This document discusses Quality by Design (QbD) in API manufacturing. It begins by quoting Joseph M. Juran that quality must be built in by design, not tested in. It then defines QbD as a systematic approach that emphasizes product and process understanding and control based on science and risk management. The document outlines some of the key aspects of QbD like design space, quality risk management, and using tools like design of experiments. It compares the traditional and QbD approaches and discusses some of the pros and cons of QbD.

1. QUALITY BY DESIGN (QBD)
IN API
DR ANTHONY CRASTO
1

2. THE QUALITY MANTRA
“Quality can not be tested
into products; it has to be
built in by design”
Joseph M Juran

3. WHAT IS QUALITY BY DESIGN?
“You can’t test quality into drug
products” has been heard for decades
– so what’s new?
It’s a culture - incorporates quality principles as well as
strong compliance function
Incorporates risk assessment and management
Refocuses attention and resources on what’s important
to the customer, i.e. the patients, health professionals,
payors and distribution chain

4. QUALITY BY DESIGN
Continuous improvement is a hallmark of
quality by design
G. Taguchi on Robust Design: design changes during
manufacture can result in the last product produced
being different from the first product
In pharmaceutical manufacturing, we
don’t want this – patients and
physicians must count on each batch
of drug working just like the batches
that came before

5. QUALITY BY DESIGN
In generic pharmaceutical manufacturing, there are additional
constraints
 Fixed bioequivalence targets
 Regulatory requirements to duplicate formulation of innovator drug
 Lack of access to innovator development data

6. LEAD POINTS
1. QbD Basic concept
2. Steps in QbD
3. DoE as a tool for QbD
4. Example Torcetrapib
5. Pros and cons
6. Conclusion

7. WHAT IS QUALITY?
Quality
Patient
Target Product
Quality Profile
Requirements
= need or
expectations
“Good pharmaceutical quality represents
an acceptably low risk of failing to achieve
the desired quality attributes.”

8. DEFINITION: QUALITY BY DESIGN
Quality by Design is
a systematic approach to development
that begins with predefined objectives
and emphasizes
- product and process understanding
- and process control,
based on sound science and quality risk management.

9. THE REVOLUTION IN QUALITY
THINKING
Quality by Testing
and Inspection
Enhanced
• product knowledge
• process
understanding
Quality by Design
quality assured by well designed product & process

10. INTRODUCED BY FDA IN 2002
ICH Q8 + ICH Q9 + ICHQ10
Pharmaceutical Quality Risk Quality
Development Management Management
=
Quality by
Design
Quality by Design – GMP for the 21st
Century
Merck & Co’s Januvia (2006) : first FDA
approved product

11. QUALITY BY DESIGN (QBD)
Myth : An expensive development tool !
Fact : A tool that makes product development and
commercial scale manufacturing simple !
Actually saves money !
How ?

12. OUTLINE
FDA initiatives for quality
 The desired state
 Quality by design (QbD) and design space (ICH Q8)
Application of statistical tools in QbD
 Design of experiments
 Model building & evaluation
 Statistical process control

13. FDA’S INITIATIVE ON QUALITY BY
DESIGN
In a Quality-by-Design system:
 The product is designed to meet patient requirements
 The process is designed to consistently meet product critical quality
attributes
 The impact of formulation components and process parameters on
product quality is understood
 Critical sources of process variability are identified and controlled
 The process is continually monitored and updated to assure consistent
quality over time

14. Quality
by
Design

16. Pros and Cons
• Scientific understanding
• Holistic approach
• Less data to manage
• Meaningful data
• Fewer non conformances
• Lean processes – more cost
efficient
• Better control of process
• Continuous improvement
• Managed based on risk
• Patient first approach
• Up to 30% savings*
• New concept – hard to get
buy in
• Just starting to be
recognised by authorities
• Culture change
• Investment up front
• Time to get to know
process and product
• Difficult to apply
retrospectively

17. DESIGN SPACE (ICH Q8)
Definition: 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

18. ICH Q9 QUALITY RISK MANAGEMENT
The primary objective is to find a harmful event
in the process
Initiate Quality Risk
Management Process
The new language
1.Risk Assessment
2. Risk Control
Output / Result of the Quality
Risk Management Process
4. Risk Review
Formal
Risk Management
Process

19. CURRENT VS. QBD APPROACH TO
PHARMACEUTICAL DEVELOPMENT
Current 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

20. MAPPING THE LINKAGE
Input Output
M1
M2
Material Attributes
P1
P2
P3
CQA1
CQA2
CQA3
Relationships:
CQA1 = function (M1)
CQA2 = function (P1, P3)
CQA3 = function (M1, M2, P1)
P2 might not be needed in the
establishment of design space
Process
Parameters
Critical
Quality
Attributes

21. PHARMACEUTICAL DEVELOPMENT
& PRODUCT LIFECYCLE
Product Design & Development
Candidate
Selection
Process Design & Development
Manufacturing Development
Continuous Improvement
Product
Approval

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

24. BACKGROUND OF FDA’S
“PHARMACEUTICAL QUALITY FOR
THE 21ST CENTURY INITIATIVE
In 2002, FDA identified a series of ongoing
problems and issues in pharmaceutical
manufacturing that traditional approaches
had not solved
FDA undertook an internal and external
assessment of the causes
As a result, the agency started a major
change initiative that is continuing
Stimulating more use of PAT was an early
component of initiative

25. STATE OF REGULATION CIRCA 2002
Pharmaceutical manufacturing HIGHLY regulated (e.g., compared to
foods, fine chemicals)
Cost of cGMP compliance very high
Despite this: process efficiency and effectiveness low (high wastage
and rework); and level of technology not comparable to other
industries

26. FUNCTIONAL CONSEQUENCES
Inability to predict effects of scale-up
Lack of agility – usually takes years to bring
up a new production site
Operations fragmented around globe
Inability to understand reasons for
manufacturing failures

27. RESULT: FOR REGULATORS
Extensive oversight of manufacturing resource-intensive (in era of cost
reductions and increased mandates)
Expensive and time-consuming litigation and legal actions in cGMP area
Need to deal with recalls and shortages of medically necessary drugs

28. RESULT: FOR INDUSTRY
Culture: antithesis of “continuous
improvement”
Less focus on quality, more on
compliance
Regulatory burden high and costly, but
not viewed as contributing to better
science
Consequences of noncompliance:
potentially catastrophic
Lack of innovation: “test but don’t tell”

29. OUTCOMES
• High cost of production for products due to
– Low efficiencies in manufacturing
– Waste
– Long manufacturing cycle times based on testing requirements during production
• Drug shortages due to inability to manufacture
• Lack of improvements based on new technologies
• Slowed development/access for investigational drugs
• Need for intensive regulatory oversight

30. FDA NEEDED TO MODERNIZE PHARMACEUTICAL
MANUFACTURING REGULATION
• More than 40 years ago, Congress required that all
drugs must be produced in accordance with Current
Good Manufacturing Practice (cGMP).
• Requirement was intended to address significant
concerns about substandard drug manufacturing
practices by applying quality assurance and quality
control principles to drug manufacturing.
• Last comprehensive revisions to the regulations
implementing cGMP requirements occurred over 25
years ago.
• The initiative was started in August 2002 as the
Pharmaceutical cGMPs for the 21st Century - A Risk-
Based Approach initiative to enhance and modernize
the regulation of pharmaceutical manufacturing and
product quality — to bring a 21st century focus to
this critical FDA responsibility.

31. THE DESIRED STATE: A MUTUAL GOAL OF INDUSTRY,
SOCIETY AND THE REGULATORS
A maximally efficient, agile, flexible pharmaceutical manufacturing
sector that reliably produces high quality drug products without
extensive regulatory oversight
Qbd on cleaning

32. GUIDANCE FOR INDUSTRY: QUALITY SYSTEMS
APPROACH TO PHARMACEUTICAL CGMP REGULATIONS
Help manufacturers bridge between 1978 regulations
and modern quality systems and risk management
approaches
Extends beyond CGMP expectations; however, does not
create requirements on manufacturers.
Implementation of this model should ensure
compliance and encourage use of science, risk
management and other principles of the 21st Century
Initiative.
“When fully developed and effectively managed, a quality system will
Describes lead a to comprehensive consistent, predictable quality processes system that ensure model that
and
how CGMP regulations link to QS elements
pharmaceuticals are safe, effective, and available for the consumer.”

33. QUALITY SYSTEMS : IMPLEMENTATION
AND INTERNATIONAL DEVELOPMENT
AS THE PQS
• Manufacturers with a robust quality system and
appropriate process knowledge can implement
many types of improvements and take
responsibility for quality
–Eliminate most of the burden of CMC post approval regulatory
submissions
–Allow for more focused and fewer FDA inspections
–Adoption by industry is starting to take hold – fewer deviations, cost
savings in manufacturing
• ICH adopted this concept as Q 10 Pharmaceutical
Quality System (PQS) to fulfill the ICH Quality
Vision
–Covers the product lifecycle from pharmaceutical development, tech
transfer, commercial manufacturing, to discontinuation
–Focuses on the commercial manufacturing process, predicted by
development and utilizes knowledge for process improvement and future
development

34. INTERNATIONAL HARMONIZATION
In addition to Q10, Quality Systems:
Q8 Pharmaceutical Development
Q9 Quality Risk Management

35. HEPARIN WAS A WAKEUP CALL
• Up to 30% contamination of finished product
• Present worldwide in various APIs: many countries affected
• Undetected by acceptance and release testing
• Persisted in drug supply until serious adverse events triggered
investigation
• Brought home the need for vigilance throughout supply chain and in
all global settings

36. SIGNIFICANT CHALLENGES FOR BOTH
MANUFACTURERS AND FDA
• Explosion of globalized manufacturing
• Increased complexity of supply chains
• Greater potential for exploitation (e.g., counterfeits, terrorism)
• Global regulatory system still fragmented
• (US) Erosion of inspectional coverage over last several decades
• (US) Lack of modern IT (e.g., registration and listing systems,
inspection tracking, imports)

37. IMPROVEMENTS STARTED IN 21ST CENTURY INITIATIVE
ARE CRITICAL
Global harmonization of manufacturing standards
Continuous improvement in manufacturing science
Application of quality risk management
Quality by design

38. ROLE OF THIS PAT WORKSHOP
Gathering of academics, pharmaceutical industry, FDA, PAT equipment
manufacturers
Goal: update on use of the technology, present case studies,
understand barriers to more widespread adoption
Understanding of how PAT fits into the future of quality by design

39. QUALITY BY DESIGN APPROACH
CAN BE USED FOR

40. STEPS IN A QUALITY BY DESIGN
APPROACH?
1.QUALITY
TARGET
PRODUCT
PROFILE
1.QUALITY
TARGET
PRODUCT
PROFILE
2. CRITICAL
QUALITY
ATTRIBUTES
2. CRITICAL
QUALITY
ATTRIBUTES
6. PRODUCT
LIFECYCLE
MNGMNT
6. PRODUCT
LIFECYCLE
MNGMNT
3. LINK
3. LINK
MAs AND PPs
TO CQAS
MAs AND PPs
TO CQAS
4. ESTABLISH
DESIGN
4. ESTABLISH
DESIGN
5. ESTABLISH
CONTROL
STRATEGY
5. ESTABLISH
CONTROL
STRATEGY
SPACE
SPACE

41. STEP1 : QUALITY TARGET PRODUCT
PROFILE (QTPP)
Target Product Profile:
- a prospective and dynamic summary of the quality
characteristics of a drug product
- that ideally will be achieved to ensure that the desired
quality, and hence the safety and efficacy, of a drug
product is realized.
The TPP forms the basis of design of the product.

42. STEP 2. DETERMINE THE CRITICAL QUALITY
ATTRIBUTES (CQAS)
- DEFINITION
A critical quality attribute (CQA) is a
- physical, chemical, biological, or
microbiological property or characteristic
- that should be within an appropriate
limit, range, or distribution
- to ensure the desired product quality.

43. STEP 2. DETERMINE THE CRITICAL QUALITY
ATTRIBUTES (CQAS)
Drug product CQAs are used to guide the
product and process development.
 SOLID ORAL DOSAGE
FORMS:
 Particle size
 Polymorphic form
 Water content
 Residual solvent
 Organic and inorganic
impurities
 OTHER DELIVERY
SYSTEMS:
 Include more product specific
aspects, such as
 Sterility for Parenteral,
 Adhesive force for
transdermal patches.

44. STEP 3. LINK THE DRUG AND EXCIPIENTS
ATTRIBUTES AND THE PROCESS
PARAMETERS TO THE CQAS
People
I Chart
Process
Parameters
Equipment
Measurement
Process
Materials
Environment
INPUTS
(X)
Quality Attributes
y = ƒ(x)
Inputs to the process
control variability
of the Output
y
UCL=114.17
OUTPUT
Observat ion
Observat ion
Observat ion
Observat ion
Individual Value
20 22 24 26 28 30 32 34 36 38 40
120
115
110
105
100
95
90
UCL=111.55
UCL=112.65
UCL=112.65
UCL=116.68
_
X=102.37
LCL=88.05
I Chart
Individual Value
40 42 44 46 48 50 52 54 56 58 60
115
110
105
100
95
90
85
80
_
X=97.94
LCL=83.23
I Chart
Observat ion
Individual Value
60 62 64 66 68 70 72 74 76 78 80
115
110
105
100
95
90
UCL=111.55
_
X=99.63
LCL=87.71
I Chart
Observat ion
Individual Value
80 82 84 86 88 90 92 94 96 98 100
110
105
100
95
90
85
UCL=111.17
_
X=98.76
LCL=86.35
I Chart
Individual Value
40 42 44 46 48 50 52 54 56 58 60
115
110
105
100
95
90
85
80
_
X=97.94
LCL=83.23
I Chart
Individual Value
60 62 64 66 68 70 72 74 76 78 80
115
110
105
100
95
90
_
X=99.63
LCL=87.71
Observat ion
Indiv idual Value
1 11 21 31 41 51 61 71 81 91
115
110
105
100
95
90
85
_
X=99.95
LCL=85.72
I Char t
4 DESIGN SPACE
………..LATER

45. STEP 5. CONTROL STRATEGY
Elements of a control strategy can include, but are not limited
to, the following:
• Control of input material attributes based on an
understanding of their impact on process ability or product
quality
• Product specification(s)
• Controls for unit operations that have an impact on
downstream processing or end-product quality
• In-process or real-time release in lieu of end-product testing

46. STEP 5. DEFINE THE CONTROL
STRATEGY
The control strategy should describe and
justify how
• in-process controls and
• the controls of
- input materials
(drug substance and excipients),
- container closure system,
- intermediates and
• the controls of end products
contribute to the final product quality

47. TOOLS FOR RISK MANAGEMENT
Preliminary hazard analysis ( PHA)
Failure mode effect and criticality analysis
( FMECA)
Risk ranking
Risk filtering

48. BETTER PROCESSES UNDERSTANDING WILL
LEAD TO PRODUCTS
WITH LESS VARIABILITY

49. What are the steps in a
Quality by Design approach?
1.QUALITY
TARGET
PRODUCT
PROFILE
1.QUALITY
TARGET
PRODUCT
PROFILE
2. CRITICAL
QUALITY
ATTRIBUTES
2. CRITICAL
QUALITY
ATTRIBUTES
6. PRODUCT
LIFECYCLE
MNGMNT
6. PRODUCT
LIFECYCLE
MNGMNT
3. LINK
3. LINK
MAs AND PPs
TO CQAS
MAs AND PPs
TO CQAS
4. ESTABLISH
DESIGN
4. ESTABLISH
DESIGN
5. ESTABLISH
CONTROL
STRATEGY
SPACE
5. ESTABLISH
CONTROL
STRATEGY
SPACE

50. DEFINITION OF DESIGN SPACE
• The material attributes and process
parameters that assure quality.
• The multidimensional combination
and interaction of input variables
(e.g. material attributes) and
• process parameters that have been
demonstrated to provide assurance
of quality.

52. STEPS IN A QUALITY BY DESIGN
APPROACH?
1.QUALITY
TARGET
PRODUCT
PROFILE
1.QUALITY
TARGET
PRODUCT
PROFILE
2. CRITICAL
QUALITY
ATTRIBUTES
2. CRITICAL
QUALITY
ATTRIBUTES
6. PRODUCT
LIFECYCLE
MNGMNT
6. PRODUCT
LIFECYCLE
MNGMNT
3. LINK
3. LINK
MAs AND PPs
TO CQAS
MAs AND PPs
TO CQAS
4. ESTABLISH
DESIGN
4. ESTABLISH
DESIGN
5. ESTABLISH
CONTROL
STRATEGY
5. ESTABLISH
CONTROL
STRATEGY
SPACE
SPACE

53. Knowledge
Space
Design Space
Control Space
CONTROL SPACE

54. DESIGN OF EXPERIMENTS (DOE)
Structured, organized method for determining the
relationship between factors affecting a process and the
response of that process
Application of DOEs:
 Scope out initial formulation or process design
 Optimize product or process
 Determine design space, including multivariate relationships

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

56. A DOE IS USEFUL TO
Identify important factors
Establish process stability
Find best operating conditions

57. Graphical Analysis
Geo-Gram:
The geo-gram is a geometrical representation of the data.
The shape is determined by the number of factors ( i.e. 2 factors is a
square, 3 factors is a cube), the number of levels and the distance
between levels.
SQUARE GEO-GRAM
35
47
41 50
+
Temp
B
- +
Time
A
-
This defines the inference space
or the experimental boundaries
of your experiment within your
process.

58. 1a
Response ssuurrffaaccee pplloott CCoonnttoouurr pplloott

59. Pre-formulation
studies
QbD
Literature
review formulation
QC and
Evaluatio
n
Out
Product
Current approach:-
• Quality assured by testing and inspection
• Data intensive submission
• Specifications based on batch history
• “Frozen process,” discouraging changes
• Focus on reproducibility – often avoiding or ignoring variation
QbD Approach:-
• Quality built into product & process by design, based on scientific
understanding
• Knowledge rich submission – showing product knowledge & process
understanding
• Specifications based on product performance requirements
• Flexible process within design space, allowing continuous improvement
• Focus on robustness – understanding and controlling variation
QbD replaces QbT( Quality by Testing)

60. Experimental Approach for
Identifying Parameters
Design of Experiments (DOE) is an efficient method to
determine relevant parameters and interactions
1. Choose Experimental Design
(e.g., full factorial, fractional )
2. Conduct Randomized Experiments
3. Analyze Data
Determine significant factors

61. MODEL BUILDING & EVALUATION -
EXAMPLES
Models for process development
 Kinetic models – rates of reaction or degradation
 Transport models – movement and mixing of mass or heat
Models for manufacturing development
 Computational fluid dynamics
 Scale-up correlations
Models for process monitoring or control
 Chemometric models
 Control models
All models require verification through statistical
analysis

62. Model Building & Evaluation -
Chemometrics
Chemometrics is the science of relating measurements
made on a chemical system or process to the state
of the system via application of mathematical or
statistical methods (ICS definition)
Aspects of chemometric analysis:
 Empirical method
 Relates multivariate data to single or multiple responses
 Utilizes multiple linear regressions
Applicable to any multivariate data:
 Spectroscopic data
 Manufacturing data

63. QUALITY BY DESIGN & STATISTICS
Statistical analysis has multiple
roles in the Quality by Design
approach
Statistically designed experiments (DOEs)
Model building & evaluation
Statistical process control
Sampling plans

64. A SHARED VISION OF QUALITY
GPhA supports the FDA CGMP initiative
Generic drug manufacturing companies:
Exist to make affordable drug therapies available to all
Companies, staff, volumes and revenues are smaller
It is completely appropriate that
regulatory requirements apply to all
companies small and large, as long as
regulatory guidance provides flexibility
in recognition of more limited
resources at smaller firms

65. SUGGESTED ACTIONS
Give credit for good performance
Continue to reduce unnecessary
supplements
Continue to develop the Pharmaceutical
Inspectorate
Reward process innovation
Eliminate unnecessary testing
requirements
Address oversight of overseas API mfrs

66. Solid-State Polymorphism
Different crystalline forms of the same drug substance
(ICH Q6A)
•Crystalline forms
•Solvates (Hydrates)
•Amorphous forms

67. Drug Product Bioavailability/Bioequivalence
Solubility/Dissolution
Pharmaceutical Solid Polymorphism
Mechanical Properties/
Hygroscopicity
Processability /
Manufacturability
Chemical Reactivity
Stability

68. Polymorphism and the Effect on Bioavailability
10
0 2 4 6 8
0 2 4 6 8 10 12
Time
Conc
Dissolution/Solubility
Limited Oral Absorption
(e.g. chloramphenicol palmitate)
8
6
4
2
0
0 2 4 6 8 10 12
Time
Conc
Gastric Emptying or Permeation
Limited Oral Absorption
(e.g. ranitidine HCl)
Form I
Form II Intestinal
Membrane
Solubility: Form II > Form I
Intestinal
Membrane

69. Polymorphism and the Effect on Stability
Crystalline: Degradation: 0.5%
Amorphous: Degradation: 4.5%
Formulation I
X Crystalline/
Amorphous
Formulation II
Optimize the formulation mitigate degradation pathways
(e.g., adjust pH microenvironment to limit degradation,
anti-oxidant to limit oxidative degradation)
Crystalline: Degradation 0.6%
Amorphous Degradation 0.7%

70. Polymorphism and the Effect on Manufacturability
Paracetamol Form I Paracetamol Form I I
Direct Compression
Wet Granulation
Paracetamol Form I Paracetamol Form I I
E. Joiris , Pharm. Res. 15 (1998) 1122-1130

71. Selection and Control of
Polymorphic Forms?
Formulation
Variables
Biopharmaceutical Properties
Manufacturing Process
Variables
Intrinsic Properties
of Different Forms

72. N O 2
N
H
S
C H 3
C
N
“
”
Regulatory Considerations:
Can One Consider Polymorphs to be the Same Active?
Materials Science
J. Am. Chem. Soc. 122 (2000) 585-591
8
6
4
2
0
0 2 4 6 8 10 12
Time
Conc
Form I Form II
Drug Product
Safety/Effectiveness

73. QBD PARADIGM: POLYMORPHS
From ICH Q8: “The physicochemical and biological properties of
the drug
substance that can influence the performance of the drug
product and its
manufacturability, or were specifically designed into the drug
substance
(e.g. solid state properties), should be identified and discussed. “
Expectation that sponsors justify in pharmaceutical development the selection
and control of the polymorphic form (as applicable) to achieve drug product
performance characteristics, stability and ensure manufacturability

74. FDA REGULATORY SCHEME
21 CFR 320.1(c), Food and Drugs, Definitions: Pharmaceutical equivalent
means drug
products in identical dosage forms that contain identical amounts of the
identical active
drug ingredient, i.e., the same salt or ester of the same therapeutic
moiety…; do not
necessarily contain the same inactive ingredients; and meet the identical
compendial or
Same Active Moiety
other applicable standard of identity, strength, quality, and purity,
including potency.
Different Active Ingredients
Phosphate Sulfate
FDA Regulatory Scheme: Pharmaceutical Alternatives
No Possibility for Therapeutic Equivalence for Different Salts

75. Co-Crystals
A
A
A
A
A
A
A
A
A
A
A
A A
A
A
A A A
A A A
A A A A A
A
A
A
A A
A A
A A A A
G
A
A
A
G
A A
A
A A
G
G
G
G G
A
A
A
G
G
A
G
A+ A+
A+
C- C- C-C-
C-A+
A+
C- C- C-A+
A+
A+ A+
Salts Co-crystals
Polymorphs
Crystalline Molecular Complexes:
Co- Crystal / Salt Continuum
Crystalline Molecular Complexes:
Analogous to Polymorph Solvate
(Except other Component in Crystal
Lattice is a Solid (not Liquid))

76. Where Do Co-Crystals Fit in Our Regulatory Scheme?
A
A
A
A
A
A
A
A
A
A
A
A A
A
A
A A A
A A A
A A A A A
A
A
A
A A
A A
A A A A
G
A
A
A
G
A A
A
A A
G
G
G
G G
A
A
A
G
G
A
G
A+ A+
A+
C- C- C-C-
C-A+
A+
C- C- C-A+
A+
A+ A+
Salts
Co-crystals??
Polymorphs
Same Active Moiety Same API
Different API
Where Do Co-Crystals Fit?
Is a New Regulatory
Class of Solids Needed?

77. CASE STUDY –API TORCETRAPIB
The concept and application of quality by design
(QbD) principles has been and will undoubtedly continue to
be an evolving topic in the pharmaceutical industry.
However, there are few and limited examples that demonstrate
the actual practice of incorporating QbD assessments,
especially for active pharmaceutical ingredients (API)
manufacturing processes described in regulatory submissions.
We recognize there are some inherent and fundamental
differences in developing QbD approaches for drug
substance (or API) vs drug product manufacturing processes.
In particular, the development of relevant process understanding
for API manufacturing is somewhat challenging
relative to criteria outlined in ICH Q8 (http://www.ich.org/
cache/compo/276–254–1.html) guidelines, which are primarily
oriented toward application of QbD for drug product
manufacturing. ……………………………………………J Pharm Innov (2007) 2:71–86

78. In an effort to establish a consensus and develop consistency, industry and regulators
have frequently described quality by design (QbD) by dividing it into three
fundamental, interrelated concepts: control strategy, design space, and
criticality.1 Figure 1 describes a QbD approach for developing design space,
establishing control strategy, and delineating criticality for an active
pharmaceutical ingredient (API) that essentially serves as a map for how these
conceptual elements were used to establish design space for the torcetrapib API
manufacturing process. A preliminary assessment of the QbD strategy for the
manufacture of the API typically begins early in development when chemists and
engineers evaluate synthetic route selection as well as intermediate quality
attributes (QAs) impacting API specifications. As a default, established API
specification limits serve as a primary control standard for QAs and surrogate
control in the absence of a process control strategy and relevant intermediate
specifications.
Torcetrapib (CP-529,414, Pfizer) was a drug being developed to
treat hypercholesterolemia (elevated cholesterol levels) and prevent
cardiovascular disease.

80. The API specification, by default, serves as a predictor of critical QAs (CQAs) because
the combination of their measurements may directly correlate to potential impact
to the safety and efficacy of the drug product and thus to the
patient. API CQAs may include physical characteristics beyond such things as the
impurity specification of the API, e.g., particle size, polymorphic form, and salt
selection are Mrelevant for drug product manufacture.3 The analytical
control strategy for an API manufacturing process that evolves during development is
routinely focused with the attention on the formation and purge of impurities and
their cascade effects on the multiple process steps, including the
potential impact to the API’s CQAs. To establish design space, a formal, prospective
risk assessment is executed in accordance with ICH Q9 (B in Fig. 1). A process
risk assessment is performed as a precedent to formally develop a design space
for the commercial manufacturing process so that potential critical process
parameters (CPPs) can be identified. In general, a process risk assessment
considers prior knowledge, mechanistic understanding of the chemistry,
and relevant chemical manufacturing experiences.

92. Starting and Raw Materials
Before parameters and ranges can be evaluated in any multivariate designed
experiment, the appropriate quality of SMs (or key intermediates) and raw
materials must be established. For the torcetrapib manufacturing process,
some of the specifications of compound 4 were deemed CQAs because of their direct
impact on controlling the relative genotoxic impurities in steps 5 and 6. In
addition, ECF (raw material) is a commodity chemical used in step 5 that is
incorporated into the structure of the API. Fate and purge development work,
batch history, and appropriate communications with vendors are a few methods
to establish appropriate specifications for SMs and raw
materials. Appropriate specifications were established for each of these materials
before any of the multivariate designs were initiated for torcetrapib, and by
default, some of these specifications were deemed CQAs. The validity of
a multivariate experimental design used to establish a design space depends on
understanding the functional relationship between these CQAs/specifications and
the API CQAs.

94. CONCLUSION ON CASE STUDY
We have provided a case study of a QbD effort, including a risk assessment, for the
torcetrapib drug substance process. Fundamentally, different from the drug
product, API processes have multiple steps. Understanding the functional
relationship between FAs, QAs, and process parameters as they progress through the
manufacturing process is the most universally challenging aspect of QbD for API
development. Analytical specifications and control strategy aspects of the QbD plan
remain the foundation for change throughout the evolution of the manufacturing
process (from phase I to launch).
The role of the chemist and engineer during the course of development is to
effectively eliminate as many of the CQAs and CPPs as possible from the
commercial manufacturing process through continuous improvement efforts.
Designed experiments generate the data required to establish a design space for
commercial manufacturing processes, while providing the process understanding
that facilitates sound business decisions. First principles ofchemistry can expand
this “toolbox” to include kinetic models, computer predictive programs, and more
diverse concepts of prior knowledge.

95. SUMMARY:
Quality by Design (QbD) presents to the industry ,
various pro’s like reduction in cost , a better model
,hassle free processes better interacted with FDA.
Along with that ,new technologies can be implemented
once a thorough understanding of product is done.
For a manager ,It cuts down time to the industry , if
used effectively.
Thus , it brings about a worthwhile change in every
Pharmaceutical Operation and thus the popularity of
this subject and shift in the paradigm is signified.

96. SUMMARY
The public expects their drugs to be
of reliable high quality
Tradition of empirical development of
formulation and manufacturing
process makes reliability a
challenge
Globalization introduces more risks
of quality problems
FDA introduced “Pharmaceutical
Quality for 21st Century” to address
these challenges

97. SUMMARY
Improved manufacturing science
(QbD), when paired with a robust
quality system, is the key to reliable
drug quality
Technologies such as PAT are crucial
to implementing the knowledge
gained from QbD in a meaningful
and efficient way
FDA encourages adoption of these
technologies, and is modifying its
own processes in order to facilitate

98. CONCLUSION
Quality by Design and the FDA
CGMP Initiative make
excellent business and
scientific sense
The generic pharmaceutical
industry welcomes the
opportunity to work with FDA

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101. THANKYOU
DR ANTHONY CRASTO
amcrasto@gmail.com
http://newdrugapprovals.org/