Quality by Design approaches to Analytical Method Development

Vedantika Das¹, Bhushan Bhairav¹, R. B. Saudagar²

¹Department of Quality Assurance, R.G. Sapkal College of Pharmacy, Anjaneri, Nashik.

²Department of Pharmaceutical Chemistry, R.G. Sapkal College of Pharmacy, Anjaneri, Nashik.

*Corresponding Author E-mail: vedantika19@gmail.com

ABSTRACT:

The concept of QbD to the analytical method development is as known AQbD (Analytical Quality by design).It is an informal in the pharmaceutical industry to perform analytical quality by design (AQbD) in method development activity as a part of risk management, pharmaceutical development, and pharmaceutical quality system. Testing of final product is not enough, but prominence is on ‘Total Quality Management’ through in-process testing and analysis is required today. The International Conference for Harmonization (ICH) has announced regulatory guidelines for pharmaceutical development.

KEYWORDS:.

INTRODUCTION:

Quality should be built in by design, it cannot be tested in a product, is the main precept of ‘Total Quality Management’. To attain this goal of reform quality product, the understanding information from pharmaceutical development studies and manufacturing provides the scientific background.

Quality by Design (QbD) ICH guidance Q8(R2) describes QbD as, “a systematic approach to pharmaceutical development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management”.

The scientific understanding gained during the method development process can be used to compose the method control elements and to manage the risks are recognized. The difference between Current approach and QbD shown in table no-1

Table no 1:- The difference between Current approach and QbD approach

QbD is all about designing an appropriate process and understanding process performance for the desired product performance. Major element in the overall scheme is continuous improvement, which in turn is based on the knowledge gained during process understanding. The concept drifts towards a ‘desired state’ marked with ‘regulatory flexibility’ focusing on scientific knowledge building, superior design, demonstration of performance, Quality Risk Assessment (QRM), Design of Experiments (DoE), Process Analytical Technology (PAT) tools, continuous improvement and learning, and life-cycle management.

In pharmaceutical development, it formally started with release of a guidance document entitled ‘Pharmaceutical cGMPs for the 21st Century: A Risk-Based Approach’, by USFDA in August, 2002. Since then, a lot has happened in pharmaceutical QbD area resulting in issue of multiple regulatory guidelines listed in table no-2

Analytical sciences are considered an integral part of pharmaceutical development. Analytical method and product development go hand in hand during the entire life cycle of any pharmaceutical product. The traditional approach of analytical method development is quite tedious owing to high degree of variability involved at each stage of method development. In order to eliminate the hiccups encountered during method development, the systematic QbD-based approach has slowly been permeating into the mind-set of analytical scientists. Accordingly, efforts have been made to extend QbD approach to analytical method development, endeavoring for understanding the predefined objectives to control the Critical Method Variables (CMVs) affecting the Critical Method Attributes (CMAs) to achieve enhanced method performance, high robustness, ruggedness and flexibility for continual improvement.

Table No: 2List of QbD related activities

Agencies	Guidelines/Activities	Month Year
USFDA	Pharmaceutical cGMP for the 21st Century - A Risk-Based Approach: Second Progress Report and implementation Plan	Sep 2003
USFDA	Guidance for Industry: PAT - A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance	Sep 2004
USFDA	Pharmaceutical cGMP for the 21st Century - A Risk-Based Approach: Final report	Sep 2004
EMA	The European Medicines Agency Road Map to 2010: Preparing theGround for the Future	March 2005
ICH	Pharmaceutical Development (Q8)	Nov 2005
ICH	Quality Risk Management (Q9)	Nov 2005
ICH	Pharmaceutical Quality System	June 2008
ICH	Pharmaceutical DevelopmentQ8(R2)	Aug 2009
WHO	Quality Risk Management	Aug 2010
EMA	Road map to 2015	Dec 2010
USFDA	Guidance for Industry: Process Validation: General Principles and Practices	Jan 2011
EMA-USFDA	EMA-FDA pilot program for parallel assessment of Quality by Design applications	March 2011
ICH	ICH-Endorsed Guide for ICHQ8/Q9/Q10 Implementation	DEC 2011
EMA	ICH Quality IWG Points to consider for ICH Q8/Q9/Q10 guidelines	Feb 2012
EMA	Guideline on Real Time Release Testing(formerly Guideline on ParametricRelease)	March 2012
EMA	Guideline on Process Validation (draft)	March 2012
USFDA	Quality by Design for ANDAs: An Example for Immediate-Release Dosage Forms	April 2012
ICH	Development and Manufacture of Drug Substances (Chemical Entities &Biotechnological/Biological entities) (Q11)	May 2012
EMA-USFDA	EMA-FDA pilot program for parallel assessment of Quality-by-Design applications: lessons learnt Q&A resulting from the first parallel Assessment	Aug 2013
EMA	Guideline on process validation for finished products - information and data to be provided in regulatory submissions	Feb 2014

Benefits of Analytical QbD:

· Increased understanding and control

· Beyond traditional ICH procedure of method validation

· Flexibility in analysis of API, impurities in dosage forms, stability samples, and metabolites in biological samples

· Reduction in variability in analytical attributes for improving the method robustness

· To keep the values of analytical attributes within the pharmacopoeia monographs, and away from Out Of Specification (OOS) limits

· Smooth process of method transfer to the production level

· No requirement of re-validation within MODR

QbD Principles for Analytical Method Development:

To ensure the quality product analytical method should also be in unison with the QbD and PAT. Thus, due stress should also be laid on regulatory guidelines for AQbD describing the development of method as per DoE including risk management and details of quality systems required.

Proposed key definitions for AQbD (Tang, Yubing, 2014 and Chatterjee, Sharmista, 2013):

According to ICH Q8, main terminology used in the process optimization are Quality Target Product Profile (QTTP), Design Space (DS) and Design of Experiments (DoE). The analogous terminologies for analytical method development used by quality experts are Analytical Target Profile (ATP), Method Operable Design Region (MODR) and Method Development Strategy (MDS).

Fig No- 1:Key definitions for AQbD

Mostly the QbD technique is applied to the broad arena of product development. This necessitates a discussion of application of Qbd to analytical techniques. The time has come to make the traditional analytical method obsolete and embrace the data driven and scientific approach of AQbD. The key concepts and activities associated with successful implementation of AQbD have been discussed below in a step-wise manner.

1. Creation of Knowledge Space:

The generation of knowledge space constitutes elementary ground work essential for designing quality into a product or the method. For the later, it starts with defining aim of the method and its applicability under various situation. Once this is known efforts to build-up knowledge space involve broad understanding 3C’s, i.e., contribution, correlation and consequences. Contributors mainly include, but are limited to ‘material attributes’ and ‘method parameters’. Contributors can be system attributes, risk assessment tools, and experimental design, etc., which could affect the consequences. Correlation among contributors and consequencess most important during risk assessment and data analysis. During data analysis, it directs for adequate selection of design model and representation of data, etc. Consequences are the effects of contributors on the system, method and quality attributes. With understanding of these, knowledge space is further strengthened as method development reaches to an end and the same is useful for deciding the control strategy and life cycle management

KNOWLEDGE SPACE

Fig no:2-Activities involved in the building knowledge space

2. Analytical Target Profile:

In AQbD, Analytical Target Profile (ATP) is similar to Quality Target Product Profile (QTPP) element in QbD. ATP is way for method development or it is simply a tool for method development and has been mentioned in the ICH Q8 R(2) guidelines. It describes the method requirements which are expected to be measured. Recently PhRM5A and EFPIA defined ATP as: “ATP is a statement that defines the method’s purpose which is used to drive method selection, design, and development activities.”[1] Another definition of ATP as given by USP council of experts in their stimuli article is, “the requirements for the “product” of the test procedure, which in this case is the reportable result” or “the objective of the test and quality requirements, including the expected level of confidence, for the reportable result that allows the correct conclusion to be drawn regarding the attributes of the material that is being measured”

It is basically, the combination of all performance criteria required for the intended analytical application that direct the method development process. An ATP would be developed for each of the attributes defined in the control strategy. The ATP defines what the method has to measure (i.e., acceptance criteria) and to what level the measurement is required (i.e., performance level characteristics, such as precision, accuracy, working range, sensitivity, and the associated performance criterion). The ATP requirements are general ones and associate with primarily to the intended purpose, not to a specific method. Any method conforming to the ATP is considered suitable, thus giving the process regulatory flexibility. The ATP can be regarded as the focal point for all stages of the analytical life cycle.

Applying QbD principles to analytical methods committed an organization to incorporate the best scientific practice by linking prior knowledge of techniques and methods to an ATP, a mechanistic understanding based on chemical and physical knowledge of the factors that influence method performance, an investigation of multivariate relationships across method factors and an understanding of how variation in these method factors affects the analytical result. This knowledge provides an insight into the contribution that variability in the method makes to the overall product and process variability, ensures a more focused method control strategy and provides a thorough understanding of the impact of planned method changes, all resulting in better methods in both their operation and outcome.

For the future, the ATP concept may be a means of proposing more advanced regulatory approaches to method submission and review. The ATP is defined with the help of knowledge and scientific understanding of the analytical process, which is where the role of knowledge space comes in.

3. Establishment of Analytical Target Profile (ATP):

The foundation of any analytical method developed through QbD principles is ‘ATP’, which is similar to Quality Target Product Profile (QTPP), as defined in ICH Q8 (R2). USP council of experts define ATP in their stimuliarticle as, “the requirements for the “product” of the test procedure, which in this case is the reportable result” or “the objective of the test and quality requirements, including the expected level of confidence, for the reportable result that allows the correct conclusion to be drawn regarding the attributes of the material that is being measured” [1]. ATP is not limited to method development only, but should also bemet during method transfer and also during lifecycle management. Also, ATP is not always limited to single method and more than one method/analytical technique can satisfy the same ATP. Moreover, one can always evaluate available methods to meet ATP. In case of compendia methods, monograph specifications and available performance understanding of the product can be used to establish the ATP [2]. ATP is a key parameter in AQbD that facilitates greater continuous improvement of analytical methods and their choice, once the regulatory authorities approve the ATP statement. In pharmaceutical industry, internal change control management system is responsible for effective implementation of ATP to provide regulatory flexibility [3, 4].

4. Identification of potential and critical method variables and attributes:

According to ICH Q9, risk assessment can be done in three steps, viz., risk identification, risk analysis and risk evaluation. Risk identification involves uncovering of all the Potential Method Variables (PMVs) and Potential Method Attributes (PMAs) including all aspects related to man, material, machine, method, environment and measurement. This can be done with the help of flowcharts and check lists, etc. Subsequently, PMV sare categorized according to their source of origin (by using fish bone diagram) or control required on these (by CNX approach). A simplified example of fishbone/Ishikawa or cause-effect diagram for purity/impurity LC method is depicted in

Fig 3:Ishikawa cause-and-effect fish-bone diagram for a liquid Chromatographic method development

5. Design-guided method development:

Application of DoE principles facilitates understanding of multiple method parameters and variables that tend to affect CMAs, while unravelling the prevalence of (any) interactions and reducing intricacies.

For the successful execution of DoE study, the knowledge of response variables or CMAs, CMVs, their ranges, and best fitting of the mathematical model (s) is obligatory. DoE-based Response Surface Methodology (RSM) is helpful in systematic development of analytical methods involving significant nonlinearity between CMV-CMA relationship (s) using diverse experimental designs like Factorial design, Central Composite design, Box-Behnken design, Optimal design, etc [5, 6]. The experimental designs help in mapping the responses on the basis of the studied objective(s), CMAs being explored, at high (coded as +1), medium (coded as 0), or low (coded as -1) levels of CMVs. It tends to unearth the mechanisticthe fruition of any DoE method depends upon several parameters especially the experimental accuracy and measurement precision. Accordingly, the best practice before validating a MODR would be to perform confirmatory validation runs to ratify the empirical model resulting from a DoE exercise [7].

7. Control strategy:

A planned set of control (s) for all possible variation (s) assures that ATP requirement would be met during analytical method transfer as well as routine use. This can be attained with continuous monitoring of CMAs or system suitability parameters. Control strategy is not always a one-time exercise that is performed only during method development, but it can get changed with different stages of method lifecycle [2]. It is noted that method control strategy of AQbD approach does not differ from the traditional control strategy. However, method controls need to be established to ensure relation between method purpose and method performance [8].

8. Continuous Monitoring/Lifecycle Management:

This follows the establishment of an analytical method for quality control or routine testing and is established by monitoring the method performance over the time to ensure that the method remains in compliance with the defined ATP criteria. In pharmaceutical industry, it is represented by using control charts or other tools to track system suitability data and method related investigations. This continuous monitoring allows an analyst to detect, identify, and address any abnormal or out-of-trend performance of the analytical method.

Regulatory Perspective of AQbD:

Analytical methods are the important part of the control strategy (ICH guidelines Q10).

Therefore, analytical methods are applied to the control strategy in the manufacturing process for ensuring the predetermined performance and product quality which includes the parameter and belongs to the drug substance, drug product materials components including facility, instrument operating conditions, finished product specification and method associated with it. Application of AQbD is expected to strengthen the concept of ‘right analytics at right time’ which plays a vital role in the drug product development cycle.

Table 3: Regulatory perspective; product QbD versus analytical AQbD.

Stage	Qbd	AQbD
Stage 1	Define quality target product profile (QTPP)	Define analytical target profile (ATP
Stage 2	Critical quality attributes	Critical quality Attributes
Stage3	Risk assessment	Risk assessment
Stage4	Design space	Method operable design region
Stage 5	Control strategy	Control strategy
Stage 6	Life cycle management	Life cycle Management

Table 4-Role of analytical method in pharmaceutical testing and control strategy:

Sr. No	Pharmaceutical testing	Control strategy
1	Raw material testing	· Specification based on product QTPP and CQA · Effects of variability, including supplier variations, on process and method · development are understood · 2 In-process testing
2	In-process testing	· Real time (at-, on-, or in-line) measurements · Active control of process to minimize product variation · Criteria based on multivariate process understanding
3	Release testing	· Quality attributes predictable from process inputs (design space) · Specification is only part of the quality control strategy · Specification based on patient needs (quality, safety, efficacy, and performance
4	Stability testing	· Predictive models at release minimize stability failures · Specification set on desired product performance with time ion purpose only

Implementation of QbD:

QbD can be applied equally to processes and analytical. It displays how QbD for methods, analytical methods is driven by the overall process. Fundamental to any method development is being clear about the design intent of the method. Method-performance criteria and method-operational intent are two important aspects of this design intent. [10]

Fig No 4: Analytical QbD approach

CQAs are identified, through a thorough understanding of those characteristics of a drug substance or a drug product that may need to be controlled to ensure the safety or efficacy of a product. For methods measuring these CQAs, criteria, such as the following, would need to be met.

· Precision—the need for method variability to be a small proportion of the specification,

· Selectivity—being clear on which impurities actually need to be monitored at each step in a process and ensuring adequate discrimination between them.

· Sensitivity-ensuring the method is sufficiently sensitive relative to the specification limit.[11]

PAT methods often meet the criteria above in a different way from traditional end-point testing methods such as high-performance liquid chromatography (HPLC). Selectivity, for example, may be achieved through a multivariate model as opposed to resolution between adjacent peaks in an HPLC method. For these methods, precision could be demonstrated by checking the prediction validity of the model.

Method operational intent:

These criteria address the aspects of the method that are required to facilitate ease of use in routine operation (e.g., analysis time, acceptable solvents, and available equipment). Opportunities for the implementation of improved or new technology also may be identified. These criteria can be generated by performing an analysis of the voice of the customer (VoC) (i.e., the aspects of a method that are considered important for the quality control laboratories within manufacturing where the commercial methods will be operated). [12]

Method development (design selection):

Fundamental to design selection is the method-development phase. To develop a QbD method, the method performance criteria must be understood as well as the desired operational intent that the eventual end user would wish to see in the method.

Application of QbD in analytical methods of measurement:

QbD can be applied for various analytical method Chromatographic techniques like.[13]

· HPLC (For stability studies, method development, and determination of impurities

· Hyphenated technique like LC–MS

· Advanced techniques like mass spectroscopy, UHPLC,

· Capillary Electrophoresis

· Karl Fischer titration for determination of moisture content

· Vibrational spectroscopy for identification and quantification of compounds e.g. UV

· Analysis of genotoxic impurity.

· Dissolution studies.

· To biopharmaceutical processes.

Elements of QbD to analytical method:

In determination of impurity:

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. 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, Dry Lab was used to perform computer simulations.

In screening of column used for chromatography:

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.

In development of HPLC method for drug products/substances:

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. [14]

In stability studies:

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 degradants and preservative oxidative degradants peaks, and peaks for preservative and another drug degradants. 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.

In UHPLC:

Rapid high performance liquid chromatography with high prediction accuracy, with design space computer modeling, 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.

Opportunities of and barriers against a QbD approach to analytical methods [16,17]:

Several opportunities of this QbD approach to analytical methods, including:

· Methods will be more robust and rugged, resulting in fewer resources spent investigating out-of-specification results and greater confidence in analysis testing cycle times.

· Resources currently invested in performing traditional technology transfer and method validation activities will be redirected to ensuring methods are truly robust and rugged

· The introduction of new analytical methods—from research and development to quality control laboratories—using a QbD approach will lead to a higher transfer success rate than with traditional technology-transfer approaches

· Specified process will help the systematic and successful implementation of the QbD methodology and fosters a team approach.

· A true continuous learning process is established through the use of a central corporate knowledge repository that can be applied across all methods.

· By registering only a commitment to ensure method changes meet the registered method performance criteria, flexibility to continuously improve methods can be achieved.

· Current expectations of analytical technology transfer and method validation must change because current validation guidance does not lead to methods that can always be reliably operated.

· Acceptance must be gained for registration of the method performance criteria rather than the method conditions.

· External guidance must be developed in this area; ICH guideline Q2 (R1) requires revision (or removal) and Center for Drug Evaluation and Research guidance must be created for analytical methods.

· A common language for some of the new terms is required, including analytical method design space, analytical method control strategy, and method performance criteria.

· Analysts must learn new tools and skills

· A consistent worldwide approach is required for this initiative to be effective.

REFERENCES:

1. EMA,http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2012/04/WC500125401.pdf

2. USP Validation and Verification Expert Panel, Lifecycle Management of Analytical Procedures: Method Development, Procedure Performance Qualification, andProcedurePerformanceVerification,http://www.usp.org/sites/default/files/usp_pdf/EN/USPNF/revisions/lifecycle_pdf.pdf. (Accessed on June 29, 2014).

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10. International Conference on Harmonisation (ICH) Tripartite Guideline, ICH Q1A(R2), February, 2003.

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15. Krull I, Swartz M, Turpin J, Lukulay PH, Verseput R. 2008.A quality-by-design methodology for rapid LC method development, part I. LCGC N Am 26:1190–1197

16. Janwitayanuchit W. Development of HPTLC method for determination of bromphenirami maleate and phenylphrine hydrochloride tablet. J Intern Pharm Sci, 2014; 06:106-109.

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Received on 08.06.2017 Modified on 07.07.2017

Research J. Pharm. and Tech. 2017; 10(9): 3188-3194.

DOI: 10.5958/0974-360X.2017.00567.4