Host cell protein analysis by mass spectrometry and its application in a comparability exercise

Florian Wolschin, Martin Schiestl

CMC Strategy Forum, Washington, 26. Jan 2015

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Topics

Introduction

Use of mass spectrometry in HCP analysis

Application in a comparability exercise

Role of mass spectrometry versus ELISA in HCP analysis

• Comparability following a manufacturing change

• Biosimilar exercise

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Host Cell Proteins (HCP)

including modifications

Source: Animal cell. Wikimedia Commons, author: Mediran.

The cell

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HCP immuno assay development Standard approach

Cell line without

product-coding

gene

Bioprocess

Isolation

Choose suitable

step to take HCP

preparation

Purification

steps

Immunization

Purification and

qualification of

polyclonal

antibody sera

Immunoassay

development

ELISA and

related assay

formats

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LC-MS in HCP analysis

LTQ OrbitrapTM Q-ExactiveTM

Mass spectrometry allows the identification of low abundant

proteins in complex mixtures

• Increasing use of LC-MS techniques in HCP analysis

• Ongoing progress in increasing sensitivity and mass accuracy

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Analysis of proteins in complex mixtures Database search concept

Protein

Protein Digestion

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HCP LCMS identification workflow

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Sample

Protein digestion (e.g. Trypsin)

LC-MS/MS

Database search of

MS/MS spectra

Process sample

Capture eluate

(Protein A purified)

Drug substance

Exclusion list

Derived from API peptides

Inclusion list

Derived from HCPs

identified in capture eluate

Library of potential HCPs

In drug substance

+ +

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Effect of using exclusion and inclusion lists

Increase of detectability

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How reliable are the identifications? MS/MS spectra verification with synthetic peptides

V. Reisinger, H. Toll, R.E. Mayer, J. Visser, F. Wolschin, Analytical Biochemistry 463 (2014) 1-6.

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HCP analysis in a comparability exercise

Case: Exchange of the depth filter in the manufacturing process

ELISA results showed comparable levels of HCP in the drug substance batches before and after the filter change

LC-MS/MS using inclusion and exclusion lists

• Pre- and post change batches were analyzed for HCPs using automatic identification

• In addition, all HCPs automatically identified in one of the two sample sets were manually checked for their presence in the other

10 V. Reisinger, H. Toll, R.E. Mayer, J. Visser, F. Wolschin, Analytical Biochemistry 463 (2014) 1-6.

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HCP analysis in a comparability exercise

X ... Identified by automatic analysis

(X) ... Identified by manual analysis

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Protein Identified before

filter change

Identified after

filter change

Protein S100-A10 X X

Protein S100-A4 X X

Protein S100-A11 X (X)

Protein S100-A6 X (X)

Anionic trypsin-2 X (X)

Thioredoxin X X

Galectin-1 X (X)

V. Reisinger, H. Toll, R.E. Mayer, J. Visser, F. Wolschin, Analytical Biochemistry 463 (2014) 1-6.

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Exemplary HCP quantification results

Batches before filter change

Batches after filter change

Arb

itra

ry u

nit

s

Arb

itra

ry u

nit

s

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Quantification workflow

LC-MS/MS with accurate mass

(Q-Exactive)

Semi-automated data evaluation for identification

and quantification. De novo sequencing possible.

Manual verification of identification and integration

Quantification of peptides using targeted MS/MS

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y = 51790x - 210171R² = 0.982

0

5000000

10000000

15000000

20000000

25000000

0 100 200 300 400 500

Manual versus automated quantitative analysis Standard protein spicked into DS

Manual

Arb

itra

ry u

nit

s

y = 7110.9x + 50667R² = 0.9695

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

-100 0 100 200 300 400 500

Automated

Arb

itra

ry u

nit

s

y = 61110x - 687950 R² = 0.9775

-1000000

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

0 20 40 60 80 100 120

[ng/mg] [ng/mg]

[ng/mg]

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Poor correlation of ELISA and quantitative MS

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Co

rrela

tio

n v

alu

e E

LIS

A/M

S

HCPs

Pearson

Spearman

MS

ELISA

Exemplary graphs

HCP #13

HCP #2

Possible reasons

• Narrow HCP distribution in process samples

• Method variability

• Complementary HCP recognition

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Physicochemical HCP properties

Attribute Median CapE HCPs (n=48) Median DS HCPs (n=8) p-value

pI 5.59 5.49 0.9862

mw [Da] 50651.88 20297.51 0.0662

GRAVY -0.25 -0.37 0.2079

Attribute Median CapE HCPs (n=33) Median DS HCPs (n=7) p-value

pI 5.55 5.49 0.9931

mw [Da] 41991.88 11239.58 0.0009

GRAVY -0.25 -0.25 0.6564

Attribute Median CapE HCPs (n=24) Median DS HCPs (n=3) p-value

pI 5.49 5.23 0.9891

mw [Da] 41867.28 11239.58 0.0304

GRAVY -0.34 -0.33 0.5227

Samples after filter change

Proof of principle samples

Samples before filter change

V. Reisinger, H. Toll, R.E. Mayer, J. Visser, F. Wolschin, Analytical Biochemistry 463 (2014) 1-6.

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Role of MS versus ELISA

ELISA is the assay of choice for routine analysis

• Precise and sensitive assay format

• Provides relative but no absolute quantitative results

• Due to HCP-specific immunogenicity some HCPs may react stronger than others

• Despite some limitations, history demonstrated the appropriateness of HCP control by well developed ELISAs

MS complements ELISA

• Identification and quantification of single HCPs

• Capture more abundant HCPs in process samples and drug substance

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Role of MS versus ELISA

Comparability exercises following manufacturing process changes

• ELISA is the routine tool to compare HCP clearance before and after the change

• MS provides characterization data for the more abundant HCPs

– Useful addition for risk mitigation or trouble shooting

Biosimilar exercises

• HCP is a process related feature

• A biosimilar company needs to justify adequate low levels of HCPs for their own process

– Different processes may result in different HCPs

– Therefore, a direct comparison with the reference product is normally not useful

• HCP-ELISA needs to be qualified for a specific process and is not suitable to compare HCPs load of products resulting from differently developed manufacturing processes

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Biosimilar exercise: HCP-ELISAs are not suitable to compare different manufacturing processes

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HC

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Summary

Mass spectrometry is a useful tool for HCP analysis

MS-based label free methods are capable of identifying and quantifying individual proteins down to single digit ppm (ng/mg)

Exclusion and inclusion lists can enhance the sensitivity of HCP detection

• Be aware of potential bias when using inclusion lists

Mass spectrometry provides complementary results to ELISA

• Identification and quantitation of (more abundant) HCP proteins

– May compensate limitations of ELISA

• Useful in evaluating manufacturing process changes

Biosimilar exercise

• As a process related feature, HCP comparison is normally not useful

• HCP-ELISA needs to be qualified for a specific process and is not suitable to compare products from differently developed processes

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