Enhanced Physico-Chemical
Characterization of Candidate
Compounds
using the
pKa AnalyzerPRO™
Challenges in Drug Development
• Increasing cost of drug development
– $0.9 to $1.3 billion per successful drug
– Clinical testing is very expensive; hence, want
only high-probability leads entering this phase.
• Large libraries of candidate compounds
have been created from combinatorial
chemistry
– Characterization of these leads is causing
major increases in analytical work loads
Nov. 05
2
Changes in Drug Development Process
• Adopt strategy of “fail often, but fail early”
– Characterization of candidates as early as possible
– Eliminate “drug duds” very early in the process
• Perform physicochemical testing earlier in the
drug development process
– ADME (Adsorption, Digestion, Metabolism, Excretion)
– Toxicity
Nov. 05
3
Why Physicochemical Properties?
• Many physicochemical assessments are laborintensive, and hence, are delayed until “hits” are
turned into “leads”
• Unsuitable physicochemical properties account
for up to 30% of drug failures
• Earlier determination of physicochemical
properties will generate better qualified
candidates to clinical testing – provided the
screening can be made cost-effective.
–Need new tools and technologies
Nov. 05
4
Drug Discovery Process
0.5-1 Year
1-3 Years
Basic
Research
Disease
model
hypotheses
Exploratory
Research
Target
Identification
Characterize
genes &
proteins as
candidates
in the
disease
process
Target
Validation
Discriminate
valid from
invalid
biological
targets
1-2 Years
Lead
Identification
HTS
Screening of
leads
Lead
Optimization
6-8 Years
Clinical
Trials
Market
Evaluate leads
for optimal
pharmacologic
efficacy &
selectivity
L
E
A
10,000
500
10
D
S
Nov. 05
5
90-95% of Development Cost occurs in the
Clinical Trials Phase
1
Drug Discovery Process
0.5-1 Year
1-3 Years
Basic
Research
Disease
model
hypotheses
Exploratory
Research
Target
Identification
Characterize
genes &
proteins as
candidates
in the
disease
process
Target
Validation
Discriminate
valid from
invalid
biological
targets
1-2 Years
Lead
Identification
HTS
Screening of
leads
6-8 Years
Lead
Optimization
Clinical
Trials
Market
Evaluate leads
for optimal
pharmacologic
efficacy &
selectivity
L
E
A
10,000
500
3
D
S
Nov. 05
With better early characterization of leads,
significant cost savings are achieved
6
1
Key Physicochemical Parameters
• Solubility
• pKa (Acid-base dissociation constant)
• Partition coefficient (log Pow, log D, …)
• Permeability (Caco-2, PAMPA, …)
• Integrity
Nov. 05
7
Key Physicochemical Parameters
• Solubility
• pKa (Acid-base dissociation constant)
• Partition coefficient (log Pow, log D, …)
• Permeability (Caco-2, PAMPA, …)
• Integrity
Nov. 05
8
pKa : Acid-base Dissociation Constant
• The pKa value is a measure of the ionization
ability of a weak acid or base:
HA  H+ + AKa = [H+][A-] / [HA]
pKa = - log Ka
pH = -log [H+]
pKa = pH – log ([A-] / [HA])
• From this last relationship, it is seen that the pKa
value is the pH at which a compound is 50%
ionized ([A-]/[HA] = 1; log 1 = 0)
Nov. 05
9
pKa : Acid-base Dissociation Constant
HO
HO
HO
N
H+
O
H 3C
O
O
H 3C
H3C
N
H+
N
H+
Quinine
Nov. 05
10
N
N
N
Physicochemical Properties - pKa
• Why is pKa important?
– Most all drugs are weak acids or weak bases
– The pKa value of a compound strongly influences its
solubility, ability to permeate cell membranes,
complexation to drug targets, and bioactivity
– The pKa value is of fundamental importance in early
discovery and development processes for:
• Prediction of ADME (adsorption, distribution, metabolism,
excretion)
• Assessment of potential challenges in formulation/process
development
• Prediction of chromatographic / electrophoretic separation
behavior
Nov. 05
11
Biologically Relevant pH Range for
Pharmaceutical Products
pharmaceutical products
stomach
small intestines
colon
urine
Nov. 05
0
2
4
cola
vinegar
orange
juice
12
6
milk
blood
8
10
12
bleach
High Throughput determination of
Physicochemical Properties - pKa
• Conventional pKa methods are lengthy and
labor-intensive
– Potentiometry – requires many hours; mg of pure sample;
stringent buffer conditions
– UV spectroscopy – requires a chromaphore influenced by
charge state; μg - mg of pure sample
– HPLC or capillary electrophoresis – relaxes purity demand, but
still low throughput (runs at multiple pH values)
Nov. 05
13
Technology Overview
-
+
-–
+
Bulk Flow: EOF + Vacuum
+
N
-
N
UV
Time
• CE-based platform; application of high voltage across capillary filled with
aqueous-based buffer
• Narrow bore, fused silica capillaries (75 mm i.d., 150 mm o.d.; 55 cm total
length/33 cm to detector)
• Electroosmotic flow (EOF) provides bulk flow towards cathode at pH > 4
• Application of vacuum provides additional bulk flow to detector at all pH values
• Migration time depends on analyte charge-to-mass ratio; neutral compounds
migrate with bulk flow
• Many publications describe single capillary CE for the determination of
compound pKa values, dating back >14 years
Nov. 05
14
Principles of pKa AnalyzerPRO™ Technology
• UV light passing through the detection window of a 96-capillary array is imaged onto a
linear photodiode array detector
• Capillary inlets are arranged 8 x 12 for direct injection from 96-well sample plates; capillary
outlets are bundled to a common reservoir enabling vacuum-assisted separation
• Different pH buffers are injected into different capillaries of the array prior to separation
• Samples are separated by the application of a high voltage with vacuum flow
• Separation of compounds from the neutral marker as a function of pH is directly
proportional to their charge state, yielding the compound pKa value
Nov. 05
15
Attributes of the pKa AnalyzerPRO™ for pKa Analysis
High Sample Throughput
96 separation channels allow for the measurement of 8 compounds over 12 pH
values, or 4 compounds over 24 pH values in a single analysis
Small Sample Consumption
Approximately 5 mg per sample well required for analysis; typical sample well
volume of 50 ml; only nl volumes injected
Separation of Potential Interferents
Sample impurities or degradants possessing different charge-to-mass ratios can
be resolved from target compound; compound pKa values can be measured in the
presence of UV absorbing counterions
Sample Requirements
Only UV absorptivity at 214 nm required; spectral changes between ionization
states not required; exact sample concentration does not need to be known
Multiplexed Format
Provides the capability to effectively span a wide pH range (pH 1.8 to pH 11.2) with
good resolution (0.4 pH units) to identify extreme pKa values, deconvolute closely
spaced pKa values, and improve confidence in results
Nov. 05
16
pKa AnalyzerPRO™ System Specifications
pKa Determination Method: Plot of compound ionic mobility (from migration time vs. neutral
DMSO marker) vs. buffer pH value
Detection: UV Absorbance at 214 nm; other wavelengths available (chromophore does not
have to be in proximity of ionization center)
Detection Sensitivity: ~10 mg/ml (ppm) depending on chromophore; typical working
concentration 50 - 100 mg/ml
Sample Volume Required: Typical volume 50 ml/well (minimum volume 20 ml/well); 24 wells
per 24 pH point analysis; 12 wells per 12 pH point analysis
Sample Format: Typical DMSO concentration 0.1-0.2% (v/v); higher DMSO concentrations can
be tolerated at higher wavelengths
Sample Purity Requirements: Compound of interest should be major species present;
impurities and degradants can often be separated
Maximum Sample Throughput: 12 – 24 compounds/h (24 or 12 pH points/sample)
pKa Determination Range: 1.8 – 11.2
Data Export Format: Microsoft Excel spreadsheet
Nov. 05
17
pKa AnalyzerPRO™: Some Equations for pKa Measurement
Effective Mobility (Meff)
Meff =
Ltot  Leff
V
(1/ta – 1/tm)
Ltot = Total length of capillary
Leff = Length to detector
V = Applied voltage
ta = Migration time of analyte
tm = Migration time of neutral marker (DMSO)
Meff =
Z
6r
Z = fractional charge on analyte
 = viscosity of medium
r = hydrodynamic radius of analyte
Relationships between Meff, pH, and Apparent pKa
Monoacid:
Monobase:
Meff =
Meff =
Ma10-pKa
10-pKa + 10-pH
Mb10-pH
Ma, Mb = Meff of completely ionized species
10-pKa + 10-pH
To calculate the pKa value, a regression fit of Meff against pH is performed using the
appropriate fitting equation
Additional equations can be found in: J. M. Miller et al. Electrophoresis, 2002, 23, 2833-2841.
Nov. 05
18
Technology Overview
-
++
-–
+
N
Bulk Flow: EOF + Vacuum
UV
+
N
-
• Effective mobility determined from the
migration time of the solute
Time
• The software determines the best fit of mobility
data vs. pH to various equations, and selects
the proper choice
• The data is plotted with fitted line; the pKa
values are reported (and can be exported as
.csv file)
Nov. 05
19
pKa AnalyzerPRO™: Sample and Buffer
Tray Configuration for pKa Analysis
• 12 different pH buffers are drawn into sets of 8
capillaries
– 8 capillaries having the same buffer, 12 capillary sets,
each with a different pH value
• 8 different samples are loaded in 12 wells across
the 96-well plate
– 8 different sets of the same sample in 12 wells
Nov. 05
20
Sample and Buffer Tray Configuration for pKa Analysis
12 pH Point pKa Analysis (8 Samples)
1
2
3 4
5
6 7
8
9 10 11 12
Acyclovir
Acyclovir
4-Aminopyridine
4-Aminopyridine
Benzoic Acid
Benzoic Acid
Quinine
Quinine
A
B
C
D
Sample Tray
Analyte
E
F
G
H
1
2
3 4
5
6 7
8
9 10 11 12
A
B
C
D
Inlet Buffer Tray
The marked well (E7)
corresponds to benzoic
acid analyzed at pH 6.84
E
F
G
pH
Nov. 05
21
2.07
2.89
3.42
4.41
5.21
6.01
6.84
7.58
8.41
9.19
10.00
10.83
H
Experimental User Interface Screen
• User selects experimental mode (12 or 24 point aqueous, 12 or 24 point co-solvent)
• Compound names, molecular weights and predicted pKa values (if available) are entered
• Buffer pH information file is loaded
• Information is saved for pKa calculation and report generation
Nov. 05
22
Results for 4-Aminopyridine (monobase)
• 4-Aminopyridine (red cursor) is a basic compound; therefore it migrates
before the DMSO neutral marker (black cursor)
Nov. 05
23
Results for 4-Aminopyridine (monobase)
pKa
• Mobility vs. pH plot yields a titration curve; inflection point corresponds to the pKa
value (9.19).
• The software automatically predicts the charge of the compound (e.g., monobase or
dibase) from its MW and maximum mobility: Charge(4-AP) = +1.09.
Nov. 05
24
Results for Benzoic Acid (monoacid)
• Benzoic Acid (red cursor) is an acidic compound; therefore it migrates
after the DMSO neutral marker (black cursor)
Nov. 05
25
Results for Benzoic Acid (monoacid)
• pKa value = 4.07
• Charge (benzoic acid) = -1.09
Nov. 05
26
Results for Quinine (dibase)
• pKa values = 4.29, 8.51
• Charge (quinine) = +1.91
Nov. 05
27
Results for Acyclovir (monoacid/monobase zwitterion)
• pKa values = 2.09, 9.17
• Charge (acyclovir) = +0.60; -1.00
Nov. 05
28
Exported Excel
Report for Quinine
The measured pKa value(s),
titration curve, predicted
charge, and buffer information
are exportable; a structural
image file of the compound can
be inserted if available
Nov. 05
29
pKa Results Data Table
• Each saved pKa result is entered into a sortable data table for easy access to data
Nov. 05
30
pKa Analysis of Tyrosine (monobase/diacid zwitterion)
• pKa Values = 2.21, 8.79, 10.08
• Charge = +0.71, -1.62
Nov. 05
31
The –COOH pKa value was not observable
by UV spectrophotometry
pKa Analysis of a Procaine/4-Aminobenzoic Acid Sample
**
pH 1.78 (Top Left) – pH 6.46 (Bottom Right)
Effective Mobility (x 106 cm2/V•s)
• A 4-aminobenzoic acid hydrolysis impurity (20%) of procaine was present
• The pKa values for both species were determined in the same experiment
Procaine
300
250
200
150
100
50
0
-50 1
pH Value
2
3
4
5
6
7
-200
-250
4-ABA
-300
*
Nov. 05
32
9
-150
Procaine pKa’ Values:
2.20, 9.04
4-ABA pKa’ Values:
2.37, 4.38
+
pH 6.82 (Top Left) – pH 11.20 (Bottom Right)
8
-100
*
+
10
11
Some pKa Results Obtained with the pKa Analyzer PRO™
Compound
Acebutolol
Acyclovir
MW
336
225
Type
B
A/B
n
15
13
4-Aminopyridine
Benzoic Acid
Betahistine
94
122
136
B
A
2B
8
13
11
Cefadroxil
363
2A/B
13
Cefuroxime
423
2A
9
Clomipramine
Furosemide
315
331
B
2A
9
24
Imipramine
Indomethacin
Piroxicam
280
358
331
B
A
A/B
5
13
8
Procaine
300
2B
16
Quinine
324
2B
18
Tyrosine
181
2A/B
10
pK a Analyzer PRO ™ pKa' (I = 50 mM)
9.51
2.19
9.20
9.22
4.07
3.88
9.97
2.57
7.21
9.70
2.12
11.19
9.56
3.61
10.39
9.60
4.02
1.87
5.35
2.13
9.06
4.33
8.50
2.23
8.85
10.05
SD
0.09
0.03
0.01
0.03
0.03
0.02
0.04
0.03
0.04
0.05
0.01
0.15
0.04
0.05
0.09
0.03
0.08
0.05
0.06
0.09
0.04
0.05
0.06
0.02
0.08
0.07
• Literature pKa values were reported at ionic strengths from 0 – 150 mM
• To date, the pKa values for >100 compounds have been measured
• Average SD ± 0.06 units; typical agreement to literature ± 0.2 units or better
Nov. 05
33
Literature Values
9.37 - 9.56
2.16 - 2.34
9.04 - 9.31
9.02 - 9.29
3.98 - 4.26
3.46 - 5.21
9.78 - 10.13
2.47 - 2.86
7.14 - 7.41
9.89
2.04
NR
9.17 - 9.38
3.35 - 3.74
10.15 - 10.90
9.21 - 9.66
4.06 - 4.51
2.33 - 2.53
4.94 - 5.32
2.27 - 2.29
9.01 - 9.15
3.95 - 4.24
8.35 - 8.60
2.18 - 2.20
8.94 - 9.21
9.99 - 10.47
pKa Analysis of an Aqueous Insoluble Compound
ppt
pH 6.80
MW: 371.5
pH 7.20
Calculated log P: 7.88 ± 0.75
Calculated solubility: 0.05 mg/ml
Measured solubility: 0.01 mg/ml
Calculated values from ACD I-Lab V. 7
Measured value from Avdeef (2003)
ppt
Nov. 05
34
• 24-Pt aqueous pKa Analysis at 30 ppm
(30 mg/ml)
• Precipitation from solution at pH 6.8 – 7.2
• Sample dilution to detection limit = ppt
Cosolvent pKa Extrapolation of Insoluble Compounds
Method:
• pH values of methanol containing buffers were measured using aqueous standards
(ws pH) and converted to s pH values as previously described*
s
• The ss pKa’ values are determined for compounds using 30%, 40%, 50% and 60%
(v/v) methanol-containing buffers
• ss pKa’ values are plotted as a function of solution dielectric constant ( ) and
extrapolated to 0% cosolvent to yield the w pKa’ value (Yasuda-Shedlovsky Method)
w
• Four compounds can be run in parallel over 24 pH values or eight compounds can
be analyzed over 12 pH values (throughput of 2 - 4 compounds/h)
* Roses, M.; Bosch, E. J. Chromatogr., A 2002, 982, 1-30.
Nov. 05
35
pKa Analysis of Tamoxifen in 30% (v/v) Methanol
• Tamoxifen stays in solution when analyzed at ~20 mg/ml in 30% (v/v)
cosolvent buffers
Nov. 05
36
Yasuda-Shedlovsky Extrapolated pKa’ Value for Tamoxifen
• Extrapolated pKa’ value = 8.53 ± 0.07 (n = 9) (I = 50 mM)
• Literature pKa’ value = 8.58 (Avdeef, 2003) (I = 150 mM)
Nov. 05
37
Cosolvent pKa Results for Test Compounds
Compound
# Runs
Extrapolated pKa'
(Yasuda-Shedlovsky)
Amiodarone*
4
8.69
0.27
8.73 - 9.06
Bifonazole
Chlorpromazine*
4
4
6.19
9.18
0.01
0.05
5.72
9.16 - 9.38
Clomipramine
4
9.32
0.03
9.17 - 9.38
5.19
Clotrimazole
4
5.84
0.02
n/a
5.20
Imipramine
12
9.44
0.03
9.21 - 9.66
4.39
Miconazole*
4
6.44
0.03
6.07 - 6.44
0.6
Nortriptyline
4
9.98
0.01
10.10 - 10.19
17.4
4.39
Promethazine
4
8.82
0.02
8.62 - 9.10
11.6
4.05
Quinacrine*
4
7.34
0.04
7.34 - 7.74
9.96
0.08
9.97 - 10.20
SD
Literature Values
Solubility (mg/ml) log P Value
0.005
7.80
1.7
4.77
5.40
Tamoxifen*
9
8.53
0.07
8.48 - 8.71
0.01
5.26
Terfenadine*
4
9.53
0.04
9.21 - 9.86
0.1
5.52
Trimipramine
4
9.24
0.01
9.24
Verapamil
4
8.67
0.02
8.92 - 9.07
9.7
4.33
• Compounds marked (*) required cosolvent due to low solubility; other compounds
listed could be successfully analyzed at low concentrations with aqueous buffers
on the pKa Analyzer PRO™ system [amiodarone could only be analyzed at 50%60% methanol]
• Overall, the extrapolated pKa’ values agree well with available literature values
Nov. 05
38
Summary
• The pKa AnalyzerPRO™ system provides a very rapid method for pKa
measurements of drug compounds
• Reproducible pKa results in good agreement to literature values can be obtained
over a wide range of pH values (1.8 – 11.2)
• Impurities, degradants or UV absorbing counterions can be successfully resolved
from the target compound
• pKa values undetectable by UV spectrophotometry can be successfully measured
• Compound charge can be predicted, allowing detection of closely spaced pKa
values
• A maximum throughput of 24 compounds/h (12 pH points) or 12 compounds/h (24
pH points) can be obtained for aqueous pKa analysis
• Insoluble compounds can be analyzed for pKa using methanol cosolvent buffers
and linear extrapolation to 0% cosolvent
Nov. 05
39
Literature References
Reviews Describing pKa Measurement by CE
Weinberger R: Determination of the pKa of Small Molecules by Capillary Electrophoresis. American
Laboratory 2005, August:36-38.
Jia Z: Physicochemical Profiling by Capillary Electrophoresis. Curr. Pharm. Anal. 2005, 1:41-56.
Poole SK, Patel S, Dehring K, Workman H, Poole CF: Determination of acid dissociation constants by
capillary electrophoresis. J. Chromatogr. A 2004, 1037:445-454.
Papers Describing pKa AnalyzerPRO™ Core Technology
Zhou C, Jin Y, Kenseth JR, Stella M, Wehmeyer KR, Heineman WR: Rapid pKa Estimation Using
Vacuum-Assisted Multiplexed Capillary Electrophoresis (VAMCE) with Ultraviolet Detection. J.
Pharm. Sci. 2005, 94:576-589.
Pang H, Kenseth J, Coldiron S: High-throughput multiplexed capillary electrophoresis in drug
discovery. Drug Discovery Today 2004, 9:1072-1080.
Reference Book for pKa, log P and Solubility Data
Avdeef A: Absorption and Drug Development. Hoboken, NJ: John Wiley & Sons, Inc.; 2003.
Nov. 05
40
Key Physicochemical Parameters
• Solubility
• pKa (Acid-base dissociation constant)
• Partition coefficient (log Pow, log D, …)
• Permeability (Caco-2, PAMPA, …)
• Integrity
Nov. 05
41
Why is log P Important?
Drugs need to have enough lipophilicity in order
to:
• Absorb into the bloodstream and cross biological membranes
• Interact with proteins and/or receptors
• Have a reasonable half-life to carry out their function
However, too much lipophilicity in a drug can:
• Limit the mode of delivery
• Limit the release of the drug from the formulation
• Increase potential toxicity
The majority of marketed drugs possess log Pow
values between 1 and 5
Nov. 05
42
Experimental Design for MCE-UV log P Screening
• Multiplexed, microemulsion electrokinetic chromatography (MEEKC) was employed
for indirect log Pow evaluation.
• MEEKC is based on the differential partitioning of solutes between an aqueous phase
and an immiscible microemulsion (ME) phase comprised of oil droplets + surfactant
–
+
• More lipophilic compounds favor the ME phase and migrate slower
• Order of migration: DMSO (EOF marker), solute, dodecylbenzene (ME marker)
Poole, S. K.; Durham, D.; Kibbey C. J. Chromatogr. B 2000, 745, 117-126.
Figure adapted from http://www.ceandcec.com (Author Kevin Altria)
Nov. 05
43
Multiplexed MEEKC Electropherogram for
Six-Component log Pow Standard Mixture
4
DMSO
(EOF Marker)
5
2
Dodecylbenzene
(ME Marker)
6
3
1
Standards: 1. Pyrazine, 2. Benzamide, 3. Nicotine, 4. Quinoline, 5.
Naphthalene, 6. Imipramine
Nov. 05
44
Typical Calibration Plot Constructed from a M-MEEKC Run
• Averaged (n = 4) log k’ values for the six standards were used to
construct the calibration plot
Nov. 05
45
MCE-UV log Pow Screening: 96-Capillary MEEKC Data
Order of migration in each capillary is DMSO, Solute, Dodecylbenzene
Nov. 05
46
Long Term (> 8 months) Reproducibility of log Pow Values
Nov. 05
Solute
n
MMEEKC log k'
avg. ± SD
%RSD
MMEEKC log Pow
avg. ± SD
%RSD
Lit. log P OW
D log P OW
acebutolol
1-aminonaphthalene
2-aminopyridine
aniline
anthracene
benzamide
caffeine
4-chloroaniline
chlorpromazine
chlorthalidone
coumarin
3,5-dimethylaniline
ethyl pethylbenzene
ethylbenzoate
hydroquinine
imipramine
indazole
lidocaine
2,4-lutidine
3,5-lutidine
α-methylbenzylamine
2-methylbenzylamine
3-methylbenzylamine
naphthalene
nefopam
nicotine
nitrobenzene
phenanthrene
phenylacetate
pyrazine
pyrene
pyrilamine
pyrimidine
quinoline
tetracaine
42
37
34
36
6
50
35
36
7
38
26
15
36
6
38
42
52
46
36
12
14
8
12
9
53
32
53
35
13
36
53
8
35
36
53
38
0.41 ± 0.03
0.71 ± 0.03
-0.41 ± 0.01
-0.12 ± 0.02
2.09 ± 0.10
-0.17 ± 0.02
-0.59 ± 0.02
0.62 ± 0.03
2.21 ± 0.04
0.07 ± 0.02
0.22 ± 0.02
0.57 ± 0.03
0.40 ± 0.09
1.49 ± 0.01
0.97 ± 0.04
1.26 ± 0.06
1.86 ± 0.08
0.38 ± 0.03
0.89 ± 0.04
0.31 ± 0.01
0.42 ± 0.02
0.24 ± 0.03
0.34 ± 0.02
0.47 ± 0.02
1.36 ± 0.07
1.14 ± 0.05
0.18 ± 0.02
0.40 ± 0.02
1.92 ± 0.06
0.18 ± 0.02
-0.96 ± 0.01
2.21 ± 0.23
1.18 ± 0.06
-1.05 ± 0.02
0.54 ± 0.03
1.42 ± 0.07
7.32
4.23
2.44
16.67
4.78
11.76
3.39
4.84
1.81
28.57
9.09
5.26
22.50
0.67
4.12
4.76
4.30
7.89
4.49
3.23
4.76
12.50
5.88
4.26
5.15
4.39
11.11
5.00
3.13
11.11
1.04
10.41
5.08
1.90
5.56
4.93
1.80 ± 0.04
2.31 ± 0.03
0.41 ± 0.01
0.90 ± 0.02
4.54 ± 0.17
0.81 ± 0.02
0.11 ± 0.07
2.16 ± 0.04
4.74 ± 0.06
1.22 ± 0.05
1.48 ± 0.05
2.04 ± 0.05
1.78 ± 0.15
3.54 ± 0.01
2.75 ± 0.04
3.23 ± 0.10
4.23 ± 0.08
1.75 ± 0.08
2.62 ± 0.03
1.60 ± 0.03
1.77 ± 0.03
1.48 ± 0.04
1.65 ± 0.03
1.86 ± 0.04
3.40 ± 0.09
3.04 ± 0.04
1.40 ± 0.02
1.79 ± 0.04
4.29 ± 0.11
1.41 ± 0.03
-0.51 ± 0.03
4.75 ± 0.38
3.11 ± 0.05
-0.67 ± 0.03
2.00 ± 0.04
3.52 ± 0.10
2.22
1.30
2.44
2.22
3.74
2.47
63.64
1.85
1.27
4.10
3.38
2.45
8.43
0.28
1.45
3.10
1.89
4.57
1.15
1.88
1.69
2.70
1.82
2.15
2.65
1.32
1.43
2.23
2.56
2.13
5.88
8.00
1.61
4.48
2.00
2.84
1.71
2.25
0.49
0.9
4.45
0.64
-0.07
1.88
5.19
0.85
1.39
2.17
1.86
3.15
2.64
3.43
4.42
1.77
2.26
1.9
1.78
1.49
1.62
1.62
3.3
3.05
1.17
1.85
4.46
1.49
-0.26
4.88
3.27
-0.4
2.03
3.73
0.09
0.06
-0.08
0
0.09
0.17
0.18
0.28
-0.61
0.37
0.09
-0.13
-0.08
0.39
0.11
-0.2
-0.19
-0.02
0.36
-0.3
-0.01
-0.01
0.03
0.24
0.1
-0.01
0.23
-0.06
-0.17
-0.08
-0.25
-0.13
-0.16
-0.3
-0.03
-0.21
47
Comparison of Sample Throughput
Among Indirect log Pow Methods
Method
Average Analysis
Time per Sample
(min)
Approximate
Throughput
(samples/h)
Reference
RP-HPLC
20
3
1,2
MEKC
15
4
3
MEEKC
18-23
30
2-3
(100 per week)
2
4
5
6
M-MEEKC
1.25
46*
7
(pKa AnalyzerPRO™)
* 4 of 96 capillaries are used for the standard mixture
Nov. 05
1.
Lombardo F.; Shalaeva M.Y.; Tupper K.A.; Gao F.; Abraham M.H. J Med Chem 2000, 43, 2922-2928.
2.
Lombardo F.; Shalaeva M.Y.; Tupper K.A.; Gao F. J Med Chem 2001, 44, 2490-2497.
3.
Smith J.T.; Vinjamoori D.V. J Chromatogr B 1995, 669, 59-66.
4.
Mrestani Y.; Neubert R.H.H.; Krause A. Pharm Res 1998, 15, 799-801.
5.
Kibbey C.E.; Poole S.K.; Robinson B.; Jackson J.D.; Durham D. J Pharm Sci 2001, 90, 1164-1175.
6.
Jia Z.; Mei L.; Lin F.; Huang S.; Killion R.B. J Chromatogr A 2003, 1007, 203-208.
7.
Wong, K-S; Kenseth J.R.; Strasburg, R.S. J Pharm Sci 2004, 93, 916-931.
48
Summary – log Pow
• Log Pow can be estimated with good correspondence
using micro-emulsion electrokinetic chromatography
(MEEKC)
• This MEEKC method has been adapted to the pKa
AnalyzerPRO™, enabling rapid screening of log Pow
values for target drug candidates (46 samples/hr)
• Poorly soluble drug candidates can be analyzed using
co-solvent method
• Calculation and reporting of results is easily
accomplished with dedicated software
Nov. 05
49
cePRO-9600™ System
Nov. 05
50
Robotic Arm for Unattended Operation
Nov. 05
51
pKa AnalyzerPRO™
Discussion
Nov. 05
53