Improving Physicochemical Properties of Biopharmaceutical Drug Candidates

David Litzinger, PhDDirector, Pharmaceutical SciencesAmylin Pharmaceuticals, Inc.

PEGS ConferenceMay 20, 2010Boston, MA

Small Molecules

<500 Da

Peptides1-6 kDa

Proteins15-150 kDa

High

Medium

Low

Negligible

Slight

Significant

Drug Platform(typical MW)

Analog Evaluationin Drug Development

ImmunogenicityConcern

Analogs in Drug DevelopmentComparisons Across Platforms

Drug Substance

Endogenous Counterpart

Mutations Result

pramlintide amylin • Three proline substitutions

• Prevents insoluble fibrous aggregate formation• Based on rat amylin (has the three corresponding prolines, is not amyloidogenic)

Insulin glargine

insulin • Two Arg added to B chain (shifts pI from 5.4 to 6.7)• Gly to Asn at A21

• Formulated as a solution at acidic pH• Following injection, comes out of solution at physiological pH to form crystals that slowly dissolve

Insulin lispro insulin • Lys and Pro at the C-terminal end of the B-chain reversed

• Blocks the formation of insulin dimers and hexamers• Rapid acting insulin

Insulin aspart

insulin • Pro to Asp at B28 • Increased charge repulsion prevents the formation of hexamers• Rapid acting insulin

Insulin glulisine

insulin • Asn to Lys at B3 • Lys to Glu at B29

• Rapid acting insulin

Peptide Analogs as Drug SubstancesExamples Related to Aggregation

Chemical Modification

– Polymer conjugation

Peptide and Protein OptimizationExample Options for Improving Physical Stability

Mutational

– Changing the pI

– Decrease hydrophobicity

– Increase hydrophilicity

– Increase net charge

– Mutations based on superior properties in alternate species

Approaches to Improving Physical Stability*

* More that one approach can be combined

√

√

√

√

√

√

√

√

√

√

> Glucose-dependent Insulinotropic Polypeptide (GIP)– 42-amino acid hormone synthesized and secreted from intestinal K-cells– Integral role in regulating insulin secretion and response– Amylin Pharmaceuticals currently investigating GIP as a possible

mono- or combination therapy for Type 2 Diabetes Mellitus

– Native GIP rapidly inactivated by dipeptidyl peptidase-IV (DPP-IV) and has a very short half-life– Development of GIP analogs challenging due to poor solubility

> Development Challenges

– G1 effort addressed DPP-IV metabolism, optimized activity– G2 GIP analogs identified and evaluated for improved solubility

• In Silico modeling used for primary sequences analysis • pH-solubility profile, physical and chemical stability were screened• CD used to monitor secondary structure

> Second Generation Effort (G2)

Glucose-Dependent Insulinotropic PolypeptideExample of Analog Evaluation in Drug Development

2nd Round of Screening

Note: Biological Activity- Receptor binding, mouse OGTT, mouse GL, DOA by rat IVGTT, plasma stability, HbA1c in ob/ob mice Physical Stability- Aggregation, precipitation, solubility

Generation Peptide ID# Metabolism Biological

ActivityPhysical Stability

P Human GIP (1-42) X X

G1 G1-A xG1 G1-B xG2 G2-C G2 G2-D

Native GIP (1-42) G1 Analogs G2 Analogs

GIP Drug DevelopmentHistory and Efforts to Identify Alternative GIP Analogs

Generation Peptide ID# Primary Sequence MW

P Human GIP YAEGTFISDYSIAMDKIHQQDFVNWLLAQKGKKNDWKHNITQ-OH 4983.6

G1 G1-A YaEGTFISDYSIAMDKIHQQDFVNWLLAQKPSSGAPPPS-NH2 4309.8

G1 G1-B YaEGTFISDYSIAMDKIHQQDFVNWLLAQKPSSGAPPNS-NH2 4326.8

G2 G2-C YaEGTFISDYSIALEKIRQQEFVNWLLAQKPSSGAPKPS-NH2 4369.9

G2 G2-D YaEGTFISDYSIALEKIRQQEFVNWLLAQKPSSGAPPKSK-NH2 4498.1

> Sequences ranked according to In Silico modeling and assessment tools– Tango2 – Protein aggregation prediction model based on TANGO algorithm of physico-chemical

principles of b-sheet formation

– In Silico Tool – Primary sequence assessment and pharmaceutical properties predictor created in-house

• GRAVY– Grand average of hydropathicity: GRAVY value, hydrophobicity ( solubility)• Peptide Charge Calculator – Computes theoretical net charge on peptide from composition of

ionizable residues

> Compounds synthesized and evaluated

Underlined residues denote substitutions; Red - potentially labile residues; Blue – C-terminal end modification

GIP Analog ScreeningPrimary Sequence Ranking by In Silico Tools

> G2 analogs showed improved properties over G1 analogs:• Higher pI• Good solubility at acidic pH

> Labile Residues:• D – potential aspartic acid isomerization at pH 4• M, W – potential site for oxidation• N, Q – potential deamidation

• Fair/Average solubility at neutral pH• Highly charged at pH 4 compared to pH 7

Calculated

pI

pH 4

Solubility

pH 7

Solubility

Net Charge

pH 4

Net Charge

pH 7

Overall

StabilityPotential Labile Residues

Human GIP

(1-42)-0.80 -7.00 7.5 Good

Fair Average

+ 5.68 + 0.39Fair

AverageD(4), M(1), N(3), Q(4), W (2)

G1-A -0.37 -7.10 5.8Fair

AverageFair

Average+ 2.86 - 0.85 Good D(3), M(1), N(1), Q(3), W (1)

G1-B -0.42 -6.78 5.8Fair

AverageFair

Average+ 2.86 - 0.85 Good D(3), M(1), N(2), Q(3), W (1)

G2-C -0.41 -13.89 8.6 GoodFair

Average+ 3.86 + 0.91 Good D(1), N(1), Q(3), W (1)

G2-D -0.50 -14.57 9.2 GoodFair

Average+ 4.86 + 1.91 Good D(1), N(1), Q(3), W (1)

Chemical Stability

ID #Hydrophilicity (Gravy Score)

Aggregation (Tango 2 Score)

Solubility

GIP Analog ScreeningIn Silico Pharmaceutical Property Assessments

> G2 analogs show improved solubility profile compared to the G1 analogs

ID #Solubility at Formulated

pH

Hydrophilicity (Gravy Score)

Aggregation (Tango 2 Score)

Measured pI

Calculated pI

Human GIP (1-42) nd -0.80 -7.00 6.7 7.5

G1-A < 1 mg/ml -0.37 -7.10 5.8 5.8

G1-B ~ 1 mg/ml -0.42 -6.78 4.7 5.8

G2-C > 5 mg/ml -0.41 -13.89 8.4 8.6

G2-D > 5 mg/ml -0.50 -14.57 9.0 9.2Note: nd – not determined

Measured Solubility ResultsG2 Analogs Have Improved Solubility

> G2 analogs proved to have the most physically stable profile.

ID #pH Buffer 0 1 25.0 30 mM Acetate6.0 30 mM Phosphate6.0 30 mM Histidine6.5 30 mM Phosphate7.0 30 mM Phosphate

5.0 30 mM Acetate6.0 30 mM Phosphate6.0 30 mM Histidine6.5 30 mM Phosphate7.0 30 mM Phosphate

6.0 10 mM Phosphate6.5 10 mM Phosphate6.5 10 mM Histidine7.0 10 mM Phosphate7.0 30 mM Phosphate7.0 10 mM Histidine7.5 10 mM Phosphate

5.0 10 mM Acetate5.5 10 mM Acetate6.0 10 mM Histidine6.5 10 mM Histidine7.0 10 mM Histidine7.5 10 mM Histidine

G1-A

G1-B

G2-C

G2-D

Temperature at 25°C Time Point (Weeks)

Clear, Colorless

Slight Precipitation, Aggregation

Moderate to Severe Precipitation, Aggregation

Formulation ScreeningG2 Analogs Have Improved Physical Stability

Visual Analysis

1 mg/mL concentration;No agitation

-20000

-15000

-10000

-5000

0

5000

10000

15000

20000

25000

190 200 210 220 230 240 250 260Wavelength (nm)

Mea

n Re

sidu

e El

liptic

ity (M

RE)

(mde

g*(c

m2/

dmol

)

G1-A pH 6 Phosphate

G1-B pH 6 Phosphate

G2-C pH 4 Acetate

G2-C pH 7 Phosphate

G2-D pH 4 Acetate

G2-D pH 7 Phosphate

Structure (l nm)

α-helix 208, 220

β-sheet 215

Random Coil 195

> G2 analogs show greater α-helical content– Correlates with less aggregation– Similar 2° structure at both pH 4 & 7

Secondary Structure AnalysisEvaluation of GIP Analogs

Far UV CDFar UV CD

> G1 analogs demonstrated improved biological efficacy and longer duration of action compared to native GIP, but had poor physical stability

> G2 analogs showed both improved efficacy and physical stability – Experimental results correlated well with their higher net charge and more negative GRAVY

scores predicted in silico. – At 1 mg/mL concentrations were physically and chemically stable under the tested conditions

with little to no visible aggregation. 

– Secondary structure is predominantly α-helical in liquid state (pH 4.0 and pH 7.0)

GIP Analog OptimizationConclusions

• 16.2 kd 147 amino acids, (native leptin 146 AA)• Isoelectric point 6.1• Single disulfide bond• No free cysteines• Limited solubility at neutral pH, 2-3 mg/mL, higher at lower pH• Four helix bundle tertiary structure

MetreleptinCompound Properties and Obesity Treatment Approaches

> Amgen pursued leptin monotherapy as a treatment for obesity– High dose, up to 0.3 mg/kg (~30 mg per injection)– Heymsfield et al. (1999) JAMA

> Amylin is evaluating leptin in combination with pramlintide for treatment of obesity

– Lower dose– Roth et al. (2008) PNAS

MetreleptinCharge Profile

> Calculated pI= 6.1 > Suggests high solubility at low pH, and low solubility at neutral pH

Charge calculator/pI finder by Gale Rhodeshttp://spdbv.vital-it.ch/TheMolecularLevel/Goodies/Goodies.html

Net Charge of Metreleptin vs pH

> Murine leptin is more soluble than human leptin at neutral pH– 43 mg/mL for murine leptin – 31 mg/mL for W100Q/W138Q analog

MetreleptinSolubility Profile

Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.

○ leptin solubility

▲ reversibility of precipitation

> Solubility of human leptin– At low pH is high

> 70 mg/mL at pH 4– At neutral pH is low

2-3 mg/mL

> Precipitation at neutral pH is essentially irreversible

MVPIQKVQDDMVPIQKVQDD

TKTLIKTIVTTKTLIKTIVT

RINDISHTQSRINDISHTQS

VSSKQKVTGLVSAKQRVTGL

DFIPGLHPILDFIPGLHPIL

TLSKMDQTLASLSKMDQTLA

SRNVIQISNDSQNVLQIAND

LENLRDLLHVLENLRDLLHL

LAFSKSCHLPLAFSKSCSLP

WASGLETLDSQTSGLQKPES

LGGVLEASGYLDGVLEASLY

STEVVALSRLSTEVVALSRL

QGSLQDMLWQQGSLQD I LQQ

LDLSPGCLDVSPEC

0 10 20 30

40 6050 70

130

9080

120

110100

VYQQILTSMPVYQQVLTSLP

140

HUMAN:MURINE:

HUMAN:MURINE:

HUMAN:MURINE:

HUMAN:MURINE:

> Comparison of human and murine leptin sequences

Residues that differ between the human and murine sequences are in red.Note that the first methionine residue associated with E. coli production is not counted.

– Differ at 22 sites– Sequence differences of particular significance in solubility/aggregation properties

Human and Murine LeptinAmino Acid Sequence Comparison

Trp 138

> Surface modeling shows region around Trp 138 has potential role in aggregation– Low electrostatic potential– High lipophilicity

Electrostatic SurfaceRed = Basic (+) Blue = Acidic(-)

Hydrophobicity SurfaceBrown = Lipophilic

Blue = Hydrophilic, charged

MetreleptinSurface Modeling

Benchware3DExplorer (Tripos)

Human LeptinEvidence for Leptin Conformational Transition with pH Change

● human

○ murine

> Suggests a folding intermediate with increased hydrophobicity populated at pH 4-5> May result in the formation of soluble multimeric species under acidic conditions

> Increased ANS fluorescence at pH 4 to 5

– Not observed for murine leptin

Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.

Human LeptinLow pH Aggregation and Relation to Neutral pH Precipitation

Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.

▲ human, % aggregates, pH 4

● human, % precipitation, pH 7

∆ murine, % aggregates, pH 4

○ murine, % precipitation, pH 7

Initial concentration at low pH varied Precipitation induced by diluting into neutral pH buffer

Inset: human leptin multimers formedat 50 mg/mL, pH 4:

• diluted to 5 mg/mL, pH 4 • diluted again into pH 7

Forms multimers at low pH Precipitation correlates with multimer formation Multimers formed at acidic pH dissociate upon dilution in acid pH Precipitation at pH 7 decreases with multimer dissociation Did NOT form multimers and did not precipitate

Human leptin

Murine leptin

N I U

Iassoc precipitation

N: native stateI: folding intermediateU: unfolded conformerIassoc: folding intermediate self associated into a soluble multimer

Human LeptinProposed Aggregation Mechanism

Murine Leptin

Precipitation not observed*

Multimers notobserved*

Increased hydrophobicity atacidic pH not observed**

* Under conditions in which human leptin precipitatedand formed multimers.

** As observed for human leptin in ANS studies.

,

Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.

Chemical Modification Example Succinylation

O

O

Protein-NH2 + Protein-N-C-CH2-CH2-C-O-

H2

O O

> Reaction at pH 7.0– 5-fold molar excess of succinic anhydride– 2-16 hours at 4oC

> Purification by ion exchange chromatography– 45-47% final yield

> Site-specific conjugation to N-terminus– Endoproteinase Lys-C – Peptides resolved by RP-HPLC

• Succ-(M1-K6): Succinylated N-terminal peptide

• M1-K6: N-terminal peptide

From Gegg et al. US Patent 6,420,340

O

Diethylenetriamine-pentaacetic acid (DTPA)

Ethylenediaminetetra-acetic acid (EDTA)

N-R-N O

O

O

O

O

H2O (1) or H2N-Protein (2)H2N-Protein

O

O

N-ProteinH

O

O

O

O

N-ProteinH

O

O

N-ProteinH

N-R-N

Monomer conjugate Dimer conjugate

N-R-N

-CH2-CH2-N-CH2CH2-

COOH

H+

CH2

-CH2-CH2-R =

R =

From Gegg et al. US Patent 6,420,340

Two Related ExamplesDTPA and EDTA

(1) (2)

O

OHOHHO HOOH

Sample Maximum Solubility in PBS* (mg/mL)

Unmodified leptinSuccinyl-leptinDTPA-leptin monomerEDTA-leptin monomer

3.28.431.659.9

N/A **-0.7 **Not reportedNot reported

** Leptin pI = 6.1; succinyl-leptin estimated to be 5.4* pH = 7.0

Change in pI

From Gegg et al. US Patent 6,420,340

Succinylation and Related ModificationsImpact on pI and Solubility of Metreleptin

> Conjugations with acidic moieties to the N-terminus lower pI and increase solubility at neutral pH

Acetate buffer, pH 4.0

Unmodified leptin(in acetate buffer, pH 4.0)

PBS buffer, pH 7.5

Succinyl-leptin (in PBS, pH 7.5)

SampleConcentration

(mg/mL)Injection volume

(mL) Precipitation

000505050000505050

202020202020202020202020

000441.500000.50

Score system: 0 Normal, 0.5-1 minimal change, 1.5-2 mild change, 2.5-3 moderate change, 3.5-4 marked change, 4.5-5 massive change

> Three mice dosed per sample> Tissues sections from the injection sites examined histologically

From Gegg et al. US Patent 6,420,340

SuccinylationReduces Injection Site Precipitation of Metreleptin

– Normal mice dosed s.c. daily, 10 mg/kg– Results shown as % weight-loss relative to buffer control

> Similar activity in vivo for conjugates relative to unmodified leptin

From Gegg et al. US Patent 6,420,340

Succinylated and Related Metreleptin ConjugatesRetain In Vivo Activity

> Why PEGylation?

– Slow clearance/maintain circulating concentrations/reduce dose frequency– Increase solubility– Reduce aggregation– Reduce proteolysis– Reduce immunogenicity– In several approved products

> What is PEGylation?– Covalent attachment of poly(ethylene glycol) (PEG)– Example PEGylation reagent:

CH3O-(CH2-CH2-O)n-CH2-CH2-XMethoxy cap Reactive group

Polymer Conjugation ExamplePEGylation

> Why site-directed PEGylation?– Optimally preserve biological activity– Homogenous product/consistent lot-to-lot activity

Protein-OOC

NeH3+

NH2

NeH3+

Protein-OOC

NeH3+

NH-CH2-PEG

NeH3+

H-C-PEG

O

NaCNBH3

– Low pH selectively protonates lysine e-amino groups– N-terminal amino group remains unprotonated and reactive– Reductive alkylation specific to the N-terminus

Example: Neulasta® (20kDa PEG-rhGCSF)

Site-Directed PEGylationN-Terminal Site-Specific Example

> Under conditions in which GCSF rapidly precipitated, 20kDa PEG-GCSF remained completely soluble

> PEG-GCSF remained clear and showed no turbidity, unlike GCSF> Free PEG was unable to prevent GCSF precipitation

From Rajan, R.S. et al. (2006) Protein Science

Effect of PEGylation on SolubilityPEG-GCSF Has Improved Solubility

Samples formulated at 5 mg/mL in phosphate buffer, pH 6.9 and incubated at 37oC

> Significant loss of GCSF monomer due to conversion into insoluble forms

> 20K PEG-GCSF accumulated into soluble, higher order multimeric forms eluting in the void volume

* Aliquots analyzed after 72 h of incubation at neutral pH and 37oC

From Rajan, R.S. et al. (2006) Protein Science

PEG-GCSF Forms Soluble AggregatesAnalysis by Size-Exclusion Chromatography

– Resolubilized GCSF and PEG-GCSF soluble aggregates comparison • Both included a mixture of monomer, dimers, trimers, and higher order multimers• Multimers in both cases were covalent, disulfide-linked• Similar extent of covalent formation

> PEGylation does not alter the linkages or heterogeneity of the aggregates

> PEGylation does not alter the helix-to-sheet transition that accompanies aggregation

– GCSF and PEG-GCSF showed similar starting FTIR spectral profiles as well as temperature-induced conversion to b-sheet – The GCSF precipitate and the PEG-GCSF soluble aggregate showed similar extent of b-sheet content by FTIR analysis

> PEGylation confers improved solvation by water molecules– In phase partition studies, GCSF aggregates partitioned to octanol while

PEG-GCSF aggregates remained in the aqueous phase

From Rajan, R.S. et al. (2006) Protein Science

PEGylation and AggregationMechanism Findings

Aggregation and Drug DevelopmentImproving the Drug Compound

> Identify potential issues early– Dose level, dose concentration– Solubility at physiological pH– Manufacturing, shipping and handling

> Generally, testing compounds early is preferred– Logistical benefit, test compounds while in vitro and in vivo screens are

in process (rather than restarting assays)– Opportunity to solve before Candidate Nomination

> Consider strategy to reduce aggregation– Remove aggregates during manufacture– Formulate to prevent aggregate formation– Modify the compound to reduce/remove aggregation potential

Stage 2

• Analytical method optimization

• Late screening• Developability risk assessment

Stage 3

• IND enabling

• Phase I enabling

Candidate nomination

Stage 1

• Analytical method

development

• Early screening

Compound screening

Pre-project activities

• In silico modeling

Phase I activities• Monitor• Address

questions/issues

Team formation IND

Early Pharmaceutical Development

Opportunities to identify and solve aggregation issues during SAR development

M.S. Ricci et al. (2006) Mutational Approach to Improve Physical Stability of Protein Therapeutics Susceptible to Aggregation. In Misbehaving Proteins (Murphy RM and Tsai AM, ed) pp331-350. New York: Springer.

Acknowledgments and References

References

Rajan, R.S. et al. (2006) Modulation of protein aggregation by polyethylene glycolConjugation: GCSF as a case study. Protein Science 15: 1063-1075.

Gegg, C. and Kinstler, O. (2002) Chemical modification of proteins to improve biocompatibility and bioactivity. US Patent 6,420,340

Biology, cont’dPam SmithChristine VillescazTina WhisenantLynn JodkaKim DeConzoJulie HoytJenne PierceAmy CarrollAung Lwin

InformaticsEugene CoatsRobert Feinstein Paul NelsonResearch Chemistry Odile LevyRamina NazarbaghiLawrence D’SouzaJohn Ahn

Pharmaceutical SciencesSteven RenDerrick KatayamaEllen PadriqueJohnny GonzalesJenny Jin

Biology Diane HargroveEric KendallAugustine ChoKrystyna TatarkiewiczSlave Gedulin

Bioanalytical ChemistrySwati GuptaKristine De DiosLiying Jiang

Acknowledgments