Process Validation of API

Process Validation in API Facilities:

What ? Why ? How?

P.S.Rao
1 1

Validation: Definition

 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.
2 2

Validation studies

 Analytical Test
 Equipment
 Process
 Support process (Drying, Blending,
Micronization, Cleaning, sterilization, sterile
filling, etc
 facility systems (air, Nitrogen, water, AHU etc)

3 3

Validation studies

 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.

4 4

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

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

6

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).

7


 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.

8


 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

9


 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.
10


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

11

Process Validation Overview

 [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)

12 12

Approaches to validation

 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).

13 13


 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).

14 14

 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.
(ICH15 12.44)
Q7
15


 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).

16 16

Why Validate the Process ?

 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.

17 17

Process Validation
requires a rational approach

Key Process
Variables
Lab-scale
process
Optimization/Process
Process
Understanding
Characterization
Phase I/II Trial
process
Robustness
Worst case challenges?

Lab Scale Validation
Manufacturing
Process process
Validation
18 Process Validation at
18
Full-scale

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!

19 19

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.

20 20

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
21 21

Process Validation

1. Select CPPs, CQAs

2. Process Validation Protocol

3. Execute

4. Assay

5. Report

6. File

22 22

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

23 23


Step Goal CPPs CPP How CQA Samples CQA Methods
Range controll Range
ed

Ferment High pH 7.0 0.5 DCS Final Broth – 1–3 Analytical
ation cell Temp Glucose final time g/L methd
density Concn. point SOP XYZ

24 24


 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)

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

26 26

Process Validation Program (ICHQ7)

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.

27 27

Periodic Review of Validated Systems(ICHQ7)

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 (?).

28 28

RE-VALIDATION (HSA: GUIDE-MQA-007-007 )

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.
29 29

RE-VALIDATION (HSA: GUIDE-MQA-007-007 )

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.
30 30

CHANGE CONTROL-Revalidation

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.
31 31


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);
32 32


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).

33 33

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)

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.
35 35

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
36

Stage 3: Continued Process Verification

Process Validation
Stage 2

Process
Stage 1
Process Qualification
Design

Continued
Process
Verification

Stage 3

37

Stage 3: Continued Process Verification

Develop
Monitoring Develop Monitoring Reports
Plan from Control Assessing the data
Strategy Document.
on a frequent basis
Continually monitor
(e.g., monthly, quarterly)
critical areas of the
process

Make any
Goal=To continually assure
adjustments
that the process remains in a to continually
state of control (the validated assure the process
state) during commercial remains in a state
manufacture. of control. Update
Control Strategy document
if needed
38

Learning progression

Good planning, expected path

Continued
Comprehensive Sound, thorough Verification,
process process Process
design, scientific qualification. learning and
process Confirms design improvement
understanding

Poor design, planning, process understanding
Unexplained variation,
Product and process
problems.
Process not in control.
Poor, PQ checklist Major learning!
minimal exercise w/little Potentially
39
design understanding substandard 39
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

• 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

51 51

Process Capability

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” LSL  Width  USL
• Cpk = Cp when process is centered
• Cpk < Cp when process is not centered

52 52

Process Capability

53 53

Spécial Cause versus Common Cause variation

Common Cause (Random) Special Cause Variation -
Variation - Natural variation Occasionally in a process
within a process

COMMON SPECIAL
• Always present • Irregular occurrences
• Lots of them • Relatively rare
• Small cumulative effect • Large impact
• Hard to remove/ reduce • Mostly easy to correct

54 54

Causes of Variation, Examples

Common Causes Special Causes

• „In Control‟ •„Out of Control‟
• Normal equipment wear • Equipment breakdown
• Material variation • Change of supplier
• Equipment tolerances • Instability in process
• Process parameters parameter, e.g. blending
with set points, e.g. speed
blending speed

55 55

Knowledge and understanding Variability is the basis
for manufacturing control

• 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 Variable
Fixed Variable Adjustable Consistent
Process Process
Process Process Process Process
Process output Process output
Input Input 56

To summarize New approach versus traditional

Traditional New PV approach
• Compliance focus • Science and risk based
• Following rules • Basis of product quality understood
without thinking • PV leads ( i.e. equipment qualification
• DQ/IQ/OQ/PQ supports PV) & is not
• Validating 3- an „add-on‟
batches = • Must have statistical
assumes product understanding
quality assurance

57 57

The Question of Process Validation

• 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?
58 58

Validation: Type of Documentation

 Validation master plan (VMP)
 Validation protocol (VP)
 Validation reports (VR)
 Standard operating procedures (SOPs)

59

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
60

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

61

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
62

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.

63

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

64 64

Process Validation of API

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