drug and
19Conceptual Design Space. Region of final moisture and then overlay the four
operability. Uncertain space. Design solutions to find the design space that
Space. Opt. Region of Interest. will meet all of the criteria at the same
20Tablet Process Example. Filler Lactose time.
Mannitol Lubricant Steraric Acid Mag 54Scale-Up. Scale-up may not be linear
Stearate Disintegrant Maze Starch Assume that the basic equations will apply
Microcrystalline Cell Binder PVP Gelatine. Assume the design space will be somewhat
Intact drug % Content uniformity robust and rugged. Need to do confirmation
Impurities Moisture Disintegration experiments to confirm assumptions. Or
Dissolution Weight Hardness Friability reestablish the design space.
Stability. 55Design Space Conclusions. ICH Q8 and
21Chemical Process Example. Catalyst the FDA are asking for designed
10-15 lbs Temperature 220-240 degrees experiments and predictive equations for
Pressure 50-80 lbs Concentration 10-12%. each aspect of a new product. Descriptions
Yield Percent converted Impurity pH Color need to be mathematical and statistical
Turbidity Viscosity Stability. equations. Empirical equations are the
22Statistical Design Space. “The most common, but a few mechanistic
mathematically and statistically defined equations may be possible.
combination of Factor Space and Response 56Design Space Conclusions. This is a
Space that results in a system, product or new and perhaps confusing issue for the
process that consistently meets its pharmaceutical industry. To implement this
quality characteristics, SSQuIP, with a approach will require designed experiments
high degree of assurance.” LDT. with overlays of multiple responses for
23Modeling the World. “All Models are each new product. Sometimes retrospective
wrong, but some are useful.” G. E. P. Box studies of existing products can be done
Empirical Models: Simple linear, y = a + with historical data.
bx Quadric equation, y = a + bx + cx2
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How to Define Design Space

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