A Platform Approach to Preformulation Development for

Antibody Products

Tim Kelly, Ph.D.Vice President, Biopharmaceutical Development

KBI Biopharma, Inc.

A Typical Antibody Preformulation Project• IgG MAb has emerged from Research into

Development

• Short term goal is IND submission and initiation of Phase I Clinical trials

• MAb will be administered IV for early clinical studies, but is expected to require SC administration for late stage clinical and commercial use

• Have basic chemical information about MAb (sequence, MW, pI, etc), but little / no stability data

“Platform” Preformulation for MAbs• Not a series of pre-defined formulation buffers that all

MAbs are wedged into regardless of individual properties

• A streamlined, but rational process development approach that takes advantage of “platform-able”biophysical and analytical techniques

• Takes into account certain formulation considerations that commonly affect MAbs

• Low concentration versus high concentration• Surfactants

MAb Preformulation Workflow• “Research Phase”

• Biophysical Screening

• Solubility Evaluation

• DOE & Accelerated Stability

• Forced Degradation

Identify critical factors, Eliminate non-critical factors

MAb Preformulation Workflow / Timeline

Preformulation “Research Phase”• Basic Chemical Information

• pI is most critical

• Desired Formulation Type• Liquid versus Lyophilized Powder

• Route of Administration• IV, SC, IM, etc.

Preformulation “Research Phase”• Buffer & Formulation pH Selection

• Identify suitable buffers based on pKa relative to pI• Typically formulate in acidic or slightly acidic buffers, based

on high pI’s of MAbs» Acetate, Succinate, Histidine, Citrate, Phosphate

• Excipient Selection• Polyols and Sugars: Solubility, Thermal Stability, Chemical

Stability• Salt: Solubility, Ionic strength, Osmolality• Amino Acids: Solubility, Viscosity • Surfactants: Aggregates and Particulates

Initial Biophysical Screening

• To limit the number runs to be evaluated as a part of the DOE study

• Utilize a combination of biophysical tools• DSC: Thermal/conformational stability• DLS: Aggregation and polydispersity• FTIR: Secondary structure evaluation• Circular Dicroism: Secondary structure evaluation

• Take advantage of orthogonal techniques to make decisions about formulation factors

Thermal Stability via DSC• Differential Scanning Calorimetry (DSC) measures the

differential absorption of heat by protein and buffer samples

• Endothermic transitions such as protein unfolding result in higher absorption of heat by protein sample relative to the buffer sample

• The apparent mid-point of endothermic transitions correspond to Tm, where Tm is defined as the temperature at which protein is equally distributed in the folded and unfolded forms

• Higher Tm implies higher thermal/conformational stability of the molecule

• Unfolding or partial unfolding can lead to aggregation

Size Measurements via DLS• Dynamic Light Scattering measurements rely on the random

(Brownian) motion of molecules under constant temperature conditions

• Larger molecules move more slowly relative to the smaller molecules

• The correlation between scattered light from multiple molecules is measured as a function of time

• If the sample viscosity is known, the molecule size can be estimated based on DLS data

• DLS data can be used to estimate the extent of aggregation or degradation

• Polydispersity Index values (PDI) can be used to estimate the width of size distribution for various species.

Effect of Excipients on Thermal Stability

20 30 40 50 60 70 80 90 100 110 120

-80

-60

-40

-20

0

20

40

60

80

100

With NaCl With Sucrose

Cp

(kca

l/mol

e/o C

)

Temperature (oC)

69.8 and 77.5Sucrose

66.3 and 75.4NaCl

Apparent Tm values (ºC)Excipient

Effect of Excipients on Polydispersity

0

5

10

15

0.1 1 10 100 1000 10000

Inte

nsity

(%)

Size (d.nm)

Size Distribution by Intensity

Record 54: With NaCl Record 55: With Sucrose

56

73

% Monomer

0.65315.0Sucrose

0.38412.7NaCl

PDIMeasured Size(nm)

Excipient

Effect of Excipients on Thermal Stability

20 30 40 50 60 70 80 90 100 110 120

-60

-40

-20

0

20

40

With Sorbitol With Sucrose With NaCl

Cp

(kca

l/mol

e/o C

)

Temperature (oC)

60.6Sorbitol

59.1Sucrose

60.6NaCl

Apparent Tm1 (ºC)Excipient

Effect of Excipients on Polydispersity

0

5

10

15

20

25

0.1 1 10 100 1000 10000

Inte

nsity

(%)

Size (d.nm)

Size Distribution by Intensity

Record 36: With Sorbitol Record 37: With Sucrose Record 38: w ith NaCl

0.2988915.6Sucrose

98100

% Monomer

0.18514.3Sorbitol0.02111.7NaCl

PDIMeasured Size(nm)

Excipient

Biophysical Screening Data - DSCThermal Transitions as a

Function of Buffer Type & Excipient

55

60

65

70

75

None Sodium Chloride Sorbitol Sucrose

T m1

Acetate Histidine Phosphate Succinate

• Able to rank buffers & excipient type• Buffer ranking: phosphate > succinate/histidine >>acetate• Excipient ranking: polyol or disaccharide best, NaCl worst

• Results typically observed:• Organic acids/amino acids best• Polyols and disaccharides often used as excipients

Sucrose

Sorbitol

Sodium Chloride

NoneSuccinate

Sucrose

Sorbitol

Sodium Chloride

NonePhosphate

Sucrose

Sorbitol

Sodium Chloride

NoneHistidine

Sucrose

Sorbitol

Sodium Chloride

NoneAcetate

ExcipientBuffer type

Solubility Evaluation

• Goal from these activities is to rule out categorical factors for follow-on DOE

190-220NaCl, Sucrose, or Sorbitol

190None6.8Phosphate

160-220NaCl, Sucrose, or Sorbitol

220None6.0Histidine

220-250NaCl, Sucrose, or Sorbitol

230None5.5Succinate

220-250NaCl, Sucrose, or Sorbitol

250None4.5Acetate

Conc (mg/mL)ExcipientpHBuffer

Types of Designs Typically Used in Drug Development

• Factorial or Fractional Factorial• Screening design

» Main effects/interactions» Linear model with / without curvature check

• Response Surface• Process / Formulation optimization

» Will fit quadratic surface

• Specialty • Placket-Burman – Robustness design• D-optimal – Handles categorical factors in fewer runs

Basic 2-Level Factorial Design

• May use a series of designs to evaluate different buffers or categorical factors

• Each factor (k) varied over 2 levels (center points actually add a 3rd level)

• Minimum of 3 independently prepared center points

• Provide estimate of error• Also provide information on curvature

• Numeric data are key – try and avoid qualitative/semi-quantitative assays

• DSC fits well in this approach• SDS-PAGE (replace with SDS-CGE)• IEF (replace with cIEF)

Number of runs:

N = 2k + center pointsi.e., for 3 factor design,8 + 3 = 11 runs

Typical RSM Design (Central Composite)

• Response surface designs:• Designed for process (or formulation)

optimization• Core design is factorial• “Star” or axial points to increase ability to

detect an effect from a particular factor• Good granularity at the center of the

design• Will fit quadratic surface• 4 (or more) center points for estimation of

error

The DOE• Individually developed for each MAb, based

on formulation goals and results of biophysical screening and solubility evaluation

• Keep buffer concentration constant within a range conferring sufficient buffering capacity

• Buffer concentration (assuming sufficient capacity) is rarely a significant factor affecting MAb stability

The DOE• Perform DOE at MAb concentration intended for IV

administration (~10-30 mg/mL)

• Prepare additional center point formulations at concentrations relevant for SC (~100-250 mg/mL, based on solubility evaluation)

• “Off-Design”

• Prepare additional center point formulations with and without surfactant

• Or, perform forced agitation & freeze-thaw studies in parallel with and without surfactant

The DOE• Perform selected biophysical techniques on

candidates at Time Zero• DSC, DLS, FTIR

• Set stress temperature based on thermal properties of MAb (first transition temperature observed via DSC)

• Allows maximum stress on molecule without unfolding• Particularly important for MAbs because of high thermal

stability• Typically ranges from 45-55°C

• Place candidate formulations on accelerated stability at 5°C and stress temperature

• Perform stability-indicating analytical methods on stressed samples and 5°C controls (typically 4 week incubation)

The DOE• Example Design

Assays Used to Support DOE

Concentration, Soluble/insoluble aggregatesA280 and A320

T = 4 weeks

Time Zero

Structural stabilityFTIR*

Aggregation, polydispersityDLS

Aggregation / degradationSEC-HPLC

Charge variants, deamidationCEX-HPLC

Aggregation / degradationSDS-PAGE / SDS-CGE*

Thermal / conformational stabilityDSC

Charge variantsIEF / cIEF*

PurposeAssay

Include Potency Assay if available* Perform on Select Candidate Formulations

Data Quality from DSC

• Currently use Capillary DSC:

• Baselines/baseline stability greatly improved

• Permits qualitative assessment of early unfolding events

• Precision is excellent» <0.5% for centerpoint

formulations » (n = 6, individual preps)

Buffer screen for MAbEffect of 4 buffers/variety of pHs

Center-point formulations

Tm1 for Centerpoint Formulations

Time 0 Time 4 wks66.466.566.666.766.866.967.067.167.267.367.467.5

T m1

Number of valuesMinimum25% PercentileMedian75% PercentileMaximum

MeanStd. DeviationStd. Error

Lower 95% CIUpper 95% CI

Time 0666.5566.6266.8966.9766.99

66.820.17170.07008

66.6467.00

Time 4 wks666.5366.5766.9567.2267.30

66.910.30280.1236

66.5967.23

Tm2 for Centerpoint Formulations

Time 0 Time 4 wks

80.4

80.5

80.6

80.7

80.8

80.9

81.0

81.1

T m2

Number of valuesMinimum25% PercentileMedian75% PercentileMaximum

MeanStd. DeviationStd. Error

Lower 95% CIUpper 95% CI

Time 0680.4280.4980.7780.8480.86

80.700.17300.07062

80.5280.88

Time 4 wks680.4180.4580.8480.9781.02

80.750.25010.1021

80.4981.01

DOE Results– DSC Data Quality• DOE requires tight statistics to identify effects• Centerpoints are used to assess experimental error• Results are shown for T=0 & 4 wks

Stability-Indicating Analytical Methods for Preformulation DOE

• SEC-HPLC• Tosoh TSKgel Column• Modifications to Mobile Phase composition if necessary to optimize peak

shape and HMW species recovery• Evaluate change in % monomer and/or % HMW species for stressed

candidate formulations versus controls

• CEX-HPLC• Dionex Propac Column• Phosphate/Salt Mobile Phases• Optimize gradient and/or MP pH based on MAb pI• Quantify acidic and basic variants together, compare stressed

candidates versus controls based on three values:» % MP, % acidic, % basic

Stability-Indicating Analytical Methods for Preformulation DOE

• cIEF• Beckman or Convergent Systems generally robust• Quantify acidic and basic variants together, compare stressed

candidates versus controls based on three values:» % MP, % acidic, % basic

SEC-HPLC

SEC-HPLC• Time Zero, Formulation # 7

SEC-HPLC• T= 1 Month, Formulation # 7

CEX-HPLC

CEX-HPLC• Time Zero, Formulation # 7

CEX-HPLC• T= 1 Month, Formulation # 7

cIEF

cIEF Results• Time Zero, Formulation # 7

cIEF Results• T = 1 Month, Formulation # 7

Effect of Buffer Type on MAb Stability

• DOE Summary• Two fractional factorial designs• Selected to span a wide range of

pH conditions• MAb concentrated to >200

mg/mL; 40oC for 4 weeks• Full panel of analytics performed:

• SEC showed effect of buffer/pH on HMW species

• Phosphate buffer: HMW increases with increasing pH

• Histidine buffer: HMW stable from pH 6 - 7

Design-Expert® Software

HMW species

Design Points

D1 HistidineD2 Phosphate

X1 = A: pHX2 = D: Buffer Type

Actual FactorsB: Buffer Conc = 35.00C: NaCl Conc = 75.00

D: Buffer Type

6.00 6.25 6.50 6.75 7.00

Interaction

A: pH

HM

W s

peci

es

0.4

1.15

1.9

2.65

3.4

2

2

Statistical Significance vs. Operational Significance

Design-Expert® Softw are

Tm1

Design Points

X1 = A: pH

Actual FactorsB: Buffer Concentration = 35.00C: Excipient Concentration = 115.00

5.25 5.63 6.00 6.38 6.75

58

61.5

65

68.5

72

A: pH

Tm1

One Factor

4343

Design-Expert® Softw are

Tm1

Design Points

X1 = B: Buffer Concentration

Actual FactorsA: pH = 6.00C: Excipient Concentration = 115.00

20.00 27.50 35.00 42.50 50.00

58

61.5

65

68.5

72

B: Buffer Concentration

Tm1

One Factor

4343

pH has an effect on thermal stability Buffer concentration has almost no effect on stability (~1/50th the effect of pH)

Assays/Inputs Used for PreformulationAssay Purpose Utility

DSC Thermal/conformational stability HighSEC Aggregates HighCEX Charge variants Medium - HighA320/A280 Soluble/insoluble aggregates HighIntact Mass LC/MS Chemical degradants Medium - HighBioAssay/ELISA Activity VariesSDS-Page Covalent aggregates, degradants Low - MediumIEF Charge variants Low - Medium

These data are easier to handle…….than these!

Formulation Selection Balances All Assays

Design-Expert® Software

Tm171.14

58.72

X1 = A: pHX2 = B: Buffer Conc

Actual FactorC: Excipient Conc = 115.00

5.25

5.63

6.00

6.38

6.75

20.00

27.50

35.00

42.50

50.00

61

63.75

66.5

69.25

72

Tm

1

A: pH B: Buffer Conc

Design-Expert® Software

SEC mon89.397

38.1047

X1 = A: pHX2 = B: Buffer Conc

Actual FactorC: Excipient Conc = 115.00

5.25

5.63

6.00

6.38

6.75

20.00

27.50

35.00

42.50

50.00

59

67.25

75.5

83.75

92

SE

C m

on

A: pH B: Buffer Conc

DSC: Thermal stability increases with increasing pH

SEC: Purity by SEC begins to decrease as pH approaches 7

Selection of Final Formulation

• Selection of final formulation typically balances:

• Thermal stability• Aggregation• Chemical stability• Activity

• Ideally, can use numeric data from preformulation studies to create a response surface

0

5.25

5.63

6.00

6.38

6.75

20.00

27.50

35.00

42.50

50.00

0.330

0.473

0.615

0.758

0.900

Des

irabi

lity

A: pH B: Buffer conc

Forced Degradation• Performed on 1-2 lead candidate formulations, based

on Preformulation results

Conclusions• Critical aspects of MAb Preformulation are “platform-

able”• Biophysical screening to reduce factors• Analytical methods that are readily applicable to diverse MAbs

• Individually developed DOE’s are more likely to result in optimized design space compared to menu of pre-defined formulation buffer recipes

• Rely on quantitative, orthogonal methods• Evaluate MAb-specific considerations in parallel with

DOE if warranted (i.e., “off-design”)• Strive for conditions that balance thermal, chemical,

physical, and biological stability

Acknowledgements

• Alex Tracy, PhD, Director, Biopharmaceutical Development

• Pooja Arora, PhD, Scientist I, Formulation Development