Enhanced Physico-Chemical Characterization of Candidate

Compounds

using the

pKa AnalyzerPRO™

Nov. 05 2

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 3

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 4

Why Physicochemical Properties?

• Many physicochemical assessments are labor-intensive, 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 5

Basic Researc

h

TargetIdentificatio

n

LeadIdentificatio

n

TargetValidatio

n

LeadOptimizatio

n

Disease model hypotheses

ExploratoryResearch

Characterize genes & proteins as candidates in the disease process

Discriminate valid from invalid biological targets

HTS Screening of leads

Evaluate leads for optimal pharmacologic efficacy & selectivity

Clinical

Trials

1-3 Years 0.5-1 Year 1-2 Years

10,000 500 10 1

L

E

A

D

S

Market

6-8 Years

Drug Discovery Process

90-95% of Development Cost occurs in the Clinical Trials Phase

Nov. 05 6

Basic Researc

h

TargetIdentificatio

n

LeadIdentificatio

n

TargetValidatio

n

LeadOptimizatio

n

Disease model hypotheses

ExploratoryResearch

Characterize genes & proteins as candidates in the disease process

Discriminate valid from invalid biological targets

HTS Screening of leads

Evaluate leads for optimal pharmacologic efficacy & selectivity

Clinical

Trials

1-3 Years 0.5-1 Year 1-2 Years

Market

6-8 Years

Drug Discovery Process

L

E

A

D

S

10,000 500 3 1

With better early characterization of leads, significant cost savings are

achieved

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

Key Physicochemical Parameters

• Solubility

• pKa (Acid-base dissociation constant)

• Partition coefficient (log Pow, log D, …)

• Permeability (Caco-2, PAMPA, …)

• Integrity

Nov. 05 9

pKa : Acid-base Dissociation Constant

• The pKa value is a measure of the ionization ability of a weak acid or base:

HA H+ + A- Ka = [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 10

pKa : Acid-base Dissociation Constant

N

O

H 3C

HO

N

Quin ine

N

O

H 3C

HO

N

H +N

OH 3C

HON

H +

H +

Nov. 05 11

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 12

0 1262 4 8 10

stomach

blood

small intestines

vinegar orangejuice

milk bleachcola

pharmaceutical products

colonurine

Biologically Relevant pH Range for Pharmaceutical Products

Nov. 05 13

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 14

Technology Overview

• CE-based platform; application of high voltage across capillary filled with aqueous-based buffer

• Narrow bore, fused silica capillaries (75 m i.d., 150 m 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

Time

+ -N-Bulk Flow: EOF + Vacuum

UV

+

-

N

+ –

Nov. 05 15

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 16

Attributes of the pKa AnalyzerPRO™ for pKa AnalysisHigh 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 g per sample well required for analysis; typical sample well volume of 50 l; 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 17

pKa AnalyzerPRO™ System SpecificationspKa 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 g/ml (ppm) depending on chromophore; typical working concentration 50 - 100 g/ml

Sample Volume Required: Typical volume 50 l/well (minimum volume 20 l/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 18

pKa AnalyzerPRO™: Some Equations for pKa Measurement

Effective Mobility (Meff)

Ltot Leff

V(1/ta – 1/tm)Meff = Meff =

Z

6r

Ltot = Total length of capillaryLeff = Length to detectorV = Applied voltageta = Migration time of analytetm = Migration time of neutral marker (DMSO)

Z = fractional charge on analyte = viscosity of mediumr = hydrodynamic radius of analyte

Relationships between Meff, pH, and Apparent pKa

Meff =Mb10-pH

10-pKa + 10-pHMonobase:

Ma10-pKa

10-pKa + 10-pHMeff =Monoacid:

Ma, Mb = Meff of completely ionized species

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 19

Technology Overview

• Effective mobility determined from the migration time of the solute

• 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)

Time

+ -N

+ -Bulk Flow: EOF + Vacuum

UV

+

-

N

+ –

Nov. 05 20

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 21

Sample and Buffer Tray Configuration for pKa Analysis

The marked well (E7) corresponds to benzoic

acid analyzed at pH 6.84

Sample Tray

122 3 4 5 6 7 8 9 10 111

A

H

B

C

D

E

F

G

122 3 4 5 6 7 8 9 10 111

A

H

B

C

D

E

F

G

Acyclovir

Acyclovir4-Aminopyridine

4-Aminopyridine

Benzoic AcidBenzoic Acid

QuinineQuinine

Analyte

Inlet Buffer Tray

2.07

2.89

3.42

4.41

5.21

6.01

6.84

7.58

8.41

9.19

10.0

010

.83

pH

12 pH Point pKa Analysis (8 Samples)

Nov. 05 22

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 23

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 24

Results for 4-Aminopyridine (monobase)

• 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.

pKa

Nov. 05 25

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 26

Results for Benzoic Acid (monoacid)

• pKa value = 4.07• Charge (benzoic acid) = -1.09

Nov. 05 27

Results for Quinine (dibase)

• pKa values = 4.29, 8.51• Charge (quinine) = +1.91

Nov. 05 28

Results for Acyclovir (monoacid/monobase zwitterion)

• pKa values = 2.09, 9.17• Charge (acyclovir) = +0.60; -1.00

Nov. 05 29

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 30

pKa Results Data Table

• Each saved pKa result is entered into a sortable data table for easy access to data

Nov. 05 31

• pKa Values = 2.21, 8.79, 10.08• Charge = +0.71, -1.62

pKa Analysis of Tyrosine (monobase/diacid zwitterion)

The –COOH pKa value was not observable by UV spectrophotometry

Nov. 05 32

pKa Analysis of a Procaine/4-Aminobenzoic Acid Sample

• A 4-aminobenzoic acid hydrolysis impurity (20%) of procaine was present• The pKa values for both species were determined in the same experiment

4-ABA pKa’ Values: 2.37, 4.38

Procaine pKa’ Values: 2.20, 9.04

++

-300

-250

-200

-150

-100

-50

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11

pH Value

Eff

ecti

ve M

ob

ility

(x

106

cm2 /

V•s

) Procaine

4-ABApH 1.78 (Top Left) – pH 6.46 (Bottom Right)

pH 6.82 (Top Left) – pH 11.20 (Bottom Right)

**

**

Nov. 05 33

Some pKa Results Obtained with the pKa Analyzer PRO™

• 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

Compound MW Type n pK a Analyzer PRO ™ pKa' (I = 50 mM) SD Literature Values

Acebutolol 336 B 15 9.51 0.09 9.37 - 9.56Acyclovir 225 A/B 13 2.19 0.03 2.16 - 2.34

9.20 0.01 9.04 - 9.314-Aminopyridine 94 B 8 9.22 0.03 9.02 - 9.29

Benzoic Acid 122 A 13 4.07 0.03 3.98 - 4.26Betahistine 136 2B 11 3.88 0.02 3.46 - 5.21

9.97 0.04 9.78 - 10.13Cefadroxil 363 2A/B 13 2.57 0.03 2.47 - 2.86

7.21 0.04 7.14 - 7.419.70 0.05 9.89

Cefuroxime 423 2A 9 2.12 0.01 2.0411.19 0.15 NR

Clomipramine 315 B 9 9.56 0.04 9.17 - 9.38Furosemide 331 2A 24 3.61 0.05 3.35 - 3.74

10.39 0.09 10.15 - 10.90Imipramine 280 B 5 9.60 0.03 9.21 - 9.66

Indomethacin 358 A 13 4.02 0.08 4.06 - 4.51Piroxicam 331 A/B 8 1.87 0.05 2.33 - 2.53

5.35 0.06 4.94 - 5.32Procaine 300 2B 16 2.13 0.09 2.27 - 2.29

9.06 0.04 9.01 - 9.15Quinine 324 2B 18 4.33 0.05 3.95 - 4.24

8.50 0.06 8.35 - 8.60Tyrosine 181 2A/B 10 2.23 0.02 2.18 - 2.20

8.85 0.08 8.94 - 9.2110.05 0.07 9.99 - 10.47

Nov. 05 34

pKa Analysis of an Aqueous Insoluble Compound

MW: 371.5

Calculated log P: 7.88 ± 0.75

Calculated solubility: 0.05 g/ml

Measured solubility: 0.01 g/ml

Calculated values from ACD I-Lab V. 7Measured value from Avdeef (2003)

ppt

ppt pH 7.20

pH 6.80

• 24-Pt aqueous pKa Analysis at 30 ppm (30 g/ml)

• Precipitation from solution at pH 6.8 – 7.2• Sample dilution to detection limit = ppt

Nov. 05 35

Cosolvent pKa Extrapolation of Insoluble Compounds

* Roses, M.; Bosch, E. J. Chromatogr., A 2002, 982, 1-30.

Method:• pH values of methanol containing buffers were measured using aqueous standards

( pH) and converted to pH values as previously described*

• The pKa’ values are determined for compounds using 30%, 40%, 50% and 60%

(v/v) methanol-containing buffers

• pKa’ values are plotted as a function of solution dielectric constant ( ) and

extrapolated to 0% cosolvent to yield the pKa’ value (Yasuda-Shedlovsky Method)

• 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)

ws

ss

ss

ss

ww

Nov. 05 36

pKa Analysis of Tamoxifen in 30% (v/v) Methanol

• Tamoxifen stays in solution when analyzed at ~20 g/ml in 30% (v/v) cosolvent buffers

Nov. 05 37

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 38

Cosolvent pKa Results for Test Compounds

• 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

Extrapolated pKa'

Compound # Runs (Yasuda-Shedlovsky) SD Literature Values Solubility (g/ml) log P Value

Amiodarone* 4 8.69 0.27 8.73 - 9.06 0.005 7.80

Bifonazole 4 6.19 0.01 5.72 4.77

Chlorpromazine* 4 9.18 0.05 9.16 - 9.38 1.7 5.40

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

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

Nov. 05 39

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 40

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 41

Key Physicochemical Parameters

• Solubility

• pKa (Acid-base dissociation constant)

• Partition coefficient (log Pow, log D, …)

• Permeability (Caco-2, PAMPA, …)

• Integrity

Nov. 05 42

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 43

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

Poole, S. K.; Durham, D.; Kibbey C. J. Chromatogr. B 2000, 745, 117-126.

• More lipophilic compounds favor the ME phase and migrate slower

• Order of migration: DMSO (EOF marker), solute, dodecylbenzene (ME marker)

Figure adapted from http://www.ceandcec.com (Author Kevin Altria)

+ –

Nov. 05 44

Multiplexed MEEKC Electropherogram for Six-Component log Pow Standard Mixture

DMSO(EOF Marker)

Dodecylbenzene(ME Marker)

1

2

3

4

5

6

Standards: 1. Pyrazine, 2. Benzamide, 3. Nicotine, 4. Quinoline, 5. Naphthalene, 6. Imipramine

Nov. 05 45

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 46

MCE-UV log Pow Screening: 96-Capillary MEEKC Data

Order of migration in each capillary is DMSO, Solute, Dodecylbenzene

Nov. 05 47

Long Term (> 8 months) Reproducibility of log Pow ValuesMMEEKC log k' MMEEKC log Pow

Solute n avg. ± SD %RSD avg. ± SD %RSD Lit. log P OW log P OW

acebutolol 42 0.41 ± 0.03 7.32 1.80 ± 0.04 2.22 1.71 0.091-aminonaphthalene 37 0.71 ± 0.03 4.23 2.31 ± 0.03 1.30 2.25 0.06

2-aminopyridine 34 -0.41 ± 0.01 2.44 0.41 ± 0.01 2.44 0.49 -0.08aniline 36 -0.12 ± 0.02 16.67 0.90 ± 0.02 2.22 0.9 0

anthracene 6 2.09 ± 0.10 4.78 4.54 ± 0.17 3.74 4.45 0.09benzamide 50 -0.17 ± 0.02 11.76 0.81 ± 0.02 2.47 0.64 0.17

caffeine 35 -0.59 ± 0.02 3.39 0.11 ± 0.07 63.64 -0.07 0.184-chloroaniline 36 0.62 ± 0.03 4.84 2.16 ± 0.04 1.85 1.88 0.28chlorpromazine 7 2.21 ± 0.04 1.81 4.74 ± 0.06 1.27 5.19 -0.61chlorthalidone 38 0.07 ± 0.02 28.57 1.22 ± 0.05 4.10 0.85 0.37

coumarin 26 0.22 ± 0.02 9.09 1.48 ± 0.05 3.38 1.39 0.093,5-dimethylaniline 15 0.57 ± 0.03 5.26 2.04 ± 0.05 2.45 2.17 -0.13

ethyl p- 36 0.40 ± 0.09 22.50 1.78 ± 0.15 8.43 1.86 -0.08ethylbenzene 6 1.49 ± 0.01 0.67 3.54 ± 0.01 0.28 3.15 0.39ethylbenzoate 38 0.97 ± 0.04 4.12 2.75 ± 0.04 1.45 2.64 0.11hydroquinine 42 1.26 ± 0.06 4.76 3.23 ± 0.10 3.10 3.43 -0.2imipramine 52 1.86 ± 0.08 4.30 4.23 ± 0.08 1.89 4.42 -0.19

indazole 46 0.38 ± 0.03 7.89 1.75 ± 0.08 4.57 1.77 -0.02lidocaine 36 0.89 ± 0.04 4.49 2.62 ± 0.03 1.15 2.26 0.36

2,4-lutidine 12 0.31 ± 0.01 3.23 1.60 ± 0.03 1.88 1.9 -0.33,5-lutidine 14 0.42 ± 0.02 4.76 1.77 ± 0.03 1.69 1.78 -0.01

α-methylbenzylamine 8 0.24 ± 0.03 12.50 1.48 ± 0.04 2.70 1.49 -0.012-methylbenzylamine 12 0.34 ± 0.02 5.88 1.65 ± 0.03 1.82 1.62 0.033-methylbenzylamine 9 0.47 ± 0.02 4.26 1.86 ± 0.04 2.15 1.62 0.24

naphthalene 53 1.36 ± 0.07 5.15 3.40 ± 0.09 2.65 3.3 0.1nefopam 32 1.14 ± 0.05 4.39 3.04 ± 0.04 1.32 3.05 -0.01nicotine 53 0.18 ± 0.02 11.11 1.40 ± 0.02 1.43 1.17 0.23

nitrobenzene 35 0.40 ± 0.02 5.00 1.79 ± 0.04 2.23 1.85 -0.06phenanthrene 13 1.92 ± 0.06 3.13 4.29 ± 0.11 2.56 4.46 -0.17phenylacetate 36 0.18 ± 0.02 11.11 1.41 ± 0.03 2.13 1.49 -0.08

pyrazine 53 -0.96 ± 0.01 1.04 -0.51 ± 0.03 5.88 -0.26 -0.25pyrene 8 2.21 ± 0.23 10.41 4.75 ± 0.38 8.00 4.88 -0.13

pyrilamine 35 1.18 ± 0.06 5.08 3.11 ± 0.05 1.61 3.27 -0.16pyrimidine 36 -1.05 ± 0.02 1.90 -0.67 ± 0.03 4.48 -0.4 -0.3quinoline 53 0.54 ± 0.03 5.56 2.00 ± 0.04 2.00 2.03 -0.03tetracaine 38 1.42 ± 0.07 4.93 3.52 ± 0.10 2.84 3.73 -0.21

Nov. 05 48

MethodAverage 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™)

Comparison of Sample Throughput Among Indirect log Pow Methods

* 4 of 96 capillaries are used for the standard mixture

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.

Nov. 05 49

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 50

cePRO-9600™ System

Nov. 05 51

Robotic Arm for Unattended Operation

CONFIDENTIAL

Frost and Sullivan Award Winner

COMBISEP, INC. RECEIVES THE 2005 PRODUCT DIFFERENTIATION LEADERSHIP AWARD FROM FROST

AND SULLIVANFrost & Sullivan presented the 2005 Award for Product Differentiation Leadership in the U.S. absorption, distribution, metabolism, andexcretion/toxicology (ADME/Tox) market to CombiSep, Inc. for thecePRO 9600. The product enables a much higher throughput than traditional methods for measurement of the key physicochemical properties pKa and logP. These properties have typically been measured early in the lead optimization process, but only for a limited number of compounds due to the low throughput. Solubility, pKa and logP are three interrelated properties, which are critical in determining bioavailability; thus, these analyses would ideally be run as early as possible.

CONFIDENTIAL

Co-Winner Best Poster at Tides

CombiSep and IDT Poster Co-Winner Best Poster Tides 2005 Conference

The poster titled “Comparisons between Multiplexed, Absorbance-Based Capillary Electrophoresis, Capillary Electrophoresis, and Ion Exchange Chromatography for Analysis of n-1 Oligonucleotide Impurities” by Wei Wei, Ho-ming Pang, Dennis Tallman, and Jeremy Kenseth of CombiSep, Inc and Lisa Bogh of Integrated DNA Technology was recently selected as the co-winner of the best poster at Tides 2005. The Tides Conference is an industry event for manufacturing and development of oligonucleotide and peptide products. The meeting was held May 1st – 5th, 2005 at the Boston Convention & Exhibition Center.

The poster award was sponsored by BioProcess International. The selection criteria was based on novelty, applicability, and clarity of data presented.

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