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P R E S E N T E D B Y :

Catherine A. Srebalus Barnes, Ph.D.

Senior Director

Biosimilars Analytical R&D

The Role of the Critical Quality Attribute Assessment in Biotherapeutic Product Development

Epoetin Hospira SDV Commercial Specifications (Additional Methods Added in Response to CRL)

OCTOBER 20, 2016

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What Are CQAs?

• Critical Quality Attributes (CQAs) are defined as “physical, chemical,

biological, or microbiological properties or characteristics that should be

within an appropriate limit, range, or distribution to ensure the desired

product quality” [ICH Q8(R2)]

• CQAs represent the attributes which are important with respect to product

safety and efficacy

• CQAs designations are not meaningful without strong documented

evidence supporting the justification for classification as either critical

(CQAs) or not critical (non-CQAs)

• CQA designations are not linked to target numerical ranges – an attribute

is either critical or not

• If critical, then the attribute should be controlled or demonstrate control is not required

• The range to which the attribute should be confined is based on knowledge of the safety

and efficacy of the product at different levels of the attribute

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CQAs … the Center of the Universe? (for Biotherapeutic Product Development)

YES ….the development process revolves around understanding

the CQAs and figuring out what CQA ranges are acceptable and

how to control the product within those ranges

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Evolution of Product and Process Knowledge Across the Development Program

Definition of

product,

intended use,

and predefinition

of quality targets

(wrt clinical

relevance,

efficacy, and

safety)

Summary of

scientific

understanding

of product and

process.

Justification and

description of

multidimen-

sional space

that assures

quality

(interrelation-

ships and

boundaries of

clinical

relevance)

Definition of

control strategy

based on design

space leading to

control of

quality and

quality risk

managment.

(process

robustness)

Overview of

quality by

design, key

actions and

decisions taken

to develop new

scientific

knowledge, e.g.,

DoE, PAT, risk

assessment,

and risk control

Summary of

prior scientific

knowledge

(drug substance,

excipients;

similar

formulations and

processes).

Initial risk

assessment

Proposal of

regulatory

flexibility based

on product and

process,

scientific

knowledge, and

quality risk

management.

(materials, site,

scale, etc.)

Quality Target

Product

Profile

Prior

Knowledge

Product /

Process

Development

Product /

Process

Design Space

Control

Strategy

Regulatory

Flexibility

Breadth and depth of knowledge regarding CQAs and how they can be

modulated by the manufacturing process informs the commercial

control strategy and regulatory requirements for commercial

manufacturing and post-launch changes

Commercial control strategy and

regulatory expectations are

informed by extensive CQA and

product/process knowledge and

are right-sized to ensure patient

safety and product efficacy

EFPIA Working Group with minor modifications

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Biotherapeutic Product CQA Assessments Should Include Evaluation of the Following

• Product-specific CQAs

‒ Unique to the specific molecule or molecule type

‒ Related to sequence, structure and mechanism of action (MOA)

‒ Include: product-related impurities, product variants, glycosylation profile, etc.

• Process-specific CQAs

‒ Process-related impurities

‒ Contaminants that may be introduced during manufacture

‒ Leachates that may be introduced by product contact during manufacture or storage

• Composition / Strength / Product Stability CQAs

‒ Strength attributes related to product dosing (concentration, volume)

‒ Formulation-specific attributes linked to product stability or patient experience and

compliance (e.g., pain during or post injection)

‒ Dosage-form specific attributes (liquid v/s lyo)

‒ Combination product elements important for ensuring delivered dose

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Product-Specific CQAs

• Know the Molecule

‒ Mechanism(s) of Action (Known, Likely and Plausible)

‒ Potential Off-Target Effects Not Related to Primary MOAs

• Unintended Effector Functions

• Binding to Cell-Surface Ligands or Receptors

• Clearance Mechanisms

‒ Amino Acid Sequence and Post-Translational Modifications

• Degradation Hot Spots or Hot Spots for Enzymatic Activity

• Relevance of Specific Post-Translational Modifications (e.g., Glycosylation Profile)

‒ Sequence Regions Important for Ligand or Receptor Binding (e.g., MAb CDRs)

‒ Structual Motifs Important for Binding (e.g., helices)

• Know the Literature (as it Relates to the Molecule of Interest)

• Know the Platform (Related Molecules on the Market or in Your Company’s and Other

Companies’ Pipelines)

‒ Platform Knowledge May Include Knowledge from Endogenous Related Proteins (e.g.,

Properties of Circulating Endogenous Antibodies)

• Fill the Knowledge Gaps with Data From Supporting Studies

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Molecule and Platform Knowledge: EPO BiosimilarExample

• MOA = stimulates the proliferation and differentiation of erythroid precursors in the bone

marrow causing increased red blood cell (RBC) production

• ~28 to 32 kDa, highly glycosylated

• 2 disulfides – only one is critical for structure and function

• 4-helix bundle motif important for EPO receptor binding

• 3-N-linked glycosylation sites

• 1-O-linked glycosylation site

• N-linked glycan sialylation critical for in vivo half-life

• Primary route of degradation is Met oxidation – no impact on in vivo or in vitro activity

• 1-deamidation site in receptor binding region – levels of deamidation at this site are low

Elliott, S. Blood. 1996, 87: 2702-2713 (epo sequence reference)

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Molecule and Platform Knowledge: EPO BiosimilarExample

Knowledge Sources:

• Published literature for EPO and related ESAs

• Comparative testing of reference product and other on-market products coupled

with published safety and efficacy study data

• Functional testing of enriched variants and degradation products or following

enzymatic treatment (e.g., sialidase and other glycosidases)

• Pre-clinical and clinical studies (clinical design space)

Elliott, S. Blood. 1996, 87: 2702-2713 (epo sequence reference)

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Molecule and Platform Knowledge: MAb “ABC” Example

Figures from Deperalta, et al., Mabs 2013, 5(1), 86-101 and Sigma-Aldrich (2016)

• MOA = Complex, 1º MOA is ligand binding other MOAs may also be relevant (see example next

slide)

• Isotype IgG1 – potential for binding effector cells (FcR, C1q, FcRn)

• Ligand associated with 1º MOA exists in soluble and cell-surface bound forms – cells expressing

ligand may serve as target cells for intended or unintended effector functions

• Fc glycan fucosylation and galactosylation may impact effector functions

• High mannose structures may impact PK

• Modifications to amino acids in CDRs may impact ligand binding

• C-terminal Lys variants and N-terminal Glu/Gln/pyroGlu variants are not critical

• Many other considerations ….

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Complex MOA: Infliximab Example but Approach Can be Applied to Any MAb

FDA Arthritis Advisory Committee Briefing Document for BLA 125544 (Infliximab Biosimilar), Feb 2016

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MAb Effector Function Risk Assessment

Risk Assessment• IgG sub-class?

• Are there sequence or glycan modifications to reduce or enhance effector function?

• Known effector function potential (MOA and off-target effects)?

• Soluble, membrane-bound or cell-surface antigen?

• If primary antigen is soluble, do membrane-bound or cell-surface antigen forms exist?

(expression levels? limited to specific cell or tissue types?)

Low

Effector Function Potential

Med High

+Preliminary Effector Function Testing

(Relative to “High” and “Low” Controls)

Define Preliminary Glycosylation CQAs and Functional

Assay Testing Strategy

FcRI, FcRII, FcRIII, C1q

(binding)

ADCC, CDC, ADCP, apoptosis

(cell-based assays)

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Potential Fc Glycosylation CQAs for Model MAbs with Different Mechanisms of Action

Fc Glycosylation

CQAs Related To:

MAb Primary Mechanisms of Action

Ligand Binding

(Soluble Ligand)

Target Cell Surface Antigen Binding and

ADCC / CDC

Mechanism of Action • None • Core fucosylation (ADCC)

• Galactosylation (CDC / ADCC)

• Non-glycosylated HC (CDC / ADCC)

• High mannose (CDC / ADCC)

• High levels of sialylated glycans (ADCC?)

PK/PD • High mannose • High mannose

Immunogenicity • NeuGc (NANA)*

• -1,3-Gal*

• NeuGc (NANA)*

• -1,3-Gal*

Additional CQAs Related

to Effector Functions (not

associated with MOA) or

Off-Target Effects

TBD Based on Effector Function

Assessment

May include: core fucosylation and/or galactosylation

Recommended review article:

Reusch, D. and Tejada, M.L., Glycobiology (advance access) Aug 11, 2015

* consider the expression system for NeuGc and -1,3-Gal, routine testing likely not required for CHO

if levels are demonstrated to be low (more relevant for Sp2/0 or NS0)

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Molecule and Platform Knowledge: MAb “ABC” Example

• Functional testing of MAbs with “high” and “low” effector function (controls) to improve

understanding of likely and plausible MOAs

• Pre-clinical and clinical studies (clinical design space)

• Product quality testing of clinical samples to understand in vivo clearance or

formation/degradation of specific variants in vivo

• Comparative testing of other related on-market products (take a page from the biosimilar

development book …. why not?)

Figure taken from Lee, et al., Nature Biotechnol. 2014, 32, 356

Potential Knowledge Sources:

• Published literature for MAbs (including

characterization of endogenous MAbs)

• Platform knowledge from other internal MAb

programs (unpublished)

• Discovery data from genetic engineering studies

performed to optimize CDR sequence or

enhance/reduce effector function

• Functional testing of enriched variants and/or

degradation products

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Risk Assessment Approaches to Assess Attribute Criticality

• Exact Approach and Specific Tools Utilized are Not Critical

• Scientific Depth and Breadth of the Assessment is What Matters

• Most Companies are Using Only Severity and Uncertainty for CQA Risk Assessment

‒ Occurrence and Detectability are Generally Addressed Later as Part of Control Strategy Risk Assessments or Process Capability Assessments

• Document Key Internal and External References Used to Inform CQAAssignments

‒ Internal Technical Reports or Data

‒ Regulatory Agency Feedback

‒ External Literature References

• CQA Risk Assessment Will be Included in BLA or Other Submissions for Marketing Authorization (Health Authorities Will Ask)

‒ Document Should be Easy to Follow with Clear Rationale for Assignments

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CQA Risk Assessment Tools: One Example (Definitions are Simplified for Illustrative Purposes, More Specific Definitions are Recommended)

Attribute XXX

Biological Activity

or EfficacyPK/PD Immunogenicity Safety

Impact 9 1 1 1

Uncertainty 1 2 3 2

Overall Score

(Impact Uncertainty)9 2 3 2

CQA Designation CQA (Potential Impact on Biological Activity or Efficacy)

Immunogenicity and Safety are

often combined

HIGH MEDIUM LOW

Impact

Degree of correlation

between the attribute and

the biological effect

Score = 9

Relative abundance of the

attribute is correlated with a

change in activity for the

relevant MOAs OR No

information is available

Score = 3

Relative abundance of the

attribute may be correlated

with a change in activity for

the relevant MOAs

Score = 1

Relative abundance of the

attribute is not correlated

with a change in activity for

the relevant MOAs

Uncertainty

Credibility, specificity and

abundance of the

knowledge

Score = 3

No information or data is

available that can be

leveraged for the

assessment

Score = 2

Some information or data for

the specific molecule or a

related molecule is available

Score = 1

A significant body of

credible information or data

for the specific molecule is

available

Efficacy may be excluded (difficult to assess unless there are published clinical studies

for related molecules with attribute present across a range)

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Overall Score High Uncertainty Medium Uncertainty Low Uncertainty

High Impact

Impact Score = 9

Uncertainty Score = 9

Overall Score = 27

CQA

Impact Score = 9

Uncertainty Score = 2

Overall Score = 18

CQA

Impact Score = 9

Uncertainty Score = 1

Overall Score = 9

CQA

Moderate Impact

Impact Score = 5

Uncertainty Score = 3

Overall Score = 15

CQA

Impact Score = 5

Uncertainty Score = 2

Overall Score = 10

CQA

Impact Score = 5

Uncertainty Score = 1

Overall Score = 5

non-CQA

Low Impact

Impact Score = 1

Uncertainty Score = 3

Overall Score = 3

non-CQA

Impact Score = 1

Uncertainty Score = 2

Overall Score = 2

non-CQA

Impact Score = 1

Uncertainty Score = 1

Overall Score = 1

non-CQA

CQA Risk Assessment Tools: One Example

• Develop a Standardized Scoring Matrix and Decision Tree

• Make Scoring Definitions Specific and Quantitative (if Possible) to Ensure

Consistent Scoring by Different Project Teams

• Use it Consistently Across Products to Enable Direct Comparisons

• Create and Leverage Platform CQA Assessments for Specific Molecule Types

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Beyond Product-Specific Attributes: How to Address Other Attribute Types

Process-Related Impurities

• Most will be CQAs (e.g., HCPs, DNA, Microbial Contaminants)

• Likelihood that Levels Exceed an Established Safety or Immunogenicity

Threshold (Occurrence) Should be Evaluated as Part of the Control Strategy Risk

Assessment or Process Capability Assessment

• Evaluate Starting Levels Relative to Thresholds –Starting Levels May be

Acceptable without Any Removal

‒ e.g., Cell Culture Additives Like Antifoam or Solvents for Column Storage

• It May be Possible to Justify Removal of Routine Testing and Specifications at

BLA or Post Approval if Data Package is Strong

‒ Column Challenge Studies Using Higher Loads of Impurities

‒ Demonstrated Process Capability for Impurity Clearance at Small Scale (Wide Design

Space)

‒ Full Scale Process Data Demonstrating Multiple Unit Operations are Capable of

Complete Clearance (Process Redundancy)

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Beyond Product-Specific Attributes: How to Address Other Attribute Types

Composition / Strength / Product Stability CQAs

• Many are Compendial Requirements

‒ Call them “Expected CQAs” (or equivalent term) and skip the scoring

‒ No justification required other than – these are a regulatory

expectation

• Leverage Formulation DOEs to Understand Criticality and Ranges

Required for Acceptable Stability

• Utilize Stability Studies to Identify Attributes That Change Over

Time

‒ Stability data analyses can be used to justify exclusion of attributes

that don’t change over time from post approval stability commitments

and commercial shelf-life specs

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CQA Assessment: Summary of Guiding Principles

• CQA Assessment Should be Documented and Should Include References to Credible

Knowledge Sources

• CQA Assessment Should Consider ALL Relevant MOAs

• CQA Assessment Should be Focused on the Potential Impact of the Attribute if it is

Observed (Attributes are Either Critical or Not Critical Regardless of the Relative

Abundance of the Attribute or Level of Control)

‒ Potential CQAs that are not observed or observed at very low levels may be removed

from the CQA list (or categorized as “low abundance CQAs”) once data is available

using methods with demonstrated capability to detect and quantify the attribute

‒ Relative abundance of the attribute (occurrence) and capability of the analytical

methods to detect the attribute (detectability) are generally addressed as part of the

control strategy risk assessment

• Attributes with High Uncertainty Should be Designated as CQAs

‒ Target supporting studies to improve product understanding so these attributes may be

more appropriately classified

• CQA Assessment Should Evolve During the Development Program

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Control Strategy Elements

• ICH Q10 definition:

• “A planned set of controls,

derived from current product

and process understanding that

ensures process performance

and product quality. The controls

can include parameters and

attributes related to drug

substance and drug product

materials and components,

facility and equipment

operating conditions, in-

process controls, finished

product specifications, and the

associated methods and

frequency of monitoring and

control.”

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What Should be Controlled by the Process and Product Control Strategies?

ANDOther attributes or process

outputs that are indicative

of process consistency

Why Control Other Attributes?

• There may be additional critical attributes that we don’t know about which impact product

safety and efficacy

• Regulators may require us to monitor attributes or process outputs that we might not

believe to be critical to demonstrate process consistency

• Degree of additional monitoring required will depend on the degree of process and product

understanding

• Robustness of the CQA assessment and process parameter classifications

• Data package supporting the proposed control strategy

(universe) (black hole)

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CQA Assessment and Product/Process Understanding Form the Basis for the Commercial Control StrategyCQA Assessment (WHAT Needs to be

Controlled)• Prior Knowledge (Published Studies)

• Platform Knowledge

• Forced Degradation Studies

• Supporting Functional Studies Using

Enriched Variants

• Pre-Clinical Studies

• Clinical Studies

• PQ Testing of Clinical Samples

• On-Market Product Testing

Product and Process Understanding (HOW It Can Be

Controlled)• Process Characterization DOEs

• Process Hold Time Studies

• Impurity Clearance Studies

• Formulation DOEs

• Patient In-Use Studies and/or Human Factor Studies

• Method Capability (Validation, Control Charting)

• In-Process and Release Testing Results

• Stability Data Analyses

• Process Risk Assessments (e.g., FMEA, C&E, etc.)

• Process Validation and Continued Process Verification

Understanding of Molecule Attributes that

are Critical for Safety and Efficacy

Understanding Regarding How to Control the CQAs (and

some non-CQAs indicative of process consistency) During

Manufacture, Distribution, Storage, and Administration of the

Product

Process and Product Control Strategies

• Process Parameter Controls

• In-Process and Release Testing Specifications

• Shelf-Life Specifications

• Input Material or Component Controls

• Validated Controls

• Process Monitoring (alert and action limits, CPV Program and APQRs)

• Additional Characterization Testing (e.g., for Comparability Studies)

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Control Strategy Elements Used to Control CQAs and Other Process Consistency Attributes

Control Strategy Element

or Testing RequirementsDescription

Validated Control or RemovalRobust removal and/or process capability for control of the attribute has been

demonstrated through small-scale or large-scale process validation studies.

In-Process Testing

(with acceptance criteria)

Testing of in-process samples to ensure that selected manufacturing operations are

performing adequately to achieve the intended product quality. In-process tests have

specified acceptance criteria.

Specification Testing (Release) Tests with associated acceptance criteria that are conducted as part of lot release to

confirm that specific quality attributes are within a range that ensures the quality of the

product. Attributes which change during storage will also be monitored using specification

tests as part of the stability program.Specification Testing (Stability)

(for attributes that change during storage)

Input Material or Component Controls

Controls pertaining to raw materials, excipients and components used to manufacture the

product, including supplier quality management systems, raw

material/excipient/component qualification and specifications.

Process Parameter Controls

Process parameters that are linked to Critical Quality Attributes (CQAs), Critical Process

Parameters (CPPs), and process parameters linked to process performance, Key

Process Parameters (KPPs), are controlled within the batch record limits to ensure

product quality

Process Monitoring

Testing or evaluation of selected attributes and/or parametric data to trend product quality

or process performance and/or to enhance confidence in an attribute‘s normal distribution.

The frequency of monitoring is periodically reviewed and adjusted based on trends. The

process monitoring program may include limits for evaluating data trends (e.g., action or

alert limits).

Characterization TestingTesting of specific attributes outside of lot release testing for the purposes of product or

process characterization.

Descriptions adapted from A-Mab case study (CASSS)

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Factors to Consider as Part of the Establishment of Commercial Product Specifications

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Accounting for Attribute Occurrence and Detectability: Example #1

• Occurrence: Assess the Relative Abundance or Likelihood that Levels of Each Attribute Exceed an Established Safety or Immunogenicity Threshold or the Levels Observed for Clinical Materials

• Detectability: Assess Capability of the Analytical Methods for Detection and Quantitation of Each Attribute (or Changes in the Attribute)

• Use the Combined Occurrence and Detectability Scores to Assess the Capability of the Process and Product Control Strategies

• This Approach is Useful During the Development Program to Identify Gaps in:

‒ Process or Product Control Strategies

‒ Process or Product Understanding

‒ Analytical Method Capability or Testing Strategies

• Also Useful Post Approval to Inform Areas of Focus for CPV Programs or APQRs

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Accounting for Attribute Occurrence and Detectability: Tool Example #1

Tables From: Bonam, CMC Strategy Forum Europe, 2013

Typically not

observed and

high detection

capability

Frequently

observed and

low detection

capability

Reduce risks by increasing process/product

understanding during development program and

implementing more robust methods or controls

Part 1:

Part 2

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Accounting for Attribute Occurrence and Detectability: Tool Example #2

• Assess Occurrence of Each Attribute with Respect to:

‒ Depth of Existing Knowledge Regarding How to Control the Attribute (i.e.,

Extensive Knowledge and Data v/s Limited Knowledge and No Data)

‒ Degree of Demonstrated Control of the Attribute in Large-Scale and Small-Scale

Process Runs

• Within the Normal Operating Range (NOR)

• Across a Wider Proven Acceptable Range (PAR) – From DOE Experiments

• Evaluate the Capability of the Process to Control Each Attribute within the

Range of Materials Used in Clinical Studies

• Use the Severity and Occurrence Scores to Determine Required

Detectability for Routine Commercial Manufacturing (“Solve for D”)

• This Approach is Useful:

‒ As Justification for the Commercial Control Strategy Proposed in BLA or Other

Marketing Authorization Applications

Detectability Requirement Score (Dreq) = Occurrence (O) Severity (S)

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Example Occurrence Scoring Matrix: Tool #2

Occurrence

(O) ScoreDefinitions

9

Routine monitoring of the attribute is a clear Regulatory expectation or compendial requirement. Lot

release and/or stability testing (with specifications) are required regardless of demonstrated attribute

control and/or observed attribute range relative to clinical materials OR

Limited knowledge is available regarding the capability of the process and/or material controls for

control of the attribute AND

The attribute levels routinely approach the limits of clinical experience

7

Robust process control was demonstrated within the NOR but no or limited data are available to define

the impact on the attribute outside of the NOR AND

The attribute levels routinely approaches the limits of clinical experience

5Robust process control was demonstrated within the NOR and a wider PAR AND

The attribute levels routinely approach the limits of clinical experience

3

Limited process knowledge is available regarding the impact of process parameters on the attribute but

robust control of the attribute has been demonstrated through the manufacture of multiple DS lots

within the NOR AND

The attribute levels are routinely well within the limits of clinical experience

1Robust process control was demonstrated within the NOR and a wider PAR AND

The attribute levels are routinely well within the limits of clinical experience

1 Attribute is not observed (below the method limit of detection) or is observed only at trace levels.

1For process-related impurities, levels of the impurity are below levels of concern in representative lots

and can be supported by published or internal safety data

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Determining Control Strategy Requirements Using Detectability Requirement Scores: Example Tool #2

Detectability

Requirement

Score

(Dreq = S O)

Required Control Strategy

or Testing Requirements

≥ 50

Validated Control or Removal

In-Process Testing

(with acceptance criteria)

Specification Testing (Release)

Specification Testing (Stability)

(for attributes that change during storage)

30 to 49

Input Material or Component Controls

Process Parameter Controls

Process Monitoring

≤ 30 Characterization Testing

Attribute

Occurrence

Score

Attribute Severity Score

(CQA Assessment)

9 5 1

9 81 (H) 45 (M) 9 (L)

7 63 (H) 35 (M) 7 (L)

5 45 (M) 25 (L) 5 (L)

3 27 (L) 15 (L) 3 (L)

1 9 (L) 5 (L) 1 (L)

RPN ScoreRequired Control Strategy

or Testing Requirements

High (H)

• Validated Control or Removal

• In-Process Testing

• Release Specification

• Shelf-Life Specification

Medium (M)

• Input Material or Component Controls

• Process Parameter Controls

• Process Monitoring

Low (L) • Characterization Testing

non-CQAs Will Generally Fall Into Less Stringent Control Categories

(Process Monitoring or Characterization Testing)

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Describing the Control Strategy in the BLA: A Few Example Drug Substance Attributes

DS Attribute and

Method Reference

CQA or

Non-CQA

Severity

(S)

Score

Occurr-

ence (O)

Score

Justification for

Assigned

Occurrence Score

Supporting

Data

Reference

Calculated

Detectability

Requirement

Score

(Dreq = S O)

Control Strategy

Implemented to Address

Detectability Requirement

pH

pH <791>CQA 9 9

Compendial

requirement

3.2.S.2.6

3.2.S.2.4

3.2.S.4.5

3.2.S.7.3

81

In-Process Testing (IPT)

Specification Testing

(Release and Stability)

Endotoxin

Bacterial Endotoxins USP <85>CQA 9 9

Compendial

requirement

3.2.S.2.4

3.2.S.4.4

3.2.S.4.5

3.2.S.7.3

81

In-Process Testing (IPT)

Specification Testing

(Release and Stability)

Residual HCP

Host Cell Protein (ELISA)CQA 9 9

Regulatory

requirement

3.2.S.2.4

3.2.S.4.4

3.2.S.4.5

81

Process Parameter

Controls

Specification Testing

(Release)

Residual Solvents

Residual Solvents (GC-FID)

- Isopropyl alcohol

CQA 9 9Compendial

requirement3.2.S.2.5 81 Validated Clearance

High Mannose Structures

N-Linked Glycans (HILIC-UPLC)CQA 9 1

Purification

process within

the NOR

effectively

removes low

levels of High

Mannose present

at end of cell

culture (process

characterization).

Levels in DS are

below limit of

detection.

3.2.S.2.6

3.2.S.3.29

Process Characterization

Characterization Testing

Continue Table for All Drug Substance Attributes

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Evolution of Product and Process Knowledge Across the Development Program

Definition of

control strategy

based on design

space leading to

control of

quality and

quality risk

managment.

(process

robustness)

Proposal of

regulatory

flexibility based

on product and

process,

scientific

knowledge, and

quality risk

management.

(materials, site,

scale, etc.)

Quality Target

Product

Profile

Prior

Knowledge

Product /

Process

Development

Product /

Process

Design Space

Control

Strategy

Regulatory

Flexibility

Breadth and depth of knowledge regarding CQAs and how they can be

modulated by the manufacturing process informs the commercial

control strategy and regulatory requirements for commercial

manufacturing and post-launch changes

Commercial control strategy and

regulatory expectations are

informed by extensive CQA and

product/process knowledge and

are right-sized to ensure patient

safety and product efficacy

CQA Assessment and Knowledge from

Process and Product Development and

Clinical Studies

EFPIA Working Group with minor modifications

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Pre-Clinical (Tox)

Early Clinical

(Ph 1)

Late Clinical

(Ph 2-3)

Validation PPQ

Commercial

Leverage historical experience

Platform Processes, Methods & Specifications

Batch Records

Product knowledge and risk assessments

Process Robustness, Process Parameter Ranking & Validation

Quality Attribute Ranking & Specifications

Method Validation

Continued Process & Method Verification

Quality Systems

Annual Product Quality Review (APQR)

Comparability to Support Post-Approval Changes

Application of Principles Across the Product Development Timeline

Acquire and Document Knowledge Apply Knowledge

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Acknowledgements

• James Carroll (CASSS speaker invitation)

• Sam Billingham

• Mariah Deguara, Dave Sharp

• Richard Cornell, Katrina Kearns, David Cirelli

• Bryan Bernat

• Xiaoyu Chen

• Julie Terwee

Thank You!