1. Design of Experiments as a Tool for QbD in Pharmaceutical Product Development.
Dr Dehghan M. H
Professor in Pharmaceutics,
Y B Chavan College of Pharmacy, Aurangabad
Date:23rd Jan’ 2016

2. Pharmaceutical Development
Aim: To design a quality product and its manufacturing process to consistently deliver the intended performance of the product.
“Quality cannot be tested into a product Quality should be built in by design”
NDA –Merck & Co “Januvia” first product approved based on QbD

3. Pharmaceutical Development
Components of Drug Product
Drug Substance
Excipients
B. Drug Product
Formulation Development
Overages
Physicochemical and Biological Properties
Manufacturing Process Development
Container and Closure system
Microbiological Attributes
Compatibility.
Ref.: ICH Q8 (R1)

4. Traditional vs. QbD Approach to Pharmaceutical Development
Traditional Approach
QbD Approach
Quality assured by testing and inspection
Quality built into product & process by design, based on scientific understanding
Data intensive submission – disjointed information without “big picture”
Knowledge rich submission – showing product knowledge & process understanding
Specifications based on batch history
Specifications based on product performance requirements
“Frozen process,” discouraging changes
Flexible process within design space, allowing continuous improvement
Focus on reproducibility – often avoiding or ignoring variation
Focus on robustness – understanding and controlling variation

5. Pharmaceutical Development & Product Lifecycle
Product Design & Development
Process Design & Development
Manufacturing Development
Continuous Improvement
Product Approval
Candidate Selection

6. Statistical Process Control
Pharmaceutical Development & Product Lifecycle
Statistical Tool
Product Design & Development:
Initial Scoping
Product Characterization
Product Optimization
Design of
Experiments
(DOE)
Process Design & Development: Initial Scoping
Process Characterization
Process Optimization
Process Robustness
Model Building
And Evaluation
Statistical Process Control
Manufacturing Development and Continuous Improvement:
Develop Control Systems
Scale-up Prediction
Tracking and trending

7. Product Knowledge Continuous Improvement Quality by Design
Process Understanding
Product Knowledge
Product Specifications
Product Quality Attributes
Process Controls
Process Parameters
Desired Product
Performance
Process Design
Unit operations, control
strategy, etc.
Product Design
Dosage form, stability,
formulation, etc.
Cpk, robustness, etc.
Process Performance
Quality by
Design
FDA’s view on QbD, Moheb Nasr, 2006

8. Overview of QbD Quality Target Product Profile (QTPP)
Product Design and Understanding
Process Design and Understanding
Control Strategy
Continuous Improvement
Quality Target Product Profile (QTPP)
Define Critical Quality Attributes (CQAs)
Perform risk assessment
Link raw material attributes and process parameters to CQAs
Design and implement a control strategy
Manage product lifecycle, including continuous improvement

9. Quality Target Product Profile-QTPP
What is QTPP?
A set of elements that defines the drug product
The target or goal set in advance
A guide to Drug Product development
What forms the basis for QTPP?
The RLD and its label
Applicable regulatory guidelines
When to define QTPP?
At the start of development
Knowledge gained in development may change some elements

10. Components of QTPP
Components related to safety, efficacy, identity, purity and potency
Critical and non-critical components, e.g.
Critical: Assay, content uniformity
Non-critical: Appearance
Fixed and variable components
Fixed elements must be present
e.g. Dosage form, strength
Variable elements may have a range of acceptable values
e.g. Tablet weight, assay

11. An Example of QTPP components for IR tablet
Dosage Form
Route of administration
Strength
Weight
Pharmacokinetics
Appearance
Identity
Assay
Impurities
Content uniformity
Friability
Dissolution
Residual solvents
Specific requirements
Scored tablets
Weight variation between two halves
Dissolution of half tablet
Orally Disintegrating tablets
Hardness
Disintegration time
Container closure
Extended Release products
Alcohol induced dose dumping

12. Critical Quality Attributes
CQAs are a subset of the QTPP
Include critical parameters that are likely to change based upon variations in raw materials and processes
CQAs ensure that DP remains within safe and effective levels.
QTPP components
Dosage Form
Route of administration
Strength
Weight
Pharmacokinetics
Appearance
Identity
Assay CQAs
Assay (efficacy)
Impurities (safety)
C.U. (efficacy)
Dissolution (efficacy)
Critical Quality Attributes (CQA’s)
Assay (efficacy)
Impurities (safety)
C.U. (efficacy)
Dissolution (efficacy)

13. What factors affect drug product CQAs?
Properties of Input Materials- Identify Critical Material Attributes (CMAs)
Properties of in-process materials- CQAs of one step become CMAs for a downstream unit operation
Manufacturing process parameters- Identify Critical Process Parameters (CPPs)

14. Risk Assessment Risk assessment for
Formulation – starting material properties, levels of components
Manufacturing process
Steps for risk assessment
List out all components / processes
Prepare the process flow chart
Identify all potential failure modes for each item with risk query (what might go wrong?)
Risk analysis
Risk evaluation

15. Risk Assessment
Various formal methodologies available for risk assessment
Failure Mode Effects Analysis & Failure Mode Effects & Criticality Analysis
Hazard & Operability Analysis
Supporting statistical tools
It is neither always appropriate nor always necessary to use a formal risk management process….. The use of informal risk assessment processes can also be considered acceptable. – ICH Q9
A risk-based justification based on experience and data is always necessary!

16. Risk Assessment Quality by Design for ANDA:
An Example for Immediate-Release Dosage Forms
Generic product development for Acetriptan Tablets, 20 mg.
Acetriptan is a BCS Class II compound displaying poor aqueous solubility (less than mg/mL) across the physiological pH range.
It exists in three different polymorphic forms which may affect dissolution.
Polymorph III is the most stable polymorph.
Drug product is prepared with roller compaction process.

17. Risk assessment for formulation components Formulation Variables
Drug Product CQA
Formulation Variables
Drug Substance PSD
MCC/Lactose Ratio
CCS Level
Talc Level
Magnesium Stearate Level
Assay
MEDIUM
LOW
Content Uniformity
HIGH
Dissolution
Degradation Products

18. Risk assessment of DP manufacturing process
Drug Product CQAs
Process Steps
Pre-RC* Blending and Lubrication
Roller Compaction
Milling
Final Blending and Lubrication
Compression
Assay
MEDIUM
LOW
Content Uniformity
HIGH
Dissolution
Degradation Products
* RC: Roller compaction

19. Justification for assigned risks

20. Control Strategy
A planned set of controls, derived from current product and process understanding that ensures process performance and product quality…..” ICH Q8 (R2) & Q10
Control Strategy includes following elements (but not limited to):
Input material attributes (e.g. drug substance, excipients, container closure)
Equipment operating conditions (process parameters)
In-process controls
Finished product specifications
Controls for each unit operations
Methods and frequency of monitoring and control.

22. QbD Tools Design of experiments (DoE)
Process Analytical Technology (PAT)

23. Experimental Designs 1. Success / Failure
Useful for screening of variables with significant impact on DP CQAs
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
Several runs, one factor varied, two outcomes
Easy to Design, has comparison of outcomes
Limited number of experiments gives limited information
Can’t find interactions and is inefficient

24. Design of Experiments (DOE)
Structured, organized method for determining the relationship between factors affecting a process and the response of that process
Multiple runs, multiple factors varied at a time
Multiple outcomes, will find interactions
Is much more efficient
Comparison of outcomes
Used in optimization studies, enables creation of “design space”

25. Scope of Experimental Design
Expertise and Experience
Define the measured responses (CQA)
Identify factors (CPPs/CMAs)
Select 2-7 factors to be treatments
Depending on qualitative/quantitative factors select levels or values
Select a design

26. Some Designs
P B: Plackett- Burman Designs

27. DOE Methodology (1) Choose experimental design
(e.g., full factorial, d-optimal)
(2) Conduct randomized experiments
Experiment
Factor A
Factor B
Factor C 1 + - 2 3 4 A B C
(3) Analyze data
(4) Create multidimensional
surface model
(for optimization or control)

28. Polynomial mathematical interaction expression
Y= B0+B1X1+B2X2+B3 X12 +B4 X22 +B+5 X1 X2 + B6 X1X+B7X12+B8X12X22
Y – Response (CQA)
Bi – Regression coefficient for various terms containing the levels of the independent variables.
X – Independent variables (CMA/CPP)

29. CONTOUR PLOT FOR TABLET HARDNESS
CONTOUR PLOT FOR Tablet dissolution(T50%)
GRAPH OBTAINED BY SUPER IMPOSITION OF
TABLET HARDNESS & DISSOLUTION

30. Design Space (ICH Q8) Statistically designed experiments (DOEs)
An efficient method for determining impact of multiple
parameters and their interactions and for the generation of design
Space
Definition of Design Space: The multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality
Working within the design space is not considered as a change. Movement out of the design space is considered to be a change and would normally initiate a regulatory post-approval change process.
Design space is proposed by the applicant and is subject to regulatory assessment and approval

31. Design Space
Dependent
Response
Space
Independent
Factor
Space ?

32. Conceptual Design Space
Operation Space
Opt
Region of Interest
Factor Space, X and Y
Response Space, the contours
Region of operability
Uncertain space

33. 19 August 2008

34. Process Inputs and Outcomes
Critical Quality Attributes
Design Space
Process Step
Input Materials
Output Materials
(Product or Intermediate)
Measured
Parameters
or Attributes
Control Model
Process Measurements
and Controls
Input
Process Parameters

35. Process Analytical Technology (PAT)
Timely measurements during processing
Critical quality and performance attributes
Raw and in-process materials
At-line, on-line or in-line measurements
Founded on “Process Understanding”
Opportunities for improvement
More reliable and consistent processes (& product)
Less failures, less reworks, less recalls
Flexibility w.r.t. scale and equipment
Better / faster Quality Systems
Process Enhancement Opportunities

36. PAT in Tablet manufacturing

37. Examples of PAT
Real-time Blend Uniformity by using TruProcess™ Analyzer
Spectral Probe NIR Analyzer installed on viewing window of Glatt FBD without any dryer modification

38. References Guidance for Industry: Q8(R2) Pharmaceutical Development
Guidance for Industry: Q9 Quality Risk Management
Guidance for Industry: Q10 Pharmaceutical Quality System
Guidance for Industry PAT: A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance
Quality by Design for ANDAs: An Example for Modified Release Dosage Forms
Quality by Design for ANDAs: An Example for Immediate Release Dosage Forms
G A Lewis, Didier Mathieu, Roger Phan-Tan-Luu. Pharmaceutical Experimental Design , publishers Informa Healthcare, New York.

39. Thank You