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

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%)

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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Expiry Date

Tota

l lo

ts

w/o

Dri

ft lo

ts

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

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%)

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