leveraging process and product understanding to develop...

This document provides an outline of a presentation and is incomplete without the accompanying oral commentary and discussion. Conclusions and/ or potential strategies contained herein are NOT necessarily endorsed by Pfizer

management. Any implied strategy herein would be subject to management, regulatory and legal review and approval before implementation.

Leveraging Process and Product Understanding to

Develop and Implement a Holistic Control Strategy

Ranga Godavarti

WCBP, Washington DC

27 January, 2015

Presentation Outline

• Control Strategy Concepts

• Pfizer’s Lifecycle Approach to Control Strategy

• Case Study 1: Late Phase implementation of Control

Strategy for high molecular mass species CQA (HMMS)

– Focus on enhanced process understanding

• Case Study 2: ‘Fit-for-purpose’ or lifecycle implementation

of control strategy for HMMS

– Focus on enhanced product and process understanding

• Future Directions

• Conclusions

Pfizer Confidential │ 2

3

Comprehensive Approach to Control Strategy

Delineates Various Control Elements

‘Fit-for-purpose’/Lifecycle Approach to Control Strategy Continuum:

Control attributes consistent with level of knowledge and clinical stage


Discovery

• Molecular Assessments

• Select best candidate by engineering out high risk attributes

Early Clinical

Phase 1/2

• Identify potential CQAs based on prior knowledge, literature

• In-vitro/non-clinical studies for certain product variants

• Understand mechanism of action (MOA)

Post-POC/Ph 3

• Revise CQAs based on non-clinical, in-vivo studies as well as MOA understanding

• Develop control strategy for CQAs and non-CQAs

Launch/BLA Post-market

• Finalize DS

and DP control

strategy

• Testing and

monitoring plan

• Specs based

on clinical

exposure,

structure-

function and

non-clinical data

• Life cycle

management

Process Development

Drug Safety/Tox

Research Units

Process Development

Tech Services Manufacturing


Ele

men

t

Description

Drug Substance Drug Product

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1 Direct In-process Monitoring or

Control of Product QA None None

2 Monitoring or Control of PP or MA

Related to Product QA a a a b b


Control of PPA N/A


Related to PPA N/A

5 Drug Substance & Drug Product

Testing (Routine & Non-routine)c QA Controlled with Acceptance Criteria QA Controlled with Acceptance Criteria

6 Stability Testingc QA Controlled with Acceptance Criteria QA Controlled with Acceptance Criteria

7 Control of Raw Material Related to

QA or PPA None

8 Facility and Equipment Controls None

a Culture viability during inoculum train controlled to prevent sub-selection of cells which could lead to altered product quality. b Quality attribute controlled by process design of this unit operation with no specific PP or MA related to quality attribute. c Drug substance and drug product testing and stability monitoring only performed on the final material and not in-process.

QA: Quality Attribute; PP: Process Parameter; PPA: Process Performance Attribute; MA: Material Attribute; N/A: Not applicable

Areas that are in yellow indicate the controls in place.

Case Study 1: Initial Control Strategy for HMMS Relies on

Process Design, DS and DP Release and Stability Testing

Enhanced Process Understanding for Control of

HMMS: mAb Purification Process

Protein A

Clarified CHO Culture

Anion exchange

Virus filter

UF/DF

Capture column

Single polishing step (“weak partitioning mode”)

Assurance of viral safety

Buffer exchange and concentration

Weak Partitioning Chromatography: A high

capacity, high performance polishing option

Log Cl -

Lo

g K

p

Bind Flowthrough

Weak

Partitioning

• Pool collection - isocratic

• Binds 1-20 g/L of product

• Maximize purity with acceptable yield p C

Q K = =

[free]

[bound]

Total Cl-

pH

Kp >10

Kp 10

Kp 3.0

Kp 1.0

Kp 0.3

Kp

Enhanced Process Characterization Reveals HMMS

and Impurity Breakthrough on AEX step

Fraction Turbidity % HMMS HCP (LRV)

Load 28.1 3.5 -

1 4.9 0.9 >3.0

2 18.6 2.1 1.1

3 24.8 2.8 0.9

4 25.3 3.2 0.9

5 21.4 3.2 0.9

1200

1300

1400

1500

1600

1700

1800

mAU

55.0

60.0

65.0

70.0

75.0

80.0

mS/cm

500 1000 1500 2000 2500 ml

F2 F3 F4 F5 F6 F7

Impurity Breakthrough

1 2 3 4 5 Control Limit

(250 mg/mL)

HMMS breakthrough correlates to other impurities: HCP, DNA, virus

Impurity breakthrough also correlates to turbidity increase

Dynamic Light Scattering of AEX Load suggests

presence of large multimeric species

• ~25 nm multimeric

species present-

confirmed as protein

• Levels higher in early

Protein A (TMAE load)

cycles

• Higher levels result in

higher turbidity of

TMAE load

Larger species

~ 25 nm.

0

10

20

30

40

50

60

70

80

1 10 100

TMAE Load pools

DLS at 10 mg/mL

R(nm)

Cycle # 2

Cycle # 6

Cycle # 10

Scatt

ering I

nte

nsity (

%)

R (nm)

Pro A

Culture

AEX

Depth

filtration

Depth Filtration of AEX Load Provides

Significant Reduction of HMMS and Turbidity

• Depth filtration of AEX load

– Significant reduction in HMMS and turbidity

– Capacity was regained to >1000 mg/mL

AEX Pool Purity

Assay No-Depth Filter Post Depth Filter

Turbidity (NTU) 26 5

HMW (%) 4.3 1.0

HCP (LRV) <1.0 >3


0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

0 10 20 30 40 50 60

HM

MS

NTU

HMMS Multimer (%)

HMMS Dimer (%)

Practically eliminated

After

Depth

Filter

Before Depth Filter of

Pro A Peak Pools

~ 2x reduction

Turbidity Measurement is a Surrogate for

multimeric HMMS: PAT to Control HMMS

• Reduction of turbidity (NTU)

post-depth filtration correlates to

reduction of HMMS

• PAT control:

• NTU measured on

manufacturing floor

• Results within 1 minute

• ~10 NTU correlates to < 0.2%

multimeric HMMS

• Two-fold reduction in dimeric

HMMS

• AEX step downstream

designed to provide additional

HMMS reduction

• If post-filtration NTUs >10, re-

filter


Ele

men

t

Description

Drug Substance Drug Product

Via

l T

haw

Sh

ake

Fla

sks

& C

ult

ure

Bag

s

See

d B

iore

acto

rs

Pro

du

ctio

n F

ed-B

atch

Bio

reac

tor

Har

ves

t

Pro

tein

A

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H

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ap

VR

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Fin

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Sto

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Tra

nsp

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Po

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Man

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Ste

rile

Fil

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Ste

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Ho

ld

Fil

l &

Sto

pp

er

Cap

Insp

ect

Sto

re


Control of Product QA None None


Related to Product QA a a a b b c


Control of PPA N/A


Related to PPA N/A

5 Drug Substance & Drug Product

Testing (Routine & Non-routine)d None QA Controlled with Acceptance Criteria

6 Stability Testingd None QA Controlled with Acceptance Criteria

7 Control of Raw Material Related to

QA or PPA None

8 Facility and Equipment Controls None

a Culture viability during inoculum train controlled to prevent sub-selection of cells which could lead to altered product quality. b Quality attribute controlled by process design of this unit operation with no specific PP or MA related to quality attribute. c In-process PAT control via turbidity testing of TMAE load. d Drug substance and drug product testing and stability monitoring only performed on the final material and not in-process.

QA: Quality Attribute; PP: Process Parameter; PPA: Process Performance Attribute; MA: Material Attribute; N/A: Not applicable

Areas that are in yellow indicate the controls in place.

Incorporating In-process PAT into Final Control Strategy

for HMMS can Enable Release Testing of DP only

Case Study 2: ‘Fit-for-purpose’ / Lifecycle

Approach to Control Strategy Implementation

• Background

– Typical monoclonal antibody

– Atypically high levels of high molecular mass species (HMMS) observed during early development

• HMMS Control Strategy – Early Clinical Phase

– ‘Force fit’ into mAb Platform process with significant yield loss and facility fit bottlenecks

• HMMS Control Strategy – Late Clinical Phase

– Increased titers; unexpected increase of HMMS at large scale

– Dramatic impact on process robustness, facility fit and overall yield/manufacturability

– Mechanistic investigation to understand the underlying cause of the HMMS issue

Early Stage Control Strategy for HMMS relies

on Low Yielding Platform Process

pH Inactivation

Harvest / Clarification

Centrifugation

Production Bioreactor

~ 1.6 g/L

11-24% HMMS

MabSelect Protein A

Chromatography

Planova 20 Viral Filtration

Viral clearance

≤ 200 L/m2

Ultrafiltration/Diafiltration

Final Concentration

AEX Weak Partitioning

≤ 60 mg/mL Loading

HMMS < 3%

Final Formulation

~100 mg/mL DS

HMMS < 3%

• Near platform process able to

remove high level of HMMS to

acceptable Phase I levels • 24% HMMS in harvest reduced to

< 3% in DS

• Acceptable process for Phase I

• Issues for Late Stage Process

• Low process recovery (~55%)

• Not suitable for commercial

manufacture due to low

productivity and lack of process

robustness

Late Stage Control Strategy: Reducing HMMS Level

at Harvest can Mitigate Downstream Bottlenecks

Theoretical process for high HMMS at harvest

Harvest/Clarification

MabSelect Protein A

AEX Chromatography

Polishing Column 2

~20-30% HMMS

10 cycles/batch

Theoretical HMMS 1 – 3%

Theoretical yield ~30 – 40%

Final Formulation

9 cycles/batch

Polishing steps:

Buffer volume: 3100 L/Kg

Processing time: 65 hr

Eliminate 2nd Polishing step

Theoretical process for low HMMS at harvest

Harvest/Clarification

MabSelect Protein A

AEX WP Chromatography

~2% HMMS

Theoretical HMMS <1%

Theoretical yield ~70 – 80%

Final Formulation

3 cycles/batch

Polishing step:

Buffer volume: 150 L/Kg

Processing time: 12 hr

Focus on Product Understanding: Reducing CGE

Showed Excess LC in the HMMS Enriched Sample

Sample Name % LC % HC %LC/%HC

Fully purified reference material 36.6% 63.4% 0.58

HMMS enriched sample 48.8% 51.2% 0.95

L Chain

L Chain H Chain

H Chain Fully purified reference material

HMMS enriched sample

Subunit analysis of HMMS Enriched Sample Revealed a

Significant Amount of LC with N-terminal Extension.

H Chain

AU

0.00

0.05

0.10

0.15

0.20

0.25

AU

0.00

0.05

0.10

0.15

Minutes

10.00 15.00 20.00 25.00 30.00 35.00 40.00

Fully purified reference material

HMMS enriched sample

L Chain

L Chain

H Chain

-19SVP…ARCcm-L Chain

-19Ac-SVP…ARCcm-L Chain

Full length signal peptide detected in ~50% of LC in HMMS enriched sample

Molecular design: Unexpected Involvement of a

Full Length Signal Peptide

• Based on historical experience, the finding of uncleaved full length

signal peptide 1 was unexpected.

• Could HMMS levels be lowered by using a different signal peptide?

Signal peptide 1 Framework 1

Framework 1

LC CDR1

LC CDR1 Signal peptide 1

-20

-20

1

1

24

24

34

34

mAb X

mAb Y

Expected

cleavage site

Identical aa sequence Identical aa sequence Different aa sequence

8 – 24% HMMS

~2% HMMS

Molecular Design: Clones with an Alternate Signal Peptide

Increased Expression by ~70% and Reduced HMMS to 2%

SEC-HPLC shows dramatically

reduced HMMS with alternate

signal peptide

Molecular and Process design results in an

efficient and elegant control strategy

• Robust process with consistent low levels of high molecular

weight aggregates

• Simpler process fit in manufacturing facilities; ‘greener process’


Process Initial Process

Final Commercial

Process

Buffer Usage (L/batch) 74000 6400

Buffer Usage (L/Kg product) 3100 150

Solvent usage (Ethanol) L/Kg

product 220 25

Conc. NaOH

(L/Kg product) 410 0

Disposable (filters/bags) waste

(Kg/Kg product) 14 1

Typical Current State mAb Release Spec

Future Directions: Continue to Develop and Implement

Technologies Enabling ‘Fit-for-Purpose’ Control Strategies

Can we get from here…….

Potential Future State mAb Release Spec

Key technology needs:

• Multi-attribute analytical release method

• Broad rapid bioburden technology

• Rapid adventitious viral test method

• Robust technologies BRX control

• In-line/at-line technologies

• Enhanced characterisation of inputs

To there…..?

mAb Enabling Trends & Opportunities – Online/At-Line - Multi-Attribute Testing, Statistical Models

34030627223820417013610268341

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.0

Process Progress

La

cta

te (

g/

L)

NOVA

Raman

Time Series Plot of Lactate

Conclusions

• A comprehensive lifecycle approach to Control Strategy relies on parallel development of product, process and analytical knowledge

• Investment in fundamental product and process understanding and PAT tools can result in efficient control strategies that are ‘fit-for purpose’

• Understanding the mechanisms underlying mAb aggregation can lead to design solutions to control CQAs (i.e. HMMS)

• A robust control strategy is determined by an understanding of the manufacturing process and material attributes of the components in the product and confirmed by the appropriate specification criteria and analytical methods

Acknowledgments

Tim Iskra

Lucy Liu

Keith Johnson

Mary Switzer

Alice Ferguson

Dave Cirelli

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