Method development and validation of capillary electrophoresis: A practical aspect L. Suntornsuk

Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Mahidol University, 447 Sri-Ayudhaya Rd., Rajathevee, Bangkok 10400, Thailand pylll@mahidol.ac.th

The current review illustrates the method development and validation of capillary

electrophoresis (CE) from experiences of the author research group. Various examples including

drug monitoring, pharmaceutical, and natural product analyses are described. The author

emphasizes that no specific CE condition is applicable for all problems. Analytes’ physico-

chemical properties (e.g., solubility, dissociation constant, polarity, absorptivity, etc.) and their

stability are major consideration. Sample matrices (e.g., biological fluid and tissues, foods,

medicinal plants, etc.) can usually complicate an analysis and should be accounted for before a

method is developed. Consequently, sample pretreatment/preparation procedures have to be

carefully optimized as well. Successes in CE separation involve adjustments of both chemical

(e.g., background electrolyte concentrations and pH, organic solvents, electro-osmotic flow

modifiers, additives, etc.) and instrumental (e.g., sample loading techniques, temperature,

voltage, capillary dimension, detectors, etc.) factors. Optimization of these factors can be

achieved by univariate approach or statistical experimental design. The final optimum CE

condition should be justified by acceptable analytical parameters (e.g., resolution, tailing factor,

number of theoretical plate, total analysis time, etc.). Method validation is a follow up process,

which should be carried out according to the predetermined protocol and criteria of performance.

These criteria normally include specificity, linearity and range, accuracy, precision, and

robustness. BGE and sample solution stability may be required in certain cases and system

suitability should be carried out for method transfer.

1. INTRODUCTION

Capillary electrophoresis (CE) is now a well

established analytical method, which has

numerous applications in separation science

(Marina, 2005; Altria, 1998; Landers and Oda,

1997; Westan and Brown, 1997; Kuhn and

Hoffstetter-Kuhn, 1993; Altria et al., 2006;

Morzunoval, 2006). The method has a long

history of developments since 1886 by

integrating unique features of different

techniques such as the principle of gel

electrophoresis, the fused silica capillary of gas

chromatography (GC) and the high sensitive

detectors of high performance liquid

chromatography (HPLC) (Landers and Oda,

1997). The first commercial CE instrument was

available in 1989 (Landers and Oda, 1997) and

since then, this technique has played important

roles in solving analytical problems, especially

in the human genome project (HGP) (Dovichi

and Zhang, 2000; Collins et al., 1998).

CE separation is based on different

migration of solutes in an electric field and

electrophoresis is performed in narrow-bore

capillaries filled with background electrolyte

(BGE) (Fig. 1). In contrast to paper, agarose

and polyacrylamide gel, electrophoresis in a

capillary can use high voltage (up to 800 V/cm)

due to physical properties of fused silica

capillaries. Additionally, a large surface area to

volume ratio of a capillary provides efficient

heat dissipation than other separating media.

Small amounts of samples and BGE (nanoliter

per injection) are usually required due to the

small dimension of a capillary (typically 25-75

cm long x 25-75 µm inner diameter). CE

instrument can be fully automated with on-

capillary detection, which consumes less time

and labor compared to gel electrophoresis.

Importantly, CE provides high separation

efficiency with number of theoretical plate (N)

> 10,000 and various modes that enable the

analyses of different classes of compounds.

In principle, when analytes are separated by

CE, they migrate with different mobilities under

an electric field. Their mobilities are influenced

by their sizes, charges and degree of ionization,

viscosity, temperature and dielectric constant of

the BGE. In addition to the electrophoretic

migration, electro-osmotic flow (EOF) is a

main driving force in CE that enables the

migration of analytes along the capillary. The

EOF is generated by the multiple ionization of

silanol groups on the inner surface of a silica

capillary. These silanol groups possess

isoelectric point (pI) of 1.5 that makes them

easily ionized at any pHs above 3.0 (Righett et

al., 2001; Camilleri, 1998). Controlling EOF

has pronounced effects on the separation

efficiency and selectivity. Several factors (e.g.,

pH, concentration/ ionic strength of the BGE,

additives, capillary coatings, electric field,

temperature, etc.) can influence the magnitude

and direction of the EOF (Pancorbo et al.,

2005). Advantages of the EOF include a flat

flow profile which provides narrow peaks with

high symmetry and number of theoretical

plates, and simultaneous separation of cationic,

anionic and neutral species. Similar to HPLC,

resolution, efficiency, selectivity and peak

dispersion are considered as important

analytical parameters in CE. These parameters

can be improved by manipulating the electrode

polarity, voltage, temperature, capillary

dimension, BGE properties, temperature,

sample preparation and loading.

2. MATERIALS AND METHODS

2.1. Instrumentation

The setup of a CE instrument generally

consists of a capillary, a voltage supply,

electrodes, sample and liquid handling system,

cooling system and a detector (Fig. 2).

Capillaries are mainly made of fused silica or

teflon with a dimension of 20-100 cm in length

x 20-200 µm inner diameter and an outer

diameter of 300-400 µm. Capillaries should be

regularly pre-conditioned or washed to remove

residual adsorbates from the capillary wall and

to prevent sample cross contamination.

Voltage supply can be operated in a positive or

negative polarity, in a range of 15-30 kV. An

autosampler is used for delivery of samples and

BGE. Samples can be introduced to the

capillary by hydrodynamic or electrokinetic

injection. Hydrodynamic injection is achieved

by applying pressure at the inlet or vacuum at

the outlet or by siphon effect (elevating the

inlet). Electrokinetic injection is also

performed for sample introduction by applying

a low voltage (3-5 times lower than the

separating voltage, for example 5-10 kV)

during an injection (Olechno and Nolan, 1996).

In cases of low concentration samples,

isotachophoresis injection or sample stacking is

recommended prior to CE separation in order to

enhance the sensitivity. Cooling system either

air or liquid cooling, is an integral part of the

CE instrument to maintain a constant

temperature (± 0.1°C) during an analysis.

UV/diode array (DAD) spectrophotometer,

spectrofluorometer and electrochemical

detector are commonly used as on-capillary

detectors in CE, whereas mass spectrometer

(MS) can be used as an external detector. On-

capillary detection provides sharp and

symmetric peak shape since sample band

broadening is minimal.

2.2. Modes of Separation

A major advantage of CE is that various

modes are available for the analyses of different

analytes (Weston and Brown, 1997; Kuhn and

Hoffstetter-Kuhn, 1993). Capillary zone

electrophoresis (CZE) is the simplest and most

versatile CE mode, which is based on distinct

mobilities of analytes under an electric field.

CZE can be applied for the analyses of organic

and inorganic species, amino acids, peptides,

proteins and enantiomers. Micellar

electrokinetic chromatography (MEKC) is a

hybrid of electrophoresis and chromatography.

Surfactants at above critical micelle

concentrations (CMC) are added into the BGE

to form micelles and are employed as

separating media. MEKC enables the

simultaneous separation of neutral as well as

ionic species. Thus, this mode has numerous

applications in pharmaceutical analysis and

other small organic molecules. Capillary gel

electrophoresis (CGE) is well known for the

separation of biopolymers such as proteins and

nucleic acids. In this mode, capillaries are

filled with gel (either cross-linked

polyacrylamide or agarose), which acts as

molecular sieve. Consequently, biopolymers

are separated according to their size. Capillary

isoelectric focusing (CIEF) is useful for

separation of zwitter ions (e.g. amino acids,

peptides and proteins) which contain both

positive and negative charges in their

molecules. Separation mechanism depends on

different isoelectric points of analytes.

Capillary isotachophoresis (CITP) is known as

“moving boundary” where analytes are

separated as continuous zones that migrate at

the same velocity. Migration of analytes is

based on differences in their conductivity

according to the conductivity of the leading

electrolyte (high conductivity at the outlet) and

the terminating electrolyte (low conductivity at

the inlet). CITP normally serves as pre-

concentration step prior CE separation.

Most of the mentioned CE modes employ

aqueous buffer as the BGE. However, non-

aqueous BGE can also be used. Non-aqueous

CE (NACE) has been developed for separation

of non-polar and water-insoluble compounds

which can be easily absorbed on the capillary

wall. Organic solvents such as acetonitrile,

methanol, ethanol and mixtures of these

solvents are used for BGE preparation. Due to

the physico-chemical properties of these

solvents, separation selectivity and analyte

solubility and stability can be improved.

Microemulsion electrokinetic chromatography

(MEEKC) is another CE mode that can be an

alternative method for the separation of a wide

range of compounds. In MEEKC,

microemulsion droplets consisting of oil and the

aqueous phase stabilized by surfactants and co-

surfactants, are used as the pseudo-stationary

phase. MEEKC offers a chromatographic

partition of analytes between the pseudo-

stationary phases and the aqueous BGE which

allows the simultaneous separation of neutral

and ionic species. Chiral capillary

electrophoresis (CCE) is a valuable mode for

separation of chiral drugs of which different

enantiomers possess different pharmacological

activities or toxicity. Indirect CCE can be

simply performed by adding chiral selectors

into the BGE to sterioselectively interact with

each enantiomer. Separation mechanism in

indirect CCE depends upon the chiral selectors

used. For example, inclusion complex occurs

when cyclodextrin or chiral crown ether are

employed. Other mechanisms include ligand

exchange, chiral micelles and affinity

interaction.

2.3. Method Development

The ultimate gold in the method

development is to obtain an efficient and

reliable method that provides baseline

separation of all analytes with high resolution

(Rs), theoretical plate (N) and symmetric peaks

in reasonable times. Rs indicates how well the

two closest peaks are separated from each other

and the value should be greater than 1.5. N

represents the separation efficiency and, for CE,

N is generally in the range of 104-10

5. Tailing

factor (TF) shows the peak symmetry and,

ideally, it should close to 1.0. Rs, N and TF are

calculated from equations 1-3.

Rs =

2(t2-t1) (1)

w1 + w2

T = w0.05 (2) 2f

N = 5.54( t

)2 (3) w1/2

where tx is migration time and wx is baseline

peak width (in time) of analyte x, w0.05 and w1/2

is peak width at 5% and at half height,

respectively, and f is peak width from the

leading edge of peak to the intercept of a

perpendicular line dropped from the peak

maximum to the base.

Developments of a CE method involve

several factors including electrode polarity,

BGE (e.g., type, concentration and pH),

voltage, temperature, capillary dimension and

sample loading method. Varying these factors

causes either unidirectional change or

bidirectional change in analytical parameters

(e.g., resolution (Rs), number of theoretical

plate (N), tailing factor (TF), migration time

(tm), etc). For instance, increasing the voltage

elevates temperature and current, enhances

EOF, but might decrease/increase resolution

and sensitivity. While increasing of BGE

viscosity reduces EOF and mobilities, hence,

increase the migration time.

Optimization of CE condition can be

performed by univariate approach or statistical

experimental designs (SED). The first

approach, in which each factor is varied one at a

time is simple but can be time consuming. In

addition, interaction of the factors can not be

determined by this approach. SED increasingly

plays an important role in analytical method

development. Effects of different factors can be

simultaneously optimized and interaction of

each factor can be inferred; thus, time and the

number of experiments are greatly reduced.

Central composite design (CCD), factorial

design (FD) and fractional factorial design

(FFD) are common tools for SED in CE

optimization.

FD was employed for the development of

NACE for the separation of three β-agonists

(i.e., clenbuterol, salbutamol and terbutaline)

(Anurukvorakun et al., 2006). Effects of BGE

ionic strength, amount of acetonitrile, injection

time, voltage and temperature on key responses

(i.e., Rs, N, TF and total tm) were investigated.

Model equations for the responses could be

derived from the data of 32 experiments and

revealed that BGE had impacts on Rs, TF and

total tm; whereas, the amount of acetonitrile

influenced N, TF and total tm. Importantly,

BGE and acetonitrile had strong interaction

with each other more than other factors. The

final optimization offered the baseline

separation of the three analytes in less than 12

min (Fig. 3). Other examples include the use of

full FD for the analysis of antihistamine

(Capella-Peiro et al., 2006), angiotensin-

converting enzyme inhibitors (Hillaert et al.,

2002) zinc, sodium, calcium and magnesium in

water (Jurado-Gonzalae et al., 2003), Plackett-

Burman full FD and CCD for determination of

impurities in peptide (Brunnkvist et al., 2004)

and CCD for analysis of flavonoids in

Epimedium (Liu et al., 2001).

2.4. Components and Processes of Method

Development

Prior to development of an analytical

method, physico-chemical properties of

analytes, including dissociation constants,

isoelectric point, solubility, purity and stability,

should be determined. Additional information

of analytes, including sample matrices,

interferences, UV absorptivity and whether the

analyte is a major or minor component in the

sample, should be acquired to facilitate the

development process. Last but not least,

successes of development of an analytical

method require competent analysts, proper uses

of reference standards, reference materials or

certified reference materials, suitable selection

of methods and well maintained equipment and

instrument.

Rules of thumb for development processes

of CE methods include selection of appropriate

BGE composition, capillary dimension,

temperature, voltage and detection technique.

Despite these variables, general guidelines of

CE condition for analysis of small molecules,

peptide, protein and nucleic acid are well

suggested in Ref. 3. In summary, the

development a CE method should be carefully

and systematically investigated for different

kind of analytes since one recipe can not fit all.

2.5. Method Validation

Method validation is a testing procedure to

check whether a method is appropriate for its

intended uses. The testing is performed

according to the predetermined protocol and the

results must meet the predetermined criteria of

performance. Method validation of a CE

method and HPLC is performed in a similar

manner in order to verify that the method has

acceptable precision and accuracy. For method

transfer, robustness, injection precision as well

as stability of BGE and sample solution should

be tested. Following are recommended criteria

of performance when a CE method is validated.

This is adapted from the International

Conference on Harmonization of Technical

Requirements for Registration of

Pharmaceutical for Human Use (ICH

Harmonized Tripartite Guideline, 2005).

2.5.1. Specificity

Specificity indicates whether a method can

differentiate the analyte of interest from other

interferences. This criterion is a very important

for the analysis of impurities in pharmaceuticals

and for chiral drug, which should be performed

during identification, impurity testing and

assay. This test is usually carried out by

spiking samples with suitable amounts of

impurities or matrices. Resolution of the

impurities and matrices and the major

components should be demonstrated and the

assay results should not be affected by these

substances compared with the unspiked

samples. Additionally, degradation products

obtained from stress conditions (e.g., light, heat,

humidity acid/base hydrolysis and oxidation)

may be included in the specificity testing.

2.5.2. Linearity and range

Linearity reveals the relationship of signals

and analyte’s concentrations. A minimum of

five concentrations in a range of 80-120% of

the test concentration is recommended. This

relationship is expressed by a regression line

calculated from least square methods

accompanied with correlation coefficient, y-

intercept, slope of the regression line and

residual sum of squares. Generally, signals

calculated from peak area provide better a

linearity range than those from peak height

since the latter is highly influenced by peak

shape.

2.5.3. Accuracy

Accuracy implies the closeness of the

analytical results to the true values. Accuracy

can be performed by spiking know amounts of

analytes into samples and percent recoveries are

evaluated. Accuracy should be carried out

across the specific range of the method, i.e.,

normally, nine determinations over a minimum

of three concentrations. Otherwise, accuracy

can be assessed by comparing the results of the

proposed method with a well-established

method.

2.5.4. Precision

Precision represents the closeness of the

analytical results of an analytical method. This

is expressed as percent relative standard

deviation, standard deviation, variance or

confidence interval. Precision is performed in

three levels: repeatability, intermediate

precision and reproducibility. For repeatability,

a minimum of nine determinations over three

concentrations is recommended. Intermediate

precision includes closeness of results from

different days, analysts or instruments, whereas

reproducibility refers to the results from

different laboratories/environment.

2.5.5. Detection and quantitation limits

Detection (DL) and quantitation limits (QL)

represent method sensitivity. DL is the lowest

amount of the analyte, which can be detected,

while QL is the lowest amount that can be

quantitatively determined with acceptable

precision and accuracy. DL and QL can be

calculated based on: a) signal to noise ratios

(S/N), b) standard deviation of the response and

the slope, c) standard deviation of the blank or

d) the calibration curve. S/N of 3:1 or 2:1 is

generally used for DL, while S/N of 10:1 is

typical for QL.

2.5.6. Robustness

Robustness is a criterion that indicates the

validity of a method among small, but

deliberate variations in experimental factors.

Examples of these variations are pH, BGE

composition, capillary, temperature, voltage,

etc. If any of these variations significantly

influences the analytical results, appropriate

precautions should be mentioned in the

analytical procedures.

2.5.7. Solution stability

During the method validation process,

stability of sample or standard solutions and

BGE composition should be monitored in order

to obtain shelf lives information. This test

indicates whether the solutions and BGE are

stable and do not produce any degradations

during an analysis. Most BGE have shelf-lives

of 3 months, except BGE containing

cyclodextrin, which tends to show bacterial

growth during storage. Stability of stored

solutions should be compared with the freshly

prepared solutions or should be analyzed after

certain storage times. No impurity, degradation

or contaminated peaks should be observed in

the stored solutions.

2.5.8. Peak purity

Peak purity testing is recommended in CE

since co-migrated peaks can be observed in a

analysis. This test is performed in a similar

manner as in HPLC, usually by comparison of

spectral characteristics with standard peaks.

DAD is preferred since the spectra can

monitored at different wavelengths

simultaneously.

2.5.9. System suitability

System suitability is intended to test

whether an instrument or method is suitable and

in good agreement with the predetermined

criteria prior the application of a method.

System suitability criteria include Rs, N and TF.

Other criteria may be included depending upon

application, for example, LOD and resolution

are recommended for enantiomeric separation

of drug impurities and injection precision is

required for assay of active pharmaceutical

ingredients.

3. RESULTS AND DISCUSSION

3.1. Case studies

Development and validation of CE methods

for the monitoring of drugs in serum level, for

quality control of pharmaceutical formulations

and phytochemical substances are illustrated in

case studies 1-4, respectively.

3.1.1. Case study 1

Drug monitoring is one of the essential

tasks in pharmaceutical care in order to achieve

the therapeutic efficacy and safety. This

example reveals a MEKC method developed for

the analysis of mycophenolic acid (MPA) from

serum of transplant recipients (Meyer et al.,

2004). MPA is a metabolite of mycophenolate

mofetil, an immuno suppressive agent, which is

used to prevent tissue rejection. Monitoring of

serum MPA level is essential for dose

adjustment to avoid side effects. In this work,

sample pre-treatment (i.e., solid phase

extraction, SPE) greatly influenced the method

accuracy. Adjusting the serum pH to 1.0 and

using 100 µL methanol to reconstitute the drug

residue were key steps in SPE that enabled the

recoveries of 80.0-100.8 % with % relative

standard deviations (%RSDs) of 8.5-23.9%.

Factors affecting MEKC of MPA were injection

time (20 mbar x 0.1-0.2 min) and detection

wavelengths (217, 254 and 251 nm). Increasing

of injection time enhanced method precision

since an accurate volume of sample was more

controllable compared to the results of a short

injection time. Applying the injection time of

0.2 min provided the lowest %RSDs and a

maximum recovery of 93.0%. The appropriate

detection wavelength for MPA was at 217 nm,

which gave the highest absorbance and lowest

%RSDs. Optimum MEKC condition for the

analysis of MPA was in 20 mM phosphate-

borate buffer (pH 8.0) consisting of 50 mM

sodium dodecyl sulfate (SDS) and 16% v/v

acetonitrile, using hydrodynamic injection of 20

mbar x 0.2 min, a capillary effective length of

49.5 cm with an inner diameter of 50 µm,

voltage and temperature of 25 kV and 20 °C,

respectively, and a detection wavelength at 217

nm (Fig. 4).

The method showed good linearity in a

range of 1.0-5.0 µg/mL with a linear regression

y = 0.1456x + 0.018 (r2 = 0/9964). Precision

calculated from %RSDs of peak height was

within 17.8% and the LOD calculated from S/N

of 3 was 1.0 µg/mL. This validation data

indicated that the method could be applied for

the analysis of MPA serum level in transplant

patients.

3.1.2. Case study 2

CE becomes a valuable tool for

pharmaceutical quality control as described in

the previous review (Suntornsuk, 2007).

Common cold ingredients (Fig. 5) are the most

widely used drug in various countries. Quality

control of these drugs is, therefore, essential for

consumer protection. In 2001, the research

group optimized CZE and MEKC for the

analysis of PPA, CPM, DEX and PARA

(Suntornsuk, 2001). CZE offered baseline

separation of PPA, CPM and DEX, however,

the method was not suitable for PARA PARA

is a neutral compound and co-migrated as a

broad peak with the EOF. MEKC was more

efficient when non-ionic species is included. In

this study, effects of pH of BGE (4.0-6.0),

concentrations of BGE (10-20 mM phosphate-

borate) and surfactant (10-50 mM SDS) and

organic solvent (2.5-20% v/v methanol) on the

separation of PPA, CPM, DEX and PARA were

investigated. The optimum condition was in 10

mM phosphate-borate buffer (pH 9.0)

consisting of 50 mM SDS and 10% v/v

methanol, using voltage of 25 kV, which

provided the separation of all compounds in

11.4 min with a Rs of 1.2.

In 2003, the research group had continued

its work in the separation of nine common cold

ingredients using MEKC (Suntornsuk et al.,

2003b). Further optimization was performed by

varying types (i.e., methanol, ethanol,

isopropanol and acetonitrile) and amount (0-

40% v/v) of organic solvents, pH (4.0-10.0)

and concentrations (5-30 mM) of phosphate-

borate buffer, temperature (25-35 °C) and

voltage (10-25 kV). Organic solvents greatly

affected MEKC separation efficiency and

selectivity by enlarging the separating window,

enhancing analytes’ solubility and reducing

analytes’ mobilities and diffusion. BGE

concentration influenced the EOF and current,

whereas pH impacted migration order of the

analytes. Increasing of temperature and voltage

affected the separation in the same direction

resulting in the decreasing of BGE viscosity

and migration time. Optimum MEKC

condition for the analysis of the nine common

cold ingredients was in 10 mM phosphate-

borate buffer (pH 9.0) consisting of 50 mM

SDS and 26% v/v methanol, using

hydrodynamic injection of 50 mbar x 10 s, a

capillary effective length of 50 cm, voltage and

temperature of 15 kV and 30 °C, respectively.

Baseline separation was obtained in 25.5 min

with a Rs of 3.0 (Fig. 6).

The developed MEKC was validated in

terms of linearity, precision, accuracy LOD and

LOQ for the determination of PARA and CPM

in pharmaceutical formulations. The regression

lines over the range of 10-250 µg/mL were y =

4.29x + 18.12 (r2 = 0.999) and y = 6.00x +

18.33 (r2 = 0.999) for PARA and CPM,

respectively. The %RSDs of the slopes and

intercepts were in the range of 0.2 and 11.3% (n

= 3), respectively. The injection precision (n =

10) calculated from the %RSDs of peak area

were 1.7 and 2.4% for PARA and CPM,

respectively. The different day precision (n =

6) were within 2 and 3% for the migration time

and peak area for both compounds. Recovery

experiments from spiking 50-150% of the label

amount (500 mg and 2.5 mg per tablet for

PARA and CPM, respectively) showed the

mean recoveries of 100.6 and 99.5% for PARA

and CPM, respectively, with the %RSDs of <

2.7% (n = 3). The LOD based on S/N = 3 were

0.4 and 0.5 µg/mL and the LOQ based on the

S/N = 10 were 2 and 4 µg/mL, for PARA and

CPM, respectively. The linearity, precision,

accuracy LOD and LOQ data showed that the

MEKC method was valid for the assay of

PARA and CPM in pharmaceutical

formulations.

3.1.3. Case study 3

Analysis of phytochemical substances is

another focused research by the research group

(Suntornsuk, 2002; Suntornsuk et al., 2003a;

Suntornsuk and Anurukvorakun, 2005). An

example of CZE of aglycone quercetin in

Morus alba L., mulberry leaves is described

herein (Suntornsuk et al., 2003a). This was the

first Thai application of CE on the analysis of

flavonoids. Flavonoids have attracted attention

due to their several pharmacological activities

such as anticancer, antibacterial, antiviral and

antioxidant. The investigated flavonoids

included rutin, quercetin, kaempferol, quercetin,

cathecin and gallic acid (Fig. 7). Both chemical

(i.e., pH and concentrations of boric acid as the

BGE, concentration of SDS and amounts of

methanol) and instrumental (i.e., temperature

and voltage) factors were varied to obtain the

optimum condition for the separation of the six

flavonoids. Increasing boric acid concentration

lengthened the migration time due to the

reduction of EOF (Fig. 8). The EOF reduction

stemmed from the decrease of zeta potential at

the interface of inner surface of the capillary

wall and the sample. Varying of pH of the

BGE greatly affected the selectivity/ migration

order of the flavonoids since they were weak

acidic and were ionized in basic condition. The

migration time was longer at high pH because

more negative net charges were obtained and

they were attracted toward the anode. Adding

5% v/v methanol into the BGE enhanced the

resolution of the separation due to the increase

of the separating window. However, when 10-

20 %v/v was added, overlapped peaks and

migration time of more than 30 min were

observed. This was due to the decrease of

analyte solubility in the presence of high

amount of organic solvent. Addition of SDS

into the BGE changed to CE from CZE to

MEKC modes, which caused peak broadening

due to the borate complex formation of the

BGE and the flavonoids. Thus, for these

flavonoids, CZE was more suitable. Increasing

temperature and voltage decreased the BGE

viscosity which subsequently increased the

EOF and analytes’ mobility and reduced the

migration time. Results indicated that all six

flavonoids were well separated in 16.5 min in

150 mM boric acid (pH 10.0) using a capillary

effective length of 42.5 cm, voltage and

temperature of 18 kV and 32 °C, respectively

(Fig. 8 (150 mM)).

For analysis of phytochemical substances,

which are present in complex matrices (i.e.,

plants), an internal standard (IS) usually benefit

the method precision. In this work, rutin was

employed as an IS for the quantitation of

aglycone quercetin in mulberry leaves.

Standard addition method was selected for

method validation and applications. Linearity

regression of aglycone quercetin, in a range of

40-160 µg/mL, calculated from peak height

ratio gave the best r2 (Table 1). Intra- and inter-

day precision calculated from the use of IS

provided the %RSDs of less than 2.5%,

whereas those without an IS was between 2.3-

4.5% (Table 2). LOD and LOQ of the method,

calculated from S/N = 3 and 10, were 0.86 and

3.16 (%RSD = 1.8%) µg/mL, respectively.

Mean recovery of the method was 100%

(%RSD < 0.8%, Table 3). Validation data

indicated the method was suitable for the

quantitative analysis of aglycone quercetin in

mulberry leaves.

3.1.4. Case study 4

In 2005, the research group optimized a

CZE method for the precision improvement and

for the analysis of flavonoids (i.e., rutin,

kaempferol, quercetin, myricetin and apigenin)

in selected Thai medicinal plants (i.e., Centella

asiatica, Rosa hybrids and Chromolaena

odorata) (Suntornsuk and Anurukvorakun,

2005). Additionally, organic carboxylic acids

(i.e., ethacrynic acid (E) and xanthene-9-

carboxylic acid (X)) were included as internal

standards (IS) or markers. CZE using 10 mM

sodium dihydrogen phosphate-disodium

hydrogen phosphate (pH 8.0) was chosen as a

starting condition for the separation of the

seven analytes. Under this condition, the

analytes were partially separated. Further

optimization was investigated by varying types

and amounts of organic modifiers (methanol

and acetonitrile), concentrations of the BGE

(i.e. 10 and 20 mM), temperature (20-30 °C)

and voltage (15-30 kV). Importantly, the final

optimization was achieved by adding a second

organic modifier (e.g. methanol and

acetonitrile) into the BGE. The optimum CZE

condition was in the BGE consisting of 20 mM

sodium dihydrogen phosphate and disodium

hydrogen phosphate (pH 8.0), 10% v/v

acetonitrile and 6% v/v methanol, using voltage

and temperature of 25 kV and 30 °C,

respectively (Fig. 9). All analytes were

baseline separated in 10 min with a Rs of 2.8.

Interestingly, two different organic solvents

were employed as additives in the BGE to

improve the analytes’ solubility, enhance

separation selectivity and efficiency.

This work first applied the corrected

migration time (tc), using a single marker or two

markers, and marker index (MI) to improve

method precision. Normally, migration time in

CE can deviate from1-2% due to the varied

EOF resulted from the unstable inner capillary

wall surface. Furthermore, migration times of

analyte depend on BGE concentration and pH

and sample matrices, which can be varied from

those of standard solutions. For example,

migration times of flavonoids in medicinal

plants usually differ from those in standard

solutions, which make their identification

difficult. Tc and MI can simplify this problem

by using the well separated compounds as

markers (i.e., E and X). In tc technique, E was

appropriate as a single marker, where as EOF

and E were suitable two markers. For MI

technique, both E and X were selected as

markers. Equations for the calculation of

corrected migration time and marker index were

described in detail in the original paper (27).

%RSDs of migration times of the flavonoids

decreased from 1.88-14.67% to 0.65, 0.82 and

1.28% for tc(E), tc(E/EOF) and MI(E/X), respectively.

Among them, MI gave the lowest %RSDs, a

99-fold of precision was obtained in the

identification of kaempferol in roses. Fig. 10

shows the migrations time of flavonoids in the

plant extracts compared to those calculated

from tc using E as a single marker.

The method was validated for the analysis

of kaempferol in C. asiatica and rose and rutin

in Ch. odorata. Linearity of the CZE method

was performed in spiked samples to avoid

interference from sample matrices over a range

of 40-160 µg/mL. Peak area ratio using E as an

IS showed good linearity for the analysis of the

flavonoids in all three plants (r2 > 0.999) (Table

4). Precision of migration time greatly reduced

from 1.88-14.67% to less than 0.65% when tc(E)

was employed (Table 5). Peak area ratios using

E as and IS also provided the smallest %RSDs

of 0.30-1.66% (Table 5). Recoveries from

standard addition method were between 95.6-

102.0% for all plants and the LOD and LOQ

calculated from S/N were within 2.23 and 7.14

µg/mL, respectively (Table 6). The method

was applicable for the determination of

kaempferol in C. asiatica and rose and rutin in

Ch. odorata.

4. CONCLUSION

The development of a CE method should be

systematically investigated since several factors

including chemical and instrumental parameters

are involved. An optimum condition for each

analyte depends upon the analyte’s physico-

chemical properties and sample’s complexity.

CE separation of analytes in standard solution

can be varied from sample matrices. Thus,

sample pretreatment and using of an IS are

always recommended to improve method

precision. The optimized CE condition is

usually a compromise of analytical parameters

such as the separation efficiency, analysis time,

resolution and peak symmetry. Prior

applications of a CE method, validation of the

method should be evaluated according to the

predetermined criteria, for instance, linearity

and range, accuracy, precision, detection and

quantitation limits, and robustness. In certain

cases, these criteria are extended to solution

stability, peak purity and system suitability.

Although an individual analyte in a sample has

unique characteristics, case studies presented in

this review can serve as guideline for

development and validation of CE method for

analysis of various analytes in different sample

matrices.

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Table I. Regression Data of Aglycone Quercetin (n =3)

(Reproduction with Permission from Suntornsuk et al., 2003a).

Calculated from Equation Correlation coefficient (r2) with the internal standard peak height ratio y = 0.0093x + 0.926 0.9992 peak area ratio y = 0.0208x + 2.039 0.9956 normalized peak area ratio y = 0.0102x + 1.076 0.9819 without the internal standard peak height y = 0.1606x + 17.403 0.9819 peak area y = 2.5945x + 232.020 0.9845 normalized peak area y = 0.1579x + 15.294 0.9847

Table II. Injection, Intra-Day and Inter-Day Precision for Aglycone Quercetin

(Reproduction with Permission from Suntornsuk et al., 2003a).

%RSD Injection Intra-day Inter-day precision precision precision (n = 6) (n = 10) (n = 6)

Migration time 2.3 4.5 2.3 Migration time ratio 2.0 2.0 1.1 Peak height 3.7 3.1 3.2 Peak height ratio 0.6 1.3 0.7 Peak area 3.6 3.1 2.5 Peak area ratio 1.0 0.8 0.8 Normalized peak area 3.3 3.5 2.6 Normalized peak area ratio 2.4 2.3 1.3

Table III. Recoveries of Aglycone Quercetin from Mulberry Leaves (n = 6)

(Reproduction with Permission from Suntornsuk et al., 2003a).

Amount added (µg/ml) Mean of amount found

(µg/ml)

Mean recoveries

(%)

% RSD

80% 79.56 79.85 100.16 0.8

100% 99.13 99.80 100.67 0.8

120% 118.70 118.76 100.05 0.7

Table IV. Regression Data of the Flavonoids in Plant Extracts

(Reproduction with Permission from Suntornsuk and Anurukvorakun, 2005).

Calculated from Linear equation Standard error Correlation coefficient

Slope Intercept (r2)

Kaempferol in C. asiaticaa

Peak area ratio (E) y = 0.0186x + 0.1513 0.031 2.719 0.9997

Peak area ratio (X) y = 0.0071x + 0.1734 0.014 1.228 0.9809

Peak height ratio (E) y = 0.0097x + 0.5312 0.024 2.211 0.9703

Peak height ratio (X) y = 0.0054x + 0.3329 0.013 1.259 0.9684

Normalized peak area ratio (E) y = 0.0215x + 0.1584 0.035 3.105 0.9996

Normalized peak area ratio (X) y = 0.0094x + 0.2086 0.018 1.587 0.9829

Kaempferol in R. hybridsa

Peak area ratio (E) y = 0.0420x + 0.3957 0.067 6.010 0.9995

Peak height ratio (E) y = 0.0323x + 0.0391 0.047 4.094 0.9902

Normalized peak area ratio (E) y = 0.0498x + 0.2058 0.079 6.973 0.9996

Rutin in Ch. odorataa

Peak area ratio (E) y = 0.0106x + 0.5639 0.025 2.309 0.9994

Peak area ratio (X) y = 0.0053x + 0.3573 0.014 1.319 0.9958

Peakheight ratio (E) y = 0.0045x + 0.6777 0.018 1.712 0.9908

Peak height ratio (X) y = 0.0012x + 0.4842 0.010 0.958 0.9909

Normalized peak area ratio (E) y = 0.0137x + 0.6858 0.032 2.940 0.9903

Normalized peak area ratio (X) y = 0.0079x + 0.4669 0.020 1.851 0.993 aLetter in parenthesis represents the internal standard used. Identification: E = ethacrynic acid, X = xanthene-9-carboxylic acid

Table V. %RSDs of Migration Times and Marker Indices of the Standard Flavonoids

(Reproduction with Permission from Suntornsuk and Anurukvorakun, 2005).

R K Q M A

%RSDs of tma 1.37 1.42 1.43 1.47 1.52 %RSDs of tc1b tc(EOF) 0.79 0.93 1.00 1.05 1.04

tc(E) 0.15 0.08 0.09 0.12 0.06

tc(X) 0.20 0.18 0.17 0.14 0.19 %RSDs of tc2c tc(EOF/E) 0.20 0.18 0.20 0.20 0.12

tc(EOF/X) 0.22 0.24 0.26 0.25 0.22

tc(E,X) 0.44 0.30 0.27 0.27 0.17

%RSDs of MId

MI(EOF/E) 0.53 0.60 0.66 0.70 0.67

MI(EOF,X) 0.50 0.57 0.63 0.67 0.64

MI(E,X) 0.30 0.24 0.23 0.22 0.14 atm = uncorrected migration time

btc1 = corrected migration time using single-marker, letters in parentheses represent the markers

ctc2 = corrected migration time using two-marker, letters in parentheses represent the markers

dMI = migration indices letters in parentheses represent the markers

Identification: R= rutin and K= kaempferol

Table VI. Recoveries, LOD and LOQ of the Flavonoids in the Plant Extracts (n = 6)

(Reproduction with Permission from Suntornsuk and Anurukvorakun, 2005).

K. in C. asiatica K. in R. hybrids R.in Ch. odorata Amount added (µg/mL) 80.0 100.0 120.0 84.0 105.0 126.0 80.8 101.0 121.2 Mean of amount found (µg/mL) 80.0 102.0 119.2 80.7 100.4 120.4 79.9 98.3 119.4 Mean recoveries (%) 100.0 102.0 99.4 96.1 95.7 95.6 98.8 97.3 98.5

%RSD 1.70 1.41 0.52 0.35 0.43 0.55 0.40 0.59 1.56

LOD (µg/mL) 0.44 2.23 1.76

LOQ (µg/mL) 1.45 7.14 4.39 Identification: R = rutin, K= kaempferol

Figure 1. Principle of Capillary Electrophoresis: (-) anion; (+) cation;

(N) neutral; (EOF) electroosmotic flow.

Figure 2. Capillary Electrophoresis Instrumentation.

Figure 3. Electropherogram of a Standard Mixture of ββββ-Agonists (100 µµµµg/mL).

Condition: BGE, 18mM Ammonium Acetate Buffer Containing 66:33:1% (v/v)

MeOH:ACN; Capillary, 64.5 cm Total Length (8.5 cm to Detector), 75 µµµµm ID

(with an Extended Light Path); Hydrodynamic Injection at 50 mbar for 4 s;

Voltage 28 kV; Temperature, 24 ◦C; Detection by UV Absorbance at 220 nm.

(Reproduction with Permission from Anurukvorakun et al., 2006).

Figure 4. MEKC Electropherogramm of MPA and the Internal Standard CBE after SPE

from CBE Spiked (10.0 mg/mL) Serum of a Kidney-Transplant Recipient.

Condition: see text: CBE = Carboxybutyl Ether of MPA.

(Reproduction with Permission from Myer et al., 2004).

Figure 5. Structures of Common Cold Ingredients

(Reproduction with Permission from Suntornsuk et al., 2003b).

Fig. 6: A Typical Electropherogram of the Standard Mixture Solution (100 mg/ml)

under the Optimum Condition (see text). Peak Identification: (1) PPA; (2) CAF;

(3) PARA; (4) CPM; (5) DPH; (6) DEX; (7) TPL; (8) LOR; (9) ASA.

(Reproduction with Permission from Suntornsuk et al., 2003b).

Fig. 7: Structures of the Flavonoids.

(Reproduction with Permission from Suntornsuk et al., 2003a).

Fig. 8: Effect of the BGE Concentrations on the Resolution of a Standard Mixture of the

Flavonoids and Phenolic Acid. Separation Conditions: Boric Acid Solution at Various

Concentrations, pH 10.0; Capillary, 51 cm Full Length (8.5 cm to the detector), 50 _m ID;

Hydrodynamic Injection at 50 mbar for 10 s; Oven Temperature, 32_C;

Applied Voltage, 18 kV; Detector by UV Absorbance at 270 nm.

Peak Identification: (1) Rutin; (2) Catechin; (3) Quercitrin; (4) Kaempferol; (5) Aglycone

Quercetin; (6) Gallic Acid. (Reproduction with Permission from Suntornsuk et al., 2003a).

Fig. 9: Electropherogram of a Standard Mixture of the Flavonoids and Organic Carboxylic

Acids under the Optimized Conditions (see text). Peak Identification: (R) Rutin;

(K) Kaempferol; (Q) Quercetin; (M) Myricetin; (A) Apigenin;

(E) Ethacrynic Acid; (X) Xanthene-9-Carboxylic Acid.

(Reproduction with Permission from Suntornsuk and Anurukvorakun, 2005).

Fig. 10: Migration Times of the Flavonoids within 6 days. tm and tc1(E) are Uncorrected

Migration Times and Corrected Migration Times using E as a Marker.

(Reproduction with Permission from Suntornsuk and Anurukvorakun, 2005).