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Process Validation
BY
Dr. Suman Pattanayak
Associate Professor
Department of Pharma Analysis & QA.
Vijaya Institute of Pharmaceutical Sciences for Women
B. Pharm IV year/ II Sem
DRA, IPR & Patents
2 2
• Validation is the term widely used in the pharmaceutical industry. It
comes from the word “Valid” which means “ Can be justified or Legally
Defined”.
• It can be said as “Validation is demonstrating and documenting that
something does (or is) what is supposed to do (or be)”.
• In short validation is defined as “Full detailed documentation that all
process and procedures are functioning in the manner they are designed
for”
• Validation is the documented act of proving that any procedure, process,
equipment, material, activity or system actually leads to the expected
result.
Validation: Definition
3 3
• Analytical Test
• Equipment
• Process
• Support process (Drying, Blending, Micronization,
Cleaning, sterilization, sterile filling, etc
• facility systems (air, Nitrogen, water, AHU etc)
Validation studies
4 4
• verify the system/process under test, under the extremes
expected during the process to prove that the system
remains in control.
• Critical equipment and processes are routinely
revalidated at appropriate intervals to demonstrate that
the process remains in control.
Validation studies
Type of validation
• Laboratory-and pilot-scale validations
– some production processes cannot be carried
out in production facility
• Plant-and Commercial-scale validations
– Production processes carried out in
production facility with Defined Batch size.
5
6
Facility systems and equipment: Stage
of validation
• Design qualification (DQ)
• Installation Qualification (IQ)
• Operational Qualification (OQ)
• Performance Qualification (PQ)
Systems and EQ; PQ=validation
Depending on the function and operation of some EQ
7
Facility systems and equipment
• Design qualification (DQ)
– necessary when planning and choosing EQ or systems to ensure that
components selected will have adequate capacity to function for the
intended purpose, and will adequately serve the operations or
functions of another piece of EQ or operation.
Which includes,
– Utilities and building services
– Equipment features
– Auxiliary Equipment features
– All Eng drawings, schematics, layouts and list of manufacturers
functional specifications (and its comparison with URS).
8
Facility systems and equipment
• Installation Qualification (IQ)
– This is the first step towards equipment validation
– Upon receipt the equipment, the user shall inspect the equipment to
ensure that, it meets the spec’s submitted with the initial order
– written for critical processing EQ and systems
– list all the identification information, location, utility requirements, and
any safety features of EQ
– verify that the item matches the purchase/Design specifications
– It is the responsibility of the vendor, the operating dept and the project
team to complete the IQ successfully.
9
Facility systems and equipment
• Operational Qualification (OQ)
– outlines the information required to provide evidence that all component
of a system or of a piece of EQ operate as specified.
– At this stage COP’s should be finalized
– There must be min 3 consecutive successful runs to demonstrate
repeatability
– should provide a listing of SOPs for operation, maintenance and calibration
– define the specification and acceptance criteria
– include information on EQ or system calibration, pre-operational activities,
routine operations and their acceptance criteria & frequency
– Training on operation of EQ
10
Facility systems and equipment
• Performance Qualification (PQ)
– performed after both IQ and OQ have been
completed, reviewed and approved
– describes the procedures for demonstrating that a
system or piece of EQ can consistently perform and
meet required specification under routine operation
and, where appropriate, under worst case situations
– include description of preliminary procedures
required, detailed performance tests to be done,
acceptance criteria
– other supporting EQ used during qualification have
been validated.
– Process validation and PQ may overlap.
11
Facility systems and equipment
pH meter, incubator, Temp Sensor, freezer; IQ,OQ
system: air (HVAC), compressed air, pure steam, raw
steam, purified water, WFI, central vacuum; IQ, OQ,
PQ
EQ: Reactor, oven, lyophilizer, centrifuge, Drier; IQ,
OQ, PQ
12 12
• [To establish] documented evidence which provides a
high degree of assurance that a specific process will
consistently produce a product meeting pre-determined
specifications and quality attributes.
• (FDA, May 1987)
Process Validation Overview
13 13
• Prospective
– pre-planned protocol
– Prospective validation is the preferred approach, but
there are exceptions where the other approaches
(Concurrent/Retrospective) can be used
– Prospective validation performed on an API process
should be completed before the commercial
distribution of the final drug product manufactured
from that API (ICH Q7 12.42).
Approaches to validation
14 14
• Concurrent
– base on data collected during actual performance of a process
already implemented & Validated in a manufacturing facility
– suit manufacturers of long standing, have well-controlled
manufacturing process
– Concurrent validation can be conducted when data from replicate
production runs are unavailable because only a limited number of
API batches have been produced, API batches are produced
infrequently, or
– API batches are produced by a validated process that has been
modified. Prior to the completion of concurrent validation, batches
can be released and used in final drug product for commercial
distribution based on thorough monitoring and testing of the API
batches (ICH Q7 12.43).
Approaches to validation
15 15
• Retrospective
– for production for a long time, but has not been validated according to a
prospective protocol and concurrent validation is not realistic option
– is not generally accepted
• An exception can be made for retrospective validation for well established processes
that have been used without significant changes to API quality due to changes in raw
materials, equipment, systems, facilities, or the production process. This validation
approach may be used where:
(1) Critical quality attributes and critical process parameters have been identified;
(2) Appropriate in-process acceptance criteria and controls have been established;
(3) There have not been significant process/product failures attributable to causes other
than operator error or equipment failures unrelated to equipment suitability; and
(4) Impurity profiles have been established for the existing API.
(ICH Q7 12.44)
Approaches to validation
16 16
 Batches selected for retrospective validation should be representative of
all batches made during the review period, including any batches that
failed to meet specifications, and should be sufficient in number to
demonstrate process consistency. Retained samples can be tested to
obtain data to retrospectively validate the process (ICH Q7 12.44).
Approaches to validation
17 17
• Demonstrate process control and consistency
• Comply with regulatory requirements for licensure or for
filing
• Provide assurance that release tests will be met; the
need for some release testing may be eliminated.
Why Validate the Process ?
18 18
Key Process Variables
Optimization/Process
Understanding
Robustness
Worst case challenges?
Process Validation at
Full-scale
Process
Characterization
Process
Validation
Phase I/II Trial
process
Lab-scale
process
Manufacturing
process
Lab Scale Validation
Process Validation
requires a rational approach
19 19
Characterization vs. Validation
• Characterization
– “Validation” studies at bench-scale using scaled-down models, if
possible.
– Well-documented in Lab notebooks and key technical reports (no
protocol)
– Learning, not “Validating”
• Validation
– Usually at Full-scale in actual process equipment
– Conducted by Manufacturing under Protocol
– Testing what we already know, NOT EXPERIMENTING!
20 20
Understand Your Process
• Ruggedness
– Multiple lots of raw materials
– Multiple lots of resins/filters
– Explore failure limits at laboratory/pilot scale
• Scaled-down process should reflect full scale
manufacturing performance as closely as
possible so that data generated are relevant.
21 21
Definitions
Critical Process Parameter (CPP):
An input variable that must be controlled within a specified range to ensure
success.
A critical parameter is that a processing parameter that directly influences the
drug substance characterization and impurity profile at or after a critical step.
Critical Quality Attribute (CQA):
An output parameter from a unit operation that must be within a specified
range to demonstrate control, consistency, and acceptable product quality.
CPP CQA
pH/Temp Yield
SM content/Reaction Time Purity
22 22
1. Select CPPs, CQAs
2. Process Validation Protocol
3. Execute
4. Assay
5. Report
6. File
Process Validation
23 23
Process Validation Protocol
• CPPs, CQAs w/ acceptance criteria
– Background / rationale for ranges
• How will they be sampled / monitored ?
• How many validation lots ?
• How will deviations be handled ?
Define Roles and Responsibilities
Manufacturing, Quality, Technology
24
24
Process Validation Protocol
Step Goal CPPs CPP
Range
How
controll
ed
CQA Samples CQA
Range
Methods
Ferment
ation
High
cell
density
pH
Temp
7.0± 0.5 DCS Final
Glucose
Concn.
Broth –
final time
point
1 – 3
g/L
Analytical
methd
SOP XYZ
Process Validation Protocol
• Detailed chemical synthesis of product
• List of approved vendors
• Reference of R&D and pilot scale up studies and technology transfer report
• Detailed manufacturing instructions
• List of EQ/Instruments used and its qualification/Calibration status
• Critical process steps and CPP identification/description/justification
• Sampling and testing plans (pictorials)
• Validated analytical methods for IP and Int/final product testing
• Statistical techniques to be used in the data analysis
• ACC with scientific rationale
• List of validation members
• Deviations/ conclusions/ Recommendations/certification & Report pattern
25
Process Validation Program (ICHQ7)
26
26
The number of process runs for validation should depend on the
complexity of the process or the magnitude of the process change being
considered.
For prospective and concurrent validation, three consecutive successful
production batches should be used as a guide, but there may be
situations where additional process runs are warranted to prove
consistency of the process (e.g., complex API processes or API processes
with prolonged completion times).
For retrospective validation, generally data from ten to thirty consecutive
batches should be examined to assess process consistency, but fewer
batches can be examined if justified
Process Validation Program (ICHQ7)
27
27
Critical process parameters should be controlled and monitored during
process validation studies. Process parameters unrelated to quality, such
as variables controlled to minimize energy consumption or equipment
use, need not be included in the process validation.
Process validation should confirm that the impurity profile for each API is
within the limits specified. The impurity profile should be comparable to
or better than historical data and, where applicable, the profile
determined during process development or for batches used for pivotal
(key) clinical and toxicological studies.
Periodic Review of Validated Systems(ICHQ7)
28
28
Systems and processes should be periodically evaluated to verify that they
are still operating in a valid manner.
Where no significant changes have been made to the system or process,
and a quality review confirms that the system or process is consistently
producing material meeting its specifications, there is normally no need
for revalidation (?).
RE-VALIDATION (HSA: GUIDE-MQA-007-007 )
29
29
Re-validation provides the evidence that changes in a process and/or the
process environment, introduced either intentionally or unintentionally,
do not adversely affect process characteristics and product quality.
There are two basic categories of re-validation:
1. Re-validation in cases of known change (including transfer of
processes from one company to another or from one site to another);
and
2. Periodic re-validation carried out at scheduled intervals.
A system should be in place (Validation Master Plan requirements) to
ensure both situations are addressed.
RE-VALIDATION (HSA: GUIDE-MQA-007-007 )
30
30
The need for periodic re-validation of non-sterile processes is considered to be a lower
priority than for sterile processes.
In the case of standard processes on conventional equipment, a data review similar to
what would be required for Retrospective Validation may provide an adequate assurance
that the process continues under control. In addition, the following points should also be
considered:
The occurrence of any changes in the master formula, methods or starting material
manufacturer;
Equipment calibrations carried out according to the established program;
Preventative maintenance carried out according to the program;
Standard operating procedures (SOPs) up to date and being followed;
Cleaning and hygiene program still appropriate; and
Unplanned changes or maintenance to equipment or instruments.
CHANGE CONTROL-Revalidation
31
31
Change control is an important element in any Quality Assurance system.
Written procedures should be in place to describe the actions to be taken
if a change is proposed to a product component, process equipment,
process environment (or site), method of production or testing or any
other change that may affect product quality or support system
operation.
All changes should be formally requested, documented and accepted by
representatives of Production, QC/QA, R&D, Engineering and Regulatory
Affairs as appropriate. The likely impact (risk assessment) of the change
on the product should be evaluated and the need for, and the extent of
re-validation discussed. The change control system should ensure that all
notified or requested changes are satisfactorily investigated, documented
and authorized.
CHANGE CONTROL-Revalidation
32
32
Products made by processes subjected to changes should not be released
for sale without full awareness and consideration of the change by the
responsible personnel.
Changes that are likely to require re-validation are as follows:
Changes of raw materials (physical properties such as density, viscosity,
particle size distribution may affect the process or product);
Change of starting material manufacturer;
Changes of packaging material (e.g. substituting plastic for glass);
Changes in the process (e.g. mixing times, drying temperatures);
CHANGE CONTROL-Revalidation
33
33
Changes in the equipment (e.g. addition of automatic detection systems).
Changes of equipment which involve the replacement on a ‘like for like’
basis would not normally require a re-validation;
Production area and support system changes (e.g. rearrangement of
areas, new water treatment method);
Transfer of processes to another site; and
Unexpected changes (e.g. those observed during self-inspection or
during routine analysis of process trend data).
Major PV problems facing during regulatory audits.
• Failure in life cycle approach to validation
• People are thinking that once they complete their prospective
validation that is end and they are on their way
• Lack of scientific rationale in acceptance criteria & in preparing
protocol.
• Lack of documentation execution
• Lack of awareness on process validation
• Lack of justification on CPP & CQA of the process
• Lack of seriousness on validation, etc.
34 34
New PV Guidance By FDA (Jan,2011)
35
35
Process validation is defined as the collection
and evaluation of data, from the process
design stage through commercial production,
which establishes scientific evidence that a
process is capable of consistently delivering
quality product.
A series of activities taking place over the
lifecycle of the product and process.
36
Requirements of FDA Validation Guidance
• FDA Guidance for Industry: Process Validation: General Principles and Practices,
published January 2011 distinguishes three stages of validation:
– Stage 1 – Process Design: The commercial manufacturing process is defined during this
stage based on knowledge gained through development and scale-up activities.
– Stage 2 – Process Qualification: During this stage, the process design is evaluated to
determine if the process is capable of reproducible commercial manufacturing.
– Stage 3 – Continued Process Verification: Ongoing assurance is gained during routine
production that the process remains in a state of control.
• Further states that manufacturers should understand the sources of variation
– Detect the presence and degree of variation
– Understand the impact of variation on the process and ultimately on product
attributes
– Control the variation in a manner commensurate with the risk it represents to the
process and product
37
Stage 3: Continued Process Verification
Stage 1
Stage 2
Stage 3
Process Validation
38
Stage 3: Continued Process Verification
Develop Monitoring
Reports
Assessing the data
on a frequent basis
(e.g., monthly, quarterly)
Make any
adjustments
to continually
assure the process
remains in a state
of control. Update
Control Strategy document
if needed
Develop
Monitoring
Plan from Control
Strategy Document.
Continually monitor
critical areas of the
process
Goal=To continually assure that
the process remains in a state of
control (the validated state)
during commercial manufacture.
Learning progression
39
39
Good planning, expected path
Comprehensive
process
design, scientific
process
understanding
Sound, thorough
process
qualification.
Confirms design
Continued
Verification,
Process
learning and
improvement
Poor design, planning, process understanding
Poor,
minimal
design
PQ checklist
exercise w/little
understanding
Unexplained variation,
Product and process
problems.
Process not in control.
Major learning!
Potentially substandard
product on market
Process Validation: General Principles and Practices
• 1. Further the goals of the CGMPs for the 21st Century Initiative such as
advancing science and technological innovation.
• 2. Update Guidance based on regulatory experience since 1987.
i. Emphasis on process design elements and maintaining process control
during commercialization
ii. Communicate that PV is an ongoing program and align process
validation activities with product lifecycle
iii. Emphasize the role of objective measures and statistical tools and
analyses.
iv. Emphasize knowledge, detection, and control of variability.
Lifecycle approach is more rational, scientific and can improve control and
assurance of quality.
40 40
Stage 1: (Why)Process Design
• “Focusing exclusively on qualification efforts without
understanding the manufacturing process and associated
variations may not lead to adequate assurance of quality.”
• Poor quality drugs on the market, evidenced by recalls,
complaints and other indicators, from supposedly
“validated” processes pointed to a lack of process
understanding and adequate process control. This was an
impetus (drive) for revising the 1987 Guideline.
41 41
Stage 2: Process Qualification
• Two Aspects
• Design of facilities and qualification of
equipment and utilities
• Process Performance qualification (PPQ)
42 42
PPQ - Process Performance Qualification
• Protocol(s) include
• “Criteria and process performance indicators
that allow for a science- and risk-based
decision about the ability of the process to
consistently produce quality products.”
• “A description of the statistical methods to be
used in analyzing all collected data (e.g.,
statistical metrics defining both intra-batch
and inter-batch variability).”
43 43
Basis for commercial distribution
• “Each manufacturer should judge whether it
has gained sufficient understanding to
provide a high degree of assurance in its
manufacturing process to justify distribution
of the product.”
• Criteria for high level of assurance is specific
to the particular product and process being
validated (results of stages 1 & 2) and is
judged by the firm.
44 44
Concurrent Release in the PV Guidance
• In the PV guidance, the term “concurrent release” is meant
exclusively in terms of the process performance qualification
(PPQ) study protocol. It means releasing a lot(s) included in a
pre-planned study protocol before the study is completed,
data collected and analyzed, and conclusions drawn.
• PV Guidance definition
• Concurrent Release: Releasing for distribution a lot of
finished product, manufactured following a qualification
protocol, that meets the [lot release criteria] standards
established in the protocol, but before the entire study
protocol has been executed.
45 45
Stage 3 - Continued Process Verification
• CGMP requirements, specifically, the
collection and evaluation of information and
data about the performance of the process,
will allow detection of undesired process
variability. Evaluating the performance of the
process identifies problems and determines
whether action must be taken to correct,
anticipate, and prevent problems so that the
process remains in control (§211.180(e)).
46 46
Stage 3- Continued Process Verification
• A strategy for trending and monitoring.
• What is the goal?
• For example, determining machine-to-machine
variability? within a machine? Batch to batch
variability for certain attributes?
• May need to tailor approaches, use different
tools, for different products and processes.
• Obtain expertise applying statistical tools and analysis to
manufacturing data.
• Further refine the control strategy.
47 47
Stage 3- Continued Process Verification
• “An ongoing program to collect and analyze product and
process data that relate to product quality must be
established (§211.180(e)).
The data collected should include relevant process trends and
quality of incoming materials or components, in-process
material, and finished products.
The data should be statistically trended and reviewed by
trained personnel.
The information collected should verify that the quality
attributes are being appropriately controlled throughout the
process.”
48
Statistical expectations
– from the Process Validation Guide
• Statistician or adequate trained personnel in statistical
process control techniques should develop
– Data collection plan, stage 2 and 3
– Statistical methods for evaluating process stability
and process capability
• Statistical methods to include:
– Trending
– Evaluation of process stability and capability
– Detection of unintended process variability
– Guarding against overreaction to individual events
49 49
Basic statistical terms:
– Mean ( μ): Statistical average
• Mean,μ = Σxj/N
Sum of individual Measurements (xj)/number of measurements (N)
– Standard deviation (σ) : Common measure of statistical dispersion,
which measures how widely spread the values in a data set are.
It is calculated as the square root of variance:
A large standard deviation indicates that the data points are far from the mean and
a small standard deviation indicates that they are clustered closely around the
mean
– Normal distribution: The most common distribution.
Approx 68% of the values are within 1 standard deviation
of the mean, about 95% of the values are within two
standard deviations and about 99.7% lie within 3
standard deviations of the mean
50
Process Capability
51 51
• Process capability analysis compares the performance
of a process against its specifications
• A process is capable if virtually all of the possible
variable values fall within the specification limits
• Uses “capability indices” to measure the ability of a
process to meet the specifications:
– Cp, Cpk, Ppk etc are common measures of process
capability
– They measure the spread of the specifications
relative to the six-sigma spread in the process
Process Capability
52 52
Cpk = min(Cpu, Cpl)
– Cpu = (USL-μ)/(3σ)
– Cpl = (μ-LSL)/(3σ)
• Takes into account the location of the process mean relative
to specifications
“Process Centering”
• Cpk = Cp when process is centered
• Cpk < Cp when process is not centered
LSL  Width  USL
Process Capability
53 53
Spécial Cause versus Common Cause variation
54 54
Common Cause (Random)
Variation - Natural variation
within a process
Special Cause Variation -
Occasionally in a process
COMMON
• Always present
• Lots of them
• Small cumulative effect
• Hard to remove/ reduce
SPECIAL
• Irregular occurrences
• Relatively rare
• Large impact
• Mostly easy to correct
Causes of Variation, Examples
55 55
Common Causes Special Causes
• ‘In Control’
• Normal equipment wear
• Material variation
• Equipment tolerances
• Process parameters
with set points, e.g.
blending speed
•‘Out of Control’
• Equipment breakdown
• Change of supplier
• Instability in process
parameter, e.g. blending speed
Knowledge and understanding Variability is the basis for manufacturing
control
56
• Manufacturers should
– understand the sources of variation,
– detect the presence and measure degree of variation,
– understand its impact on the process and ultimately product attributes, and
– manage it in a manner commensurate with risk it represents to the process
and product
• Mechanisms for managing variability is part of the control strategy
– e.g., may choose advanced manufacturing technologies that employ
detection, analysis and control feedback loops to react to input variability
(PAT)
Variable
Process
Process
Input
Fixed
Process
Variable
Process
output
Variable
Process
Process
Input
Adjustable
Process
Consistent
Process
output
To summarize New approach versus traditional
Traditional
• Compliance focus
• Following rules
without thinking
• DQ/IQ/OQ/PQ
• Validating 3-
batches =
assumes product
quality assurance
New PV approach
• Science and risk based
• Basis of product quality understood
• PV leads ( i.e. equipment qualification
supports PV) & is not
an ‘add-on’
• Must have statistical
understanding
57 57
The Question of Process Validation
58 58
• Do I have confidence in my
manufacturing process?
• what scientific evidence assures me that
my process is capable of consistently
delivering quality product?
• How do I demonstrate that my process
works as intended?
• How do I know my process remains in
control?
59
Validation: Type of Documentation
• Validation master plan (VMP)
• Validation protocol (VP)
• Validation reports (VR)
• Standard operating procedures (SOPs)
60
Master validation plan (MVP)
• Is a document pertaining to the whole facility that describes which EQ,
systems, methods and processes will be validated and when they will be
validated.
• provide the format required for each particular validation document (IQ,
OQ, PQ for EQ and systems; process validation, analytical assay
validation)
• indicate what information is to be contained within each document
• indicate why and when revalidations will be performed
• who will decide what validations will be performed
• order in which each part of the facility is validated
• indicate how to deal with any deviations
• state the time interval permitted between each validation
• Enables overview of entire validation project
• List items to be validated with planning schedule as its heart
• like a map
61
Validation: In summary, VMP should contain at least
• Validation policy
• Organizational structure
• Summary of facilities, systems, equipment,
processes to be validated
• Documentation format for protocols and
reports
• Planning and scheduling
• Change control
• Training requirements
62
Validation: Protocol
• Objectives of the validation and qualification
study
• Site of the study
• Responsible personnel
• Description of the equipment
• SOPs
• Standards
• Criteria for the relevant products and processes
63
Validation: Report
• Title
• objective of the study
• Refer to the protocol
• Details of material
• Equipment
• Programme’s and cycles use
• Details of procedures and test methods
• Conclusion and certification.
64 64
Process Validation
 Complete 3 Validation Lots
 Obtain, Analyze data
 Address deviations
Transient deviations
Equipment malfunctions
 Additional lots if needed
 Complete / approve report
 Include in license
Questions, please…. ?

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4 validation jntu pharmacy

  • 1. 1 Process Validation BY Dr. Suman Pattanayak Associate Professor Department of Pharma Analysis & QA. Vijaya Institute of Pharmaceutical Sciences for Women B. Pharm IV year/ II Sem DRA, IPR & Patents
  • 2. 2 2 • Validation is the term widely used in the pharmaceutical industry. It comes from the word “Valid” which means “ Can be justified or Legally Defined”. • It can be said as “Validation is demonstrating and documenting that something does (or is) what is supposed to do (or be)”. • In short validation is defined as “Full detailed documentation that all process and procedures are functioning in the manner they are designed for” • Validation is the documented act of proving that any procedure, process, equipment, material, activity or system actually leads to the expected result. Validation: Definition
  • 3. 3 3 • Analytical Test • Equipment • Process • Support process (Drying, Blending, Micronization, Cleaning, sterilization, sterile filling, etc • facility systems (air, Nitrogen, water, AHU etc) Validation studies
  • 4. 4 4 • verify the system/process under test, under the extremes expected during the process to prove that the system remains in control. • Critical equipment and processes are routinely revalidated at appropriate intervals to demonstrate that the process remains in control. Validation studies
  • 5. Type of validation • Laboratory-and pilot-scale validations – some production processes cannot be carried out in production facility • Plant-and Commercial-scale validations – Production processes carried out in production facility with Defined Batch size. 5
  • 6. 6 Facility systems and equipment: Stage of validation • Design qualification (DQ) • Installation Qualification (IQ) • Operational Qualification (OQ) • Performance Qualification (PQ) Systems and EQ; PQ=validation Depending on the function and operation of some EQ
  • 7. 7 Facility systems and equipment • Design qualification (DQ) – necessary when planning and choosing EQ or systems to ensure that components selected will have adequate capacity to function for the intended purpose, and will adequately serve the operations or functions of another piece of EQ or operation. Which includes, – Utilities and building services – Equipment features – Auxiliary Equipment features – All Eng drawings, schematics, layouts and list of manufacturers functional specifications (and its comparison with URS).
  • 8. 8 Facility systems and equipment • Installation Qualification (IQ) – This is the first step towards equipment validation – Upon receipt the equipment, the user shall inspect the equipment to ensure that, it meets the spec’s submitted with the initial order – written for critical processing EQ and systems – list all the identification information, location, utility requirements, and any safety features of EQ – verify that the item matches the purchase/Design specifications – It is the responsibility of the vendor, the operating dept and the project team to complete the IQ successfully.
  • 9. 9 Facility systems and equipment • Operational Qualification (OQ) – outlines the information required to provide evidence that all component of a system or of a piece of EQ operate as specified. – At this stage COP’s should be finalized – There must be min 3 consecutive successful runs to demonstrate repeatability – should provide a listing of SOPs for operation, maintenance and calibration – define the specification and acceptance criteria – include information on EQ or system calibration, pre-operational activities, routine operations and their acceptance criteria & frequency – Training on operation of EQ
  • 10. 10 Facility systems and equipment • Performance Qualification (PQ) – performed after both IQ and OQ have been completed, reviewed and approved – describes the procedures for demonstrating that a system or piece of EQ can consistently perform and meet required specification under routine operation and, where appropriate, under worst case situations – include description of preliminary procedures required, detailed performance tests to be done, acceptance criteria – other supporting EQ used during qualification have been validated. – Process validation and PQ may overlap.
  • 11. 11 Facility systems and equipment pH meter, incubator, Temp Sensor, freezer; IQ,OQ system: air (HVAC), compressed air, pure steam, raw steam, purified water, WFI, central vacuum; IQ, OQ, PQ EQ: Reactor, oven, lyophilizer, centrifuge, Drier; IQ, OQ, PQ
  • 12. 12 12 • [To establish] documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting pre-determined specifications and quality attributes. • (FDA, May 1987) Process Validation Overview
  • 13. 13 13 • Prospective – pre-planned protocol – Prospective validation is the preferred approach, but there are exceptions where the other approaches (Concurrent/Retrospective) can be used – Prospective validation performed on an API process should be completed before the commercial distribution of the final drug product manufactured from that API (ICH Q7 12.42). Approaches to validation
  • 14. 14 14 • Concurrent – base on data collected during actual performance of a process already implemented & Validated in a manufacturing facility – suit manufacturers of long standing, have well-controlled manufacturing process – Concurrent validation can be conducted when data from replicate production runs are unavailable because only a limited number of API batches have been produced, API batches are produced infrequently, or – API batches are produced by a validated process that has been modified. Prior to the completion of concurrent validation, batches can be released and used in final drug product for commercial distribution based on thorough monitoring and testing of the API batches (ICH Q7 12.43). Approaches to validation
  • 15. 15 15 • Retrospective – for production for a long time, but has not been validated according to a prospective protocol and concurrent validation is not realistic option – is not generally accepted • An exception can be made for retrospective validation for well established processes that have been used without significant changes to API quality due to changes in raw materials, equipment, systems, facilities, or the production process. This validation approach may be used where: (1) Critical quality attributes and critical process parameters have been identified; (2) Appropriate in-process acceptance criteria and controls have been established; (3) There have not been significant process/product failures attributable to causes other than operator error or equipment failures unrelated to equipment suitability; and (4) Impurity profiles have been established for the existing API. (ICH Q7 12.44) Approaches to validation
  • 16. 16 16  Batches selected for retrospective validation should be representative of all batches made during the review period, including any batches that failed to meet specifications, and should be sufficient in number to demonstrate process consistency. Retained samples can be tested to obtain data to retrospectively validate the process (ICH Q7 12.44). Approaches to validation
  • 17. 17 17 • Demonstrate process control and consistency • Comply with regulatory requirements for licensure or for filing • Provide assurance that release tests will be met; the need for some release testing may be eliminated. Why Validate the Process ?
  • 18. 18 18 Key Process Variables Optimization/Process Understanding Robustness Worst case challenges? Process Validation at Full-scale Process Characterization Process Validation Phase I/II Trial process Lab-scale process Manufacturing process Lab Scale Validation Process Validation requires a rational approach
  • 19. 19 19 Characterization vs. Validation • Characterization – “Validation” studies at bench-scale using scaled-down models, if possible. – Well-documented in Lab notebooks and key technical reports (no protocol) – Learning, not “Validating” • Validation – Usually at Full-scale in actual process equipment – Conducted by Manufacturing under Protocol – Testing what we already know, NOT EXPERIMENTING!
  • 20. 20 20 Understand Your Process • Ruggedness – Multiple lots of raw materials – Multiple lots of resins/filters – Explore failure limits at laboratory/pilot scale • Scaled-down process should reflect full scale manufacturing performance as closely as possible so that data generated are relevant.
  • 21. 21 21 Definitions Critical Process Parameter (CPP): An input variable that must be controlled within a specified range to ensure success. A critical parameter is that a processing parameter that directly influences the drug substance characterization and impurity profile at or after a critical step. Critical Quality Attribute (CQA): An output parameter from a unit operation that must be within a specified range to demonstrate control, consistency, and acceptable product quality. CPP CQA pH/Temp Yield SM content/Reaction Time Purity
  • 22. 22 22 1. Select CPPs, CQAs 2. Process Validation Protocol 3. Execute 4. Assay 5. Report 6. File Process Validation
  • 23. 23 23 Process Validation Protocol • CPPs, CQAs w/ acceptance criteria – Background / rationale for ranges • How will they be sampled / monitored ? • How many validation lots ? • How will deviations be handled ? Define Roles and Responsibilities Manufacturing, Quality, Technology
  • 24. 24 24 Process Validation Protocol Step Goal CPPs CPP Range How controll ed CQA Samples CQA Range Methods Ferment ation High cell density pH Temp 7.0± 0.5 DCS Final Glucose Concn. Broth – final time point 1 – 3 g/L Analytical methd SOP XYZ
  • 25. Process Validation Protocol • Detailed chemical synthesis of product • List of approved vendors • Reference of R&D and pilot scale up studies and technology transfer report • Detailed manufacturing instructions • List of EQ/Instruments used and its qualification/Calibration status • Critical process steps and CPP identification/description/justification • Sampling and testing plans (pictorials) • Validated analytical methods for IP and Int/final product testing • Statistical techniques to be used in the data analysis • ACC with scientific rationale • List of validation members • Deviations/ conclusions/ Recommendations/certification & Report pattern 25
  • 26. Process Validation Program (ICHQ7) 26 26 The number of process runs for validation should depend on the complexity of the process or the magnitude of the process change being considered. For prospective and concurrent validation, three consecutive successful production batches should be used as a guide, but there may be situations where additional process runs are warranted to prove consistency of the process (e.g., complex API processes or API processes with prolonged completion times). For retrospective validation, generally data from ten to thirty consecutive batches should be examined to assess process consistency, but fewer batches can be examined if justified
  • 27. Process Validation Program (ICHQ7) 27 27 Critical process parameters should be controlled and monitored during process validation studies. Process parameters unrelated to quality, such as variables controlled to minimize energy consumption or equipment use, need not be included in the process validation. Process validation should confirm that the impurity profile for each API is within the limits specified. The impurity profile should be comparable to or better than historical data and, where applicable, the profile determined during process development or for batches used for pivotal (key) clinical and toxicological studies.
  • 28. Periodic Review of Validated Systems(ICHQ7) 28 28 Systems and processes should be periodically evaluated to verify that they are still operating in a valid manner. Where no significant changes have been made to the system or process, and a quality review confirms that the system or process is consistently producing material meeting its specifications, there is normally no need for revalidation (?).
  • 29. RE-VALIDATION (HSA: GUIDE-MQA-007-007 ) 29 29 Re-validation provides the evidence that changes in a process and/or the process environment, introduced either intentionally or unintentionally, do not adversely affect process characteristics and product quality. There are two basic categories of re-validation: 1. Re-validation in cases of known change (including transfer of processes from one company to another or from one site to another); and 2. Periodic re-validation carried out at scheduled intervals. A system should be in place (Validation Master Plan requirements) to ensure both situations are addressed.
  • 30. RE-VALIDATION (HSA: GUIDE-MQA-007-007 ) 30 30 The need for periodic re-validation of non-sterile processes is considered to be a lower priority than for sterile processes. In the case of standard processes on conventional equipment, a data review similar to what would be required for Retrospective Validation may provide an adequate assurance that the process continues under control. In addition, the following points should also be considered: The occurrence of any changes in the master formula, methods or starting material manufacturer; Equipment calibrations carried out according to the established program; Preventative maintenance carried out according to the program; Standard operating procedures (SOPs) up to date and being followed; Cleaning and hygiene program still appropriate; and Unplanned changes or maintenance to equipment or instruments.
  • 31. CHANGE CONTROL-Revalidation 31 31 Change control is an important element in any Quality Assurance system. Written procedures should be in place to describe the actions to be taken if a change is proposed to a product component, process equipment, process environment (or site), method of production or testing or any other change that may affect product quality or support system operation. All changes should be formally requested, documented and accepted by representatives of Production, QC/QA, R&D, Engineering and Regulatory Affairs as appropriate. The likely impact (risk assessment) of the change on the product should be evaluated and the need for, and the extent of re-validation discussed. The change control system should ensure that all notified or requested changes are satisfactorily investigated, documented and authorized.
  • 32. CHANGE CONTROL-Revalidation 32 32 Products made by processes subjected to changes should not be released for sale without full awareness and consideration of the change by the responsible personnel. Changes that are likely to require re-validation are as follows: Changes of raw materials (physical properties such as density, viscosity, particle size distribution may affect the process or product); Change of starting material manufacturer; Changes of packaging material (e.g. substituting plastic for glass); Changes in the process (e.g. mixing times, drying temperatures);
  • 33. CHANGE CONTROL-Revalidation 33 33 Changes in the equipment (e.g. addition of automatic detection systems). Changes of equipment which involve the replacement on a ‘like for like’ basis would not normally require a re-validation; Production area and support system changes (e.g. rearrangement of areas, new water treatment method); Transfer of processes to another site; and Unexpected changes (e.g. those observed during self-inspection or during routine analysis of process trend data).
  • 34. Major PV problems facing during regulatory audits. • Failure in life cycle approach to validation • People are thinking that once they complete their prospective validation that is end and they are on their way • Lack of scientific rationale in acceptance criteria & in preparing protocol. • Lack of documentation execution • Lack of awareness on process validation • Lack of justification on CPP & CQA of the process • Lack of seriousness on validation, etc. 34 34
  • 35. New PV Guidance By FDA (Jan,2011) 35 35 Process validation is defined as the collection and evaluation of data, from the process design stage through commercial production, which establishes scientific evidence that a process is capable of consistently delivering quality product. A series of activities taking place over the lifecycle of the product and process.
  • 36. 36 Requirements of FDA Validation Guidance • FDA Guidance for Industry: Process Validation: General Principles and Practices, published January 2011 distinguishes three stages of validation: – Stage 1 – Process Design: The commercial manufacturing process is defined during this stage based on knowledge gained through development and scale-up activities. – Stage 2 – Process Qualification: During this stage, the process design is evaluated to determine if the process is capable of reproducible commercial manufacturing. – Stage 3 – Continued Process Verification: Ongoing assurance is gained during routine production that the process remains in a state of control. • Further states that manufacturers should understand the sources of variation – Detect the presence and degree of variation – Understand the impact of variation on the process and ultimately on product attributes – Control the variation in a manner commensurate with the risk it represents to the process and product
  • 37. 37 Stage 3: Continued Process Verification Stage 1 Stage 2 Stage 3 Process Validation
  • 38. 38 Stage 3: Continued Process Verification Develop Monitoring Reports Assessing the data on a frequent basis (e.g., monthly, quarterly) Make any adjustments to continually assure the process remains in a state of control. Update Control Strategy document if needed Develop Monitoring Plan from Control Strategy Document. Continually monitor critical areas of the process Goal=To continually assure that the process remains in a state of control (the validated state) during commercial manufacture.
  • 39. Learning progression 39 39 Good planning, expected path Comprehensive process design, scientific process understanding Sound, thorough process qualification. Confirms design Continued Verification, Process learning and improvement Poor design, planning, process understanding Poor, minimal design PQ checklist exercise w/little understanding Unexplained variation, Product and process problems. Process not in control. Major learning! Potentially substandard product on market
  • 40. Process Validation: General Principles and Practices • 1. Further the goals of the CGMPs for the 21st Century Initiative such as advancing science and technological innovation. • 2. Update Guidance based on regulatory experience since 1987. i. Emphasis on process design elements and maintaining process control during commercialization ii. Communicate that PV is an ongoing program and align process validation activities with product lifecycle iii. Emphasize the role of objective measures and statistical tools and analyses. iv. Emphasize knowledge, detection, and control of variability. Lifecycle approach is more rational, scientific and can improve control and assurance of quality. 40 40
  • 41. Stage 1: (Why)Process Design • “Focusing exclusively on qualification efforts without understanding the manufacturing process and associated variations may not lead to adequate assurance of quality.” • Poor quality drugs on the market, evidenced by recalls, complaints and other indicators, from supposedly “validated” processes pointed to a lack of process understanding and adequate process control. This was an impetus (drive) for revising the 1987 Guideline. 41 41
  • 42. Stage 2: Process Qualification • Two Aspects • Design of facilities and qualification of equipment and utilities • Process Performance qualification (PPQ) 42 42
  • 43. PPQ - Process Performance Qualification • Protocol(s) include • “Criteria and process performance indicators that allow for a science- and risk-based decision about the ability of the process to consistently produce quality products.” • “A description of the statistical methods to be used in analyzing all collected data (e.g., statistical metrics defining both intra-batch and inter-batch variability).” 43 43
  • 44. Basis for commercial distribution • “Each manufacturer should judge whether it has gained sufficient understanding to provide a high degree of assurance in its manufacturing process to justify distribution of the product.” • Criteria for high level of assurance is specific to the particular product and process being validated (results of stages 1 & 2) and is judged by the firm. 44 44
  • 45. Concurrent Release in the PV Guidance • In the PV guidance, the term “concurrent release” is meant exclusively in terms of the process performance qualification (PPQ) study protocol. It means releasing a lot(s) included in a pre-planned study protocol before the study is completed, data collected and analyzed, and conclusions drawn. • PV Guidance definition • Concurrent Release: Releasing for distribution a lot of finished product, manufactured following a qualification protocol, that meets the [lot release criteria] standards established in the protocol, but before the entire study protocol has been executed. 45 45
  • 46. Stage 3 - Continued Process Verification • CGMP requirements, specifically, the collection and evaluation of information and data about the performance of the process, will allow detection of undesired process variability. Evaluating the performance of the process identifies problems and determines whether action must be taken to correct, anticipate, and prevent problems so that the process remains in control (§211.180(e)). 46 46
  • 47. Stage 3- Continued Process Verification • A strategy for trending and monitoring. • What is the goal? • For example, determining machine-to-machine variability? within a machine? Batch to batch variability for certain attributes? • May need to tailor approaches, use different tools, for different products and processes. • Obtain expertise applying statistical tools and analysis to manufacturing data. • Further refine the control strategy. 47 47
  • 48. Stage 3- Continued Process Verification • “An ongoing program to collect and analyze product and process data that relate to product quality must be established (§211.180(e)). The data collected should include relevant process trends and quality of incoming materials or components, in-process material, and finished products. The data should be statistically trended and reviewed by trained personnel. The information collected should verify that the quality attributes are being appropriately controlled throughout the process.” 48
  • 49. Statistical expectations – from the Process Validation Guide • Statistician or adequate trained personnel in statistical process control techniques should develop – Data collection plan, stage 2 and 3 – Statistical methods for evaluating process stability and process capability • Statistical methods to include: – Trending – Evaluation of process stability and capability – Detection of unintended process variability – Guarding against overreaction to individual events 49 49
  • 50. Basic statistical terms: – Mean ( μ): Statistical average • Mean,μ = Σxj/N Sum of individual Measurements (xj)/number of measurements (N) – Standard deviation (σ) : Common measure of statistical dispersion, which measures how widely spread the values in a data set are. It is calculated as the square root of variance: A large standard deviation indicates that the data points are far from the mean and a small standard deviation indicates that they are clustered closely around the mean – Normal distribution: The most common distribution. Approx 68% of the values are within 1 standard deviation of the mean, about 95% of the values are within two standard deviations and about 99.7% lie within 3 standard deviations of the mean 50
  • 51. Process Capability 51 51 • Process capability analysis compares the performance of a process against its specifications • A process is capable if virtually all of the possible variable values fall within the specification limits • Uses “capability indices” to measure the ability of a process to meet the specifications: – Cp, Cpk, Ppk etc are common measures of process capability – They measure the spread of the specifications relative to the six-sigma spread in the process
  • 52. Process Capability 52 52 Cpk = min(Cpu, Cpl) – Cpu = (USL-μ)/(3σ) – Cpl = (μ-LSL)/(3σ) • Takes into account the location of the process mean relative to specifications “Process Centering” • Cpk = Cp when process is centered • Cpk < Cp when process is not centered LSL  Width  USL
  • 54. Spécial Cause versus Common Cause variation 54 54 Common Cause (Random) Variation - Natural variation within a process Special Cause Variation - Occasionally in a process COMMON • Always present • Lots of them • Small cumulative effect • Hard to remove/ reduce SPECIAL • Irregular occurrences • Relatively rare • Large impact • Mostly easy to correct
  • 55. Causes of Variation, Examples 55 55 Common Causes Special Causes • ‘In Control’ • Normal equipment wear • Material variation • Equipment tolerances • Process parameters with set points, e.g. blending speed •‘Out of Control’ • Equipment breakdown • Change of supplier • Instability in process parameter, e.g. blending speed
  • 56. Knowledge and understanding Variability is the basis for manufacturing control 56 • Manufacturers should – understand the sources of variation, – detect the presence and measure degree of variation, – understand its impact on the process and ultimately product attributes, and – manage it in a manner commensurate with risk it represents to the process and product • Mechanisms for managing variability is part of the control strategy – e.g., may choose advanced manufacturing technologies that employ detection, analysis and control feedback loops to react to input variability (PAT) Variable Process Process Input Fixed Process Variable Process output Variable Process Process Input Adjustable Process Consistent Process output
  • 57. To summarize New approach versus traditional Traditional • Compliance focus • Following rules without thinking • DQ/IQ/OQ/PQ • Validating 3- batches = assumes product quality assurance New PV approach • Science and risk based • Basis of product quality understood • PV leads ( i.e. equipment qualification supports PV) & is not an ‘add-on’ • Must have statistical understanding 57 57
  • 58. The Question of Process Validation 58 58 • Do I have confidence in my manufacturing process? • what scientific evidence assures me that my process is capable of consistently delivering quality product? • How do I demonstrate that my process works as intended? • How do I know my process remains in control?
  • 59. 59 Validation: Type of Documentation • Validation master plan (VMP) • Validation protocol (VP) • Validation reports (VR) • Standard operating procedures (SOPs)
  • 60. 60 Master validation plan (MVP) • Is a document pertaining to the whole facility that describes which EQ, systems, methods and processes will be validated and when they will be validated. • provide the format required for each particular validation document (IQ, OQ, PQ for EQ and systems; process validation, analytical assay validation) • indicate what information is to be contained within each document • indicate why and when revalidations will be performed • who will decide what validations will be performed • order in which each part of the facility is validated • indicate how to deal with any deviations • state the time interval permitted between each validation • Enables overview of entire validation project • List items to be validated with planning schedule as its heart • like a map
  • 61. 61 Validation: In summary, VMP should contain at least • Validation policy • Organizational structure • Summary of facilities, systems, equipment, processes to be validated • Documentation format for protocols and reports • Planning and scheduling • Change control • Training requirements
  • 62. 62 Validation: Protocol • Objectives of the validation and qualification study • Site of the study • Responsible personnel • Description of the equipment • SOPs • Standards • Criteria for the relevant products and processes
  • 63. 63 Validation: Report • Title • objective of the study • Refer to the protocol • Details of material • Equipment • Programme’s and cycles use • Details of procedures and test methods • Conclusion and certification.
  • 64. 64 64 Process Validation  Complete 3 Validation Lots  Obtain, Analyze data  Address deviations Transient deviations Equipment malfunctions  Additional lots if needed  Complete / approve report  Include in license