Tunnell Consulting

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Tunnell Consulting
Discover the Value

• Improving Process Understanding Through
  Statistical Analysis
• Approach and Case Study
• By
• Philippe Cini, Ph.D.

900 East Eighth Avenue / Suite 106 / King of
Prussia, PA 19406 610.337.0820
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Context

• The cGMP guidelines for the 21st Century are
  built on two guiding principles
• A Science-Based Approach
• A Risk-Based Approach
• The PAT initiative and its draft guidance
  document are intended to help the industry answer
  the question What does the FDA mean by a
  Science-Based Approach? Isnt it what we have
  been doing all along!
• In the context of PAT, the FDA promotes and
  advocates the use of four categories of tools
• Multivariate data acquisition and analysis tools
• Modern process analyzers or process analytical
  chemistry tools
• Process and endpoint monitoring and control tools
• Continuous improvement and knowledge management
  tools
• The same principles and tools apply to root cause
  analysis and corrective action

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Process Understanding, Corrective Action, and
Control- A Flexible and Comprehensive Framework -
Achieving Process Understanding and Root Cause
Development / Manufacturing Strategy
Process Mapping and Data Collection
Process Capability Determination
Key Variables Identification
Measurement System Analysis
Variation Reduction Strategy
Specification Limit Development
Achieving Process Control and Sustaining the Gains
Dashboard and Reporting Requirements
Process Control Strategy / Infrastructure
IT Infrastructure
Cultural Change
Organizational Skills Development
Analytical Technology Strategy / Infrastructure
Data Integration Strategy / Infrastructure
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Outline

• Approach and Tools for Root Cause Analysis
• A Case Study
• Summary of Other Case Studies

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Process Capability Index The Meaning of Cpk
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Process Capability Index A Powerful Yet
Easy-to-Use Investigation Tool

• Cpk values can be calculated for a given
  parameter or quality attribute for a group of
  batches (in-between lot variation).
• Cpk values can be calculated for a given
  parameter or quality attribute for a specific
  batch over a period of time (within lot
  variation).
• Both values provide quantitative insight into how
  capable a process parameter is of consistently
  meeting its specification limits.
• Combining Cpk information with technical
  knowledge leads to the identification of focus
  areas for the sources of variation.
• This typically helps to reduce a problem
  complexity and/or identify focus areas that may
  have been overlooked.

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Example of Process Capability Index Summary Solid
Dose Process
This process is incapable of consistently meeting
its specification limits
Main Unit Operation
Remarkably, three clinical successful batches had
been manufactured
Down- stream Equipment
?
44.5
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44.5
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Process Control Charts Another Powerful Yet
Easy-to-Use Investigation Tool
OOS
Shift
Shift
Finished Product Release Parameter
Shift
OOS
Lot Number
Cpk 0.464
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Process Understanding, Optimization, and
Control- A Flexible and Comprehensive Framework -
Achieving Process Understanding and Optimization
Development / Manufacturing Strategy
Process Mapping and Data Collection
Process Capability Determination
Key Variables Identification
Measurement System Analysis
Variation Reduction Strategy
Specification Limit Development
Achieving Process Control and Sustaining the Gains
Dashboard and Reporting Requirements
Process Control Strategy / Infrastructure
IT Infrastructure
Cultural Change
Organizational Skills Development
Analytical Technology Strategy / Infrastructure
Data Integration Strategy / Infrastructure
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Regression Analysis Using Historical Data
Another Powerful Investigation Tool-
Commercially Manufactured Drug Example -
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Regression Analysis Using Historical
DataAnother Powerful Investigation Tool-
Commercially Manufactured Drug Example -
(Continued)
The top two

Table of Effects
effects far
outweigh the
others
Screen 20
(
-
1.21)
Negative
Effect
1.17
Blend Water
Screen 80
0.29
Positive
Effect
Thru Screen 200
(
-
0.24)
Active Ingredient
(
-
0.2)
Screen 100
0.19
Volume As Is
0.13
Screen 40
(
-
0.09)
Screen 200
0.08

84.4 of variation
0
0.2
0.4
0.6
0.8
1
1.2
1.4
explained by
The top two effects are directly related to the
two areas where precisely manufacturing
capabilities are low!
model

89 lots used in
model
S
Mixture Constraint
S
creens 1
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A Possible Explanation for the Correlation
Between Fraction of Coarse Particles and Tablet
Water Content
Air
Air
High Packing Density Less Effective Drying
Low Packing Density More Effective Drying
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Regression Analysis Using Historical Development
Data- The Challenge Data is Limited -
Instead of doing a single, large regression
analysis that includes all or many of the input
parameters of interest, a series of
sub-regression analyses that include only 2 to 4
input parameters are generated.
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Regression Analysis Using a Very Limited
Historical Data Set
Parameters 2 and 5
Parameters 2, 10, and 11
Parameters 5 and 6

• With multiple sub-regression analyses, it is no
  longer possible to quantify the relative
  contribution of various input parameters to the
  overall variation using a table of effects.
• A substitute for a table of efforts is required.

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Rough Estimate of Individual Contributions to the
Overall Variation

• A rough estimate of the individual contributions
  to the overall variation can be obtained by
  calculating the ratio of the sum of squares of an
  individual parameter to the sum of the sum of
  squares for all individual parameters in all
  sub-regressions.
• Contribution
• Raw Material 39
• Main Unit Op. Process Conditions 48
• Downstream Equipment 13
• Caution This approach has limitations and
  potential flaws.

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Regression Analysis Using Very Limited Historical
Data Set- Benefits and Path Forward -
Benefits
Path Forward

• Redirected and reenergized development effort
• Provided critical technical input to adjust
  business, regulatory, and manufacturing
  strategies
• Significantly increased the probability of
  obtaining regulatory approvals
• Provided critical technical input for a
  successful tech transfer and for achieving
  process robustness

• Run confirmatory experiments
• Run optimization Design of Experiments

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Outline

• Approach and Tools for Root Cause Analysis
• A Case Study
• Summary of Other Case Studies

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Other Case Studies

• This approach and tools have been used with great
  success to troubleshoot a broad array of commonly
  encountered technical challenges. Among those
  were
• Low potency
• Excess water content
• Excessive tablet defects (picking and sticking)
• Dissolution rate

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