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AdvanceBio SEC Optimizing Quantification of mAb and ADC Aggregates: Speed versus Resolution February 16, 2016 Agilent Technologies 1

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Page 1: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

AdvanceBio SEC Optimizing Quantification of mAb and ADC Aggregates: Speed versus Resolution

February 16, 2016 Agilent Technologies 1

Page 2: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Optimizing Quantification of mAb and ADC

Aggregates: Speed versus Resolution

February 16, 2016 Agilent Technologies 2

What is size exclusion chromatography?

Why is resolution important?

How much resolution is needed?

How to speed up the analysis?

What is the benefit?

Dr Linda Lloyd, BioColumns Product Manager

Dr Andrew Coffey, Senior Applications Chemist

Page 3: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Aggregation

February 16, 2016 Agilent Technologies 3

Aggregates can be tangled clusters of denatured mAbs

• Irreversibly formed during production

• Expression, downstream processing

• Storage as drug substance or drug product

Aggregates can be ordered structures of native mAbs

• May be reversible or irreversibly

• Interaction may be hydophobic and/or electrostatic

• Dimer produced from association of two monomers

Aggregation is impacted by

• Biochemical and biophysical properties of the mAb

• Physicochemical environment

Aggregation impacts

• Process yield and economics

• Product immunogenicity

Page 4: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

When does aggregation matter?

February 16, 2016 Agilent Technologies 4

• candidate

selection

• protein

cloning

Discovery

• clone

selection

• stability

studies

• QbD

Development

• process

monitoring

• Continuous

improvements

• QC

Manufacture

Characterization

SEC for soluble aggregates

Aggregation is critical quality attribute - size exclusion chromatography is required technique to quantify aggregation

Page 5: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

100s of samples for analysis

Clone selection/development

• Bio-Monolith Protein

A/Protein G

How much is

expressed

• AdvanceBio SEC How much is

aggregated

• AdvanceBio Glycan

Mapping

What is the

glycan form

Formulation

Drug product (DP) requires

formulations that meet the target

product profile (TPP)

Require analytical methods needed

to determine stability and set shelf

life

Requires high throughput assays to

monitor multiple formulations as a

function of time

February 16, 2016 Agilent Technologies 5

Page 6: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Small number of samples

Candidate Characterization

• Multiple

characterization

techniques

What is the

candidate

• Aggregation What are the

critical quality

attributes

• Is the level of

aggregation likely to

cause late stage failure

Is it suitable to

move forward

Quality control

Batches of drug product (DP) must

meet the defined impurity profile

Require analytical methods with

sensitivity and resolution to ensure

batch complies with specification

Require robust analytical methods

that deliver accurate data for every

sample

February 16, 2016 Agilent Technologies 6

Page 7: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

What does that mean for SEC

February 16, 2016 Agilent Technologies 7

• Columns must deliver accurate, precise quantitation for mAbs and next generation biologics

• High resolution for more accurate quantitation

• Faster analysis speeds for delivery to deadlines

• No change to sample integrity

• Sensitivity for quantitation at low levels - 1 to 5%

• Methods must be easily transferred to other locations

AdvanceBio SEC columns improve lab productivity by providing robust, reliable methods

that eliminate sample re-analysis and increased sample throughput.

Page 8: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Size Exclusion Chromatography

• Size Exclusion Chromatography (SEC) allows the separation of

molecules based on the size in solution.

• Larger molecules are excluded from the pores of the stationary

phase and elute first.

• Smaller molecules diffuse into the pores and elute later.

• There is no interaction between the analyte and the stationary

phase.

• It is the method of choice for quantifying the amount of

aggregates, dimers and larger oligomers, of therapeutic

proteins such as monoclonal antibodies (mAbs).

February 16, 2016 Agilent Technologies 8

Page 9: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

SEC animation

February 16, 2016 Agilent Technologies 9

Page 10: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Detecting and quantifying mAb aggregation

February 16, 2016 Agilent Technologies 10

Page 11: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Detecting and quantifying mAb aggregation

February 16, 2016 Agilent Technologies 11

Page 12: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Detecting and quantifying mAb aggregation

February 16, 2016 Agilent Technologies 12

# Time Area Area

%

1 4.66 2.8 0.06

2 5.18 10.9 0.22

3 5.72 32.3 0.66

4 6.58 4849.0 98.40

5 8.13 20.4 0.41

6 8.80 14.2 0.29

1 2

3

4

5 6

Page 13: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Some definitions

• Column volume

• Exclusion limit / Void volume

• Interstitial volume

• Pore volume

• Total permeation

• Non-specific interaction

February 16, 2016 Agilent Technologies 13

Column Dimensions: 7.8 x 300 mm

Column Volume = 14.3 mL

Page 14: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

What are these inside the column?

• Interstitial volume

• Pore volume

February 16, 2016 Agilent Technologies 14

Interstitial or inter-

particle volume

Pore Volume or intra-

particle volume

Silica particles

Page 15: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

min2 4 6 8 10 12 14

Norm.

0

50

100

150

200

250

300

What are these regions on a chromatogram?

February 16, 2016 Agilent Technologies 15

Colu

mn V

olu

me

Pore

Volume

Interstitial

Volume

Exc

lusi

on

Lim

it /

Void

volu

me

Tota

l P

erm

eati

on

Non

-speci

fic

inte

ract

ion?

Page 16: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Rule Number #1

• Choose the right pore size

– It is essential to select a column that has pores

sufficiently large to allow your molecule to

permeate into the pore structure of the stationary

phase and not be excluded.

– It is also essential to choose a pore size that is not

too large.

February 16, 2016 Agilent Technologies 16

For monoclonal antibodies the optimum pore size is around 300Å …

Page 17: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Agilent SEC pore size selection

February 16, 2016 Agilent Technologies 17

Page 18: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

SEC Chromatogram of proteins

min2 4 6 8 10 12 14

mAU

0

50

100

150

200

250

300

350

February 16, 2016 Agilent Technologies 18

AdvanceBio SEC 300Å, 7.8 x 300 mm, 2.7 µm

1.0 mL/min, 150 mM Sodium Phosphate pH 7.0

UV, 220 nm

1 Thyroglobulin aggregates

2 Thyroglobulin

3 γ-Globulin (IgG) dimer

4 γ-Globulin (IgG)

5 Ovalbumin dimer

6 Ovalbumin

7 Myoglobin

8 Uridine

9 Vitamin B12 1

2

3

4

5

6 7

8

9

Page 19: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Creating a calibration curve

Thyroglobulin

dimer Thyroglobulin

IgG dimer

IgG Ovalbumin

dimer Ovalbumin

Myoglobin

Aprotinin

Neurotensin Angiotensin II

Uridine

2.00

2.50

3.00

3.50

4.00

4.50

5.00

5.50

6.00

6.50

4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00

Log(M

W)

Retention Time (min)

AdvanceBio SEC 300Å, 7.8 x 300 mm, 2.7µm Protein or Peptide MW Log(MW) RT (min)

Thyro Aggs 1340000 6.13 4.64

Thyroglobulin 670000 5.83 5.13

IgG Dimer 300000 5.48 5.65

γ-Globulin 150000 5.18 6.53

Oval Dimer 88600 4.95 7.25

Ovalbumin 44300 4.65 8.14

Myoglobin 16950 4.25 8.78

Aprotinin 6511 3.81 9.21

Neurotensin 1672 3.22 10.36

Angiotensin-II 1040 3.02 10.64

Uridine 244 2.39 11.22

February 16, 2016 Agilent Technologies 19

Page 20: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

What impacts resolution

• Resolution at half height

February 16, 2016 Agilent Technologies 20

Rt - Rt2 1

W1/2

𝑅𝑠 = 2 (𝑅𝑡2 − 𝑅𝑡1)

1.7 (𝑊0.5 1 + 𝑊0.5 2)

We have maximised Pore Volume in

order to give greatest retention time

difference …

… we have optimised Particle Size

and column loading in order to give

sharper peaks (while retaining the

ability to run on 400 bar instruments).

Page 21: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Mobile phase selection

February 16, 2016 Agilent Technologies 22

min2 4 6 8 10 12 14

mAU

0

50

100

150

200

250

300

min2 4 6 8 10 12 14

mAU

0

50

100

150

200

250

4.6 x 300 mm

150 mM Sodium Phosphate, pH 7.0

0.35 mL/min

4.6 x 300 mm

20 mM Tris, 90mM NaCl, pH 8.0

0.35 mL/min

Page 22: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

AdvanceBio SEC columns

• Optimized pore size – 300Å for larger biotherapeutic proteins, mAbs and ADCs

– 130Å covering a wide range of smaller proteins and polypeptides

• Optimized pore volume – Highest pore volume for maximum resolution

• Optimized particle size – 2.7 µm totally porous particles for high efficiency and applicability

from 400 bar to UHPLC

• Optimized column loading – Multiple column dimensions for speed and resolution with

maximum lifetime

• Optimized surface chemistry – Proprietary hydrophilic coating to reduce non-specific interactions

February 16, 2016 Agilent Technologies 23

Page 23: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Characterization and QC

Need more

resolution

Slower flow

rates

Multiple

columns

February 16, 2016 Agilent Technologies 24

Page 24: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Need more resolution

• Resolution at half height

February 16, 2016 Agilent Technologies 25

Rt - Rt2 1

W1/2

𝑅𝑠 = 2 (𝑅𝑡2 − 𝑅𝑡1)

1.7 (𝑊0.5 1 + 𝑊0.5 2)

Page 25: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Column Performance Uridine (small molecule)

120000

125000

130000

135000

140000

145000

150000

155000

160000

165000

170000

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

Pla

tes/

m

Flow Rate (mL/min)

Plates/m

February 16, 2016 Agilent Technologies 26

Page 26: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Column Performance Vitamin B12

100000

110000

120000

130000

140000

150000

160000

170000

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

Pla

tes/

m

Flow Rate (mL/min)

Plates/m

February 16, 2016 Agilent Technologies 27

Page 27: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Column Performance Resolution (BioRad and IgG I9640)

1.30

1.40

1.50

1.60

1.70

1.80

1.90

2.00

2.10

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

Reso

luti

on F

act

or

Flow Rate (mL/min)

Rs IgA/IgG

Rs Ova/Myo

Rs I9640

February 16, 2016 Agilent Technologies 28

Page 28: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Increased sample throughput

February 16, 2016 Agilent Technologies 29

Need more

speed

Shorter 15cm

columns

Faster flow

rates

Page 29: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Initial Conditions

min2 4 6 8 10 12 14 16 18

mAU

0

10

20

30

40

50

6.9

90

8.0

00

8.7

57

10.1

80

11.6

64

15.2

20

February 16, 2016 Agilent Technologies 30

5µm Diol-type SEC column

7.8 x 300 mm

Flow rate 0.8 mL/min

Run time 20 min

Resolution monomer / dimer 1.77

Page 30: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Same flow rate, 15cm column Same resolution, much shorter run time

min1 2 3 4 5 6 7 8

mAU

0

20

40

60

80

100

120

140

2.9

12

3.3

18

3.5

77

4.0

93

4.8

77

7.1

64

February 16, 2016 Agilent Technologies 31

AdvanceBio SEC 300

7.8 x 150 mm

Flow rate 0.8 mL/min

Run time 9 min

Resolution monomer / dimer 1.73

Page 31: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Highest flow rate tested, 15cm column Resolution less than 1.5, but sufficient for rapid screening

min0.5 1 1.5 2 2.5 3 3.5 4 4.5

mAU

0

20

40

60

80

100

120

1.5

58

1.9

13

2.1

91

2.6

09

3.8

19

February 16, 2016 Agilent Technologies 32

AdvanceBio SEC 300

7.8 x 150 mm

Flow rate 1.5 mL/min

Run time 5 min

Resolution monomer / dimer 1.45

Page 32: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Flow rate impact on sample throughput

0

50

100

150

200

250

300

350

400

450

0.0

5.0

10.0

15.0

20.0

25.0

0.8 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0

Sam

ple

Thro

ughput

*

Run T

ime (

min

s)

Flow Rate (mL/min)

Throughput (samples/24h) Run Time

February 16, 2016 Agilent Technologies 33

Page 33: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Increase speed of analysis

min2 4 6 8 10 12 14

Norm.

0

20

40

60

80

100

120

140

February 16, 2016 Agilent Technologies 34

0.5 mL/min

1.0 mL/min

1.5 mL/min

Signals normalised and aligned.

Run time reduced from 12 to 4

minutes

3X sample throughput

Sufficient resolution

AdvanceBio SEC 300Å 7.8 x 150 mm

Page 34: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Reduce laboratory running costs

More to

increase

productivity

Longer column

lifetime

Fewer

columns,

reduced

downtime

February 16, 2016 Agilent Technologies 35

Page 35: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Extended Lifetime

min2 4 6 8 10 12 14

mAU

0

10

20

30

40

February 16, 2016 Agilent Technologies 36

Every 200 injections of IgG I9640 during

extended lifetime experiment (14 days; up to

1200 injections)

Page 36: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Economic Value

February 16, 2016 Agilent Technologies 37

250Å Diol-type, 5µm 7.8 x 300 mm

Page 37: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Economic value calculation …

February 16, 2016 Agilent Technologies 38

250Å Diol-type, 5µm

Page 38: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Multiple sample types

mAbs and next generation biologics

Need more

generic

methods

Reduced

secondary

interactions

Fewer

methods,

better peak

shape

February 16, 2016 Agilent Technologies 39

Page 39: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Difficult Samples Problematical mAbs …

February 16, 2016 Agilent Technologies 40

290Å 3µm

250Å Diol-type, 5µm AdvanceBio SEC 300Å

300Å 3µm

Page 40: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Difficult Samples Antibody Drug Conjugates (ADCs)

February 16, 2016 Agilent Technologies 41

290Å 3µm

250Å Diol-type, 5µm

200Å 1.7µm

AdvanceBio SEC 300Å

Page 41: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Recap

February 16, 2016 Agilent Technologies 42

Need more speed Shorter 15cm columns Faster flow rates

Need more resolution Slower flow rates Multiple columns

Need more generic

methods

Reduced secondary

interactions

Fewer methods, better

peak shape

Page 42: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Column choice - resolution or speed

- requires different column formats

February 16, 2016 Agilent Technologies 43

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0

Flow Rate (mL/min)

Two 7.8 x 300 mm

7.8 x 300 mm

7.8 x 150 mm

Speed Resolution

Page 43: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Separation of protein standards and IgG

using different Agilent HPLC systems

min0 2 4 6 8 10 12 14

Norm.

0

25

50

75

100

125

150

175

200

Agilent 1100 LC System

min2 4 6 8 10 12 14

Norm.

0

25

50

75

100

125

150

175

200

Agilent 1260 Bio-inert LC System

min2 4 6 8 10 12 14

Norm.

0

25

50

75

100

125

150

175

Agilent 1290 Infinity LC System

Conditions

Eluent 150 mM Sodium phosphate buffer, pH 7.0

Flow rate 1.0 mL/min (7.8 mm ID columns) or 0.35 mL/min (4.6 mm ID columns)

Temperature Ambient

Sample 1 mg/mL protein concentration

Instrument Agilent 1100 HPLC instrument (legacy, 400 bar)

1260 Infinity Quaternary Bio-inert (600 bar)

1290 Infinity Binary LC with G1315D DAD and Bio-inert flow cell (1200 bar)

Wavelength 220 nm

February 16, 2016 Agilent Technologies 44

Page 44: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Agilent AdvanceBio SEC Ensuring reliability

February 16, 2016 Agilent Technologies 45

min0 2 4 6 8 10 12 14 16

mAU

0

10

20

30

40

50

60

70

Injection #1

Injection #1200

Injection #800

Injection #400

Injection Rs

#1 2.16 (after 0 days)

#400 2.16 (after 4 days)

#800 2.20 (after 8 days)

#1200 2.19 (after 12 days)

Page 45: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Effect of analysis temperature of on monomer /

dimer / aggregate content of γ-Globulin

February 16, 2016 Agilent Technologies 46

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

65.0%

67.0%

69.0%

71.0%

73.0%

75.0%

77.0%

79.0%

81.0%

83.0%

85.0%

15°C 20°C 25°C 30°C 35°C 40°C 45°C 50°C 55°C

Aggs

and D

imer

Are

a %

Monom

er

Are

a %

Injection Number

Monomer% Aggs% Dimer%

Page 46: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Control of temperature

February 16, 2016 Agilent Technologies 47

min4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

mAU

0

25

50

75

100

125

150

175

200

225

15 °C 167.5 bar

Rs 1.758

Monomer Area% 74.8%

25 °C 140.6 bar

Rs 1.825

Monomer Area% 73.9%

Page 47: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Column dimensions

February 16, 2016 Agilent Technologies 48

4.6 or 7.8 x 300 mm 4.6 or 7.8 x 150 mm

Two 4.6 or 7.8 x 300 mm

min5 10 15 20 25

mAU

0

10

20

30

40

50

60

70

min5 10 15 20 25

mAU

0

10

20

30

40

50

min2 4 6 8 10 12 14

mAU

0

25

50

75

100

125

150

175

min2 4 6 8 10 12 14

mAU

0

5

10

15

20

25

30

35

40

min2 4 6 8 10 12 14

mAU

0

25

50

75

100

125

150

175

min2 4 6 8 10 12 14

mAU

0

10

20

30

40

50

60

70

80

min1 2 3 4 5 6 7

mAU

0

50

100

150

200

250

min1 2 3 4 5 6 7

mAU

0

20

40

60

80

100

120

Page 48: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Robustness or sensitivity

February 16, 2016 Agilent Technologies 49

min2 4 6 8 10 12 14

mAU

0

25

50

75

100

125

150

175

200

min2 4 6 8 10 12 14

mAU

0

25

50

75

100

125

150

175

200

4.6 mm ID (1260 Bio-inert)

Flow rate 0.35 mL/min

Inj vol 2 µL

7.8 mm ID (1260 Bio-inert)

Flow rate 1.0 mL/min

Inj vol 6 µL

Pressure 174.4 bar

Rs 1.91

Rs 2.23

Pressure 154.1 bar

Rs 1.82

Rs 2.12

Page 49: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Resolution 150 mm vs 300 mm vs 2 x 300 mm

min5 10 15 20 25

mAU

0

20

40

60

80

100

120

min5 10 15 20 25

mAU

0

5

10

15

20

25

30

35

40

min5 10 15 20 25

mAU

0

10

20

30

40

50

February 16, 2016 Agilent Technologies 50

7.8 x 150 mm

Pressure 102.3 bar

Rs 1.63

7.8 x 300 mm

Pressure 188.7 bar

Rs 2.06

2 x 7.8 x 300 mm

Pressure 330.1 bar

Rs 2.53

Page 50: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

• For resolution use longer column lengths 300 mm

– Reduce flow rate

• For speed use shorter columns 150 mm

– Increase flow rate

• Generic methods for wide range of sample types

– Use an innovative SEC column that has minimal

non-specific interactions

Summary

February 16, 2016 Agilent Technologies 51

The AdvanceBio SEC columns

provide solutions for all the above

Page 51: Optimizing Quantification of mAb and ADC Aggregates · Detecting and quantifying mAb aggregation February 16, 2016 Agilent Technologies 11 . Detecting and quantifying mAb aggregation

Thank you !

February 16, 2016 Agilent Technologies 52