Quality by Design and Process Analytical Technology

Quality by Design and
Process Analytical
Technology
By Chandani Chandarana
Assistant Professor
SSR College of Pharmacy, Silvassa.
1/23/2020
1

What is QbD?
QbD (Quality by Design) is defined in the ICH Q8
guideline as “a systematic approach to development
that begins with predefined objectives and emphasizes
product and process understanding and understanding
and process control, based on sound science and
quality risk management”
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Requirement of QbD
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Current approch QbD approch
Quality is assured by testing and
inspection. Here, any specifications are
based on batch history. Here
Quality is built into product & process
by design and based on scientific
understanding.
It includes only data intensive
submission which includes disjointed
information without “big picture”.
It includes Knowledge rich submission
which shows product knowledge &
process understanding.
Here, any specifications based on batch
history.
Here, any specifications based on
product performance requirements.
Here there is “Frozen process,” which
always discourages changes.
It focuses on reproducibility which
often avoids or ignores variation.
Here there is Flexible process within
design space which allows continuous
improvement.
It focuses on robustness which
understands and control variation

Advantages of QbD
For industry
a) It helps in better understanding of the process.
b) It reduces batch failure.
c) It ensures better design of products with fewer problems in manufacturing.
d) It allows for continuous improvement in products & manufacturing process.
For FDA
a) It enhances scientific base for analysis.
b) It provides better consistency.
c) It provides more flexibility in decision making.
d) It ensures decisions are made on scientific base & not on obsereved
information. 1/23/2020
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A QBD DEVELOPMENT PROCESS MAY INCLUDE
 It is started with a target product profile that illustrates the use, safety
and efficacy of the product.
 Then, introduces a target product quality profile that the formulators and
process engineers use as a quantitative surrogate for aspects of clinical
safety and efficacy of the product during development.
 The collection of relevant prior knowledge about the drug substance,
potential excipients and process operations into a knowledge space is
also done.
 Application of risk assessment tools to prioritize knowledge gaps for
further investigation is necessary. e. Formulation of a design to find the
critical material (quality) attributes of the final product that is necessary
to be controlled to meet the target
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Also formulate the design of manufacturing process to produce a
final product having the required critical materials attributes.
Find out the critical process parameters and raw material
attributes that should be controlled to achieve these critical
material attributes of the final product.
Risk assessment must be used to prioritize process parameters
and material attributes for experimental verification.
Combination of prior knowledge with experiments is important
to establish a design space or other representation of process
understanding. 1/23/2020
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Making of a control strategy for the entire process that must
include raw material controls, process controls and monitors,
design spaces around individual or multiple unit operations,
and/or final product tests.
 The control strategy must encompass expected changes in scale
and can be guided by a risk assessment.
Monitoring and update of the process to assure consistent quality
continuously.
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Elements involved in QbD based product
development
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The Target Product Quality Profile (TPQP)
TPQP has been defined as 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 thus the safety and efficacy, of a drug product is realized”
This includes dosage form and route of administration, dosage form strength(s),
therapeutic moiety release or delivery and pharmacokinetic characteristics (e.g.,
dissolution and aerodynamic performance) appropriate to the drug product
dosage form being developed and drug product-quality criteria (e.g. sterility and
purity) appropriate for the intended marketed product. The concept of TPP in
this form and its application is novel in the QbD paradigm.
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Basis for product design
Dosage form
Route of administration
 Strength, maximum and minimum
 Release/delivery of the drug
Pharmacological characteristic
Drug product quality criteria
Pharmaceutical elegance
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Critical Quality Attributes
 Once TPQP has been identified, the next step is to identify the relevant CQAs.
 A CQA has been defined as “a physical, chemical, biological, or microbiological
property or characteristic that should be within an appropriate limit, range, or
distributed to ensure the desired product quality” Identification of CQAs is done
through risk assessment as per the ICH guidance Q9.
 Prior product knowledge, such as the accumulated laboratory, nonclinical and
clinical experience with a specific product-quality attribute, is the key in making
these risk assessments. Such knowledge may also include relevant data from
similar molecules and data from literature references.
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Decision tree for CQA
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CQA for drug substance and drug product
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 The use of robust risk assessment methods for identification of CQAs is
novel to the QbD paradigm CQAs of solid oral dosage forms are typically
those aspects affecting product purity,strength, drug release and stability.
 CQAs for other delivery systems can additionallyinclude more product
specific aspects, such as aerodynamic properties for inhaledproducts, sterility
for parenteral, and adhesion properties for transdermal patches.
 For drug substances, raw materials and intermediates, the CQAs can
additionallyinclude those properties (e.g., particle size distribution, bulk
density) that affect drugproduct CQAs.
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Critical Process Parameter
 Critical process parameters (CPPs) are defined as “parameters whose variability
have an impact on a CQA and therefore should be monitored or controlled to
ensure the process produces the desired quality”.
 Process robustness is defined as the ability of a process to demonstrate
acceptable quality and performance and tolerate variability in inputs at the same
time.
 To demonstrate the reproducibility and consistency of a process, process
capability should be studied. Process capability is a statistical measure of the
inherent process variability for a given characteristics.
 The most widely accepted formula for process capability is six sigma. Process
capability index is the value of the tolerance specified for a particular
characteristic divided by the process capability
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If the CpK is significantly greater than one, the process is defined
capable. If the process capability is low, there are five step procedures to
progressively reduce the variability of the process.
Define Measure Analyse Improve Control
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Quality Risk Assessment
 Quality risk management is a systematic process for the assessment,
control, communication and review of risks to the quality of the drug
(medicinal) product across the product lifecycle.
 The initial list of potential parameters which can affect CQAs can be
quite extensive but can be reduced and prioritized by quality risk
assessment (QRA)
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Overview of quality risk management process
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 QRA is a science based process that can aid identification of CPPs and thus
eliminating risk, resulting in high confidence that the analytical method will meet
the QTTP under all conditions of use.
 Thus, a large number of parameters can actually be safely eliminated by use of
QRA tools, for example failure mode effects analysis (FMEA) and Ishikawa
diagrams on the basis of prior knowledge and initial experimentation.
 In FMEA the variables are ranked on the basis of the likelihood failure will occur
(probability), affect on the pharmaceutical results (severity), and difficulty of
detection (detectability), resulting in a risk priority number (RPN).
 Factors with an RPN above a cut-off level can then be evaluated by subsequent
studies whereas factors with a lower RPN can be eliminated from further study.
Ishikawa diagrams segregate risks into different categories, for example those
associated with instrumentation, materials, methods, measurements, laboratory
climate, and human factors.
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 A fault tree analysis is used to link the potentially critical quality attribute “content
uniformity” to a potential failure mode and potential causes. Four main causes, i.e., raw
and intermediate material properties, processing parameters, equipment and design
parameters as well as environmental factors, and the associated sub-causes were
identified and afterwards systematically listed in an Ishikawa diagram
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Design Space
The ICH Q8(R2) States that the design space is 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.
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Design space is proposed by the applicant and is subject to
regulatory assessment and approval1. Design space is
potentially scale and equipment dependent, the design space
determined on the laboratory scale may not be relevant to the
process at the commercial scale.
Therefore, design-space verification at the commercial scale
becomes essential unless it is confirmed that the design
space is scale-independent
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Control Strategy
 The ability to evaluate and ensure the quality of in-process and/or final product
based on process data which typically include a valid combination of measured
material attributes and process controls. ICH Q8(R2).
 Control strategy is defined as “a planned set of controls, derived from current
product and process understanding that assures process performance and product
quality”. The control strategy in the QbD paradigm is established via risk
assessment that takes into account the criticality of the CQA and process
capability.
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 The control strategy can include the following elements:
 procedural controls, in process controls, lot release testing, process monitoring,
characterization testing, comparability testing and stability testing Particularly, the
control strategy may include:
 Control of raw material attributes (e.g., drug substance, excipients and primary
packaging materials) based on an understanding of their impact on process-ability or
product quality.
 Product specifications
 Procedural controls
 Facility controls such as utilities, environmental systems and operating conditions
Controls for unit operations that have an impact on downstream processing or end-
product quality (e.g. the impact of drying on degradation, particle size distribution of
the granulate on dissolution
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PAT Used in QbD
Online and Offline analysis design space
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A system for designing, analyzing and controlling manufacturing through
timely measurement of critical quality performance attributes of raw and
in process materials and processes with the goal of ensuring final product
quality.
Multidimensional combination of and interaction of input variables and
process parameters that have been demonstrated to provide Quality
Assurance
Linkage between process inputs (inputs variables and process
parameters) and critical quality attributes
 Proposed by Applicant
Working within the design space: not considered as a change

Online and Offline analysis design space
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Formulation by Design
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Process flow diagram for orally dispersible tablet
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Risk analysis of Critical Process Parameters
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AQBD
 Analytical Target Profile (ATP)
 This analytical procedure is capable of quantifying related substances in XYZ drug
product over the range of 0.1% (the reporting threshold specified in ICH Q3B) to 0.2%
(specification criterion). The accuracy and precision of the procedure are maintained as
reportable results fall within ± 0.02% of the true value with an 80% probability determined
with a 95% confidence when 0.1% to 0.2% related substances are measured.
 To satisfy the ATP above, analytical procedures are required to conform to the
“Performance criteria” shown below.
 Specificity: Not affected by the excipient components of the drug product, capable of
determining the target impurities specifically with sufficient discrimination capability.
 Sensitivity: The quantitation limit (S/N ratio is not less than 10) is not more than 0.1%.
 Range: In the range between 0.1% and 0.2%, reportable results fall within ± 0.02% of the
true value with an 80% probability determined with a 95% confidence.
 Other requirements Linearity: The analytical procedure shows linearity in the range
between 0.05% and 1.0%. The correlation coefficient of the regression equation is not less
than 0.99 and the regression line passes through the origin. 1/23/2020
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Analytical Procedure Development
 Selection of analytical techniques
 Physicochemical properties of the drug substance
 Formulation of the drug product
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 Characterization of impurities (Target impurities)
 Evaluation and determination of analytical techniques
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Analytical procedure design
 A screening study was carried out examining the organic
solvent (acetonitrile) ratio in the mobile phase, buffer pH, and
column temperature, the parameters known to have a
significant impact on peak retention and separation in HPLC
analysis.
 A detection wavelength of 220 nm was selected on the basis
of the already determined UV spectrum of XYZ drug
substance and the UV spectrum data for the target impurities.
 The analytical columns used were AAA, BBB, and CCC
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 An experiment was made in a 2-level full factorial design with three factors to develop
a multiple regression model for the number of peaks and the minimum resolution.
 AAA was selected as the analytical column because it produced the best peak shape.
Figure presents contour plots at column temperatures of 30°C, 35°C, and 40°C. The
red area in each contour plot represents the region within which the number of peaks
is less than 7 and all of the target impurities (Imps 1 to 6) are not separated from
each other.
 On the other hand, each blue area indicates the region within which the resolution
between the closest peaks is less than 1.5.
 It was predicted from the regression model that the number of peaks would be 7 or
more and the resolution between the closest peaks would be 1.5 or more in cases
where the acetonitrile ratio in the mobile phase would be about 40%, the buffer pH
about 7 to 8, and the column temperature about 40°C (white area).
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HPLC operating conditions Detector:
 An ultraviolet absorption photometer (detection wavelength: 220 nm).
 Column: AAA (4.6 mm ID × 150 mm, particle diameter 5 µm)
 Mobile phase: A mixture of borate buffer solution, pH 8.0 and
acetonitrile (60:40)
 Flow rate: Adjust the flow rate so that the retention time of XYZ is
about 15 minutes.
 Column temperature: A constant temperature of about 40°C.
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Primary risk assessment
 The performance of an HPLC analytical procedure for impurities is greatly
characterised by its specificity, namely, separation performance. Thus, factors
considered to affect separation performance were extracted and compiled into a
cause and effect diagram as presented in Figure 3. For each factor, more detailed
factors were extracted and classified according to respective characteristics as
shown in Table 1. The assessment was carried out by utilizing the findings gained
in the initial screening study and the general knowledge and the experience
regarding the analytical technique.
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Experimental evaluation
 HPLC operating conditions
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1/23/2020
58 HPLC operating conditions
• Detector: An ultraviolet absorption photometer
(detection wavelength: 220 nm)
• Column: AAA (4.6 mm ID × 150 mm, particle diameter: 5
µm)
• Mobile phase: A mixture of borate buffer, pH 8.0, and
acetonitrile (55:45)
• Flow rate: A constant flow rate of 1.0 mL/min
• Column temperature: A constant temperature of about
39ºC Sample injection volume: 5 µL

Secondary risk assessment For the factors categorized as
Factor N in the primary risk assessment, an FMEA was
conducted using the optimized analytical procedure. Prior
to the determination of risk priority, Risk Priority Number
was defined as follows:
Risk Priority Number (RPN) = S × O × D
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Table shows the results of the FMEA and those of the risk reductions achieved for the factors
under Factor N with a medium or high risk priority. For the factors considered to bear a
potential risk, a reduction of the risk was undertaken by setting system suitability or
establishing SOPs

Verification of Analytical Procedure Performance: The
analytical procedure was verified for performance in
accordance with the ICH Q2 Guideline on Validation of
Analytical Procedures using the performance criteria laid
down in Section 1 according to the ATP. The results
confirmed that the established analytical procedure fulfilled
the requirements based on the performance criteria, thus
demonstrating the performance of this procedure.
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Specificity Using forced degradation samples or orthentic impurity samples, specificity of the
analytical procedure was confirmed by conducting confirmatory verification of the separation
performance elaborated during the development of the procedure.
3.2 Accuracy Accuracy of the analytical procedure was evaluated in terms of the recovery of the
impurity from the spiked samples. The spiked sample preparations were conducted at 3
concentrations in the range of 0.1% (reporting threshold) to 0.2% (specification value).
3.2 Precision (repeatability and intermediate precision) Precision of the analytical procedure was
evaluated in terms of the recovery of the impurity from the spiked samples. The spiked sample
preparations were conducted at 3 concentrations in the range of 0.1% (reporting threshold) to 0.2%
(specification value).
3.3 Linearity Linearity was verified in the range of 0.1% (reporting threshold) to 0.2%
(specification value). The results gained were analyzed for linear regression to evaluate for linearity.
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Control Strategy:
For HPLC operating conditions, it has been experimentally
demonstrated that the variability of parameters does not affect
the separation performance of this analytical procedure within
the verified region on the basis of the optimization study
results shown in Section 2.2.3. Thus, the risks associated with
Factor X had already been reduced during the development of
this analytical procedure, indicating that the ranges presented
in Section 3.6 can be a method operable design region
(MODR), i.e., a robust region within which the analytical
results are not affected.
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Process analytical technology (PAT)
• Process analytical technology (PAT) has been defined by the
United States Food and Drug Administration (FDA) as a
mechanism to design, analyze, and control pharmaceutical
manufacturing processes through the measurement of Critical
Process Parameters (CPP) which affect Critical Quality
Attributes (CQA).
• The concept actually aims at understanding the processes by
defining their CPPs, and accordingly monitoring them in a timely
manner (preferably in-line or on-line) and thus being more efficient
in testing while at the same time reducing over-processing,
enhancing consistency and minimizing rejects.

PAT is process analysis in real-time. At-line real-time
analytical measurements can replace off-line time
consuming chemical analyses. Locating information
in those measurements, identifying the important
process parameters and creating a model able to
measure the quality instantaneously are the main
stakes in PAT. MVA is the key tool.

The basics
• PAT is a term used for describing a broader change in pharmaceutical
manufacturing from static batch manufacturing to a more dynamic approach.
It involves defining the Critical Process Parameters (CPPs) of the equipment
used to make the product, which affect the Critical Quality Attributes (CQAs)
of the product and then controlling these CPPs within defined limits. This
allows manufacturers to produce products with consistent quality and also
helps to reduce waste & overall costs.
• This mechanism for producing consistent product quality & reducing waste
presents a good case for utilizing continuous manufacturing technologies.
The control of a steady state process when you understand the upstream &
downstream effects is an easier task as common cause variability is easier to
define and monitor.

The variables
• It would be acceptable to consider that raw materials used to manufacture pharmaceutical
products can vary in their attributes e.g. moisture content, crystal structure etc. It would also
be acceptable to consider that manufacturing equipment does not always operate in exactly
the same fashion due to the inherent tolerance of the equipment and its components. It is
therefore logical to say that variability in raw materials married with a static batch process
with inherent variability in process equipment produces variable product. This is on the basis
that a static batch process produces product by following a fixed recipe with fixed set-points.
• With this in mind the PAT drive is to have a dynamic manufacturing process that
compensates for variability both in raw materials & equipment to produce a consistent
product.

PAT implementation
• The challenge to date with PAT for pharmaceutical manufacturers is knowing how to
start. A common problem is picking a complex process and getting mired in the
challenge of collecting and analyzing the data.
• The following criteria serve as a basic framework for successful PAT roll-outs:
• Picking a simple process. (Think Water for Injection (WFI) or Building Monitoring
System (BMS)
• All details and nuances are well understood and explained for that process.
• Determine what information is easily collected and accessible through current
instrumentation.
• Understanding the appropriate intervals for collecting that data.
• Evaluating the tools available for reading and synchronizing the data.

PAT Tools
• in order to implement a successful PAT project, a combination of three main
PAT tools is essential:
• Multivariate data acquisition and data analysis tools: usually advanced
software packages which aid in design of experiments, collection of raw data
and statistically analyzing this data in order to determine what parameters
are CPP.
• Process analytical chemistry (PAC) tools: in-line and on-line analytical
instruments used to measure those parameters that have been defined as
CPP. These include mainly near infrared spectroscopy (NIRS); but also
include biosensors, Raman spectroscopy, fiber optics and others.
• Continuous improvement and/or knowledge management tools: paper
systems or software packages which accumulate Quality Control data
acquired over time for specific processes with the aim of defining process
weaknesses and implementing and monitoring process improvement
initiatives. These products may be the same or separated from the statistical
analysis tools above.

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QUALITY OBJECTIVES & GMP
QUALITY CONTROL
 Quality control (QC) is a procedure (s) intended to ensure that a manufactured
product or performed service adheres to a defined set of quality criteria or
meets the requirements of the client or customer.
 It is a combination of all the characteristics of a product that determine the degree
of acceptability of the product.
 QC is similar to, but not identical with, quality assurance (QA).

QUALITY CONTROL VERSUS QUALITY ASSURANCE
 The terms often used interchangeably to refer to ways of ensuring the
quality of a service or product.
 Quality Assurance: The planned and systematic activities implemented
in a quality system so that quality requirements for a product or service
will be fulfilled.
 Quality Control: The observation techniques and activities used to fulfill
requirements for quality. An evaluation to indicate needed corrective
responses; the act of guiding a process in which variability is attributable
to a constant system of chance causes
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INTRODUCTION TO GMP
Good manufacturing practice (GMP) is a system for ensuring
that products are consistently produced and controlled
according to quality standards.
It is designed to minimize the risks involved in any
pharmaceutical production that cannot be eliminated
through testing the final product.
BASIC FUNDAMENTALS INCLUDES
Quality
Safety
Effectiveness

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GMP covers all aspects of production, including;
Personnel
Premises
Equipment
Starting materials
Production & In-process control
Laboratory Control
Packaging & Labeling
Holding & distribution (ware house)
Documentation:
There must be systems to provide documented proof that correct
procedures are consistently followed at each step in the
manufacturing process - every time a product is made.

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Why is GMP important?
Avoids poor quality medicines, a health hazard
Saves waste of money for both government and individual
consumers.
Helps boost pharmaceutical export opportunities
Reduces and prevents errors
Prevents contamination & cross contamination
Minimizes variance in drug potency
Prevents toxicity
Prevents mislabeling
Avoids adulteration

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ORGANIZATION AND PERSONNEL
 Lay out of clean rooms
 Wear clean clothing
 Wear protective apparel to prevent contamination Practice
good sanitation
 If sick or have open lesions that would impact the drug,
excluded from direct contact with the product
 Regular medical check-ups

1/23/2020
78 BUILDING AND FACILITIES
• Building will be adequately sized for proper storage of
equipment and material
• Operations will be performed in specific areas
• Raw materials received will be placed in quarantine until tested
• Rejected material will be separated Adequate lighting
• Adequate environmental controls
• Air breaks on drains

EQUIPMENTS
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• Maintained in a good state & qualified (Design, Cleanliness,
Installation, Performance)
• Placed in appropriate place ( temperature & humidity control)
• Will be cleaned with approved cleaning agents will not affect
product
• written schedule of cleaning
• clean after each batch
• ID number on equipment

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STARTING MATERIAL
• Received in Quarantine
• not used until released
• Written procedures on receipt, handling and sampling
• Stored off the floor
• Each container marked with lot number, name and
status (released, quarantined, rejected)

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PROCESS CONTROL
• There will be written procedures
• Document activities
• batch record
• log books
• Work Instruction & operating procedures
• Control contamination
• Line clearance & Cleanliness & tanks, paddles
etc Keep organized

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WARE HOUSE
• It shall be clean
• Sections clearly identified:
• quarantine - yellow
• released - green
• rejected - red
• FIFO: First In - First Out
• Track inventory and sold lots

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83 PACKAGING AND LABELLING
• The written display on the container Document
receiving
• Separate labeling to avoid mix up
• Set procedures for appropriate:
• Identity
• Storage
• Handling
• Sampling
• Testing
• Inspection prior to issuance
• Label control begins with design

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QC LAB
 Have specifications, standards, sampling plans,
test procedures
 Shall have a calibration and maintenance program
 written with a time period for performance
Document all testing
 use logbooks
 Stability testing done
 Reserve samples will be kept for final products
over the period of the expiration date

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85 DOCCUMENTATION
• Records maintained
• Batch records
• testing
• investigations
• training
• maintenance
• Cleaning
If it was not documented, then it did not happen!

DUTIES OF H.O.D
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 Authorization of written procedures
 Control & Monitoring
 Process validation
 Calibration of analytical apparatus
 Plant hygiene
 Training
 Retention of records
 Monitoring of compliance of GMP
 Inspection and investigation to assure quality

DUTIES OF PRODUCTION INCHARGE
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To ensure following:
• Product produced, stored and documented as per quality
• Approve instruction for production operations & strict implementation
• Evaluation of production records and its availability to QC
• Check maintenance of department, premises and equipment
• Ensure process validation
• Training

DUTIES OF QUALITY CONTROL INCHARGE
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• To approve, reject the starting material, packaging material, intermediate,
bulk and finished good.
• Evaluate batch record
• Approve sampling instruction
• Ensure necessary testing
• Check maintenance of department, premises and equipment
• To ensure training of other QC personnel’s

Quality by Design and Process Analytical Technology

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