Improving Physicochemical Properties of Biopharmaceutical Drug Candidates
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Transcript of Improving Physicochemical Properties of Biopharmaceutical Drug Candidates
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
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> 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