Improving Physicochemical Properties of Biopharmaceutical Drug

Report
Improving Physicochemical Properties of
Biopharmaceutical Drug Candidates
David Litzinger, PhD
Director, Pharmaceutical Sciences
Amylin Pharmaceuticals, Inc.
PEGS Conference
May 20, 2010
Boston, MA
Analogs in Drug Development
Comparisons Across Platforms
Drug Platform
(typical MW)
Analog Evaluation
in Drug Development
Immunogenicity
Concern
Small
Molecules
High
Negligible
Medium
Slight
Low
Significant
<500 Da
Peptides
1-6 kDa
Proteins
15-150 kDa
Peptide Analogs as Drug Substances
Examples Related to Aggregation
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
Insulin lispro
Insulin
aspart
insulin
insulin
• Formulated as a solution at acidic pH
• Following injection, comes out of
solution at physiological pH to form
crystals that slowly dissolve
• Lys and Pro at the
C-terminal end of
the B-chain reversed
• Blocks the formation of insulin dimers
and hexamers
• Pro to Asp at B28
• Increased charge repulsion prevents the
formation of hexamers
• Rapid acting insulin
• Rapid acting insulin
Insulin
glulisine
insulin
• Asn to Lys at B3
• Lys to Glu at B29
• Rapid acting insulin
Peptide and Protein Optimization
Example Options for Improving Physical Stability
Approaches to Improving
Physical Stability*
Mutational
Chemical
Modification
– Mutations based on superior
properties in alternate species
√
– Decrease hydrophobicity
√
√
– Increase hydrophilicity
√
√
– Increase net charge
√
√
– Changing the pI
√
√
– Polymer conjugation
* More that one approach can be combined
√
Glucose-Dependent Insulinotropic Polypeptide
Example of Analog Evaluation in Drug Development
> 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
> Development Challenges
– 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
> Second Generation Effort (G2)
– 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
GIP Drug Development
History and Efforts to Identify Alternative GIP Analogs
Generation
Peptide
ID#
Metabolism
Biological
Activity
Physical
Stability
P
Human
GIP (1-42)
X
X

G1
G1-A
G1
G1-B
G2
G2-C
G2
G2-D








x
x


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
Native GIP (1-42)
G1 Analogs
2nd Round of
Screening
G2 Analogs
GIP Analog Screening
Primary Sequence Ranking by In Silico Tools
Generation Peptide ID#
P
Primary Sequence
Human GIP YAEGTFISDYSIAMDKIHQQDFVNWLLAQKGKKNDWKHNITQ-OH
MW
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
Underlined residues denote substitutions; Red - potentially labile residues; Blue – C-terminal end modification
> 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
GIP Analog Screening
In Silico Pharmaceutical Property Assessments
Solubility
ID #
Human GIP
Hydrophilicity
Aggregation
(Gravy Score)
(Tango 2 Score)
Calculated
pH 4
pH 7
Net Charge
Net Charge
Overall
pI
Solubility
Solubility
pH 4
pH 7
Stability
Good
+ 5.68
+ 0.39
+ 2.86
- 0.85
Good
D(3), M(1), N(1), Q(3), W (1)
+ 2.86
- 0.85
Good
D(3), M(1), N(2), Q(3), W (1)
+ 3.86
+ 0.91
Good
D(1), N(1), Q(3), W (1)
+ 4.86
+ 1.91
Good
D(1), N(1), Q(3), W (1)
-0.80
-7.00
7.5
G1-A
-0.37
-7.10
5.8
G1-B
-0.42
-6.78
5.8
G2-C
-0.41
-13.89
8.6
Good
G2-D
-0.50
-14.57
9.2
Good
(1-42)
Chemical Stability
Fair
Average
Fair
Fair
Average
Average
Fair
Fair
Average
Average
Fair
Average
Fair
Average
Fair
Average
Potential Labile Residues
D(4), M(1), N(3), Q(4), W (2)
> G2 analogs showed improved properties over G1 analogs:
• Higher pI
• Good solubility at acidic pH
• Fair/Average solubility at neutral pH
• Highly charged at pH 4 compared to pH 7
> Labile Residues:
• D – potential aspartic acid isomerization at pH 4
• M, W – potential site for oxidation
• N, Q – potential deamidation
Measured Solubility Results
G2 Analogs Have Improved Solubility
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
9.2
Note: nd – not determined
> G2 analogs show improved solubility profile compared to the G1 analogs
Formulation Screening
G2 Analogs Have Improved Physical Stability
ID #
Temperature at 25°C
pH
G1-A
Buffer
5.0
30 mM Acetate
6.0
30 mM Phosphate
6.0
30 mM Histidine
6.5
30 mM Phosphate
7.0
30 mM Phosphate
5.0
30 mM Acetate
6.0
30 mM Phosphate
6.0
30 mM Histidine
6.5
30 mM Phosphate
7.0
30 mM Phosphate
6.0
10 mM Phosphate
6.5
10 mM Phosphate
6.5
10 mM Histidine
7.0
10 mM Phosphate
7.0
30 mM Phosphate
7.0
10 mM Histidine
7.5
10 mM Phosphate
5.0
10 mM Acetate
5.5
10 mM Acetate
6.0
10 mM Histidine
6.5
10 mM Histidine
7.0
10 mM Histidine
7.5
10 mM Histidine
Time Point (Weeks)
0
1
2
Visual Analysis
Clear, Colorless
Slight Precipitation, Aggregation
G1-B
G2-C
G2-D
Moderate to Severe Precipitation, Aggregation
> G2 analogs proved to have the
most physically stable profile.
1 mg/mL concentration;
No agitation
Secondary Structure Analysis
Evaluation of GIP Analogs
Far
FarUV
UVCD
CD
Mean Residue Ellipticity (MRE)
(mdeg*(cm2/dmol)
25000
20000
Structure
l (nm)
15000
α-helix
208, 220
10000
β-sheet
215
Random Coil
195
5000
G1-A pH 6 Phosphate
G1-B pH 6 Phosphate
G2-C pH 4 Acetate
0
G2-C pH 7 Phosphate
-5000
-10000
G2-D pH 4 Acetate
-15000
-20000
190
G2-D pH 7 Phosphate
200
210
220
230
Wavelength (nm)
240
250
> G2 analogs show greater α-helical content
–
–
Correlates with less aggregation
Similar 2° structure at both pH 4 & 7
260
GIP Analog Optimization
Conclusions
> 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)
Metreleptin
Compound Properties and Obesity Treatment Approaches
• 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
> 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
Metreleptin
Charge Profile
Net Charge of Metreleptin vs pH
> Calculated pI= 6.1
> Suggests high solubility at low pH, and low solubility at neutral pH
Charge calculator/pI finder by Gale Rhodes
http://spdbv.vital-it.ch/TheMolecularLevel/Goodies/Goodies.html
Metreleptin
Solubility Profile
○ 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
> Murine leptin is more soluble than human leptin at neutral pH
– 43 mg/mL for murine leptin
– 31 mg/mL for W100Q/W138Q analog
Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.
Human and Murine Leptin
Amino Acid Sequence Comparison
> Comparison of human and murine leptin sequences
0
HUMAN: MVPIQKVQDD
MURINE: MVPIQKVQDD
40
HUMAN: DFIPGLHPIL
MURINE: DFIPGLHPIL
80
HUMAN: LENLRDLLHV
MURINE: LENLRDLLHL
120
HUMAN: STEVVALSRL
MURINE: STEVVALSRL
10
20
30
TKTLIKTIVT
TKTLIKTIVT
RINDISHTQS
RINDISHTQS
VSSKQKVTGL
VSAKQRVTGL
50
60
70
TLSKMDQTLA
SLSKMDQTLA
VYQQILTSMP
VYQQVLTSLP
SRNVIQISND
SQNVLQIAND
90
100
110
LAFSKSCHLP
LAFSKSCSLP
WASGLETLDS
QTSGLQKPES
LGGVLEASGY
LDGVLEASLY
130
140
QGSLQDMLWQ
QGSLQD I LQQ
LDLSPGC
LDVSPEC
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
Metreleptin
Surface Modeling
Electrostatic Surface
Red = Basic (+)
Blue = Acidic(-)
Hydrophobicity Surface
Brown = Lipophilic
Blue = Hydrophilic, charged
Trp 138
> Surface modeling shows region around Trp 138 has potential role in aggregation
– Low electrostatic potential
– High lipophilicity
Benchware3DExplorer (Tripos)
Human Leptin
Evidence for Leptin Conformational Transition with pH Change
● human
○ murine
> Increased ANS fluorescence
at pH 4 to 5
– Not observed for murine
leptin
> Suggests a folding intermediate with increased hydrophobicity
populated at pH 4-5
> May result in the formation of soluble multimeric species under
acidic conditions
Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.
Human Leptin
Low pH Aggregation and Relation to Neutral pH Precipitation
▲ 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 formed
at 50 mg/mL, pH 4:
• diluted to 5 mg/mL, pH 4
• diluted again into pH 7
Human leptin  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
Murine leptin
 Did NOT form multimers and did not precipitate
Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.
Human Leptin
Proposed Aggregation Mechanism
Increased hydrophobicity at
acidic pH not observed**
N
Multimers not
observed*
Murine Leptin
I
U
Iassoc
Precipitation not
observed*
precipitation
* Under conditions in which human leptin precipitated,
and formed multimers.
N: native state
I: folding intermediate
** As observed for human leptin in ANS studies.
U: unfolded conformer
Iassoc: folding intermediate self associated into a soluble multimer
Ricci, M.S. et al. (2006) in Misbehaving Proteins. New York: Springer.
Chemical Modification Example
Succinylation
O
O
Protein-NH2
+
O
Protein-N-C-CH2-CH2-C-OH2
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
• M1-K6: N-terminal peptide
From Gegg et al. US Patent 6,420,340
O
• Succ-(M1-K6): Succinylated
N-terminal peptide
Two Related Examples
DTPA and EDTA
O
O
O
N-R-N
O
H2N-Protein
R = -CH2-CH2-N-CH2CH2H+
(2)
O
O
O
HO
OH
OH
HO
O
O
N-Protein
H
CH2
H2O (1) or H2N-Protein (2)
(1)
O
COOH
O
O
N-R-N
Diethylenetriaminepentaacetic acid (DTPA)
Monomer conjugate
From Gegg et al. US Patent 6,420,340
O
OH
N-R-N
N-Protein
H
O
N-Protein
H
Dimer conjugate
Ethylenediaminetetraacetic acid (EDTA)
R = -CH2-CH2-
Succinylation and Related Modifications
Impact on pI and Solubility of Metreleptin
Sample
Maximum Solubility in PBS* (mg/mL)
Change in pI
Unmodified leptin
Succinyl-leptin
3.2
8.4
N/A **
-0.7 **
DTPA-leptin monomer
EDTA-leptin monomer
31.6
59.9
Not reported
Not reported
* pH = 7.0
** Leptin pI = 6.1; succinyl-leptin estimated to be 5.4
> Conjugations with acidic moieties to the N-terminus lower pI and increase
solubility at neutral pH
From Gegg et al. US Patent 6,420,340
Succinylation
Reduces Injection Site Precipitation of Metreleptin
> Three mice dosed per sample
> Tissues sections from the injection sites examined histologically
Sample
Concentration
(mg/mL)
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)
0
0
0
50
50
50
0
0
0
50
50
50
Injection volume
(mL)
20
20
20
20
20
20
20
20
20
20
20
20
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
From Gegg et al. US Patent 6,420,340
Precipitation
0
0
0
4
4
1.5
0
0
0
0
0.5
0
Succinylated and Related Metreleptin Conjugates
Retain In Vivo Activity
> Similar activity in vivo for conjugates relative to unmodified leptin
– Normal mice dosed s.c. daily, 10 mg/kg
– Results shown as % weight-loss relative to buffer control
From Gegg et al. US Patent 6,420,340
Polymer Conjugation Example
PEGylation
> What is PEGylation?
– Covalent attachment of poly(ethylene glycol) (PEG)
– Example PEGylation reagent:
Methoxy cap
CH3O-(CH2-CH2-O)n-CH2-CH2-X
Reactive group
> Why PEGylation?
– Slow clearance/maintain circulating concentrations/reduce dose frequency
– Increase solubility
– Reduce aggregation
– Reduce proteolysis
– Reduce immunogenicity
– In several approved products
Site-Directed PEGylation
N-Terminal Site-Specific Example
NeH3+
-OOC
NeH3+
O
H-C-PEG
Protein
-OOC
NH2
Protein
NaCNBH3
NeH3+
NeH3+
– 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)
> Why site-directed PEGylation?
– Optimally preserve biological activity
– Homogenous product/consistent lot-to-lot activity
NH-CH2-PEG
Effect of PEGylation on Solubility
PEG-GCSF Has Improved Solubility
> Under conditions in which GCSF rapidly precipitated, 20kDa PEG-GCSF
remained completely soluble
Samples formulated at 5 mg/mL in phosphate buffer, pH 6.9 and incubated at 37oC
> 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
PEG-GCSF Forms Soluble Aggregates
Analysis by Size-Exclusion Chromatography
> 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
PEGylation and Aggregation
Mechanism Findings
> PEGylation does not alter the linkages or heterogeneity of the aggregates
– 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 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
Aggregation and Drug Development
Improving the Drug Compound
> Identify potential issues early
– Dose level, dose concentration
– Solubility at physiological pH
– Manufacturing, shipping and handling
> Consider strategy to reduce aggregation
– Remove aggregates during manufacture
– Formulate to prevent aggregate formation
– Modify the compound to reduce/remove aggregation potential
> 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
Early Pharmaceutical Development
Opportunities to identify and solve aggregation issues
during SAR development
Stage 1
Stage 3
Stage 2
• Analytical method
development
• Analytical method
optimization
• Early screening
• Late screening
• IND enabling
• Phase I enabling
• Developability risk
assessment
Team formation
Compound
screening
Pre-project
activities
• In silico modeling
Candidate
nomination
IND
Phase I activities
• Monitor
• Address questions/issues
Acknowledgments and References
Acknowledgments
Pharmaceutical Sciences
Steven Ren
Derrick Katayama
Ellen Padrique
Johnny Gonzales
Jenny Jin
Biology
Diane Hargrove
Eric Kendall
Augustine Cho
Krystyna Tatarkiewicz
Slave Gedulin
Biology, cont’d
Pam Smith
Christine Villescaz
Tina Whisenant
Lynn Jodka
Kim DeConzo
Julie Hoyt
Jenne Pierce
Amy Carroll
Aung Lwin
Bioanalytical Chemistry
Swati Gupta
Kristine De Dios
Liying Jiang
References
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.
Gegg, C. and Kinstler, O. (2002) Chemical modification of proteins to improve
biocompatibility and bioactivity. US Patent 6,420,340
Rajan, R.S. et al. (2006) Modulation of protein aggregation by polyethylene glycol
Conjugation: GCSF as a case study. Protein Science 15: 1063-1075.
Informatics
Eugene Coats
Robert Feinstein
Paul Nelson
Research Chemistry
Odile Levy
Ramina Nazarbaghi
Lawrence D’Souza
John Ahn

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