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QUALITY BY DESIGN (QBD) 
IN API 
DR ANTHONY CRASTO 
1
THE QUALITY MANTRA 
“Quality can not be tested 
into products; it has to be 
built in by design” 
Joseph M Juran
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
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
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
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
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.”
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.
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
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
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 ?
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
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
Quality 
by 
Design
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
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
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
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
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
PHARMACEUTICAL DEVELOPMENT 
& PRODUCT LIFECYCLE 
Product Design & Development 
Candidate 
Selection 
Process Design & Development 
Manufacturing Development 
Continuous Improvement 
Product 
Approval
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
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
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
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
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
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”
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
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.
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
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.”
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
INTERNATIONAL HARMONIZATION 
In addition to Q10, Quality Systems: 
Q8 Pharmaceutical Development 
Q9 Quality Risk Management
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
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)
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
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
QUALITY BY DESIGN APPROACH 
CAN BE USED FOR
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
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.
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.
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.
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
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
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
TOOLS FOR RISK MANAGEMENT 
Preliminary hazard analysis ( PHA) 
Failure mode effect and criticality analysis 
( FMECA) 
Risk ranking 
Risk filtering
BETTER PROCESSES UNDERSTANDING WILL 
LEAD TO PRODUCTS 
WITH LESS VARIABILITY
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
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.
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
Knowledge 
Space 
Design Space 
Control Space 
CONTROL SPACE
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
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
A DOE IS USEFUL TO 
Identify important factors 
Establish process stability 
Find best operating conditions
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.
1a 
Response ssuurrffaaccee pplloott CCoonnttoouurr pplloott
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)
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
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
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
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
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
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
Solid-State Polymorphism 
Different crystalline forms of the same drug substance 
(ICH Q6A) 
•Crystalline forms 
•Solvates (Hydrates) 
•Amorphous forms
Drug Product Bioavailability/Bioequivalence 
Solubility/Dissolution 
Pharmaceutical Solid Polymorphism 
Mechanical Properties/ 
Hygroscopicity 
Processability / 
Manufacturability 
Chemical Reactivity 
Stability
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
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%
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
Selection and Control of 
Polymorphic Forms? 
Formulation 
Variables 
Biopharmaceutical Properties 
Manufacturing Process 
Variables 
Intrinsic Properties 
of Different Forms
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
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
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
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))
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?
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
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.
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.
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.
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.
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.
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
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
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
•Jun Huan et al, Quality by design case study: An integrated multivariate approach to drug product and 
process development, International Journal of Pharmaceutics, 382 (2009) 23–32 
•Chi –Wan Chen, Christine Moore ,Role of Statistics in Pharmaceutical Development Using Quality-by- 
Design Approach – an FDA Perspective, September 27 -29, 2006. 
• Lindsay I Smith A tutorial on Principal Components Analysis February 26, 2002 
•Quality Risk Management (ICH Q9) EMA/INS/GMP/79766/2011. 
•Http://www.ceruleanllc.com/resources/published-articles-case-studies/#qbd 
• Spaceamit Mukharya et al, Quality risk management of top spray fluidized bed process for 
antihypertensive drug formulation with control strategy engendered by Box-behnken experimental 
design Int J Pharm Investig. 2013 Jan-Mar; 3(1): 15–28. 
•Http://www.ngpharma.com/article/PAT-and-qbd-in-pharmaceutical-development/ 
•Http://www.drugregulations.org/2012/08/qbd-for-beginners-design-space.html?Q=qbd, qbd for 
beginners part 4 , uday shetty 
•Glodek, M et al., Pharm. Eng 2006, 26, 1-11. 
•Rath, T, Strong, D.O., Rath & Strong's Six Sigma Pocket Guide. Lexington, AON Consulting 
Worldwide, MA 2002. 
•International Conference on Harmonization (ICH) of Technical Requirements for Registration of 
Pharmaceuticals for human use, topicq2 (R1): Validation of Analytical Procedures: Text and 
methodology, ICH, Geneva, Switzerland, 2005.
• Juran, J.M. (1992) Juran on Quality by design – The New Steps for Planning Quality into Goods and 
Services,thefreepress 
• Pharmaceutical development - annex ICH harmonized tripartite guideline 
• Dr C. V. S. Subramanian, Quality by Design - Principles “, 29th Jan, 2013. 
• Http://en.wikipedia.org/wiki/Quality_by_Design 
• PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing, and quality 
assurance, September 2004, http://www.fda.gov/cder/guidance/6419fnl.pdf. 
• Guidance for industry Q8(R2),pharmaceutical development , November 2009,ICH revision 2 
• Innovation and continuous improvement in pharmaceutical manufacturing pharmaceutical cGMP for 
the 21st Century, U.S. Food and Drug Administration, 2004 September, Available from: 
URL:http://www.fda.gov/cder/gmp/gmp2004/manufsciwp.pdf. 
• Ashwini Gawade1 et al , Pharmaceutical Quality by Design: A New Approach in Product Development., 
ISSN: 2320-1215 Research and Reviews: Journal of Pharmacy and Pharmaceutical Sciences 
• International Conference on Harmonization (ICH) of Technical Requirements for Registration of 
Pharmaceuticals for Human Use, topicq9: Quality Risk Management, ICH, Geneva, Switzerland, 2005. 
• Purohit, k. V. Shah, Quality by design (QbD): new parameter for quality improvement & pharmaceutical 
drug development vol - 4, issue - 3, supl -1 apr-jul 2013 ISSN: 0976-7908 
• Yubing Tang , Quality by Design Approaches to Analytical Methods FDA Perspective, October 25, 
2011, FDA/CDER/ONDQAAAPS, Washington DC 
• R.Somma, “ Development Knowledge Can Increase Manufacturing Capacity and Facilitate Quality 
by Design” J.Pharm.Innov. 2, 87-92 (2007) 
• Naseem A et al, Quality by design approach for formulation development: A case study of dispersible 
tablets, International Journal of Pharmaceutics, December 2011. 
• Jun Huang, et al , Quality by design case study: An integrated multivariate approach to drug product and 
process development, International Journal of Pharmaceutics, 382 (2009) 23–32 
• Jessy Shaji and Shital Lodha Response Surface Methodology for the Optimization of Celecoxib Self-microemulsifying 
Drug delivery System , Indian J Pharm Sci. 2008 Sep-Oct; 70(5): 585–590 
10.4103/0250-474X.45395PMCID: PMC3038281
THANKYOU 
DR ANTHONY CRASTO 
amcrasto@gmail.com 
http://newdrugapprovals.org/

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Qbd by Anthony Melvin Crasto for API

  • 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
  • 15.
  • 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
  • 22.
  • 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.
  • 51.
  • 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.
  • 79.
  • 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.
  • 81.
  • 82.
  • 83.
  • 84.
  • 85.
  • 86.
  • 87.
  • 88.
  • 89.
  • 90.
  • 91.
  • 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.
  • 93.
  • 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
  • 99. •Jun Huan et al, Quality by design case study: An integrated multivariate approach to drug product and process development, International Journal of Pharmaceutics, 382 (2009) 23–32 •Chi –Wan Chen, Christine Moore ,Role of Statistics in Pharmaceutical Development Using Quality-by- Design Approach – an FDA Perspective, September 27 -29, 2006. • Lindsay I Smith A tutorial on Principal Components Analysis February 26, 2002 •Quality Risk Management (ICH Q9) EMA/INS/GMP/79766/2011. •Http://www.ceruleanllc.com/resources/published-articles-case-studies/#qbd • Spaceamit Mukharya et al, Quality risk management of top spray fluidized bed process for antihypertensive drug formulation with control strategy engendered by Box-behnken experimental design Int J Pharm Investig. 2013 Jan-Mar; 3(1): 15–28. •Http://www.ngpharma.com/article/PAT-and-qbd-in-pharmaceutical-development/ •Http://www.drugregulations.org/2012/08/qbd-for-beginners-design-space.html?Q=qbd, qbd for beginners part 4 , uday shetty •Glodek, M et al., Pharm. Eng 2006, 26, 1-11. •Rath, T, Strong, D.O., Rath & Strong's Six Sigma Pocket Guide. Lexington, AON Consulting Worldwide, MA 2002. •International Conference on Harmonization (ICH) of Technical Requirements for Registration of Pharmaceuticals for human use, topicq2 (R1): Validation of Analytical Procedures: Text and methodology, ICH, Geneva, Switzerland, 2005.
  • 100. • Juran, J.M. (1992) Juran on Quality by design – The New Steps for Planning Quality into Goods and Services,thefreepress • Pharmaceutical development - annex ICH harmonized tripartite guideline • Dr C. V. S. Subramanian, Quality by Design - Principles “, 29th Jan, 2013. • Http://en.wikipedia.org/wiki/Quality_by_Design • PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing, and quality assurance, September 2004, http://www.fda.gov/cder/guidance/6419fnl.pdf. • Guidance for industry Q8(R2),pharmaceutical development , November 2009,ICH revision 2 • Innovation and continuous improvement in pharmaceutical manufacturing pharmaceutical cGMP for the 21st Century, U.S. Food and Drug Administration, 2004 September, Available from: URL:http://www.fda.gov/cder/gmp/gmp2004/manufsciwp.pdf. • Ashwini Gawade1 et al , Pharmaceutical Quality by Design: A New Approach in Product Development., ISSN: 2320-1215 Research and Reviews: Journal of Pharmacy and Pharmaceutical Sciences • International Conference on Harmonization (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use, topicq9: Quality Risk Management, ICH, Geneva, Switzerland, 2005. • Purohit, k. V. Shah, Quality by design (QbD): new parameter for quality improvement & pharmaceutical drug development vol - 4, issue - 3, supl -1 apr-jul 2013 ISSN: 0976-7908 • Yubing Tang , Quality by Design Approaches to Analytical Methods FDA Perspective, October 25, 2011, FDA/CDER/ONDQAAAPS, Washington DC • R.Somma, “ Development Knowledge Can Increase Manufacturing Capacity and Facilitate Quality by Design” J.Pharm.Innov. 2, 87-92 (2007) • Naseem A et al, Quality by design approach for formulation development: A case study of dispersible tablets, International Journal of Pharmaceutics, December 2011. • Jun Huang, et al , Quality by design case study: An integrated multivariate approach to drug product and process development, International Journal of Pharmaceutics, 382 (2009) 23–32 • Jessy Shaji and Shital Lodha Response Surface Methodology for the Optimization of Celecoxib Self-microemulsifying Drug delivery System , Indian J Pharm Sci. 2008 Sep-Oct; 70(5): 585–590 10.4103/0250-474X.45395PMCID: PMC3038281
  • 101. THANKYOU DR ANTHONY CRASTO amcrasto@gmail.com http://newdrugapprovals.org/

Editor's Notes

  1. 30 years after implementation of 210, 211… “This guidance describes a comprehensive quality systems model, which, if implemented, will allow manufacturers to support and sustain robust, modern quality systems that are consistent with CGMP regulations.“ Quality professionals are aware that good intentions alone will not ensure good products.