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Microfluidic Electrophoresis Assays for Rapid Characterization of Protein in Research and Development

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Participating Experts:

Brought to you by the Science/AAAS Custom Publishing Office


14 November, 2012

Joey Studts, Ph.D. Boehringer Ingelheim Pharma GmbH & Co. KG Biberach, Germany

Timothy Blanc ImClone Systems Branchburg, NJ

Bahram Fathollahi, Ph.D. PerkinElmer San Francisco, CA


© 2009 PerkinElmer © 2009 PerkinElmer © 2009 PerkinElmer © 2009 PerkinElmer

Bahram Fathollahi Microfluidics R&D November 14, 2012 Science/AAAS Microfluidics Webinar

Microfluidic Assays for High Throughput Screening of Protein Quality in Bioprocess Development

What is a Microfluidic Device?

An integrated device with controlled transport of sample and reagents in microchannels to carry out bio/chemical analysis Advantages Miniaturization Fast analysis/high throughput Small sample volume Integration Automation

4

Microfluidic Chip Format and Fabrication Planar Chip Single use Samples added to wells manually

Sipper Chip Reusable Samples introduced automatically

from microtiter plate

Chip Fabrication Chips manufactured using photolithography

and wet etching technology Quartz and glass substrate Highly reproducible and precise control of

channel geometry Typical depth - 5 µm to 25 µm Typical width - 10 µm to 100s µm

Sipper (autosampler)

5

Electrophoretic Separation in Microfluidic Chips

SAMPLE LOAD

AND INJECTION

SEPARATION DETECTION

Sample Reservoir

Waste Reservoir

Sample Load

Sample Separation

LIF detection

Sample Injection

Buffer Reservoirs

B C D

A

B

A

∆V ∆V ∆V ∆V

6

Commercial Microfluidic Electrophoresis Platforms

Bioanalyzer 2100

Experion

Higher Throughput

LabChip |DX/GX/GXII

Planar chip format

Sipper chip format

• RNA & DNA analysis

• Proteins

• N-Glycans (LabChip Only)

• Digital information

• Easy-to-use

• Time and cost savings

7

8

Protein Characterization Assays on LabChip GX II

Microchip

LabChip GX II

Multiple HT Screening Assays on a Single Microfluidic Platform

1) Microchip CE-SDS – 40 sec/sample Protein expression optimization Assess purity

Reduced and non-reduced Titer Quantify impurities

Product- and process-related Monitor fragmentation and Ab assembly

2) N-Glycan Profiling – 60 sec/sample Measure relative amounts of major N-linked glycans

3) Charge Variant Profiling – 68 to 90 sec/sample Identify and measure relative amounts of basic, main,

acidic variants

Microchip CE-SDS Assay Workflow

Crude or purified protein sample (2µL)

Add Sample Buffer Heat denature ~15min

Prepare Gel/Dye-

Solution and Ladder

Add Reagents to chip

Place Ladder and Buffer on GXII

Reusable chip Up to 400 samples

~ 40 sec per sample ~ 75 min for 96-well plate

Protein Analysis

E-gram

Plate View

Sizing, Conc., and

Purity

Identified expected protein

peaks

Gel View

9

10

Attributes Assay Instrument time Microchip CE-SDS

Concentration ProA HPLC RP HPLC

2-5 min ~20 min

< 1 min

Assembly, covalent aggregation nrCE-SDS 30-50 min < 1 min

Fragmentation, Degree of N-glycosylation rCE-SDS 30-50 min < 1 min

10

12

14

16

18

20

22

24

26

28

30

LC HC

NGHC LM

8

Fluorescence

Time (seconds)

0

250

500

750

1000

1250

13 18 23 28 33 38 43 48 53

HHL Aggregates (covalent)

Monomer

HL

In-process sample

Reducing Non-reducing

X. Chen et al .Electrophoresis 2008, 29, 4993-5002

Microchip CE-SDS

Conventional CE-SDS

Microchip CE-SDS vs. Conventional CE-SDS

30 seconds

HT N-Glycan Profiling Sample Prep Workflow

Denaturing plate

PNGase-F Plate

Glycan Labeling Plate

Denature and Reduce mAb in Denaturing Buffer

Add Denatured Reduced mAb to Enzyme Plate

Transfer to Dye Plate

Heat Assay Plate at 55 °C for ~2h

Heat (Denatured mAb + Enzyme) at 37 °C for ~1h

Dilute with separation Buffer

Read 96-well plate on LabChip GXII ~1.5h

G1F’ G1F G0F

G2F M5 G0

LabChip GXII

microchip

11

Man5 G0

G0F

G1F

G2F

G1’F

UNK

G2 UNK

UNK

G1

Digested and Labeled N-Glycan Profile

12

Methods of Characterizing Charge Heterogeneity Three methods of separation used in the biotherapeutics industry: Ion Exchange Chromatography (IEC)

Extension of HPLC systems Proteins interact with charged resin, based on pI and hydrophobicity

Capillary Zone Electrophoresis (CZE) Based on Capillary Electrophoresis (CE) systems Proteins migrate at different speeds, based on pI and hydrodynamic drag

Isoelectric Focusing (icIEF) Based on imaged CE systems Proteins migrate to a particular position within a pH gradient, based on pI

Limitation of current methods: Lack of speed

13

Analysis Time IEC icIEF CZE Microchip-CZE

Per Sample 30 - 90 min 15 - 20 min 8 - 30 min 1 - 2 min

Per 96-Well Plate 48 - 144 hrs 24 - 32 hrs 16 - 48 hrs 1.8 - 2.9 hrs

HT Protein Charge Variant Assay

Variant Detection Conventional methods use absorbance at 280 nm LabChip detects via LIF Dye must be conjugated to protein variants Dye must absorb & emit at wavelengths that are compatible with instrument optics Dye must conserve charge of protein variants

14

Rel

ativ

e A

mou

nt (%

)

Acidic Variants

Main Variant

Basic Variants

Before Labeling After Labeling

From icIEF analysis

Charge profile does not change

Direct Comparison With Alternative Methods

15

Minutes0 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00 3.20 3.40

8.58

5

8.71

2M

ain

Isof

orm

- 8.

810

8.94

89.

044

8.00 8.20 8.40 8.60 8.80 9.00 9.20 9.40 9.60

HT PCV

Conventional CZE ~10min

icIEF 15 min

Acidic Basic

Acidic Basic Acidic Basic

Microchip-CZE 60 sec

Small-Scale High Throughput Process Development

Mother Plate

Purity Assessment

N-Glycan profiling

Charge Variant

BioTx workstation

Daughter Plate

Analytics for determination of critical quality attributes

16

Clone selection/cell

culture optimization

Screening high number of cell clones in small-scale bioreactors

µscale chromatographic purification

Sample prep/ µscale purification

Daughter Plate

Daughter Plate

Informatics

Higher demand of product quality requires multi-factorial DOE studies in upstream and downstream process development

Process parameter optimization

Optimization and

Scale-up

Process understanding and decisions

Microfluidics R&D Tobias Wheeler Lucy Sun Rajendra Singh Mai Ho Hui Xu Melissa Takahashi Roger Dettloff

Chip and Reagent Fabrication Joan McAuliffe Ken Summers Trang Le Khushroo Gandhi

Software Advit Bhatt Dan Camporese Renil Das

17

Acknowledgements

Thank you!

Marketing & App Support Rick Bunch Krystyna Hohenauer Nate Cosper Seth Cohen Linda Gary Marsha Paul

Process Science Germany, 2012


14 November 2012

Project Timelines Focus on Critical Bottlenecks in Development

19

Exploratory Research

Preclinical Development

Development Clinical Dev. Phase I,II

Phase IIb/ III Registration

Market Supply

Overall Project Timeline

• Critical bottleneck is time to the clinic

• Reduce time to clinic to shorten time to market Process

Development/ optimization

GMP Pilot Plant

Ph I - Scale up Cell line

non GMP scale up,

Tox material

• Fast track development by applying “platform technologies”

• Material supply: 1 g - 2 kg

Bottleneck to Clinic

• Often is data on the critical path in development

• Early process understanding critical to efficiency and safety

More data Better Decisions Efficient Development Better Products

BI-PurEx: Lean Development Strategy Understanding the product & the process

25

• Cell line development is on critical path • Rate limiting step is cell growth, very little material with which to

gain knowledge • Choosing the correct cell line for each product is most critical • Impacts product quality, functionality, expression levels,

comparability… • Early knowledge and correct decisions will have an significant

impact on efforts and timeline throughout the development process.

Cell Line Development Process Development USD & DSD

Scale-up USD & DSD

Pilot Scale GMP

Product & Process are critical

Product Understanding Glyco Patterns

26

• Initial challenges in Glycosylation • Mainly controlled by cell line decision • Purification normally has very little impact on glycans • Impacts comparability and functionality of molecule • Critical to get early knowledge and impact cell line development decisions!

20 30 40 50 60 70

8 7

6A 4A

S:/B

PQC/

QC/Q

CAS/

LG7/

FOB/

Calip

er D

aten

abgl

eich/

T1-H

EX-1

10-0

9.op

j/13.

01.2

011

Zug

Retention Time [min]

Ex 330

nm

/ Em

420 n

m

6 5 4

3

2

1

HPLC: 20 min/run MS: >> 20 min/run

Product Understanding High Throughput Glyco Analysis

27

T9 Std. 5 mg/mL

T9-HEX2-101-01

T9-HEX2-101-02

T9-HEX2-101-03

T9-HEX2-101-04

T9-HEX2-101-05

T9-HEX2-101-06

T9-HEX2-101-07

T9-HEX2-101-08

T9-HEX2-101-10

Man5 7,48 4 6,3 6,15 8,39 3,24 3,1 4,28 4,83 3,07

NGA2 3,09 1,94 1,23 0,92 6,65 1,73 1,16 1,19 2,54 2,31

NGA2F 16,95 14,71 17,45 0,37 0,73 12,03 9,15 12,17 14,2 11,52

NA2G1F 3,66 1,79 1,89 0 0,73 1,54 0,73 1,21 1,55 1,61

NA2 0,06 0,1 0 0 0 0 0,07 0,08 0,04 0,15

NA2F 0,24 0,26 0,14 0,37 0,22 0,17 0,1 0,17 0,17 0,26

0

2

4

6

8

10

12

14

16

18

20%

CGU

(Cali

per G

luco

se U

nits

)

Standard Clone 1 Clone 2 Clone 3 Clone 4 Clone 5 Clone 6 Clone 7 Clone 8 Clone 9

• Using Microfluidic Assay – all pools are analyzed for glycan map prior to cell line decision.

Product Understanding High Throughput Glyco Analysis

28

DS01 [5mg/mL] Inj. 1 Inj. 2 Inj. 3 Mean SD VK Std.

Method Man5 4,05 4,27 4,24 4,19 0,12 2,85 4,52

NGA2 2,93 2,89 2,83 2,88 0,05 1,75 2,73

NGA2F 59,61 57,5 59,1 58,79 1,10 1,87 60,48

NA2G1F 14,2 13,8 13,82 13,94 0,23 1,62 20,6

NA2F 1,7 1,83 1,43 1,65 12,34 12,3 1,9

HT - Microfluidic Assay • High Throughput • Very reproducible • Comparable to standard

Methods.

Product Understanding Product Based Impurities

29

Standard 97.1 % Purity Clone 1 94.1 % Purity Clone 2 94.6 % Purity Clone 3 95.1 % Purity Clone 4 94.3 % Purity Clone 5 94.2% Purity

• Product purity influenced by purification process development • Microfluidic Assay helps point out critical impurities to focus later

development efforts and to track in cell line decisions.

Electorpherogram from reduced mAb sample

Product Understanding Product Purity – Charge Heterogeneity

30

7.03

0 7.17

8

7.30

4

7.41

7

7.55

5 7.65

5

7.76

3

7.84

2

Minutes6.90 7.00 7.10 7.20 7.30 7.40 7.50 7.60 7.70 7.80 7.90

iCE

16.1

36

16.5

55

17.7

66 18.2

79

19.1

20

19.7

60

20.9

13

Minutes13.50 14.00 14.50 15.00 15.50 16.00 16.50 17.00 17.50 18.00 18.50 19.00 19.50 20.00 20.50 21.00 21.50 22.00 2

WCX

BPG

BPG BPG

APG

APG APG

MP

MP

MP

Qualitative analysis no longer enough • Impact on safety and efficacy Critical to Comparability • Impacted by cell line • Impacted by fermentation process • Impacted by purification process

High throughput method required to look

at all samples

acidi

c Pe

akgr

oup

- 18.

324

Mai

npea

k - 1

9.21

2

basic

Pea

kgro

up -

19.8

21

Minutes13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00 22.00 23.00 24.00 31

Aci

dic

Pea

k 1

- 7.0

36

Aci

dic

Pea

k 2

- 7.1

91

Aci

dic

Pea

k 3

- 7.3

08 Mai

n P

eak

- 7.4

09

Bas

ic P

eak

1 - 7

.543

Bas

ic P

eak

2 - 7

.633

Minutes.80 6.90 7.00 7.10 7.20 7.30 7.40 7.50 7.60 7.70 7.80 7.90 8.00

acid

ic P

eakg

roup

- 18

.332

Mai

npea

k - 1

9.23

5

basi

c P

eakg

roup

- 19

.772

Minutes13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00 22.00

iCE

WCX

Clone Z Clone X

Clone Z Clone X

Clone Z Clone X

R&D 1 Clone Z

Aci

dic

Pea

k 1

- 7.0

35

Aci

dic

Pea

k 2

- 7.1

80

Aci

dic

Pea

k 3

- 7.3

04

Mai

n P

eak

- 7.4

17

Bas

ic P

eak

1 - 7

.554

Bas

ic P

eak

2 - 7

.635

Bas

ic P

eak

3 - 7

.759

Bas

ic P

eak

4 - 7

.841

Minutes6.85 6.90 6.95 7.00 7.05 7.10 7.15 7.20 7.25 7.30 7.35 7.40 7.45 7.50 7.55 7.60 7.65 7.70 7.75 7.80 7.85 7.90 7.95

R&D 1 Clone Z

R&D 1 Clone Z

iCE

WCX

Sensitivity very high Ability to detect differences between clones

Ability to detect

differences to reference material.

Product Understanding Product Purity – Charge Heterogeneity

Process Understanding RAPPTor®

32

Fully automated purification screening platform From resin and plate preparation to step elution Screen 96 variables and generate of up to 500 sample per day

Fully automated sample preparation and analytical assays Automated homogeneous assays to screen critical output parameters

Tecan 150 – HT Screening Tool Tecan 200 - HT Analytical Tool

Separate but Seamless

Rapid Automated Protein Purification Technology

Process Understanding High-Throughput Parallel Chromatography

33

gaining process knowledge earlier in a shorter timeframe with less material demand

288

72

4

33

9

4

0 100 200 300

Serial Column runs

RoboColumn runs

Filterplate run

time (h)

robustness study (11 runs) initial screening (96 runs)

• Microfluidic Assay allows analysis of impurities profile for each of the samples generated.

Process Understanding Critical Impurities

34

Sample Name % Purity Type

Standard 0,22 Unknown

AT Prod Pool 0,88 Unknown

DF Prod Pool 0,87 Unknown

AEX Prod Pool 0,88 Unknown

CEX Prod Pool 0,76 Unknown

Bulk Prod Pool 0,79 Unknown

• Assay set-up not complex, carried out within development lab • Data delivered within hours, not days • Can take next step to test fractionation of individual process steps • IMPACT on real time decsions!

Process Understanding Determination of aggregates

35

Size exclusion chromatography Molecular weight standard

HPLC TSK G3000 SWXL, 7.8 x 300 mm, 5 µm, 20 µL

ACQUITY UPLC BEH200 SEC, 4.6 x 150 mm, 1.7 μm,4 µL ~ 8 min

~ 20 min

Acquity UPLC H-Class: • Shorten analysis time by

factor of 2.5 • Increase resolution through

smaller particle diameter • Lower injection volumes • Low carry over • Applicable to WCX, RP….

Process Understanding Analytical Throughput: Method portfolio

36

UPLC- SEC 96-well UV detection

Analytical techniques with increased throughput. Understand impact of each step on product quality and contaminant removal.

Lab Chip GXII

Automated ELISA Anti-CHO HCP conjugated

acceptor bead

Streptavidin-coated

Donor bead

Excitation 680 nm Emission 615 nm 1O2

Host cell proteins

CHO HCP AlphaScreenTM (768 data points overnight)

iCE280

Boehringer Ingelheim Biopharma Process Science

37

Thanks for your attention!!!

Thanks to many colleagues at Boehringer Ingelheim especially: to H. Kaufmann, D. Ambrosious to, J. Stolzenberger, S. Combe, O. Haas, S. Müller, D. Dieterle

Boehringer Ingelheim, Bibearch, Germany

Company Confidential Copyright © 2010 ImClone LLC

The Use Of Microfluidics Technology in the Pharmaceutical Industry: MicroChip Electrophoresis as a High Throughput Process Analytical Platform to support the Development of Therapeutic Monoclonal Antibodies

Tim Blanc and Qinwei Zhou ImClone Systems. Branchburg, NJ 08876

39 Company Confidential Copyright © 2010 ImClone LLC

Introduction

Rapid analytical separations is an important application stemming from the development of Microfluidics. One such separation technique is MicroChip Electrophoresis (MCE). MCE can be performed in several modes to provide valuable insights to the relationship between bioprocess parameters and the quality attributes of biopharmaceutical products. Recombinant Monoclonal antibodies commonly exist as heterogeneous mixtures of product variants. Several factors contribute to product variants, one such factor is glycosylation. Using Glycosylation as the example, It is important to understand what the relationship is between process parameters and glycan distribution expressed on the antibody. An effective Quality by Design (QbD) approach uses design of experiments (DOE) to determine the most important process parameters, termed Critical Process Parameters (CPPs). However the number of samples required for the experimental design can be high. Testing this number of sample to gain the most thorough process understanding is time and cost prohibitive by standard methods. Discussed will the regulatory and biopharmaceutical issues that have accelerated the need for rapid analytical separation. Then, will be discussed application on MCE that have been developed to address those needs.


The New Quality Paradigm • ICH Q8 (R2) Pharmaceutical Development

• ICH Q9 Quality Risk Management

• ICH Q10 Pharmaceutical Quality Systems

• ICH Q11 Development and Manufacture of

Drug Substance ICH Q11: “Risk management, and scientific knowledge are used more

extensively to identify and understand process parameters and unit operations that impact critical quality attributes (CQA’s) and develop appropriate control strategies applicable over the lifecycle of the drug substance


Quality Risk

Management

Product Knowledge

Quality Systems

Process Knowledge

Critical Process

Parameters

Critical Quality

Attributes

Control Strategy

Quality Risk Management: Linking Process Knowledge, Product Knowledge and Quality Systems

Ref.- Quality Attributes of Recombinant Thereapeutic Proteins: An Assessment of Impact on Safety and Efficacy as part of a Quality by Design Development Approach Eon-Duval, A. et.al BIOTECHNOL. PROG., 2012, Vol.00, No. 00


Good Business too

IND Phase I Phase II Phase III BLA

Process Development and Scale-up (Changes)

Tox & PK Studies

Comparability Studies- Linking Commerical scale product back to original material use in Tox. & PK Studies

Assure QCA’s are maintained within acceptable ranges (QTPP), Quality Target Product Profile, throughout Process Development. Maintain link to Tox. & PK studies.


Heterogeneity of Monoclonal Antibodies

Therapeutic Mab Product Contents

Product Variants

Process Related Impurities Trace amounts (ppb-ppm) • Residual Host Cell DNA, • Residual Host Cell Protein, • Residual Protein-A.

ProductRelated Impurities 1-5% • Antibody Fragments, • Aggregates

Product Variants Post-Translational Modifications:

• Glycan Variants, • C-Terminal Truncation, • Deamidation, etc.

Critical Quality Attributes (CQA’s)


Heterogeneity of Monoclonal Antibodies

Therapeutic Mab Product Contents

Product Variants

Multiple Sources give rise to Product Variants


Critical Process Paramenters (CPP)

CPPs are independent process parameters most likely to affect the quality attributes of a product or intermediate

CPPs are determined by analytical testing, scientific judgment and on research, scale‐up or manufacturing experience

CPPs are controlled and monitored to confirm that the impurity profile is comparable to or better than historical data from development and manufacturing.

Quality attributes related to CPPs include:

• Product Variants Distribution (Glycosylation is a major contributor) • Product-Related Impurities • Process-Related Impurities


Glycosylation


Implications of Glycosylation Variants

• The greatest source of Mab Product Variants is Glycosylation

• Glycosylation is very closely tied to process parameters

• Aspects of glycosylation will frequently be CQA’s

Glycan Structural Characteristic Implication Fucose: Effector Function (e.g. ADCC) Sialic Acids (NANA, NGNA) PK modulation (up or down) NGNA Immunogenicity α-Galactose Immunogenicity


MCE and Product Variants

Sample prep designed in microtiter plate format with immobilized enzyme to reduce sample prep from 2 days to ½ day (Glycans).

Rapid electrophoretic separation on Microchip with sensitive laser-induced fluorescence detection. (<60 seconds per sample)

Analytical separations in under 60 seconds for determinations of:

• Size Heterogeneity • Charge Heterogeneity • Glycosylation Heterogeneity

Throughput and Accuracy for thorough QbD testing, CPP determination

and Successful Control Strategy efforts


Data is all numerical for statistical comparison

High Throughput Platform for PAT

MCE N-Linked Glycan Analysis

% G0F % G1F % G2F % α-Gal % Fucosylated % Sialylated (NGNA)

Glycosylation MCE-CZE

Charge-Based Evaluation

Relative Distribution Of Product Variants

% APG % NPG % BPD

Charge MCE-SDS

Size-Based Evaluation

% Purity (NR) % Aggregate % Fragment % Purity (Red.) % Non-Reducible % Aglyc HC

Size


MCE Platform: Size Heterogeneity

MCE-SDS < 60 SECONDS per Samples

CE-SDS ≈ 60 Minutes Samples


MCE Platform For QbD: Charge Heterogeneity

MCE < 60 SECONDS per Samples

IEC >60 MINUTES per Sample


MCE Platform: Glycan Heterogeneity

MCE < 60 SECONDS per Samples

HPLC ≈ 60 Minutes Samples


Conclusions

• Rapid Analysis time and easily automated.

• Allows more samples tested and better insight to Impact of process parameters.

• CPP’s determined and detailed process understanding.

• Effective Control Strategy.

• Relevant Drug Substance Specification (JOS).

Sponsored by:

Participating Experts:

Brought to you by the Science/AAAS Custom Publishing Office


17 October, 2012

ADVANCING EPIGENETICS: NOVEL DRUG DISCOVERY STRATEGIES FOR EPIGENETIC TARGETS

To submit your questions, type them into the text box

and click .


14 November, 2012

Joey Studts, Ph.D. Boehringer Ingelheim Pharma GmbH & Co. KG Biberach, Germany

Timothy Blanc ImClone Systems Branchburg, NJ

Bahram Fathollahi, Ph.D. PerkinElmer San Francisco, CA


Brought to you by the Science/AAAS Custom Publishing Office Brought to you by the Science/AAAS Custom Publishing Office

Look out for more webinars in the series at: webinar.sciencemag.org

For related information on this webinar topic, go to:

www.perkinelmer.com/biotherapeutics

To provide feedback on this webinar, please e-mail your comments to [email protected]

Sponsored by:


14 November, 2012


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