Quality-focused Development Strategy of Biosimilar Product · • Monitor throughout the entire...
Transcript of Quality-focused Development Strategy of Biosimilar Product · • Monitor throughout the entire...
Quality-focused Development Strategy of Biosimilar Product
Kyungah Kim
Samsung Bioepis Co., Ltd.
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PART I Quality-focused Analytical Assessment
PART II Heterogeneity of Biologic Product
PART III Similarity Assessment
PART IV Closing Remarks
Outline
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PART I
Quality-focused Analytical Assessment
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Quality Based Biosimilar Development Strategy
US Health and Human Services, Food and Drug Administration. Guidance for industry, clinical pharmacology data to support a demonstration of biosimilarity to a reference product. Rockville (MD): FDA; 2016 Dec.
Science-based quality evaluations maximize clinical biosimilarity.
Stepwise assessment begins with extensive structural and functional characterization of the reference product and the biosimilar.
Thorough
Focus on Quality
to Ensure
Clinical Biosimilarity Clinical
Studies
Non-clinical
Biological Characterization
Physicochemical Characterization
Totality of Evidence
“Abbreviated” Development Program. 351(k) BLA
Analytical Similarity
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Characterization as the Foundation
Comparing products using a analysis algorithm that covers a large number of product quality attributes with highly sensitive, orthogonal methods ensures similarity of clinical outcome
Microbial enumeration
Endotoxin Virus
Sterility
HCP
HCD
PrA leachate
Antifoam
Insulin Peptide mapping
Reduced intact Mass
Amino acid analysis
N-term sequencing
C-term sequencing
Extractable volume
Particulate matter
Protein concentration
pH
% Gal by UPLC
NANA/NGNA (HPLC)
FcRn binding
TNF-α binding
Acidic isoforms by icIEF
Basic isoforms by icIEF Inactive form by HI-HPLC
HCP
Extractable volume
Particulate matter
Protein concentration
N-linked Glycan
LMW by CE-SDS
pH
CDC
O-glycan occupancy by LC-MS ADCC
% Gal by UPLC
Afucosylation
NANA/NGNA (HPLC)
HIC Fragments
Inactive form by HI-HPLC
Peptide mapping
Reduced intact Mass
Amino acid analysis
N-term sequencing
C-term sequencing
Particulate matter
N-linked Glycan
AUC
MFI HMW
LMW by CE-SDS
FTIR
DSC
CD
Disulfide bond
pH
Quality Attributes
Safety
PK
Immuno- genicity
Efficacy
Safety
PK
Efficacy
Clinical Effects
Immuno- genicity
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Importance of Analytical Method Sensitivity
Adapted from a presentation by Anthony Mire-Sluis, 9th Symposium on the Practical applications of Mass Spectrometry in the Biotechnology Industry (mass Spec 2012); 11-14 September,2012, San Diego, CA,
USA.
Sensitivity of analytical method is important for similarity assessment
Mass spectrometry example
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PART II
Heterogeneity of Biologic Product
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Monoclonal Antibodies as the Biosimilar
Higel F et al. European Journal of Pharmaceutics and Biopharmaceutics 100 (2016) 94–100
Monoclonal antibodies are complex molecules.
− Post-translational modifications
Mode of action is complex and may involve contributions from multiple mechanisms.
− Need to consider the correlation of functional activities with physicochemical results or with the results for preclinical and clinical studies
FcR binding → ADCC
C1q binding → CDC
FcRn binding → Half-life
Analytical characteristics
Fab
Fc
Antigen binding
Specificity
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Heterogeneity for Quality Attribute in Biologics
Schiestl M, et al. Acceptable changes in quality attributes of glycosylated biopharmaceuticals, Nature Biotechnology (2011) 29:310-312
Reference etanercept
• Two distinct glycosylation profiles in some of later batches (after 2009)
Reference rituximab • Higher unfucosylated glycans (G0) and ADCC in some of later batches (after 2010)
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Heterogeneity for Quality Attribute in Biologics
Kim S, et al. Drifts in ADCC-related quality attributes of Herceptin : Impact on development of a trastuzumab biosimilar, mAbs (2017) 9(4):704-714
Reference trastuzumab
• ADCC activity showed 2 marked drifts.
− 1st drift: A marked downward drift in %afucose
− 2nd drift: An upward drift in %high mannose
Pre-drift period (Mean ± 3SD) 1st drift period
(Mean ± 3SD)
2nd drift period (Mean ± 3SD)
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2015 2016 2017 2018 2019 2020
Rela
tive A
DC
C A
cti
vit
y (
%)
Expiry Date
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Heterogeneity Risk Mitigation
1 Gonçalves J, et al. Clin Exp Rheumatol 2016;34(4):698-705
Sample As Many As Possible, As Long As Possible
Define a Quality Target Range for the Biosimilarity Assessment
• Characterize multiple lots of reference (Innovator) product
• Monitor throughout the entire biosimilar development period
Biosimilar mAb has to take in consideration of the largest historical data of reference mAb batches to derive a quality range1
Originator mAbs Originator post manufacturing change Biosimilar
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PART III
Similarity Assessment
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Tollgate System for Similarity Assessment
Tollgate system ensures high quality biosimilar development.
Establish stringent quality goals for a go/no go decision at key development steps
Similarity Assessment
Lab Scale Pilot Scale Mass-Production Scale
(Material for Clinical Trial and Commercial Production)
Cell Line Selection
Tollgate 1 Tollgate 2 Tollgate 3 Tollgate 4
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Tiering of Quality Attributes
.1 Data on file; Samsung Bioepis Co., Ltd
Each similarity assessment was designated to a tier based on the clinical relevance of the attribute.
Tier 1
Tier 2
Tier 3
Analytical Similarity Assessments by Risk-based Assessment
(Case of SB3, a Herceptin® Biosimilar Candidate)
Inhibition of cell proliferation
Antibody-dependent cellular cytotoxicity (ADCC)
HER2 binding
FcγRIIIa binding
FcRn binding
C1q binding
Purity
Glycosylation
Charge variant
Fc Receptor binding
In vitro angiogenesis
Surface HER2 level
HER2 ECD shedding
Akt phosphorylation
Combination with chemotherapy
Antibody-dependent cellular phagocytosis (ADCP)
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Similarity Range Set-up: Case study
Data on file
Quality Target Range was defined for the biosimilarity assessment
− Reference product has been monitored throughout the entire biosimilar development period.
− 146 lots of reference trastuzumab were analyzed for setting the similarity range.
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2015 2016 2017 2018 2019 2020
Rela
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DC
C A
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vit
y (
%)
Expiry Date
Tota
l lo
ts
w/o
Dri
ft lo
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Reference Trastuzumab Target Range
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Quality Management of SB3
Data on file
ADCC activity of SB3 showed high consistency.
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Re
lati
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AD
CC
Ac
tivit
y (
%)
PPQ batches
Clinical batches
Reference trastuzumab Min-Max range
• PPQ: Process Performance Qualification
SB3 Min-Max range
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Clinical Efficacy of SB3
a Pivot X, et al. J Clin Oncol 2018 :JCO2017740126 [Epub ahead of print]
b Data on file
pCR in breast at primary endpoint was not inferior to reference trastuzumab.
− Slightly above the upper end of pre-defined equivalence margin
− Consider for shift of ADCC activity for some reference trastuzumab batches used for clinical trial
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Ontruzant® Herceptin®
pC
R (
%)
Adjusted difference 10.70% (95% CI, 4.13, 17.26)
Adjusted ratio 1.259 (90% CI, 1.112, 1.426)
pCR in Breast
Δ+10.70 51.7%
42.0%
Reference
Trastuzumab SB3
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PART IV
Closing Remarks
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Striving to develop methods that can determine analytical similarity is an important step in biosimilar characterization.
Biologics have inherent structural complexity and modifications.
Quality control is critical for identifying changes in the reference product quality profile that can impact development.
Monitoring similarity against the quality target range throughout the product lifecycle ensures a continuous focus on quality throughout biosimilar development.
Tight quality management of biosimilar product ensures biosimilarity to the originator product.
Summary