Design and Optimization of Mefloquine Hydrochloride Microparticles for Bitter
Punit P. Shah,1,2Rajashree C. Mashru,1Yogesh M. Rane,1and Arti Thakkar1
Received 24 July 2008; accepted 19 January 2008; published online 20 February 2008
Abstract. The objective of the present investigation was to reduce the bitterness with improved
dissolution, in acidic medium (pH 1.2), of mefloquine hydrochloride (MFL). Microparticles were
prepared by coacervation method using Eudragit E (EE) as polymer and sodium hydroxide as
precipitant. A 32full factorial design was used for optimization wherein the drug concentration (A) and
polymer concentration (B) were selected as independent variables and the bitterness score, particle size
and dissolution at various pH were selected as the dependent variables. The desirability function
approach has been employed in order to find the best compromise between the different experimental
responses. The model is further cross validated for bias. The optimized microparticles were characterized
by FT-IR, DSC, XRPD and SEM. Bitterness score was evaluated by human gustatory sensation test.
Multiple linear regression analysis revealed that the reduced bitterness of MFL can be obtained by
controlling the dissolution of microparticles at pH 6.8 and increasing the EE concentration. The increase
in polymer concentration leads to reduction in dissolution of microparticles at pH>5 due to its
insolubility. However the dissolution studies at pH 1.2 demonstrated enhanced dissolution of MFL from
microparticles might be due to the high porosity of the microparticles, hydrophilic nature of the EE, and
improved wettability, provided by the dissolved EE. The bitterness score of microparticles was decreased
to zero compared to 3+ of pure ARM. In conclusion the bitterness of MFL was reduced with improved
dissolution at acidic pH.
KEY WORDS: bitterness; eudragit; full factorial design; mefloquine HCl; microparticles.
In recent years, the importance of patient compliance,
not only in drug efficacy per se, but also in overall economics
of healthcare, has been increasingly recognized. Efforts to
improve patient compliance have included attempts to
improve the palatability of orally administered pharmaceuti-
cal agents especially for children and elderly (1,2). In
particular, a bitter taste is known to decrease patient
compliance, and thus reduce effective pharmacotherapy.
In the present study, the possibility of masking the
bitterness of mefloquine hydrochloride (MFL), a drug used
as a treatment for malaria, was investigated. MFL has an
extremely unpleasant bitter taste due to presence of quinine
moiety (3). As this is likely to give rise to non-compliance
when administered orally, it would be a considerable advan-
tage to be able to mask the bitterness of oral formulations
In order to achieve an acceptable palatability, the addition
of flavors or sweeteners is limited and may not be efficient
enough to mask the bitter taste of drugs, requiring the use of
technological processes (4–6). A number of taste-masking
approaches have been described in the literature, including
the use of cyclodextrin (7), ion exchange resin (8,9), film
coating (10), viscosity modification (11) and melt granulation
(12). Among the various techniques, microencapsulation has
often proved to be the most successful in reducing the
bitterness of bitter active pharmaceutical ingredients because
it is simple, economic and advantageous (13).
The objective of present investigation was to completely
mask the bitter taste of MFL by encapsulation in micro-
particles, while allowing the complete release of MFL under
the acidic conditions of stomach (pH 1.2). The pH inside the
oral cavity has been reported to be about 6.8 (14). A 32full
factorial design was used for optimization wherein the drug
concentration (A) and polymer concentration (B) were
selected as independent variables and the bitterness, particle
size and dissolution at various pH were selected as the
Eudragit E, an acid-soluble polymer, was selected for the
encapsulation of MFL. It has been reported that this polymer
is a cationic copolymer based on dimethyl aminoethyl
methacrylate and neutral methacrylic esters soluble up to
pH 5; however it is swellable and permeable above pH 5
(15,16). Sodium hydroxide was used as precipitating agent.
This alternative microparticles preparation method can be
applied, replacing the complicated and sophisticated quasi
emulsion solvent diffusion (17), spray drying (16), solvent
1530-9932/08/0200-0377/0#2008 American Association of Pharmaceutical Scientists
AAPS PharmSciTech, Vol. 9, No. 2, June 2008 (#2008)
1Center of Relevance and Excellence in NDDS, Pharmacy Depart-
ment, The M. S. University of Baroda, G H Patel building, Donor’s
Plaza, Fatehgunj, Vadodara, Gujarat, India, 390 002.
2To whom correspondence should be addressed. (e-mail: punit
evaporation (18), solid dispersion by supercritical fluids (19),
co evaporates (20) and non-aq. granulation (15) used in prior
formulations. Further the present method avoids use of
special instrument, hazardous organic solvent and is easy to
MATERIALS AND METHODS
Mefloquine hydrochloride (Batch no. 031209) was a gift
from Ajanta Pharma Ltd, (Mumbai, India). Eudragit E (EE)
(Batch no. G041131159) was a gift from Degussa India Pvt.
Ltd., (Mumbai, India). Methanol was purchased from Quali-
gens Fine Chemicals (Mumbai, India) and was used as
received. Sodium hydroxide, hydrochloric acid, potassium
dihydrogen phosphate, and acetic acid were purchased from
S. D. Fine-Chem Ltd., (Mumbai, India) and were used as
Preparation of Microparticles
Microparticles were prepared by coacervation phase
separation method. A concentrated solution of EE (∼1% w/v)
was prepared in 1% v/v acetic acid. The required quantity of
the MFL (0.6 g in 50 mL of final EE solution) was mixed for
5 min. Ten milliliters of 10% w/v sodium hydroxide solution
was introduced into a 10-ml of glass syringe with a 18G×1/2”
flat-cut hypodermic needle. The droplets were amputated at a
flow rate of 3 ml/min into EE solution. The resulting micro-
particles were allowed to harden for 60 min under gentle
stirring at 400 rpm (Remi Equipments Pvt. Ltd., Mumbai,
India) with small magnetic bar. Actual values of independent
factors are listed in Table I. Different concentrations of MFL
and EE were used, according to the experimental runs,
mentioned in Table II. The microparticles were collected,
decanted, washed with deionized water and dried to a constant
weight in oven (Shree Kailash Industries, Baroda, India) at
80 °C for 24 h, and then stored in the desiccator until use. The
percentage yield was calculated as:
Percent yield ¼Calculated yield
Theoretical yield? 100
A 32full factorial design was employed to systematically
study the joint influence of the effect of independent variables
Table I. Variables in 32Full Factorial Design
Drug Conc. (A in g) Polymer Conc. (B in mL)a
Dissolution at pH 1.2
Dissolution at pH 6.8
amL of 1% w/v EE solution, prepared in 1% v/v acetic acid
Table II. Presentation of Experiments with Coded Values for Factor Levels for 32Full Factorial Design with their Percent Yield and
Incorporation Efficacy of Microparticles
Factors and Factor Levels
Incorporation Efficiency (%)±SDa
Drug Conc. (A)Polymer Conc. (B)
aValues represent the mean±SD of three experiments
378 Shah et al.
A and B on the dependent variables. In this design, two
factors were evaluated, each at three levels, and experimental
trials were performed at all nine possible combinations. A
statistical model incorporating interactive and polynomial
terms was used to evaluate the response (21).
Y ¼ b0 þ b1A þ b2A þ b11A2þ b22B2þ b12AB
where, Y is the dependent variable, b0 is the arithmetic mean
response of the nine runs, and bi is the estimated coefficient for
the factor, drug (A) and polymer concentration (B). The main
effects (A and B) represent the average result of changing one
factor at a time from its low to high value. The interaction
terms (AB) show how the response changes when two factors
are simultaneously changed. The polynomial terms (A2and
B2) are included to investigate nonlinearity.
Optimization of Responses Using Desirability Function
This technique involves a way of overcoming the difficulty
of multiple, sometimes opposing responses (22). Each response
is associated with its own partial desirability function. If the
value of the response is optimum, its desirability equals 1, and
if it is totally unacceptable, its value is zero. Thus the
desirability for each response can be calculated at a given
point in the experimental domain. The optimum is the point
with the highest value for the desirability.
The dissolution at pH 1.2 was targeted to maximize in
the procedure, as higher values of this is desirable. Greater
dissolution at pH 1.2 leads to greater availability of MFL in
stomach. Moreover microparticles showed complete release
within few min. Hence dissolution at pH 1.2 in 15 min (t15)
was selected. So the desirability function of this parameter
was calculated by using Eq. 3.
Where d1is individual desirability and Yiis experimental
results of dissolution at pH 1.2. The values of Yminand Ymax
of dissolution at pH 1.2 were 59.89 and 99.59 % respectively.
To avoid grittiness of microparticles after ingestion in
oral cavity, minimum particles size was desired. The observed
Yminand Ymaxvalues of particle size were 32.08 and 236.78 μ,
respectively. Further the problem of bitter taste of the drug,
generally encountered due to dissolution of the active
component in oral cavity. In addition the microparticles
remain for maximum 5 min in oral cavity. To avoid this,
minimum dissolution at 5 min was desired. The values of Ymin
and Ymaxof dissolution at pH 6.8 in 5 min (t5) were 2.45 and
5.25 %, respectively. Similarly the lowest value of bitterness
score was desired for complete taste masking. Though the
observed Ymaxvalue of bitterness score was 3, it was selected
as 0.5 because no bitterness to very slightly bitterness was
desired. The values of Ymaxand Yminof bitterness score were
0.5 and 0, respectively. So the desirability function of particle
size, drug release at pH 6.8 and bitterness score was
calculated by using following equation.
where di is the individual desirability while Yi is the
experimental result. In all the experiments performed, all
the experimental values were acceptable, however, the values
far from the target, were little penalized, by choosing 0<s<1
(1 in this case) in Eqs. 5, 6 and 7.
di¼ 1 if Yi < Ymin
if Ymin? Yi? Ymin
di¼ 0 if Yi> Ymax
Table III. Grading for Gustatory Sensory Test
Very slightly bitter
Slight to moderate bitter
Moderate to strong bitter
Very strongly bitter
Table IV. Results of Regression Analysis
Particle Size (μ) Drug Release at pH 1.2 (t15in %)Dissolution at pH 6.8 (t5in %)Bitterness Score
− Indicates term is omitted in reduced model, FM full model, RM reduced model, t5 and t15 percent drug released at 5 and 15 min, respectively
379Design and Optimization of Mefloquine Hydrochloride
The combined desirability value was calculated from the
individual values by using following equation:
D ¼ d1? d2? d3? d4
CHARACTERIZATION OF MICROPARTICLES
Determination of Incorporation Efficiency
Microparticles containing 10 mg MFL were weighed
accurately and dissolved in methanol. Drug concentration was
determined by UV spectrophotometry (Shimadzu UV visible
spectrophotometer 1601) at 284 nm. A calibration curve was
used, based on standard solutions in methanol. The polymer
did not interfere with the analysis at this wavelength. The
percent yield and incorporation efficiency for all formulations
are shown in Table II. To determine the incorporation
efficiency, the following practical relationship was used:
ðÞIncorporation efficiency ¼Calculateddrug concentration
Theoratical drug concentration
Particle Size Analysis
The average particle diameter and size distribution of
microparticles were determined by using Malvern (Mastersizer
2000 Malvern Instruments, UK). Approximately 10 mg of
microparticles were dispersed in 2–3 ml of filtered and
degaussed phosphate buffer pH 6.8 containing 0.1% Tween
80 for 1 min using an ultrasonic bath. An aliquot of the
microparticle suspension was then added into the small volume
recirculation unit and circulated 3500 times/min. Each sample
was measured in triplicate in the analysis. Particle size was
expressed as the weighted mean of the volume distribution.
The in vitro drug release profile of microparticles was
determined according to the paddle method described in the
United State Pharmacopoeia (USP; XXIV). The in vitro drug
release study was carried out in phosphate buffer pH 6.8
because the pH of the saliva is in the range from 6.3 to 7.2.
Further the in vitro drug release study was performed in
hydrochloric acid buffer pH 1.2 to demonstrate the availabil-
ity of MFL in gastric pH. Both the buffers of particular pH
were prepared according to Indian Pharmacopoeia. An
appropriate amount of microparticles containing 250 mg of
MFL were suspended in 900 mL of the buffer solution, and
3 mL sample was withdrawn at 1, 5, 10, 15, 30, 45 and 60 min
and analyzed using UV spectrophotometer at 284 nm. Each
sample was replaced with fresh 3 ml buffer solution having
the same temperature.
Table V. ANOVA Results for Measured Responses
Sum of Square
Particle size (Y1 in μ)
Dissolution at pH 1.2
(Y2 in %)
Dissolution at pH 6.8
(Y3 in %)
ANOVA Indicates analysis of variance, df degrees of freedom, SS sum of squares, MS mean of squares, F Fischer’s ratio, R2regression coefficient, FM full model, RM reduced model
380Shah et al.
Gustatory Sensation Test
Twenty volunteers participated in sensory test. Micro-
particles containing 500 mg of MFL were dispersed in 25 ml
of water for 15 s. Immediately after preparation, each
volunteer held about 1 ml of the dispersion in the mouth for
30 s. After expectoration, bitterness was evaluated using
bitterness score, classified in eight grades, corresponding to
increasing bitterness and comparison of bitterness among the
samples was performed on the total number of persons who
selected “bitter” and “slightly bitter”. The ranking scheme
used is shown in Table III. The threshold of bitterness of
microparticles was determined as point at which half of the
volunteers described the taste as bitter or slightly bitter.
Fourier Transform Infra-red Spectroscopy (FTIR)
IR transmission spectra were obtained using a Fourier
Transform Infrared spectrophotometer (FTIR-8300, Shimadzu,
Japan). A total of 2% (w/w) of sample, with respect to the
potassium bromide (KBr; S. D. Fine Chem Ltd., Mumbai,
India) disc, was mixed with dry KBr. The mixture was ground
into a fine powder using an agate mortar before compressing
into KBr disc under a hydraulic press at 10,000 psi. Each KBr
Fig. 1. Surface plots showing the effect of various formulation components
381Design and Optimization of Mefloquine Hydrochloride
disc was scanned 16 times at 4 mm/s at a resolution of 2 cm−1
over a wave number region of 500–4,000 cm−1. The
characteristic peaks were recorded.
Differential Scanning Calorimeter (DSC)
Differential scanning calorimetry study of pure MFL, EE
and microparticles was performed using Differential Scanning
Calorimeter (Mettler Toledo, DSC 822). All the samples were
accurately weighed (5–8 mg), sealed in aluminium pan and
heated at a scanning rate of 5 °C/min. Nitrogen was used as
the purge gas with the flow rate set at 40 mL/min. Aluminum
pans and lid were used for all samples. An empty aluminum
pan was used as reference.
X-ray Powder Diffractometry (XRPD)
Vacuum grease was applied over a glass slide to stick the
sample. About 100 mg of sample was sprinkled over it to
make a layer having a thickness of ~0.5 mm. All the
experiments were performed on an X-ray diffractometer
(Philips X’Pert MPD, Eindhoven, The Netherlands) having
a sensitivity of 0.1 mg. The sample slide was placed vertically
at an angle of 0° in the sample chamber. An X-ray beam
(Philips Cu target X-ray tube) of 2 kW was allowed to fall
over the sample. As the slide moves at an angle of theta
degree, a proportional detector detects diffracted X-rays at
angle of 2θ°. XRD patterns were recorded using Philips
JPCD software for powder diffractometry.
Scanning Electron Microscopy (SEM)
The microparticles were mounted on brass stubs using
carbon paste. SEM micrographs were taken using a scanning
electron microscope (JSW-5610LV, Jeol Ltd, Tokyo, Japan) at
the required magnification at room temperature. a working
distance of 39 mm was maintained, and the acceleration
voltage used was 5 kv, using the secondary electron image
(SEI) as the detector.
RESULTS AND DISCUSSION
MFL is extremely bitter due to presence of quinine
moiety, suggesting a strong need to reduce the bitterness of
MFL. Therefore, microencapsulation method was employed
for reducing the bitterness of MFL in the present investigation.
Preliminary investigations of the process parameters
revealed that factors, drug (A) and polymer (B) concentra-
tion highly influenced the bitterness in human volunteers,
particle size and dissolution at pH 1.2 and 6.8. Hence these
responses were used for further systematic studies. The
dependent and independent variables were related using
mathematical relationships obtained with the statistical pack-
age, DOE v6.0.5 (Stat-Ease, Inc.). The fitted polynomial
equations (full and reduced model) relating the response to
the transformed factors are shown in Table IV. The polyno-
mial equations can be used to draw conclusions after
Table VI. Observed and Predicted Values of Response for 32Full Model
Particle Size (μ)±SD*
Dissolution at pH 1.2 (t15)±SDa
Dissolution at pH 6.8 (t5)±SDa
t15Percent drug dissolved in 15 min, t5percent drug dissolved in 5 min
aValues represent the mean±SD of 3 experiments
382Shah et al.
considering the magnitude of coefficient and the mathemat-
ical sign it carries, i.e., positive or negative.
Table V shows the results of analysis of variance
(ANOVA), which was performed to identify insignificant
factors (23). High values of correlation coefficient (R2) for all
dependent variables indicate a good model fit. F-value
compares the variance with the residual (error) variance. If
the variances are close, the ratio will be close to one and it is
less likely that the term has a significant effect on the response.
The model F-value implies that the model is significant for all
dependent variable. Prob>F is a probability seeing the
observed F value, if the null hypothesis is true (there is no
factor effect). Smaller probability values call for rejection of
the hypothesis i.e. if the Prob>F value is very small (less than
0.05), terms in the model have a significant effect on the model.
The terms having Prob> Fvalue more than 0.05 were omitted
in reduced model (24,25).
PRESS (predicted residual error sum of squares) indi-
cates how well the model fits the data. The coefficients for the
model were calculated without the first point. This new model
was then used to estimate the first point and calculate the
residual for point one. This was done for each data point and
the squared residuals were summed. PRESS values for all
formulation shows good fit of model.
Adj-R2measures variation around the mean explained
by the model, adjusted for the number of terms in model.
AdjR2¼ 1 ?
Pred-R2measures amount of variation in new data
explained by model. Adj-R2and Pred-R2values are in
reasonable agreement, signifying good model fit.
PredR2¼ 1 ?
Adequate precision (Adeq Precision) is a signal to noise
ratio. It compares the range of predicted value at the design
points to the average prediction error.
Adeq Precision ¼pd2
Where p is number of model parameters including
intercept (b0), d is residual MS from ANOVA table and n is
number of experiments. Both models, full model (FM) and
reduced model (RM), showed Adeq precision value greater
than 4, indicating adequate model discrimination.
Multiple linear regression analysis (Table IV) revealed
that A2and B2terms were insignificant for particle size and
dissolution at pH 1.2 while AB term was insignificant for
Fig. 2. Dissolution of optimized microparticles batch and MFL
Fig. 4. Response surface of combined desirability for measured
Fig. 3. Individual and combined desirability for measured responses
383Design and Optimization of Mefloquine Hydrochloride
dissolution at pH 6.8. A2term was insignificant for bitterness
score. The surface plots are shown in Fig. 1. The theoretical
(predicted) values were obtained by substituting the values of
A and B in the equation. It was found that the predicted
(theoretical) and experimental (observed) values were in
reasonably close agreement. Table VI shows the experimental,
predicted and residual values.
Percent yield and incorporation efficiency were two
important factors in the evaluation of the quality of the
microparticles. The percent yield of most of the micro-
particles was always exceeded 80%, while the incorporation
efficiency varied for all formulations, showed in Table II.
Incorporation efficiency improves with increase in polymer
(26). However higher quantity of EE solution prepared in 1%
acetic acid, showed solubilization of MFL. This resulted in
decreased incorporation efficiency (27). This finding suggests
that the present method is suitable for the preparation of
microparticles of a poorly water-soluble drug, such as MFL in
For particle size, drug concentration (A) is negative
while polymer concentration (B) is positive. This indicates
that on increasing EE concentration, particle size increases. It
was observed that the polymer viscosity influenced particle
size (26). Increasing the EE concentration have led to an
increase in its viscosity and consequently a decrease in the
frequency of dissociation or separation of the particles with
the addition of sodium hydroxide. This results in an increase
in the overall size of the microparticles.
In Vitro Drug Release
For dissolution in acidic pH, both drug (A) and polymer
(B) concentrations are positive. This indicates additive effect
of MFL concentration and EE concentration. This suggests
that the MFL release and solubility would be improved at
acidic pH. Release of MFL from the microparticles was
completed within few minute at acidic pH, followed by a
plateau. This may be because of the high porosity of the
microparticles, the hydrophilic nature of the EE, and
improved wettability, provided by the dissolved EE
(17,20,28). Dissolution profile is shown in Fig. 2.
For dissolution at pH 6.8, drug concentration (A) is
positive while polymer concentration (B) is negative. This
indicates that on increasing EE concentration, dissolution of
microparticles at pH 6.8 decreases. This finding suggests that
the drug release is polymer dependent. As the concentration
of EE was increased, thicker film was formed around the
MFL particles, which retarded the MFL release, because of
being insoluble at salivary pH (15). EE is expected to behave
as insoluble and inert material at pH 6.8 and showed slightly
decreased release rate. This is due to the decrease in drug
diffusion and/or membrane infiltration (20,28). In a neutral or
alkaline environment, the EE films swells, and slowly erodes
and dissolves (29). However, after 15 min the microparticles
starts swelling and releases MFL in normal way (30).
Table VII. Optimum Levels for the Independent Variables and their Responses
Actual Values of Independent Variables
Particle Size (μ)
Dissolution at pH 1.2 (t15in %)
Dissolution at pH 6.8 (t5in %)
A in g
B in mL#
Actual ± SD*
Actual ± SD*
Actual ± SD*
amL of 1% EE solution, t15– percent drug dissolved in 15 min, t5percent drug dissolved in 5 min
bValues represent the mean±SD of three experiments
384 Shah et al.
Gustatory Sensation Test
For bitterness score, drug concentration (A) is positive
while polymer concentration (B) is negative. This indicates
that on increasing EE concentration, bitterness score of
microparticles decreases. This finding is in agreement with
dissolution studies carried out at pH 6.8, because the pH of
the saliva is in the range from 6.3 to 7.2. Further it has been
reported that the MFL quinine moiety is responsible for the
higher bitterness score. It has been reported that MFL
produces bitterness by depolarizing taste cells by closing K+
channels (31). The microparticles are insoluble at salivary pH
and forms physical barrier between the MFL and K+channel
present in the cell membrane of taste buds. Thus reducing the
bitterness score of microparticles.
Optimization Using Desirability Function
Any process can only be authenticated when optimum
level of its variables (affecting the process) for microparticles
of best quality characteristics is recognized. Desirability
function is one excellent tool for identifying the optimum
levels of variables. In this procedure, all the measured
responses for independent variables which are supposed to
affect the quality of the microparticles are taken into
consideration. Some of these responses have to be minimized
Table VIII. Comparison of Responses Between Predicted and Experimental Values for the Cross-validation Set
Experimental Values ± SDa
Predicted Values Bias (%)
Particle size (μ)1
Dissolution at pH 1.2 (t15)
Dissolution at pH 6.8 (t5)
t15Percent drug dissolved in 15 min, t5percent drug dissolved in 5 minute, *Values represent the mean ± SD of 3 experiments
Fig. 5. FT-IR spectra of MFL, EE, blank microparticles and optimized microparticles
385Design and Optimization of Mefloquine Hydrochloride
and some have to be maximized, in order to pour desired
characteristics in the microparticles. Using the desirability
function, all the dependant variables were combined to get
one combined response i.e., the overall or combined desir-
ability. The combined desirability response was calculated
from the individual desirability of each of the responses using
DOE v6.0.5 (Stat-Ease, Inc.). The individual desirability of all
measured responses is reported in Fig. 3. The optimized batch
was identified with a combined desirability value of 0.83
(Fig. 4). Table VII enlists the optimized values for all the
independent process variables and their responses.
Cross Validation of the Model
The reliability of the equation that described the
influence of factors on all responses was assessed by cross
validation of the model. The response data for two indepen-
dent check point batches was collected (32). The experimen-
tal values and predicted values of each response are shown in
Table VIII. The percent relative error between predicted
values and experimental values of each response was
calculated using following equation.
PV ? EV
Where PV is predicted value and EV is experimental
value. The percent bias obtained from checkpoint batches
was in range of −100 to 4.80. A low value of percent bias
depicts that in all cases there was a reasonable agreement in
predicted and experimental values (33).
Fourier Transform Infra-red Spectroscopy (FTIR)
The optimization batch following the acceptable limits has
been further evaluated for physical characterization viz. FT-IR,
DSC and XRPD. Pure MFL and EE were also run as control.
The samples used for the study were prepared 48 h before and
preserved in desiccator before use. The FT-IR spectrum of
pure MFL, EE, blank microparticles and optimized micro-
particles are shown in Fig. 5. The characteristic peaks of MFL
at 3,110 cm−1are assigned to N–H stretching vibration. In
addition, the absorption peaks at 1,603, 1,363, 1,111, and
1,069 cm−1can be assigned to quinine ring stretching vibration.
The peak at 1,316 cm−1can be assigned to CF3stretching
vibration. The peaks at 2,875 and 2,918 cm−1are assigned to
C–H bridge and CH2respectively. The peak at 1,555 cm−1is
assigned to C=N/C=C. The peaks at 1,288 and 1,055 cm−1are
assigned to C–N and piperidine ring respectively. The peak at
1,174 cm−1is due to the C–C/N-H stretching vibration. The
spectrum of EE is dominated by the carbonyl (C=O) stretching
vibration at 1,735 cm−1and the ester C–O stretching vibrations
at 1,148 and 1,188 cm−1. In addition, C–H vibrations can be
discerned at 1,389, 1,450–1,490 and 2,962 cm−1. The
absorptions at 2,772 and 2,822 cm−1can be assigned to the
Fig. 6. DSC curve of MFL, EE, blank microparticles and optimized microparticles
386 Shah et al.
dimethyl-amino groups. The spectrum of microparticles
corresponds to the superimposition of MFL and EE with no
significant shift in the major peaks. This confirms presence of
MFL in microparticles.
Differential Scanning Calorimeter (DSC)
Figure 6 shows the DSC curve of pure MFL, EE, blank
microparticles and optimized microparticles. The pure MFL
shows an endothermic peak at 271.38 °C, followed by
exothermic peak at 308.36 °C. The characteristic endothermic
peak corresponding to melting peak of MFL was shifted
towards lower temperature (164.53 °C), with reduced intensity
in the microparticles, suggesting phase transition of MFL in
X-ray Powder Diffractometry (XRPD)
XRPD analysis was performed to confirm the results of
DSC studies. XRPD patterns of MFL, EE, blank micro-
particles and optimized microparticles are shown in Figure 7.
In X-ray diffractogram of MFL, sharp peaks at a diffraction
angle (2θ) of 11.52°, 14.31°, 16.37°, 18.03°, 20.11°, 21.26°,
23.37°, 25.50°, 32.57° indicates the presence of crystalline
drug, while microparticles shows sharp peaks at 7.88°, 13.84°,
14.80°, 16.56°, 17.82°, 19.57°, 20.50°, 22.23°, 23.39°. New peaks
at 7.88°, 13.84°, 17.82°, 19.57° and 22.23° were observed in
microparticles, indicating phase transition of MFL in EE
Scanning Electron Microscopy (SEM)
Figure 8 illustrated the SEM micrographs of MFL, EE
and optimized microparticles. MFL existed in needle shape
whereas EE was seen as small cubes. Original morphology of
both components was disappeared in microparticles. Micro-
particles showed encapsulation of the drug particles. There-
fore the close contact between the polymer and drug might be
responsible for masking the bitter taste in microparticles.
The study conclusively demonstrated complete taste mask-
ingofMFLinmicroparticlesusing EEaspolymer.Present work
suggests that both variables have its own significant complimen-
tary role in enhancement of the process rather than having
exclusive effect. The FTIR, DSC and XRPD studies indicated
interaction ofMFL,atthemolecular level,inEEmicroparticles.
pharmaceutical industries dealing with bitter drugs to improve
Fig. 7. XRPD patterns of MFL, EE, blank microparticles and optimized microparticles
387Design and Optimization of Mefloquine Hydrochloride
it is possible to mask the bitterness of single high dose (250 mg)
drugs like MFL with comparatively minimum concentration of
polymer for oral formulations.
The authors are thankful to Degussa India Pvt. Ltd.,
Mumbai for providing the polymeric material. Further the
support from STIC, Cochin is greatly acknowledged.
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389Design and Optimization of Mefloquine Hydrochloride