1 options for automated solubility measurement in discovery and developments: science issues and...
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Options for Automated Solubility Measurement In Options for Automated Solubility Measurement In Discovery and Developments:Discovery and Developments:
Science Issues and Practical SolutionsScience Issues and Practical Solutions
Arnon ChaitANALIZA, Inc.
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OUTLINEOUTLINE
Solubility: the basics Solubility assays Particles in solution: why should we care? Focus: elemental solubility assay
– How does it work?– Sample data for pH, excipient screening
DMSO effect: The Good, the Bad, and the Ugly
How do we deal with impure samples?
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Assay Effects: Summary (1)Assay Effects: Summary (1)
DRYDRY
DMSODMSO
TurbidityTurbidity
AbsorbanceAbsorbance
ElementalElemental
Small
Large
INCREASE
IndirectIndirect
DirectDirect
Variable/unknown
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Assay Effects: Summary (2)Assay Effects: Summary (2)
Solid particles are an integral part of the solubility assay– Particles are always present– They must be present for turbidity to work– They are artifacts in absorbance/elemental
assays
The effects of particles on the data must be considered when examining the data– Subtle to substantial influence on quality of
results
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Assay Effects: Summary (3)Assay Effects: Summary (3)
DMSO effect can be very large, and is unpredictable
Starting material has significant influence on the data
DMSO effect can not be neglected, even at small amounts
Late discovery and development should avoid DMSO if at all possible
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A Simple ConceptA Simple Concept
Solubility = Concentration of a dissolved compound in equilibrium with its solid
But:– Which solid?
Equilibrium (most stable form) vs. apparent (other forms)
– Which solvent? Buffers (intrinsic?) and co-solvents (kinetic)
– Which equilibrium? Time (kinetic) and temperature
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But It’s All in the DetailsBut It’s All in the Details
Conceptually a very easy experiment to conduct
But:– We don’t always have the right form (discovery)– We don’t always have time to wait for
equilibrium– Everything matters:
Probably one of the most sensitive thermodynamic experiments to conduct
– Different users refers to same term with different meanings
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Who Are The Users?Who Are The Users?
Discovery:– Obtain a measure of solubility of relevance to HTS and early
ADMET Can we determine if the compound will crash out of
solution?
– Obtain ADMET information of relevance for selecting amongst hits
Development:– Early lead characterization– Lead optimization– Formulation excipient selection
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Who Are The Users? (2)Who Are The Users? (2)
Will the compound crash out? solubility
Everyone else needs good data:
– For promoting a compound: binning may be sufficient
– For lead optimization: accurate data
– For formulation development: accurate data
– For anything regulatory: accurate data
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How Does a Compound Come Out of How Does a Compound Come Out of Solution?Solution?
Homogeneous vs. heterogeneous nucleation
Growth by dislocations (crystalline) vs. amorphous
G
rr*
http://monet.physik.unibas.ch/~lang/gallery/gallery.htm
Courtesy: Rick Rogers, NASA GRC
Hard spheresInsulin
YBCuO
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Solid FormsSolid Forms
Amorphous
Crystalline
Small molecules: Multiple crystalforms Amorphous is rare
Biomolecules: Single crystalform Amorphous is the norm
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Key Differentiating FactorKey Differentiating Factor
Elemental Concentration:CarbonNitrogen
...
Static Light Scattering
Absorbance
Evaporative LightScattering
No standards / calibration
No standards / calibration
Compound specific
Are you measuring the actual concentration?
Elemental:Yes, directly
Absorbance:Yes, indirectly
Turbidity:No, solubility is inferred from dilution factor off a standard
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What Controls the Size Distribution in Time?What Controls the Size Distribution in Time?
Ostwald coarsening: Particles nucleate at a minimum radius (critical radius)
Growth is an interplay between:oversaturation level in the liquidgain/loss from dissolving/growing neighbors
particles
The particle size distribution is a solution this interplay
Lifshitz-Slezov and Marqusee and Ross theories predict a continuous growth of larger particles at the expense of smaller ones: 1/3( , )f r t t
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But Why Should We Care?But Why Should We Care?We Can Always Filter the ParticlesWe Can Always Filter the Particles
You can NOT filter all the particles– You must have solid at solubility
Filtering simply places a dynamic cutoff limit to the size distribution function – but it will again change in time!
Filtering is necessary to reduce the potentially deleterious effects of particles
Log(Size) Log(Size)
Time
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Take Home Message #1Take Home Message #1
Particles are a fact of life:without them - we have no solubility
Particle size is changing dynamically
You can only interfere – for a while - with the natural size distribution by filtering
Each assay technique is sensitive to particles to a different degree
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Optical Properties of Particles in SolutionOptical Properties of Particles in Solution
Van de Hulst, 1957
Gold particles
Scattering is very small in comparison with absorbance when the solid particles are small
MeasuredSignal
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Can We Predict Optical Effects of Particles Can We Predict Optical Effects of Particles In Practice?In Practice?
Light scattering depends on:– Angle, refractive indices, sizes, cross section
efficiencies, concentration, wave length, structure factor, time… - in a nonlinear and non-intuitive way!
Plus:– Structure of the compound in solution changes with
concentration (monomers dimers trimers …)– Static light scattering is VERY sensitive to
everything: Free surface shape, scratches, dust, fingerprints, …
Too complex to predict in practice!
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A Little Experiment in Light Scattering (1)A Little Experiment in Light Scattering (1)
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Saturated solutionsPhosphate buffer, pH 111 week incubation
Left to Right:
ChlorpromazineHCl Bendroflumethiazide Clofazimine Bifonazole ThioridazineHCl TriflupromazineHCl Nifedipine Perphenazine PromazineHCl
Can You Tell The Saturated Solution?Can You Tell The Saturated Solution?
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So Let’s Filter the StuffSo Let’s Filter the Stuff
Dynamic Light Scattering:
Bendroflumethiazide, saturated, filtered
Filter,m
Particle size,nm
Polydispersity
0.2 481 – 4,000 0.226
0.45 270 0.096
1 543 - 2,000 0.327
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Particle Effects in Optical Assays (1)Particle Effects in Optical Assays (1)
Turbidity:– Relies on particles to produce scattering– No filtering is desired– Particle evolution is unpredictable
Absorbance:– Scattering is an undesired artifact
– Filtering is desired– Scattering contribution to data is unpredictable
0 scattered transmittedI I I
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Particle Effects in Optical Assays (2)Particle Effects in Optical Assays (2)
I0It
No particles:
No scattering
Beer’s law works
Is
Particles in solution:
Scattering
Beer’s law does not work
~A C Determine from dissolved samples (undersaturated)
Use in saturated solutions
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Caffeine concentration, mg/ml
0 20 40 60 80 100
Ana
lytic
al S
igna
l
0
10
20
30
40
50
60
70
The Ideal ExperimentThe Ideal Experiment
All of these data have particle effects!
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Saturation is a Difficult Place To AssaySaturation is a Difficult Place To Assay
nm solids artifacts:
- Assay specific- Significant for optical techniques
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Take Home Message #2 Take Home Message #2
Particles will affect solubility data:
Turbidity:Increase, perhaps
significantly
Absorbance:Increase, unpredictably
Elemental:Increase, more predictably
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What Do We Want to Study?
Time
Temperature
DMSO Crystalform
Salt
Co-Solvent/Excipient
pH
Solubility
Time
Temperature
DMSO Crystalform
Salt
Co-Solvent/Excipient
pH
Solubility
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How We Chose to Do the Job:How We Chose to Do the Job:Automated Solubility WorkstationAutomated Solubility Workstation
Philosophy of Design:– Accuracy is everything– Assay flexibility is a must– Medium throughput is acceptable (up to 250/day)– System must be compatible with dry and DMSO-
dissolved– Minimize number of assumptions– Native assay relies on elemental assays: no
standards required– Eliminate the need for experienced chemist by using
intelligent software– Simplify and modernize everything significant
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Solubility: Where Do You Spend Solubility: Where Do You Spend YourYour Time? Time?
Weighing
Preparing standards (or believing nominal library concentrations)
Deciphering data – trapping errors
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Streamlined Solubility AssayStreamlined Solubility Assay
Weighing:– Optional. Useful only for detecting
insufficient source material (undersaturated solution)
Preparing standards (or believing nominal library concentrations)– Eliminated. You only need MW and #of
nitrogens Deciphering data – trapping errors
– Intelligent data analysis, smart error detection, automated reporting
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Two Options on One PlatformTwo Options on One Platform
Native Assay: Equimolar nitrogen detection
Dry or dissolved sample
No calibration required
Optional Assay:
Millipore MultiScreen®
solubility plates
DMSO dissolved samples
UV assay
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The ASolWNative Assay
Millipore MultiScreen® Solubility Protocol
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ADW - Automated Discovery WorkstationADW - Automated Discovery Workstation
ANALIZA’sADWIn-house DevelopmentSystem
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ASolW – Automated Solubility WorkstationASolW – Automated Solubility Workstation
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Total Nitrogen DetectionTotal Nitrogen Detection
Exceptions:– N2 – nothing is detected!
– Nitrosamine (for GC)– Azides (1/3 response)– Double bonds (partial
response)
)900600(2*23
1050
2
nmhONOONO
productsNOONR
Separate
calibration
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Effect of Nitrogen StructureEffect of Nitrogen Structure
Compound # N atoms Adjacent N? mg/ ml Yield % caffeine 4 None 1.35 94.7 HEPES 2 None 6.29 90.9 propranolol HCl 1 None 2.52 96.5 sulfanilamide 2 None 2.07 98.3 tris base 1 None 4.97 100.4 benzocaine 1 None 0.60 100.2 verapamil HCl 2 None 0.47 86.0 nicotinamide 2 None 2.65 99.7 alprenolol HCl 1 None 1.67 102.7 trimethoprim 4 None 0.12 86.7 phenacetin 1 None 0.17 110.1
Average
yield: 96.6%
Compound # N atoms Adjacent N? mg/ ml Yield % antipyrine 2 2 1.98 82.1 allopurinol 4 2 0.08 76.4
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Assay Using Nitrogen ContentAssay Using Nitrogen Content
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Dynamic RangeDynamic Range
ppm N of calibrator
1 10 100 1000 10000
Ana
lytic
al s
igna
l +/-
1 s
d (
n=3
)
0.01
0.1
1
10
100
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AccuracyAccuracy
Sexp = 0.036(±0.018) + 1.005(±0.008)*Slit
N = 12; r2 = 0.9993; s = 0.0596,
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Data DispersionData Dispersion
ppm N of calibrator
1 10 100 1000 10000
rela
tive
sta
ndar
d d
evia
tion,
CV
, %
(n
=3)
0.01
0.1
1
10
100
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Repeated MeasurementsRepeated Measurements
Run #
0 5 10 15 20
Sol
ubili
ty,
mg/
ml
0.0
0.1
0.2
0.3
0.4
0.5
Average = 0.264Upper Limit = 0.283
Lower Limit = 0.245
Allopurinol in 0.15M NaCl in 0.01M Universal buffer, pH 6.6
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Effect of Filter Type on ConcentrationEffect of Filter Type on Concentration
ANALIZA recommends PTFE 0.45
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Solubility-pH ProfilesSolubility-pH Profiles
0.01M universal buffer
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Solubility with PEG600
0
2
4
6
8
10
12
14
16
18
0 20 40 60 80 100 120
% PEG 600
mg
/ml
clofazimine bifonazole nifedipine
Excipients/Co-Solvent Effects (1)Excipients/Co-Solvent Effects (1)
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Excipients/Co-Solvent Effects (2)Excipients/Co-Solvent Effects (2)
Solubility with Tween80
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 2 4 6 8 10 12 14 16 18
% Tween
So
lub
ility
mg
/ml
clofazimine bifonazole nifedipine
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What is the Effect of DMSO?What is the Effect of DMSO?
DMSO is a fact of life during screening
DMSO solubility is a current issue in HTSe.g. K. Balakin, “DMSO Solubility and Bioscreening”, Current Drug Discovery, (August 03)
Key Issue: How did you start?– DMSO-dissolved sample: NO solid
Precipitating solid at saturation crystalline form
Difficult experiment requiring high concentrations
– DMSO added to solid form
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DMSO – Time ExperimentsDMSO – Time Experiments
30 mM DMSO stock solutions, 20-fold dilution Powder with buffer or with 5% DMSO 50 mM phosphate buffer at pH 11
Source % DMSOIncubationTime, hrs.
Powder 0 20
DMSO stock 5 20
DMSO stock 5 1
Powder 0 1
Powder 5 20
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Test Compounds – Solubility (mg/ml)Test Compounds – Solubility (mg/ml)
1 bendroflumethiazide 0.3507
2 nifedipine 0.0013
3 nitrofurazone 0.1615
4 perphenazine 0.0006
5 trimethoprim 0.3440
6 nafoxidineHCl 0.0040
7 nadolol 0.0038
8 imipramineHCl 0.0007
9 verapamilHCl 0.0064
10 clofazimine 0.0006
11 bifonazole 0.0009
12 clomipramineHCl 0.0004
13 labetalolHCl 0.5946
14 chlorpromazineHCl 0.0023
15 triflupromazineHCl 0.0013
16 thioridazineHCl 0.0007
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Group I: Fully DissolvedGroup I: Fully Dissolved
#1 #5 #13So
lub
ility
Re
lativ
e t
o T
ota
l Co
mp
ou
nd
Con
cen
tra
tion
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Powder in Buffer alone, 20 hr incubation30 mM DMSO stock, diluted 20-fold in bufferPowder in buffer with 5% DMSOPlot 1 Upper Control Line
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Group II: Similar ResultsGroup II: Similar Results
#3 #7 #11 #14 #15
So
lub
ility
Rel
ativ
e t
o P
ow
der
in B
uff
er
Alo
ne
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
Powder in Buffer alone, 20 hr incubation30 mM DMSO stock, diluted 20-fold in bufferPowder in buffer with 5% DMSOPlot 1 Upper Control Line
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Group III: Significant DMSO Stock Effect Group III: Significant DMSO Stock Effect
#4 #2 #6 #10 #16
Sol
ubili
ty R
elat
ive
to P
owde
r in
Buf
fer
Alo
ne
0
10
20
30
40
Powder in Buffer alone, 20 hr incubation30 mM DMSO stock, diluted 20-fold in bufferPowder in buffer with 5% DMSOPlot 1 Lower Control Line
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Group IV: Significant DMSO Effect Group IV: Significant DMSO Effect
#4 #8 #9 #12
So
lubi
lity
Rel
ativ
e t
o P
owde
r in
Buf
fer
Alo
ne
0
5
10
15
20
25
Powder in Buffer alone, 20 hr incubation30 mM DMSO stock, diluted 20-fold in bufferPowder in buffer with 5% DMSOPlot 1 Upper Control Line
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Powder Plus DMSO: Reasonable at Low %Powder Plus DMSO: Reasonable at Low %
Allopurinol
Bendroflumethiazide
Butamben
Clofazimine
Nitrofurazone
Theophylline
Nifedipine
Perphenazine
Phenacetin
Sulfanilamide
Trimethoprim
pH 7.4
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Powder Plus DMSO: Reasonable at Low %Powder Plus DMSO: Reasonable at Low %
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DMSO Stock Effect is Still Significant at 1%DMSO Stock Effect is Still Significant at 1%
Equilibrium Solubility in PBS/ 1% DMSO
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Kin
etic
Sol
ubili
ty fr
om D
MS
O s
tock
, mg/
ml
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1
73
9 8 2
5
4
6
1 bendroflumethiazide2 benzocaine3 benzthiazide4 butamben5 nifedipine6 nitrofurazone7 perphenazine8 phenacetin9 trimethoprim
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Take Home Message #3Take Home Message #3
DMSO effect is unpredictable
DMSO effect is most pronounced when starting material is DMSO-dissolved
DMSO effect is still significant and unpredictable in practice, even at low DMSO %, when starting from DMSO-dissolved samples
DMSO-dissolved samples are fine for early discovery questions, but can not be relied on for later discovery and development
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How Do We Deal With Impure Samples?How Do We Deal With Impure Samples?
Impurities are a fact of life:– Combi libraries are 90-95% pure– Lead synthesis is similarly pure
Turbidity:– No need, usually, but you don’t know what
came out of solution
Absorbance:– Use spectral techniques – not trivially
Elemental:– Clean sample: inline column + fast gradient
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Final ThoughtsFinal Thoughts
If you need good numbers, you have to watch your steps:– Particle effects in optical methods– Filter effects– DMSO effects when starting from dissolved
samples Elemental method provides for automated,
accurate determinations with full accessibility to later discovery/development questions: pH, temperature, salts, etc…
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Coming Up: Integrating ADMET (1)Coming Up: Integrating ADMET (1)
Hardware is expensive Software is very expensive Gold-standard assays are always that Only big pharma can own “one of each” In silico predictive analysis works much
better on same series, if properly trained Chemists will use your data if it is GOOD,
USEFUL, COMPREHENSIVE, and EASILY AVAILABLE
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Coming Up: Integrating ADMET (2)Coming Up: Integrating ADMET (2)
Automated Discovery Workstation: Multi-assay on the same hardware platform:
– Solubility (dry/DMSO, pH, salts,…)– LogD (pH)– BBB (near term GIT) permeability– Coming: Tox (cardiac), protein binding
Nothing proprietary, no magic, only gold-standard assays
Never have to weigh or prepare standards Never have to believe your library concentration Optional on-line sample cleanup Future integration with predictive software
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Thank YouThank You
Acknowledgements
Padetha Tin
Pam LechnerAlexander BelgovskiyBoris Zaslavsky