CHAPTER EIGHT
APPLICATIONS OF THE DEGRADABLE INTERPENETRATING
POLYMERIC NETWORKS AND HYDROGELS IN CONTROLLED
DRUG DELIVERY
Ana-Maria Oprea, Raluca Petronela Dumitriu, Irina Elena RÎ
schip,
and Cornelia Vasile"
 P. Poni Institute of Macromolecular Chemistry, Physical Chemistry of Polymers Department,
41 A Gr. Ghica Voda Alley, 700487, Iasi, Romania
8.1. Introduction: Principles of the Controlled Drug Delivery
For most biomedical applications, biodegradable hydrogels are favored
over nondegradable gels since they degrade in clinically relevant time
scales under relatively mild conditions. Compared to nondegradable hy-
drogels, degradable carriers do not require additional surgeries to re-
cover the implanted gels. However, proper techniques for predicting hy-
drogel degradation rates are critical for successful application of these
degradable systems as they facilitate the design of implants with optimal
degradation profiles that result in proper rates of drug release or tissue
regeneration, hence maximizing therapeutic effects. The fabrication and
modeling of hydrolytically degradable hydrogels are well-developed. For
example, West and Hubbell fabricated PLA-b-PEG-b-PLA hydrogels
composed of poly(lactic acid) (PLA) and poly(ethylene glycol) (PEG)
block copolymers for protein release applications [1].
While all polymers will eventually degrade under extreme environ-
mental conditions (high temperatures or low pH solutions), biodegradable
hydrogels degrade over clinically relevant time scales under relatively
mild conditions (aqueous solutions, physiological temperature, and pH)
[2]. Hydrogels are potential candidates for many different biomedical
applications like diagnostic, therapeutic, and implantable devices, such as
catheters [3], biosensors, artificial skin, controlled release drug delivery
systems (because of their drug diffusion, swelling ratio, and specific mesh
or pore size) [4 8], contact lenses [9], and tissue engineering, because of
their biocompatibility with the human body. In addition to this, hydrogels
resemble natural living tissue more than any other class of synthetic
"
Corresponding author. [e-mail]; [e-mail]
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 337
biomaterial due to their high content water, transport properties, and
tissue-like physical and mechanical behavior [10].
Biodegradable hydrogels, natural (derived from natural sources such
as chitosan, gelatin, dextran, etc.) or synthetic, degrade in vivo either
enzymatically or nonenzymatically to produce biocompatible or nontoxic
by-products and, therefore, surgical removal of the exhausted delivery de-
vice can be avoided [11]. Biodegradable hydrogels, if correctly designed,
will break down into lower molecular weight, water-soluble fragments in
vivo that can then be resorbed or excreted by the body once the desired
function of the gel is accomplished [2].
Development of optimized drug delivery systems using biodegradable
polymers can offer significant improvement in patient comfort and com-
pliance. These systems in many cases reduce the dose intake and thus
unwanted toxicities, as well as providing better therapeutic efficacy owing
to continuous availability of drug in the therapeutic ranges over a long
period of time; the stimuli-responsiveness of a hydrogel network can also
mediate the amount and rate of drug delivery [11].
The drugs are usually in contact with water and thus the drug solu-
bility is an important factor in drug release. The release of drugs with
appreciable water solubility will be rapid and independent of the matrix
degradation rate. Thus, in general, hydrogels may not be suitable for the
controlled release of most low-molecular-weight, water-soluble drugs.
The biodegradable hydrogel systems are useful for the delivery of macro-
molecular drugs, such as peptides and proteins, which are entrapped in
the gel network until the gel is degraded [12].
The treatment of the disease states has traditionally involved the use of
multiple daily dosing of a therapeutic agent using a conventional dosage
form like tablets or capsules. In order to achieve successful administra-
tion, a parent drug chemical needs to be mixed with other ingredients
into a pharmaceutical formulation. Together, these accessory ingredients
form the carrier of the parent drug. If the drug remains associated with
the carrier after administration so that biodistribution of the drug follows
that of the carrier, the carrier is then considered to be a delivery system
for the drug. The drug is assembled with the delivery system either by
attachment through covalent bonds or by noncovalent interactions such
as encapsulation, solubilization, association, or adsorption. The delivery
system thus protects the drug from degradation and elimination, and
redirects distribution of the drug.
Drugs can be introduced in the human body by various anatomical
routes. They may be intended for systemic effects or targeted to various
338 CHAPTER EIGHT
organs and diseases. The choice of the route of administration depends on
the disease, the effect desired, and the product available [13].
In oral administration, the drug is absorbed into the systemic circula-
tion by the following consecutive stages:

drug diffusion through the matrix of the dosage form,

drug dissolution within the aqueous fluid of the gastrointestinal tract,

drug diffusion through the aqueous fluid of the gastrointestinal tract to
the surrounding tissue,

absorption of the drug across the wall of the gastrointestinal tract, and

entry into the systemic circulation and deposition at the required site of
action.
The profiles of the drug plasma concentration as a function of time
following oral administration (conventional)/controlled release of an oral
dosage form are represented in Figure 8.1.
In conventional oral drug delivery systems (solid line), when the drug
is released from the dosage form, the concentration in the blood plasma
level rapidly rises and then exponentially decays as the drug is excreted
and/or metabolized, within a short (defined) period  allowing subsequent
absorption into the systemic circulation  the onset and duration of effect
of a therapeutic agent being controlled by the absorption step. The mass
and rate of drug absorption from conventional oral dosage forms, being
so rapid, will increase concentrations of drug in the systemic circulation
[14, 15]. In a typical profile of the concentration of drug in the plasma as a
function of time following, administration of two doses of a conventional
oral dosage form (Figure 8.1) three regions can be observed:
(a) the subtherapeutic range, in which the concentration of drug in the
systemic circulation is insufficient to render a therapeutic response;
Figure 8.1 The profiles of the drug plasma concentration as a function of time following oral
administration (conventional)/controlled release of an oral dosage form (adapted from [184]).
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 339
(b) the therapeutic region where the control of the disease state is opti-
mal; and
(c) the third region in which the concentration of the drug is toxic and
exceeds the maximum safe plasma concentration.
In controlled drug delivery system (dotted line), the frequency of dosing
is dramatically reduced, the concentration of therapeutic agent being
maintained within the therapeutic window for a prolonged period, thereby
reducing the incidence of side-effects.
Other administration route for drug delivery is intravenous injection
of an aqueous form into a superficial vein or continuous infusion via a
needle or a catheter placed in a superficial or deep vein, the dose being
distributed rapidly throughout the vascular system. Theoretically, none
of the drug is lost, and smaller doses are required than with other routes
of administration. The rate of infusion can be controlled for prolonged
and continuous administration. A system delivering via this route must
fulfill three requirements if it is to deliver a drug to the target cells. First,
the payload needs to remain intact with the carrier before reaching the
target site [16]. Premature cleavage or leakage of the drug from its carrier
not only will decrease the amount of drug that reaches the target site
but also will result in elevated systemic toxicity. Therefore, the delivery
system must tolerate assaults from plasma such as opsonin adsorption
and enzyme degradation. Second, a delivery system must remain in the
circulation long enough to have time to accumulate in the target cells
[17]. In order to have a long duration of circulation, the delivery system
needs to avoid quick clearance by the mononuclear phagocyte system
(MPS; also referred to as the reticuloendothelial system). If the target
is the vascular endothelial cell layer, the delivery system can reach the
target site readily via the blood circulation. To reach other tissues such
as hepatocytes and cancer cells in solid tumors, the carrier needs to
extravasate through the endothelial capillaries and diffuse to the target
site. The endothelial cells that outline the capillaries enforce an upper size
limit of about 100 nm if the delivery system is to reach the extravascular
tissues. Third, on accumulation at the target site, the active drug must
be released at a high level to mediate an effective therapeutic response
[11, 18, 19]. The particles in the intravenous solution are distributed to
various organs depending on the particle size. Particles larger than 7 µm
are trapped in the lungs and those smaller than 0.1 µm accumulate in the
bone marrow. Those with diameter between 0.1 and 7 µm are taken up by
the liver and the spleen.
340 CHAPTER EIGHT
Now it is possible to modify the kinetics of disposition and sometimes
the metabolic profile of a drug given by intravenous route. This can be
achieved by incorporating the drug into nanovesicles such as liposomes
[13].
Hydrogels, like other polymeric materials, have a unique combination
of characteristics that make them useful in drug delivery applications.
Hoare and Kohane [20] discussed the recent progress in overcoming
these challenges, particularly with regard to effectively delivering hydro-
gels inside the body without implantation, prolonging the release kinetics
of drugs from hydrogels, and expanding the nature of drugs that can be
delivered using hydrogel-based approaches.
Hydrogels are commonly used, also, in clinical practice and experi-
mental medicine for a wide range of applications, including tissue en-
gineering and regenerative medicine [21], diagnostics [22], cellular im-
mobilization [23], separation of biomolecules or cells [24], and barrier
materials to regulate biological adhesions [25].
The highly porous structure of hydrogels can easily be tuned by
controlling the density of crosslinks in the gel matrix, and the affinity of
the hydrogels for the aqueous environment in which they are swollen;
due to their hydrophilicity, hydrogels can imbibe large amounts of water
( >90 wt%).
Their increased porosity also permits loading of drugs into the gel
matrix and subsequent drug release at a rate dependent on the diffusion
coefficient of the small molecules or macromolecules through the gel
network. Indeed, the benefits of hydrogels for drug delivery may be
largely pharmacokinetic  specifically that a depot formulation is created
from which drugs slowly elute, maintaining a high local concentration of
drug in the surrounding tissues over an extended period, although they can
also be used for systemic delivery. Hydrogels are also generally highly
biocompatible, as reflected in their successful use in the peritoneum [26]
and other sites in vivo.
Both simple and sophisticated models have been developed to predict
the release of an active agent from a hydrogel device as a function of time.
These models are based on the rate-limiting step for controlled release and
are, therefore, categorized as follows [189, 190]:
1. diffusion controlled;
2. swelling controlled;
3. chemically controlled.
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 341
Diffusion controlled is the most widely applicable mechanism for
describing the drug release from hydrogels. Fick s law of diffusion with
either constant or variable diffusion coefficients is commonly used in
modeling diffusion-controlled release. Drug diffusivities are generally
determined empirically or estimated a priori using free volume, hydro-
dynamic, or obstruction-based theories [27].
Swelling-controlled release occurs when diffusion of drug is faster
than hydrogel swelling. The modeling of this mechanism usually involves
moving boundary conditions where molecules are released at the interface
of rubbery and glassy phases of swollen hydrogels. The release of many
small molecule drugs from hydroxypropyl methylcellulose (HPMC) hy-
drogel tablets is commonly modeled using this mechanism. For example,
R
Methocel© matrices  a combination of methylcellulose and HPMC 
from Dow Chemical Company are commercially available for preparing
swelling-controlled drug delivery formulations exhibiting a broad range
of delivery time scales [28, 29]. Chemically controlled release is used
to describe molecule release determined by reactions occurring within
a delivery matrix. The most common reactions that occur within hydro-
gel delivery systems are cleavage of polymer chains via hydrolytic or
enzymatic degradation or reversible or irreversible reactions occurring
between the polymer network and releasable drug. Under certain condi-
tions, the surface or bulk erosion of hydrogels will control the rate of drug
release, which is applied mainly for degradable hydrogels. Alternatively,
if drug-binding moieties are incorporated in the hydrogels, the binding
equilibrium may determine the drug release rate.
Chemically controlled release can be further categorized according
to the type of chemical reaction occurring during drug release. Gener-
ally, the liberation of encapsulated or tethered drugs can occur through
the degradation of pendant chains or during surface erosion or bulk-
degradation of the polymer backbone.
8.2. Diffusion-Controlled Delivery Systems
Understanding the mechanisms and identifying the key parameters that
govern drug release from hydrogels are the first step toward accurately
predicting the entire release profile. For porous hydrogels, when pore
sizes are much larger than the molecular dimensions of the drug, the
diffusion coefficient can be related to the porosity and the tortuosity of
the hydrogels [30].
342 CHAPTER EIGHT
Figure 8.2 Schematic depiction of drug release from a hydrogel-based reservoir delivery
system (adapted from [36]).
However, for nonporous hydrogels and for porous gels with pore sizes
comparable to the drug molecular size, drug diffusion coefficients are
decreased due to steric hindrance provided by polymer chains within the
crosslinked networks [27, 30, 31]. In these cases, the average free volume
per molecule available to the drug is decreased and the hydrodynamic
drag experienced by the drug is increased, leading to increased drug
diffusion path length compared to porous hydrogels with pore sizes much
larger than the encapsulated drug [32 34]. Due to the usually high perme-
abilities of hydrogel networks and the advantages of in situ fabrication,
most research efforts are focused on understanding diffusion-controlled
release of encapsulated drugs from three-dimensional hydrogel matrices.
Drug diffusion within highly swollen hydrogels is best described by
Fick s law of diffusion or Stefan Maxwell equations [35, 194]. Diffusion-
controlled hydrogel delivery systems can be either reservoir or matrix
systems [36, 191].
For a reservoir system (Figure 8.2), where the drug depot is surrounded
by a polymeric hydrogel membrane, Fick s first law of diffusion can be
used to describe drug release through the membrane:
dCA
JA =-D . (8.1)
dx
Here, JA is the flux of the drug, D is the drug diffusion coefficient, and
CA is the drug concentration. In many cases, the drug diffusion coefficient
is assumed constant to simplify the modeling. However, in the general
case it is a function of drug concentration, and a special correlation in-
corporating the concentration-dependent drug diffusivity must be utilized
to accurately predict drug flux. Another assumption of this expression is
that JA is the drug flux corresponding to the mass average velocity of the
system.
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 343
Figure 8.3 Schematic depiction of drug release from a hydrogel-based matrix delivery system
(adapted from [36, 191].
This is an extremely useful device as it facilitates time-independent or
zero-order release.
The major drawback of this type of drug delivery system is the po-
tential for catastrophic failure of the device. In the event that the outer
membrane ruptures, the entire content of the device will be delivered
nearly instantaneously. When preparing these devices, care must be taken
to ensure that the device does not contain pinholes or other defects that
may lead to rupture
For a matrix system (Figure 8.3), where the drug is uniformly dis-
persed throughout the matrix, unsteady-state drug diffusion in a one-
dimensional slap-shaped matrix can be described using Fick s second law
of diffusion:
dCA d2CA
= D . (8.2)
dx dx2
Here, the drug diffusion coefficient is again assumed to be a constant.
Release occurs due to diffusion of the drug throughout the macro-
molecular mesh or water-filled pores. In these systems, the release rate
"
is proportional to square root of time (i.e., Ä… time). Significant in that,
it is impossible to obtain time-independent or zero-order release in this
type of system with simple geometries.
Other assumptions include sink condition and a thin planar geometry
where the release through slab edges is neglected. When diffusivity is
concentration dependent, the following equation is used:

"CA " "CA
= D (CA) . (8.3)
"t "x "x
Many previous attempts to model diffusion-controlled drug delivery from
hydrogels rely largely on empirically determined diffusion coefficients.
344 CHAPTER EIGHT
Once the diffusion coefficient is determined, Eqs. (8.1) (8.3) can be
solved, together with proper initial and boundary conditions, to yield drug
concentration profiles that dictate the release kinetics. For example, an
exact analytical solution to Eq. (8.2) can be obtained using separation
of variable technique. The ratio of the amount of molecule released up
to any time t(Mt) to the final amount of molecule release (M") can be
expressed as

"

Mt 8 (2n + 1)2 Ä„2 D
= 1 - exp - t . (8.4)
M" L2
(2n + 1)2 Ä„2
n=0
This equation can be used to predict the diffusion of a broad range of
molecules including small-molecular-weight drugs and biomacromole-
cules like proteins and DNA once an appropriate diffusion coefficient
is obtained. Although this simple solution applies to many diffusion-
controlled drug release systems, model complexity will increase as other
mechanisms, polymer drug interactions, and when nonspherical drugs
are used [37]. Another empirical equation developed by Peppas et al.
assumes a time-dependent power law function [28, 35, 194]:
Mt
= ktn. (8.5)
M"
Here, k is a structural/geometric constant for a particular system and n
is designated as release exponent, representing the release mechanism.
Table 8.1 lists the n values for delivery matrices with different geometries
and release mechanisms [28], and Table 8.2 lists the diffusion exponent
values for slabs geometries and relese mechanisms. It is noteworthy that
in a purely swelling-controlled slab-based delivery system, the drug frac-
tional release (Mt/M") appears to be zero order as the release exponent
equals unity. The power law is easy to use and can be applied to most
diffusion-controlled release systems. However, it is too simple to offer
Table 8.1 Release exponent values (n) in the empirical power law model [28].
Diffusion-controlled Swelling-controlled
Matrix geometry delivery system (Case I) delivery system (Case II)
Slab n = 0.5 n = 1
Cylinder n = 0.45 n = 0.89
Sphere n = 0.43 n = 0.85
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 345
Table 8.2 Drug transport mechanisms and diffusional exponents for hydrogel
slabs [38].
Diffusional exponent (n) Type of transport Time dependence
0.5 Fickian diffusion t1/2
0.5 < n < 1 Anomalous transport tn-1
1 Case-II transport time independent
n>1 Super case-II transport tn-1
a robust prediction for complicated release phenomena. For example, in
diffusion-controlled systems where n = 0.5, the power law is only valid
for the first 60% of the release profile. These empirical models can only
predict the release profile after certain release experiments are conducted
and have limited capability to predict how the release profiles will change
as the chemical or network properties of the system are varied. Analytical
solutions to Fick s law are not available when more complex geometries
or nonconstant drug diffusivities are incorporated into the model descrip-
tions.
Except in extremely dilute systems, drug diffusion coefficients will be
a function of drug concentration.
Additionally for hydrogel systems, diffusivities of encapsulated mole-
cules will depend on the degree of swelling and crosslinking density of
the gels. Therefore, the diffusion coefficient used to describe drug release
will be sensitive to environmental changes or degradation of the polymer
network and may vary over the timescale of release [27, 35, 194]. Gen-
erally, theoretical models for predicting molecule diffusion coefficients
have the following general form:

Dg
= f rs,½2,s ,¾ . (8.6)
Do
Here, Dg and Do are the drug diffusion coefficients in the swollen hy-
drogel network and in pure solvent, respectively, rs is the size of the
solute molecules, ½2,s is the swollen-state polymer volume fraction, and
¾ is the network mesh size. This general expression takes into account
factors affecting drug release such as the structure of the gel, the polymer
composition, the water content, and the size of the molecules. For a
degradable hydrogel, Dg changes as the network degrades due to an
increase in gel mesh size and a decrease in polymer volume fraction over
time.
346 CHAPTER EIGHT
Several theories have been developed to correlate the relationship
between drug diffusivity in the gels and in the solution [27]. For example,
Eq. (8.7), by applying a free-volume approach proposed by Lustig and
Peppas, can be used to describe the relationship between drug diffusivity
and network structure [37]:

Dg rs ½2,s
= 1 - exp -Y . (8.7)
Do ¾ 1 - ½2,s
Here, Y is defined as the ratio of the critical volume required for a transla-
tional movement of the encapsulated drug molecule and the average free-
volume per molecule of solvent. A good approximation for Y is unity.
For highly swollen (Q > 10) hydrogels with degradable crosslinks, the
diffusivity correlation shown in Eq. (8.7) can be simplified during the
initial stages of degradation to [39, 40]:
Dg rs
E
1 - = <" e-7/5 jk t. (8.8)
Do ¾

Here, the lumped parameter jkE is the pseudo-first-order reaction rate
constant for the hydrolysis of a labile crosslink, and t is release time. From
this expression, one can realize that mesh size is time-dependent due to
network degradation. It is clear that Dg increases as degradation proceeds
and approaches Do. The rate of increase in drug diffusivity depends on
network structure and bond cleavage kinetics [39, 187, 197].
The drug release behavior of a biodegradable stimuli-sensitive hydro-
gel based on alginic acid (Alg) and N-isopropylacryl amide (NIPAAm)
was studied in case of ketoprofen and vanillin loading [41, 42].
The release profile of ketoprofen from NIPAAm/Alg hydrogel matrix
(Figure 8.4) is different depending on solvent content in the gel  the
higher the solvent content, the higher is the quantity of the released drug
(which is <" 100% from loaded quantity) for unswollen matrix that means
physically mixing of matrix with drug, and it decreases at about 60%
from loaded quantity when the matrix was swollen at maximum SR =
3300%. The matrix swollen in drug solution up to an SR = 1750% shows
an intermediary behavior between physically loading and the case when
maximum swollen was used.
The kinetic parameters obtained are presented in Table 8.3.
The drug release profiles depend on solvent quantity used for drug
loading so that in dried state, the release rate constant value is four times
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 347
120
LIVE GRAPH
Click here to view
100
80
60
40
20
NIPAM/ALG 75/25 (a)
0
NIPAM/ALG 75/25 (b)
NIPAM/ALG 75/25 (c)
-20
0 50 100 150 200 250 300
Time (min)
Figure 8.4 Drug release profile of ketoprofen at 25ć%C from 75%NIPAAm/25% Alg hydrogel
with different swelling ratios in ethanol (a) unswollen; (b) SR = 1750%; (c) SR = 3500%.
higher than the values obtained for the same constant in case of 3500%
and 1750% swelling ratio, respectively. The releasing mechanism of keto-
profen occurs according to case II of transport; the dominant mechanism
for drug transport is due to polymer relaxation as the gel swells in ethanol.
In case of vanillin loaded in N-isopropylacryl amide (NIPAAm) and
sodium alginate based hydrogels using twice-distilled water as release
medium, the kinetic parameters are presented in Table 8.4.
In that case, the alginate content in NIPAAm/Alg hydrogels and re-
lease rate constant values are connected, thus the increase of alginate
content leading to a decrease of release rate constant values and diffusion
exponent (nr ). The values of the diffusion exponent nr indicating an
anomalous transport, which appear by coupling Fickian diffusion with
the relaxation of the hydrogel network.
An interpolymeric complex based on a natural polymer like alginic
acid and PEG with composition 16%AgA/84%PEG was tested for con-
trolled delivery of procaine [43].
Table 8.3 The kinetic parameters of the ketoprofen release from
75/25 NIPAAm/Alg hydrogels.
Hydrogel Qeq(%) nr kr min-n
75/25 NIPAAm/Alg 0 1 2.2 × 10-3 min-1
1750 1 3.6 × 10-4 min-1
3500 0.98 9.8 × 10-4 min-1
Drug release (%)
348 CHAPTER EIGHT
Table 8.4 The kinetic parameters of the vanillin release
from NIPAAm/Alg hydrogels.
Hydrogels nr kr min-n
95/5 NIPAAm/Alg 0.97 1.1 × 10-3 min-0.97
85/15 NIPAAm/Alg 0.70 3.2 × 10-3 min-0.70
75/25 NIPAAm/Alg 0.79 9.4 × 10-4 min-0.79
The obtained release profiles (Figure 8.5) show that the optimal pH
range for the release of procaine hydrochloride is 1.14 2.00, similar
to the pH of the physiological medium from stomach; therefore, the
interpolymeric complex based on alginic acid and PEG/procaine can be
a promising material for the release of active substances in stomach (at
acidic pHs).
The cellulose (C)/chondroitin sulfate (GAG) hydrogels with different
compositions, loaded with paracetamol and theophylline, were also tested
for oral drug delivery [44].
8.3. Swelling-Controlled Delivery Systems
Another mechanism for drug delivery is swelling-controlled delivery.
Hydrogels may undergo a swelling-driven phase transition from a glassy
state (Figure 8.6), where entrapped molecules remain immobile, to a
rubbery state where molecules rapidly diffuse. In these systems, the rate
35
LIVE GRAPH
Click here to view
30
25
20
15
10
pH=2.16
pH=3.09
5
pH=1.14
0 50 100 150 200 250 300 350
Time (min)
Figure 8.5 Release profiles for the procaine hydrochloride from 16% AgA/84% PEG inter-
polymeric complex at different pH values, at 25ć%C.
Drug release (%)
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 349
Figure 8.6 Schematic of HPMC hydrogel tablet in the glassy (left) and rubbery (right) state
(adapted from [47]).
of molecule release depends on the rate of gel swelling. One example of
swelling-controlled drug delivery systems is HPMC. Drug-loaded HPMC
tablets are three-dimensional, hydrophilic matrices that are usually stored
in a dry, glassy state. After oral administration, HPMC polymer absorbs
liquid and a rapid glassy-to-rubbery phase transition occurs once the glass
transition temperature (Tg) is reached, causing the systematic release of
loaded drugs. The drug release rates are modulated by the rate of water
transport and the thickness of the gel layer.
Drug diffusion time and polymer chain relaxation time are two
key parameters determining drug delivery from polymeric matrices. In
diffusion-controlled delivery systems, the time scale of drug diffusion,
t, (where t = ´(t)2/D, where ´(t) is the time-dependent thickness of
the swollen phase) is the rate-limiting step, while in swelling-controlled
delivery systems the time scale for polymer relaxation () is the rate-
limiting step. The Deborah number (De) is used to compare these two
time scales [45 47]:
 D
De = = . (8.9)
t
´ (t)2
In diffusion-controlled delivery systems (De << 1), Fickian diffusion
dominates the molecule release process and diffusion equations described
earlier can be used to predict molecule release. In swelling-controlled
delivery systems (De >> 1), the rate of molecule release depends on
the swelling rate of polymer networks. The empirical power law (Eq.
(8.4)) used to describe diffusion-controlled drug release from hydrogel
matrices can also be used comprehensively in swelling-controlled deliv-
ery systems. A modification of Eq. (8.4) takes into account both the drug
diffusion and polymer relaxation [48]:
Mt
= k1tm + k2t2m, (8.10)
M"
350 CHAPTER EIGHT
where k1, k2, and m are constants. The two terms on the right side
represent the diffusion and polymer relaxation contribution to the release
profile, respectively.
The above empirical relationship does not account for  moving-
boundary conditions in which the gel expands heterogeneously as wa-
ter penetrates and swells the gels. For this more rigorous description,
Korsmeyer and Peppas introduced a dimensionless swelling interface
number, Sw, to correlate the moving boundary phenomena to hydrogel
swelling [46, 47, 49, 50]:
v´(t)
Sw = . (8.11)
D
Here, v is the velocity of the hydrogel swelling front and D the drug
diffusion coefficient in the swollen phase. For a slab system when Sw <<
1, drug diffusion is much faster than the movement of glassy rubbery
interface, and thus a zero-order release profile is expected. A more rigor-
ous method for predicting molecule release [37, 51 54], from swelling-
controlled systems is provided by a sequential layer model developed by
Siepmann and Peppas [55 60]. In this model, drug diffusion, polymer
relaxation, and dissolution are all taken into account. Drug transport in
both radial and axial directions is accounted for using Fick s second
law of diffusion in a cylindrical geometry with concentration-dependent
diffusion coefficients as shown in Eq. (8.12) [58, 59]:

"Ck " "Ck Dk"Ck " "Ck
= Dk + + Dk . (8.12)
"t "r "r r"r "z "z
Here, Ck and Dk are the concentration and diffusivity of the diffusible
species (1: water; 2: drug), respectively. Concentration-dependent diffu-
sivities derived by a  Fujita-like free-volume model can be expressed as
[61]

c1
D1 = D1eq exp -²1(1 - , (8.13)
c1eq

c1
D2 = D2eq exp -²2(1 - , (8.14)
c1eq
where ²1 and ²2 are dimensionless constants and  eq represents the
equilibrium drug concentration at the water matrix interface where poly-
mer disentanglement occurs.
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 351
Due to the concentration-dependent diffusion coefficients, Eqs. (8.12)
(8.14) can only be solved numerically. Siepmann et al. demonstrated that
these numerical solutions agreed well with experimental results [55, 56].
This model is, therefore, useful in predicting the shape and dimensions of
HPMC tablets needed to acquire desired release profiles [57].
Table 8.5 presents some polymeric systems with controlled release of
bioactive substances by the swelling mechanism.
8.4. Chemically Controlled Delivery Systems
In addition to diffusion- and swelling-controlled delivery systems, a third
type of molecule release mechanism is chemically controlled delivery.
The latter can be further classified as (1) purely kinetic-controlled re-
lease where polymer degradation (bond-cleavage) is the rate-determining
step and diffusion term is assumed to be negligible; and (2) reaction-
diffusion-controlled release in which both reaction (e.g., polymer degra-
dation, protein drug interaction) and diffusion terms must be included
in the model to accurately predict drug release. The reaction-diffusion-
controlled release is particularly intriguing as more synthetic hydrogel
systems designed with drug-binding capacity are utilized in drug delivery
[73 75] and tissue engineering [76].
Drug release from bioerodible polymers can occur by any one of three
basic mechanisms shown schematically in Figure 8.7. In mechanism A,
the active agent is covalently attached to the backbone of a biodegradable
polymer and it is released as its attachment to the polymer backbone
cleaves by hydrolysis of bond A. Because it is not desirable to release
the drug with polymer fragments still attached, the reactivity of bond A
should be significantly higher than the reactivity of bond B. In mechanism
B, the active agent is contained within a core and is surrounded by a
bioerodible rate-controlling membrane. Release of the active agent is then
controlled by its diffusion across the membrane. In mechanism C, the
active principle is dispersed in a bioerodible polymer and its release is
controlled by diffusion, by a combination of diffusion and erosion or by
pure erosion [185].
8.4.1. Kinetic-Controlled Release  Pendant Chain Systems
There are two types of kinetic-controlled-release systems: pendant chain
(prodrugs) and surface-eroding systems. In pendant chain systems, drugs
are covalently linked to the hydrogel network via cleavable spacers and
Table 8.5 Example of polymeric systems with controlled release of bioactive substances by swelling mechanism.
Polymeric systems Obtaining procedure, characteristics, observations Bioactive substance Application References
Dextran Microspheres based on dextran hydrogels with ammonium Bile salts Intragastric [62]
quaternary group administration
Dextran and Degree of substitution is 4. (DS  number of methacrylates per 100 Immunoglobulin G Intragastric [63]
methacrylate glycopyranose residues) administration
Hydroxypropyl HPC gels with rheologically different behaviors Theophylline Drug with small [64, 65]
cellulose (HPC) molecular weight
Crosslinked HPC Crosslinked particle by HPC gels Furazolidone Intragastric [66]
administration
Carboxymethylcellulose Microspheres of polysaccharides for the genetic information DNA Genetic therapy [67, 68]
delivery
Hydrogel based on Xyloglucan polysaccharide derived from tamarind seeds with the Drug with low- Rectal and [69, 70, 186]
xyloglucan thermoreversible properties molecular-weight, intragastric
Indomethacin, administration
Diltiazem
Xanthan Xanthan and poly(vinyl alcohol) based matrices Chloramphenicol Ocular [71]
administration
Chitosan and Preparation of semi-interpenetrating hydrogel based on Chlorhedixiniacetas Intragastric [72]
polyether crosslinking chitosan with glutaraldehyde interpenetrating the and cimetidine administration
polyether network
Chitosan and gelatin Crosslinked chitosan/gelatin with a glutaraldehyde hybrid polymer Levamisole, Intragastric [69]
network cimetidine, administration
chloramphenicol
352
CHAPTER EIGHT
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 353
Figure 8.7 Schematic representation of drug release mechanisms (adapted from [185]).
drug release is controlled by the rate of spacer-bond cleavage. In surface-
eroding systems, drug release is mediated by the rate of surface erosion.
Drug diffusion does not determine the rate of drug release in either
system.
Prodrugs or polymer drug conjugates are designed to enhance the
therapeutic efficacy of the drug. This strategy is especially useful when
growth factors are to be delivered as most of them are susceptible to
rapid proteolytic degradation [77, 78]. Generally, the release of covalently
tethered prodrugs is determined by the degradation rate of the polymer
drug linkage [79 81, 192]. Most of these linkages have been designed
to be hydrolytically degradable allowing degradation and release rates
to be characterized by fairly simple first-order kinetic relationships [82].
However, in particular applications, for example where a more targeted
delivery profile is desired, it is advantageous to design enzymatically
cleavable spacer bonds [83].
In cases where the prodrugs are tethered to degradable hydrogel ma-
trices, the kinetics of gel degradation may also play a significant role in
determining overall drug release profiles [79 81, 83, 84, 192]. Ehrbar
354 CHAPTER EIGHT
et al. recently developed fibrin matrices tethered with pendant vascular
endothelial growth factor (VEGF) variants linked by plasmin-sensitive
peptidyl substrates [83]. These covalently bound VEGF variants can only
be liberated from the insoluble matrix through plasmin-mediated cleavage
of the engineered peptide substrates. First-order cleavage kinetics has
been used to model the time-dependent VEGF release. Accurate predic-
tion of VEGF release profiles also required a description of VEGF-release
via matrix-mediated degradation.
Two adjustable parameters were, therefore, used to accurately predict
complete VEGF release profiles. The first parameter was the pseudo first-
order degradation rate constant, k. The degradation of bonds within the
fibrin network and the plasmin-sensitive substrates used to link VEGF
to the fibrin were assumed to follow the same first-order kinetics. The
second adjustable parameter, N, represented the number of fibrin repeat
units between two crosslinks and was an indication of fibrin network
structure.
DuBose et al. covalently incorporated fluorescently labeled probe
molecules within the three-dimensional network structure of PEG-based
hydrogels formed via step-growth polymerizations [84]. As shown in
Figure 8.8, they demonstrated that hydrolytic degradation of covalent
bonds within the step-crosslinked modified-PEG network as well as the
cleavage of immobilized probe molecules resulted in a biphasic release
profile, in which a constant molecular release profile is obtained prior to
gel dissolution and an almost instantaneous burst release following gel
dissolution. The authors demonstrated that the slope of the approximate
LIVE GRAPH
LIVE GRAPH
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Figure 8.8 Fractional probe release from degradable PEG-acrylate/dithiol gels formed via
step growth polymerization (A) gels fabricated from 30 wt% eight-armed PEG-acrylate/DTT
precursor solutions and degraded at varying temperatures: 37ć%C( ) and 46ć%C( ); (B) In case of
gels fabricated with four-arm/10-kDa the release profile is constant until the 6 days of experiment
prior to gel dissolution, a burst release being observed after that; for gels with eight-arm/20-kDa
( ) the burst release is observed after 11 days (adapted and redrawn from [84]).
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 355
zero-order delivery regime as well as the extent of the latent burst could be
controlled by degradation kinetics (varying temperature, pH, or chemistry
of the degradable bond) and crosslinker functionality (tetra-functional
versus octa-functional PEG).
8.4.2. Kinetic-Controlled Release  Surface-Eroding Systems
Other kinetic-controlled systems are found when drug release is mediated
by surface erosion of the polymer matrix. For hydrophobic polymer
networks, surface erosion occurs when the rate of water transport into
the polymer is much slower than the rate of bond hydrolysis. Due to the
inherently high water content of hydrogels, surface erosion only occurs
in enzymatic degrading systems where the transport of enzyme into the
gel is slower than the rate of enzymatic degradation.
While no hydrogels have been specifically designed to degrade
in this fashion, surface erosion of enzymatically degradable PEG-
polycaprolactone (PCL-b-PEG-b-PCL) block copolymer hydrogels,
when exposed to relatively high concentrations of lipase, has been ob-
served in vitro by Rice et al. [85].
Most of the models focusing on surface-eroding polymers are based on
hydrolytic-degrading polymers. These relationships, however, can also be
applied to enzymatically degradable, surface-eroding hydrogel systems.
Surface-eroding matrices are advantageous for drug delivery applications
as the structural integrity of the carrier device is maintained during deliv-
ery and zero -order release of the encapsulated molecules can be readily
obtained by appropriate choice of device geometry [86].
Hopfenberg initially developed a drug delivery model where the re-
lease only depends on matrix erosion rates. Equation (8.15) describes
the release from surface-eroding devices with an initial dimension a0
(radius for a spherical or cylindrical geometry and half-thickness for slab
geometry) and drug concentration C0 [87]:

Mt kat
= 1 - 1 - . (8.15)
M" c0a0
In this equation, n is a geometrical factor, a0 is the initial radius of the
tablet, and a number of 1, 2, or 3 is used for a slab, cylinder, or sphere,
respectively. It is clear that when a slab-shaped device is used (n = 1),
drug release appears to be a zero-order profile. Following Hopfenberg s
work, Katzhendler, Hoffman, and coworkers further developed a general
mathematical model for heterogeneous eroding networks accounting for
356 CHAPTER EIGHT
different radial and vertical erosion rate constants for a flat tablet (ka and
kb for radial and vertical degradation constant, respectively) (Eq. 8.16)
[88]:
2
Mt kat 2kbt
= 1 - 1 - 1 - . (8.16)
Mx c0a0 c0b0
Here b0 is the thickness of the tablet. By changing the radius-to-thickness
ratio of the device, one can easily obtain various drug release rates. It
is noteworthy that in these models, swelling of the matrices is either
not considered or is assumed to occur prior to erosion and drug release.
Stemming from these initial efforts, several additional models have been
developed to predict molecule release via surface erosion [7, 56, 89, 90].
8.4.3. Reaction-Diffusion-Controlled Release  Bulk
Degrading Systems
Many of the approaches for modeling drug release from hydrogel net-
works assume only one mechanism  either diffusion, swelling, or degra-
dation  which dominates the release process. Although not realistic for
many cases, this is one way to simplify the model and, in many cases,
obtain a reasonable fit to experimental results. As more complicated
drug delivery systems are designed to fulfill the ever-increasing needs for
advanced drug delivery and tissue engineering, the assumption of a single
dominant release mechanism will no longer be suitable. Overlooking the
coupled effects of diffusion and matrix degradation within degradable
hydrogel matrices will result in significant deviations when comparing
modeling and experimental results.
The coupling of reaction and diffusion phenomena is already notable
in bulk degrading networks where drug release profiles are governed
by both network degradation and molecule diffusion. Macroscopically,
this degradation diffusion coupling phenomena can be observed through
the swelling characteristics and mechanical properties. The degradation
behavior of chain-polymerized hydrogels with hydrolytically or enzy-
matically labile bonds can be tailored through a variety of parameters.
Sawhney incorporated degradable PLA moieties within hydrophilic PEG
macromers [91], the resulting PLA PEG PLA block copolymers being
polymerized to form hydrolytically degradable hydrogels. Metters et
al. further described the release of encapsulated macromolecules from
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 357
LIVE GRAPH
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LIVE GRAPH
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Figure 8.9 (A) Volumetric swelling ratio and (B) fractional release of bovine serum albumin
(BSA) as a function of degradation time from a PLA-b-PEGb-PLA hydrogel polymerized with
)
25 wt% ( and 35 wt% ( ) macromer. Lines represent exponential fits to the swelling data (A)
and solute release predictions based on scaling equations (B) (adapted from [39]).
bulk-degrading, covalently crosslinked PLA PEG PLA hydrogels con-
sidering network structure as well as degradation kinetics [92, 93]. Gen-
erally, molecule diffusivity decreases as crosslinking density increases
(Mc decreases  the average molecular weight of an crosslinked section
of polymer chain, see Chapter 1), as the size of the solute molecules
(rs) increases, and as the swollen-state polymer volume fraction, (½2,s),
increases [30, 94, 95]. In PLA PEG PLA hydrogel systems, molecule
diffusivity can be correlated to gel degradation kinetics and used to pre-
dict drug release corresponding to gel degradation, as shown in Figure 8.9
[39, 40]. The diffusion coefficient of a solute from the degrading network
with time-dependent mesh size can then be obtained by using Eq. (8.8).
The degradation behaviors described are only valid for hydrogels
made from di-vinyl macromers. For hydrogels formed via free radi-
cals chain-polymerization of multifunctional macromers such as acry-
lated poly(vinyl alcohol) (PVA), Martens et al. developed a general-
ized statistical-co-kinetic model to predict their degradation behaviors
[96 98]. In this model, a statistical approach was used to predict the
different configurations of the crosslinking molecules and kinetic chains.
The model was verified by experimental observation of gel swelling,
mass loss, and compressive modulus [98]. Combining the degradation
kinetics provided by this model and the diffusivity estimated by Eq. (8.8),
the release of a model protein  bovine serum albumin (BSA)  was
verified [40].
358 CHAPTER EIGHT
For hydrogels formed via step-growth polymerization, Metters and
Hubbell have shown that the degradation rates of networks depend on
molecular weight, hydrophilicity, and degree of functionality of the start-
ing monomers [99]. In addition to the statistical modeling approaches
assuming homogeneous changes in gel properties, Monte Carlo simu-
lations have also been used to predict protein release from degradable
polymer networks at the microscopic level. Gopferich and Langer [100
103] developed Monte Carlo simulations to predict polymer erosion and
monomer release. Although this work was not for hydrogel systems, it al-
lowed the calculation of porosity distributions within the polymer and was
useful in predicting drug and degraded monomer release. Monte Carlo
simulation is good for describing the network morphological changes;
however it does not provide any information regarding molecule release.
Diffusion equations (Fick s law) must be incorporated in order to link
the network degradation to molecular diffusion [103]. The following
modified diffusion equation can be used to describe one-dimensional
diffusion in porous polymers:
" " "c(x, t)
C(x, t)µ(x, t) = Deff (C)µ(x, t) . (8.17)
"t "x "x
Here, C(x, t) is the concentration of diffusing monomer, µ(x, t) is
the porosity along the diffusion path, and Deff(C) is the effective
concentration-dependent diffusion coefficient. Vlugt-Wensink et al. de-
veloped kinetic Monte Carlo simulations to predict protein release from
crosslinked dextran microspheres [104].
The macroscopic models used to correlate solute release (diffusion)
with gel degradation (reaction) provide a powerful tool for predicting
protein release with changing network structure. Macroscopic observa-
tions in gel swelling and mass erosion are not sufficient to obtain precise
predictions due to the averaging of microscopic events. On the other hand,
models describing network changes at a microscopic level may provide
more accurate release predictions. Gel swelling, a very important charac-
teristic of hydrogel drug carriers, must be included during the simulation
since solute diffusivity is tightly coupled to water content.
In Table 8.6, some polymeric hydrogel systems are presented, which
release bioactive substances controlled by degradation/solubilization
mechanism.
Table 8.6 Biodegradable systems releasing bioactive substances by degradation/solubilization mechanisms.
Polymeric systems Preparation, characteristics, observation Bioactive substance Applicability fields References
Multiporous beads of Chitosan is dissolved in acetic acid or formic acid solution. Using a Protease nefedipine, Cell culture carrier [64, 105 107]
chitosan compressed air nozzle, this solution is blown into NaOH, ampicilin Oral administration
NaOH methanol, or ethanediamine solution to form coacervate
drops
These coacervate beads can be hardened by crosslinking with Rotundine Oral administration [64, 108]
glutaraldehyde or epoxy chloroprene to produce microcapsules
Chitosan- The preparation techniques based on an ionic gelation process is BSA Continuous release [109 112]
poly(ethylene oxide) extremely mild and involves the mixture of two aqueous phases at of the entrapped
nanoparticles room temperature protein
Chitosan/calcium The encapsulation process of chitosan and calcium alginate Hemoglobin, BSA Intragastric [113, 114, 187,
alginate beads administration 188]
Albumin Crosslinking of albumin microspheres by suspension in the Chlothiazide Site-directed [115, 116]
microspheres absence of any surfactant using paraffin oil as the dispersion delivery of
medium and formaldehyde as the crosslinking agent antitumor drugs
Gellan-gum beads Microcapsules containing oil and other core materials have been Encapsulation of Controlled release of [64, 117]
formed by complex coacervation of gellan gum gelation mixture fragile drugs fragile drugs
Microspheres based Collagen and gelatin genetic recombined Antitumoral drug Intragastric [118]
on collagen and administration
gelatin
Crosslinked chitosan Crosslinked chitosan microspheres coated with polysaccharides or Cimetidine Oral administration [64, 119, 120]
microspheres lipid for intelligent drug delivery systems
HPC beads Developed and evaluated adhesive patches for buccal Lidocaine Buccal releasing [121, 122]
administration, consisting of two-ply laminates of an impermeable
backing layer and a hydrocolloid polymer layer containing the drug
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS
359
360 CHAPTER EIGHT
8.5. Dynamic Hydrogel Delivery Systems
8.5.1. Composite Hydrogel Delivery Systems
Modeling drug release from composite hydrogel systems has proven to
be challenging due to the fact that their material and molecule transport
properties change dramatically with spatial location within the device.
Two primary types of composite hydrogel delivery systems  multilayer
and multiphase systems  have been investigated. These composite sys-
tems have great potential in delivering multiple protein therapeutics for
tissue engineering applications where temporal and spatial control over
drug delivery is desirable. The simultaneous delivery of multiple proteins
is known to occur in vivo during angiogenesis, bone remodeling, and
nerve regeneration. For example, several angiogenic proteins including
VEGF, basic fibroblast growth factor (bFGF), transforming growth factor
beta (TGF-²), platelet-derived growth factor (PDGF), and matrix metal-
loproteinases (MMPs) are involved in the angiogenesis process. Peattie
et al. utilized crosslinked hyaluronan (HA) hydrogels to simultaneously
deliver VEGF and keratinocyte growth factor (KGF) to enhance angio-
genesis [123]. Simmons et al. used alginate hydrogels to deliver bone
morphogenetic protein-2 (BMP2) and TGF-²3, and showed enhanced
bone formation compared to delivery of either single protein [124].
Although in vivo tissue growth was improved in animal models using
these dual-protein delivery systems, it is not clear whether tissue growth
would be further enhanced if the proteins were delivered at optimized
rates since no independent control over the release profiles has been
shown in these studies.
8.5.2. Multilayer Hydrogel Delivery Systems
In multilayer systems, a basal polymer layer is fabricated, followed by
lamination of subsequent layers. Different proteins can be encapsulated
into each layer during fabrication, and tunable multiple protein release or
unique single-protein release profiles are made possible by independently
adjusting the crosslinking density of each layer. Many models have been
developed for predicting drug release from multilayer hydrogel compos-
ites. For example, Streubel et al. developed a multilayer system to achieve
bimodal drug release [125]. Fick s second law of diffusion was used to
predict drug release profiles. They derived diffusion equations accounting
for constant or nonconstant diffusivities, as well as stationary or mov-
ing boundary conditions. Grassi et al. fit their experimental data into a
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 361
semiempirical model accounting for the resistance the drug experienced
when diffusing through the multilayer system [126]. They started the
modeling with an equation governing the dissolution of solid drug and
accounted for the gel layer resistance (R) and drug dissolution resistance
(1/K), and obtained the following equation:
dC Õd A Cs - C
= , (8.18)
dt V (1/K ) + R
where C is the drug concentration, t is the dissolution time, CS is the
solubility of the drug in the dissolution medium, Õd is the drug volume
fraction, A is the surface area at the solid liquid interface, and V is
the volume of the medium. The release of some small-molecular-weight
drugs from partially coated matrices containing different drug to polymer
fractions can be fit into the analytical solution of this model.
Sohier and colleagues developed a porous scaffold containing three hy-
drogel layers with different porosities to simultaneously deliver lysozyme
and myoglobin [127]. The governing equations used to model this system
were based on Fick s second law with a time-dependent diffusion coef-
ficient related to the rate of polymer degradation. Although this model
successfully predicted the release of lysozyme from a multilayer poly-
mer construct, it did not provide an accurate description of dual-protein
delivery.
In addition to multiple-protein delivery, multilayer matrices can also be
used to decrease the problematic burst release  a common challenge that
drug delivery encounters. For example, Lu and Anseth [128] developed
a multilaminated hydrogel system prepared by photopolymerization. A
desirable, zero-order release profile was obtained through nonuniform
initial drug loading in multilaminated hydrogels, and the results were
verified by a diffusion model [128, 129, 187, 188]. Their model was
based on the well-known diffusion model first developed by Crank [130].
Assuming a constant diffusion coefficient and one-dimensional release
under sink conditions, the fractional passive release of drug (Mt/M")
from these composite hydrogels can be analytically derived from Fick s
second law of diffusion and expressed as the following equation:

" (-1)n+1 2 Dt L
e-n 0 f (x) sin (nx) dx
n=0
Mt n
= 1 - , (8.19)
" 1 Dt L
M"
n
e-2 f (x) sin (nx) dx
n=0
n 0
where n = ((n + 0.5) Ä„) L.
362 CHAPTER EIGHT
In this expression, f(x) is the initial concentration profile, D is the mole-
cule diffusion coefficient, n is geometrical factor, and L is the thickness
of the gel.
8.5.3. Multiphase Hydrogel Delivery Systems
Another strategy for multiple-protein delivery is multiphase systems. In
this approach, prefabricated microspheres containing one or more pro-
teins are uniformly embedded within a hydrogel containing a second
protein [131 133]. The release of the microsphere-encapsulated protein
is delayed due to the combined diffusional resistances of the microsphere
polymer and surrounding gel. Richardson and colleagues prepared a
composite polymeric scaffold containing PLGA microspheres embedded
in porous PLGA matrices with different intrinsic viscosities to deliver
VEGF and PDGF simultaneously. The in vitro and in vivo results us-
ing this approach have shown promising results in an animal model to
enhance the maturation of vasculatures [134]. Although this multiphase
formulation is not considered to be a hydrogel system, it was the first
heterogeneous polymeric system for delivering two proteins with distinct
release profiles. Holland et al. also fabricated degradable oligo(PEG
fumarate) hydrogels containing gelatin microspheres to independently
control the delivery of insulin-like growth factor-1 (IGF-1) and TGF-²1.
Release profiles can be adjusted by varying the protein loading in each
polymer phase [131].
8.5.4. Micro/Nanoscaled Hydrogel Delivery Systems
Over the past few decades, polymeric microspheres and, more recently,
nanoparticles have been widely used for sustained or targeted drug deliv-
ery [135], as well as cell encapsulation [136 138]. Numerous studies have
been conducted using PLGA as a matrix for encapsulating proteins, pep-
tides, DNA, and small-molecular-weight drugs. However, the hydropho-
bicity, acidic degradation products, and harsh fabrication/encapsulation
processes of PLGA micro/nanoparticles make them unfavorable as carri-
ers for biomacromolecules such as protein and DNA [141]. Alternatively,
micro/nanoparticles made from hydrophilic hydrogels are more suitable
for encapsulating these fragile biomacromolecules. These miniaturized
drug-containing vehicles can be fabricated in vitro and then administered
via oral [142, 141] or nasal route [142, 143], or injected into the patients
in a minimally invasive manner to increase patient compliance.
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 363
Protein-containing microparticles can also be fabricated and loaded
into a bulk gel containing a second protein for dual-protein delivery. Two
types of mathematical approaches have been used to predict molecule re-
lease from hydrogel microspheres: macroscopic diffusion models and mi-
croscopic Monte Carlo simulations. For macroscopic modeling, the most
applicable models are still based on Fick s second law of diffusion. Par-
ticle size and geometry are the most important parameters in this type of
modeling, as along with surface area, since this appears to correlate with
the observed burst effects. As with other diffusion-controlled delivery
systems, simple empirical relationships have been used to estimate mole-
cule diffusivity [144].
Burst effect represents the stage in which drug will saturate the matrix,
and an initially higher rate of drug released in solution is observed (Figure
8.10).
Membrane reservoir systems have a period of constant release, steady-
state permeation, preceded by a period of increasing (tB) (burst) or de-
creasing (tL) (lag time) flux. This period may affect the time of appear-
ance of a drug in plasma after the first dose but may become insignificant
in case of multiple dosing.
LIVE GRAPH
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Figure 8.10 Release amount Qt versus time t plots. Illustration of time lag (tL ) and burst time
effect (tB ) in a reservoir-type diffusion controlled drug delivery systems (adapted from [11]).
364 CHAPTER EIGHT
Another technique to model molecule release from hydrogel mi-
crospheres is Monte Carlo simulation. This method has proven it valuable
for describing the transport behavior of molecules within degradable mi-
crosphere systems and has been widely applied to hydrophobic polymer
networks such as PLGA [28, 60, 145]. Vlugt-Wensink et al. utilized
Monte Carlo simulations to predict protein release from degradable dex-
tran microspheres [104]. Unfortunately, the accuracy of the model is
highly protein-specific. For example, for larger proteins such as IgG,
model predictions only qualitatively agreed with experiments in most
cases. This may be due to the fact that swelling of the dextran gels
was not accounted for in the Monte Carlo description of the degrading
hydrogel network. One of the unique challenges facing microscaled ma-
trix delivery systems is burst release due to the high surface-to-volume
ratio of these particulate systems [146, 147]. Burst release may cause a
 dose-dumping effect and is potentially harmful to patients in clinical
applications. Several possible causes of burst release have been identified
including material/drug interactions, fabrication conditions, and sample
geometry and/or morphology [146]. Although not completely under-
stood, burst release has been taken into consideration during the design of
delivery matrices as well as in modeling approaches [128, 129, 148, 149,
187, 188]. Several methodologies have been developed in an attempt to
decrease the degree of burst release. These include increasing crosslink-
ing density of the matrix surface [150, 151], coating additional drug-free
layers [126, 149, 152], embedding the drug-containing particles within a
bulk polymeric matrix [131 133, 153], and loading drug unevenly with
higher concentrations toward the center of the matrix [154, 155].
The prediction of burst release is problematic as the exact mechanism
has not been elucidated. Typically, diffusion-controlled release can be
divided into two phases: a rapid burst phase and a prolonged diffusion-
controlled phase. The latter can be modeled by conventional diffusion
theories, while the prediction of initial burst release is not readily attain-
able. Models in this area are, therefore, very limited.
Several attempts have been made to predict burst release in polymeric
delivery matrices. For example, the simplest model employed to describe
the impact of burst release on drug delivery profiles is to add an extra
parameter, namely Ä…, into the well-known fractional release (Eq. (8.5)) to
lead to Eq. (8.20) [146]:
Mt
= ktn + Ä…. (8.20)
M"
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 365
8.6. In situ Forming Hydrogels
Recent advances in polymer chemistry and hydrogel engineering have
promoted the development of in situ forming hydrogels for drug delivery
applications.
Through intelligent design of monomers/macromers with desired func-
tionalities, hydrogel precursor solutions can be injected and subsequently
polymerized in situ. This in situ sol gel transition enables the surgery or
implantation procedure to be performed in a minimally invasive manner.
Several physical or chemical crosslinking mechanisms have been used
for in situ network formation. Physically, in situ forming gels are formed
by one of the following mechanisms: hydrogen bonding, hydrophobic
hydrophobic interactions, or electrostatic interactions. Sodium alginate
hydrogels, for example, can be physically crosslinked through the ad-
dition of calcium ions [135]. The common disadvantage of physical
crosslinking, however, is that the gels thus formed are unstable and
may disintegrate rapidly and unpredictably. For long-term drug delivery
applications, covalent crosslinking methods performed under physiolog-
ical conditions, such as photopolymerization of multivinyl macromers,
are more favorable compared to physical crosslinking methods as they
produce relatively stable hydrogel networks with predictable degradation
behaviors.
The photocuring process, for example, is fast, usually taking only
seconds to minutes to complete, and can be conducted at room temper-
ature without organic solvents [1]. Photopolymerization of degradable
hydrogels has been applied in protein [156, 157, 189, 190] and gene
delivery [158 160] and permits in situ encapsulation of these species
during network fabrication.
These advantages overcome the complexities and limitations associ-
ated with postloading techniques and provide a convenient and efficient
way of loading high concentrations of proteins and other releasable
solutes for subsequent long-term delivery. When in situ forming hy-
drogels are used to deliver macromolecules such as DNA and protein,
reduced or incomplete release of these biomolecules is commonly ob-
served [158 160, 189, 190]. Incomplete protein release decreases the
bioavailability of the therapeutic agent and alters the overall delivery
profile. In addition, the protein trapped within the gel is generally mod-
ified or denatured, which can lead to undesirable antigenic responses
when applied in vivo. The factors influencing incomplete biomolecule
release from these hydrogel carriers have commonly been attributed to the
366 CHAPTER EIGHT
fabrication processes. For example, several researchers have studied the
effect of drug polymer interactions on molecule release using thermally
responsive poly(N-isopropylacrylamide) hydrogels [161, 162] and algi-
nate microparticles [163]. Although these studies observed and verified
the incomplete release phenomena, no mathematical model was derived
for predicting molecular release.
When in situ forming gels are used to deliver proteins, irreversible
interactions between the encapsulated proteins and polymerizing polymer
chains decrease the efficacy of the therapeutic agent. van de Wetering
et al. identified the modification of hGH by reactive thiol macromers
in a PEG-based hydrogel system prepared via Michael-type addition
reaction [164]. Additionally, Quick and Anseth specified free radicals as
the major source of incomplete DNA release when photopolymerization
was used to fabricate DNA containing hydrogels [158 160]. Free radi-
cals produced from the photoinitiation process attacked DNA molecules
during UV irradiation, leading to DNA damage. Based on similar obser-
vations during protein encapsulation, Lin and Metters utilized a metal-
ion-chelating molecule, iminodiacetic acid (IDA), to block undesirable
protein polymer conjugation reactions mediated by free radicals. This
protective agent increased the fractional release of target proteins such as
BSA from 40 to 100% following in situ photocuring of PEG-diacrylate
hydrogels [189, 190]. A mathematical model accounting for reversible
protein IDA binding directly correlated the extent of BSA release to the
degree of protein IDA binding.
Modeling drug release from in situ forming hydrogels is challenging
due to several reasons. First, the effects of reduced/incomplete protein
release discussed earlier can only be taken into account after identifying
the sources of protein destabilization and quantifying the extent of in-
teraction. These interactions will greatly depend on the selected polymer
and drug chemistries as well as the method of gel fabrication. Second, in
situ forming gels assume irregular geometries at the implant site, which
are difficult to predict prior to injection. This irregular geometry will
increase model complexity and may also contribute to nonuniform drug
distribution within the gels, which further increases the difficulty to accu-
rately represent the real system in a mathematical construct. Experimental
measurement of release profiles is usually accomplished through in vitro
release studies.
Other biomedical applications of hydrogels are listed in Table 8.7.
Table 8.7 Other biomedical applications of the hydrogels.
Polymeric systems Preparation, characteristics, observation Applicability fields References
Superporous hydrogels with poly The insulin absorption through intestinal mucosa was improved Oral drug delivery [165]
(acrylic acid-co-acrylamide)/O- with absorption enhancers or enzyme inhibitors, chemical
carboxymethyl chitosan modification and design of suitable carriers such as nanoparticles
(O-CMC)-full interpenetrating and liposomes
polymer networks (SPH-IPNs)
Semi-interpenetrating polymer Emulsion-crosslinking method using glutaraldehyde (GA) as a Oral drug delivery [166]
network (SIPN) microspheres of crosslinker.
acrylamide grafted on dextran
(AAm-g-Dex) and chitosan (CS)
Chondroitin sulfate (CS) based Transport of drugs occurs to the surrounding medium by molecular Drug delivery [167]
hydrogels diffusion through the walls of the polymeric microspheres.
pH-sensitive semi-interpenetrating Microspheres prepared by water-in-oil (w/o) emulsion Drug delivery [168]
networks (semi-IPN) of technique.Drug was released in a controlled manner
N, N -dimethylacrylamide
(NNDMA) and chitosan (CS)
Thermo-responsive guar gum Introduction of GG component improves the temperature Specific-colonic [169]
(GG)/poly(N-isopropylacrylamide) sensitivity and permeability of GG/PNIPAAm IPN hydrogels drugs
(PNIPAAm) hydrogels
Hydroxypropyl-²-cyclodextrin Carbopol microgels provide ms-IPNs with flexibility, bioadhesion, Drug delivery or [170]
(HP²CD) hydrogels with domains of swelling ability and pH-responsiveness. HP²CD network is other biomedical
R
interpenetrating Carbopol© responsible for the drug loading and the control of the release. applications
microgels (i.e. loosely crosslinked
PAA micronetworks)
(Continued)
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS
367
Table 8.7 (Continued)
Polymeric systems Preparation, characteristics, observation Applicability fields References
Alginate/porous CaCO3 In-situ release of Ca2+ from CaCO3 microparticles is induced by Ibuprofen delivery [171]
microparticle hybrid hydrogels hydrolysis of D-glucono-´-lactone to reduce pH
pH-sensitive interpenetrating IPN microgels crosslinked with glutaraldehyde Controlled release of [172]
polymeric network (IPN) microgels cefadroxil
(MGs) based on chitosan,
acrylamide-grafted-poly(vinyl
alcohol) and hydrolyzed
acrylamide-grafted-poly(vinyl
alcohol)
Semi-interpenetrating polymer The SIPNs showed a low cytotoxicity on the keratinocytes and Wound dressing [173]
networks (SIPNs) composed of fibroblasts. In- vivo test, granulation tissue formation and wound application
chitosan (CS) and contraction for the CS/poloxamer SIPNs and DHEA-loaded
poloxamerDehydroepiandrosterone CS/poloxamer SIPNs wound dressing are faster than any other
(DHEA)-loaded CS/poloxamer groups.
SIPNs
Physically crosslinked hydrogels  Water diffusivity in hydrogel could be used as a monitor of drugs Antimicrobials drug [174]
pea starch (PS) and calcium alginate release delivery  trisodium
(ALG) gel phosphate (TSP) and
acidified sodium
chlorite (ASC)
Thermoresponsive multiblock Thermo-responsive copolymer films formed highly swollen Biomedical applica- [175]
poly(ester urethane)s comprising hydrogel-like materials when soaked in cold water and shrank tions
poly(µ-caprolactone) (PCL), when soaked in warm water. The copolymers are noncytotoxic
poly(ethylene glycol) (PEG), and
poly(propylene glycol) (PPG)
segments
368
CHAPTER EIGHT
Ä…- and ²-chitin/gelatin membranes Chitin/gelatin membranes with GlcNAc have good biodegradation, Tissue engineering [176]
prepared using chitin regenerated swelling, mechanical and NIH/3T3 fibroblast cell growth
hydrogel (RG) and swelling hydrogel properties.
(SG) with gelatin and
N-acetyl-D-(+)-glucosamine
(GlcNAc)
Chitosan-based polysaccharide Support chondrogenesis, ability to integrate with the host matrix, Cartilage repair [177]
hydrogel neocartilage production
Electrically controlled drug delivery Hydrogels prepared by solution-casting using sulfosalicylic acid as Drug delivery [178]
hydrogels based on poly(vinyl the model drug and glutaraldehyde as the crosslinking agent.The
alcohol) (PVA) diffusion coefficients of the charged drug depend critically on the
electric field strength between 0 and 5 V and electrode polarity.
Chitosan (CS) and montmorillonite The exfoliated silica nanosheets act as crosslinkers to form a Vitamin B12 deliv- [179]
(MMT) based nanocomposites network structure between the CS and MMT.A lower MMT ery
hydrogel (nanohydrogel) concentration (1 wt%), shows a pseudo-zero-order release of
vitamin B12, the release mechanism being changed from a
diffusion-controlled mode to a swelling-controlled mode under
electrostimulation.Increasing the MMT content reduced both the
diffusion exponent n and the responsiveness of the nanohydrogel to
electrostimulation.Nanohydrogel with 2 wt% MMT shows
mechanically reliable and practically desirable pulsatile release
profile and excellent anti-fatigue behavior, compared with that of
the pure CS.
(Continued)
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS
369
Table 8.7 (Continued) Other biomedical applications of the hydrogels.
Superporous hydrogels containing Insulin release from the SPH-IPNs exhibited sensitivity toward pH Insulin absorption [165]
poly(acrylic acid-co-acrylamide)/O- and ionic strength via oral route
carboxymethyl chitosan (O-CMC)
full interpenetrating polymer
networks (SPH-IPNs)
Hydrogel membranes composed of All latex particles used are acrylic systems and synthesized by Caffeine delivery [180]
three kinds of latex particles within emulsion polymerization with the addition of potassium persulfate
carboxymethyl cellulose (CMC) as initiator, and a crosslinking agent, methylene bisacrylamide.
matrix Poly(acrylic acid-co-sodium acrylate) copolymer was applied to
increase the swelling ability of hydrogel membrane.
Mucoadhesive microparticles with Microspheres produced by spray-drying technique. Metoclopramide [181]
5-methylpyrrolidinone chitosan hydrochloride (MC)
(MPC) delivery
PLGA PEG PLGA (poly(ethylene Copolymer synthesized via ring-opening polymerization No Potential bandage [182]
glycol) and poly(lactic-co-glycolic adverse cytotoxicity was observed. for corneal wound
acid)) triblock copolymer repair
Hydrogels based on hydrophilic Hydrogels prepared by salt leaching method. Delivery vehicle of [183]
poly(ethylene glycol) (PEG) and chondrocytes for the
hydrophobic poly(µ-caprolactone) formation of
(PCL) neocartilage
370
CHAPTER EIGHT
APPLICATIONS OF DEGRADABLE IPNS AND HYDROGELS 371
8.7. Future Trends
The futures developments in biomedical field are focused on benefits
extend of biodegradable drug delivery systems to a large group of drugs
and therapeutic conditions. The combination of the degradability with
stimuli responsivity to control of the targeting delivery and degradation
rates are the future tasks for research.
Acknowledgments
The authors are greatful to the CNCSIS and ANCS for financial support
by the IDEI 17/2007, 2561/2008 and NOSITEC 41-017/2007 research
projects.
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