Quality by Design (QbD) in api

Quality by Design (QbD) in api
DR ANTHONY CRASTO

“Quality can not be tested into products; it has to be built in by design”
The Quality Mantra 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

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 QbD Basic concept Steps in QbD DoE as a tool for QbD
Example Torcetrapib Pros and cons Conclusion

Quality Patient What is Quality? Requirements Target Product
= need or expectations Target Product Quality Profile Patient “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

Quality by Design – GMP for the 21st Century
INTRODUCED BY FDA IN 2002 ICH Q ICH Q 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

Product Knowledge Continuous Improvement Quality by Design
Process Understanding Product Knowledge Product Specifications Product Quality Attributes Process Controls Process Parameters Desired Product Performance Process Design Unit operations, control strategy, etc. Product Design Dosage form, stability, formulation, etc. Cpk, robustness, etc. Process Performance Quality by Design

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

Output / Result of the Quality Risk Management Process
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 Formal Risk Management Process 2. Risk Control Output / Result of the Quality Risk Management Process 4. Risk Review

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

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

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

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

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. Describes a comprehensive quality system model and how CGMP regulations link to QS elements 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. “When fully developed and effectively managed, a quality system will lead to consistent, predictable processes that ensure that 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
API Excipients Analytics Simple dosage forms Advanced drug delivery system Devices

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

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.

Quality Attributes Process Parameters y = ƒ(x) y
STEP 3. LINK THE DRUG AND EXCIPIENTS ATTRIBUTES AND THE PROCESS PARAMETERS TO THE CQAS Quality Attributes People Equipment Measurement Process Materials Environment Process Parameters Inputs to the process control variability of the Output I N P U T S (X) y = ƒ(x) y OUTPUT 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?

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?

CONTROL SPACE Design Space Knowledge 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 Experiment Factor A Factor B Factor C 1 + - 2 3 4 A B C (3) Analyze data (4) Create multidimensional surface model (for optimization or control)

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

Graphical Analysis Temp B - Time + A Geo-Gram: Square 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 50 41 47 Temp B Time A + - This defines the inference space or the experimental boundaries of your experiment within your process.

1a Contour plot Response surface plot

Pre-formulation studies
QbD Literature review Pre-formulation studies formulation QC and Evaluation 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

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

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

Polymorphism and the Effect on Bioavailability
Form I Form II Intestinal Membrane Solubility: Form II > Form I Dissolution/Solubility Limited Oral Absorption (e.g. chloramphenicol palmitate) Intestinal Membrane Gastric Emptying or Permeation Limited Oral Absorption (e.g. ranitidine HCl)

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 Paracetamol Form I I Paracetamol Form I Wet Granulation E. Joiris , Pharm. Res. 15 (1998)

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

Regulatory Considerations:
Can One Consider Polymorphs to be the Same Active? N O 2 H S C 3 “ ” Form I Form II Drug Product Safety/Effectiveness Materials Science J. Am. Chem. Soc. 122 (2000)

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 other applicable standard of identity, strength, quality, and purity, including potency. Same Active Moiety Different Active Ingredients Phosphate Sulfate FDA Regulatory Scheme: Pharmaceutical Alternatives No Possibility for Therapeutic Equivalence for Different Salts

Co-Crystals Polymorphs Co-crystals Salts
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?
Is a New Regulatory Class of Solids Needed? Salts Polymorphs Same Active Moiety Different API Same API

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 ( 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 preventcardiovascular 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 this change

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 , 2006. Lindsay I Smith A tutorial on Principal Components Analysis February 26, 2002 Quality Risk Management (ICH Q9) EMA/INS/GMP/79766/2011. 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. 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. PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing, and quality assurance, September 2004, 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: Ashwini Gawade1 et al , Pharmaceutical Quality by Design: A New Approach in Product Development., ISSN: 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: 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, (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 Sep-Oct; 70(5): 585–590 / X.45395PMCID: PMC

THANKYOU DR ANTHONY CRASTO

Quality by Design (QbD) in api

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