Developability Evaluation During Early Pre-formulation: The Meeting Point Between Research and Development

Bernardo Perez-Ramirez, MS, Ph.D. Senior Scientific Director BioFormulations Development, Global BioTherapeutics One the Mountain Rd. Framingham MA 01701, USA bernardo.perez@sanofi.com

Stability of Biopharmaceuticals: Getting the Chemistry Right. 4th Annual MIBIO Conference. Tuesday, September 30th, 2014. Downing College, Cambridge-UK.

Challenges Facing Protein Formulation and Product Development ● Time and budget allotted for developing and implementing formulations. ● Regulatory requirements. ● Requirements to work closely across sites and divisions as well as with

external suppliers. ● Need for quality, innovation and rapid time to market.

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Dev

elop

men

t Tr

ansi

tion

Product Development Timeline

● Need time for robust formulation development ● Insufficient window for real-time data ● Start formulation development early

(integration with research)

Phase 1/2 Formulation Development Timeline

Purification

Cell Culture

Formulation

Characterization & Analytical

Manufacturing/

Clinical Trials

Cell Culture

Formulation

Characterization & Analytical

Purification Purification

Cell Culture

Formulation

Characterization & Analytical

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Principles of the Formulation Developability Assessment: The Interface with Discovery Research

● Intrinsic Quality of the Constructs ● Can it handle the stresses associated with development and

manufacturing process? ● What are the degradation “pathways” of the protein? ● Rank candidates

● Information on Proper Handling ● Reduce false negative results due to incorrect handling

● Very Early Information on Protein Solution Behaviour ● Accelerates the formulation development process ● Foundation for QbD

● Great Return on Investment ● Cost ~20 mg and 4-8 weeks.

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Developability Evaluation During Early Pre-Formulation

Drug Discovery

Approach to Developability

Development

Manufacturing

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Protein Expression Clone stability Growth properties Titer Production Variability

Cellular Immunology In vitro characterization In-silico response

Formulation Stability of process intermediates Protein Stability

Purification Process Development Impurity Profile Yields Stability

Development Candidate Risk Assessment – Synergistic Collaboration

“Developability” Assessment

Candidate Selection

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Formulations Role in Developability Assessment

Developability Evaluation

Relevant Process Stresses Freeze/thaw Shear/Mechanical stress -Viscosity, injectability, solubility Mock viral inactivation

Forced Decomposition Degradation (pH 5-8) Temperature (45 °C)

• Desired results: Sufficient degradation to understand protein profile and differentiate candidate molecules

• Desired results: No change

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Stability and Solution Behavior Concerns

• Oxidation • Deamidation • Isomerization • Fragmentation • Disulfide exchange

Physical Stability • Soluble aggregation • Self association • Insoluble aggregation • Particle formation • Solubility • Viscosity

Chemical Stability

Function/binding

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Analytics

A280 (concentration) Turbidity Circular dichroism (secondary and tertiary structure) CE-SDS (purity) SDS-PAGE (purity) SEC (aggregation, fragmentation) N-terminal sequencing (identity) AUC (aggregates/oligomerization)

cIEF (charge variants) Peptide mapping Oxidation ( methionines in CDR) Isomerization (aspartic acid in CDR) Deamidation (PENNY peptide)

Physical Stability

Chemical Stability

Functional Stability Surface Plasma Resonance (Biacore)

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CASE STUDY: Which candidate has the best chance of making it through development and manufacturing…?

* *

* *

Construct 1

Construct 2

Construct 3

Construct 4

* *

* *

* *

* *

Mouse IgG2

Human IgG1 1

Human IgG1 2

CDR Grafting

Sequence Optimisation

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More thermal stability in Constructs 1 and 2 Less secondary structure in Construct 3

General Properties

Wavelength (nm)

210 220 230 240 250C

D S

igna

l

-10

0

10

Construct 1Construct 2Construct 3Construct 4

Construct 1 Construct 2 Construct 3 Construct 4

Mel

ting

Tem

pera

ture

(o C)

74

76

78

80

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Wavelength (nm)

210 220 230 240 250

CD

Sig

nal

-10

0

10

Construct 4 post-viral inactivationConstruct 4 time 0

Wavelength (nm)

210 220 230 240 250

CD

Sig

nal

-10

0

10

Construct 3 post-viral inactivationConstruct 3 time 0

Wavelength (nm)

210 220 230 240 250

CD

Sig

nal

-10

0

10

Construct 2 post-viral inactivationConstruct 2 time 0

Wavelength (nm)

210 220 230 240 250

CD

Sig

nal

-10

0

10

Construct 1 post-viral inactivationConstruct 1 time 0

Construct 4Construct 3

Construct 2Construct 1

Very slight decrease in structure

Slight decrease in structure

Red = time 0 Black = post vi

PROCESS STRESSES: Mock Viral Inactivation - Secondary Structure by CD

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PROCESS STRESSES: Mock Viral Inactivation (VI)

No change Minor change Moderate change Major change

Quality Attribute C-1 C-2 C-4 Comments

Aggregation

Purity

Charge Heterogeneity

Oxidation

Secondary Structure Possible ↓Construct 2

Turbidity

Melt Point *Quality attributes ranked in order of criticality

C3 was not considered as a candidate due to its obvious weak performance on most analytics and lack of in vitro activity

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PROCESS STRESSES: Shear/Mechanical Stress

Quality Attribute C-1 C-2 C-4 Comments

Aggregation

Purity

Charge Heterogeneity

Secondary Structure

Turbidity

Melt Point

No change Minor change Moderate change Major change *Quality attributes ranked in order of criticality

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PROCESS STRESSES: Freeze Thaw Study

Quality Attribute* C-1 C-2 C-4 Comments

Aggregation

Purity

Charge Heterogeneity

Secondary Structure

Turbidity

Melt Point

No change Minor change Moderate change Major change *Quality attributes ranked in order of criticality

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Slight increase in deamidation, except Construct 2

Significant increase in deamidation Least in Construct 2

Time (weeks)

0 1 2 3 4 5PE

NN

Y D

eam

idat

ion

(%)

0

5

10

15

20

25Construct 1 pH 7.2Construct 2 pH 7.2Construct 3 pH 7.2 Construct 4 pH 7.2

Time (weeks)

0 1 2 3 4 5

PEN

NY

Dea

mid

atio

n (%

)

0

5

10

15

20

25Construct 1 pH 5.0 Construct 2 pH 5.0 Construct 3 pH 5.0Construct 4 pH 5.0

FORCED DECOMPOSITION: pH Study - Deamidation of PENNY Peptide

pH 5.0 pH 8.0

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More clipping in Construct 1 Significant clipping in all constructs. Least in Construct 2, most Construct 1

Time (weeks)

0 1 2 3 4 5H

C C

lippi

ng (%

)

0

5

10

15

20

25Construct 1 pH 7.2Construct 2 pH 7.2Construct 3 pH 7.2 Construct 4 pH 7.2

Time (weeks)

0 1 2 3 4 5

HC

Clip

ping

(%)

0

5

10

15

20

25Construct 1 pH 5.0 Construct 2 pH 5.0 Construct 3 pH 5.0Construct 4 pH 5.0

FORCED DECOMPOSITION: pH Study - Heavy Chain Clipping

pH 5.0 pH 8.0

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FORCED DECOMPOSITION: Low pH (5.0) and Elevated Temperature

Quality Attribute C-1 C-2 C-4 Comments

Aggregation

Purity ↑Fragmentation

HC Clip

Isomerization

Deamidation

Charge Heterogeneity

Oxidation

Secondary Structure

Turbidity

Melt Point

No change Minor change Moderate change Major change *Quality attributes ranked in order of criticality

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FORCED DECOMPOSITION: High pH and Elevated Temperature

Quality Attribute* C-1 C-2 C-4 Comments

Aggregation

Purity ↑Fragmentation

HC Clip

Isomerization

Deamidation Significant ↑ in PENNY peptide

Charge Heterogeneity Significant ↑acidic forms

Oxidation

Secondary Structure

Turbidity Slight opalescent

Melt Point

No change Minor change Moderate change Major change *Quality attributes ranked in order of criticality

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Prob

abili

ty

Severity

Risk Analysis in Formulation

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Formulation Developability Ranking Construct 2>Construct 1>Construct 4>>Construct 3

Developability Ranking

Stress C-1 C-2 C-4

General

Freeze-thaw

Shear

Viral Inactivation

High temperature, pH 8.0

High temperature, pH 5.0

Favorable Neutral Weak Detrimental

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SUMMARY: Improving formulation strategies and outcomes by strengthening the Interface with discovery research

● Identify problematic candidates ● Identify analytical challenges ● Accumulate solution behavior data which will help guide development and

Quality by Design (QbD) ● Early information about the solution behavior of candidate proteins helps in

development strategies for robust dosage form development in a timely fashion.

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Acknowledgments

● Patrick Flanagan ● Rob Simler ● Nick Guziewicz ● Andrew Massetti ● Laura Geagan (AD) ● Lunds Anders (AD) ● Bill Brondyk (NPE) ● Bob Mattaliano

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