INDUSTRY CASE STUDY: CONTINUED PROCESS VERIFICATION (CPV

INDUSTRY CASE STUDY: CONTINUED PROCESS VERIFICATION (CPV) FOR A BIOTECH PRODUCT OUTPUT FROM BIOPHORUM OPERATIONS GROUP (BPOG) COLLABORATION OF BIOTECH COMPANIES Presenting to the IFPAC Meeting (Jan 2014) on behalf of the BPOG CPV Workstream

Outline Background Case Study 1.

Why write this Case Study?

2.

How has it been put together?

3.

What does the Case Study contain?

4.

What are the Key Learning Points?

Application Scenarios CPV Benefit Estimates Outstanding topics for further discussion CPV Document Slide Pack V5.4 4-Feb-14

2

Background The BioPhorum Operations Group (BPOG) is an industrywide collaboration to enable networking and to share best practice in the area of Operations. Beginning in 2008, it now has 26 member companies with over 600 participating representatives. The community primarily consists of experts from biopharmaceutical drug substance operations, who meet and work together at face-to-face meetings in the USA and Europe, on regular teleconferences and via web meetings. The group has established best practice on a wide range of quality, engineering and organizational topics considered central to the challenge of mastering effective biotech drug substance operations. CPV Document Slide Pack V5.4 4-Feb-14

3

1. Why Write a CPV Case Study?  New industry regulatory guidelines published by FDA in 2011  Little experience submitting new license applications under these guidelines

 Very few articles on the topic and most literature covers only some aspects of the topic

 Very few articles written by actual practitioners  Cross-functional and complex – affecting several functions & disciplines

 Convenient & clear way to share perspectives across the industry and with regulators CPV Document Slide Pack V5.4 4-Feb-14

4

Purpose • To exemplify implementation of Continued Process Verification (CPV), third stage of process validation lifecycle as presented in FDA’s 2011 Process Validation guidance • To identify then realize the benefits of implementing CPV: – Comply with FDA guidance – Improve process control – Clarify opportunities for process improvement – Reduce operating costs – Reduce cost of goods – Increase access to products

CPV Document Slide Pack V5.4 4-Feb-14

5

Concept of the Case Study  Recommendations & rationale for “end-to-end” illustrative plan for Continued Process Verification (CPV)  Plan links process design to continued process verification and its lifecycle • Initial CPV plan focus (post-PPQ completion)

 Process description and development taken from industry generated “A-mAb Case Study”* • Except without building on design space claims

 Case study focuses on Drug Substance • Drug Product effort planned (with analogous DP Biophorum group) • Ref:A-mAb: A Case Study in Bioprocess Development, CMC Biotech Working Group. 2009 (Available free download at ispe.org) CPV Document Slide Pack V5.4 4-Feb-14

6

2. How was it assembled?  Reference to the A-mAb case study  Independent co-ordination & facilitation  Broad input & contributions from all participating member companies  A sequence of virtual meetings  A face-to-face event  An editorial process  An approvals process  Free of charge access to full case study, once finalised • http://www.biophorum.com/page/123/BPOG-CPV-Case-Study.htm


7

3. What does the Case Study contain? Selected Outline Descriptions of CPV implementation

• • • • •

Purpose and Scope Roles and Responsibilities References (as used in CPV Plan) Product and Process Description Development of a CPV Strategy

Embedded elements of an illustrative CPV plan

– Scope of Data Collection and Analysis Plans – Establishing Initial Control Limits

• CPV Execution Plan - Including Lifetime Limits & Other Monitoring - Change control decision tree

• Sampling and Data Management - Sample Plans/Templates – Data Entry and Verification – Data Analysis Methods & Responses CPV Document Slide Pack V5.4 4-Feb-14

• Discretionary Elements of Guidance • External references

8

Product and Process Description Product and Process for CPV plan is based on A-mAb study Product Development based on a “QbD approach”** applying principles from ICH guidelines Q8, Q9, Q10 & Q11 Identification of Quality Attributes (QA) based on Quality Target Product Profile (QTPP) Risk evaluation to identify Critical Quality Attributes (CQAs) Upstream / Downstream process description Risk-based approaches and analyses to classify process parameters and other variables linked to product quality (e.g. identification of Critical Process Parameters - CPPs) • Univariate or Multivariate Approaches to define Proven Acceptable Ranges or Design Space** • Rational approach to define Control Strategy that reflects product/process knowledge and risk • Background used to develop presumed Process and Equipment Performance Qualification (Stage 2) to verify established control strategy (Stage 1)

• • • •

** Although A-mAb claims a design space, this case study does not address CPV concepts associated with design space implementation CPV Document Slide Pack V5.4 4-Feb-14

9

Pre-requisites for Continued Process Verification

TPP

QTPP

CQA

CPP

Covered in A-Mab Study

PV Stage 1

• •

Proven Acceptable Ranges (Design Space)

CPV

CPV

PPQ EQ

PV Stage 2

Short-term Plan

Long-term plan

PV Stage 3

CPV plan (this work), covering PV stage 3 requirements, follows available data from PV stage 1 (A-mAb) & assumed outcome from PV stage 2 Short-term (initial) plan created that develops into a long-term (lifetime) plan


10

CPV Strategy: Assurance of Control Strategy  Control strategy consists of quality-linked process parameters (CPPs and WCCPPs), Key Process Parameters (KPPs), Key Process Attributes (KPAs) and IPCs.  Control strategy ensures required product quality (CQAs) and consistent / robust process  Elements of control strategy should be monitored and improved in accordance with ICH Q10 Sect. 3.2.i): “Pharmaceutical companies should plan and execute a system for the monitoring of process performance and product quality to ensure a state of control is maintained. An effective monitoring system provides assurance of the continued capability of processes and controls to meet product quality and to identify areas for continual improvement.” CPV Document Slide Pack V5.4 4-Feb-14

11

CPV Strategy: Production Monitoring Considerations  Demonstration of consistent robust production within validated parameters  Product history and knowledge  Areas of greatest risk  Frequency of production


12

CPV Strategy: Recommendations for A-mAb drug substance Written plan to examine data that establishes process capability and control limits that account for normal process variability – Assumes successful PQ (PPQ & EQ)

Variables to be considered for data gathering include: – Critical Quality Attributes (CQAs) – Critical Material attributes (CMAs) – Critical Process Parameters (CPPs) – In-process controls (IPCs) – Key process parameters and key process attributes (KPPs and KPAs)

Not required to include every CQA, CPP, CMA, etc. in CPV plan, but provide justification for what is included/not included -- Explain why included items sufficient to meet CPV plan’s objectives


13

CPV Strategy: Application to A-mAb Drug Substance Process Example – Step 6, Low pH treatment for reduction of adventitious viral agents (AVA) Variable

Class

CQAs impacted

CPV recommendation & rationale

Recommended elements to include in CPV

pH (during inactivation)

CPP

AVA, aggregates

Include, to confirm product quality

Post-inactivation aggregates

CQA

--

Include, to establish SPC capability

Optional elements to include in CPV (supplementary) (Inactivation) time

CPP

AVA

Optional, to augment SPC capability

Quantity of acid added

KPP

--

Optional, to further confirm process consistency; linked to inactivation pH





Additional justification for including/excluding other variables (e.g., KPPs and KPAs, remaining CQAs and CPPs) based on sufficient verification during PPQ and expectations of minimal variation Qualitative nature of measurement may also justify exclusion


14

CPV Strategy: Scope of Data Collection and Analysis Plans • Typically starts with the PPQ batches • Informed by clinical or scale up batch data • Two phases: – Initial, Short-term: Stage III-A • Prior to Statistical Process Control (SPC) • Accumulate ~30 batches to set limits based on statistical significance • Review parameters and update risks

– Long-Term: Stage III-B • • • •

Introduce SPC with rules for alerts Continue ongoing process verification Understand variation and trends Identify opportunities to continuously improve process


15

CPV Strategy: Establishing Initial Control Limits  Although clinical and scale up batches indicate process performance, they may not give statistically valid basis for establishing control limits. PPQ batches (commercial scale) are of course relevant here… • Initial control limits must not be regarded as ‘acceptance criteria’

 Once sufficient data gathered and performance of process vs. variation in attributes / parameters understood through correlation, control limits can be confirmed  May be possible to aggregate some data sources to establish highly sensitive multivariate performance indicators • PLS model utilized in A-mAb for production bioreactor

 High level of statistical competence required to ensure performance indicators interpreted appropriately CPV Document Slide Pack V5.4 4-Feb-14

16

CPV Execution Plan (post-PPQ timeframe) Tables of variables selected for CPV for each process step with:  Classification of each variable (CPP, CQA, KPP, KPA, IPC, CMA)  Data treatment prior to analysis • Unadjusted, converted for standardization, combinations/data interactions  Monitoring tool options • Run chart, Control chart, EWMA (Exponentially-Weighed Moving Average), 3SD tunnel, or by exception (trend atypical results only)  Initial baseline monitoring (Short-term) • Series of next several batches (~30) to set long term sigma for control limits  Initial baseline control limits (Short-term) • Based on PPQ limits and other data (not acceptance criteria but alert triggers linked to control strategy content). No long-term limits during initial period.  Periodic evaluation (time/batch-based or event-based) • Every X batches, annually, or at end of campaign; aligned to raw material lot changes, etc.  (Proposed) Lifetime control limits (Long-term) • Robust SPC ranges & PpK from baseline analysis. Avoid limit updates that mask drift or special cause variation. Track limit history in case reset needed.  For cause evaluation (change-based) • Planned process change triggers (e.g. cell bank, modified controls) CPV Document Slide Pack V5.4 4-Feb-14

17


18

Sampling Management  Sample plan and frequency • Routine monitoring • Non-routine monitoring o Baseline monitoring, time-based periodic monitoring, or special event / change based monitoring

• Other sampling o Intermediate stability/hold time, resin reuse, cleaning verification

 Specific / representative sampling location and collection • Sample container and container size • Sample volume, aliquots, and retains o Sample labelling o Sample storage temperature and transport conditions • Follow existing SOPs and batch records for collection • Tests to be performed (including additional samples such as reference solutions)

 Testing limits or ranges of expected results Sample Plan Matrix Sampling/Testing Template CPV Document Slide Pack V5.4 4-Feb-14

19

Sample Plan Matrix (Attributes)

Product variant

Truncated impurity

Antifoam

•

ο

Methotrexate

•

ο

ο

•

∆ ο

ο

Affinity ligand

•

•

ο

DNA

•

ο

Potency

•

product conc.

ο

HCP

•

Aggregates

Charge Variants

Conductivity

•

10 mls <-40 °C N Y 42

Step 4: Affinity chromatography Load post hold period Load flow-through Elution pool Strip flow thru Step 9: UFDF Load pool post hold period Permeate during concentration Retentate pool post diafiltration Step 10: Bulk filtration and Freezing post hold period, prior to filter Bulk sample prior to freeze

Routine test Retain Non-Routine test Stability Reuse Lifetime Performance Cleaning Verification CPV Document Slide Pack V5.4 4-Feb-14

Endotoxon

U n it o p s

Product Quality Tests

Bioburden

Sample volume Storage temp Testing offsite Testing onsite Method SOP

pH

Retain

CQA/IPCs/KPAs

A280 conc

On-floor tests QC Micro

ROUT RETN NROU STBL LFTM CLNV

•

•

Type of test

20

Template for Sampling and Testing (Attribute) Process Step Step 7: Cation Exchange Chromatography Variable Aggregation Classification (Quality Attribute or Process Parameter) Assay Method Sample Plan Sample Frequency

Sample location Sampling device Sample Collection

Sample Storage Sample Transportation Assay Testing Results

Container MOC Container Size Sample Volume Sample Replicates Sample Retain Sample Handling Sample Labeling Temp Location Transport Who Reference/Blank Criteria

Options for consideration

CQA SEC

CPP

KPP

KPA

Routine Monitoring

Baseline Monitoring

Time-based Periodic Monitoring

Special Event or change based monitoring

Multiple times in a batch (e.g., every day for bioreactor)

once per batch

every X batches

automated sample valve no sample - on-line instrument

automated sampling device

After eluate is well-mixed at the eluate collection tank manual sample valve PP tube, sterile 10 ml 5 ml None None Nothing additional Driven by SOP Ambient Manufacturing Yes (per SOP) Manufacturing Reference Release specifications

2 Yes aliquoted

in-line sensor

prepared for shipping

2-8 C QC Lab No

-20 C Development lab

-70 C Sample Control

QC Dept Blank Solution Control limit

Development Dept Control Control chart rules

External Lab None None

Selections highlighted (in yellow) CPV Document Slide Pack V5.4 4-Feb-14

21

Data Management • Covers data collation, entry and verification • Data aggregation in usable format--preferably single digital file • Many data sources likely manually recorded

• Goal: Verify data accurately transcribed from source (batch records, assay forms) to data storage system Database

• Double Blind Data Entry / System

• Data Entry / Manual Verification

• Error Proofing

Database

– Errors during manual data entry are unavoidable but can be minimized – Data Storage System flags out of range /out of trend values CPV Document Slide Pack V5.4 4-Feb-14

22

Discretionary Elements of Guidance  Although fundamentals clear, several ‘discretionary’ elements exist Element

Description

Guidance text

Operational or Performance Elements

Process performance attributes (i.e., bioreactor titer, column elution volumes) or input parameters linked to process performance attributes..

“Many products are single-source or involve complicated manufacturing processes…..Validation offers assurance that a process is reasonably protected against sources of variability that could affect production output, cause supply problems, and negatively affect public health.” “An ongoing program to collect and analyze product and process data that relate to product quality must be established (§ 211.180(e))….The information collected should verify that the quality attributes are being appropriately controlled throughout the process. “

Multivariate Analysis (MVA)

MVA, particularly Partial least squares (PLS) regression or Principal component analysis (PCA), may be used to identify latent variables and increase understanding

“We recommend an integrated team approach to process validation that includes expertise from a variety of disciplines (e.g., process engineering, industrial pharmacy, analytical chemistry, microbiology, statistics, manufacturing, and quality assurance). “

Column/Resin/UF Membrane Cleaning and Performance Lifetime Verification

Full scale verification of column and/or ultra-filtration membrane cleaning and performance out to established lifetime limits

“The extent to which some materials, such as column resins or molecular filtration media, can be re-used without adversely affecting product quality can be assessed in relevant laboratory studies. The usable lifetimes of such materials should be confirmed by an ongoing PPQ protocol during commercial manufacture. “


23

4. What are the Key Learning Points? • Differences in regulatory histories of biotech companies lead to different perspectives on response(s) to regulatory guidelines • With a common purpose, differences can be recognised & accounted for, quickly establishing a consistent position (or else clear reasons for divergence!) • Establishing a CPV plan is complex, requiring a team with a range of knowledge working together to be comprehensive and deliver real results • Additional monitoring, beyond what has been previously done, can be a value-add • Simple and cost-effective IT solutions are needed to support CPV implementation


24

Utility of the CPV Case Study  Comprehensive industry mock example to illustrate CPV program implementation

 Embedded detailed available process design and process development information from widely available prior case study  Includes perspectives from wide cross-section of biotech industry participants

 Groundwork for further useful discussion on implementation


25

Scenario 1. Supplier change notification: Culture media manufacturing change  A supplier modified their process to manufacture a cell culture media ingredient that may alter performance of A-mAb process, despite lack of impact on raw material specifications. Supplier claimed that no intentional changes to composition, test requirements or certificate of analysis were made.  Justification for the change was provided: (1) Improved control of temperature during blending reduces potential for degradation of the heat labile components; (2) Equipment cleaning will use robust validated cycles to reduce ingredient carryover risks; (3) Equipment is located in an Animal Origin Free area to reduce cross contamination risks.


26

Scenario 1. Supplier change notification: Culture media manufacturing change  Strategy employed to introduce revised cell culture media: • Risk-based determination of process and quality impact for the material change through change control process o Outcome: Verification testing needed to assess culture performance and ability to operate within established parameters and attributes

• Small scale study completed from thaw through the production bioreactor to provide additional process characterization data o Outcome: Minor but statistically significant differences for key process parameter normal operating ranges and attributes (e.g. VCC, , titer and turbidity at harvest) identified

 Media qualification attributes assessed in the change control evaluation to determine if/how these attributes may be impacted  Small scale production bioreactor material purified. No structural modifications to protein, or shifts in CQAs observed  CPV impact: Based on small scale study outcome, DS product quality at full-scale should be

evaluated to provide further verify step performance and process control ranges by examining data before/after change. Based on this evaluation, and associated risk assessment, changes to CPV monitoring plan can be considered.


27

Scenario 2. High Protein A leachate observed in chromatography eluate, step 5  A PPQ batch contained 123 mg of protein A/g A-mAb in Protein A pool, which exceeded in process control limit, but not DS release specification, for this process-related impurity.  Investigation revealed that: • Protein A ligand released from the chromatography resin (‘Resin A’ from Supplier A) and entered process stream during product elution. R&D and Supplier A confirmed that elevated amounts of Protein A can leach from bead surface during an initial elution after extended resin storage-- even when storing under recommended conditions. • Extended storage can cause increased Protein A leaching in the next use cycle. The resin storage time of more than 12 months between last clinical manufacturing batch and first PPQ batch was longer than previously experienced and was not represented in small scale trials used to establish PPQ limits. CPV Document Slide Pack V5.4 4-Feb-14

28

Scenario 2. High Protein A leachate observed in chromatography eluate, step 5  Strategy developed: • Risk analysis of the level measured in eluate was orders of magnitude below impurity safety limit for final drug product. • Downstream clearance of Protein A below detectable level was demonstrated for this batch, which is consistent with small-scale observations that subsequent chromatography steps capable of removing leached Protein A. • Additional Design of Experiments (DOE) study conducted after PPQ to determine potential for Protein A leaching relative to storage time, resin age (use cycles) and storage conditions. • Spiking study confirmed downstream clearance capabilities and identified new CPPs to control clearance which then were updated in control strategy

 CPV impact • For an initial period, in-process testing of Protein A content performed to assess process capability • Newly identified CPPs monitored for a set of 3 batches, then consider addition to plan CPV Document Slide Pack V5.4 4-Feb-14

29

Benefits vs Costs of CPV  Estimates of intangible and tangible (eg, monetary) benefits highly dependent on the product/process scenario  Data and information gained as a result of CPV is likely to: • Raise the standard of reporting at APRs; • Lead to improvements in the manufacturing process • …….Enhance transparency internally and with regulators

 Costs associated with CPV vary considerably based on data retrieval system • Estimate of effort required to create one CPV report for A-mAb product • For “mostly manual” system, working assumptions made: o 3 CPV reports (excluding APR) o 20 attributes/parameters trended o Per data set: 3 hrs to retrieve; 1 hr to create control chart; 4 hrs to analyse / investigate

• Indicates about 10 additional person-weeks of effort each year (~ $50 K at $200 K/person/year) o For 3 sites each executing 5 CPV plans, manual implementation costs ~$250k/year

 A multi-site integrated data management system costing ~ $1.25 MM expected to reduce effort by ~ 50% or $125k/year • System takes ~ 3 years to pay for itself • Shorter payback if consider costs of losing one batch (~ 1 MM)


30

Outstanding Topics for Further Discussion  Type & extent of supporting justification for not initially trending certain “wellcontrolled” variables not subject to random variation or performance drift  Additional rationale for initial decisions on what is trended and how that monitoring accomplished considering limited commercial-scale experience • Ability to justify exclusion of qualitative measurements

 Return to initial “short term” control limits before setting (or re-setting) lifetime “long-term” control limits after implementation of changes  Extent and application of statistics, especially for non-normal data  Use of formalized acceptance criteria or limits in an approved plan that might trigger extensive investigations (eg, control chart rule triggers) • Decision-tree for product quality impact

 Risk-based monitoring of attributes/parameters related to understanding/improving process consistency (eg, titer, yield, intermediate stream quality measures, cycle time, etc)  Relationship of CPV plan to ongoing PPQ protocols (eg, resin / membrane reuse)  Application of CPV to licensed products with extensive manufacturing experience CPV Document Slide Pack V5.4 4-Feb-14

31

BACKUP

 Some additional background slides


32

Pfizer

Covers short term Control Limits

Covers long term Control Limits

This is an attempt to link CPV related documents (red) with corporate (orange) and site specific (white) documentation. It is still a work in progress. CPV Document Slide Pack V5.4 4-Feb-14

33

Industry Case Study: Continued process verification (CPV) for a biotech product Beth Junker, Merck and Co, on behalf of BPOG Version: 1 Date: 21 Dec 2013

 Continued Process Verification (CPV) encompasses a written plan for monitoring a licensed biopharmaceutical manufacturing process, then documenting and reporting the results. CPV reporting provides a basis from which to improve process understanding, and hence risk assessment, control strategy, and ultimately process improvement. This presentation describes one of the first cross-company efforts to be compiled on CPV in response to the FDA’s 2011 process validation guidance. It has been created by representatives from 20+ biopharmaceutical companies, sharing and building knowledge, with support and facilitation from the BioPhorum Operations Group (BPOG) (www.biophorum.com). We describe general approaches to implementing CPV and offer some specific recommendations on the content of a CPV Protocol, along with associated rationale. These recommendations are based on a typical cell culture production process for making a fictitious monoclonal antibody product described in the ‘A-Mab Case Study’. Consequently, these recommendations may not apply directly to specific products or processes, but the principles and concepts described can be considered where applicable.  In general, the nature and extent of CPV is aligned with the outcomes of Process Qualification (PQ). Adopting a monitoring system to reveal manufacturing trends offers the ability to acquire more data over the product’s lifetime. Hence, a deeper understanding of the process is acquired, along with a foundation for enhancements to the Control Strategy (CS). CPV execution may involve examination of process control variables to improve methods for data tracking and analysis. Monitoring process performance provides the opportunity to identify sources of variation and hence improve process robustness. For products that are recently commercialized, there is unlikely to be a statistically robust set of manufacturing scale data. To practically, manage this situation, short term control criteria are set initially based on prior process experience including at the laboratory or clinical scales. This early period of production then is used to establish the longer term criteria.  The implementation of CPV systems likely requires significant effort, beyond what is typically prepared for the Annual Product Review (APR), because substantial amounts of additional data are collected and analyzed to improve understanding of process variability. The benefits of improved process management are expected to outweigh this additional investment. Such benefits include improved information supporting both annual products and continuous process improvements. The frequency of data analysis and reporting depends on several factors, including: whether production is campaigned or continuous; the extent of variability apparent in the process; if risks to product quality (and thus product disposition) and process consistency are sufficiently mitigated, and the intended usage of the reported data. CPV Document Slide Pack V5.4 4-Feb-14

34

Background from a-mAb – Step 1: The Quality Target Product Profile (QTPP) QTPP describes quality characteristics (attributes) of the Product to reproducibly deliver therapeutic benefit promised in the label Attributes in the red box are tested during Drug Substance manufacturing. These attributes reflect DS CQAs relevant for CPV monitoring. The Criticality Analysis was performed using risk ranking approaches (per ICH Q9).

QTPP used to establish Critical Quality Attributes (CQAs)


35

Background from A-mAb – Step 2: Critical Quality Attributes (CQAs) Claimed acceptable ranges based on prior knowledge, in-vitro studies, non-clinical studies and clinical experience. Attribute

Claimed Acceptable Range

Rationale for Claimed Acceptable Range

Afucosylation

2-13%

2-13% afucosylation correlates with 70-130% ADCC activity. Lower end covered by prior knowledge; upper end covered by modeled material in animal model.

Aggregation

0-5%

5% upper range claimed based on prior clinical experience with X-Mab.

Deamidated isoforms

None claimed; measure of consistency

NA

Galactose Content

10-40%

Range is based on a combination of prior knowledge (Y-Mab experience) and clinical experience.

HCP

0-100 ng/mg

Sialic Acid High Mannose

0-2% 3-10%

100 ng/mg upper limit claimed based on prior clinical experience with XMab. In vitro studies with A-Mab. Clinical Experience with A-Mab.

Non-Glycosylated Heavy Chain

0-3%

Clinical Experience with A-Mab.


36

Background from A-mAb: Risk Evaluation of Process Parameters

Consistency of Terminology Addressed

Parameters divided into critical and non-critical groups. Further differentiation into a wellcontrolled section made based on control and capability

Terminology used from A-mAb study. Key for each company to explain individual risk evaluation approach selected terminology. Terminology preferably based on ICH. CPV Document Slide Pack V5.4 4-Feb-14

37

Background from A-mAb – Step 3: Critical and Key Process Parameters (CPPs and KPPs) Upstream process Process Step WCB

CPP

KPP

none

temperature, time

Step 1: Culture expansion in disposables

none

temperature, culture duration, initial VCC/ split ratio

Step 2: Culture expansion in fixed bioreactors

none

temperature, pH, dissolved oxygen, culture duration, initial VCC/ split ratio

temperature, pH, dissolved CO2, culture, duration, osmolality, remnant glucose

antifoam concentration, time of nutrient feed, volume of nutrient feed, time of glucose feed, volume of glucose feed dissolved oxygen

none

flow rate, pressure

Step 3: Production culture

Step 4: Centrifugation and filtration


Critical and key process parameters established for upstream and downstream steps.

Used as basis for establishing control strategy .

38

Background from A-mAb – Step 3: Critical and Key Process Parameters (CPPs and KPPs) Downstream Process Process Step

CPP

KPP

Step 5: Protein A Chromatography

protein Load, elution buffer, pH

end collection

Step 6: Low pH treatment

pH, time, temperature

none

Step 7: Cation Exchange Chromatography

protein load, load/wash, conductivity, elution pH, elution stop collect

none

Step 8: Anion Exchange Chromatography

load pH, protein load, flow rate, load conductivity

none

Step 9: Small virus retentive filtration

operating pressure, filtration Volume

none

Step 10: Ultrafiltration, diafiltration

none

none

Step 11: Final filtration, freezing

none

none


Critical and key process parameters established for upstream and downstream steps.

Used as basis for establishing control strategy .

39

Background from A-mAb: Typical commercial mAb upstream manufacturing process Thaw Working Cell Bank

Upstream Process: Starting Material:

Seed Maintenance

Seed Culture Expansion (flasks or bags)

Seed Maintenance

Seed Culture Expansion (tank)

- Frozen Working Cell Bank Seed Culture Bioreaction (3,000L)

End of Upstream Process: - Clarified Bulk

Nutrient Feeds Process Flow charts used as basis for CQA/CPP evaluation and establishment of Control strategy prior to Product & Process Qualification (PPQ)


Production Bioreaction (15,000L) Harvest Centrifugation and Filtration 40

Background from A-mAb: Typical commercial mAb downstream manufacturing process Protein and Affinity Chromatography

Downstream Process: Starting Material:

- Clarified Bulk

Low pH Incubation Cation Exchange Chromatography Anion Exchange Chromatography

End of Downstream Process:

- A-mAb drug substance

Small Virus Retentive Filtration Formulation – Ultra-filtration and Diafiltration

Process Flow charts used as basis for CQA/CPP evaluation and establishment of Control strategy prior to PPQ CPV Document Slide Pack V5.4 4-Feb-14

Formulation – Final filtration and freeze 41

Background from A-mAb: Development of Control Strategy (upstream)

Monitoring and control ensures that process operated in consistent and predictable manner. Control of key process parameters and attributes also ensures commercial success criteria (such as cycle time and yield) are met.


42

Background from A-mAb: Development of Control Strategy (downstream)

From A-Mab Case Study. CPV Document Slide Pack V5.4 4-Feb-14

43

INDUSTRY CASE STUDY: CONTINUED PROCESS VERIFICATION (CPV

Recommend Documents