Biomaterials 24 (2003) 2789–2798

Scleroglucan/borax: characterization of a novel hydrogel system

suitable for drug delivery

T. Covielloa,*, M. Grassib, R. Lapasinb, A. Marinoa, F. Alhaiquea

aDipartimento di Studi di Chimica e Tecnologia delle Sostanze Biologicamente Attive, Universit "a ‘‘La Sapienza’’,

Piazzale Aldo Moro 5, 00185 Rome, ItalybDipartimento di Ingegneria Chimica, dell’Ambiente e delle Materie Prime, Universit "a di Trieste, P.zza Europa 1, 34127 Trieste, Italy

Received 1 October 2002; accepted 27 January 2003

Abstract

A new hydrogel, with scleroglucan using borax as a crosslinker, has been prepared. The physical gel has been loaded with a model

molecule (theophylline) and the release of the drug from the gel was evaluated. The same system was used to prepare tablets and the

delivery of theophylline in different environmental conditions (HCl and SIF) was determined. A recent theoretical approach has

been applied to the dissolution profiles obtained from the tablets and a satisfactory agreement has been found with the experimental

data. Furthermore, the diffusion coefficient of the model molecule was evaluated according to a suitable strategy that was tested on

two set of data obtained with different set-ups (permeation and diffusion experiments). A simplified mathematical approach allows

to reduce the two-dimensional problem of the Fick’s second law in a one-dimensional system leading to a much easier handling of

the data without loosing the accuracy of the original problem in two dimensions. The characterization of the gel has been also

carried out following the kinetics of swelling in terms of water uptake.

r 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Scleroglucan; Borax; Hydrogel; Modified release; Physically crosslinked gels

1. Introduction

Hydrogels are hydrophilic three-dimensional swella-

ble networks that can be obtained by chemical and/or

physical crosslinking of polymers. They show a wide

variety of applications as medical devices and in the field

of pharmaceutics [1]; in this sense, particular attention

has been focused, since several years, to the use of

hydrogels for modified release formulations [2,3]. This

type of study requires, together with a more practical

approach, also a careful and deep investigation on the

structure and on the morphology of the rate-controlling

polymeric network as well as an analysis of the diffusive

behavior of the tested drugs through and from the

hydrogel.

We report here the results of our studies on the

behavior of a new hydrogel prepared with scleroglucan

and borax.

Scleroglucan (Sclg) is a branched homopolysacchar-

ide consisting of a main chain of (1-3)-linked b-d-

glucopyranosyl units bearing, every third unit, a single

b-d-glucopyranosyl unit linked (1-6) (Fig. 1). This

polysaccharide is resistant to hydrolysis and its solutions

show an interesting rheological behavior: viscosity

remains practically constant, even at high ionic strength,

up to pH=12 and to 90�C.

Due to its peculiar properties, Sclg was extensively

used for various commercial applications (secondary oil

recovery, ceramic glazes, food, paints, cosmetics, etc.)

[4]; it was also investigated for modified/sustained

release formulations such as monolithic swellable

matrices [5–9] and ophtalmic preparations [10]. Oxidized

Sclg was proposed for pH-controlled delivery oral

dosage forms [11,12] and several crosslinked derivatives

have been prepared and studied for the same purposes

[13–19].

Borax is a crosslinker used with polymers containing

hydroxyl groups [20–31] that was previously studied for

the preparation of complexes with guar gum suitable for

colonic delivery purposes [32].

*Corresponding author. Tel.: +39-06-4991-3300; fax: +39-06-4991-

3133.

E-mail address: tommasina.coviello@uniroma1.it (T. Coviello).

0142-9612/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved.

doi:10.1016/S0142-9612(03)00087-5

The characterization of the new hydrogel in the

present study was performed in terms of water uptake

and permeation experiments. Furthermore, the drug

release from the swollen hydrogel as well as from tablets

prepared with the freeze-dried product was determined;

in both cases theophylline (TPH) was used as a model

drug.

A suitable strategy, that allows to simplify the

mathematical procedure, was applied to the data

obtained from two different experimental procedures

in order to evaluate the diffusion coefficient of TPH and

the trend of the dissolution profiles from the tablets was

studied according to Dokoumetzidis–Macheras [33].

2. Materials and methods

2.1. Purification of scleroglucan

A given amount of Sclg (Actigum CS 11), provided by

Mero-Rousselot-Satia (France) (molecular weight=

1.4� 106 from viscometric measurements) was dissolved

in distilled water, then kept under magnetic and

mechanical stirring at room temperature for 24 h. The

solution was exhaustively dialyzed at 7�C against

distilled water and then freeze-dried.

2.2. Hydrogel preparation

The gel was obtained, in a beaker, by addition of a

calculated amount (i.e. moles of borax=moles of

repeating unit of Sclg) of 0.1m borax to a polymer

solution previously prepared; the mixture was magneti-

cally stirred for 5 min and then left overnight for gel

setting. The final polymer concentration (cp) was 0.7%

(w/v).

When needed the gel was loaded with TPH (Carlo

Erba product). For this purpose a given amount of drug

was dissolved in the polymer solution before the

addition of borax (Carlo Erba product).

All experiments were carried out in triplicate.

2.3. Release experiments from gels

The gel, freshly prepared in a beaker, was obtained

with the cylindrical shape of the glass vessel

(height=1.0 cm, diameter=2.2 cm) and it was tested

for the release of TPH, chosen as a model drug, at 7�

and 37 �C. For release experiments the gel was soaked in

an appropriate medium (V ¼ 200:0 cm3), i.e., distilled

water (pH=5.4), SIF (pH=7.4, phosphate buffer

according to USP. XXIV) or NaOH at different

concentrations (pH=10, 12, 13 and 14).

The gel was kept at a certain height from the bottom

of the container by a thin web, while the medium was

gently magnetically stirred. Three-milliliter samples were

withdrawn from the solution at appropriate time

intervals and replaced with the same amount of fresh

solvent.

TPH was spectrophotometrically detected at 272 nm

(Perkin-Elmer, lambda 3a, UV-Vis spectrometer) using

quartz cells with pathlengths of 1.0 or 0.1 cm.

The possible erosion of the gel, in terms of polymer

dissolution in the medium during the release experi-

ments, was quantitatively determined by a colorimetric

method [34], using phenol in the presence of sulfuric

acid.

2.4. Tablet preparation

For the preparation of the tablets about 160 mg of

Sclg and 20 mg of TPH were magnetically stirred in

water for 24 h. Then the calculated amount of 0.1m

borax was added and the system was kept under

magnetic stirring for 5min. The obtained gel

(cp ¼ 0:7%; r ¼ 1:0) was kept overnight at 7�C and then

freeze-dried.

Tablets were finally prepared from the freeze-dried

sample with an IR die (Perkin-Elmer hydraulic press)

using a force of 5.0 kN. The weight of tablets was

230710 mg, the diameter was 13.0070.05 mm and the

thickness was 1.4070.10 mm.

2.5. Release experiments from tablets

Release experiments from the model dosage forms

were carried out according to USP. XXIV, using the

rotating basket apparatus at 37.070.1�C, 100 rpm and

three different dissolution media: SGF (pH=2.0),

distilled water (pH=5.4) and SIF (pH=7.4).

Aliquots of the dissolution medium were taken at

fixed time intervals, released TPH was spectrophotome-

trically determined and the same amount of fresh

solvent was added.

Fig. 1. Repeating unit of Sclg.

T. Coviello et al. / Biomaterials 24 (2003) 2789–27982790

2.6. Water uptake and height increase studies

Water uptake was evaluated by the relative increase of

weight of the tablets in distilled water at 37�C. During

the experiment, the dimensional variations of the tablets

were evaluated with a caliper with appreciation to

0.2 mm.

2.7. Permeation experiments

Permeation experiments were carried out at constant

temperature (3770.5�C) under magnetic stirring using a

two-compartment diffusion cell (Fig. 2). The compart-

ment A (V ¼ 1:0 cm3), separated from the receptor

compartment B (V ¼ 14:5 cm3) by a cellophane mem-

brane (Visking tubing, cut-off 12.000), contained the gel

of Sclg/borax loaded with TPH. The diffusion of the

model drug from the gel to the receptor compartment B

containing distilled water was spectrophotometrically

evaluated. An appropriate blank, i.e., a TPH solution in

compartment A, was used as reference. The cellophane

membrane in no case was the rate-limiting step of the

overall diffusion mechanism through the gel.

2.8. Data analysis

A fundamental prerequisite for an appropriate

utilization of a swollen gel as a modified release system

is the knowledge of its diffusive characteristics, usually

represented by the diffusion coefficient exhibited by a

model drug moving through the network meshes.

Among the different experimental set-ups that can be

designed for the calculation of the diffusion coefficient

[35] we considered and compared two of them. Accord-

ingly, for the first case we studied the cylindrical gel

described in Section 2.3, not undergoing significant

erosion and/or further swelling (being the hydrogel

already in equilibrium conditions), that releases a model

drug into a stirred solution. For the second case a two-

compartment permeation cell was considered in order to

calculate the diffusion coefficient (see Fig. 2).

The first case requires the solution of Fick’s second

law at least in a two dimensions (2D) cylindrical

coordinates system, while the second one needs a Fick’s

second law solution in a one dimension (1D) rectangular

coordinates system.

Since in the first case a time consuming numerical

technique is required, we proposed, as reported

below, a possible way to overcome such a problem by

reducing the 2D problem to a much easier to handle 1D

problem without loosing the accuracy of the original 2D

solution.

2.8.1. Release from a cylinder

Supposing a constant drug diffusion coefficient D and

a negligible gel density variation due to the diffusion

process, Fick’s second law, in a 2D cylindrical coordi-

nates system, can be written as

qC

qt¼

D

R

q

qRRqC

qR

� �

þDq2C

qZ2; ð1Þ

where t is time, C is the drug concentration (mass/

volume) in the cylinder, R and Z are the radial and axial

axes, respectively. This equation must satisfy the

following initial and boundary conditions; initial condi-

tions:

CðZ;RÞ ¼ C0; �ZcpZpZc 0pRpRc; ð2Þ

Crel ¼ 0 ð3Þ

Fig. 2. Schematic representation of a two-compartment diffusion cell (a and b).

T. Coviello et al. / Biomaterials 24 (2003) 2789–2798 2791

boundary conditions:

CðZ;Rc; tÞ ¼ Cð7Zc;R; tÞ ¼ kpCrelðtÞ; ð4Þ

VrelCrelðtÞ ¼ pR2c2ZcC0 �

Z Zc

�Zc

Z Rc

�0

CðZ;R; tÞ2pR dR dZ;

ð5Þ

where 2Zc and Rc are, respectively, the cylinder height

and radius, C0 is the initial drug concentration in the

cylinder, Crel and Vrel are the drug concentration

and the volume of the release medium and kp is the

drug partition coefficient between the cylindrical gel

and the environmental release fluid. Eqs. (2) and (3)

state that the release environment is initially drug free,

while the cylinder is uniformly loaded by a drug

concentration C0: Eq. (4) expresses the partitioning

condition at the cylinder/release fluid interface, while

Eq. (5) is a drug mass balance for the cylinder/release

fluid system, that allows to state the relation between

Crel and CðZ;R; tÞ: The equations set (1)–(5) can be

numerically solved by means of the control volume

method [36].

Due to the fact that Eq. (1) data fitting can be very

heavy (if not impossible) in terms of calculation

time when the number of control volumes considered

increases (we noticed that, practically, on a Pentium IV

1.7 GHz personal computer, 225 (15� 15 grid)

control volume elements represents the upper limit

for data fitting), we propose a possible way to reduce

the 2D problem in a simpler 1D problem. Due to the

neatly lower calculation time, the 1D problem solution

can be simply embodied in an Excel macro (as user

defined function) to be used directly as one of the other

native Excel functions. In this manner, this could be a

useful tool also for researchers that are not so used to

handle mathematical equations.

The strategy adopted to perform the 2D–1D

transformation is based on the idea of finding

the correction factor to be applied to the 1D solution

to make it coincident with the 2D one, provided

the same boundary and initial conditions are con-

sidered. In order to optimize the numerical solution

procedure (control volume method [36]) of the 1D

problem, we suppose to divide the cylinder in

cylindrical shells (computational elements), character-

ized by the same ratio K between the height (2Z)

and the corresponding radius (R) (see Fig. 3).

Consequently, the volume of the generic cylindrical

shell is given by

dV ¼ dð2ZpR2Þ ¼ dðKpR3Þ ¼ 3pKR2 dR

K ¼2Zc

Rc

¼2Z

R: ð6Þ

Supposing a uniform drug concentration inside the

cylindrical shell, Fick’s second law reads

�dVqC

qt¼ 2pðRþ dRÞ2 Z þ dZð ÞNRþdR

� 4pRZNR þ 2pðRþ dRÞ2NZþdZ � 2pR2NZ;

ð7Þ

where NR and NRþdR are, respectively, the radial matter

fluxes evaluated in R and Rþ dR; while NZ and NZþdZ

are, respectively, the axial matter fluxes evaluated in Z

and Z+dZ (note that the factor 2 in the axial balance is

related to the fact that drug diffusion takes place

through both the two cylindrical shell bases). Recalling

that

NZ ¼ �DqC

qZ

�

�

�

�

Z

¼ �D2

K

qC

qR

�

�

�

�

R

¼2

KNR

NZþdZ ¼ �DqC

qZ

�

�

�

�

ZþdZ

¼ �D2

K

qC

qR

�

�

�

�

RþdR

¼2

KNRþdR

ð8Þ

we finally have the expression of Fick’s second law on

this particular kind of computational elements:

qC

qt¼

2

3

2 þ K2

K2

� �

1

R2

q

qRR2D

qC

qR

� �

: ð9Þ

Of course, the above-described mathematical treatment

makes Eq. (9) solution different from that of Eq. (1), as

we started from a 2D diffusion in a cylinder and,

basically, we get the equation describing the diffusion in

2Zc

2Rc

2(R+dR)

2Z

2R

2(Z+dZ)

Fig. 3. Schematic representation of the cylindrical shells used to solve

Fick’s second law in order to reduce the 2D diffusion problem in a 1D

diffusion problem.

T. Coviello et al. / Biomaterials 24 (2003) 2789–27982792

a sphere [37]. Our goal is to find out a correction factor

making the two solutions coincident, provided that

Eq. (9) satisfies the following initial and boundary

conditions:

initial conditions

CðRÞ ¼ C0; 0pRpRc; ð10Þ

Crel ¼ 0; ð11Þ

boundary conditions

CðRc; tÞ ¼ kpCrelðtÞ; ð12Þ

VrelCrelðtÞ ¼ pR2c2ZcC0 �

Z Rc

0

C R; tð Þ3pKR2 dR: ð13Þ

Obviously, these equations express the same conditions

set by Eqs. (2)–(5). Accordingly, the cylinder is, initially,

uniformly drug loaded (Eq. (10)), the release environ-

ment is initially drug free (Eq. (11)), partitioning

conditions hold at the gel/external fluid interface

(Eq. (12)) and a global mass balance is considered in

order to state the relation between Crel and CðRÞ:It is possible to numerically verify that Eqs. (1) and

(9) solutions are approximately equal if a proper

correcting factor f ðKÞ is introduced in Eq. (9):

f ðKÞ ¼ 0:797ð1 � e�ð0:677ðKþ0:993ÞÞÞ ð0:5oKo16Þ: ð14Þ

The f dependence on K has been determined by

considering the dimensionless expression of Eqs. (1)

and (9):

qCþ

qt¼

1

Rþ

q

qRþRþqC

þ

qRþ

� �

þq2Cþ

qðZþÞ2; ð10Þ

qCþ

qt¼ f Kð Þ

2

3

2 þ K2

K2

� �

1

ðRþÞ2q

qRþðRþÞ2

qCþ

qRþ

� �

; ð90Þ

where

t ¼ tD=R2c ; Cþ ¼ C=C0; Rþ ¼ R=Rc; Zþ ¼ Z=Rc:

ð15Þ

The solution of Eq. (10) for a discrete set of different K

values (0:5oKo16) and the choice, for each K value, of

the proper f value allow the overlapping of Eqs. (90) and

(10) solutions. Accordingly, Fig. 4 can be drawn, where

the correcting factor f (circles) is reported for the

discrete K set chosen. In order to generalize this result,

we successfully fit the f trend on K by means of the

following exponential equation (solid line in Fig. 4):

f ðKÞ ¼ a� 1 � e�ðb�ðKþgÞÞ� �

; ð16Þ

whose best fit parameter values (a; b and g) are those

shown in Eq. (14). It is evident that, for KX6; f

becomes constant and equal to 0.8, while, for lower K

values, it progressively decreases. We limited our

analysis to the above-mentioned K range because, for

Ko0:5 and K > 16; the 2D diffusion problem can be,

respectively, approximated to a 1D totally axial or

totally radial diffusion problem.

As an example, in the case of K ¼ 1 (fE0:7), Fig. 5

reports the trend of the ratio Crel=Crelinf (where Crelinf is

the Crel value at infinite time) vs. the dimensionless time

t for Eqs. (10) (open circles) and (90) (solid line). The

coincidence of the solutions is evident.

According to the above-reported speculations, it is

interesting to underline that, ultimately, we suggest an

empirical method for the acquisition of an approximate

analytical solution of Eq. (10), resorting to Eq. (90).

Thus, Eq. (9) solution will coincide with that of Eq. (1),

provided that the correcting factor f is considered in

Eq. (9):

qC

qt¼ f ðKÞ

2

3

2 þ K2

K2

� �

1

R2

q

qRR2D

qC

qR

� �

: ð900Þ

Interestingly, a different choice of the computational

shells shape would reflect only on the analytical

expression of the correcting factor f as the constant

factor multiplying the term ð1=R2Þðq=qRÞðR2DqC=qRÞ in

Eqs. (9) and (900) would be different.

0.4

0.5

0.6

0.7

0.8

0.9

0 2 4 6 8 10 12 14 16 18K

f(K

)

Fig. 4. Correcting factor f (circles) dependence on a discrete set of K

values necessary to ensure the equivalence of the Eqs. (10) and (90)

solution. This trend can be profitably fitted by Eq. (16) (solid line).

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 0.05 0.1 0.15 0.2

τ

Cre

l/C

rel

inf

eq.(1')

eq.(9')

Fig. 5. Comparison between the solution of Eq. (10) (open circles) and

Eq. (90) (solid line) when K ¼ 1:

T. Coviello et al. / Biomaterials 24 (2003) 2789–2798 2793

2.8.2. Permeation

In order to calculate the drug diffusion coefficient

from permeation data, it is necessary to solve the 1D

Fick’s second law inside the gel and the cellophane layer

(see Fig. 2b). For this purpose, we used a recently

proposed model [16,17] whose main characteristics are

here briefly recalled. Fick’s second law equations for the

gel and the cellophane layer read

qC

qt¼

q

qXDqC

qX

� �

; ð17Þ

qCc

qt¼

q

qXDc

qCc

qX

� �

; ð18Þ

where D; Dc; C and Cc are, respectively, the drug

diffusion coefficients and concentrations in the gel and

in the cellophane layer. The above-reported equations

must be solved with the following boundary conditions:

qC

qX

�

�

�

�

X¼0

¼ 0; ð19Þ

Dc

qCc

qX

�

�

�

�

X¼hg

¼ DqC

qX

�

�

�

�

X¼hg

; ð20Þ

Vr

dCr

dt¼ �DcS

qCc

qX

�

�

�

�

X¼hgþhc

; ð21Þ

C

Cc

¼ kpg;Cc

Cr

¼ kpc; ð22Þ

and the following initial conditions:

Cr ¼ 0; ð23Þ

Cc ¼ 0; hgoXohg þ hc; ð24Þ

C ¼ C0; 0oXohg; ð25Þ

where Vr represents the receptor volume, Cr is the drug

concentration in the receptor compartment at time t; Sis the permeation surface, hc and hg are the thicknesses

of the cellophane layer and that of the gel, while kpc and

kpg are the drug partition coefficients of the cellophane

layer and that of the gel with respect to the solution of

the receptor compartment. Eq. (19), zeroing the drug

concentration gradient, ensures that no matter flux can

exist at X ¼ 0 where a drug-impermeable layer is placed.

Eq. (20) imposes that the drug flux leaving the gel is

equal to that entering the cellophane (X ¼ hg); Eq. (21)

ensures that the drug entering in the receptor compart-

ment is equal to that leaving the cellophane layer, so

that no mass accumulation occurs at the cellophane/

receiver–fluid interface. Eq. (22) imposes the drug

partitioning conditions at the gel/cellophane and

at the cellophane/receptor fluid interfaces, respectively.

Eqs. (23) and (24) state that the receptor compartment

and the cellophane layer are initially drug free, while

Eq. (25) sets to C0 the drug concentration in the gel.

Eqs. (17)–(25) need a numerical solution [36].

3. Results and discussion

3.1. Gel stability test

In order to verify if and when erosion of a Sclg–borax

matrix can be considered negligible, the amount of

polymer dissolved in the medium was detected as a

function of time by the colorimetric method. The data

reported in Table 1 show how up to pH=10 the erosion

of the gel is practically absent for at least the first 8 h,

and even after 1 day the loss of polymer is very low. At

higher pH values, the dissolution of the matrix becomes

more appreciable; anyhow, after 24 h half of the gel is

still intact at pH=12, while it is completely dissolved at

pH=13.

3.2. Release experiments from the gel

Experiments on model drug release were carried out

from both a freshly gel (i.e., in its swollen form),

reported in this paragraph, and from tablets (i.e. freeze-

dried and compressed gel); in both cases reproducibility

is such that error bars, related to the experimental data,

are smaller than the dimensions of the symbols used in

the figures.

On the basis of the gel stability test, we focused our

attention on the TPH release from a cylindrical gel at

37�C and pH=5.4 (indeed, in this condition the gel does

not undergo erosion). Fig. 6 shows the reasonably good

agreement between the experimental data (circles)

and Eq. (900) best fitting (solid line) performed knowing

that Rc ¼ 1:1 cm, K ¼ 1:771; C0 ¼ 4486 mg/cm3, Vrel ¼

200 cm3 and assuming kp ¼ 1: The resulting diffusion

coefficient is D ¼ ð7:472:1Þ � 10�6 cm2/s which is

Table 1

Percentage of gel erosion at different pH values, at 37�C

Time (h) pH=5.4 pH=7.4 pH=10.0 pH=12.0 pH=13.0

1 — — 0.9 3.5 3.2

3 — — 2.2 7.7 11.3

8 — — 5.2 19.5 27.2

24 5.3 7.5 13.3 48.0 94.6

T. Coviello et al. / Biomaterials 24 (2003) 2789–27982794

practically coincident with the D value supplied by the

Eq. (1) fitting on the same data.

The determination of the TPH diffusion coefficient,

calculated by fitting Eqs. (17) and (18) on the permea-

tion data (Fig. 7), obtained considering S ¼ 1:77 cm2,

C0¼5546 mg/cm3, Vr¼14:5 cm3, hg¼0:6 cm, hc¼0:005 cm,

Dc ¼ 2:72 � 10�6 cm2/s [16], and assuming kpg ¼ kpc ¼

1; leads to D ¼ ð4:270:05Þ � 10�6 cm2/s. The discre-

pancy between the two values of D (in principle they

must be equal) can be explained considering the fact that

the geometrical hypothesis (perfectly cylindrical shape

of the delivery system) assumed in the first case is surely

less reliable than that occurring in the permeation case

where the system geometry is ensured by an outer

boundary (the permeation cell apparatus). This is

substantiated by the lower D standard deviation in the

permeation case (0.05� 10�6 cm2/s) with respect to the

cylinder case (2.1� 10�6 cm2/s) (standard errors have

been calculated performing data fitting on each of the

three experimental repetitions in order to get three

diffusion coefficient values. Then, mean value and

standard deviation have been determined). In this sense,

we believe that our findings are reasonably reliable in

both cases. Moreover, it is possible that, in the case of

release experiments from the gel, there is a little

convective contribution to TPH release, due to the

almost negligible gel erosion (see Table 1), that could

determine an apparent increase of the diffusion

coefficient. In Fig. 8 TPH release rates from the

hydrogel, collected at different pH values (from

pH=5.4 to 14.0), are reported as Mt=MN; where Mt

indicates the amount of TPH released at the time t

and MN indicates the amount of drug released at

infinite time (corresponding to the total amount

loaded in the formulation). It is possible to observe

that, while at pH=14.0 the sample is completely

dissolved within the first 30 min and all the loaded drug

is rapidly released, at lower pH values the presence of

the gel leads to a remarkably reduced release rate.

Furthermore, the shape of the profiles indicates that the

gel behavior is not appreciably influenced by environ-

mental pH variations.

This result allows us to suggest a connection bet-

ween the model drug release and a mechanism

of diffusion and/or relaxing of the polymeric chains

within the pH range 5.4–13.0. That points out that,

when erosion occurs, it does not affect significantly

the overall mechanism of release. On the contrary,

at pH=14, as expected from the gel stability test,

erosion becomes the predominant process which leads to

an almost immediate release of TPH (see Fig. 8) with a

Fig. 8. Release profiles of TPH from gels in different media at 37�C.

y = 3.884x - 0.536

r2 = 0.998

0

2

4

6

8

10

12

0.0 0.5 1.0 1.5 2.0 2.5 3.0

time0.5 (h0.5)

(w-w

0)/w

0

Fig. 9. Water uptake from tablets, at 37�C, reported as a function of

the square root of time.

0

100

200

300

400

0 5 10 15 20 25time (h)

C ( µ

g/cm

3 )

Fig. 7. Comparison between the experimental permeation data from

the two-compartment cell (circles) and the best fitting (Eqs. (16) and

(17), solid line).

0

10

20

30

40

50

60

70

80

90

0 5 10 15 20 25

time (h)

Cre

l (µg

/cm

3)

data

model

Fig. 6. Comparison between the experimental release data from

cylinders (circles) and the 1D model best fitting (Eq. (900), solid line).

T. Coviello et al. / Biomaterials 24 (2003) 2789–2798 2795

complete dissolution of the matrix within the first

30 min.

3.3. Water uptake and height increase studies

The increase of weight of the tablets (prepared from

freeze-dried gels loaded with TPH) was determined at

37�C as a function of time. After 2 days, equilibrium

was reached and a maximum relative increase of weight

equal to twenty was detected. The experimental values,

reported as a function of the square root of time (Fig. 9),

give a straight line, suggesting that solvent penetration

within the matrix occurs, macroscopically, according to

a Fickian process.

As it is possible to observe from Fig. 10, water uptake

leads to an anisotropic swelling of the matrix that takes

place essentially in the axial direction while it is almost

negligible in the radial direction. It is worth to underline

that, as far as we know, this is the first time that an

anomalous swelling of a polymeric matrix is found; thus

work is in progress to elucidate the mechanism of such

peculiar behavior. As the water uptake rate, also the

increase of height shows a linear trend when reported as

a function of the square root of time.

3.4. Release experiments from tablets

When the gels loaded with TPH and freeze-dried were

used as matrices for tablets, a release behavior similar to

that obtained with freshly prepared gels was observed.

Again no appreciable differences were detected ranging

from SGF (pH=2.0) to SIF (pH=7.4). The data,

reported in Fig. 11, show how the solvent pH does not

affect the model drug release from tablets.

Being the dissolution curves practically coincident, we

can assume that the solvent penetration rate into the

polymer rules out the TPH release both in SGF and in

SIF.

3.5. Modeling of dissolution from tablets

The problem of data modeling in the case of a

swelling tablet is not a trivial task because of the

numerous phenomena involved in the overall release

process. Moreover, the classical approach based on

Fick’s second law is not suitable for this purpose since

matrix continuity, fundamental prerequisite for a

classical diffusion analysis, cannot be accomplished,

especially at the beginning of the release process.

Fig. 10. Pictures of a tablet before (right) and after (left) swelling (a red dye was used for a better visualization).

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 1 2 3 4 5 6 7 8 9

Φ =

Mt/M

inf

experimental pH = 2model pH = 2experimental pH = 5.4model pH = 5.4experimetal pH = 7.4model pH = 7.4

time (h)

Fig. 11. Release profiles from tablets (symbols) and model best fitting

(Eq. (28)) of TPH at 37�C and at different pH values.

T. Coviello et al. / Biomaterials 24 (2003) 2789–27982796

Accordingly, a possible alternative is the approach

proposed by Dokoumetzidis–Macheras [33]; in his

model only discrete time intervals are considered and

what happens in between is ignored. Thus it is possible

to write an empirical expression where the amount of

drug that dissolves during the experiment is not any

more function of time but it is described in terms of

subsequent generations.

The authors, defining Xn and Yn as the population of

the drug molecules in the solid state and in solution in

the nth generation, respectively, describe the change of

Yn at the nþ 1 generation as follows:

Ynþ1 ¼ Yn þ RXn ¼ Yn þ RðX0 � YnÞ; ð26Þ

where R is a proportionality parameter and X0 is the

population of drug molecules in the solid state,

corresponding to the initial drug concentration in the

delivery system. Taking into account that the drug has a

solubility threshold in the release environment, Eq. (26)

becomes

Ynþ1 ¼ Yn þ RðX0 � YnÞ 1 �Yn

y

� �

; ð27Þ

where y is the saturation level of the population, i.e drug

solubility. If Eq. (27) is normalized in terms of dose (X0)

and if we define Fn ¼ ðYn=X0Þ; we obtain

Fnþ1 ¼ Fn þ Rð1 � FnÞ 1 �FnX0

y

� �

; ð28Þ

where Fn and Fnþ1 represent the drug mass fraction

dissolved at generation n and nþ 1; respectively. On the

basis of Eq. (28), knowing that X0=y is equal to

1.4� 10�3 and assuming that a new generation occurs

every 0.25 h, we fitted our experimental results as shown

in Fig. 11. Here it is possible to observe that, although a

systematic bias exists between data (symbols) and model

(solid lines), nevertheless the fitting is to be considered as

quite satisfactory. Although using Eq. (28) we a priori

renounced to any physical characterization of our

delivery system (we cannot estimate, for example, the

drug diffusion coefficient), Eq. (28) actually helps us to

compare the three different situations studied. The

calculated R values (R ¼ 0:162 pH=2.0; R ¼ 0:136

pH=5.4; R ¼ 0:143 pH=7.4) underline that, from the

Eq. (28) standpoint, the three situations do not appre-

ciably differ among each other.

4. Conclusions

The hydrogel, obtained with Sclg and borax, appears

to be suitable for a sustained drug delivery as indicated

by the results obtained when the hydrogel is loaded with

TPH. A similar behavior was observed when a swollen

gel was used and when the freeze-dried hydrogel was

used as matrix for tablets. A new theoretical approach,

to evaluate the diffusion coefficient of TPH, has been

applied to the data acquired by two different experi-

mental set-ups. The mathematical method allows to

solve the Fick’s second law in one dimension without

any loss of accuracy of the original system in two

dimensions.

The profiles release of TPH from tablets in different

media have been analyzed in term of the model

proposed by Dokoumetzidis–Macheras; a satisfactory

agreement was found between the model and the

experimental data in all the cases that were investigated.

The swelling of the hydrogel has been monitored,

leading to the assertion that the overall process obeys

to a Fickian mechanism.

Acknowledgements

This work was carried out with the financial support

of MIUR.

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