1September2015,Le MeridienDubai ,UnitedArabEmirates Sundar...

GaBI Educational Workshops 1 September 2015, Le Meridien Dubai, United Arab Emirates

•  Director, Global R & D and Regulatory Policy, Amgen Inc, USA

Sundar Ramanan, PhD, USA

GaBI Educational Workshops 1 September 2015, Le Meridien Dubai, United Arab Emirates

Biologicals and biosimilars – the complexity of structure and funcBon

Sundar Ramanan, PhD 1 September 2015

The Role of Analytical and Structure–Function Studies in the Assessment of Biosimilarity

Sundar Ramanan, Ph.D.

Director, Policy - R&D and Regulatory Affairs

Amgen Inc.

GaBI ME SBP Workshop, September 1, 2015, Dubai, UAE

Discussion Topics

• Overview of biosimilar development

• Elements and limitations of analytical studies

• Role of structure-function studies


3

Discussion Topics




4 The Role of Analytical and Structure–Function Studies in the Assessment of Biosimilarity

Approval is Based on the “Totality of Evidence”1

1. Foundation- Structural and functional comparisons

2. Non clinical in vitro and in

vivo testing

Biosimilar

1. Quality

Cross reference

2. Non-Clinical

3. Clinical

Cross reference

Cross reference – Prior findings of safety and

efficacy

Integrated Biosimilarity Exercise – Quality, Safety and Efficacy

Originator BLA

Biosimilar?

Biosimilar?

Biosimilar?

Biosimilar development proceeds through a stepwise similarity exercise

3. Clinical

Food and Drug Administration. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM291128.pdf. Accessed 24 January 2013.


5

1. Foundation- Structural and functional comparisons

2. Non clinical in vitro and in

vivo testing Biosimilar?

Process design and analytical studies form the foundation of biosimilar development

3. Clinical

Before non-clinical and clinical testing can proceed: • Define the target quality profile

• Design the process

• Compare structural and functional attributes

• Use state-of-the-art analytical characterization and functional assays to assess any structural difference

• Understand the importance and limitation of functional assays


6

Carbohydrates & other post-translational modifications

Chemical modifications &

PEGylation

Synthesis and Folding

(a) Primary structure

(b)Secondary structure

β Pleated sheet

(c)Tertiary structure

(d) Quaternary structure

α Helix

Sugar side chains (can affect safety and efficacy)

Chemical modifications (can affect purity, safety, or potency)

[Image Source: Tim Osslund; Amgen Usage Rights: Unlimited world-wide usage rights for an unlimited time; http://kvhs.nbed.nb.ca/gallant/biology/protein_structure.html. Data source: USP-NF 1045. Biotechnology-derived articles: 3-20]

Biologics may have 4 orders of structure plus modifications that affect in vivo characteristics


http://kvhs.nbed.nb.ca/gallant/biology/protein_structure.html

Biological products have very complex structures

Monoclonal antibody

Glycan modifications • G0, G1, G2 • Core fucosylation • High mannose • etc

Peptide modifications • Deamidation • Succinimide • Oxidation • N & C-terminal variants • Amino acid substitution • Disulfide isoforms Folding/Size • Truncation • Half molecules • Dimer • Multimers • Aggregates • Particles


Figure adapted from D. Kelner (Amgen), “Comparability and Biosimilarity: Two Sides of the Same (or a Different) Coin?” presented at IBC Analytical Technologies,San Diego, CA (March 2012)

Typical analytical similarity assessment evaluates 90 to 100 unique attributes

Results from a wide breadth of assay combinations compares the analytical “footprint” of the biosimilar to the reference product.

Is it possible to “match” all attributes?


Figure adapted from J. Liu et al. (Amgen), “Analytical Similarity Assessment of Biosimilars” presented at the Spring ACS Meeting, Dallas, TX (March 2014)

QbD for biosimilars • Assess criticality based on

literature & experience

• Characterize reference product quality attributes

• Design biosimilar to minimize differences for high criticality attributes

• Assess potential clinical relevance of remaining differences

Biosimilar development can use a Quality-by-Design (QbD) approach

Product Quality Attributes

Criticality Assessment

Safety and Efficacy Data

High Criticality Attributes

Low Criticality Attributes

Product Understanding

Clinical Studies

Animal Studies

In-Vitro Studies

Prior Knowledge

Focus on the most important

attributes

Lower criticality attributes are

not “forgotten”


Figure adapted from G. Grampp (Amgen), “Challenges of Structure-Function Studies for Assessing Similarity”

presented at the Spring ACS Meeting, New Orleans, LA (April 2013)

Discussion Topics





Analytical studies should assess several aspects of structure

• Primary structure (sequence and linkages)

• Higher order structures (folding, aggregates)

• Covalent modifications (glycosylation and chemical modifications)

• Impurities (product and process)

• Stability profile


AU

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Minutes 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00 110.00 120.00 130.00 140.00 150.00 160.00 170.00 180.00

Biosimilar product should have identical amino acid sequence to the innovator

Peptide mapping

• 100% sequence confirmation

• Search for any low level amino acid substitution (sequence variant) due to translational errors, misincorporation, or mutation

• Post-translational modifications, such as glycosylation, acetylation, sulfation, phosphorylation, glycation, etc


Figure adapted from J. Liu (Amgen), “Analytical Testing and Characterization of Biosimilars” presented at the Health Canada SEB/Biosimilar Scientific Forum, Ottawa, Canada (November 2013)

Amgen unpublished data

Mass spectroscopy combined with separation based methods can address many uncertainties

Primary structure and covalent modifications can be assessed to high fidelity

Image obtained from University of Kentucky Mass Spectrometry Facility http://www.research.uky.edu/ukmsf/example2a.html

• Amino acid sequences confirmed to ~100% coverage

• Covalent modifications, sequence variants and glycan structures detected to <1% resolution

Example: LC ESI MS/MS


Figure adapted from G. Grampp (Amgen), “Analytical Similarity Assessments”

presented at the DIA/FDA Biosimilars Conference, Washington DC (September 2012)

Examples of some remaining challenges

• Accurate quantitation of minor species

• Identifying and quantifying disulfide bonding patterns

• Accounting for combinatorial effects

Advanced mass spectroscopy methods still leave some uncertainties

Correctly folded Disulfide misfolds 1 and 2

Std (15N)Sample (14N)

Std+Sample

Proteolysis

Mix

m/z

Stable Isotope Labeled Internal Standard (SILIS)

Figures courtesy of Jiang et al, PEGS 2011




Higher order structure and size variants are characterized by orthogonal methods

10 -4-2.0

-1.6

-1.2

-0.8

-0.4

0.0

0.4

0.8

Ab

sorb

ance

1600 1620 1640 1660 1680 1700

Wavenumbers (cm-1)

US Lot 031622EUS Lot 042212EUS Lot 050662E

ABP Lot 0010085288ABP Lot 0010085295ABP Lot 0010085297

-14

-12

-10

-8

-6

-4

-2

0

2

4

260 280 300 320

Wavelength (nm)

CD

Elli

pticity

US Lot 081492E

US Lot 092852E

US Lot 092872E

ABP Lot 0010095541

ABP Lot 0010112898

40 60 80 100

0.00000

0.00004

0.00008

0.00012

ABP Lot 0010085297ABP Lot 0010085295ABP Lot 0010085288EU Lot 02136XH02EU Lot 02129XH14EU Lot 92081XD01

US Lot 050662E

US Lot 031622EUS Lot 042212E

Cp (c

al/ C

)

Temperature ( C)

(e) Monomer, dimer, oligomers


Circular Dichroism

FTIR

Analytical Ultracentrifugation

2 4 6 8 10 12 14 16 18 20

0

1

2

3

4

5

6

7

8

9

10

US lot 970031US lot 450657US lot 970032ABP lot 0010133673ABP lot 0010112870ABP lot 0010095534EU lot H0138B01EU lot H0021B06EU lot H0134B01c(

s)

Sedimentation coefficient (Svedberg)

Calorimetry



Eg, unfolded protein spiked into product • Limit of detection is 8% by

near UV circular dichroism • How sensitive to partially

unfolded species?

A common limitation of spectroscopic methods is sensitivity to mixtures


Near UV CD

Percent UnfoldedW

eigh

ted

Spe

ctra

l D

iffer

ence

(WS

D)

0 20 40 60 80 100

Spectral changes detectableat WSD of 4.5

8.3% unfolded




• Focus on characterizing particles (0.1 m to 10 m) • Size, composition, quantity, structure • Relevance to immunogenicity

• Improving sensitivity, accuracy, and specificity • Protein vs. container

• Emerging nanotechnology-based approaches for < 1 m particles

• Quantitative and qualitative comparisons remain difficult

Particulate characterization technology is improving

Aggregation (<0.1 m)

AUC

1

10

100

1000

10000

0 5 10 15 20Par

ticl

e C

on

cen

trat

ion

(#/

mL

)

Diameter (µm)

LOQ

Light obscuration

Particulation (>1 m)

MFI



5 10 15

Aggregate

Monomer

sedimentation coefficient (S)

c(s)

5 10 15

Aggregate

Monomer

sedimentation coefficient (S)

c(s)18 The Role of Analytical and Structure–Function Studies

in the Assessment of Biosimilarity



Glycosylation is a critical quality attribute that can impact biological functions

19

Glycan mapping by HILIC and Mass Spectrometry

• Over 25 mAb glycans identified

• Correlate glycan attributes with

biological function

Glycan Type Impact to function

No glycan No ADCC

Bisecting GN Increase ADCC

High mannose Clearance and effector function

Terminal Gal Increase CDC

NANA Anti-inflammatory

Afucosylated Increase ADCC

min 5 7.5 10 12.5 15 17.5 20 22.5 25

0

10

20

30

40


Hydophobic Interaction LC (HILIC)



Product isoforms need to be fully characterized using separation methods

Size variants • Truncation • Dimer • Multimers

Charge and hydrophobic variants • N-terminal modification • C-terminal modification • Deamidation • Oxidation

min 5 10 15 20 25 30

mAU

Size Exclusion HPLC

Minutes

12 13 14 15 16 17 18 19 20 21 22 23

AU

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0.22UV - 280nmABP 494 14011712-2 A52Su 1

UV - 280nmErbitux EU 133839 A52Su

UV - 280nmErbitux US 10C00383 A52Su

Isoelectric Focusing

K K K

Ion Exchange HPLC



Amgen unpublished data Amgen unpublished data Amgen unpublished data

Separation methods also used to examine the integrity of covalent structure

Non-reducing SDS • Partial molecules • Half molecules • Fragments • Non-disulfide

linked aggregates

Heavy Chain

Light Chain

mAU

min 5 10 15 20 25

0

10

20

30

40

HC LC

Internal Std

min 5 10 15 20 25

mAU

-2

0

2

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min

1

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3 4

5

Internal Std

Reducing SDS • Truncation • Clipped species




Product-related and process-related impurities must be well characterized • High resolution and orthogonal methods are required to characterize

product-related species.

• Process-related impurities (HCP, DNA, leachables, etc) need to be characterized to ensure product quality.

• Particles and aggregates of various sizes need to be evaluated and characterized.

Size variants: • Truncation • Dimer • Multimers • Clipped species • Non-glycosylated HC

Charge and Hydrophobic Variants: • N-terminal modification • C-terminal modification • Deamidation • Oxidation

• Partial molecules • Half molecules • Fragments • Non-disulfide linked aggregates

Minutes12 13 14 15 16 17 18 19 20 21 22 23 24

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NGHC

Heavy Chain

MMW

LightChain

LMW HMW

Sig

nal (

280

nm)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Time (min)15.0 20.0 25.0 30.0 35.0 40.0

Basic

Main

Acidic



Amgen unpublished

data

Proteins undergo complex degradation and are sensitive to storage and handling

Protein stability

Thermal stress

Chemical stress

Physical stress

Enzymatic stress

Degradation contributes to eventual loss of biological activity and/or potential immunogenicity

Biosimilar stability is impacted by its manufacturing process and formulation



Forced degradation studies should demonstrate similar stability profiles Multiple accelerated thermal stress conditions (25, 40, 50°C) provide a quantitative, reproducible, and sensitive comparison of degradation profiles and rates

• Example: Size Exclusion Chromatography profiles – 50°C, T=15 days

• Rate comparisons: 0-15 days



Amgen unpublished

data

Discussion Topics


• Elements and limitations of analytical studiess



Structural comparisons leave residual uncertainties

Sources of uncertainty Potential consequences Assay limitations (limit of detection, specificity, etc.)

Unobserved differences could potentially impact efficacy or safety

Lot to lot variability and population statistics

Equivalence of means does not prove that individual lots are biologically equivalent

Observed differences in critical attributes

Could impact safety or efficacy if differences are large enough

Observed differences in less critical attributes

• Are assumptions about criticality correct?

• Could combinations of attributes become significant?

Challenges of Structure-Function Studies for Assessing Similarity 26

Functional studies are the first step in addressing these residual uncertainties

Why functional characterization? Part 1: Required by regulators

• Functional characterization required • To confirm quality and potency of the product • To address limitations of structural assays • To confirm similar mechanism(s) of action

• presence of expected function, absence of new function • specificity of target binding

• Relevant passage from FDA guidance “Depending on the structural complexity of the protein and available analytical

technology, the physicochemical analysis may be unable to confirm the integrity of the higher order structures. Instead, the integrity of such structures can be inferred from the product’s biological activity.” (Emphasis added)

FDA Draft Guidance, Quality Considerations in Demonstrating Biosimilarity to a Reference Product, February 2012




Matching all biological and functional properties is essential

Target binding to Complementarity-

Determining Regions (CDRs)

Binding Region for FcR

(ADCC, CDC)

Binding Region for FcRn (PK ½ life)

IgG1

N-glycan

Heavy chain

Intra-chain disulfide

Inter-chain disulfide

Light chain

Biological functions are dependent on the target antigen and the class of antibody

Concentration (nM)

0.1 1 10 100 1000 100000

500000

1e6

1.5e6

2e6

4-P Fit: y = (A - D)/( 1 + (x/C)^B ) + D: A B C D R^2EU Lot H0134B01 - (H0134B01: Concentr... 1.65e+06 1.31 49.4 -4.43e+04 0.997EU Lot H0021B06 - (H0021B06: Concentr... 1.64e+06 1.38 73.9 -4.51e+04 0.998EU Lot H0138B01 - (H0138B01: Concentr... 1.63e+06 1.38 65 -4.21e+04 0.997ABP Lot 0010095534 - (GMP1 0010095534: ... 1.68e+06 1.29 62.9 -5.2e+04 0.998ABP Lot 0010112870 - (GMP2 0010112870: ... 1.62e+06 1.43 71 -4.68e+04 0.992ABP Lot 0010133673 - (GMP3 0010133673: ... 1.64e+06 1.53 64.9 -3.38e+04 0.997US Lot 970032 - (970032: Concentratio...1.63e+06 1.41 74.4 -3.61e+04 0.998US Lot 450657 - (450657: Concentratio...1.64e+06 1.31 79.2 -5.64e+04 0.998US Lot 970031 - (970031: Concentratio...1.62e+06 1.65 72.5 -1.76e+04 0.998

__________Weighting: Fixed




QbD for biosimilars • Assess criticality based on

literature & experience (where available)

• Minimize differences for high criticality attributes

• Perform structure-function studies to assess remaining differences

• Relate findings to potential clinical impact

Why functional characterization? Part 2: May be essential to justify differences

Product Quality Attributes

Criticality Assessment

Safety and Efficacy Data

High Criticality Attributes

Low Criticality Attributes

Product Understanding

Clinical Studies

Animal Studies

In-Vitro Studies

Prior Knowledge

Focus on the most important

attributes

Lower criticality attributes are

not “forgotten”




Prepared samples can increase sensitivity of structure-function studies

Charge Variants % Relative Potency

Acidic variants 82

Main peak 101

Basic variants 84


Cation exchange profile of a mAb

% variant

Po

ten

cy

Observed range

Enriched sample

Slope estimate

Improved estimate of slope informs potential criticality and permitted magnitude of differences

Notional data for illustration purposes only


Figure adapted from G. Grampp (Amgen), “Challenges of Structure-Function Studies for Assessing Similarity” presented at the Spring ACS Meeting, New Orleans, LA (April 2013)

Studies must provide relevant conclusions 1) Evaluate in vitro functional data

a) Test functional equivalence of actual batches

Is a 25% difference really acceptable?

b) Relate attribute difference to parameters from structure–function studies

• Measured difference in means

• Estimated quantitative effect

• Relate to clinically meaningful differences

Att

rib

ute

Lev

el

Reference Lots


Biosimilar Lots

x coefficient = estimated

effect

Po

ten

cy

Attribute Level

Test for equivalence of means

80% < < 125%

Reference Lots Biosimilar Lots




Studies must provide relevant conclusions 2) Evaluate PK and drug metabolism where feasible

0

2

4

6

8

10

12

14

0 10 20 30Time (day)

pE b

y U

V

In vivo vs. in vitro conversion of Glu to pyroGlu

Adapted from Liu et al. 2011, J.Biol. Chem. 286, 11211-11217

• Serum incubation in vitro: is a variant formed under physiologic conditions?

• Product recovery from PK samples

0%

1%

2%

3%

4%

5%

6%

0 10 20 30

Time post injection (Days)

Perc

ent o

f tot

al g

lyco

pept

ide

G0G1M5

0%

1%

2%

3%

4%

5%

6%

0 10 20 30

Time post injection (Days)

Perc

ent o

f tot

al g

lyco

pept

ide

G0G1M5

M5 increases initially

followed by decrease



101%

98%

101%

113% 99%

90%

106%

106%

0.00

0.20

0.40

0.60

0.80

1.00

1.20

3.20 3.30 3.40 3.50 3.60 3.70 3.80

SA/N

LE/N

RB-DNM-BNM-CNM-DVY-B VY-F EM DT

101%

98%

101%

113% 99%

90%

106%

106%

Process change case study

Small effects can combine in unexpected ways

• Change resulted in shifts in 2 attributes (see figure)

• Bioassays predicted equivalent potency

• Equivalent PK shown in human clinical study

• Potency difference detected in clinical PD study

• Post hoc studies with prepared fractions identified additive effects on potency

In vitro potency of prepared fractions

Attribute 1

Att

rib

ute

2

Post-change Pre-change


Prepared fraction



• Predicting human PK/PD • Animal studies may not account for species specific

clearance mechanisms • Insufficient power due to small number of animals

• Predicting human immune response • In silico, in vitro, and in vivo methods are insufficient to

rule-out clinically relevant differences

Additional challenges in structure-function studies


• Analytical advances permit high resolution similarity assessments for many attributes • Higher order structure and particle assessments still

subject to uncertainty • Orthogonal approaches partially compensate for lower

sensitivity

• Assessing impact of differences remains challenging • Not all clinically relevant effects can be evaluated pre-

clinically (e.g., PK and immunogenicity) • Small effects and combinations difficult to assess

Summary and Conclusions


Thank you!

Challenges of Structure-Function Studies for Assessing Similarity 131

1September2015,Le MeridienDubai ,UnitedArabEmirates Sundar...

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