Download Host cell protein analysis by mass spectrometry and its application

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
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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The cell
Source: Animal cell. Wikimedia Commons, author: Mediran.
Host Cell Proteins (HCP)
including modifications
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HCP immuno assay development
Standard approach
Cell line without
product-coding
gene
Immunization
Bioprocess
Purification and
qualification of
polyclonal
antibody sera
Isolation
Purification
steps
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Immunoassay
development
Choose suitable
step to take HCP
preparation
ELISA and
related assay
formats
LC-MS in HCP analysis

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
LTQ OrbitrapTM
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Q-ExactiveTM
Analysis of proteins in complex mixtures
Database search concept
Protein
Protein Digestion
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HCP LCMS identification workflow
Process sample
Sample
Drug substance
Capture eluate
(Protein A purified)
Protein digestion (e.g. Trypsin)
LC-MS/MS
Database search of
MS/MS spectra
+
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
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V. Reisinger, H. Toll, R.E. Mayer, J. Visser, F. Wolschin, Analytical Biochemistry 463 (2014) 1-6.
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
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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
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)
X ... Identified by automatic analysis
(X) ... Identified by manual analysis
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V. Reisinger, H. Toll, R.E. Mayer, J. Visser, F. Wolschin, Analytical Biochemistry 463 (2014) 1-6.
11
Arbitrary units
Arbitrary units
Exemplary HCP quantification results
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Batches before filter change
Batches after filter change
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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Manual versus automated quantitative analysis
Standard protein spicked into DS
25000000
Manual
y = 51790x - 210171
R² = 0.982
7000000
y = 61110x - 687950
R² = 0.9775
6000000
Arbitrary units
20000000
5000000
15000000
4000000
3000000
10000000
2000000
5000000
1000000
0
0
0
100
200
300
400
500
-1000000
[ng/mg]
0
20
y = 7110.9x + 50667
R² = 0.9695
Arbitrary units
3500000
3000000
2500000
2000000
1500000
1000000
500000
0
-100
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0
100
200
300
400
60
80
100
120
[ng/mg]
Automated
4000000
40
500
[ng/mg]
Poor correlation of ELISA and quantitative MS
Exemplary graphs
0.80
Pearson
0.70
Spearman
HCP #13
0.60
0.50
0.40
0.30
0.20
MS
Correlation value ELISA/MS
0.90
0.10
HCP #2
0.00
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17
HCPs
 Possible reasons
• Narrow HCP distribution in process samples
• Method variability
• Complementary HCP recognition
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ELISA
Physicochemical HCP properties
Proof of principle samples
Attribute Median CapE HCPs (n=48)
pI
Median DS HCPs (n=8)
p-value
5.59
5.49
0.9862
mw [Da]
50651.88
20297.51
0.0662
GRAVY
-0.25
-0.37
0.2079
Samples before filter change
Attribute
pI
Median CapE HCPs (n=33)
5.55
mw [Da]
41991.88
11239.58
0.0009
GRAVY
-0.25
-0.25
0.6564
Attribute
pI
Median DS HCPs (n=7)
p-value
5.49
0.9931
Samples after filter change
Median CapE HCPs (n=24) Median DS HCPs (n=3)
p-value
5.49
5.23
0.9891
mw [Da]
41867.28
11239.58
0.0304
GRAVY
-0.34
-0.33
0.5227
16 | 26 Jan 2015
V. Reisinger, H. Toll, R.E. Mayer, J. Visser, F. Wolschin, Analytical Biochemistry 463 (2014) 1-6.
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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HCP content
HCP content
HCP content
HCP content
Biosimilar exercise: HCP-ELISAs are not suitable
to compare different manufacturing processes
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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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