Enhancing Biotherapeutic Process and Product Knowledge with theMulti-Attribute Method (MAM)

USP Biologics Stakeholder Forum

San Francisco, January 10th, 2020

Andrew Dawdy1 on behalf of the Pfizer MAM Team1,2

Biotherapeutics Pharm. Sci., Pfizer Inc, 1St Louis, MO, USA and 2Andover, MA, USA

Outline

The benefit of MAM in Biotheraputic (BTx) Development

Development of MAM workflow for BTx Development

Implementation of MAM within Pfizer BTx Development

2

Product Quality Attributes (PQAs)

3

Quality Attribute

Efficacy(potency)

Safety /Immuno-genicity

Pharmaco-kinetics

(PK)

Criticality Assignment Matrix(CQA in red)

Severity (Harm to Patient)

Un

ce

rta

inty

(in

form

ati

on

qu

ali

ty)

10 7 5 1

10

6

4

2

Attribute understanding is clinically relevant and is foundational to a good control strategy for biotherapeutic development

ICH Q8R: CQA…should be within an appropriate limit, range or distribution to ensure the desired product quality

Analytical Testing Strategies in Biotherapeutic Development

• Release and Stability Testing

◦ Compendial Testing

◦ Content

◦ Product-related species

◦ Process-related species

◦ Potency and efficacy

• Characterization Testing

◦ Primary and Higher-Order structure

◦ Orthogonal assessments

Quality Attribute Method DS DP

Appearance Compendia √ √

Moisture, Particles, Osmolality, Reconstitution Time √

pH √ √

Protein Concentration UV √ √

Charge Isoforms iCE √ √

Heavy Chain + Light Chain CGE (reducing) √ √

Fragments CGE (reducing) √ √

Monomer CGE (nonreducing) √ √

High Molecular Mass Species HPLC SEC √ √

Peptide Profile / Identity Peptide Mapping √ √

Relative Potency Binding ELISA √ √

Glycan Fingerprint HPLC √

Endotoxin √ √

Bioburden (DS),Sterility (DP) √ √

Impurities (HCP, ProA, DNA) ELISA, qPCR √

Specification

Limits

Introduction of LC-MS-Based MAM is Revolutionizing Traditional Analytical Strategy

• Multi-Attribute Method by LC-MS

◦ The analysis of multiple product quality attributes simultaneously

◦ Automated monitoring, quantitation and detection of new peaks

• Key components of MAM

◦ Primary structure analysis, including sequence modifications

◦ Post-translational modifications

◦ Degradation mechanisms

Slide 6

MAM Consortium

• Purpose: Enable the BioPharma community to implement a robust mass spec based method for

biotherapeutic characterization and release of biotherapeutics from QC.

• Membership: >320 members from >70 companies spanning government agencies, biopharma,

mass spec vendors, software vendors, reagent vendors, and CDMOs.

◦ To join the MAM Consortium, email Rich Rogers richard.rogers@junotherapeutics.com or Da Ren dren@amgen.com.

• Highlights:

1. Consortium-wide NISTmAb study to evaluate similarity of MAM data between companies and

vendors (focusing on new peak detection). The round robin is led by Trina Mouchahoir.

2. Monthly meetings featuring presentations from Consortium members

3. Software sub-team planning developing of open-source MAM software

www.mamconsortium.org

Antibody Attribute Monitoring

CH 2

CH 2

CH 3

CH 3

OptimizedPeptide Mapping

nrCGE and rCGE

Glycan Profile(HILIC)

IEX (iCE, C/AEX)Peptide Mapping

IEX (iCE, C/AEX)Peptide Mapping

HC Met Oxidation

PENNY Deamidation

HC CDRDeamidation

HC CDRIsomerization

HC Met Oxidation

Glycosylation

Fragmentation

C-terminal Lysine

Peptide Mapping

Peptide Mapping

Peptide Mapping

Peptide Mapping

using Multi-Attribute Method (MAM)

MAM allows for additional

monitoring of:

Aglycosylation

Additional N-glycosylation sites

O-glycosylation

All Oxidation sites

Asp Isomerization

Much More…

IgG1

HILIC – hydrophilic interaction liquid chromatography, CGE – capillary gel electrophoresis, IEX – ion exchange, iCE – imaged capillary electrophoresis

Attribute Detection & Monitoring by MAM

8

5 10 15 20 25 30 35 40 45 50 55 60 65 70

Time (min)

0

20

40

60

80

100

N-glycosylationOxidationDeamidationTerminal HeterogeneityClips and Other Modifications

Light Chain Heavy Chain

MAM is a single liquid chromatography/ mass spectrometry (LC/MS)-based method that is used to analyze multiple PQAssimultaneously. It allows for automated monitoring and quantitation of known QAs and detection of new peaks.

Pfizer Platform MAM Workflow

9

Low-Artifact Digestion

(e.g. Trypsin)

High resolution, Accurate mass

LC-MS/MS(CID/HCD/ETD)

PTM / HotspotSearch

Generate site-specific

catalog of PQAs

LC/MS Only

New peak detection

Targeted quantitation of

PQA catalog End State: A routine MS-based assay to

monitor expected and unexpected attributes via

comparative sample analysis

SS

SS

SS

SS

SS

SS

SS

SS

SS

SS

SS

SS

SS

SS

C

S S

S S

NH2

NH2 NH2

NH2

COOH COOH

COOH COOH

C

Characterization

Routine Monitoring

Automatic ID and Quantitation of PQAs using:

1. Chromatographic retention time

2. HR/AM = high resolution (e.g. 140,000) /

accurate mass (<5 ppm)

3. Isotopes =12,13C; 14,15N; 16,18O; 32,33,34S

BioPharma Finder Software

Chromeleon Chromatography Data System Software Chromeleon Chromatography Data

System Software

Thermo Scientific™ Vanquish™ UHPLC System

Thermo Scientific™ Orbitrap Fusion™ Tribrid™ Mass Spectrometer

Implementation of MAM at Pfizer

2016 2017 2018 2019 5 – year plan

1. Formation of MAM Team

2. Initial Training on Sample

Prep and Software

Installation of harmonized “Lab-of-the-Future”

hardware at two cross-site analytical laboratories

QE+ QE+E+ E+Lab 1 Lab 2

0

5

10

15

20

25

Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM Met Ox MAM

T=0 T=3 T=6 T=9 T=12 T=18 T=0 T=3 T=6 T=9 T=12 T=18 T=0 T=3 T=6 T=9 T=12 T=18 T=0 T=3 T=6 T=9 T=12 T=18 T=0 T=3 T=6 T=9 T=12 T=18

Batch 1 Batch 2 Batch 3 Batch 4 Batch 5

% A

bu

nd

an

ce

Piloted MAM in active projects to support

process and product development

Optimization of MAM

workflow, including:

1. sample preparation

2. LC and MS hardware

3. automated software

analysis

4. new peak detection

1. Establish MAM as the Pfizer

standard for attribute

monitoring in process and

product development

2. Continue efforts to automate

all aspects of MAM

3. Complete compliance and

risk assessments for QC

1

1.2

1.4

1.6

1.8

2

2.2

INJ 1 INJ 2 INJ 3 INJ 4 INJ 5

% A

bu

nd

an

ce

Optimization of Sample Preparation

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

mAb 1 mAb 2 mAb 3 mAb 4 mAb 5 mAb 6

IgG1 IgG2 IgG4

% A

bu

nd

an

ce

Reduction of Missed Cleavages Reduction of Method Artifacts:Reduction in % Oxidation

Improved Autosampler Stability:Reduction in % Deamidation

Original MethodOptimized Method

• Improved digestion efficiency by optimizing multiple parameters

• Lowered artifactual oxidation through addition of Met to digestion buffers

• Improved autosampler stability by adjustment of final sample conditions

11

Original MethodOptimized Method

2

2.5

3

3.5

4

No scavenger +EDTA Optimized (+Met)

% A

bu

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an

ce

Time, Temperature, Cleanup, Concentration

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

2-A

B H

ILIC

Co

nd

1

Co

nd

2

Co

nd

3

Co

nd

4

Co

nd

5

Co

nd

6

Co

nd

7

Co

nd

8

G0F minus GlcNAc: Released N-Glycan Assay vs MAM

Includes Artifact

Excludes Artifact

Mitigated in-source loss of labile species (e.g. GlcNAc) by optimizing ESI source parameters

Source Optimization Experiments

S-Lens RF

Capillary Temperature

Auxilary Gas Temperature

ESI Source

Three ESI source parameters were varied

Optimization of Source Conditions to Mitigate In-Source Fragmentation

G0F

G0F -GlcNAc

In-Source Artifact

Real

Platform

In-Source Artifact

Real

G0F

G0F -GlcNAc

Optimized

MAM Software Workflow: PQA Library Creation to Routine PQA Monitoring

PQAsTransferred Processing Method

and Report Created

PQA Library

0

5

10

15 Monitoring Oxidation in Chromeleon

0 Week3 Week

6 Week 9 Week12 Week

18 Week

%

4. Saved components to BPF

Target Peptide WorkbookBatch 2

Stress

Batch 2

Control

Batch 1

Stress

Batch 1

Control

1. Modification Table

Generated

2. Oxidation

hotspot detected

3. Data

Reviewed

Characterization (MS/MS)

1. Chromatographic retention time

2. Accurate mass (<5 ppm)

3. Isotopes =12,13C; 14,15N; 16,18O; 32,33,34S

Monitoring (MS Only)0.2%

1.2%

Non-Targeted New Peak Detection

Ensuring MAM Quality with System Suitability

System Suitability

Attribute Monitoring

Correct Isotopic distributionCorrect mass within 5 ppm

Instrument performance measured using Pierce Retention Time Mix• Accurate Mass• Peak Area• Retention Time

Results - % Attribute Abundance

Ensuring MAM Quality with Assay Acceptance

Assay Acceptance Criteria

• Similar to Reference (GDMS)Profile

• Total SignalTIC

• % Abundance within range% Missed Cleavage

• % Abundance within range% Alkylation

• % Abundance within rangeModification #1

• % Abundance within rangeModification #2

• % Abundance within rangeModification #3

• % Abundance within rangeModification #4

• % Abundance within rangeModification #5

PASS

Tracking Meta Data to Facilitate Troubleshooting of Abberant Results

Meta Data Sequence Table

0

10

20

30

40

50

0 10 20 30 40 50

% O

xid

atio

n Column A

Column B

Column C

Column D

Harmonized Labs Produce Precise Quantitation over Months of Collection

0

2

4

6

Asn Deamidation Asn Succinimide Met Ox Trp Ox C-Term Pro-NH2 C-Term Lys

% A

bu

nd

an

ce

0

10

20

30

40

50

60

70

80

90

100

G0F

% A

bu

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an

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0

1

2

3

4

5

6

7

G1F G0 Man8 G0F minus GlcNAc Man5

% A

bu

nd

an

ce

Lab 1Lab 2

• Many PQAs were measured with precision over time using a mAb standard• Data provides a basis for establishment of system suitability and assay acceptance criteria

CV 7.7%

CV 9.5%

CV 4.4%

CV 18.2%

CV 3.7%

CV 14.1%

CV 0.9% CV 6.8%

CV 6.9%

CV 8.8% CV 12.8% CV 5.7%

Lab 1Lab 2

• iCE provides global charge variant information, but no specific information on identification or location of attributes

Drug Substance Batches Subjected to 40° C Stress for 18 Weeks

0

10

20

30

40

50

60

70

0 w

k

3 w

k

6 w

k

9 w

k

12 w

k

18 w

k

0 w

k

3 w

k

6 w

k

9 w

k

12 w

k

18 w

k

Process 1 Process 2%

Ab

un

da

nc

e

Acidic Species by iCE

Basic

Main0 wk

18 wk

iCE ProfileExamples of

Charge VariantsAsn deamidation

Sialylated N-GlycansN-terminal pyro Glu

C-terminal LysC-terminal amidated Pro

Lys glycation

Charge Variants: Global to Local

Acidic

Drug Substance Batches Subjected to 40° C Stress for 18 WeeksAcidic Species by MAM

0

5

10

15

20

25

30

35

40

0 w

k

3 w

k

6 w

k

9 w

k

12 w

k

18 w

k

0 w

k

3 w

k

6 w

k

9 w

k

12 w

k

18 w

k

Process 1 Process 2%

Ab

un

da

nc

e

• Increase in acidic species by iCE trends with increase observed by MAM• MAM provides ID and site-specificity for each acidic PQA

Asn 2XXG2F + NeuAc

Asn 3XXDeamidation

Acidic Basic

Main0 wk

18 wk

iCE ProfileExamples of

Charge VariantsAsn deamidation

Sialylated N-GlycansN-terminal pyro Glu

C-terminal LysC-terminal amidated Pro

Lys glycation

Asn 2XXG2F + NeuAc

Asn 3XXDeamidation

Charge Variants: Global to Local

• Traditional methionine oxidation assay (LC-UV) targets one specific site in the Fc-region• MAM quantitates multiple sites and types of oxidation in a single assay (LC-MS)

Drug Substance Batches Subjectedto 40° C Stress for 18 Weeks

0

5

10

15

20

25

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

Me

t O

x

MA

M

T=0 T=3 T=6 T=9 T=12 T=18 T=0 T=3 T=6 T=9 T=12 T=18

Process 1 Process 2

% A

bu

nd

an

ce

Fc Met 1 Fc Met 2 Fc Met 3 CDR Trp

Fc Met Ox 1

Fc Met Ox 2

Fc Met Ox 3

CDR Trp

Met and Trp Oxidation: Traditional vs. MAM

MAM reveals that drug substance in Formulation 1 is at much higher risk for Lys glycation

MAM Identifies Effect of Formulation on Non-Enzymatic Lys Glycation

0

2

4

6

8

10

12

0wk 3wk 6wk 9wk 12wk 18wk 0wk 3wk 6wk 9wk 12wk 18wk

Formulation 1 Formulation 2

% A

bu

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ce

Contains Sucrose

Contains Trehalose

Site-specific Levels of Lys Glycation Observed on Drug Substance in Two Formulations Subjected to Thermal Stress (40° C)

Lys Glycation

Glycation

Glycation

Glycation

Glycation

0

10

20

30

40

50

60

G0F G1F G2F

% A

bu

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N-Glycoform quantitation by MAM vs 2-AB-labeled N-glycan assays

N-glycoform quantitation by MAM matches 2-AB-labeled N-glycan assays for major and minor glycoforms…

3 bioreactor samples run by:Traditional Assay (2-AB) and MAM

0

1

2

3

G0 minus GlcNAc G0F minusGlcNAc

G0 G1 M5 G2F + NeuAc G2F + 2 NeuAc

% A

bu

nd

an

ce

…and for trace-level glycoforms

12

3

12

3

min

counts

31.695 31.750 31.800 31.850 31.900 31.950 32.000 32.050 32.100 32.150 32.200 32.250 32.300 32.350 32.400 32.423

Retention Time

-5.0e5

-2.5e5

0.0e0

2.5e5

5.0e5

7.5e5

1.0e6

1.3e6

1.5e6

1.8e6

2.0e6

2.3e6

2.5e6

2.8e6

3.0e6

3.3e6

3.5e6

3.8e6

4.0e6

4.3e6

4.5e6

Inte

nsity

Detecting and Monitoring New Clips by MAM

1. Non-targeted analysis detects unidentified peak increasing upon thermal stress

2. Peak identified as a D/P clip within Fc region

0

1

2

3

4

0 6 12

Time (Weeks)

% A

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1

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3

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0 6 12

Time (Weeks)

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3

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0 6 12

Time (Weeks)%

Ab

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1

2

3

4

0 6 12

Time (Weeks)

% A

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rCGEMAM

rCGEMAM

rCGEMAM

rCGEMAM

Batch 1 Batch 2

Batch 3 Batch 4

Non-Targeted Peak Detection

5xIncrease

3. D/P clip monitoring by MAM correlates well with clipping data from traditional rCGE assay.

18 wk at 40C

0 wk at 40C

4 DS Batches Subjected to Thermal Stress (40° C)

Future Steps: Sample Prep Automation

Automation results are highly comparable to

the manual approach of sample preparation

Pfizer Confidential | 24

Hamilton Microlab STAR

IMCS SizeX 100 Tips

0 2 4 6 8 10 12

Cumulative Days for One Sample

Future Steps: Replacement of Traditional Assays

MAM has the capability to gather attribute information 5X faster than

running the traditional repertoire of assays

Pfizer Confidential | 25

MAM

Traditional

Assays

Time estimate includes sample receipt,

preparation, incubation times, instrument

setup, instrument analysis, data collection,

interpretation and archival

• Pfizer has created a functional MAM platform and the resulting data are agreeing well with the results from traditional assays

• MAM provides great benefit for biotherapeutic development by enhancing analytical process and product knowledge and efficiencies from early- through late-stage

• Upon analysis of a sufficient aggretate of side-by-side data, Pfizer plans to further increase analytical efficiencies by replacing select traditional assays with MAM

• Pfizer is moving forward with compliance and risk assessments in order to enable implementation of MAM into QC laboratories within the next 5 years

Conclusions

Acknowledgements

Rich Rogers

Artem Akhmetov

Haichuan Liu

Jennifer Sutton

John Butler

Lena Arthur

Kimy Young

Martin Hornshaw

Tom Buchanan

Royston Quintyn

Rich Klein

Ken Cook

Krisztina Radi

John Rontree

Iain Mylchreest

Betty Woo

Dave Jarzinski

Jonathan Josephs

Michael Blank

Jason Rouse (Sponsor)

Carly Daniels (STL Lead)

Keith Johnson (AND Lead)

Amy Schmidt

Anastasiya Manuilov

Andrew Dawdy

Dave Ripley

Don Stano

Gaby Ibarra-Barrera

Halyna Narepekha

Himakshi Patel

Justin Sperry

Jason Starkey

Josh Woods

Keith Davis

Keith Lutke

Kristin Boggio

Matt Thompson

Natalia Kozlova

Nataliya

Parahuz

Olga Friese

Phoebe Baldus

Sean Shen

Shibu Philip

Simon Letarte

Tiffany Medwid

Thomas Powers

Vijay Kanthan

Wenqin Ni

Ying Zhang

Meg Ruesch

Andrew Rugaiganisa

Brad Evans

Jia Liu

Rachael Utegg

Sonia Taktak

MAM Team