Quality by design approach: Regulatory need

4.1.1 Define an objective

Quality target profile (QTP) forms the basis of QbD, which is in relation to the predefined objective criteria mentioned in the definition of QbD.

As per ICH guideline Q8 R2 the Quality Target Product Profile forms the basis for design and the development of the product. Considerations for the Quality Target Product Profile could include:

• Intended use in clinical setting, route of administration, dosage form, delivery Systems.

• Dosage strength(s), Container closure system.

• Therapeutic moiety release or delivery and attributes affecting, Pharmacokinetic characteristics (e.g., dissolution, aerodynamic performance).

• Drug product quality criteria like sterility, purity, stability and drug release as appropriate for dosage form the intended for marketing.

QbD requires a Target Product Profile; it may be called as Quality Target Product Profile (QTPP) which defines the expectations in final product. In case of analytical method development it is called as analytical target profile (ATP), it is also called as Target Product Profile (TPP). The TPP can play a central role in the entire drug discovery and development processes like optimization, planning and decision making, and designing of clinical research strategies (Lawrence, 2008). The Target Product Profile (TPP) can be used to design the clinical trials, safety and ADME studies, as well as to design the drug product. The TPP will help to identify critical quality attributes such as potency, purity, bioavailability or Pharmacokinetic profile, shelf-life, and sensory properties (Vince et al. (2011a)).

4.1.2 Determination of critical quality attributes.(CQA)

According to ICH Q8 R2 “A 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”. CQAs are generally linked with the drug substance, excipients, intermediates (in-process materials) and drug product. For example CQAs of solid oral dosage forms are typically those aspects affecting product purity, strength, drug release and stability whereas for parentrals they are Sterility and clarity. The CQAs can additionally include properties like particle size distribution, bulk density that affect drug product. Mostly CQAs are derived from the Quality Target Product Profile and/or prior knowledge is used to guide the product and process development and Subsequently CQAs are accessed for risk management.

It is stated in ICH Q9 that in case of Potential drug substance CQAs are used to guide process development. Inclusion and exclusion in list of potential CQAs can be done as knowledge drug substance and process understanding increases. In case of biotechnological/biological products, most of the CQAs of the drug product are associated with the drug substance and thus are a direct result of the design of the drug substance or its manufacturing process. Impurities are an important class of potential drug substance CQAs. A quality attribute that must be controlled within predefined limits to ensure that the product meets its intended safety, efficacy, stability and performance. It means all the factors which affect final quality and safety should be controlled.

Dissolution test is crucial for a controlled release drug product and on other hand dissolution test for an immediate release drug product which belongs to the high aqueous solubility and high permeability i.e. BCS class I drug will not prove as critical attribute for quality control viewpoint (Vince et al. (2011a)). CQA differs for type process, dosage form, and type of method development hence thorough knowledge of real time data to working scientists is important.

4.1.3 Risk assessment

It is commonly understood that risk is defined as the combination of the probability of occurrence of harm and the severity of that harm. Risk assessment helps to increase quality of method or process. Also it is determinant for effect of input variable on method or processes. From risk assessment one can recognize critical attributes that are going to affect final quality of product. A risk assessment is helpful for effective communication between FDA and industry, research/development and manufacturing and among multiple manufacturing sites within company (Patricia, 2007). There may be risk and uncertainty in validation of bioanalytical method though the guidelines for validation are given by various regulatory bodies there may be a variation in interpretation of those guidelines and hence in experimental method designing which leads to unfit method development for intended purpose (Rozet et al., 2010). Risk management for excipients to determine shelf life can be done by statistical parameters (Harry and Lanju, 2012).

Principles of quality risk management are:

• Scientific knowledge based evaluation of the risk to quality which eventually links to the protection of the patient.

• Adequate effort should be taken; formality and documentation of the quality risk management process should be done with the level of risk involved.

Risk management is joint responsibility of quality unit, business development, engineering, regulatory affairs, production operations, sales and marketing, legal, statistics and clinical department.

Methods of risk assessment: Some methods of risk assessment are mentioned in ICH guideline Q9 as follows:

• Failure Mode Effects Analysis (FMEA);

• Failure Mode, Effects and Criticality Analysis (FMECA);

• Fault Tree Analysis (FTA);

• Hazard Analysis and Critical Control Points (HACCP);

• Hazard Operability Analysis (HAZOP);

• Preliminary Hazard Analysis (PHA);

• Risk ranking and filtering;

• Supporting statistical tools.

ICH guideline Q9 gives description of risk management and various terminologies associated with it, like Risk Acceptance, Risk Analysis, Risk Assessment, Risk Communication, Risk Control, Risk Evaluation, Risk Identification, and Risk Management. Quality management policies should mention procedures and practices to the tasks of assessing, controlling, communicating and reviewing risk. Risk Reduction is actions taken to lessen the probability of occurrence of harm and the severity of that harm.

4.1.4 Development of experimental design

Experimental design is the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality. Design space is proposed by the applicant and is subject to regulatory assessment and approval of ICH Q8 (R2). Pharmaceutical development scientists have began making use of computer-aided process design (CAPD) and process simulation to support process development and optimization of manufacturing. (Lawrence, 2008) Risk assessment can guide to understand linkage and effect of process parameters and material attributes on product, and ranges for variables within which consistent quality can be achieved. These parameters or attributes are selected for addition in the design space. Information regarding reason for inclusion of some variables in design space as well as exclusion of other variable has to be mentioned. Operation within the design space will result in a product meeting the defined quality. Independent design spaces for one or more unit operations can be applied; a single design space can be applied for multiple operations. For example impact of excipient variability on particle size distribution, blend segregation propensity can be included in experimental design (Joseph et al., 2011). Gel was prepared using QbD approach, the design space used was developed by a D-optimal design from a total of 15 gel batches, with five factors ethanol, water, carbomer, acid neutralized fraction, and reactor temperature (Juan et al., 2011a,b). Different mathematical models are available for design of experiment like Placket–Burman, Box Behnken, Taguchi, Surface Design, Full and fractional factorial designs. Full factorial design was used to study the effect of formulation factors on pharmaceutical properties of tablet; in that independent variables were binder and disintegrant concentration, resistance to crushing while dependant variable was drug release. Such a multidisciplinary approach is beneficial as manufacturing process improvement can be done in previously approved space; it decreases number of variation after marketing. It is a risk based approach which is based on timely quality control rather than final testing of finished product (Ivan et al., 2012).

4.1.5 Designing and implementing control strategy

Control strategy is required to ensure that material and process are within the expected lower and upper limits. Parameter and material are routinely controlled during production in order to assure reproducibility. The control space should be within the design space. Generally scale up is trial and error basis. During scale up processes parameters may differ but attributes which affect quality remain the same hence control strategy is required (Lawrence et al., 2009). QbD gives trace on reproducibility and robustness. Process capability index expresses reproducibility of process.

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Figure 1

Control space within the design space.

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4.1.6 Continuous improvement throughout product life cycle

Product quality can be improved throughout the product lifecycle; companies have opportunities to opt inventive approaches to improve quality. Process performance can be monitored to make sure consistency in quality. Additional experience and knowledge is gained during routine manufacture which contributes to method/process development. Periodic maintenance can be done within a company’s own internal quality system; but design space should be unchanged. The QbD approach avails the continuous improvement throughout products’ life cycle this is distinguishing point from the conventional method which is much frozen process.

5.1.1 Analytical target profile (ATP)

“QbD is a systematic approach to product and process design and development,” (Patricia, 2007). Hence it begins with determination of goal or method intent. In this emphasis is given on the product and process understanding (Mark et al., 2010). ATP is way for method development or it is simply a tool for method development. It describes the method requirements which are expected to be measured. In general the goal of the chromatographic method is separation, quantification and identification of drug substance, impurity or degradents. Impurity is considered to be the critical quality attribute (CQA) (Peter and Bernard, 2008). While dealing with traces of impurities it will be beneficial to have knowledge of previous synthetic and manufacturing processes and all other possible pathways which lead to the encounter of impurities (Yan et al., 2012). The method requirements will be the accuracy precision, robustness, ruggedness and so on as described in ICH guideline (Phil et al., 2007). Whether it is a conventional method or QbD method detailed information of compound should be collected like its solubility, p^ka, p^H, UV chromophore, and stability. Yan et al. (2012) stringent method goals can be set to obtain a best method. It provides framework to method development which helps for further planning. It decides what to be measured and within what limit it is required to be measured. ATP is in complete accordance with ICH guideline.

5.1.2 Method design

Method design is prepared for appropriate availability of material and setting various experimental conditions. In this the reagents required are made available. Regional and geographical conditions are taken into consideration. Feasibility of instruments is checked and experimental design is prepared. In this use of various flowcharts decision tree can be made for correct implementation. In case of HPLC method development scouting is done. In this large number of experimental conditions were tried (p^H, temperature, columns, and buffers) (Devesh and Smita, 2011). Data are collected and software is generated by entering obtained results in terms of values from actual experiments. Then that data base is generated which helps to predict the effect of various chromatographic conditions in large number. This type of software helps to predict outcome without actual experimentation. Response from design also includes resolution and run time (Frederick and Alireza, 2011). Hence it is cost effective as well as time effective. Software also assists the future changes in method. Method design also involve selection of different analytical techniques that can be used for particular method development; for example different instrumental method that can be opt like HPLC, LC, Raman and the most effective method amongst is chosen. Among various methods; suitable method to serve the desired purpose is chosen. For example, to determine impurities, HPLC with detector like PDA can be used. In method design, method that meets method requirement is established. Method design may be repeated or modified as and when required throughout the life cycle. Thorough understanding of design intent will form a better Method design. Method design should be done according to standardized approach. This approach helps in method transfer step from research to quality control department. Method development strategy (MDS) includes design of experiments (DoE) (Frederick and Alireza, 2011). It is helpful in risk assessment by gaining knowledge about existing method and allows for effective control strategies for critical parameter. K.E. Monks and et al. present a novel approach to applying Quality by Design (QbD) principles to the development of high pressure reversed phase liquid chromatography (HPLC) methods. They developed a good, robust method for the separation of nine model compounds of pharmaceutical interest in a multidimensional space comprised of four critical parameters: gradient time, temperature, pH of eluent and stationary phase. The criteria of separation success are maximum resolution, maximum robust tolerance windows and minimum run time. In this paper three dimensional experimental designs for optimization of method are given (Monks et al., 2011). Method design is made considering the ICH guidelines for validation hence validation remains formality.

Various experimental design methods are mentioned in the literature. An experimental design is an experimental set-up to simultaneously evaluate several factors at given numbers of levels in a predefined number of experiments. Experimental designs are as follows,

• full factorial,

• fractional factorial,

• Plackett–Burman designs (Bieke and Yvan, 2011).

5.1.3 Critical quality attributes (CQA)

Factors which directly affect the quality & safety of the product are first sorted out, and its possible effect on method development is studied. Understanding of the product and method will help to sort the CQA. If drug product contains the impurity which may have direct effect on quality and safety of drug product it is being considered the critical quality attribute for the HPLC method development of that particular drug compound. Safety and efficacy can be achieved by demonstrating measurable control of quality attributes i.e. product specification, intermediate specification, and process control (Mark et al., 2010).

5.1.4 Risk assessment

It is link between input process variable and CQA. Various tools for risk assessment are,

1. Ishikawa or fishbone diagram,

2. Failure mode effect analysis (FMEA),

3. Pareto analysis.

An Ishikawa or fishbone diagram is used to identify all potential variables, such as raw materials, instrumental factors, and environmental factors, which can have an impact on a particular CQA. A FMEA can then be used to rank the variables based on risk (i.e. a combination of probability, severity, and delectability) and to select the process parameters with higher risks for further studies to gain greater understanding of their effects on CQAs (Patricia, 2007. Main aim of chromatographic method development is separation and identification of compound. In QbD approach the emphasis is given on rugged and robust method through risk assessment. Risk based approach is based on the ICH guideline Q8 and Q9. Small changes in method parameter like reagents, instruments, analyst, laboratories, days, temperature, and humidity are included in risk assessment. Available tools for analysis of data are Design of Experiments (DoE) and Method System Analysis (MSA). If the primary method fails, then a backup method is risk-assessed until a suitable method is identified. If both methods are challenging each other in advantages then methods are weighed against robustness and ruggedness for choosing best method. The other factors known as risks during the risk assessment can be tested by ruggedness studies, or, to by tested robustness studies. Method which is insensitive to small variations in parameters like instrument settings is robust, whereas a rugged method is one that can bear any noise likely to be encountered during use. The risk assessment approach differs from the older non-QbD approach. Each and every step starting from sample preparation including dilution, extraction is analysed for possible risk involved in it. A fishbone diagram is divided into categories like instrumentation, materials, methods, measurements, laboratory climate, and human factors. Once the risk is assessed it is grouped into three categories.

1. High-risk factors that should be stringently controlled, typical high-risk factors that can be fixed at the time of method development that includes data analysis methods and sample preparation methods.

2. Potential noise factors,

3. Factors that can be explored experimentally to determine acceptable ranges.

For impurity profiling by HPLC method staggered cross nested design was used and for Karl Fisher Titration (KFT) Method System Analysis (MSA) was found to be useful. Design of experiment was done for the robustness studies (Frederick and Alireza, 2011).

5.1.5 Method qualification

Once the method is designed keeping analytical target profile (ATP) in mind with taking care of the risk involved in development, the next step comes is method qualification this is to ensure that method is being performed as intended. It involves equipment qualification which is part of method qualification. It is divided in, method installation qualification (MIQ), method operational qualification (MPQ), and method performance qualification (MPQ).

For demonstration of instrumental qualification HPLC instrument is considered. While developing a chromatographic method on HPLC following qualification can be done (Lukas et al., 2010; Phil et al., 2007). Design Qualification

1. Installation Qualification

2. Operational Qualification

3. Performance Qualification

Considering user requirement specifications (URS), design and technical specification of an instrument are defined, it is part of DQ. As HPLC is commercial-off-the-shelf system in this case the users should make sure that the instrument is suitable for their desired applications. User must confirm that the installation site fulfill all vendor-specified environmental requirements. Here IQ part begins. Equipment is assembled at the user’s site and checked for proper working of all the assembled parts.

The combined parameters for operational qualification and performance qualification are given below in Table 1:

5.1.6 Control strategy

It is important that set method performs as intended and consistently gives accurate results, for that purpose control on method is required. A factor identified to have risk has to be controlled. More attention is given to the high risk factors. System suitability can be checked and verified time to time by having control over it (Phil et al., 2007). On ground of practical example; the risk assessment can also help identify a specific control strategy. For example, during robustness studies for an Atomoxetine hydrochloride HPLC impurity profile method, it was found that resolution of the impurities of interest followed the same trend when method parameters such as n-propanol and temperature were varied. As a result, an early eluting impurity pair was chosen for system suitability and became a convenient method control strategy because the two compounds involved were easily obtained (Peter and Bernard, 2008; Frederick and Alireza, 2011). Validation remains the formality it is done in similar way to that of traditional method development in validation (ICHQ2) but in traditional approach method validated after development i.e. it is like checkbox tool, and in QbD the validation parameter in ICHQ2 are consider as method intent.

5.1.7 Life cycle approach

Life cycle approach differs from that of the traditional approach of method development. According to Morefield it includes continuous improvement of method performance and the design space allow flexibility for Continuous improvement in analytical method can be done without prior regulatory approval because of design space made previously (Mark et al., 2010). Knowledge gained from risk assessment and data collected from design of experiments can be used as the repository of knowledge to make justified changes wherever required. A complete process analytical method development in QbD environment is summarized in the following flow chart (see Fig. 2).

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Figure 2

Analytical method development in QbD.

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6.1.1 In determination of impurity

Gavin gives a quality by design approach to impurity method development for atomoxetine hydrochloride. An ion-pairing HPLC method was developed and associated system suitability parameters for the analysis of atomoxetine hydrochloride are studied. Statistically designed experiments were used to optimize conditions and demonstrate method robustness for the separation of atomoxetine and impurities. Weiyong Li describes a three-step method development/optimization strategy for HPLC assay/impurity methods for pharmaceuticals i.e. multiple-column/mobile phase screening, further optimization of separation by using multiple organic modifiers in the mobile phase, and multiple-factor method optimization using Plackett–Burman experimental designs. Commercially available chromatography optimization software, DryLab was used to perform computer simulations. This approach significantly reduces the number of runs in method development. When satisfactory separation was obtained, a method optimization is done with Plackett–Burman experimental designs (Weiyong and Henrik, 2003).

Peter et al. (2010a,b) given A QbD with Design-of-Experiments Approach to the Development of a Chromatographic method for the Separation of Impurities in Vancomycin using specialized software with UPLC® Technology. Traditional HPLC gradient methods have capability to separate out 13 of these impurities, while the use of QbD approach with sub-2-pm ACQUITY UPLC Column separation of as many as 26 impurities could be possible.

6.1.2 In screening of column used for chromatography

Connie et al. (2009) describes the particulars of the experimental design, evaluation criteria used and some of the most commonly used analytical columns from reputed column manufacturers. A systematic approach is used to evaluate seven RP-HPLC columns against predefined performance criteria. This approach is a fundamental part of a QbD method development. The data generated for commonly used columns provide help to practicing analyst to meet challenge of developing robust and rugged methods for use in a QbD environment. Recently better selection of column has been explored in UPLC using quality by design (Kormány et al., 2013).

6.1.3 In development of HPLC method for drug products/substances

Monks et al. (2011) presents a novel approach to applying quality by design (QbD) principles to the development of high pressure reversed phase liquid chromatography (HPLC) methods. Four common critical parameters in HPLC – gradient time, temperature, pH of the aqueous eluent, and stationary phase are evaluated within the quality by design framework by the means of computer modelling software and a column database. David et al. (2012) worked on Application of quality by design elements for the development and optimization of an analytical method for protamine sulphate. A robust method was developed. A Box–Behnken experimental design with response surface methodology was then utilized to evaluate the main, interaction, and quadratic effects of these three factors on the selected responses. Method requirements applied to the optimized conditions predicted peak resolutions between 1.99 and 3.61 and tailing factor between 1.02 and 1.45 for the four peptide peaks of protamine sulphate (David et al., 2012).

6.1.4 In capillary electrophoresis

Yi-Hui et al. (2007) worked on Experimental design and capillary electrophoresis for simultaneous analysis of arbutin, kojic acid and hydroquinone in cosmetics. Statistical parameters were used to optimize method.

6.1.5 In stability studies

Karmarkar et al. (2011) reported an application of quality by design (QbD) concepts to the development of a stability indicating HPLC method for a complex pain management drug product containing drug substance, two preservatives, and their degradants are described. The initial method lacked any resolution in drug degradant and preservative oxidative degradant peaks, and peaks for preservative and another drug degradant. The method optimization was done using Fusion AE™ software that follows a DOE approach. The QbD based method development enabled in developing a design space and operating space with particulars of all method performance characteristics and limitations and method robustness within the operating space.

6.1.6 In UHPLC

Szabolcs et al. (2009) developed Rapid high performance liquid chromatography with high prediction accuracy, with design space computer modelling, which demonstrates the accuracy of retention time prediction at high pressure (enhanced flow-rate) and shows that the computer-assisted simulation can be useful with enough precision for UHPLC applications.

6.2.1 In LC–MS method development

Joseph Turpin gives the QbD approach to liquid chromatographic method development. The article is divided in three parts which includes current approaches to column screening in terms of experimental region, knowledge space, design space coverage, data treatments to quantitation of the column screening experiment, and quantitative method robustness estimation. Parameters are classified in two types depending upon their influence on separation; (1) Primary effectors of separation are column type (column screening), pH, organic solvent type, and Gradient Time (Controls Slope) (2) Secondary effectors of separation are pump flow, gradient conditions, temperature, and ion pairing agent (Joseph, 2012; Peter et al., 2010a,b).

6.5.1 In handling complex spectroscopic data

Zengping et al. (2011) in his review focused on Process analytical technologies and real time process control of some spectroscopic issues and challenges for purpose of process understanding. Process analytical technologies (PAT) are more and more being discover and adopted by pharmaceutical and biotechnology companies. To reach this goal there is a need to extract the detail information, and gain knowledge from complex spectroscopic data. A number of new approaches are shown to overcome the limitations of existing calibration/modelling methodologies and describe a practical system which would improve robustness of the process control system and overall control strategy.

6.5.2 In mass spectroscopy

Lianming and Frederick (2012) in their review of recent advances in mass spectrometric methods for gas-phase chiral analysis of pharmaceutical and biological compounds explain Practical projection and existing challenges in quantitative chiral MS techniques for QbD (Quality-by-Design) based pharmaceutical applications.

6.5.3 In near infrared

Mark (2011) has presented a review on Quality-by-Design (QbD) Approach to Quantitative Near-Infrared Continuous Pharmaceutical Manufacturing. Krause (2009) in his review on QbD for Analytical Methods describes elements of QbD principle in relation with analytical methods.

7.1.1 In modified release products

André et al. (2011) in his review of Pharmaceutical Equivalence by Design for Generic Drugs: Modified-Release Products describes quality by design initiative (QbD) provides an enhanced evaluation of equivalent drug approach by introducing the concept of a Quality Target Product Profile (QTPP). The concept of “pharmaceutical equivalence by design”, for modified-release generic drug products is illustrated in this article.

Joseph et al. (2011) studied A Quality-By-Design Study for a Roller Compactor. Immediate Release Tablet is used to examine the impact of inconsistency in excipient material properties on the quality attributes.

7.1.2 In sterile manufacturing

Warren (2009) presented details of the applying quality by design to sterile manufacturing processes.

7.1.3 In solid oral dosage form

Deliang and Yihong (2010) in their article, ‘Understanding Drug Properties in Formulation and Process Design of Solid Oral Products’, discuss scientific and technical principles associated Product and Process Design and development for pharmaceutical product. This approach is consistent with the basic principle of QbD.

Betterman et al. (2012) given A Tale of Two Drugs: How Using QbD Tools Can Enhance the Development Process. This article explains how Quality Target Product Profile, mapping, and risk assessment tools are used. A case study of comparison of a traditional development approach with a QbD enhanced approach of Tradium and Qbidium is explained.

7.1.4 Contribution of (SEM/EDX) to QbD by investigation of pharmaceutical materials

According to Jennifer et al. (2008) Scanning Electron Microscope (SEM/EDX) and microanalysis are used for the identification and analysis of pharmaceutical materials. Detailed observations and measurement of their microstructures can be done by SEM. Hence it can be used as a PAT tool in multi-disciplinary functions to contribute to QbD for process development and control in pharmaceuticals.

7.1.5 In gel manufacturing

Juan et al. (2011a,b) developed quality by design Approach of a Pharmaceutical Gel Manufacturing Process, by Near Infrared Monitoring of Composition and Physical Parameters gel by using the near infrared spectroscopy (NIRS) technique with multivariate chemometric tools. For this purpose, a D-optimal experimental design having normal operational condition (NOC) was used. McMahon, shares his experience of PAT and QbD in Understanding PAT and QbD. He says that PAT and QbD are only stations on the road to ultimate objective (Terry, 2010).

7.1.6 QbD for ANDAs

Robert et al. (2008) in his review discussed quality by design for generics and gives a summary of the key terminology.

7.1.7 In tableting process

Stephanie (2012) recently optimized the Tableting Process with a quality by design Approach. Critical quality attributes like powder properties and granulation are covered in this article.

Andrew Prpich worked on Drug product modelling predictions for scale-up of tablet film coating. He used two fundamental tablet film coating models in a quality by design (QbD) approach to determine the operating parameters for scale-up of Varenicline IR. Role of Design space fundamental of QbD in scale up is mentioned.

Defne et al. (2013) developed a Quality by design approach for wet granulation in pharmaceutical processing: Assessing models for a priori design and scaling.

Vince et al. (2011b) discussed the current status and prospective of role of quality by design (QbD). Experience of Pfizer with FDA’s recent chemistry manufacturing, and controls pilot and implementing QbD in its operations is shared.

Morten et al. (2008) applied quality by design for Spray drying of insulin intended for inhalation.

Recently quality by design approach for formulation development for dispersible tablets has been applied (Naseem et al., 2012).

7.1.8 Impact of genotoxic impurities on process development

A current review on ‘Overall impact of the regulatory requirements for genotoxic impurities on the drug development process’ discusses analytical assessment of genotoxic impurities and the regulations in the toxicological background for establishing limits. It overall light on genotoxic impurities concerns during the development of new drug substances (Antonio et al., 2011).

7.1.9 In co-precipitation process

Quality-by-Design (QbD) has been applied recently for a dynamic pharmaceutical co-precipitation process (Huiquan et al., 2009, 2011).

7.1.10 Nanosuspension preparation

Sudhir et al. (2009) worked on quality by design approach to understand the process of nanosuspension preparation.

Lynn (2011) says that in mid-1982 their team on a development project used a statistical tool and some approaches for optimization, today it is considered as a quality-by-design (QbD). He has presented a case study in which the project met its objectives and did it in fewer days than expected. The use of DOE resulted in a better understanding of critical parameters in his article of quality by Design Circa 1982.

7.1.11 In analysis of excipients and API

Angie and Patricia (2010) applied QbD to excipient formulation and development.

Anurag and Duncan (2010) presented Managing raw materials in the QbD paradigm, understanding risks. Better process and product understanding are the basic belief of quality by design (QbD). Advanced characterization and risk involved in manufacture of raw materials that are typically used in biotech processes are discussed in this article.

Yong et al. (2011) discussed interdependence of Drug Substance Physical Properties and Corresponding Quality Control Strategy. In quality by design (QbD) concept, active pharmaceutical ingredients (APIs) are considered as a critical component. The overall control strategy to ensure drug product quality is discussed.

7.2.1 In manufacturing of protein

Alex et al. (2012) reported application of the quality by design approach to the drug substance manufacturing process of An Fc fusion protein. Quality attributes of the product were evaluated for their potential impact on safety and efficacy using risk management tools.

Xiaoming et al. (2012) worked on application of quality by design to formulation and processing of protein liposomes. Quality by design (QbD) principles are used in research work to gain a complete understanding of the preparation of superoxide dismutase (SOD) containing liposome formulations prepared using freeze-and-thaw unilamellar vesicles.

7.2.2 In production and characterization of monoclonal antibody-

A systematic quality by design (QbD) strategy was used to develop and characterize a monoclonal antibody production process (Amit, 2010).

Sheryl et al. (2011) present a systematic approach to biopharmaceutical drug product development using a monoclonal antibody as an example.

7.2.3 For chromatographic technique used for purification

Anurag et al. (2011) give High-throughput tools and approaches for development of process chromatography steps which are used for purification of biotechnology products. Hence separation of the various entities that are present at the microbial fermentation or mammalian cell culture, stages of process development are focused. Contribution of QbD in biopharmaceutical is explained in review of High-throughput process development for biopharmaceutical drug substances by Bhambure et al. (2011).

7.2.4 PAT and QbD for biopharmaceutical

Jarka et al. (2011) presented review on Process analytical technology (PAT) for biopharmaceuticals. He has mentioned that a PAT forms a part of the quality by design (QbD) concept which provides tools to facilitate the quality. According to him number of analytical methodologies and tools referred as PAT tools are also useful for QbD.

7.2.5 In nanomedicine

Eniko˝ et al. (2010) worked on rational development of a stable liquid formulation for nanomedicine products. In this work some of the key steps that must be taken for the implementation of “Quality by Design” (QbD) approach for a biotech product are used.

7.2.6 Challenges and solution for application of QbD to biopharmaceutical

Anurag (2010) explains that manufacturing of biotech products involves the number of complex steps, hence there exist number of quality attributes to control, in his article Quality by Design for biotechnology products: challenges and solutions.