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1 EVALUATION OF SOME BIOPOLYMERS FOR VARIOUS PHARMACEUTICAL APPLICATIONS BY SHAZMA MASSEY ROLL NO. 105-Ph.D-Chem-2009 SESSION: 2009-2014
1
EVALUATION OF SOME BIOPOLYMERS FOR
VARIOUS PHARMACEUTICAL
APPLICATIONS
BY
SHAZMA
MASSEY
ROLL NO.
105-Ph.D-Chem-2009 SESSION: 2009-2014
2
DEPARTMENT OF
CHEMISTRY GC
UNIVERSITY, LAHORE
EVALUATION OF SOME
BIOPOLYMERS FOR
VARIOUS
PHARMACEUTICAL
APPLICATIONS
A thesis submitted to the GC University
Lahore in partial fulfillment of the
requirements for the award of the
degree of
DOCTOR OF PHILOSOPHY IN CHEMISTRY
BY SHAZMA MASSEY
ROLL NO.
105-Ph.D-Chem-2009
SESSION: 2009-2014
3
DEPARTMENT OF CHEMISTRY GC UNIVERSITY,
LAHORE
IN THE NAME OF
THE MOST MERCIFUL AND GRACIOUS GOD “WHO
EVER BELIEVES IN HIM WILL NOT BE
DISAPPOINTED”
Romans 10: 11
DEDICATED TO MY DEAREST AND LOVING
PARENTS
PROF. ISAAC MASSEY (Late)
AND
MRS SHAKUNTALA MASSEY (Late)
4
RESEARCH COMPLETION CERTIFICATE
This is to certify that the research work contained in the thesis titled “Evaluation of some
biopolymers for various pharmaceutical applications” has been carried out and completed
by Ms.Shazma Massey, Roll No. 105-PhD -Chem-2009, Reg. No. 46 -PhD-Chem-2009
under my supervision during her PhD (Chemistry) studies in the laboratories of the
Department of Chemistry. The quantum and the quality of the work contained in this thesis
is adequate for the award of degree of Doctor of Philosophy.
Dated: June27, 2014
__________ __________
Prof. Dr. Mohammad Saeed Iqbal Dr. Irfana Mariam
Supervisor Co-Supervisor
Submitted through
______________________ _____________________
Prof. Dr. Adnan Ahmad Controller of Examination
5
Chairman GC University, Lahore
Department of
Chemistry, GC
University, Lahore.
DECLARATION
I, Ms. Shazma Massey, Reg. No. 046-PhD-Chem-2009 student of PhD in the subject of
Chemistry, session 2009-2014, hereby declare that the matter printed in the thesis titled
“Evaluation of some biopolymers for various pharmaceutical applications” is my own work
and has not been printed, published and submitted as thesis or publication in any form in
any university, research institute etc. in Pakistan or abroad.
Dated: June27, 2014
_____________________
Shazma Massey
CONTENTS
ACKNOWLEDGEMENT I - II
ABSTRACT III - IV
LIST OF ABBREVIATIONS V - VII
LIST OF FIGURES VIII - XIV
6
LIST OF TABLES XV – XVI
1. Introduction 1-30
1.1. General 1
1.2. Polymers in pharmaceuticals 2
1.2.1. Binders 2
1.2.2. Thickners 2
1.2.3. Suspending agents 3
1.2.4. Film coating agents 3
1.2.5. Drug delivery 3
1.3. Polymers from plant materials 4
1.3.1. Materials in use 4
1.3.2. Materials used in the present work 5
1.4. Some important properties of carbohydrate polymers 18
1.4.1. Structure 18
1.4.2. Surface morphology 19
1.4.3. Rheology 19
1.4.4. Thermal behavior 20
1.4.5. Monosaccharide analysis and protein analysis 20
1.4.6. NMR analysis 21
1.4.7. Swelling behavior and water retention 22
1.4.8. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) 23
7
1.4.9. Gel Permeation Chromatography (GPC) 23
1.4.10. Mechanical strength 24
1.4.11. Drug release models and mechanism 24
1.4.12. Empirical/Semi-Empirical models 27
1.4.12.1. Power law 27
1.4.12.2. Zero and First order models 28
1.4.12.3. Mechanistic realistic theories 29
2. Materials and methods 31-46
2.1. Materials 31
2.2. Methods 31
2.2.1. Isolation of biopolymers 31
2.2.2. Characterization 32
2.2.2.1. Elemental analysis 32
2.2.2.2. Moisture content 33
2.2.2.3. FT-IR spectroscopy 33
2.2.2.4. Thermal analysis 33
2.2.2.5. Scanning electron microscopy 35
2.2.2.6. Atomic force microscopy 35
2.2.2.7. Monosaccharide analysis by HPLC 35
2.2.2.8. Protein analysis 36
2.2.2.9. NMR study 37
2.2.2.10. Rheology 38
2.2.2.11. Determination of molar mass 39
8
2.2.2.12. ToF-SIMS 41
2.2.2.13. Mechanical strength 42
2.2.2.14. Swelling index 42
2.2.2.15. Water retention 42
2.2.3. Evaluation of biopolymers as drug carriers 43
2.2.4. Evaluation as binders in tablets 45
2.2.5. Evaluation as suspending agents 45
2.2.6. Evaluation as thickening agents 46
2.2.7. Evaluation as film coating materials 46
3. Results and discussion 47- 151
3.1. Isolation of biopolymers 47
3.2. Characterization 48
3.2.1. Elemental analysis 48
3.2.2. Moisture content 48
3.2.3. FT-IR spectroscopy 48
3.2.4. Thermal analysis 51
3.2.5. Electron microscopy 61
3.2.6. Atomic force microscopy 61
3.2.7. Monosaccharide analysis by HPLC 66
3.2.8. Protein analysis 66
3.2.9. NMR study 71
9
3.2.10. Rheology 76
3.2.11. Determination of molar mass 76
3.2.12. Mechanical strength 81
3.2.13. Swelling index 84
3.2.14. Water retention 84
3.3. Evaluation of biopolymers as drug carriers 84
3.3.1. Electron microscopy 86
3.3.2. ToF-SIMS 86
3.3.3. Dissolution study 91
3.3.3.1. Release profile of diclofenac sodium loaded polymer films in phosphate buffer 97
3.3.3.2. Release profile of diclofenac sodium loaded polymer films in 0.1 N HCl 98
3.3.3.3. Release profile of caffeine loaded polymer films in distilled water 98
3.3.3.4. Release profile of diclofenac sodium loaded polymer tablets in phosphate 120
3.3.3.5. Release profile of diclofenac sodium loaded polymer tablets in 0.1 N HCl 120
3.3.3.6. Release profile of caffeine loaded polymer tablets in distilled water 121
3.3.4. Targeted delivery 146
3.3.5. Disintegration study 146
3.4. Evaluation as binders in tablets 146
3.5. Evaluation as suspending agents 146
3.6. Evaluation as thickening agents 149
3.7. Evaluation as film coating materials 149
3.8. Concluding remarks 152
3.9. Research publication by the author from this work 153
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1. Introduction
1.1. General
Polymers are extensively used in formulation of various dosage forms of pharmaceuticals.
They play their roles as binders, viscosity enhancers, suspending agents, retarded release
materials, targeted delivery devices and scaffolds in tissue engineering. The polymers
employed for these applications are mostly synthetic or semi-synthetic materials [1, 2].
Early research was focused on synthetic non-biodegradable materials such as polyethylene
glycol (PEG) copolymers, which are used in cardiovascular devices. Similarly polyvinyl
alcohol (PVA) gels are used for contact lenses, lining for artificial hearts and in drug
delivery devices. The synthetic devices need to be implanted and then removed by surgery.
Thus for biomedical applications it is desirable that the materials should preferably be
biocompatible and biodegradable. The synthetic polymers are made up of highly toxic
monomers and as such lack biocompatibility. Natural sources of very useful polymers, also
known as biopolymers, are abundantly available, which can be developed as important
pharmaceutical ingredients.
Biopolymers have been isolated from animal or plant sources. Gelatin, collagen and
chitosan are among the extensively used biopolymers from animal sources. Gelatin is
widely used for fabrication of capsule shells. Plants produce large quantities of
polysaccharides; the most important are starches, celluloses and hemicelluloses. In
pharmaceutical applications the use of natural hydrogels such as guar gum, pectin, cellulose
ether, chitosan, carrageenan, hyaluronic acid and alginic acid is quite common.
Polylactide (PL), polyglycolide (PG) and their copolymer polylactide-co-glycolide
11
(PLGA), being biodegradable, have long been used for designing controlled drug delivery
devices. These degrade into glycolic and lactic acids in the body and are easily handled via
normal body metabolism.
1.2. Polymers in pharmaceuticals
The polymers being used as inactive ingredients (adjuvants) in pharmaceutical formulations
are described as follows.
1.2.1. Binders
The most commonly used polymers as binders for tablets are synthetic and include polyvinyl
pyrolidone (PVP), hydroxypropylmethyl cellulose (HPMC), hydroxypropyl cellulose
(HPC), hydroxyethyl cellulose (HEC) and carboxy methyl cellulose (CMC) [3, 4]. They
produce harder granules with greater stability, higher binding, low friability and good
flowability [5,6]. Among the natural polymers guar gum, pectin, high methoxy pectin [7-
10] have found their way in this application. These are biocompatible, low cost,
environmentally friendly and easily available materials. Some of the natural materials
including Lallemantia royleana (LR) and Astragalus tragacantha (AT) are subject of
several studies to evaluate their potential in this respect [11].
1.2.2. Thickeners
Different grades of synthetic polymers described as binders are also used thickening or
viscosity enhancing agents in formulation of oral liquids and ophthalmic solutions.
12
Among the natural materials gum Arabic, guar gum, xanthan gum and gum tragacanth are
in common use in formulation of oral liquids. Glucomannan, a food additive, is used as an
emulsifier and thickener with the E number E425(ii) [12] in candies and cosmetics.
1.2.3. Suspending agents
PVP and PVA are synthetic suspending agents mostly used in formulation of oral liquids
and ophthalmic solutions [13, 14]. But now these polymers are being replaced by natural
polymers such as guar gum and Acacia nilotica (AN) which are used as stabilizers,
emulsifier, thickening, and suspending agent in liquid formulations [15]. AN has been listed
as edible material with E number as E 414.
1.2.4. Film coating agents
Film coating of pharmaceutical tablets is generally being carried out by use of synthetic
polymers including PVP and HPMC. Now film coating materials are undergoing a transition
from synthetic or semi-synthetic to natural products. Hypromallose-pectin and ethyl
cellulose aqueous dispersion also as mixtures with chitosan are becoming popular for film
coating the tablets [16].
1.2.5. Drug delivery
All the sustained release pharmaceutical formulations invariably involve the use of
polymers. The polymers currently in use are mostly synthetic or semi-synthetic materials.
The most common polymers are PVA, HPMC, polymethyl methacrylate (PMMA) and
polylactide-co-glycolide (PLG) [17, 18]. For bioadhesive applications, high molecular
weight acrylic acid polymer crosslinked with divinyl glycol are extensively used in various
13
drug delivery systems. Buccal, intestinal, nasal, vaginal and rectal bioadhesive products can
all be formulated with such polymers [19]. These polymers, in addition to having very high
cost, have biocompatibility issues [20]. Owing to these concerns, people started exploring
natural materials for such applications. In this regard proteins and carbohydrate polymers
such as pectin, guar gum, MP, hyaluronic acid and alginic acid are being suggested as
biocompatible and biodegradable drug carriers. Hydrophilic swellable natural polymers are
promising materials for use in controlled drug delivery systems [21]. These polymers would
absorb water when in contact with body fluids, swell, and release the encapsulated drug in
a programmed manner.
Pectin have been used in controlled-release matrix tablet formulations and colonic drug
delivery applications [22]. Guar gum has been shown to retard drug release in colonspecific
drug delivery systems [23-25]. Formulations containing MP have produced release profile
similar to a commercial sustained-release formulation of diclofenac [26, 27]. Hyaluronic
acid has been used in the preparation of gels for ophthalmic drug delivery [28]. Starch is
also used for sustained release due to its gel-forming ability, biodegradability, and
biocompatibility [29].
During the last three decades or so, stent design has witnessed a fairly rapid evolution from
bare metal stents of increasing complexity, through shape memory alloy stents, polymer
coated, drug eluting stents to biodegradable stents made by use of polymers [30].
1.3. Polymers from plant materials
1.3.1. Materials in use
As discussed above only a few of several natural polymeric materials could find their use
in pharmaceutical formulations. The reason for this is that the natural materials are still
14
passing through various evaluation processes. Most of the evaluations could not reach the
level of approval due to lack of standardization and authenticity. The object of the present
work was to employ authentic methodology to study various properties of selected plant
materials, which could substantiate the claims that natural materials are better substitutes
for the synthetic or semi-synthetic polymers used for pharmaceutical applications.
1.3.2. Materials used in the present work
The materials selected for the present work were swellable when in contact with water. The
criteria for their selection included biocompatibility, biodegradability, non-toxicity and
abundant availability [31]. The plant materials thus selected were: Ocimum basillium (OB)
seeds, Mimosa pudica (MP) seeds, Lallemantia royleana (LR) seeds, Acacia nilotica (AN)
gum, Acacia modesta (AM) gum, Salvia plebian (SP) seeds, , Plantago ovata (PO) seeds
and seed husk, Astragalus tragacantha (AT). A brief description of these materials is
presented as follows.
OB plant
OB, commonly known sweet basil and locally known as „tukhm-e-raihan‟ and „niazbo‟
(Pakistan and India), is a soft green plant having approximately 2 ft height with alternate
leaves and white or pink flowers (Fig. 1). It grows in dry-hot weather (like in Asia and
Middle East) and can be grown in door with exposure to sunlight in colder parts of the
world. Its seeds are small, oval in shape and jet black in color. Its botanical classification
15
a b
c
Fig. 1. Pictures of a) OB plant, b) dry seeds and c) seeds soaked in water
16
is: kingdom: Plantae; division: Magnoliophyta; class: Magnoliopsida; order: Lamiales;
family: Labiatae; genus: Ocimum; species: bacilicum [32]. There are about 150 varieties,
including sweet basil, holy basil, lemon basil, of basil found throughout the world.
Almost all parts of the plant, including seeds, flowers, leaves and roots, are used for health
purposes and as such they do not exhibit toxic effects when consumed in normal dose. Since
ancient time OB leaves are used as flavoring agent in cooking and dried leaves for treatment
of acne, insect bites and snakebites [33-36]. The plant extracts can be used as perfumes or
room freshener. There exist several herbal remedies for treatment of brain, heart, lungs,
bladder and kidney related diseases [37], and as antiviral [38], antiinflammatory [32],
antiseptic [32, 39, 40], antifungal [33, 40-42], antispasmodic [33, 39], antivenom [39],
antioxidant [33, 43], antimicrobial [44, 45], antiulcer [32] agents.
MP plant
MP, commonly known as touch-me-not in English, „chui mui‟ and „lajwantee‟ in Pakistan
and India [46, 47]. It is a plant which closes it leaves when touched and reopens them within
few minutes. The plant grows in sunny weather a height of about 50 cm with a spread of 30
cm (Fig. 2). It can grow in a variety of soils. Seeds of MP are locally called as „tukhm-e-
lajventee‟. The seeds are reddish brown, spherical or flat; they produce mucilage when
soaked in water. The mucilage has been characterized to be mainly composed of D-xylose
and D-glucuronic acid. Its botanical classification is: kingdom: Plantae; division:
Angiospermae; class : Eudocots ; order : Fabales ; family: Fabaceae; genus: Mimosa;
species: Pudica.
All parts of this plant are being used as aphrodisiac and for treatment of various ailments,
17
a b
c
Fig. 2. Pictures of a) MP plant, b) dry seeds and c) seeds soaked in water
18
such as asthma [48], depression [49] , pain [48], infections, toxic effects of venom [50,51],
early aging [52-54] , diabetes [55,56]. It also plays a role in regeneration of nerves [57] and
wound healing [58].
LR plant
LR, commonly known as holy basil also called balango in Pakistan and India, grows in
Asia, Europe and Middle East. The height of this plant is approximately 2 ft. Its seeds are
locally known as „tukhm-e-balango‟ or „tukmalanga‟, and black psyllium seeds in English.
They are oval, jet black with a white spot at one end but bigger in size than tukhm-eraihan
(Fig. 3). The seeds are widely used in ayurvedic medicine [59]. Its botanical classification
is: kingdom : Plantae; division: Angiospermae; class: Eudicots; order : Lamiales; family:
Lamiaceae; genus: Lallemantia; species: Royleana [60].The Labiatae family (Lamiaceae)
is one of the largest family of flowering plants, with almost 4000 species and about 220
genera existing worldwide.
Balangu seed gum (BSG) is a low cost source of hydrocolloid with high molecular weight
(3.65×106 g/mole) and intrinsic viscosity (7236.18 g/ml) [61].The seeds of this plant have
cool effect on body and mind and their extract cures many diseases including inflammation
[62], heart problems [63, 64] , women specific diseases [65]; it lowers blood pressure,
removes stress and acts as sedative [66]. The paste of this plant helps cure abscesses
produced by pus.
AN plant
AN, commonly known gum Arabica (Fig. 4) and gum keekar or babul in Pakistan and
19
a
c
Fig. 3. Pictures of a) LR plant, b) dry seeds and c) seeds soaked in water
b
20
a
b
Fig. 4. Pictures of a) AN plant, b) gum
21
India. Its botanical classification is: kingdom: Plantae; division: Angiosperms; class:
Magnoliopsida; order: Fabales; family: Fabaceae; genus: Acacia; species: Nilotica. The
gum is used in treating hypotension caused by surgical shock or hemorrhage. The gum has
been successfully used in plastic surgery for grafting of destroyed peripheral nerves [67].
Use of AN pods reduces blood sugar level, plasma cholesterol, triglyceride and lowdensity
lipids but increases plasma high-density lipids [68]. Almost all mature and immature parts
of AN plant have shown to be active against a number of diseases such as cancer, asthma,
diabetes, hepatitis C, high blood pressure, bacteria, AIDS, fungal and bacterial infections.
The gum acts as antipyretic, emollient, astringent, anti-asthmatic and liver tonic [69,70].
Gum arabic is a branched-chain complex polysaccharide, may be neutral or slightly acidic,
found as mixed calcium, magnesium and potassium salt of polysaccharidic acid. Main
components of this acid are D-galactose (Gal), L-arabinose (Ara), L-rhamnose (Rha), and D-
glucuronic acid (GlcA) with the structure as:
where A = L-arabinose, R = L-rhamnose, G = D-galactose, U = D-glucuronic acid. The
backbone consists of 1,3 -linked beta- D-galactopyranosyl units. The side chains are
composed of two to five 1,3-linked beta- D-galactopyranosyl units, joined to the main chain
through 1,6-linkages. The gum is known to act as an anti-oxidant and protects hepatic-,
renal- and cardiac toxicities in rats. It enhances dental remineralization and has
antimicrobial activity. It showed adverse effects on electrolyte balance and vitamin D in
22
mice [71]. The gum is collected after 20-30 days after an incision has been made on the
tree. The gum is also known to contain some peroxidases. For this reason, it should not be
mixed with easily oxidizable compounds.
AM plant
AM , commonly known as blackwood and locally as gum phulai or Amritsar gum in
Pakistan, Afghanistan and India (Fig. 5). It belongs to a large genus acacia having about
1500 species. It grows mostly in hot weather. Its botanical classification is: kingdom:
Plantae; division: Angiosperms; class: Magnoliopsida; order: Fabales; family: Fabaceae;
genus: Acacia; species: Modesta.
AM gum has been used for effectively treating lumbago, skeleto-muscular problems and
chronic stomach disorders [72]. Ash of the bark of AM finds use in treating paralysis and
asthma. Chest pains and dysentery can also be treated by powder of dry bark with a little
quantity of salt and sugar [73,74]. AM twigs are used as tooth brush (miswak) for cleaning
teeth and is good for bleeding gums. The extracts of AM leaves was found to be effective
against most bacterial and fungal infections. The alcoholic extracts of AM leaves are known
to reduce blood glucose (Glc) level in rats significantly [75].
SP plant
SP, commonly known as sage and locally known as „kamarkas‟ and „samundersok‟, grows
on the sides of streams and rivers as a small herb (Fig. 6). Its botanical classification is:
23
a
Fig. 5. Pictures of a) AM plant, b) gum
a
Fig. 6. Pictures of a) SP plant, b) seeds soaked in water
b
b
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kingdom: Plantae; division: Magnoliophyta; class: Magnoliopsida ; order: Lamiales; family:
Lamiaceae; genus : Salvia ; species : Plebia. Its seeds and leaves have a lot of medicinal
value. The popular uses include their use in: sore throat and headach [65].
When seeds are soaked in water they develop mucilage which is carbohydrate biopolymer
[76].
PO plant
PO, commonly known as psyllium and locally known as ispaghula (Fig.7) [77], is cultivated
all over the world due to its importance as a food. Its seeds are oval in shape and brown in
color with one side smooth and the other side depressed. The seed husk is soft and needle
like fiber (Fig.7). The husk and seeds swell in water and produce a mucilage characterized
to be polysaccharides. The botanical classification is: kingdom: Plantae; division:
Magnoliophyta; class: Magnoliopsida; order: Lamiales; Family: plantaginacea; genus:
Plantago; species: Ovata.
Both the husk and seeds possess medicinal value and are used as health foods. They are
used in diarrhea and constipation, for control of body weight, blood pressure and cholesterol
level [78-81]. The mucilage is also used in frozen dairy desserts as thickener or stabilizer.
AT plant
AT, commonly known as goat's-thorn, is cultivated in middle east and Iran. It is among
3,000 species of astragalus herbs and shrubs, belonging to the legume family (Fig. 8). The
genus is native to temperate regions of the Northern Hemisphere. Botanically it is
25
a b
c
Fig. 7. Pictures of a) PO plant, b) dry seeds, c) seeds soaked in water and d) seed husk
soaked in water
d
26
a-
b-
Fig. 8. Pictures of a) AT plant, b) gum
27
classified as kingdom: Plantae, division: Spermatophyta; class: Dicotyledones; order :
Fabales; Family: Fabaceae; genus: Astragalus; species: Tragacantha. Its gum is locally
called „gond katira‟.
Gum tragacanth looks like twisted ribbons or flakes of polysaccharides (Fig. 8) having no
specific color and taste. The gum absorbs water to form gel, which can be converted into
paste. It is very commonly is used in veg-tanning the leather, as stiffener in textile industry
and binder in making artist's pastels. Its paste is used in floral sugar craft to make flower
decorations for cakes. It is also used to treat cough and diarrhea in herbal medicines.
Tragacanth mucilage has fast wound healing capacity because hydrolysis of tragacanth into
Arabinose and glucoronic acid coagulate the surface proteins for fast recovery and
prevention of infections [82, 83].
1.4. Some important properties of Polysaccharides
In order to qualify their use as pharmaceutical ingredients the polysaccharides must pass
some specific tests for their intended use. In the following paragraphs some of the most
important properties of the polymers and the methods of testing thereof have been reviewed
briefly.
1.4.1. Structure
It is one of the essential requirements for the prospective pharmaceutical ingredients that
their precise chemical composition and structure must be known. The first step towards
structural determination is the elemental analysis. This analysis can be carried out by use of
automatic CHNSO analyzers very precisely. Carbohydrate polymers, natural
polysaccharides, are reported to have C and H around 45% and 6% respectively; these
28
values largely depend upon the moisture content and some other components such as uronic
acids in the materials [84-86]. The moisture content can be determined as loss on drying or
more precisely by Karl-Fischer titration.
Infrared spectroscopy is generally helpful in identifying the nature of the polysaccharides.
In case of hemicelluloses, a strong broad bond at 3414 cm-1 (due to hydrogen-bonded
hydroxyl groups) and a band at 2919 cm-1 (due to symmetric C–H vibration) are generally
observed along with other characteristic bands at 1419, 1384, 1244, 1040, and 897 cm-1
[87]. The spectra are generally dominated with stretching and bending vibrations of C-H,
C-O, C-C, C-OH, and C-O-C groups. The band at 1039 cm-1 is mainly due to a glycosidic
linkage (C–O–C). The band at 1600 cm-1 is principally associated with absorbed water.
The peak at 630 cm-1 and 500 cm-1 are due to polymer backbone.
1.4.2. Surface morphology
Surface morphology of polymeric materials plays an important role in controlling drug
loading, distribution and release. Scanning electron (SEM) and atomic force microscopic
(AFM) techniques are powerful tools to study the surface morphology of materials. The
SEM and AFM images can be used to identify the types of voids, layers, surface roughness
and nanostructure in the polymers.
1.4.3. Rheology
Rheology involves the study of the effect of shear stress on viscosity of the dissolved
polysaccharides, which provides important information about the viscosity and elasticity of
a polymer. Elasticity is a phenomenon where a polymer is stretched on application of a
stress and readjusts to its original structure as soon as the stress is removed. It also provides
29
information about the flow (Newtonian or non-Newtonian) of viscous solutions formed by
polymers.
1.4.4. Thermal behavior
Thermal stability of polymeric materials is extremely important for determining their
potential in various applications [88,89]. Thermogravimetric analysis (TGA) and
differential scanning calorimetry (DSC) are significant and most widely used techniques to
study the stability, degradation, moisture content, glass transition temperature and other
properties of polymeric materials [90]. Thermal stability of hemicelluloses generally
decreases with decrease in molar mass [91]. Loss of moisture is associated with an
endothermic peak at 85-110°C in the DSC scans. The stability of polymers is
characteristically judged by determining its integral procedural decomposition temperature
(IPDT) and comprehensive index of thermal stability (ITS). The life-time of polymers can
also be predicted by two standard ASTM methods based on thermal analysis. However,
according to thermal community it is emphasized that better estimate of life-times can be
obtained by isoconversional methods [92]. Pyrolytic GC-MS analysis of the volatiles
formed by degradation of polysaccharides can give an insight into the mechanism of the
degradation pattern of the polymer [93-95].
1.4.5. Monosaccharide analysis and protein analysis
Monosaccharide analysis is done by hydrolyzing the polysaccharides generally by
Seamon‟s method [96]. The hydrolysis may be severe or mild. In severe hydrolysis 12M
and in mild 1M sulphuric acid is used. After hydrolysis the monosaccharides are
determined by HPLC. The monosaccharide composition of the polymer give us an idea
30
about the major and minor sugar content. Protein analysis is carried out to get a
confirmation that the biopolymers are pure carbohydrate polymers or contain some
proteins. Protein analysis is conviently performed by the use of bicinchoninic acid (BCA)
kit [97].
1.4.6. NMR analysis
NMR spectroscopy is a very powerful technique and can be used to find detailed structural
information of the sample. In case of polysaccharides, NMR peak broadening can cause
problems due to the long relaxation times involved. However, after degradation, fine
structure information regarding relationship between proton-proton and proton-carbon by
different advance NMR techniques such as two-dimensional correlation spectroscopy (2D-
COSY), total correlation spectroscopy (TOCSY), heteronuclear singlequantum correlation
(HSQC), heteronuclear multiple-quantum correlation (HMQC), and heteronuclear
multiple bond correlation (HMBC) can be obtained. Distortionless Enhancement of
Polarization Transfer using a 135 degree decoupler pulse (135-DEPT) can differentiate
between carbons having even number of protons and carbons having odd number protons.
One-dimensional 1H and 13C NMR spectra have been used in combination with two
dimensional COSY, HSQC-DEPT techniques for investigation of anomeric protons and
carbons of AN and AM [98-101]. Information on the nature, relative content of
monosaccharide residues, configuration, and the type and amount of specific linkages in
AN and AM have been determined using 13CNMR [102-104]. Signals from non- and
monosubstituted xylose residues in 13C NMR spectrum has been assigned using 13C-
HSQC-DEPT and COSY techniques [105]. Structure of AX from ispaghula seed husk has
been discussed in detail using HMQC and HMQC-TOCSY NMR
31
techniques after partial hydrolysis [106]. AN and AM were also analyzed by solid state
13C CP-MAS NMR technique [107].
1.4.7. Swelling behavior and water retention
For the polymers to be used in drug delivery it is important to know swelling behavior and
water retention of polymers used for formulation of drug delivery devices [108]. The
polymers absorb water, swell, and release the encapsulated drug in a sustained manner.
Swelling index is determined by the formula
Swelling Index = [(Weight of wet sample –Weight of dry sample) / Weight of dry sample)]
×100
The water retention was calculated by the formula:
Ww - Wd 100
Water Retention(%)
Wd where, Ww = weight of sample
in wet state, Wd = weight of sample after drying at 105 C.
1.4.8. Time-of-flight secondary ion mass spectrometry (ToF-SIMS)
ToF-SIMS is a powerful technique that can map distribution of a chemical compound
dispersed in a polymer matrix with high spatial resolution. It has emerged as a rapid
technique to study surface chemistry of materials at a spatial resolution around 1 m, and
has been used extensively to characterize a range of materials including polymers and
biological samples [109, 110]. Only a few studies involving imaging of drug delivery
32
systems by ToF-SIMS [111] have been reported. The technique involves rastering of a
cluster ion beam onto the surface of the sample, which results in generation of secondary
ions through a cascade of collisions. The secondary ions are then accelerated into time-
offlight tube. The advantages of ToF-SIMS include high mass resolution (>7,000), a large
mass range (element to a complex molecular mass), excellent spatial resolution and an
ability to simultaneously detect fragment ions over a large mass range [112]. The technique
allows several samples to be loaded on to the cryo-stage and analyzed consecutively. The
technique produces images.
1.4.9. Gel Permeation Chromatography (GPC)
The molar mass distribution and polydispersitivity index (PDI) of a polymer are important
characteristics that indicate the bulkiness and hetero-/homogenic nature of the polymer. The
mass averages generally determined are Mn, Mw and Mz, which are numberaveraged,
weight-averaged and z-averaged molar masses respectively. The PDI is defined as the ratio
Mw/Mn. For an ideal monodisperse polymer, the molar mass averages are equal i.e.
Mn=Mw=Mz and therefore PDI value is 1. However, for a polydispersed system the
relationship is Mn<Mw<Mz. The natural polymers generally exhibit a PDI value greater
than 1 due to their heterogenic nature. In case of hemicelluloses, the molar masses of
materials isolated from various sources have been found to be of the order of 10-5 with
PDI value >1 [113].
1.4.10. Mechanical strength
Mechanical strength also known as tensile strength greatly affect the film formation ability
and is measured by universal testing machine. The knowledge of strength of materials is
important and useful at the time of fabrication of devices from the polymers.
33
s = F/A Where; s = the
breaking strength (stress)
F = the force applied that caused the failure in N.
A = the least cross- sectional area of the material in m2 (original width ˣ original thickness)
1.4.11. Drug release models and mechanism
In order to study the release profiles of polymers various models have been proposed, which
describe the release mechanisms. The work on modeling started with publication of the so
called „Higuchi equation‟ by Prof. T. Higuchi [114, 115], which described the release of
drug molecules from polymer films.
M = kH t1/2 (1) where M is the amount of drug released in
time t, kH is the Higuchi release constant. Since this work, a number of empirical/semi-
empirical and mechanistic releasic models of drug release process have been suggested.
The later type models are more accurate and being based on real phenomenon, can give
insight into the phenomenon of drug release as compare to the former which lack these
capabilities. The continuous increased importance of hydrogels in CDDS, a number of
mathematical models has been suggested for such systems [116-127].
The drug release from a hydrophilic matrix is generally described by two contending
mechanisms: Diffusion-controlled release and relaxation-controlled release. The swelling
of hydrogel on contact with biological fluid changes its glassy state to the rubbery state.
The absorption of water into the hydrogel bring about its expansion due to lowering of the
glass transition temperature (Tg) being controlled by the concentration of the swelling
34
agent. The strength of the swollen gel is important for the matrix performance and it
depends upon the viscosity, concentration and structure of the rubbery polymer.
Colombo et al [124] described the swelling of heterogeneous swellable matrices by three
front positions, where „front‟ is the region in the matrix where the physical changes are
occurring sharply. The three fronts are, as shown in Fig. 9.
• the „swelling front‟; between the rubbery and the glassy region.
• the „erosion front‟; between the solvent and the matrix. The time variation of the
thickness of the gel-layer is controlled by the positions of the erosion and the
swelling fronts.
• the „diffusion front‟; between the erosion and the swelling fronts. It forms a
boundary that separates solid from dissolved drug.
The position of the diffusion front in the gel depends upon the solubility and loading of
the drug. The movement of diffusion front is a function of the dissolution rate of the
drug in the gel.
35
Fig. 9. Schematic representation of a swelling controlled drug delivery system showing
three fronts of movement is shown below.
The rate of drug release is dependent upon the interactions between polymer, water and
drug. The thickness of the gel layer and drug gradient in the gel determines the release
kinetics. The increase in thickness of gel layer is fast in the beginning owing to rapid
penetration of solvent that causes chain disentanglement, slows down as the process goes
on due to increase in distance for diffusing solvent. It therefore, follows that the gel-layer
formation and its permeability to the drug molecules is the key factor that controls the
drug release and these are governed by solvent penetration, drug diffusion and dissolution,
polymer swelling and matrix erosion. There are several other factors which can influence
the drug release phenomenon, some of which have been considered in other mechanistic
realistic theories a brief description of which follows.
In addition to the Higuchi equation discussed above, below is given a brief account of
models that appear frequently in research articles for analyzing the drug release from
hydrogels.
1.4.12. Empirical/Semi-Empirical models
These models can describe the drug release from a given polymeric device. The models
generally used are described below.
1.4.12.1. Power law
36
An empirical relationship called Power Law is frequently used to describe the Fickian,
non-Fickian, case-II transport mechanisms of drug release from a polymer matrix
[128131].
Mt lnkp nlnt (2)
ln
M
Where Mt/M∞ is the fraction of drug released in time t, kp is the Power Law constant
characteristic of the drug-matrix system and n is the diffusion exponent. The value of n
identifies different mechanism for drug release. For different geometries the limits of n are
different and are summarized in Table 1.
Case I mechanism occurs when the diffusion rate is far less than the relaxation rate and
case-II mechanism is seen otherwise. If both rates are comparable then anomalous
transport is the dominant mechanism, and for value of n greater than certain limits the drug
release become constant for a longer period (time-independent) and termed as super case-
II transport [132]. It is generally believed to be controlled by polymer erosion process
which cause and exponential increase in the release of drug towards the later stages.
Table 1: The limits of release exponent n for different geometries
Release exponent, n Mechanism of drug release
Thin Film Cylinder Sphere
0.5 0.45 0.43 Diffusion-controlled
(Fickian, Case-I, transport)
Diffusion-/swelling-controlled
0.5<n<1.0 0.45<n<0.89 0.3<n<0.85
(Anomalous transport, Non-Fickian)
37
1.0 0.89 0.85 Swelling-controlled (Case-II
tansport)
n>1.0 n>0.89 n>0.85 Time-independent release (Super
case-II tansport)
1.4.12.2. Zero and First order models
Zero order (Eq. 3) [133] and first order (Eq. 4) [134] kinetic equations are also widely
used to describe drug release from matrices. However, these models do not provide an
explanation of the physical/chemical phenomenon involved in drug release rather they are
employed to simply fit the release profile.
M=k0t (3)
where k0 is the zero order release constant, M is the amount of drug released in time t.
lnM = –k1 t + lnM0 (4) where k1 is the first order release constant, M is the remaining
amount of drug in the tablet after time t and M0 is the initial amount of drug in the tablet.
Hixon-Crowell cube root law (Mo 1/3 – M 1/3 =kHCt ) (5) where M is the amount
of drug released in time t, kHC is the Hixson–Crowell release constant and Mo is the initial
amount of the drug in the tablet [135].
1.4.12.3. Mechanistic realistic theories
Mechanistic realistic models tried to develop a real story for the drug release phenomenon
from a given device. These take into account a number of factors that may influence the
drug release. A good detail of the possible physical factors that may be related to this
phenomenon has been provided by Siepmann and Siepmann [136]. The model developed
by Korsmeyer et al. describes the diffusion of water (penetrant) and a solute for a swellable
38
polymer slab [137,138]. The developed model was successfully applied to a hydrophilic
polymer with a water-soluble drug. This interesting model suggested that the water
(penetrant) is sorbed and the drug is desorbed and released. Any form of diffusion
coefficient can be used in the model.
Ju and co-workers [139-141] developed a comprehensive mathematical model to describe
the swelling/dissolution behaviors and drug release from HPMC matrices. The major thrust
of this model is to employ an important physical property of the polymer, the polymer
disentanglement concentration, r, the polymer concentration below which polymer chains
detach of the gelled matrix. Furthermore, matrix dissolution is considered similar to the
dissolution of an object immersed in a fluid. As a result, a diffusion layer separating the
matrix from the bulk solution is incorporated into the transport regime. In addition, an
anisotropic expansion model is introduced to account for the anisotropic expansion of the
matrix, the surface area in the radial direction dominating over the surface area in the axial
direction. They predicted that the overall tablet size and characteristic swelling time
correlate with r qualitatively. Two scaling laws were established for the fractional polymer
[M (t) /M (infinity)] and drug Seipmann et al. [126127] developed a comprehensive
mathematical model describing drug release from HPMC-based matrix tablets, taking into
account the diffusion of water and drug, nonconstant diffusivities, moving boundary
conditions, the swelling of the system, polymer and drug dissolution, and radial and axial
mass transfer in cylindrical geometries (Fig. 10). The model was successfully fitted to drug
release kinetics of the ophylline from HPMC matrices.
39
Fig. 10. Mathematical modeling of drug release from HPMC-based matrix tablets; (a)
scheme of cylindrical tablet for mathematical analysis, (b) swelling matrix tablet.
2. Materials and methods
2.1. Materials
The materials and chemicals used in this study were: seeds of OB, MP, LR, PO and SP;
gums AN, AM and AT; PO Husk (purchased from local market); L-(+)-arabinose, D-
(+)galactose, D-glucose, D-(+)-xylose, L-rhamnose monohydrate, sodium azide
(SigmaAldrich, USA); BCA protein assay reagent A (cat # 23228) and B (cat # 23224)
40
and albumin standard (cat # 23209) (Thermo Scientific, Pierce, USA); lactose (Sheffield
BioScience, UK); citric acid and sodium citrate (Riedel-de Haën Chemicals, Germany);
paracetamol (NovaMed, Pakistan); titanium dioxide (Colorcon, UK); talc (Specialty
Minerals Inc., USA); Opadry II yellow (Colorcon, UK) ; dextrose (Bio-Rad, USA);
disodium hydrogen phosphate and hydrochloric acid (E. Merck, Germany). All the
chemicals were used without further purification. Distilled water was used throughout this
study.
2.2. Methods
2.2.1. Isolation of polysaccharides
Mucilage of PO, OB, MP and LR seeds
The seeds were dedusted by sifting and 50 g of them were soaked in distilled water
(seedwater ratio 1:50 w/v) separately for about 24 h. The swollen material was blended by
use of a kitchen blender for 2-3 min intermittently, taking care that the seeds are not broken.
The mucilage was separated by filtration through muslin cloth under vacuum. The water in
the mucilage was removed by evaporation in a rotary evaporator at about 30 C and the
semi-dry material was spread on polyethylene sheet and allowed to air-dry at room
temperature ( 25°C) for one week to obtain a film having thickness 0.07-0.15 mm.
Mucilage of SP seeds
The SP mucilage was prepared from the seeds according to the procedure as above by
excluding the blending step because of the softness of the SP seeds.
41
Mucilage of PO Husk
The PO husk (20 g) was soaked in water (1000 mL) for 24 h. This was followed by blending
with the kitchen blender. The excessive water was separated by filtration under vacuum (1.5
× 10-2 mbar; Edwards rotary pump E2M28) through muslin cloth (maximum pore size 1
mm) followed by further removal of water by use of the rotary evaporator at about 30 C.
The wet mucilage was spread on the polyethylene sheet and air-dried to obtain a thin film.
Purification of gums AM, AN and AT
The gums AM and AN (20 g each) as obtained from the market were freed from extraneous
matter by dissolving them in water (150 mL) separately. The solutions were filtered through
muslin cloth (maximum pore size 1 mm) under vacuum (1.5 × 10-2 mbar; Edwards rotary
pump E2M28). The volume of the filtrate was reduced to approximately 30 mL by
evaporation in a rotary evaporator at about 30°C. The thick paste was spread on
polyethylene sheets and air-dried at room temperature (~ 25°C) for five days to obtain a
film having thickness 0.22-0.25 mm. The yields were approximately 98%.
2.2.2. Characterization
2.2.2.1. Elemental analysis
Elemental analysis of the materials were performed on CHNS analyzer Vario MICRO
V1.4.2 (Elementar Analysensysteme, GmbH, Germany).
2.2.2.2. Moisture content
Moisture content was determined by Karl-Fischer titration using 701KF Titrino (Metrohm,
Switzerland) after drying the materials at 25 ᵒC.
42
2.2.2.3. FT-IR spectroscopy
The FT-IR spectra were recorded on FT-IR 640 (Varian, USA) by use of KBr disc and film
in the range 4000 – 400cm-1.
2.2.2.4. Thermal analysis
Thermogravimetric analysis was performed in the range ambient to 600 C on SDT
(Q600) thermal analyzer (TA Instruments, USA) in the TGA, DTA and DSC modes under
nitrogen at different heating rates 5, 10, 15 and 20 C min-1. The DSC scans were also
obtained in the range -40 – 300 C at 10 C min-1 heating rate. In order to determine
activation energy the data were analyzed by isoconversional Flynn–Wall–Ozawa (FWO)
method (Eq.6)
(6)
where , the heating rate; A the pre-exponential factor; R the general gas
constant and T is the temperature (K) at the conversion . The FWO method was the first
isoconversional linear integral method developed by Flynn, Wall [142] and Ozawa [143].
This method is based on the assumption that for a fixed extent of conversion, the reaction
rate depends upon temperature only. Thus it eliminates the dependence of reaction kinetics
on any model, that may be represented by an integral form g( ). Therefore, this may be
termed as a model-free approach. This method uses data obtained at different heating rates,
thus at fixed , the plot of log vs 1/T will be a straight line, the slope of which permits the
calculation of Ea. The is defined as (w0 – wt) / (w0 – wf), where wt is the weight of the
43
sample at any temperature T, w0 the initial weight and wf is the final weight at the
temperature where the mass loss is approximately negligible. Thermal stabilities of the
polysaccharides were determined by integral procedural decomposition temperature (IPDT)
and comprehensive index of intrinsic thermal stability (ITS) by Doyle [144]. This method
is considered to be most appropriate and reliable to determine these parameters because it
takes into account the whole TGA curve by measuring area under it. The ITS and IPDT
values were determined from TGA of all four heating rates and mean values are reported
for each polysaccharide. The life-times of polysaccharides were also predicted by model-
free approach based on Eq. 7. The model-free approach eliminates the limitations of other
methods such as ASTM E1641 and E698 methods which assume that the Ea remains
constant throughout the degradation step. Therefore, in cases where Ea is not constant in a
step the model-free approach is more appropriate [145].
(7)
This relationship exploits the variation of activation energy with . The integral in the
numerator has no analytical solution, however, it can be evaluated by different
approximations. In this study the Senum–Yang fourth degree approximation was used.
The data were analyzed by the use of Universal Analysis 2000 software, version 4.2E (TA
Instruments, USA), and MS Excel 2010. Hierarchical cluster analysis (HCA) was
performed to classify the materials with similar thermal properties by use of Statistica 8 and
dendrogram were drawn using weighted pair-group average and Euclidean distance.
2.2.2.5. Scanning electron microscopy
Surface morphology was studied by recording images on scanning electron microscope
(SEM) Hitachi S-3400N or Joel JSM-6060 LV after sputter coating with gold with Leica
44
EM SCD005. The micrographs were recorded at different magnifications.
2.2.2.6. Atomic force microscopy
Surface roughness was studied by atomic force microscopy (AFM). The images were
optained from the samples films in a non-contact mode on the scanning probe microscope
CP-11 (Veeco, USA) at room temperature.
2.2.2.7. Monosaccharide analysis by HPLC
Monosaccharide analysis was performed after hydrolysis [96] by using Dionex ICS 3000
HPLC system consisting of: CarboPacPA20 column (0.4 × 150 mm) and electro chemical
detector according to a reported method (CarboPack PA20: a new monosaccharide separator
column with electrochemical detection with disposable gold electrodes) [146].
The samples were subjected to both mild and severe hydrolysis treatment. The mild
procedure is a single-step method. It is used to reduce the formation of by-products. For
more stable polysaccharides severe hydrolysis treatment, the two-steps method is
required.Sugar composition determined gave slight variation depending on the one-step or
two-step hydrolysis methods used. In severe treatment the sample (30 mg) was heated with
of 12M sulphuric acid (1 mL) at 37 C for 1 h followed by addition of water (11 mL),
heating at 100 C for 2 h and quick cooling. In mild treatment the sample (30 mg) was
heated with 1M sulphuric acid (12 mL) at 100 C for 2 h and then cooled quickly. The
samples from both the treatments were diluted 100 time with 10mM NaOH. To these
solutions mannitol (50 µL) was added as an internal standard and measurements were
performed in triplicate.
45
Calibration curves were constructed for Ara, Xyl, Gal, Rha and Glc. The concentrations
used of these sugars were: 400, 200, 100, 50, 25, 12.5, 6.25, 3.125 µM.
2.2.2.8. Protein analysis
The protein content was determined by use of bicinchoninic acid (BCA) kit [97]. Briefly,
The sample (0.11g) was dissolved in distilled water (1 mL) by heating to 37 C in water
bath for 24 h and shaking. Only the materials from SP, AM, AN, MP and PO produced clear
solutions, therefore, the other materials could not be analyzed for the protein content.
The solutions were centrifuged for 3 minutes for further clarity. The albumin standard
dilutions (1000, 750, 500, 250, 125, 25 and 0 g mL-1) were prepared similarly. The sample
and the standard preparations were carried out in duplicate.
To each of the standard and sample solutions (0.1 mL) 2.0 mL of the coloring reagent
composed of reagent A (50) and reagent B (1) were added and mixed well. These solution
mixtures were covered and incubated at 37 C for 30 min. After cooling to room
temperature, absorbance was measured, within 10 min, at 562 nm by using water as
reference. The calibration curve was constructed by use of MS Excel spread sheet.
2.2.2.9. NMR study
NMR methods: sample preparation
AN and AM gums, being soluble in water, were subjected to NMR analysis. The sample
(2.00 g) were dissolved in D2O (20 mL), freeze-dried, redissolved in D2O (20 mL), freeze-
dried, and finally dissolved again in D2O (20 mL). For the solid state NMR the non-
deuterated and deuterated samples were used.
46
NMR methods: solid state experiments
13C CPMAS NMR spectra were recorded on a Bruker (Karlsruhe Germany) AVANCE 600
NMR Spectrometer with narrow bore magnet and 4mm triple resonance probe. The
parameters used in CPMAS experiments were as follows. The Proton 90º pulse length was
5 µs. Field strength of the proton and spin locking fields was 50 KHz. Samples were packed
into 4 mm rotors and spun at 10 KHz. ppm scales were referenced to the high field line of
adamantane (29.5 ppm) run as an external standard under identical conditions to the
samples. Proton decoupling was provided by a WAHUHAHA sequence and the proton
power levels during the contact time and decoupling stage could be varied independently
to provide optimum signal to noise levels.
NMR methods: high resolution experiments
All single and multi-dimensional NMR experiments were carried out on a Bruker 800 MHz
Avance III Spectrometer equipped with a QCI cyroprobe. For each sample the 90 pulse
and transmitter frequency were calibrated. The number of scans collected in each
dimension for each experiment was determined by the carbohydrate concentration. Data
acquisition and processing were carried out using Topspin 3.1.b.53 software. The 1-D
experiments were apodised using an exponential window function with 2 Hz line
broadening. For multi-dimensional datasets a shifted squared sine bell was used with the
offset being optimised to achieve the best balance between resolution and signal to noise.
All data were zero-filled by at least a factor of 2. For heteronuclear dimensions linear
prediction was employed.
47
1-Dimensional Experiments
The 1-D proton spectra were recorded using excitation sculpting water suppression, with
a spectral width of 14 ppm. The proton transmitter frequency was set to 4.702 ppm and
typically 64 scans were acquired.
2-Dimensional Experiments
The 2-D carbon protonheteronuclear single quantum coherence (HSQC) spectra were
acquired over a spectral width of 14 ppm in the 1H dimension and 200 ppm in the 13C
dimension. The transmitter frequency for carbon was centred at 100 ppm. Between 16
and 64 scans were acquired, with 128 complex points in F1. Quadrature detection in the
carbon channel was achieved using States-TPPI.
3-Dimensional Experiments
The 3-D data were acquired for the assignment of spin systems of individual sugar subunits
of the gums. The carbon and proton dimensions were optimized as for the 2-D HSQC
experiments with the carbon transmitter frequency being set at 100 ppm. A third proton
dimension enabled a TOCSY experiment to be correlated with each HSQC cross peak. 16-
64 scans and 98 - 128 points were acquired in the first proton dimension, whilst for the
second proton dimension scans and 128 points were acquired. The 3-D processing was
handled as per HSQC.
2.2.2.10. Rheology
Solution of gums and gels were extracted from the seeds and husk and weight of dry polymer
was calculated from dry and wet weight. pH of all the solutions were measured at 25 C.
48
Rheology was studied on Anton Par Physica MCR301. Double gap (Dg) cylinder was used
to measure the effect of shear rate on viscosity. Shear rate was varied from 10 -2 to 10+3 and
vice versa.
2.2.2.11. Determination of molar mass
Molar mass of the polymers, under investigation, were determined by size exclusion
chromatography coupled with multi-angled light scattering (SEC-MALS) and an online
viscometer (Torqometer, Beckman optima XL-A, USA), analytical ultracentrifuge
(Proteome LabTM XL with scanning absorption optics, USA) and from rheology data.
Intrinsic viscosity data can be used to determine shape and molar mass of polymers [147].
The concentrations of the polymer solutions were determined by use of Atago DD-5
Differential Refractometer (Jencons Scientific, UK). The intrinsic viscosity was measured
in distilled water using Anton Par Physica MCR 301and double gap cylinder. The pH of the
solutions were 4.41 (AN) and 4.29 (AM) at 24 C. Molar masses were determined in
phosphate buffer (pH 6.8) by light scattering using 1% solution of each gum and in water
for rheological data using 25% stock solution using Mark-Houwick equation (8)
[ɳ] = KMa (8)
Size Exclusion Chromatography coupled to multi-angled light scattering and an online
viscometer (SEC-MALS).
Analytical fractionation was carried out using a series of SEC columns TSK G6000PW,
TSK G5000PW and TSK G4000PW protected by a similarly packed guard column (Tosoh
Bioscience, Tokyo, Japan) with on-line MALLS (Dawn DSP, Wyatt Technology, Santa
49
Barbara, USA) and refractive index (Optilab rEX, Wyatt Technology, Santa Barbara,
USA) detectors. The eluent ( pH 6.8, phosphate buffer) was pumped at 0.8 ml min -1
(PU1580, Jasco Corporation, Great Dunmow, UK) and the injected volume was100 l ( ~
1.0 ˣ 10-3g ml-1) for each sample. Absolute weight- average molar masses (Mw) were
calculated using the ASTRA (Version 5.1.9.1) software (Wyatt Technology, Santa
Barbara, USA), using the refractive index increment, dn/dc = 0.163 ml g-1 [148].
.
Gel permeation chromatography (GPC)
Gel permeation chromatorgraphy of some of the suitable gels were performed by Agilent
1200 series (Agilent, Germany) equipped with Quat pump (G1311A) and refractive index
detector (G1362A) using water as eluent (flow rate 1.0 cm3 min-1 at 70 C) and injection
volume of 10 L. The parameters calculated were molar mass averages (Mw, Mn, Mz),
molar masses at peak top (Mp) and volumes at peak top (Vp) and polydispersity index
(PDI). The data were analyzed by use of Chem Station GPC Data Analysis software Rev.
A.02.02 (Agilent, Germany).
Ultracentrifugation
Sedimentation velocity experiments were performed using a Beckman Instruments (Palo
Alto, USA) Optima XLI Analytical Ultracentrifuge. The polymer solutions (380 L) of
various concentrations (0.25–1.0 mg/ml), pH 6.8, phosphate buffer (400 L) were injected
into the solution and reference channels, respectively, of a double sector 12 mm optical path
length cell. Samples were centrifuged at 45000 rpm at a temperature of 20.0 C
[149]. The data were analysed by using the „„least squares, ls-g(s) model” incorporated into
the SEDFIT (Version 9.4b) program [150, 151].
50
2.2.2.12. ToF-SIMS
Dispersion of drug particles into the polymer matrix was studied by ToF-SIMS. The samples
were prepared as follows. A piece (1 × 1 cm) of the dried films of MP, LR, OB, PO husk
and seed gel were immersed in 20 mL each of 1% caffeine and 2% diclofenac sodium
solutions separately for 2 h, and the films of SP gel, AN and AM gum were immersed in the
drug solutions for 10 min as the longer immersion would result in erosion of these films.
The drug-loaded polymer films were removed from the solutions, air-dried on the polythene
sheets at room temperature for about 24 h and subjected to ToF-SIMS analysis.
Measurements were carried out by use of a ToF-SIMS Ion-TOF IV (ION-TOF GmbH,
Münster, Germany) system equipped with a Bi3+ cluster source and a single-stage reflectron
analyzer. The system was evacuated to 1 × 10-6 millibar. Spectra were acquired in positive
and negative modes by rastering a primary ion energy of 25 kV along with a pulsed target
current of approximately 1 pA and post-acceleration energy of 10 kV across the sample
surface (area 225 × 225 µm at a resolution of 225 × 225 pixels). The primary ion dose
density was maintained at <1012 ions cm-2 to ensure static conditions. Data were processed
by use of imaging software (SurfaceLab 6 Image; ION-TOF GmbH).
2.2.2.13. Mechanical strength
Mechanical strength of the polymer films (1cm × 6cm ) of SP, AN, MP, OB, LR, AM, PO
seed and husk, as prepared in section 2.2.1., were measured by Universal Testing machine
AGS-J (Shimadzu, Japan) using 1 kN force at 25 2 C.
2.2.2.14. Swelling index
51
The polymer (0.10 g) was soaked in distilled water (10 mL) and wet weights were recorded
after drying externally by use of a blotting paper, after every five min for the first hour and
every hour till a constant weight was obtained. Swelling Index was calculated by the
formula.
Swelling Index = [(Weight of wet sample –Weight of dry sample) / Weight of dry sample)]
×100
2.2.2.15. Water retention
Water retention by the polymers was determined by centrifugation method [160-162].
Accurately weighed sample (0.01 – 0.3 g) was soaked in water (about 10 mL) at 30°C) in
a petri plate for 2 h (30 min for gums). The swollen material was centrifuged at 4000 rpm
for 15 min to remove excessive water. The wet samples were dried at 105 2°C in an hotair
oven to a constant weight. Water retention was calculated by the formula.
Ww - Wd 100
Water Retention(%) Wd
where, Ww = weight of sample in wet state, Wd = weight of sample after drying at 105 C.
2.2.3. Evaluation of the isolated polysaccharides as drug carriers
Preparation of tablets
Tablets (620 mg total weight) were prepared by thoroughly mixing the drug (100 mg) with
the biopolymer (100 mg), lactose (400 mg) and magnesium stearate (20 mg); grinding by
use of laboratory grinder, sieving through 0.8 mm mesh and subjecting to direct
compression at about 116 N in a 5-mm die.
52
Preparation of dissolution media
The dissolution was studied in distilled water (for caffeine), 0.1 N HCl (for diclofenac
sodium) and pH 6.8 phosphate buffer (for diclofenac sodium) as directed by US
Pharmacopeia. For the preparation of the buffer disodium hydrogen phosphate (71.5000 g)
was dissolved in water (1000 mL). Out of this 77.3 mL was mixed with 22.7 mL of a 2.1
% citric acid solution.
Drug release study
The release study was carried out in the appropriate dissolution medium (900 mL) using
USP Paddle Dissolution apparatus II at 37±0.1°C and 50 rpm for diclofenac sodium and at
100 rpm for caffeine. Samples (2 mL) were withdrawn at 15 min, 30 min, 45 min, 60 min,
120 min, 180 min intervals, filtered, suitably diluted and assayed spectrophotometrically at
273 nm ( =9124.045) for caffeine, 275 nm ( =10181.45) for diclofenac sodium in the
buffer solution and 276 nm ( =380.084) for diclofenac sodium in 0.1N HCl. The values
were determined experimentally. The measurements were made on UV-Vis
spectrophotometer (Schimadzu, Japan). After each withdrawl an equal volume of the
dissolution medium was replaced immediately. The cumulative release (percent of the drug
amount in the tablet) was plotted against time. The data was fitted into zero order, first order
[133, 134], Higuchi [152, 153] and Hixson–Crowell cube root law models in order to
determine the release pattern. Drug release data obtained via dissolution was analyzed using
following release models to investigate the true kinetics of drug release. The release
mechanism (Fickian, non-Fickian, case-II transport) was determined by applying a
generally used equation, the so-called Power Law [154-157] as follow.
53
Mt lnkp nlnt
ln
M
where Mt/M∞ is the fraction of drug released in time t, kp is the Power Law constant
characteristic of the drug matrix system and n is the diffusion exponent. The value of n
identifies different mechanisms for drug release. For best model selection, a modified
Akaike Information Criterion called Model Selection Criterion (MSC), Eq. (9) [158], was
used.
n wi(Yobsi _ 2
i 1 Yobs ) 2p (9)
MSC ln n n
wi(Yobsi Ycali )2
i 1
where Yobsi and Ycali are the observed and calculated value of i th data point respectively, the
mean of observed data points, wi the optional weight factor, n the number of data points and
p the number of parameters. MSC is independent of the scaling of data points and the model
with largest MSC value is considered to be the most appropriate. All the calculations were
performed by use of MS Excel® 2003.
2.2.4. Evaluation as binders in tablets
The polymers under investigation were evaluated for their intended use as tablet binders.
For this purpose, 20 tablets composed of acetaminophen (10 mg), the polymer (10 mg),
lactose (80 mg) and magnesium sterate (1 mg) were mixed and ground well. The
homogeneous mixture was passed through 0.8 mm sieve and pressed into bi-planar tablets
54
(9 mm diameter) under 13.9 N mm-2 force. Hardness (crushing strength) of the tablets was
determined by use of a digital hardness tester (Curio, Pakistan). The hardness was compared
with those of similarly prepared tablets by use of microcrystalline cellulose as binder.
Disintegration time was determined by use of six tablets and water as medium under
standard conditions; the disintegration apparatus used was tester VD-2 Vision Scientific
(China).
2.2.5. Evaluation as suspending agents
Acetaminophen (50 mg mL-1) suspensions were prepared as: dextrose (7.5 g) was
dissolved in water (15 mL) with stirring to obtain a clear solution; to this citric acid
(0.125g), sodium citrate (0.125 g), the appropriate mucilage (0.125 g) from OB, MP, LR,
SP, PO seeds and husk or the gum (1.25 g) of AN, AM and AT, and acetaminophen (1.25 g)
were added under stirring in that order. The suspensions thus prepared were transferred to
50-mL graduated cylinders and the volume was made up to 25 mL with water and mixed
well. The cylinders were placed undisturbed in the dark at room temperature (25 2 C) at
a safe place. Sedimentation was recorded was recorded daily after 24 h for 90 days.
2.2.6. Evaluation as thickening agents
Thickening power of the polymers was determined in terms of viscosity at a concentration
(1%) and room temperature (25 C). The results were compared with those of
carboxymethylcellulose.
55
2.2.7. Evaluation as film coating materials
The mucilage (1.5 g) of OB, MP, LR, SP , PO seeds and husk ) or the gum, AN (24 g) and
AM (30 g), was suspended in distilled water (300 mL) and heated to about 60 C on hotplate
with constant stirring for 1-2 h to allow the polymers to swell. To this Opadry yellow (1
g), titanium oxide (5 g) and talc (9 g) were added and the mixture was heated again to 60 C
with constant stirring to get a homogenous mixture, which was used to coat the lactose
tablets (round and oval) with the help of THAI COATER® (China). The coating was
subjected to film rupture test also known as drop test.
56
3. Results and discussion
3.1. Isolation of polysaccharides
In the present study nine biopolymers, characterized to be polysaccharides, were isolated
from the plant seeds or husk, purified and characterized by use of different analytical
techniques such as FTIR, elemental analysis, thermal analysis, AFM, SEM, ToF-SIMS,
protein and sugar analysis. The materials were also evaluated for their potential applications
in pharmaceuticals as binders, suspending agent, coating agents for tablets, thickeners and
as drug releasing device.
The polymers, from colorless to light brown or dark brown, were isolated in good yield (10-
98 % on dry substance basis) as listed in Table 2. The isolations could be quickened by use
of organic solvents, such as methanol, acetone or acetic acid to coagulate the polymers
dispersed in water, but in that case residual solvents were found to be present in the product.
The presence of residual solvents in pharmaceutical adjuvants is restricted because of their
toxicity. Therefore, all the isolations were achieved without the use of any solvent. It was
noted that the drying should be carried out at temperatures lower than 40 C as the color of
the product darkens at higher temperatures. Taking into account the yields obtained the cost
of the polymers was calculated based on the current local market rates of the plant materials.
It appears that the isolated materials can produced at very low costs as
compared with the commercially available synthetic polymers like
hydroxypropylmethylcellulose (HPMC) etc.
57
3.2 Characterization
3.2.1 Elemental analysis
Average percentages of carbon and hydrogen in the isolated polymers was found to be
28.75% (Table 3) ratio of % C to % H reported in the natural polysaccharide is 7.38, these
lower values than those of natural polysaccharides may be attributed to adsorbed moisture
or the presence of uronic acids in the materials [159-161]. Average percentage of sulphur
and nitrogen is 0.14 and 0.61 which is less than 1%. Thus the absence of nitrogen proves
that these are polysaccharides.
3.2.2. Moisture content
Moisture content as determined by Karl-Fischer method ranged from 0.40% to 14.81%,
which was used for the purpose of calculations on dry substance basis and explaining the
mechanical properties.
3.2.3. FT-IR spectroscopy
The absorption bands observed in the FT-IR spectra of the polymers were assigned by
comparison with literature values [162-165]. The assignments are given in Table 4. The
characteristic bands due to (OH) at 3359 – 3463 cm-1, (C–C) in arabinosyl side chain at
1000 – 1059 cm-1, -glycosidic C-H bending at 849 – 910 cm-1, and the out-of-phase
bending of hydrogen bonded hydroxyl groups in the polymer backbone at 600 – 668 cm-1
were observed in all the polymers along with some other bands. The absence of
58
characteristic bands of proteins and ferulic acid indicates that the polymers under
investigation are free from these materials.
Table 2. Physical appearance and yields of isolated polymers
Material Yield (%) Color Cost (1kg) Remarks
SP 10 Light Brown $6.00 The colour
AN
MP
PO husk
98
12
25
Light Brown
Light Brown
White
$6.00
$9.00
$7.50
appears during
drying process
due to air
oxidation at
trace level.
AM 98 Light Brown $9.00
LR 12 Light Brown $4.50
OB 12 Light Brown $6.00
PO seeds 12 Light Brown $3.00
AT 98 White $15.0
Table 3. Elemental (% on dry substance basis) and moisture analysis data
Sample N* C H S C/N C/H Moisture
SP 0.89 19.45 2.89 0.24 21.85 6.73 7.15
AN 0.34 32.21 4.94 0.00 94.74 6.52 4.77
MP 0.78 29.72 4.62 0.22 38.12 6.43 0.40
PO Husk 1.10 28.99 4.28 0.53 26.35 6.77 8.24
AM 0.20 32.47 4.98 0.00 162.35 6.52 5.23
LR 1.56 32.54 4.72 0.09 20.85 6.89 11.96
OB 0.48 23.15 3.58 0.05 48.23 6.47 14.81
59
AT
PO Seeds
0.00
0.39
32.94
27.26
5.01
3.98
0.00
0.12
32.94
69.89
6.57
6.85
10.49
10.2
*Trace amounts of N may be found after purification
Table 4. Observed FT-IR bands and their assignments
SA 3432 2929 1618 1421 1350 1250 1074 1042 891 645, 500 2154
AN 3410 2932 1626 1460 1421 1377 1253 1037 850 600 2127, 1736
MP 3359 2920 1605 1420 1377 1246 1047 896 620, 500
POH 3400 2926 1650 1460 1420 1377 1250 1150 1000 890 600, 500 2170
AM 3422 2936 1620 1460 1421 1377 1250 1037 850 600 2120, 1736
LR 3384 2923 1648 1421 1377 1244 1153 1059, 1035 896 668, 618
OB 3368 2920 1638 1460 1422 1376 1153 1057 910 618 1720
POS 3463 2926 1655 1462 1043 880, 849 616
LR 3384 2923 1648 1421 1377 1244 1153 1059, 1035 896 668, 618
OB 3368 2920 1638 1460 1422 1376 1153 1057 910 618 1720
POS 3463 2926 1655 1462 1043 880, 849 616
51
62
3.2.4. Thermal analysis
Thermal behavior of the isolated polysaccharides was studied by TGA and DSC from ambient to
600 C. TGA of all the materials, except AT, exhibited an endothermic weight loss of 8–20% in
the 80–120 C range, which was due to the loss of trapped moisture[166-169] (Fig 11-19). The
major weight loss (18–36%) occurred in the range 225–325 C (Fig. 20a), which was due to
degradation of the polysaccharide structure. This step was associated with a wide exothermic
enthalpy change as shown in the DSC scan (Fig. 20b). The mean comprehensive index of thermal
stability (ITS) and integral procedural decomposition temperature (IPDT) values were found to be
in the range 0.33–0.43 and 213–270 C, respectively (Table 5), which are indicative of good
thermal stability of the materials. In case of AT a rapid weight loss of about 90% occurred in the
ambient – 95 C, which is due to loss of water (Fig. 20c) and 100% weight loss is due to negligible
ash in the material. The isolated polysaccharides could be classified on the basis of their thermal
behavior by use of HCA as shown in Fig. 21. It can be seen that LR and SP polysaccharides with
ITS values 0.35 and 0.33, respectively, are on the lower side and they appear to form one major
group while others form the second major group containing small groups at various similarity
levels. As the IPDT and ITS are calculated from the area under the TGA curve, the LR and SP
depicted lower values due to higher moisture contents (SA = 20%, AT = 21%) in them (Fig. 20a).
Flynn–Wall–Ozawa analysis
The apparent Ea values for major stage of decomposition were calculated by FWO method at
different conversions ( = 0.1 - 0.90 with 0.1 increment). Typical -T and FWO plots for LR are
63
Fig. 11. TGA and DSC scans of the polymer isolated from AT at a 5 C, b 10 C, c 15 C and
d 20 C
Fig. 12. TGA and DSC scans of the polymer isolated from AN at a 5 C, b 10 C, c 15 C and
d 20 C
a b
c d
a b
d c
64
Fig. 13. TGA and DSC scans of the polymer isolated from AM at a 5 C, b 10 C, c 15 C d
20 C
a b
c d
a
b
c
c
c d
c
65
Fig. 14. TGA and DSC scans of the polymer isolated from PO husk at a 5 C, b 10 C, c 15 C
and d 20 C
Fig. 15. TGA and DSC scans of the polymer isolated from PO seed at a 5 C, b 10 C, c 15 C
and d 20 C
a b
c d
a b
c d
66
Fig. 16. TGA and DSC scans of the polymer isolated from SP at a 5 C, b 10 C, c 15 C and
d 20 C
Fig. 17. TGA and DSC scans of the polymer isolated from LR at a 5 C, b 10 C, c 15 C and
d 20 C
a b
c d
a b
67
Fig. 18. TGA and DSC scans of the polymer isolated from MP at a 5 C, b 10 C, c 15 C and
d 20 C
Fig.19. TGA and DSC scans of the polymer isolated from OB at a 5 C, b 10 C, c 15 C and
d 20 C
c d
a b
c d
68
Fig. 20. a) TGA curves of the polymers under study at heating rate of 5 C min-1. MP; PO seed;
SP; AN; PO husk; AM; LR; AT; OB .
Fig. 20. b) Representative TGA, DTG and DSC curves for AT at heating rate of 5 C min-1
69
Fig. 20. c) TGA curves of AT at different heating rates
Fig. 21. Thermal classification of the polymers: Dendrogram showing similarity levels of
thermograms for the polymers
shown in Fig. 22 a and b respectively. The Ea- curves (22c) indicated the dependence of Ea on
the degree of conversion . The polysaccharides from MP, SP and PO seed showed strong
dependence of Ea on suggesting a multistep degradation pattern for these materials. The Ea
values of OB, LR and AT remained almost constant indicating that these polysaccharides may be
decomposed in one step. The Ea for PO husk, AN and AM varies with , which suggests a multistep
degradation of these materials [145]. The multistep decomposition may be attributed to the
diversity of sugar content of the material. The average activation energies are given in Table 5.
Since FWO method does not provide a direct estimate of the pre-exponential factor A, this factor
was calculated by use of the compensation effect relationship [145] according to Eq. (10).
lnA = a + bEa (10)
where a and b are the compensation parameters. This relationship suggests that any change in lnA
shall be accompanied by a corresponding change, in a linear fashion, in Ea as calculated by use of
70
Coats–Redfern equation, Eq. (11). The a and b were determined by model-fitting approach using
this equation
where T is the average experimental temperature. The g( ) models used for solving the Eq. (11) in
the present work are listed in Table 6. From the ln (g( )/T2) vs 1/T plots values of A and Ea were
determined, which were used in Eq. (10) to obtain the values of a and b.
a
b
71
Fig. 22. a) Representative –T curve for AT, b) Representative FWO plot for LR to calculate Ea.,
c) Dependence of Ea on for polysaccharides
c
Table 5. Thermal and compensation effect parameters for polysaccharides
Compensation equation
Parameters
Sample
Code
a b |r| Ea (kJ
mol-1)
InA IPDT
(oC)
ITS ΔH ΔS ΔG
AT -2.410 0.222 0.999 187.0 43.8 241 0.38 182.7 114.6 122.9
AN -2.203 0.214 0.999 157.5 35.8 254 0.40 152.8 47.6 126.1
SP -2.395 0.219 0.999 157.6 36.9 226 0.35 153.2 57.1 123.0
AM -2.414 0.218 0.999 132.6 31.3 269 0.42 128.1 10.4 122.5
MP -2.199 0.208 0.999 165.0 36.6 27 0.43 160.6 54.6 131.6
OB -2.444 0.213 0.999 164.7 37.6 261 0.41 160.2 62.7 126.0
PO
Seeds
-2.414 0.212 0.999 154.9 35.2 247 039 150.2 42.5 126.4
LR -2.343 0.223 0.999 169.6 40.2 213 0.33 165.3 84.7 121.4
PO Husk -1.437 0.212 0.999 175.4 38.7 262 0.41 170.7 71.5 130.2
*Mean Ea, IPDT and ITS value are reported from different heating rates upto 600oC. InA is calculated from mean Ea
61
74
The lnA values calculated from this equation using average FWO activation energies are listed in
Table 5. The best model was selected on the basis of: i) the correleation coefficient and ii) the
closeness of the activation energy with that determined by FWO method. Thus the first order model
(F1) was found to be the best of the ten for most of the polysaccharides. The AN, SP, AM, MP, PO
seed and PO husk polysaccharides exhibited a multistep decomposition with first order kinetics,
whereas OB, LR and AT were found to be single step decompositions. This finding supports the
general practice of using Broido method for determination of kinetic parameters of polysaccharides
where the reaction mechanism is assumed to be of first order. In case of PO husk the data also fits
well in A2 model. Similarly in case of other materials, the diffusion models D1 and D3 also provide
a good fit (Table 6). All the polysaccharides under investigation exhibited very high stability (life
time > 20 years) at 40 C, except those from PO seeds and AM (life time about 1 month), as
predicted by the model-free analysis (Fig. 23). The isocoversional method provides more accurate
values of Ea and A than the single-heating rate method. By use of this method relatively more
reliable values of S , H and G are being reported here (Table 5).
3.2.5. Electron microscopy
SEM images of the polysaccharides were used to study their morphology and surface topography.
As can be seen (Fig. 24) these polymers contain voids (a – d, f, h and i) or layers (e and g), so their
structures are suitable for dispersion of drug particles in them.
3.2.6. Atomic force microscopy
The AFM images of the polymers under investigation are shown in Fig. 25. The polymers
75
Table 6. Kinetic parameters for polysaccharides determined by model-fitting approach using Coats–Redfern equation a.
Co -de g(a)
AT AN SP AM MP OB PO seeds LR PO husk
Ea InA |r| Ea In
A |r| Ea In
A |r| Ea InA |r| Ea In
A |r| Ea InA |r| Ea InA |r| Ea In
A |r| Ea InA |r|
Power Law
P1
1/4 α
13
0.23
0.849
26
2.83
0.977
11
0.13
0.78
12
0.12
0.898
8
0.60
0.72
14
0.34
0.837
17
0.79
0.888
11
0.19
0.669
72
13.31
0.984
Power
Law P2 1/3
α 20 1.63 0.885 38 5.50 0.981 18 1.15 0.83 18 1.22 0.926 14 0.22 0.80 22 1.91 0.902 26 2.67 0.911 17 1.01 0.738 99 19.3 0.985
Power
Law P3 1/2
α 34 4.99 0.910 61 10.8 0.984 32 4.24 0.87 32 4.35 0.944 25 2.56 0.85 38 5.44 0.923 43 6.59 0.928 30 4.01 0.790 154 31.14 0.986
Power
Law P4 3/2
α 121 24.65 0.932 202 41.4 0.987 113 22.6 0.91 114 22.8 0.960 95 17.8 0.90 132 26.03 0.942 148 29.34 0.944 107 21.9 0.840 480 100.9 0.987
One dimensio -nal
diffusion
D1 2 α
164 34.25 0.935 273 56.4 0.987 153 31.5 0.91 155 31.9 0.962 129 25.2 0.90 179 36.08 0.944 201 40.48 0.946 146 30.6 0.845 643 135.5 0.987
First
order F1 -ln(1-α) 114 24.00 0.977 186 38.6 0.999 108 22.3 0.96 107 21.9 0.991 90 17.7 0.95 124 25.19 0.982 139 28.23 0.980 105 22.2 0.911 440 93.08 0.993
Avrami
Erofeyev A1 [-ln(1-α) ] 1/4 22 2.28 0.960 40 6.10 0.999 20 1.83 0.93 20 1.75 0.984 16 0.71 0.91 24 2.56 0.970 28 3.34 0.968 20 1.81 0.853 103 20.27 0.992
Avrami
Erofeyev A2 [-ln(1-α) ] 1/3
32 4.75 0.967 56 9.83 0.999 30 4.13 0.94 30 4.02 0.987 24 2.51 0.93 35 5.14 0.975 40 6.19 0.973 29 4.11 0.877 140 28.49 0.992
Avrami
Erofeyev A3 [-ln(1-α) ] 1/2
53 9.66 0.973 88 17.2 0.999 49 8.76 0.95 49 8.58 0.990 41 6.36 0.94 58 10.25 0.979 65 11.81 0.977 48 8.72 0.896 215 44.77 0.993
Three
dimensio -nal
diffusion
D3 [-ln(1-α) ] 2
1/3 210 43.11 0.966 340 69.5 0.998 197 40 0.95 197 39.7 0.985 167 32 0.94 228 45.28 0.973 255 50.56 0.971 191 39.5 0.895 797 166.6 0.993
Contracti
-ng
sphere
CS 1-(1-α) 1/3
100 19.48 0.963 166 32.9 0.997 94 17.9 0.94 94 17.7 0.983 79 13.8 0.94 109 20.57 0.970 123 23.29 0.969 91 17.6 0.886 394 81.83 0.993
Contracti -
ng cylinder CC 1-(1-α)
1/2 94 18.33 0.956 156 31.1 0.996 88 16.8 0.93 88 16.7 0.978 74 12.9 0.93 103 19.37 0.963 115 21.96 0.963 85 16.5 0.873 372 77.61 0.992
63
Fig. 23. Life time prediction of the polymers at different temperatures and 5%degree of conversions for the polymers
64
79
Fig. 24. SEM images of films of : a) OB, b) LR, c) PO seeds, d) SP, e) AN, f) MP, g) AM, h) PO
husk and i) AT
)
(i)
(i)
( a ) ( b ) ( c )
( d ) ( e ) ( f )
( g ) ( h ) ( i )
80
( b ) ( c )
( a )
( e) ( f ) ( d )
( g )
81
Fig. 25. AFM images of films of : a) SP, b) MP, c) PO seeds, d) OB, e) LR, f) AN and g) AM
appeared to consist of nanostructures. The particle size of the nanostructure varied from polymer
to polymer (Fig. 26). but the size of particles in each material was different as in AN the size
ranged from 90-110 nm, in AM it was 160-240 nm, in MP it was 120-220nm, PO seed contained
the smallest particle size of 10-70 nm, OB was 100-220 nm, LR contained a large variety of
particle size from 100-650nm and SP particle size ranged from230-320 nm. The roughness
parameters of the materials under investigation are recorded in Table 7. A nanocarpet type surface
with roughness ranging from 4.3 (AN) to 196.1 nm (LR) was observed in the AFM images of
these polymers.
3.2.7. Monosaccharide analysis by HPLC
The results of monosaccharide analysis by HPLC are given in Table 8. Monosaccharide content of
AN and PO were found to be similar to those already reported [161,170 - 171]. Based on the
monosaccharide contents the polymers were characterized as: SP, rhamnoxylan; AN,
galactoarabinan; MP, glucoxylan; PO, arabinoxylan; AM, rhanogalactoarabinan; LR,
xylogalactorhamnoarabinoglucan and OB, galactorhamnoarabinoxyloglucan.
3.2.8. Protein analysis
The method used for determination of protein produced a good (R2 = 0.986) calibration curve as
shown in Fig. 27. This curve was used for determination of protein cont of SP, AN, AM, PO seeds
82
and MP; the content of other polymers could not be determined as they were insoluble. The results
are given in Table 8. The content varied from 0.1 % to 0.6 % in AN; a similar result has
83
nm nm
Fig. 26. Nanostructure in a) AN, b) AM, c) MP, d) OB, e) PO seeds, f) LR and g) SP
0
5
10
15
20
25
30
35
90-97 98-110
0 10 20 30 40 50 60 70 80 90
a b
84
nm nm
Fig. 26. (continued) d) OB, e) PO seeds, f) LR and g) SP
Table 7. Roughness parameters of the polymers
0
5
10
15
20
25
30
nm
e
0
5
10
15
20
25
30 g
85
Material RMS
roughness
(nm)
Ave
roughness
(nm)
Mean Ht
(nm)
Median
Ht
(nm)
Peak
(nm)
Valley
(nm)
Volume
( m2)
Surface
area
( m2)
Projected
area
( m2)
AN 31.15 4.349 973.5 973.8 294.3 -973.5 24.34 29.96 25
AM 22.88 17.07 199.8 201.6 110.1 -199.8 4.995 26.49 25
MP 84.37 65.37 264 260.7 233.5 -264 6.601 26.82 25
OB 59.18 46.85 159.8 154.8 217.7 -159.8 3.996 26.70 25
PO seeds 10.18 7.424 25.21 23.36 46.26 -25.21 0.6302 25.06 25
LR 225.8 196.1 624.1 635.7 500.2 -624.1 15.60 29.96 25
SP 34.07 26.42 267.4 267 195.5 -267.4 6.686 36.59 25
86
Table 8. Monosaccharide and protein analysis
Monosaccharide content (% of total monosaccharides) Protein (%)
Sample Ara Gal Glc Xyl Rha
SP (S) - - - 100 - 0.41
SP (M) - - - 99.32 0.68
AN (S) 74.17 25.83 - - - 0.09
AN (M) 75.74 24.26 - - -
MP (S) - - 30.89 69.11 - 0.26
MP (M) - - - 100 -
PO husk (S) 23.11 - - 76.89 - -
PO husk (M) 21.37 - - 78.63 -
AM (S) 68.09 30.11 - - 1.79 0.13
AM (M) 67.88 29.99 - - 2.13
LR (S) 16.39 7.55 63.90 1.19 10.97 -
LR (M) 29.14 1.28 - - 69.59
OB (S) 9.82 5.59 55.84 19.10 9.66 -
OB (M) 20.39 11.67 21.35 23.31 23.27
PO seeds (S) 21.90 - - 78.10 - 0.34
PO seeds (M) 18.99 - - 81.01 -
AT(S) - 58.12 - - 41.88 -
AT(M) - 55.92 - - 44.08 -
Fig. 27. Calibration curve for protein analysis
87
been reported earlier [170]. It can be seen that these polymers do not contain significant amounts
of proteins (0.09 – 0.41 %), therefore, they can be categorized as pure polysaccharides.
3.2.9. NMR study
AN and AM, could be characterized by NMR analysis in this work. 1HNMR spectra were in D2O
and the 13CNMR spectra were recorded in solid state. The 1HNMR spectra were complex and
proton splitting patterns were not obvious. Therefore, the assignments were made by comparing the
spectra with those reported for similar materials [86, 172-177]. In the 13CNMR spectra two major
absorptions, AN/AM: = 100.5/103.5 ppm due to C-1 of branched pyranose Gal (Galp) and =
109.6/109.6 ppm due to C-1 of furanose Ara (Araf) of the main chain [86, 172] were observed in
the anomeric region (Table 9, Fig.28). In the spectrum of AM a small signal at = 98.6 ppm due
to C-1 of branched Rhap, present in very small amount (<2%), was also observed. The resonances
of the carbons in glycosidic linkages were observed at =
109.6 ppm (C-1 of 1,5-linked Araf), 100-103.5 ppm (C-1 of 1,3- linked Galp), 80.5 ppm (C-3 of 3-
linked Galp), 82 ppm (C-2 of 2-linked Araf) and 65.1 ppm (C-5 of 5- linked Araf). The other signals
at = 175 and 17.1 ppm were due to C-6 of Galp and Rhap residues. Based on these observations
the polymers were characterized as branched structures.
The 1HNMR spectra are shown in Fig. 29 and 30. In these spectra multiplets due to H1-5 (Araf), and
H1-6 (Galp) were observed at = 5-5.5 ppm. The anomeric proton signals were well resolved and
appeared at = 5.27 ppm due to H-1 of Rhap, = 5.16 ppm due to H-1 of Araf, = 5.05 ppm
Table 9. 13C and 1H NMR data of AN and AM
88
Glycosyl
residue
Chemical shift /ppm
C1/H1 C2/H2 C3/H3 C4/H4 C5/H5 C6/H6
L-Araf 109.6 82 73.0 74.5 65.1
5.16 4.4 4.1 4.2 3.7
-D-Galp 103.5(AM)
100.5 (AN)
68.5 80.5 78.0 76.6 175.6 (AM)
178.1(AN)
5.05 4.05 4.10 4.20 4.17
Fig. 28. 13C NMR of AN and AM
89
Fig. 29. 1H spectrum of AN having several sharp lines
Fig. 30. HSQC plots showing superposition for AN (red) and AM ( blue)
90
due to H-1 of Galp and = 4.40 ppm due to H-2 of Araf (Table 9). The CH3 (on C-6 of Rhap)
signal was observed at = 1.19 ppm.
The assignments of two dimensional 13C-1H NMR (HSQC) spectra (Fig. 30) of AN and AM
polysaccharide are given in Table 9. The HSQC plots showed that each cross peak has coordinates
corresponding to the respective chemical shift of a 13C and its directly bonded proton.
The anomeric protons resonating at = 5.16, 5.05 and 5.27 ppm correlated with carbon signals at
= 109.6 (AN and AM), 100.5 (AN), 103.5 (AM) and 99.5 ppm (AN and AM). These chemical shifts
are characteristic of anomeric carbons of Araf, Galp and Rhap residues [173]. The two broad proton
signals at = 5.05 and 4.49 ppm correlated with the anomeric carbon shifts at = 100.5 (AN) and
103.5 ppm (AM) due to C-1 of Galp residues. The cross peaks in the high magnetic field at = 1.19
(CH3) and at = 17.43 (CH3) confirmed the presence of Rhap units in the polysaccharide [173].
The 13C signals with very low intensities at = 17.1 ppm (CH3 on Rhap) and 175 in AM and 178
ppm in AN (COOH on GalA) were also observed. t appears that a small amount of the H2OH on
C-5 of Galp has been oxidized to COOH [86]. The peak at =
17.1 ppm also corresponds with the monosaccharide analysis (Table 8), where Rhap is present in
AM (2%) and absent in AN.
Appearance of 13C signals due to C-1 and C-5 in Araf at relatively higher values than expected
for the monosaccharide suggests an -(1,5) linkage of L-arabinose in the main chain [176].
Similarly the appearance of peaks at = 100.5 (AN) and 103.5 (AM) due to C-1 of Galp and at 80.5
ppm for C-3 of Galp suggest a -(1,3) linkage of D-galactose in the side chain. At few points
arabinose appears to be connected at C-2 of Araf (Fig. 31).
Fig. 31. Structure suggested on the basis of NMR and literature 86, 172-177.
76
93
3.2.10. Rheology
Rheology is the study of flow and deformation of a material. Rheology study is an important aspect
in characterization of polymers. Polysaccharides behave as flexible coils in dilute solution [178].
The process of coating different materials, such as pharmaceutical tablets, with polymers is
dependent on viscosity and elasticity of the polymer. Therefore, it was relevant per se to study
rheology of the polysaccharides under investigation with a view to assess their potential as
filmcoating, viscosity enhancing and suspending agents.
The polymers were subjected to rheological measurement, at different concentrations and pH (Table
10), in shear rate region of 0.01 to 1000 s-1. AT could not be studied because it did not form a
homogeneous solution required for the study. The rheograms are shown in Fig.32. AN and AM
exhibited Newtonian flow, whereas other materials showed non-Newtonian behavior. In case of SP,
PO seeds, PO husk, OB, LR, MP no significant change in structure was observed as indicated by
the repetition of the reverse rheogram on the same line.
The viscosity decreased with an increase in shear rate. A cursory view of the viscosity data at 1%
concentration level and shear rate 10 s-1 (Table 10) shows that PO husk possesses the highest
viscosity and AN the lowest. It can be seen that the viscosity of PO husk is about two times that
produced by PO seed, whereas the latter resembles LR in this respect. The trend in viscosity was
found to be: PO husk > LR > POseeds > SP > AM > MP > OB > AN. It appears that AN and AM
polymers can be used for applications where Newtonian flow is required.
94
3.2.11. Determination of molar mass
Three different techniques, including intrinsic viscosity data, size exclusion chromatography and Table 10.
Concentration (%) and pH of polymer solutions used for rheological studies at 24 C
Name of sample Concentration(%)
pH of
solutions
polymer Viscosity of 1%
solution at shear rate
10 s-1
SP 1.15 7.04 0.017
AN
25.9
4.41 0.002
MP 1.16 6.63 0.004
PO husk
0.86 6.68 0.16
AM
24.15
4.29 0.005
LR 0.19
5.16 0.079
OB 0.29
6.78 0.003
PO seed 1.7299
6.03 0.075
95
Fig. 32. Graph of shear rate vs viscosity
ultracentrifugation, were employed to determine the molar mass of the polymers under
investigation. AN and AM being water soluble were analyzed by all the three techniques, whereas
PO husk and SP could be analyzed only by size exclusion chromatography. The molar mass of LR
(3.65×106 g/mole) is reported in literature [61] whereas other materials under study, being insoluble
in common solvents, could not be analyzed.
Calculation of molar mass from rheology data by Mark-Houwick equation involved step-wise
calculation using ɳ (from reduced and inherent viscosity plots against concentration (Fig. 33)), K
and a parameters (from SEC-MALS data). The results are given in Tables 11 and 12.
The average molar masses of the polymers under investigation ranged from 9.28 × 105 to 3.92 × 106
Daltons (Table 11(b)). The molar masses of AN and AM as determined from rheology data and
SEC-MALS were found to be similar. The mass of AN was comparable with that already reported
[179]. The most abundant high molar masses were 1.31 × 106 (AN) and 1.22 × 106
96
Daltons (AM). Shapes of AN and AM as determined by viscosity data (Fig. 34 (a) and (b)) by Ellipse
1 software [180] resembled those observed physically. This validates all the viscosity
measurements.
Different fractions of AN and AM having distinct molar masses were fractionated by
ultracentrifugation of various concentrations of the polymers. The results are given in Table 11. It
can be seen that with dilution fragmentation increases. As the branched chains are usually more
vulnerable to hydrolysis these results suggest that the polymers are branched in a complex manner.
The most abundant mass found was 6.2 × 105 Dalton from AN (96%) and AM (97.5%), which is
relatively lower than those determined by rheology data and SEC-MALS. This result suggests slight
polydispersity of the polymers. GPC analysis showed three polymeric
Fig. 33. Reduced and inherent viscosity plots against concentration of a) AN and b) AM in water at
250C
a
b
97
Table 11(a). Viscosities of AN and AM
AN
C gcm-3 [Ƞ]Pa.s Ƞr Ƞsp Ƞsp/c lnȠr lnȠr/c
0.14 0.0076 7.58 6.58 47 2.0255 14.4679
0.07 0.00303 3.024 2.024 28.9143 1.1065 15.8071
0.04 0.00175 1.746 0.746 18.65 0.5576 13.94
0.018 0.00132 1.317 0.317 17.6111 0.2756 15.3111
AM
0.28 0.278 277.44 276.44 987.286 5.6256 20.0914
0.14 0.0326 32.53 31.53 225.214 3.48216 17.4108
0.07 0.00904 9.022 8.022 114.6 2.19967 21.9967
0.04 0.00409 4.082 3.082 77.05 1.40659 58.0412
Table 11(b). Comparative molar masses
K
a
M = ([ ]/K)1/a
M (from SEC-MALS)
Most abundant
species
Average of most
abundant and high
molecular-mass
species
AN 2.709 10-2 0.462 9.06 × 105 9.28 × 105 1.31 × 106
AM 6.038 10-6 1.059 3.92 × 106 1.20 × 106 1.22 × 106
Table 12. Molar masses of different fractions from ultracentifugation
Conc. Mr(% of all fractions)
(% m/v) AN AM
1.00 6.2 × 105 (96), 2.84 × 106 (4) 6.24 × 105 (97.6), 2.84 × 106 (2.4)
0.50 1.30 × 106 (93.7), 3.75 × 106 1.30× 106 (94.1), 3.75 × 106 (2.7),
(2.9), 4.82 × 106 (3.4) 4.82× 106 (3.2)
98
0.25 9.64 × 104 (1.9), 5.72 × 105 9.64 × 104 (1.8), 5.72 × 105 (24), 8.32
(27.1), 8.32 × 105 (17.7), 1.04 × × 105 (16.8), 1.04 × 106 (16.9), 1.37 × 106
(17.9), 1.37 × 106 (17.7), 106 (16.8), 1.74 × 106 (9.3), 2.31 × 106
1.74× 106 (9.8), 2.31× 106 (15.2) (15.1)
a- b-
Fig. 34. Shapes of a) AN and b) AM as determined by Eclipse I (software) components in the isolated
fraction (Table 13a) with weight-average molar masses 9.3544 x 106 g mol-1 (fraction 1), 5.0087 x 101 g mol-
1 (fraction 2) and 1.2671 ˣ 103 g mol-1 (fraction 3). This result suggests the presence of three distinct
polysaccharides in the water-extracted gel of PO husk as reported earlier [181-183]. The mass of fraction I
is in the characteristic range of the arabinoxylan of the hull-less barley [161]. For an ideal monodisperse
polymer, the molar mass averages are equal i.e. Mn=Mw=Mz. However, for a polydispersed system the
relationship is Mn<Mw<Mz. The fraction I , 2 and 3 with PDI values of 1.20, 1.35 and1.16, respectively,
appear to be almost monodispersed polymers.
GPC analysis of SP (Table 13b) showed four polymeric components in the isolated fraction with
weight-average molar masses 7.0496 ˣ 106 g mol-1 (fraction 1), 4.7331 ˣ 101 g mol-1 (fraction 2),
1.0862 ˣ 103 g mol-1 (fraction 3) and 9.1631 ˣ 103 g mol-1 (fraction 4). This result suggests the
presence of four distinct polysaccharides in the water-extracted gel of SP. The fraction I, 2, 3 and
99
4 with PDI values of 1.18, 1.57, 1.13 and 1.28, respectively, appear to be almost monodispersed
polymers.
3.2.12. Mechanical strength
Mechanical strength is an important parameter to be determined for film forming polymers due to
their potential application in film coating of tablets and as biocompatible and biodegradable
packaging material for food items. All the polysaccharides under investigation were found to be
capable of forming strong films. The results are given in Table 14 and Fig. 35. These materials
exhibited diverse strengths ranging from 0.47 to 19.68 Nmm-2, which reflects a diversity in their
structures. Three of the materials, LR, PO seeds and husk showed higher
Table 13a. GPC data of the peak of higher molar mass for the PO husk
Parameters Fraction 1 Fraction 2 Fraction 3
Mn 7.7959 ˣ 106 3.7394 ˣ 101 1.0928 ˣ 103
Mw 9.3544 ˣ 106 5.0087 ˣ 101 1.2671 ˣ 103
Mz 1.0946 ˣ 107 6.2953 ˣ 101 1.4601 ˣ 103
Mp 9.5387 ˣ 106 4.2629 ˣ 101 1.1509 ˣ 103
Vp 1.5077 ˣ 101 9.7632 8.2798
Table 13b. GPC data of the peak of higher molar mass for the SP
Parameters Fraction 1 Fraction 2 Fraction 3 Fraction 4
Mn 5.9822 ˣ 106 3.0450 ˣ 101 9.6436 ˣ 102 7.1549 ˣ 103
Mw 7.0496 ˣ 106 4.7331 ˣ 101 1.0862 ˣ 103 9.1631 ˣ 103
100
Mz 8.1507 ˣ 106 6.4473 ˣ 101 1.2107 ˣ 103 1.1470 ˣ 103
Mp 6.9195 ˣ 106 4.2629 ˣ 101 1.1144 ˣ 103 7.2444 ˣ 103
Vp 1.5422 ˣ 101 9.7632 8.2943 7.4518
Table 14. Mechanical strength
Material
Thickness(mm)
Width(mm)
Max.force N
Tensile
strength
N/mm2
SP 0.24 15.17 12.58 3.45
AN 0.25 11.78 10.00 3.40
MP 0.10 16.65 6.075 3.66
PO husk 0.07 14.15 12.12 12.24
AM 0.22 12.46 16.38 5.98
LR 0.15 9.15 27.35 19.68
OB 0.15 15.19 0.825 0.47
PO Seeds 0.15 16.18 39.38 16.61
101
Fig. 35. Mechanical strength of SP, AN, MP, PO husk, AM, LR, OB and PO seeds. strengths than carboxy
methyl cellulose (~11 Nmm-2) [184, 185], gelatine (~6 Nmm-2) [184] and hydroxyl propyl cellulose (~14
Nmm-2) [185] , whereas the value for AM was comparable with that of gelatin. SP, AN and MP exhibited
similar moderate strengths. The overall trend was recorded as: LR > PO seeds > PO husk > AM > MP > SP
> AN > OB.
AN SP MP
PO husk AM LR
OB PO seeds
102
3.2.13 Swelling index
The swelling index of the polymers ranged from4.32% (AT) to 40.49% (PO husk) table 15. The
high swelling characteristics of these materials make them good candidates for fabrication of
delivery devices. From these polymers release of drug can be controlled by the water content and
pore size. For rapid drug release high water content and large pore size may be used [186].
3.2.14. Water retention
The results (Table 15) indicate that MP possesses the greatest capacity to hold water with an average
retention of 79% whereas in case of other materials the water retention value was in the range 4
- 48.8%. SP and AM dissolved in water, so their values could not be determined reproducibly. Thus
MP, PO and OB having very high to moderately high values can be considered as suitable materials
for formulation of ophthalmic solutions or suspensions.
3.3 Evaluation of polysaccharides as drug carriers
The polymers under investigation were evaluated for their potential as drug carriers. In this regard
the drug-loaded polymer films and synthetic matrix-tablets were subjected to electron microscopy,
ToF-SIMS and dissolution studies, the results are discussed as follows.
Table 15. Swelling index and water retention value
Sample code
Swelling
Index(%)
WRV(%)
SP Dissolved Dissolved
AN 14.4 14.88
MP 37.5 79.45
PO husk 40.49 48.83
AM Dissolved Dissolved
103
LR 16.5 29.5
OB 30.33 30.44
PO seeds 17.20 41.35
TG 4.32 4.32
3.3.1. Electron microscopy
SEM is a useful technique to study drug loading. SEM images (Fig. 36 - 44) shows that
polysaccharides under study had voids and layered structures, therefore are suitable for
encapsulation of drugs molecules. SEM images provided clear evidence of the presence of drug
substances in the polymer matrices.
104
3.3.2. ToF-SIMS
ToF-SIMS is a powerful technique for surface analysis with the potential of depth profiling [187]
and mapping of encapsulated substances in polymeric materials. In this work this technique has
been successfully employed to study drug loading and distribution in the polymers under
investigation. This technique provided important information on molecular specificity with good
sensitivity and lateral resolution [188-192].
Some of these polymers have already been studied for formulation of sustained release tablets of
some drug molecules [193-195] but these studies lack the verification of uniformity of content
therein, which is an essential requirement for mass production of a pharmaceutical product.
ToFSIMS spectra and images were obtained in respect of caffeine and diclofenac loaded polymers
under investigation. The spectra of the drugs, polymers (blank) and drug-loaded polymers are
shown in Fig. 46. The m/z peaks at 22.9932, 39.0225 and 195.09 due to Na+,C3H3+ and C8H11O2N4
+
, respectively were considered as signatures of caffeine. Similarly, the peaks at 22.9932, 39.0225
and 339.92 due to Na+, C3H3+ and C14H10Cl2NO2Na2
+respectively (Fig. 45) were considered as
signatures of diclofenac sodium. The results showed a uniform dispersion of
105
a- a-
a-
Fig. 36. SEM images of OB a) without drug, b) with CAF and c with DS
Fig. 37. SEM images of LR a) without drug, b) with CAF and c with DS
Fig. 38. SEM images of PO seeds a) without drug, b) with CAF and c with DS
b - c -
b - c -
b - c -
106
a- a-
Fig. 39. SEM images of SP a) without drug, b) with CAF and c with DS
Fig. 40. SEM images of AN a) without drug, b) with CAF and c with DS
a-
Fig. 41. SEM images of MP a) without drug, b) with CAF and c with DS
b - c -
b - c -
b - c -
107
a- a-
a-
Fig. 42. SEM images of AM a) without drug, b) with CAF and c with DS
Fig. 43. SEM images of PO husk a) without drug b) with CAF c with DS
Fig. 44. SEM images of AT a) without drug b) with CAF c with DS
b - c -
b - c -
b - c -
108
Fig. 45. Mass spectra (TOF-SIMS) of diclofenac sodium and caffeine
caffeine particles in the polymer matrix of SP, AN, AM, MP, PO seeds and husk (Fig. 46), while the
dispersion was relatively less uniform in LR and OB. In SP and AM diclofenac sodium dispersed
109
more uniformly than others. On the other hand the pattern of drug uptake was different in all the
polymers (Fig. 47.). This appears to depend upon solubility and hydrophilicity of the drug
molecules, and the polymer‟s structure. n the present list the best uptake was shown by OB for
both the drugs.
3.3.3. Dissolution study
It can be seen that there is no derth of drug substances available in the market. A number of drug
molecules are available for a treatment. The research in discovery of new molecules has reached a
level of saturation in some indications. There are drugs with excellent efficacy but these are
generally associated with several adverse effects. It is therefore, now being felt that it is more
desirable to have drugs with lower toxicity profiles. One way to reduce the toxic side effects is to
protect the body from over exposure of drugs by way of targeted delivery or controlled release.
Therefore, the focus is now shifting from synthesis of new drug entities to the targeted or controlled
delivery of existing drug substances.
Currently, most of the targeted or controlled drug delivery systems involves the use of synthetic
polymers as the matrix for drug release. Synthetic polymers release toxic degradation products in
vivo. So, the synthetic polymers are being discouraged for their use in drug delivery. The best
alternative being looked into is the potential use of natural polymeric materials for these
applications. Preliminary studies on the natural polymers which are carbohydrate polymers
obtained from plant material, under investigation suggested them to be good candidate for drug
110
111
Fig. 46. a) TOF-SIMS of caffeine loaded samples
112
113
Fig. 46. b) TOF-SIMS of diclofenac sodium loaded samples
114
Fig. 47. Uptake of caffeine by different materials
Fig. 48. Uptake of diclofenac sodium by different materials encapsulation and delivery [195].
In the present work two different formulations (drug-load films and matrix tablets) were prepared
and their release was studied by the USP dissolution methods. The drug-loaded polymers would
swell when in contact with body fluids and deliver the encapsulated drug in a controlled manner.
115
The release mechanism depends on the polymer structure and nature of drug molecule. In order to
study the kinetics and mechanism of release different models were applied. Drug release was
studied from the drug-loaded films and direct-compressed tablets containing a polymer as an
adjuvant. The results are discussed as follows.
3.3.3.1. Release profile of diclofenac sodium loaded polymer films in phosphate buffer
Mathematical models describe the release of drug as a function of time. A number of models have
been put forward to explain the release mechanism of the drugs from swellable systems. However,
none of the methods is successful enough to explain the release mechanism from all types of
systems. In the present study release profile of diclofenac sodium drug from prepared films of SP,
AN, MP, PO husk, AM, LR, OB and PO seeds was studied. The release profiles of diclofenac
sodium-loaded polymer films are shown in Fig. 49. and Table 16. As compared with the solubility
curve of naked drugs the polymers produced sustained release up to about 30 h. Drug release study
of these polymers were carried out in phosphate buffer of pH 6.8. Release data was fitted into
equations: M=k0 t (Zero order equation), lnM = k1 t (First order equation), M = kH t1/2 (Higuchi
equation), Mo1/3 – Mt
1/3 = kHC t (Hixon-Crowell cube root law) and lnMt /M = Inkp + nInt (Power
law equation). The R2value, MSC and n values for different models are recorded in
Table 16. For diclofenac sodium films MP (Fig. 53), OB (Fig. 55) and PO husk (Fig. 56) followed Higuchi
model, AM (Fig.51), AN (Fig.50) and SP (Fig.57) followed Power law, LR (Fig.54) followed first order and
PO seeds (Fig.52) followed zero order. As far as release mechanisms are concerned, AM, AN, MP, LR, OB,
SP showed non-Fickian, i. e., diffusion and swelling controlled and PO seeds and husk exhibited complex
mechanism involving diffusion, swelling and erosion,
116
The suggested mechanism was based on the n value according to the criteria: 0.45 (Fickian), 0.45
< n < 0.89 (non-Fickian) and n > 0.89 (super case-II). Thus these polymers appear to be suitable for
formulation of various types of ophthalmic solutions or suspensions.
3.3.3.2 Release profile of diclofenac sodium loaded polymer films in 0.1 N HCl
The films of diclofenac sodium drug prepared from SP, AN, MP, PO husk, AM, LR, OB and PO
seeds polysaccharides showed no release in 0.1 N HCl. The Absorbance spectra of DS-polymer
films in 0.1M HCl are shown in Fig. 58.
3.3.3.3 Release profile of caffeine loaded polymer films in distilled water
The release profiles of caffeine-loaded polymer films are shown in Fig. 59. As compared with the
solubility curve of naked drugs the polymers produced sustained release for about 30 h. The release
data of all the polymers (SP (Fig. 66), AN (Fig. 60), MP (Fig. 62), PO husk (Fig. 65), AM (Fig. 61),
LR (Fig. 63),OB (Fig. 64) and PO seeds (Fig. 67)) for caffeine fitted well in Higuchi model followed
by Power law (Table 16). Best linearity was found in Higuchi equation for all the polymers (Table
17) indicating the release of drug from matrix as a square root of time dependent process. However,
first order model gave best fit release model for MP (Fig. 62, Table 17). As far as release
mechanisms are concerned, they were: non-Fickian, i. e., diffusion and swelling controlled (AM,
AN, MP, PO husk, SP for caffeine) and complex mechanism involving diffusion, swelling and
erosion (LR, OB for caffeine). Whereas PO seeds exhibited nearly Fickian, i. e., only diffusion
controlled mechanism for caffeine. The suggested mechanism was based on the n value according
to the criteria: 0.45 (Fickian), 0.45 < n < 0.89 (non-Fickian) and n > 0.89 (super caseII). Thus these
117
polymers also appear to be suitable for formulation of various types of ophthalmic solutions or
suspensions.
118
min
Fig. 49. Release profiles of the polymer films in phosphate buffer pH 6.8 (DS)
Table 16. Fitness of release data of diclofenac sodium in phosphate buffer from different films to various mathematical models
Material/Model AM AN PO seeds MP LR OB PO husk SP
Zero order R2 0.733 0.761 0.783 0.899 0.623 0.92 0.852 0.860
MSC 1.014 1.125 3.444 1.985 0.6689 2.126 1.605 1.659
First order R2 0.909 0.918 0.858 0.976 0.818 0.953 0.949 0.961
MSC 2.093 2.204 1.553 3.429 2.563 2.674 2.682 2.943
Higuchi R2 0.908 0.930 0.882 0.993 0.824 0.980 0.973 0.980
MSC 2.083 0.396 1.739 4.666 1.432 3.547 5.017 3.640
Power law R2 0.905 0.954 0.860 0.955 0.884 0.959 0.995 0.987
MSC 2.329 2.790 1.567 2.809 1.849 2.798 4.989 4.105
n 0.621 0.484 0.381 0.630 0.494 0.451 0.259 0.472
Hixon
crowell
R2
MSC
0.733
1.014
0.761
1.125
0.783
1.128
0.899
1.985
0.623
0.669
0.92
2.126
0.852
1.605
0.860
1.389
% release
(t min50)
360 360 300 920 180 420 420 720
102
121
First order
Higuchi model
t 1/2
0 500 1000 1500 2000
t
Fig. 50. Typical model fitting plots for AN-diclofenac sodium film in phosphate buffer of (pH 6.8)
at 37±0.1°C
y = 0.4848x - 3.628 R² = 0.9548
-3
-2.5
-2
-1.5
-1
-0.5
0
0.5
0 5 10
In t
Power law
y = 1E - 07 x + 8E - 05 R² = 0.7613
0
0.00005
0.0001
0.00015
0.0002
0.00025
0.0003
0 500 1000 1500 2000
t ) min (
Zero order
y = - 0.0008 x - 8.3421 R² = 0.9188
-12
-10
-8
-6
-4
-2
0
0 1000 2000
t
y = 1.8598x + 9.0628 R² = 0.9305
0
20
40
60
80
100
0 50
y = 4E - 08 x + 3E - 05 R² = 0.7613
0
0.00002
0.00004
0.00006
0.00008
0.0001 Hixson - crowell model
122
0
1000 2000 t (min)
First order
Higuchi model
t t 1/2
0 1000 2000 t
Fig. 51. Typical model fitting plots for AM-diclofenac sodium film in phosphate buffer of (pH
6.8) at 37±0.1°C
Power law Zero order
y = 0.6214x - 4.4896 R² = 0.9054
-4
-3
-2
-1
0
1
0 5 10
In t
Power law
y = 1E - 07 x + 7E - 05 R² = 0.7333
0
0.00005
0.0001
0.00015
0.0002
0.00025
0.0003 Zero order
y = - x 0.0008 - 8.3125 R² = 0.9094
-12
-10
-8
-6
-4
-2
0
0 1000 2000
y = 1.9495x + 5.8645 R² = 0.9084
0
20
40
60
80
100
0 20 40 60
y = - 4 E - 08 x + 8E - 05 R² = 0.7333
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012 Hixson - crowell model
123
In t t (min)
t
t 1/2
Hixson-crowell model
0 500
t
Fig. 52. Typical model fitting plots for PO seeds-diclofenac sodium film in phosphate buffer of (pH
6.8) at 37±0.1°C
Power law 0.0003 Zero order
y = 0.3811x - 2.8107 R² = 0.8601
-2.5
-2
-1.5
-1
-0.5
0
0 5 10
y = 3E - 07 x + 8E - 05 R² = 0.7831
0
0.00005
0.0001
0.00015
0.0002
0 200 400 600
y = - 0.0014 x - 8.3457 R² = 0.8581
-9
-8.8
-8.6
-8.4
-8.2
-8
0 2 00 400 600
First order
y = 2.1602x + 13.242 R² = 0.8822
0
10
20
30
40
50
60
70
0 20 40
Higuchi model
y = 9E - 08 x + 3E - 05 R² = 0.7831
0
0.00001
0.00002
0.00003
0.00004
0.00005
0.00006
0.00007
124
In t
0 1000 2000
t
t 1/2
Hixson-crowell model
0 1000 2000
t
Fig. 53. Typical model fitting plots for MP-diclofenac sodium film in phosphate buffer of (pH
6.8) at 37±0.1°C
y = 0.6309x - 4.869 R² = 0.9557 -4
-3
-2
-1
0
0 5 10
y = 1E - 07 x + 4E - 05 R² = 0.899
0
0.00005
0.0001
0.00015
0.0002
0.00025
t ) min (
y = - 0.0006 x - 8.1865 R² = 0.9762
-9.4
-9.2
-9
-8.8
-8.6
-8.4
-8.2
-8
0 1000 2000
First order
y = 1.7288x - 0.9928 R² = 0.9931
0
10
20
30
40
50
60
70
80
0 20 40 60
Higuchi model
y = 4E - 08 x + 1E - 05 R² = 0.899
0
0.00002
0.00004
0.00006
0.00008
0.0001
125
t (min)
t
0.0001 Hixson-crowell model
0 1000 2000
t
Fig. 54. Typical model fitting plots for LR-diclofenac sodium film in phosphate buffer of (pH 6.8)
at 37±0.1°C
y = 0.4948x - 3.6037 R² = 0.8843 -3
-2
-1
0
1
0 5 10
In t
Power law
y = 3E - 08 x + 3E - 05 R² = 0.6234
0
0.00002
0.00004
0.00006
0.00008
y = 1E - 07 x + 1E - 04 R² = 0.6234
0
0.00005
0.0001
0.00015
0.0002
0.00025
0.0003
0 1000 2000
Zero order
y = 1.7743x + 14.203 R² = 0.8244
0
20
40
60
80
100
0 20 40 60
t 1 / 2
Higuchi model
y = - 0.0007 x - 8.4353 R² = 0.8186
-12
-10
-8
-6
-4
-2
0
0 1000 2000
First order
126
t
y = 3E - 07 x + 5E - 05 R² = 0.92
0
0.00005
0.0001
0.00015
0.0002
0 200 400 600
t ( min )
Zero order
y = - 0.0011 x - 8.2183 R² = 0.9538 -8.8
-8.7
-8.6
-8.5
-8.4
-8.3
-8.2
-8.1
0 200 4 00 600
First order
y = 2.041x + 4.3795 R² = 0.9807
0
10
20
30
40
50
0 10 20 30 t / 1 2
Higuchi model
y = 0.4515x - 3.4728 R² = 0.9592
-3
-2.5
-2
-1.5
-1
-0.5
0
0 5 10
In t
Power law
127
t
Fig. 55. Typical model fitting plots for OB-diclofenac sodium film in phosphate buffer of (pH
6.8) at 37±0.1°C
Power
law Zero order
In t t (min)
t
t 1/2
Hixson-crowell model
y = 8E - 08 x + 2E - 05 R² = 0.92
0
0.00001
0.00002
0.00003
0.00004
0.00005
0.00006
0 200 400 600
Hixson - crowell model
y = 0.2598x - 2.2489 R² = 0.995 -2
-1.5
-1
-0.5
0
0 5 10
y = 8E - 08 x + 0.0001 R² = 0.8522
0
0.00005
0.0001
0.00015
0.0002
0.00025
0.0003
0 1000 2000
y = - 0.0006 x - 8.4372 R² = 0.9497
-9.6
-9.4
-9.2
-9
-8.8
-8.6
-8.4
-8.2
0 1000 2000
First order
y = 1.3345x + 20.843 R² = 0.9732
0
20
40
60
80
100
0 20 40 60
Higuchi model
128
0 1000 2000
t
Fig. 56. Typical model fitting plots for PO husk-diclofenac sodium film in phosphate buffer of
(pH 6.8) at 37±0.1°C
Power law Zero order
In t
0
1000
2000
t (min)
t 0 20 t 1/2 40 60
y = 3E - 08 x + 3E - 05 R² = 0.8522
0
0.00002
0.00004
0.00006
0.00008
0.0001
y = 0.4723x - 3.7275 R² = 0.9879
-3
-2.5
-2
-1.5
-1
-0.5
0
0 5 10
y = 1E - 07 x + 6E - 05 R² = 0.8601
0
0.00005
0.0001
0.00015
0.0002
0.00025
0.0003
y = 1.7172x + 5.093 R² = 0.9807
0
20
40
60
80
100 Higuchi model
y = - 0.0007 x - 8.262 R² = 0.9613
-10
-9.5
-9
-8.5
-8
0 1000 2000
First order
129
Hixson-crowell model
0 1000 2000
t
Fig. 57. Typical model fitting plots for SP-diclofenac sodium film in phosphate buffer of (pH 6.8)
at 37±0.1°C
Fig. 58. Release profiles of DS-polymer films in 0.1M HCl
y = 4E - 08 x + 2E - 05 R² = 0.8601
0
0.00002
0.00004
0.00006
0.00008
0.0001
130
Fig. 59. Release profiles of the polymer films in distilled water (caffeine)
Table 17. Fitness of release data of caffeine in distilled water from different films to various mathematical models
Material/Model AM AN PO seeds MP LR OB PO husk SP
Zero order R2 0.950 0.945 0.931 0.954 0.982 0.958 0.903 0.970
MSC 2.695 2.599 1.362 2.771 3.712 3.347 2.032 3.221
First order R2 0.989 0.988 0.983 0.986 0.942 0.957 0.975 0.970
MSC 4.229 4.18 3.780 3.972 3.558 2.853 3.406 3.222
Higuchi R2 0.996 0.997 0.993 0.985 0.984 0.991 0.982 0.992
MSC 6.136 5.677 4.658 3.894 3.836 4.435 4.790 4.599
Power law R2 0.997 0.995 0.991 0.974 0.964 0.988 0.979 0.983
MSC 6.111 5.188 4.418 3.343 3.030 4.186 3.560 3.819
n 0.496 0.550 0.425 0.530 0.363 0.372 0.482 0.694
Hixon
crowell
R2
MSC
0.950
2.694
0.945
2.599
0.931
2.374
0.954
2.771
0.982
3.712
0.958
2.869
0.903
2.032
0.970
3.221
% release (t min50) 920 1080 920 1120 680 680 720 740
112
133
y = 0.5503x - 4.3922 R² = 0.9959
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
0 5 10
In t
Power law
y = 2E - 07 x + 7E - 05 R² = 0.9454
0
0.0001
0.0002
0.0003
0.0004
0.0005
0 1000 2000
t ) min (
Zero order
y = - x 0.0007 - 7.5738 R² = 0.9889
-9
-8.8
-8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4 0 1000 2000
t
First order
y = 1.7713x - 1.6602 R² = 0.9975
0
10
20
30
40
50
60
70
80
0 20 40 60
t 1 / 2
Higuchi model
y = 7E - 08 x + 2E - 05 R² = 0.9454
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
0.00014
0.00016
0 1000 2000
t
Hixson - crowell model
0
0
134
Fig. 60. Typical model fitting plots for AN-caffeine film in distilled water at 37±0.1°C.
Power law Zero order
t (min)
First order Higuchi model
t
t 1/2
Hixson-crowell model
0.00016
y = 0.4967x - 4.1071 R² = 0.9978
-3
-2.5
-2
-1.5
-1
-0.5 5 10
In t
y = 2E - 07 x + 8E - 05 R² = 0.9503
0
0.0001
0.0002
0.0003
0.0004
0.0005
0 1000 2000
y = - x 0.0006 - 7.5873 R² = 0.9893 -8.8
-8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4
0 1000 2000
y = 1.611x + 0.0316 R² = 0.9966
0 10 20 30 40 50 60 70 80
0 20 40 60
Power law
10
135
0.00014
0.00012
0.0001 0.00008
0.00006
0.00004
0.00002
0
0 1000 2000
t
Fig. 61. Typical model fitting plots for AM-caffeine film in distilled water at 37±0.1°C
Zero order
In t 0 1000 2000 t (min)
First order Higuchi model
y = 0.5306x - 4.3435 R² = 0.974 -3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
0 5 y = 2E - 07 x + 7E - 05 R² = 0.954
0
0.0001
0.0002
0.0003
0.0004
0.0005
y = 6E - 08 x + 3E - 05 R² = 0.9503
0
0
136
t t 1/2
Hixson-crowell model
0.00016
0.00014
0.00012
0.0001
0.00008
0.00006
0.00004
0.00002
0
0 1000 2000
t
Fig. 62. Typical model fitting plots for MP-caffeine film in distilled water at 37±0.1°C
y = - 0.0006 x - 7.5726 R² = 0.9861
-8.8
-8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4
0 1000 2000
y = 1.6202x - 0.975 R² = 0.985 0
20
40
60
80
0 20 40 60
y = 6E - 08 x + 2E - 05 R² = 0.954
Power law
0
0 10
137
Zero order 0.0006
t
Hixson-crowell model
y = 0.3631x - 2.9703 R² = 0.9645 -2.5
-2
-1.5
-1
-0.5 5
In t
y = 2E - x 07 + 0.0001 R² = 0.982
0
0.0001
0.0002
0.0003
0.0004
0.0005
0 1000 2000
y = - 0.0013 x - 7.5694 R² = 0.9426
-12
-10
-8
-6
-4
-2
0
0 1000 2000
t
First order
y = 1.9667x + 5.5415 R² = 0.9841
0
20
40
60
80
100
0 20 40 60 t 1 / 2
Higuchi model
y = 8E - 08 x + 0.0004 R² = 0.982 0
0.0001
0.0002
0.0003
0.0004
0.0005
0.0006
0 1000 2000
0
0 10
138
t
Fig. 63: Typical model fitting plots for LR -caffeine film in distilled water at 37±0.1°C
0 0.0006
Zero order
t (min)
y = 2E - 07 x + 0.0001 R² = 0.9583
0 1000 2000
y = 0.3723x - 2.9932 R² = 0.9888
-2.5
-2
-1.5
-1
-0.5 0 5
In t
0
0.0001
0.0002
0.0003
0.0004
0.0005
Power law
10
139
First order
Hixson-crowell model
t
y = 8E - 08 x + 4E - 05 R² = 0.9583
0
0.00005
0.0001
0.00015
0.0002
0 1000 2000
y = - x 0.0012 - 7.6227 R² = 0.9576
-12
-10
-8
-6
-4
-2
0
0 1000 2000
t
y = 1.9069x + 7.4657 R² = 0.9913
0
20
40
60
80
100
0 20 40 60 t 1 / 2
Higuchi model
0
0 10
140
Fig. 64. Typical model fitting plots for OB-caffeine film in distilled water at 37±0.1°C Power
law Zero order
t (min)
First order Higuchi model
t 1/2 t 1/2
0 500 1000 1500 2000
y = 0.4824x - 3.7626 R² = 0.9791
-3
-2.5
-2
-1.5
-1
-0.5 5
In t
y = 2E - x 07 + 0.0001 R² = 0.9036
0
0.0001
0.0002
0.0003
0.0004
0.0005
0.0006
0 1000 2000
y = - x 0.0009 - 7.6327 R² = 0.9756
-10
-8
-6
-4
-2
0
0 1000 2000
y = 1.8594x + 3.6615 R² = 0.9821 0
20
40
60
80
100
0 20 40 60
y = 7E - 08 x + 4E - 05 R² = 0.9036
0
0.00005
0.0001
0.00015
0.0002
Power law
10
141
t
Fig. 65. Typical model fitting plots for PO husk-caffeine film in distilled water at 37±0.1°C
142
t
Fig. 66. Typical model fitting plots for SP-caffeine film in distilled water at 37±0.1°C Power law
Zero order
y = 0.6946x - 5.2334 R² = 0.9839
-4
-3
-2
-1
0 0 2 4 6 8
In t
y = 3E - x + 6E 07 - 05 R² = 0.9707
0
0.0001
0.0002
0.0003
0.0004
0.0005
0.0006
0 1000 2000
t ) min (
y = 2.2186x - 7.9351 R² = 0.9926
0
20
40
60
80
100
0 20 40 60
t 1 / 2
y = 9E - 08 x + 2E - 05 R² = 0.9707
0
0.00005
0.0001
0.00015
0.0002
0 500 1000 1500 2000
y = - 0.0012 x - 7.4694 R² = 0.9707
-12
-10
-8
-6
-4
-2
0
0 500 1000 1500 2000
t 1 / 2
143
0.0005
0.0004
0.0003
0.0002
0.0001
0
t (min)
Higuchi model
80
70
60
50
40
30
20
10
0
Hixson- crowell model
0.00016
y = 0.425x - 3.5103 R² = 0.9914
-3
-2.5
-2
-1.5
-1
-0.5
0 0 5 10
In t
y = 2E - 07 x + 0.0001 R² = 0.9315
0 1000 2000
y = - x 0.0007 - 7.6402 R² = 0.9832
-9
-8.8
-8.6
-8.4
-8.2
-8 -7.8
-7.6
-7.4
0 1000 2000
t
First order
y = 1.6272x + 4.6697 R² = 0.993
0 20 40 60 t 1 / 2
144
0.00014
0.00012
0.0001
0.00008
0.00006
0.00004
0.00002
0
t
Fig. 67. Typical model fitting plots for PO seeds-caffeine film in distilled water at 37±0.1°C
3.3.3.4. Release profile of diclofenac sodium loaded polymer tablets in phosphate buffer The
release profiles of the prepared tablets are shown in Fig.68. It can be seen that all the polymers are
imparting a sustained release effect. The materials exhibited following trend in sustained release:
MP > OB ≈ SP > PO husk > PO seeds ≈ AN > AM > LR > Control (for diclofenac sodium). MP
exhibited the best sustained release for diclofenac sodium. Generally the data fitted well (R2: 0.838
– 0.998, MSC: 1.24 – 8.343) in all the release models (Table 19, Fig. 69-78). PO seeds (Fig. 72),
MP (Fig. 69), OB (Fig. 74) and AN (Fig. 70) exhibited best fit to first order and SP (Fig.76) to
Higuchi model. A good fit to the first order model and Higuchi equation showed that the drug
release decreases slowly with time (Table 19). The best fit models were selected by MSC analysis.
Zero order model showed a good fit for LR and AT which means the release was constant over the
y = 6E - 08 x + 3E - 05 R² = 0.9315
0 1000 2000
145
time. AM and PO husk exhibited power law. The release data of diclofenac sodium fitted well in
power law and first order. The power law also showed a good fit to the data. A cursory view of the
data indicates that all the materials under investigation exhibit zero-order release kinetics for at
least first 120 min. The values of n for diclofenac sodium from the power law (Table 19) suggest
non-Fickian release mechanism by diffusion and swelling for
AN, PO seeds, LR, OB, MP, SP and AM exhibit time-independent, super case-II tansport (Table 19)
release mechanisms. In case of tablets prepared from diclofenac sodium + PO husk , the n values
were significantly less than 0.45, which indicates that the release occurs through a complex
mechanism where other factors like erosion in addition to diffusion and swelling are playing a
role.
3.3.3.5 Release profile of diclofenac sodium loaded polymer tablets in 0.1 N HCl
It is desirable for diclofenac sodium not to be released in stomach rather to be delivered in the
intestine, therefore, the release of diclofenac sodium was studied at pH 6.8 and in 0.1M HCl. The
results show that its release is sustained in phosphate buffer pH 6.8 and absorbance spectra of
DSpolymer tablets show negligible release in 0.1M HCl as it is insoluble in acidic medium (Fig.79).
3.3.3.6 Release profile of caffeine loaded polymer tablets in distilled water
The release profiles of the prepared tablets are shown in Fig. 80. It can be seen that all the polymers
are imparting a sustained release effect. Caffeine solubility is pH independent so its release was
studied only in distilled water.
146
The materials exhibited following trend in sustained release: MP > AM ≈ SP > AN > PO seeds >
PO husk ≈ LR > OB > Control (for caffeine). MP exhibited the best sustained release for caffeine.
Generally the data fitted well (R2: 0.817 – 0.993, MSC: 1.24 – 8.576) in all the release models
(Table 19, Fig. 80). In caffeine the data fitted well in power law (AN, LR and OB), first order (AM,
PO husk and MP) and Higuchi (PO seeds and SP) models (Fig. 81-90). A cursory view of the data
indicates that all the materials under investigation exhibit zero-order release kinetics for at least
first 120 min. The values of n for caffeine non-Fickian (AM, AN, MP, PO husk and SP) and Fickian
(PO seeds) mechanisms were exhibited. In case of tablets prepared from caffeine + LR and caffeine
+ OB the n values were significantly less than 0.45, which indicates that the release occurs through
a complex mechanism where other factors like erosion in addition to diffusion and swelling are
playing a role.
147
Fig. 68. Release profiles of tablets in phosphate buffer pH 6.8 (DS)
Table 19: Fitness of release data of diclofenac sodium in phosphate buffer from different material tablets to various mathematical
models
Material/Model AM AN PO seeds MP LR OB PO husk SP AT Control
Zero order R2 0.954 0.962 0.963 0.912 0.998 0.901 0.838 0.943 0.959 0.925
MSC 2.525 2.605 2.303 1.869 5.787 1.817 1.020 3.724 2.506 1.925
First order R2 0.986 0.993 0.998 0.955 0.968 0.975 0.999 0.971 0.935 0.978
MSC 3.698 4.432 5.350 2.536 2.654 3.190 1.459 3.046 2.082 3.152
Higuchi R2 0.987 0.989 0.991 0.898 0.979 0.966 0.992 0.988 0.926 0.963
MSC 3.782 3.908 3.735 1.967 3.080 2.884 1.778 3.958 1.329 2.645
Power law R2 0.992 0.992 0.980 0.954 0.997 0.946 0.964 0.978 0.845 0.964
MSC 4.030 4.167 2.937 2.329 5.222 2.433 2.526 3.357 1.370 2.671
n 0.916 0.673 0.842 0.570 0.874 0.471 0.238 0.457 0.050 0.813
Hixon
crowell
R2
MSC
0.954
2.525
0.962
2.605
0.963
2.303
0.898
1.967
0.998
5.787
0.901
1.817
0.838
1.020
0.943
2.378
0.959
2.506
0.924
1.922
% release (t min50) 115 102 35 140 75 60 20 110 <15 70
124
150
Power law Zero order
0 0.00025
t (min)
First order
Higuchi model
y = 8E - 07 x + 3E - 05 R² = 0.912
0 100 200 300
y = 0.5704x - 3.3225 R² = 0.9542
-2
-1.5
-1
-0.5 0 2 4 6
ln t
0
0.00005
0.0001
0.00015
0.0002
y = - x 0.005 - 8.221 R² = 0.955
-10
-9.5
-9
-8.5
-8
0 100 200 300
t
y = 0.252x + 20.48 R² = 0.898
0
20
40
60
80
100
0 200 400
t 1 / 2
Hixson - crowell model
151
0 200 400
t (min)
Fig. 69. Typical model fitting plots for MP-diclofenac sodium tablets in phosphate buffer of (pH
6.8) at 37±0.1°C
Power law Zero order
0.0003
0.00025
0.0002
0.00015
0.0001
0.00005
0
t (min)
y = 3E - 07 x + 2E - 05 R² = 0.898
0
0.00002
0.00004
0.00006
0.00008
0.0001
y = - x 0.008 - 8.1056 R² = 0.9939 -9.8
-9.6 -9.4 -9.2
-9 -8.8 -8.6 -8.4 -8.2
-8
0 100 200
t
First order
y = 6.7674x - 12.203 R² = 0.9897
0
20
40
60
80
100
0 5 10 15 t 1 / 2
Higuchi model
y = 0.673x - 3.707 R² = 0.992
-2
-1.5
-1
-0.5
0
0 2 4 6
In t
y = 1E - 06 x + 4E - 05 R² = 0.9621
0 100 200
152
Hixson crowell model
t (min)
Fig. 70. Typical model fitting plots for AN-diclofenac sodium tablets in phosphate buffer of (pH
6.8) at 37±0.1°C
t (min)
Hixson crowell model
y = 4E - 07 x + 1E - 05 R² = 0.9621
0 0.00001 0.00002 0.00003 0.00004 0.00005 0.00006 0.00007 0.00008 0.00009
0 100 200
y = 0.916x - 4.9856 R² = 0.9824
-3
-2.5
-2
-1.5
-1
-0.5
0
0.5
0 5 10
In t
Power law y = 1E - 06 x + 2E - 05
R² = 0.9548
0
0.00005
0.0001
0.00015
0.0002
0.00025
0.0003
0.00035
0 100 200 300
Zero order
y = - 0.009 x - 7.9635 R² = 0.986
-12
-10
-8
-6
-4
-2
0
0 1 00 200 300
t
First order
y = 7.3803x - 23.241 R² = 0.9871
0
20
40
60
80
100
0 10 20
t 1 / 2
Higuchi model
153
0 200 400
t (min)
Fig. 71. Typical model fitting plots for AM-diclofenac sodium tablets in phosphate buffer of (pH
6.8) at 37±0.1°C
Power law Zero order
0
50 100
t (min)
y = 4E - 07 x + 8E - 06 R² = 0.9548
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
y = 0.8425x - 3.6978 R² = 0.9805 -2
-1.5
-1
-0.5
0
0 5
In t
y = 3E - x + 3E 06 - 05 R² = 0.9632
0
0.00005
0.0001
0.00015
0.0002
0.00025 0.0003
154
t
t 1/2
Hixson crowell model
0 50 100
t (min)
Fig. 72. Typical model fitting plots for PO seeds-diclofenac sodium tablets in phosphate buffer of
(pH 6.8) at 37±0.1°C
Power law
0 0.0003 Zero order
y = - 0.0233 x - 7.9958 R² = 0.9983
-9.6
-9.4
-9.2
-9
-8.8
-8.6
-8.4
-8.2
0 50 100
First order
y = 12.981x - 25.619 R² = 0.9912
0
20
40
60
80
0 5 10
Higuchi model
y = 1E - 06 x + 1E - 05 R² = 0.9632
0
0.00002
0.00004
0.00006
0.00008
0.0001
y = 0.8748x - 4.39 R² = 0.9976
-2.5
-2
-1.5
-1
-0.5 0 2 4 6
In t
y = 2E - 06 x + 1E - 05 R² = 0.9986
0
0.0001
0.0002
0 100 200 t ) min (
155
First order Higuchi model
Hixson-crowell model
0 50 100 150
t (min)
Fig.73. Typical model fitting plots for LR-diclofenac sodium tablets in phosphate buffer of (pH 6.8)
at 37±0.1°C
Power law 0.0003 Zero order
In t t (min)
y = - 0.0159 x - 7.8457 R² = 0.9684
-12
-10
-8
-6
-4
-2
0
0 50 100 150
t
y = 9.9342x - 29.279 R² = 0.9794
0
20
40
60
80
100
0 5 10 15
t 2 / 1
y = 7E - 07 x + 4E - 06 R² = 0.9986
0
0.00002
0.00004
0.00006
0.00008
0.0001
y = 0.4711x - 7 2.853 R² = 0.9467
-2
-1.5
-1
-0.5
0
0 5 10
y = 6E - 07 x + 8E - 05 R² = 0.9015
0
0.00005
0.0001
0.00015
0.0002
0.00025
0 200 400
156
t 0
10 20
t (min)
0 200 400
t (min)
Fig.74. Typical model fitting plots for OB-diclofenac sodium tablets in phosphate buffer of (pH 6.8)
at 37±0.1°C
Power law
y = - 0.0045 x - 8.3101 R² = 0.975
-10
-9.5
-9
-8.5
-8
0 200 400
First order
y = 4.2878x + 7.1741 R² = 0.9661
0
20
40
60
80
100 Higuchi Model
y = 2E - 07 x + 3E - 05 R² = 0.9015
0
0.00002
0.00004
0.00006
0.00008
0.0001 Hixson - crowell model
y = 0.2382x - 1.3697 R² = 0.9641
-0.8
-0.6
-0.4
-0.2
0
0 2 4 6
In t
y = 8E - 07 x + 0.0002 R² = 0.838
0
0.00005
0.0001
0.00015
0.0002
0.00025
0.0003
0 50 100 150
t ( min )
Zero order
157
t t 1/2
t (min)
Fig.75. Typical model fitting plots for PO husk-diclofenac sodium tablets in phosphate buffer of
(pH 6.8) at 37±0.1°C
Power law 0.0004 Zero order
0
y = - 0.0076 x - 8.6926 R² = 0.8955 -9.8
-9.6
-9.4
-9.2
-9
-8.8
-8.6
0 50 100 150
First order
y = 4.1816x + 34.034 R² = 0.9241
0
20
40
60
80
100
0 5 10 15
Higuchi model
y = 3E - 07 x + 5E - 05 R² = 0.838
0
0.00002
0.00004
0.00006
0.00008
0.0001
0 50 100 150
Hixson - crowell model
y = 0.4571x - 2.698 R² = 0.9789
-2
-1.5
-1
-0.5
0 2 4 6
In t
y = 7E - 07 x + 9E - 05 R² = 0.9437
0
0.0001
0.0002
0.0003
0 200 400
t ( min )
158
t t 1/2
0 200 400
t (min)
Fig. 76.
Typical
model
fitting plots
for SP-
diclofenac sodium tablets in phosphate buffer of (pH 6.8) at 37±0.1°C
0 200 400
t (min)
y = - x 0.0064 - 8.2459 R² = 0.9711
-12
-10
-8
-6
-4
-2
0
0 200 400
First order
y = 4.8015x + 6.6868 R² = 0.9884
0
20
40
60
80
100
0 10 20
Higuchi model
y = 2E - 07 x + 3E - 05 R² = 0.9437
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012 Hixson - crowell model
y = 0.0501x - 0.4709 R² = 0.8459
-0.4
-0.35 -0.3
-0.25 -0.2
-0.15 -0.1
-0.05
0
0 2 4 6
In t
Power law
y = 1E - 07 x + 0.000 2 R² = 0.9593
0.00022
0.00023
0.00024
0.00025
0.00026
0.00027
0.00028 Zero order
159
t 0 5 10 15 20
t 1/2
Hixson-crowell model
0.000095
0.00009
0.000085
0.00008
0.000075
0 200 t
(min)
400
Fig. 77. Typical model fitting plots for AT-diclofenac sodium tablets in phosphate buffer of (pH 6.8)
at 37±0.1°C
y = - 0.0021 x - 9.3 374 R² = 0.9354
-10.2
-10
-9.8
-9.6
-9.4
-9.2
0 2 00 400
First order
y = 0.8989x + 68.851 R² = 0.9269
70
75
80
85
90 Higuchi model
y = 4E - 08 x + 8E - 0 5 R² = 0.9593
160
Zero
order
t (min)
First order
Higuchi model
t 1/2
t (min)
Fig. 78. Typical model fitting plots for control tablets in phosphate buffer of (pH 6.8) at 37±0.1°C
y = 0.813x - 4.102 R² = 0.9645
-2.5
-2
-1.5
-1
-0.5
0
0.5
0 2 4 6
In t
Power law
0
0.0001
0.0002
0.0003
0.0004
y = - 0.0282 x - 7.4277 R² = 0.978 -14
-12
-10
-8
-6
-4
-2
0
0 00 1 200
t
0
20
40
60
80
100
120
y = 6E - 07 x + 1E - 05 R² = 0.9249
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
0.00014
0 100 200
Hixson - crowell model
y = 2E - 06 x + 4E - 05 R² = 0.9251
0 100 200
y = 9.7987x - 25.626 R² = 0.9635
0 5 10 15
161
Fig. 79. Absorbance spectra of DS-polymer tablets in 0.1M HCl
Fig. 80. Release profiles of polymer tablets in distilled water (caffeine)
Table 19. Fitness of release data of caffeine in distilled water from different material tablets to various mathematical models
Material/Model AM AN PO
seeds
MP LR OB PO husk SP AT Control
Zero order R2 0.936 0.899 0.926 0.852 0.908 0.922 0.912 0.967 0.836 0.920
MSC 3.383 1.898 2.106 1.240 1.995 1.988 3.481 3.027 5.527 2.129
First order R2 0.971 0.940 0.971 0.906 0.969 0.975 0.943 0.977 0.817 0.989
MSC 8.170 2.428 3.041 6.622 3.099 3.124 8.343 3.411 8.576 4.187
Higuchi R2 0.989 0.974 0.982 0.944 0.978 0.981 0.965 0.988 0.817 0.983
MSC 5.184 3.241 3.527 2.212 3.447 3.409 4.411 4.085 5.570 3.706
Power law R2 0.993 0.985 0.981 0.954 0.991 0.992 0.983 0.980 0.849 0.990
MSC 5.397 3.832 3.514 3.572 4.417 4.282 2.771 3.528 1.392 4.242
n 0.480 0.553 0.436 0.525 0.273 0.353 0.584 0.750 0.110 0.564
Hixon crowell R2
MSC
0.936
3.383
0.899
1.899
0.926
2.106
0.852
1.240
0.908
1.995
0.922
1.987
0.912
3.481
0.967
3.027
0.836
5.527
0.920
2.129
% release (t min50) 240 210 170 300 110 90 110 240 15 110
136
164
Power law
t t 1/2
0 200 400 600
t (min)
Fig. 81. Typical model fitting plots for LR-caffeine tablets in distilled water at 37±0.1°C
y = 0.2734x - 1.9024 R² = 0.9919
-1.4
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0 5 10
In t
y = 6E - + 0.0002 07 x R² = 0.9089
0
0.0001
0.0002
0.0003
0.0004
0.0005
0 200 400 600
t ( ) min
Zero order
y = - 0.0026 x - 7.9139 R² = 0.9698 -9.2
-9 -8.8 -8.6 -8.4 -8.2
-8 -7.8 -7.6
0 200 00 4 600
First order
y = 2.7011x + 23.862 R² = 0.9787
0
20
40
60
80
100
0 10 20 30
Higuchi model
y = 2E - 07 x + 0.0004 R² = 0.9089
0
0.0001
0.0002
0.0003
0.0004
0.0005
0.0006 Hixson - crowell model
165
Power law 0.0004 Zero order
0
0 200 400 600
t (min)
Fig. 82. Typical model fitting plots for AM-caffeine tablets in distilled water at 37±0.1°C
= 0.4793x y - 3.3556 R² = 0.9934
-2.5
-2
-1.5
-1
-0.5 0 2 4 6 8
In t
y = 7E - x + 1E 07 - 04 R² = 0.9365
0
0.0001
0.0002
0.0003
0 500 t ) min (
y = - 0.0019 x - 7.6426 R² = 0.9718 -8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4
0 200 400 600
t
First order
y = 2.9174x + 2.5209 R² = 0.9895
0
20
40
60
80
0 10 20 30
t 1 / 2
Higuchi model
y = 3E - 07 x + 4E - 05 R² = 0.9365
0
0.00005
0.0001
0.00015
0.0002 Hixson - crowell model
166
Power law 0.0005
0
y = - x 0.0021 - 7.6321 R² = 0.9409 -8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4
0 200 00 4 600
t
First order
y = 3.2415x - 0.46 R² = 0.9743
0
10
20
30
40
50
60
70
0 10 20 30
t 1 / 2
Higuchi model
y = 0.5537x - 3.7178 R² = 0.9855
-2.5
-2
-1.5
-1
-0.5 0 5 10
In t
y = 7E - x + 9E 07 - 05 R² = 0.8996
0
0.0001
0.0002
0.0003
0.0004
0 200 400 600
t ) ( min
Zero order
167
0 200 400 600
t (min)
Fig. 83. Typical model fitting plots for AN-caffeine tablets in distilled water at 37±0.1°C Power
law
00.0005 Zero order
10 0.0004
-0.5
0.0003
-10.0002
0.0001
-1.50
0 200 400
-2
In t t (min)
y = 2E - 07 x + 3E - 05 R² = 0.8996
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
0.00014 Hixson - crowell model
y = 9E - 07 x + 0.0001 R² = 0.9262 y = 0.4366x - 2.8597
R² = 0.9819
0 5
168
0 200 400
t (min)
Fig. 86. Typical model fitting plots for POseeds-caffeine tablets in distilled water at 37±0.1°C
Power law
y = - 0.003 x - 7.701 R² = 0.971 -8.8
-8.6
-8.4
-8.2
-8
-7.8
-7.6
0 200 400
t
First order
y = 3.5739x + 6.4961 R² = 0.9822
0
20
40
60
80
0 10 20
t 1 / 2
Higuchi model
y = 3E - 07 x + 4E - 05 R² = 0.9262
0
0.00005
0.0001
0.00015 Hixson - crowell model
y = 0.5255x - 3.6127 R² = 0.9547
-2.5
-2
-1.5
-1
-0.5
0
0 5 10
In t
y = 6E - 07 x + 1E - 04 R² = 0.8521
0
0.0001
0.0002
0.0003
0.0004
0 500 t (min)
Zero order
169
First
order Higuchi model
t t
1/2
0.00014 Hixson-crowell model
0 200 400 600
t (min)
Fig. 87. Typical model fitting plots for MP-caffeine tablets in distilled water at 37±0.1°C
Power law 0.0005 Zero order
y = - 0.0018 x - 7.6586 R² = 0.906 -8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4
0 200 00 4 600
y = 2.8453x + 2.7068 R² = 0.9447
0
20
40
60
80
0 10 20 30
y = 2E - 07 x + 3E - 05 R² = 0.8521
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
170
0
t
t 1/2
0 100 200 300
t (min)
Fig. 86. Typical model fitting plots for OB-caffeine tablets in distilled water at 37±0.1°C
y = 0.353x - 2.2107 R² = 0.9922
-1.5
-1
-0.5
0 2 4 6
In t
y = 1E - 06 x + 0.0002 R² = 0.9226
0
0.0001
0.0002
0.0003
0.0004
0 100 200 300
t (min )
y = - 0.0044 x - 7.8136 R² = 0.9752
-9
-8.8
-8.6
-8.4
-8.2
-8
-7.8
-7.6
0 100 00 2 300
First order
y = 3.9112x + 15.448 R² = 0.9813
0
20
40
60
80
0 10 20
Higuchi model
y = 4E - 07 x + 6E - 05 R² = 0.9226
0
0.00005
0.0001
0.00015
0.0002 Hixson - crowell model
171
Power law
0.0005
0 100 200 300
t (min)
Fig. 87. Typical model fitting plots for PO husk-caffeine tablets in distilled water at 37±0.1°C
y = 0.5848x - 3.4707 R² = 0.9835
-2
-1.5
-1
-0.5
0
0 2 4 6
In t
y = 1E - 06 x + 1E - 04 R² = 0.912
0
0.0001
0.0002
0.0003
0.0004
0 100 200 300
t ) min (
Zero order
y = - 0.0049 x - 7.6097 R² = 0.9436
-9
-8.8
-8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4
0 100 200 300
t
First order
y = 5.132x - 4.7416 R² = 0.9653
0 10 20 30 40 50 60 70 80
0 10 20
t 1 / 2
Higuchi model
y = 5E - 07 x + 3E - 05 R² = 0.912
0
0.00005
0.0001
0.00015
0.0002 Hixson - crowell model
172
t 0 20 40
t 1/2
Hixson-crowell model
0.00016
0.00014
0.00012
0.0001
0.00008
0.00006
0.00004
0.00002 0
0 200 400
t (min)
600
y = 0.7505x - 4.7623 R² = 0.9803
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0 0 5 10
In t
Power law
y = 9E - 07 x + 5E - 05 R² = 0.9675
0
0.0001
0.0002
0.0003
0.0004
0.0005
0 200 400 600
t (min)
Zero order
y = - 0.003 x - 7.5048 R² = 0.9779
-9
-8.8
-8.6
-8.4
-8.2
-8
-7.8
-7.6
-7.4
0 200 400 600
First order
y = 4.0802x - 10.771 R² = 0.9887
0
20
40
60
80 Higuchi model
y = 3E - 07 x + 2E - 05 R² = 0.9675
173
Fig. 88. Typical model fitting plots for SP-caffeine tablets in distilled water at 37±0.1°C Power law
0.0005 Zero order
0
t (min)
Fig. 89. Typical model fitting plots for AT-caffeine tablets in distilled water at 37±0.1°C
y = 0.1104x - 0.9893 R² = 0.8493
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1 0 2 4 6
In t
y = 4E - 07 x + 0.0003 R² = 0.8367
0
0.0001
0.0002
0.0003
0.0004
0 200 400
t (min )
y = - x 0.0019 - 8.196 R² = 0.8172 -9
-8.8
-8.6
-8.4
-8.2
-8
0 200 400
t
First order
y = 1.485x + 45.837 R² = 0.8437
0
20
40
60
80
0 10 20
t 1 / 2
Higuchi model
y = 1E - 07 x + 1E - 04 R² = 0.8367
0
0.00005
0.0001
0.00015
0.0002
0 200 400
Hixson - crowell model
174
In t t (min)
0 500
t (min)
Fig. 90. Typical model fitting plots for control tablets in distilled water at 37±0.1°C
y = 0.5643x - 3.3523 R² = 0.9904
-2.5
-2
-1.5
-1
-0.5
0
0.5
0 2 4 6 8
Power law
y = 1E - x 06 + 0.0001 R² = 0.9203
0
0.0001
0.0002
0.0003
0.0004
0.0005
0.0006
0.0007
0 200 400 600
Zero order
y = - x 0.0068 - 7.5242 R² = 0.9898
-12
-10
-8
-6
-4
-2
0
0 200 400 600
t
First order
y = 5.0745x - 2.3627 R² = 0.9835
0
20
40
60
80
100
120
0 10 20 30
t 1 2 /
Higuchi model
y = 4E - 07 x + 4E - 05 R² = 0.9203
0
0.00005
0.0001
0.00015
0.0002
0.00025 Hixson - crowell model
175
3.3.4 Targeted delivery
All of the polymers under investigation were found to be insoluble in acidic medium therefore,
the drug-loaded polymers are expected to deliver the drugs in the intestine.
3.3.5 Disintegration study
When administered orally the disintegration time of the prepared tablets from caffeine and
diclofenac sodium ranged from 8 min to 169 min (Table 20).
3.4 Evaluation as binders in tablets
The direct compressed tablets incorporating the polymer as binder and acetaminophen as an active
pharmaceutical ingredient were subjected to hardness testing The hardness of LR is 11.5 (table 21)
which is approximately the same as methyl cellulose and HPMC (range from 11-12 kg/cm2 ) [196]
which are already in use as commercial binders. Whereas the other polymers possesed less
hardness. The trend of hardness was MP< SP=AM < AN< PO seeds = AT < PO husk< OB< LR.
3.5 Evaluation as suspending agents
Sedimentation of the prepared suspensions of acetaminophen suspensions incorporating the
polymers under investigation were recorded according to the standard method. The results are
shown in Fig. 89 as bar chart. The suspensions prepared from SP and OB remained stable for more
than 2 months time. The trend of stability was found to be: SP OB AN AM PO seeds TG
PO husk LR MP. The results were compared with a standard preparation. It can be Table
20. Disintegration time of caffeine and Diclofenac sodium
176
Materials Disintegration time (min)
Caffeine Diclofenac sodium
AM 45 35
LR 60 22
PO seeds 78 36
AT 05 08
OB 43 21
PO husk 145 97
SP 169 43
AN 68 120
MP 44 14
Voltral 36
Table 21. Hardness of tablets
Material Hardness (kgcm-2)
SP 1.6
AN 2.1
MP 1.2
POH 3.6
AM 1.6
LR 11.5
OB 4.1
POS 3.8
AT 3.8
177
Fig. 91. Suspensions of paracetamol: a) sedimentation bar chart
Fig. 91. (Continued) Suspensions of paracetamol: b) pictures
149
180
seen that all the polymers produced more stable suspension than the standard.
3.6 Evaluation as thickening agents
Thickening agents increases the viscosity without significantly altering its properties. As observed
from table 10 the trend in viscosity was found to be: PO husk > LR > POseeds > SP > AM > MP >
OB > AN at 1% concentration level and shear rate 10 s-1. It shows PO husk is the best as thickener
and can increase viscosity even if added in very small amount.
3.7 Evaluation as film coating materials
Film coating is an important and versatile step in the manufacture of solid dosage forms of drug
product in the pharmaceutical industry. The film coat applied helps to protect the active ingredient
inside the tablet from environment (air or light). It mask the taste, colour and odour and make the
tablet palatable or to determine controlled release dosage form [197]. Film coating agents also play
a vital role in drug delivery by making the tablets either for immediate release or for modified
release. Film coating was performed without the use of a platicizer and rupture of film coating was
checked with drop test [198]. The pictures of the coated tablets are shown in Fig. 92. In this test
one drop of water is placed on the outer surface of tablet with the help of a micropipette and the
surface was studied after 0, 10 and 20 second. The time of film rupture was
OB SP AN AM PO seeds PO husk LR MP. Even in the absence of plasticizer LR
and MP exhibited a fairly good coating ability and there is a chance of further improvement with
the use of plasticizer.
181
Fig. 92. Coated tablets
SP AN
MP PO husk
182
Fig. 92. (Continued) Coated tablets
g - h -
AM LR
OB PO seeds
183
3.8 Concluding remarks
Polysaccharides studied in this work came out to be low cost, easily available nonhazardous and
environment friendly. They can be used as biocompatible and biodegradable materials in
pharmaceutical formulations as tablet coating agents, suspending and thickening agents, binders in
tablets, fabrication of capsule shells, filling of pharmaceutical capsules, contact lenses, targeted and
controlled drug delivery devices.
These materials have a great potential for their use in formulation of ophthalmic solutions and
suspensions due to their very high water retention, drug-loaded capacity and sustained release
characteristics. Future work on evaluation of their use as the materials for medicated contact lenses,
non-gelatin capsule shells and biomedical scaffolds would provide interesting results.
184
3.9 Research publications by the author from this work
A) Papers published in international journal
1- Mohammad S. Iqbal, Shazma Massey, Jamshed Akbar, Chaudhury M. Ashraf, Rashid Masih
(2013) ; Thermal analysis of some natural polysaccharide materials by isoconversional method.
Food Chemistry, 140(1-2): 178-82. (Impact Factor =3.334)
2- Jamshed Akbar, Mohammad S. Iqbal, Shazma Massey, Rashid Masih (2012) ; Kinetics and
mechanism of thermal degradation of pentose and hexose-based polysaccharides. Carbohydrate
polymers, 90(3): 1386-93. (Impact Factor =3.479)
3- Shazma Massey, Mohammad S. Iqbal, Bettina Wolf, Irfana Mariam, Shumaila Rao (2016);
Comparative drug loading and release study on some carbohydrate polymers. Latin American
Journal of Pharmacy, 35(1): 146-155.
B- Oral presentation
1- In the conference organized by Department of Chemistry, Forman Christian College (A
Chartered University) Lahore, Pakistan on Exploring New Avenues in Medicinal Chemistry,
Opportunities & Challenges from January 21-23, 2015.
2- Paper accepted for oral presentation in 251st ACS National Meeting to be held in San Diego,
California, March 13-17, 2016. PAPER ID: 2394304, PAPER T TLE: “ solation,
characterization and pharmaceutical applications of polysaccharides from plants”
185
References
1. Kadajji, V. G., & Betageri, G. V. (2011). Water soluble polymers for
pharmaceutical applications. Polymers, 3, 1972-2009.
2. Rajkumari, C. P., Rajkumari & Ankita, K. (2013). A boon to controlled drug delivery
system. International Research Journal of Pharmacy, 4(4), 28-34.
3. Clasen, C., & Kulicke, W. M. (2001). Determination of viscoelastic and rheooptical
material functions of water soluble cellulose derrivatives. Progress in Polymer Science,
26, 1839-1919.
4. Buhler, V., (2005). Polyvinylpyrrolidine Excipients for pharmaceuticals: Povidone,
crospovidone and povidone (1st ed.). Springer: Berlin , Germany.
5. Chowhan, Z. T. (1980). Role of binders in moisture-induced hardness increase in the
compressed tablets and its effects on in vitro disintegration and dissolution. Journal of
Pharmaceutical Sciences, 69, 1-4.
6. Chowhan, Z. T., Amaro, A. A., & Ong, J. T. H. (1992). Punch geometry and
formulation considerations in reducing tablet friability and their effect on in vitro
dissolution. Journal of Pharmaceutical Sciences, 8, 1290-294.
7. Sriamornsak, P. (2003). Chemistry of pectin and its pharmaceutical uses: A
Review. Silpakorn University. International Journal, 3, 206-228.
186
8. Slany, J. (1981). Study of functional action of citrus pectins in tablets. Ceska a
Slovenska Farmacie, 30, 195-200.
9. Slany, J. (1981). Evaluation of tablets with pectin as a binding agent. Farmaceuticky
Obzor., 50, 491-498.
10. Naghibi, F., Mosaddegh, M., Motamed, S. M., & Ghorbani, A. (2005). Labiatae family
in folk medicine in Iran, from ethnobotany to pharmacology, Iranian Journal of
Pharmaceutical Research 4(2), 63-79
11. Abdulrasool, A. A., Naseer A. A., & Rahi, F. A. (2011). Application of seed mucilage
extracted from lallemantia royleana as a suspending agent. Iraqi journal of
pharmaceutical sciences, 20(1), 1-2.
12. Current EU approved additives and their E Numbers, Food Standards Agency, 26
November 2010.
13. Krishna, N., & Brow, F. (1964). Polyvinyl alcohol as an ophthalmic vehicle: Effect on
regeneration of corneal epithelium. American Journal of Ophthalmology, 57, 99-106.
14. Paton, T. F., & Robinson, J. R. (1975). Ocular evaluation of polyvinyl alcohol vehicle
in rabbits. Journal of Pharmaceutical Sciences, 64, 1312-1316.
15. Smolinske, Susan C. (1992). Handbook of Food, Drug, and Cosmetic Excipients. page
7. ISBN 0-8493-3585-X.
187
16. Chourasia, M.K., Jain, S.K. (2003). Pharmaceutical approaches to colon targeted drug
delivery systems. Journal of Pharmaceutical Sciences, 6 (1), 33-66.
17. Azuma, J., & Sakamoto, M. (2003). Cellulosic hydrocollid system present in seed of
plants. Trends in Glycoscience Glycotechnology, 15(81), 1-14.
18. Wan, L. S. C., & Lim, L.Y. (1992). Drug release from heat treated polyvinyl alcohol
films. Drug Development and Industrial Pharmacy, 18, 1895-1906.
19. Polymers for pharmaceutical applications. (2010). Lubrizol Pharmaceutical
Bulletin 1; Lubrizol: Wickliffe, OH, USA.
20. Uhrich, K. E., Cannizzaro, S. M., Langer, R. S., & Shakesheff, K. M. (1999). Polymeric
systems for controlled drug release. Chemical Reviews, 99(11), 31813198.
21. Hoare, T. R., & Kohane, D. S. (2008). Hydrogels in drug delivery: Progress and
challenges. Polymer, 49(8), 1993-2007.
22. Krusteva, S. (1990). Pharmaceutical investigation of a bioerodible nystatin system.
Pharmazie, 45, 195-197.
23. Rama Prasad, Y. V., Krishnaiah, Y. S. R., & Satyanarayana, S. (1998). In vitro
evaluation of guar gum as a carrier for colon-specific drug delivery. Journal of
Controlled Release, 51, 281-287.
188
24. Krishnaiah, Y. S. R., Satyanarayana, S., Rama Prasad, Y. V., & Narasimha Rao, S.
(1998). Gamma scintigraphic studies on guar gum matrix tablets for colonic drug
delivery in healthy subjects. Journal of Controlled Release, 55, 245-252.
25. Krishnaiah, Y. S. R., Satyanarayana, S., Rama Prasad, Y. V., & Arasimha Rao, S.
(1998). Evaluation of guar gum as a compression coat for drug targeting to colon.
International Journal of Pharmaceutics, 171, 137-146.
26. Avachat, A. M., Dash, R. R., & Shrotriya S. N. (2011). Recent investigations of plant
based natural gums, mucilages and resins in novel drug delivery systems. Indian
Journal of pharmaceutical education and research, 45(1), 86-99.
27. Singh K., Kumar A., Langyan N., & Ahuja M. (2009). Evaluation of mimosa pudica
seed mucilage as sustained-release excipient. AAPS Pharm Sci. Tech., 10(4), 1121–
1127.
28. Bourlais, C. L., Acar, L., Zia, H., Sado, P. A., Needham, T., & Leverge, R. (1998).
Ophthalmic drug delivery systems recent advances. Progress in Retinal and Eye
Research, 17, 33-58.
29. Zhang, L. M., Yang, C., & Yan, L. (2005). Perspectives on: Strategies to fabricate
starch based hydrogels with potential biomedical applications. Journal of Bioactive
and Compatible Polymers, 20, 297-314.
30. McFadden, E. P., Stabile, E., Regar, E., Cheneau, E., Ong, A. T., Kinnaird, T.,
189
Suddath, W. O., Weissman, N. J., Torguson, R., Kent, K. M., Pichard A. D., Satler, L.
F., Waksman, R., & Serruys, P.W. (2004). Late thrombosis in drug eluting coronary
stents after discontinuation of antiplatelet therapy. Lancet, 364, 1519-1521.
31. Iqbal, M, S., Akbar, J., Hussain, M. A., Saghir, S., Sher, M. (2011). Evaluation of hot-
water extracted arabinoxylans from ispaghula seeds as drug carriers.
Carbohydrate polymers, 83 (3), 1218-1225.
32. McIntosh, Charles (1853). The Book of the Garden. Edinburgh and London, W.
Blackwood, 237.
33. Weiss, Gaea and Shandor (1985). Growing and using the healing herbs.
Ennmaas, PA: Rodale Press.
34. Hoffman, D., Medical Herbalism (2010). The Science and practice of Herbal
Medicine, Healing Arts Press, 51-52.
35. http://www.ageless.co.za/herb-basil.htm#Basil (Accessed on May01, 2013)
36. http://www.satveda.com/tulsi-herb-info.html (Accessed on May01, 2013)
37. http://www.honest-essential-oils.com/be-young-singles/basil-oil/ (Accessed on
May01, 2013)
38. Chiang L.C. (2005). Antiviral activities of extracts and selected pure constituents of
ocimum basilicum. Clinical and Experimental Pharmacology and Physiology, 32(10),
811-816.
190
39. http://www.essentialoils.co.za/therapeutic-properties.htm (Accessed on May01, 2013)
40. Ting, M. H. (1996). Characteristics of essential oil from basil (ocimum basil) grown in
Australia. Journal of Agricultural and Food Chemistry, 44, 877-881.
41. Shealy, C. N. (2000). The Illustrated Encyclopedia of Healing Remedies (1st ed.).
Element Books Ltd. ISBN 186204516X .
42. Ahmet, A., Medine, G., Meryem, Ş., Hatice, O., Fikrettin, S., & Isa K. (2005).
Antimicrobial effects of ocimum basilicum (Labiatae) extract. Turkish Journal of
Biology, 29, 155-160.
43. Jayasinghe, C., Gotoh, N., Aoki, T., & Wada, S. (2003). Phenolics composition and
antioxidant activity of sweet basil (Ocimum basilicum L.). Journal of Agricultural and
Food Chemistry, 51, 4442-4449.
44. Ilhan, K., Nazife Yiğit., & Mehlika Benli. (2008). Antimicrobial activity of various
extracts of ocimum basillium L. and observation of the inhibition effect on bacterial
cells by use of scanning electron microscopy. African Journal of Traditional,
Complementary and Alternative medicines, 5 (4), 363 – 369
45. Suppakul, P., Miltz, J, Sonneveld, K., & Bigger, S.W. (2003). Antimicrobial properties
of basil and its possible application in food packaging. Journal of
Agricultural and Food Chemistry, 51, 3197-3207
46. http://www.stuartxchange.com/Makahiya.html (Accessed on May03, 2013 )
191
47. http://www.earthclinic.com/Remedies/mimosa.html. (Accessed on June08, 2013)
48. Gandhiraja N., S. Sriram, V. Meenaa, J. Kavitha Srilakshmi, C. Sasikumar & R.
Rajeshwari, (2009). Phytochemical screening and antimicrobial activity of the plant
extracts of mimosa pudica, L. against selected Microbes. Ethnobotanical leaflets. 13,
618-624.
49. Molina, M., Contreras, C. M., & Tellez-Alcantara, P. (1999). Mimosa pudica may
possess antidepressant actions in the rat. Phytomedicine. 6 (5), 319-323.
50. Meenatchisundaram, S., Priyagrace, S., Vijayaraghavan, R., Velmurugan, A.,
Parameswari, G., & Michael, A. (2009). Antitoxin activity of mimosa pudica root
extracts against naja naja and bangarus caerulus venoms. Bangladesh Journal of
Pharmacology, 4, 105-109
51. Ibrahim,H., Vejayan J., & Othman I. (2007). The potential of mimosa pudica
(Mimosaceae) against snake envenomation. Journal of Tropical Forest Science. 19(4),
189-197.
52. Nazeema, T. H., & Brindha, V. (2009). Antihepatotoxic and antioxidant defense
potential of mimosa pudica. International Journal of Drug Discovery. 1(2), 1-4.
53. Muthukumaran, P., Shanmuganathan P., & Malathi , C. (2011) In vitro antioxidant
evaluation of mimosa pudica. Asian Journal of Pharmaceutical Research, 1(2), 44-46.
192
54. Zhang, J., Yuan, K., Zhou, W., Zhou, J., & Yang P. (2011). Studies on the active
components and antioxidant activities of the extracts of mimosa pudica Linn. from
southern China. Pharmacognosy Magazine., 7, 35-39.
55. Umamaheswari, S., & Prince, P. S. (2007). Antihyperglycaemic effect of Ilogen excel
, an ayurvedic herbal formulation in streptozotocin induced diabetes mellitus. Acta
Poloniae Pharmaceutica, 64 (1), 53-61
56. Sutar, N. G., Sutar, U. N., & Behera, B. C. (2009). Antidiabetic activity of the leaves
of mimosa pudica Linn in albino rats. Journal of Herbal Medicine and
Toxicology, 3 (1), 123-126.
57. Prasad, G. C., Khanna, R. P., Prakash, V., & Udupa, K. N. (1975). Effect of lajjawanti
(mimosa pudica) on regeneration of nerve. Journal of Research & education in Indian
Medicine, 10 (4), 37-44.
58. Kokane, D. D., More, R.Y., Kale, M. B., Nehete, M. N., Mehendale, P. C., & Gadgoli,
C. H. (2009). Evaluation of wound healing activity of root of mimosa pudica. Journal
of electronic publication, 124(2), 311-315.
59. Mazher, A., Tahir, M., Arshed, B., Muneeb, Z., & Aneel, A.(2012). Economics of
Lallemantia roylena (Tukham-e-Balangoo) production in the low intensity cropping
zone of the Punjab, Pakistan. Pakistan Journal of Agricultural Research, 25 (2).
60. http://botanical-herbs.com/content/herbal-raw-materials-seeds. (Accessed on June
193
08, 2013).
61. Amini, A. M., Razavi, S. M. A. (2012). Dilute solution properties of Balangu
(Lallemantia royleana) seed gum: Effect of temperature, salt, and sugar.
International Journal of Biological Macromolecules , 51, 235– 243.
62. Kirtikar, K. R., & Basu, B. D. (1935). Indian Medicinal Plants. International
Book Distributors, 1st ed., vol.1-8, 2791.
63. http://repository.ias.ac.in/28021/1/315.pdf (Accessed on June22, 2014)
64. http://www.sciencedirect.com/science/article/pii/S0141813012001894 (Accessed on
June 08, 2013)
65. Choudhary, M. I., & Atia-tul-Wahab (2011). Biomedical Studies and IPR (Intellectual
property rights) documentation of medicinal plants used in the treatment of women
diseases in sindh. Submitted to planning department, Government of Sindh.
International center for chemical and biological sciences,
H. E. J. Research Institute of Chemistry .University of Karachi, Pakistan. (Accessed on
June 08, 2013 )
66. Dey, K. L., Bahadur, R., & Mair, W. (1896). The indigenous drugs of India: Short
descriptive notices of the principal medicinal products met with in British India.
Calcutta, Thacker, Spink. 2nd ed., rev. and entirely re-written. (World Cat 12100637).
67. Osol, A., & Farrar, G. E. (1995). The Dispensatory of the United States,
Lippinocott, J. F, Philadelphia, 25th ed., vol.1.
194
68. Ahmad, M., Zaman, F., Sharif, T., & Zabta, C. M. (2008). Antidiabetic and
hypolipidemic effects of aqueous methanolic extract of acacia nilotica pods in alloxan-
induced diabetic rabbits. Scandinavian Journal of Laboratory Animal Science, 35(1),
29-34.
69. Ali, A., Akhtar, N., Khan, B. A., Khan, M. S., Rasul, A., Shahiq-uz-Zaman, Khalid,
N., Waseem, K., Mahmood, T. & Ali, L. (2012) . Acacia nilotica: A plant of
multipurpose medicinal uses. Journal of Medicinal Plants Research, 6 (9),
1492-1496.
70. Satish, S., Raghavendra, M. P. and Raveesha, K. A. (2008). Evaluation of the
antibacterial potential of some plants against human pathogenic bacteria. Advances in
biological research, 2 (3-4), 44-48.
71. Ali, B. H., Ziada, A., & Blunden, G. (2009). Biological effects of gum arabic, a review
of some recent research. Food and Chemical Toxicology, 47(1), 1-8.
72. Murad, W., Ahmad, A., Gilani, S., A., & Khan, M., A. Indigenous knowledge and folk
use of medicinal plants by the tribal communities of hazar nao forest ,
Malakand district, North Pakistan. Journal of Medicinal Plants Research, 5, 1072- 1086.
73. Mushtaq A., Zafar M., Khan M., A., Sultana S., Shah G., M.,& Gul J. (2012).
Ethnomedicinal investigation of phytomedicines among the local communities of arid
areas of Pakistan. Indian Journal of Traditional Knowledge , 11(3), 436-446
195
74. Ahmad , B., khan , I., Azam, S., Bashir, S., Ahmad, J., & Hussain, F. (2011). Screening
of Acacia modesta for haemagglutination, antibacterial, phytotoxic and insecticidal
activities. Journal of Medicinal Plants Research , 5 (14), 3090-3096.
75. Jawla, S., Kumar, Y., & Khan, M., S., Y. (2011). Antimicrobial and
antihyperglycemic activities of acacia modesta leaves. Pharmacology online, 2,
331-347
76. http://www.richters.com (Accessed on June08, 2013)
77. Anderson, J. R., Bukhave, K., Hojgaard; L., Rasmussen, J., Hermansen,
N.,Worning, H. & Karg, E., (1988). Decomposition of wheat bran and isabgol
husk in the stomach and small intestine of healthy men. Journal of Nutrition, 118(3),
326-331.
78. Singh, B. (2007). Psyillium as therapeutic drug delivery agent. International
Journal of Pharmaceutics, 334(1-2), 1-14.
79. Shamim, S. M., Sultana, K., Islam, F.,& Ahmad S.I. (2004). Ispaghula husk: A
common therapeutic agent for hyper-cholesterolemia . Pakistan Journal of
Pharmacology, 21(2), 49-53.
80. A guide to medicinal Plants in North Africa. (2005). ISBN: 2-8317-0893-1,
IUCN centre for Mediterranean co-operation (spain).
196
81. Abraham, Z.D., & Mehta, T. (1988). Three- week psyllium husk supplementation:
Effect on plasma cholesterol concentration, fecal steroid excretion, and carbohydrate
absorption in men. American Journal of Clinical Nutrition, 47(1), 67-74.
82. http://www.tajagroproducts.com (Assessed on july20, 2013)
83. Soni, H., Singhai A., K. (2012). A recent update of botanicals for wound healing
activity. International research journal of pharmacy, 3(7), 1-7.
84. Laidlaw, R. A., & Purcival, E. G. V. (1949). Studies on seed mucilages. Part III.
Examination of a polysaccharide extracted from the seeds of Plantago ovata
Forsk. Journal of the Chemical Society, 1600–1607.
85. Laidlaw, R. A., & Purcival, E. G. V. (1950). Studies of seed mucilages. Part V.
Examination of a polysaccharide extracted from the seeds of Plantago ovata Forsk by
hot water. Journal of the Chemical Society, 528–534.
86. Saghir, S., Iqbal, M. S., Hussain, M. A., Koschella, A., & Heinze, T. (2008).
Structure characterization and carboxymethylation of arabinoxylan isolated from
Ispaghula (Plantago ovata) seed husk. Carbohydrate Polymers, 74, 309–317.
87. Galat, A., (1980). Study of the raman scattering and infrared absorption spectra of
branched polysaccharides.Acta biochimica polonica, 27(2), 135-141.
197
88. Villetti, M. A., Crespo, J. S., Soldi, M. S., Pires, A. T. N., & Borsali, R. S., V. (2002).
Thermal degradation of natural polymers. Journal of Thermal Analysis and
Calorimetry, 67, 295-303.
89. Zohuriaan, M. J., & Shokrolahi, F. (2004). Thermal studies on natural and modified
gums. Polymer Testing, 23, 575-579.
90. Chrissafis, K. (2009). Kinetics of thermal degradation of polymers. Journal of
Thermal Analysis and Calorimetry, 95(1), 273-283.
91. Jin, A. X., Ren, J. L., Peng, F., Xu, F., Zhou, G. Y., Sun, R. C., & Kennedy, J. F. (2009).
Comparative characterization of degraded and non-degradative hemicelluloses from
barley straw and maize stems. Composition, structure, and thermal properties.
Carbohydrate Polymers, 78, 609-619.
92. Iqbal, M. S., Massey, S., Akbar, J., Ashraf, C. M., & Masih, R. (2013). Thermal
analysis of some natural polysaccharide materials by isoconversional method. Food
Chemistry, 140, 178–182.
93. Faix, O., Fortmann, I., Bremer, J., & Meier, D. (1991). Thermal degradation products
of wood. Gas chromatographic separation and mass spectrometric characterization of
polysaccharide derived products. European Journal of Wood and Wood Products,
49(5), 213-219.
198
94. Faix, O., Fortmann, I., Bremer, J., & Meier, D. (1991). Thermal degradation products
of wood. A collection of electron-impact (EI) mass spectra of polysaccharide derived
products. European Journal of Wood and Wood Products, 49(7), 299-304.
95. Müller-Hagedorn, M., Bockhorn, H., Krebs, L., & Müller, U. (2003). A comparative
kinetic study on the pyrolysis of three different wood species. Journal of Analytical
and Applied Pyrolysis, 68-69, 231-249.
96. Seaman, J. F., Moore W. E., Mitchell RL, Millet RA. (1954). Techniques for the
determination of pulp constituents by quantitative paper chromatography. Tappi, 37,
336-343.
97. Smith, P. K., Krohn, R. I., Hermanson, G. T., Mallia, A. K., Gartner, F. H., Provenzano,
M. D., Fujimoto, E. K., Goeke, N. M., Olson, B. J, & Klenk, D. C.
(1985). Measurement of protein using bicinchoninic acid. Analytical
Biochemistry, 150(1), 76–85.
98. Westerlund, E., Andersson, R. & Aman, P. (1993). Isolation and chemical
characterization of water soluble mixed linked β glucan and arabinoxylans in oat
milled fractions. Carbohydrate Polymers, 20, 115.
99. Nilsson, M., Andersson, R., Andersson, R. E., Autio, K. & Aman, P. (2000).
Heterogeneity in water-extractable rye arabinoxylan with a low degree of
disubstitution. Carbohydrate Polymers, 41, 397.
199
100. Hoffman, R. A., Kamerling, J. P. & Vliegenhart, J. F. G. (1992). Structural features of
water-soluble arabinoxylan from the endosperm of wheat. Carbohydrate Research,
226, 303–311.
101. Bengtsson, S., Andersson, R., Westerlund, E. & Aman, P. (1992). Content, structure
and viscosity of soluble arabinoxylans in rye grain from several countries. Journal of
the Science of Food and Agriculture. 58(3), 331.
102. Ebringerova, A., Hromadkova, Z., Petrakova, E. & Hricovini, M. (1990). Structural
features of a water-soluble L-arabino-D-xylan from rye bran. Carbohydrate Research.
198, 57-66.
103. Izydorczyk, M.S. and Biliaderis, C.G. 1992. Influence of structure on the
physicochemical properties of wheat arabinoxylan. Carbohydrate Polymer. 17,
237247.
104. Vinkx, C. J. A., Reynaert, H. R., Grobet, P. J. & Delcour, J. A. (1993).
Physicochemical and Functional Properties of Rye Nonstarch Polysaccharides. V.
Variability in the Structure of Water-Soluble Arabinoxylans. Cereal Chemistry. 70, 311.
105. Carvajal-Millan, E., Guilbert, S., Morel, M.-H. & Micard, V. (2005). Impact of the
structure of arabinoxylan gels on their rheological and protein transport properties.
Carbohydrate Polymers. 60, 431.
106. Fischer, M. H., Yu, N., Gray, G. R., Ralph, J., Anderson, L., Marlett, J. A. (2004).
200
The gel-forming polysaccharide of psyllium husk (Plantago ovata Forsk). Carbohydrate
Research. 339(11), 2009–2017.
107. Virkki, L., Johansson, L., Ylinen, M., Maunu, S. & Ekholm, P. (2005). Structural
characterization of water-insoluble nonstarchy polysaccharides of oats and barley.
Carbohydrate Polymers. 59, 357.
108. Hoare, T. R., & Kohane, D. S. (2008). Hydrogels in drug delivery: Progress and
challenges. Polymer, 49(8), 1993-2007.
109. Scurr, D. J., Horlacher, T., Oberli, M. A., Werz, D. B., Kroeck, L., Bufali, S.,
Seeberger, P.H., Shard, A. G. & Alexander, M. R. (2010). Surface characterisation of
carbohydrate microarrays. Langmuir, 26 (22), 17143–55.
110. Judd, A. M., Scurr, D. J., Heylings, J. R., Wan, K.-W., & Moss, G. P. (2013).
Distribution and visualisation of chlorhexidine within the skin using ToF-SIMS: A
potential platform for the design of more efficacious skin antiseptic formulations.
Pharmaceutical Research, 30, 1896–1905.
111. Belu, A. M., Davies, M. C., Newton, J. M., & Patel, N. (2000). TOF-SIMS
characterization and imaging of controlled-release drug delivery systems.
Analytical Chemistry, 72(22): 5625–38.
112. Chabala, J. M., Soni, K. K., Li, J., Gavrilov, K. L., & Levisetti, R. (1995). High
resolution chemical imaging with scanning ion probe sims. International Journal of Mass
Spectrometry and Ion Processes, 143, 191–212.
113. Lloyd R. S. (1969). Determination of asphalt molecular weight distributions by gel
201
permeation chromatography. Analytical Chemistry, 41 (10), 1223–1227.
114. Balmayor, E., Azevedo, H., & Reis, R. (2011). Controlled Delivery Systems: From
Pharmaceuticals to Cells and Genes. Pharmaceutical Research, 28(6), 1241-1258.
115. Mario, G., & Gabriele, G. (2005). Mathematical Modelling and Controlled Drug
Delivery: Matrix Systems. Current Drug Delivery, 2(1), 97-116.
116. Siepmann, J., & Siepmann, F. (2008). Mathematical modeling of drug delivery.
International Journal of Pharmaceutics, 364(2), 328-343.
117. Siepmann, J., & Peppas, N. A. (2001). Modeling of drug release from delivery systems
based on hydroxypropyl methylcellulose (HPMC). Advanced Drug Delivery Reviews,
48, 139–157.
118. Kaunisto, E., Marucci, M., Borgquist, P., & Axelsson, A. (2011). Mechanistic
modelling of drug release from polymer-coated and swelling and dissolving polymer
matrix systems. International Journal of Pharmaceutics, 418(1), 54-77.
119. Lamberti, G., Galdi, I., & Barba, A. A. (2011). Controlled release from hydrogelbased
solid matrices. A model accounting for water up-take, swelling and erosion.
International Journal of Pharmaceutics, 407(1-2), 78-86.
120. Siepmann, J., & Siepmann, F. (2012). Swelling Controlled Drug Delivery Systems.
Fundamentals and Applications of Controlled Release Drug Delivery. In: J.
202
Siepmann, R. A. Siegel, & M. J. Rathbone (pp. 153-170): Springer US.
121. Colombo, P., Bettini, R., Massimo, G., Catellani, P. L., Santi, P., & Peppas, N. A.
(1995). Drug diffusion front movement is important in drug release control from
swellable matrix tablets. Journal of Pharmaceutical Sciences, 84(8), 991-997.
122. Colombo, P., Bettini, R., & Peppas, N. A. (1999). Observation of swelling process and
diffusion front position during swelling in hydroxypropyl methyl cellulose
(HPMC) matrices containing a soluble drug. Journal of Controlled Release, 61(12), 83-
91.
123. Colombo, P., Bettini, R., Santi, P., De Ascentiis, A., & Peppas, N. A. (1996). Analysis
of the swelling and release mechanisms from drug delivery systems with emphasis on
drug solubility and water transport. Journal of Controlled Release, 39(2-3), 231-237.
124. Colombo, P., Bettini, R., Santi, P., & Peppas, N. A. (2000). Swellable matrices for
controlled drug delivery: gel-layer behaviour, mechanisms and optimal performance.
Pharmaceutical Science & Technology Today, 3(6), 198-204.
125. Siepmann, J., & Peppas, N. A. (2000). Hydrophilic Matrices for Controlled Drug
Delivery: An Improved Mathematical Model to Predict the Resulting Drug Release Kinetics (the
“sequential Layer” Model). Pharmaceutical Research, 17(10), 1290-1298.
126. Siepmann, J., & Peppas, N. A. (2001). Modeling of drug release from delivery systems
based on hydroxypropyl methylcellulose (HPMC). Advanced Drug Delivery Reviews,
48, 139-145.
203
127. Siepmann, J., Streubel, A., & Peppas, N. A. (2002). Understanding and Predicting
Drug Delivery from Hydrophilic Matrix Tablets Using the “Sequential Layer” Model.
Pharmaceutical Research, 19(3), 306-314.
128. Peppas, N. A. (1985). Analysis of Fickian and non-Fickian drug release from polymers.
Pharmaceutica Acta Helvetiae, 60, 110-111.
129. Ritger, P. L., & Peppas, N. A. (1987a). A simple equation for description of solute
release. I. Fickian and non-Fickian release from non-swellable devices in the form of
slabs, spheres, cylinders or discs. Journal of Controlled Release, 5, 23–36.
130. Ritger, P. L., & Peppas, N. A. (1987b). A simple equation for description of solute
release. II. Fickian and anomalous release from swellable devices. Journal of
Controlled Release, 5, 37–42.
131. Korsmeyer, R. W., Gurny, R., Doelker, E. M., Buri, P. L., & Peppas, N. A. (1983).
Mechanism of solute release from porous hydrophilic polymers. International
Journal of Pharmaceutics, 15, 25-35.
132. Lopes, C., Sousa Lobo, J., Pinto, J., & Costa, P. (2007). Compressed matrix core tablet
as a quick/slow dual-component delivery system containing ibuprofen. AAPS
PharmSciTech, 8(3), E195-E202.
133. Dash, S., Murphy, P. N., Nath, L., & Chowdhury, P. (2010). Kinetic modeling on drug
release from controlled drug delivery systems. Acta Poloniae PharmaceuticaDrug
Research, 67(3), 217 - 223.
204
134. Gibaldi, M., & Feldman, S. (1967). Establishment of sink conditions in dissolution rate
determinations-theoretical considerations and application to nondisintegrating dosage
forms. Journal of Pharmaceutical Sciences, 56: 1238-1242.
135. Martin, A., Bustamante, P. & Chun, A.H.C. (1993). Physical Pharmacy:
Physicochemical Principles on the Pharmaceutical Sciences, 4th Ed. Lea and Fabiger,
Philadelphia, London.
136. Siepmann, J., & Siepmann, F. (2008). Mathematical modeling of drug delivery.
International Journal of Pharmaceutics, 364, 328-343.
137. Korsmeyer, R. W., Von Meerwall, E., & Peppas, N. A. (1986). Solute and penetrant
diffusion in swellable polymers. II. Verification of theoretical models. Journal of
Polymer Science Part B: Polymer Physics, 24(2), 409-434.
138. Korsmeyer, R. W., Lustig, S. R., & Peppas, N. A. (1986). Solute and penetrant
diffusion in swellable polymers. I. Mathematical modeling. Journal of Polymer
Science Part B: Polymer Physics, 24(2), 395-408.
139. Ju, R. T. C., Nixon, P. R., & Patel, M. V. (1995). Drug release from hydrophilic
matrices. 1. New scaling laws for predicting polymer and drug release based on the
polymer disentanglement concentration and the diffusion layer. Journal of
Pharmaceutical Sciences, 84(12), 1455-1463.
140. Ju, R. T. C., Nixon, P. R., & Patel, M. V. (1997). Diffusion coefficients of polymer
chains in the diffusion layer adjacent to a swollen hydrophilic matrix. Journal of
Pharmaceutical Sciences, 86(11), 1293-1298.
205
141. Ju, R. T. C., Nixon, P. R., Patel, M. V., & Tong, D. M. (1995). Drug release from
hydrophilic matrices. 2. A mathematical model based on the polymer
disentanglement concentration and the diffusion layer. Journal of Pharmaceutical
Sciences, 84(12), 1464-1477.
142. Flynn, J. H., & Wall, L. A. (1966). General treatment of the thermogravimetry of
polymers. Journal of Research of the National Bureau of Standards-A. Physics and
Chemistry, 70A (6), 487–523.
143. Ozawa, T. (1965). A new method of analyzing thermogravimetric data. Bulletin of the
Chemical Society of Japan, 38(11), 1881–1886.
144. Doyle, C. D. (1961). Estimating thermal stability of experimental polymers by
empirical thermogravimetric analysis. Analytical Chemistry, 33, 77–79.
145. Vyazovkin, S., Burnham, A. K., Criado, J. M., Pérez-Maqueda, L. A., Popescu, C.,
& Sbirrazzuoli, N. (2011). ICTAC Kinetics Committee recommendations for performing kinetic
computations on thermal analysis data. Thermochimica Acta, 520(1–2), 1–19.
146. Weitzhandler, M., Barreto, V., Pohl, C., Jandik, P., Cheng, J., & Avdalovic, N. (2004).
Journal of Biochemical and Biophysical Methods, 60(3), 309–317.
147. Mutalik, V., Manjeshwar L.S., Wali A., Sairam M., Raju K.V.S.N., Aminabhavi T.M.
(2006). Thermodynamics/hydrodynamics of aqueous polymer solutions and dynamics
mechanical characterization of solid films of chitosan, sodium alginate, guar gum,
206
hydroxy ethyl cellulose and hydroxypropyl methylcellulose at different temperatures.
Carbohydrate polymers, 65, 9-21.
148. Rinaudo, M., Milas, M., & Le Dung, P. (1993). Characterization of chitosan.
Influence of ionic strength and degree of acetylation on chain expansion. International
Journal of Biological Macromolecules, 15, 281–285.
149. Harding, S. E. (2005). Analysis of polysaccharides size, shape and interactions. In D.J.
Scott, S. E. Harding, & A. J. Rowe (Eds.), Analytical ultracentrifugation techniques
and methods (pp. 231–252). Cambridge: Royal Society of Chemistry.
150. Schuck, P. (1998). Sedimentation analysis of noninteracting and self-associating
solutes using numerical solutions to the Lamm equation. Biophysical Journal, 75,
1503–1512.
151. Schuck, P. (2005). Diffusion-deconvoluted sedimentation coefficient distributions for
the analysis of interacting and non-interacting protein mixtures. In D. J.Scott, S. E.
Harding, & A. J. Rowe (Eds.), Analytical ultracentrifugation techniques and methods
(pp. 26–50). Cambridge: Royal Society of Chemistry.
152. Higuchi, T. (1961). Rate of release of medicaments from ointment bases containing
drugs in suspension. Journal of Pharmaceutical Sciences, 50(10), 874875.
153. Higuchi, T. (1963). Mechanism of sustained-action medication. Theoretical analysis of
rate of release of solid drugs dispersed in solid matrices. Journal of Pharmaceutical
Sciences, 52(12), 1145-1149.
207
154. Korsmeyer, R. W., Gurny, R., Doelker, E. M., Buri, P. L., & Peppas, N. A.
(1983). Mechanism of solute release from porous hydrophilic polymers. International
Journal of Pharmaceutics, 15, 25-35.
155. Peppas, N. A. (1985). Analysis of Fickian and non-Fickian drug release from polymers.
Pharmaceutica Acta Helvetiae, 60, 110–111.
156. Ritger, P. L., & Peppas, N. A. (1987a). A simple equation for description of
soluterelease. I. Fickian and non-Fickian release from non-swellable devices in the
form of slabs, spheres, cylinders or discs. Journal of Controlled Release, 5, 23–36.
157. Ritger, P. L., & Peppas, N. A. (1987b). A simple equation for description of solute
release. II. Fickian and anomalous release from swellable devices. Journal of
Controlled Release, 5, 37–42.
158. Scientist-handbook, & rev. 7EEF (1995). Micro Math, Inc., Salt Lake City, 467 159.
Laidlaw, R. A., & Purcival, E. G. V. (1949). Studies on seed mucilages. Part III.
Examination of a polysaccharide extracted from the seeds of Plantago ovata Forsk.
Journal of the Chemical Society, 1600–1607.
160. Laidlaw, R. A., & Purcival, E. G. V. (1950). Studies of seed mucilages. Part V.
Examination of a polysaccharide extracted from the seeds of Plantago ovata Forsk by hot
water. Journal of the Chemical Society, 528–534.
161. Saghir, S. (2009). Isolation, modification, characterization and pharmacological
evaluation of gellable material from ispaghula husk. Ph.D. Thesis, Department of
Chemistry, University of Sargodha, Sargodha.
208
162. Saghir, S., Iqbal, M. S., Hussain, M. A., Koschella, A., & Heinze, T. (2008).
Structure characterization and carboxymethylation of arabinoxylan isolated from
Ispaghula (Plantago ovata) seed husk. Carbohydrate Polymers, 74, 309–317.
163. Galat, A., (1980). Study of the raman scattering and infrared absorption spectra of
branched polysaccharides. Acta biochimica polonica, 27(2), 135-141.
164. Kačuráková, M., Wellner, N., Ebringerová, A., Hromadkova, R. H., Wilson, R. H., &
Belton, P. S. (1999). Characterisation of xylan-type polysaccharides and associated cell
wall components by FT-IR and FT-Raman spectroscopies. Food Hydrocolloids, 13, 35-
41.
165. Unlu, C. H., Gunister, E., & Atici, O. (2009). Synthesis and characterization of
NaMt biocomposites with corn cob xylan in aqueous media. Carbohydrate
Polymers, 76, 585-592.
166. Iqbal, M. S., Akbar, J., Saghir, S., Karim, A., Koschella, A., & Heinze, T. (2011).
Thermal studies of plant carbohydrate polymer hydrogels. Carbohydrate Polymers,
86(4), 1775 –1783.
167. Peng, Y., & Wu, S. (2010). The structural and thermal characteristics of wheat straw
hemicellulose. Journal of Analytical and Applied Pyrolysis, 88(2), 134–139.
168. Popescu, M.-C., Popescu, C.-M., Lisa, G., & Sakata, Y. (2011). Evaluation of
morphological and chemical aspects of different wood species by spectroscopy and
thermal methods. Journal of Molecular Structure, 988(1–3), 65–72.
209
169. Yang, H., Yan, R., Chen, H., Lee, D. H., & Zheng, C. (2007). Characteristics of
hemicellulose, cellulose and lignin pyrolysis. Fuel, 86(12–13), 1781–1788.
170. EL-Rassi, Z., (2002). Carbohydrate analysis by modern chromatography and
electrophoresis. Elsevier, 890.
171. Saghir, S., Iqbal, M. S., Hussain, M. A., Koschella, A., & Heinze, T. (2009).
Ethylation of arabinoxylan from Ispaghula (Plantago ovata) seed husk.
Carbohydrate Polymers 77, 125–130.
172. P.Carek, A.Kardosova and D. Lath. (1999). A neutral heteropolysaccharide from the
flowers of Malva mauritiana L. Chemical Papers, 53(20), 131-136.
173. Capeka, P., Matulováa, M., & Kardošováa, A., (1997). An Acidic
Heteropolysaccharide from the Flowers of Malva Mauritiana L. Journal of
Carbohydrate Chemistry. 16(9), 1373-1391.
174. Westphal, Y., Kühnel, S., Waard, P.,D., Hinz, S., W., A., Schols, H., A., Voragen, A.,
G., J., & Gruppen, H. (2010) Branched arabino-oligosaccharides isolated from sugar beet
arabinan. Carbohydrate research, 345(9), 1180-1189.
175. Fischer, M. H., Yu, N., Gray, G. R., Ralph, J., Andersond, L., & Marletta, J. A.
(2004). The gel-forming polysaccharide of psyllium husk (Plantago ovata Forsk)
Carbohydrate Research, 339, 2009–2017
210
176. Marisol Ochoa-Villarreal, Emmanuel Aispuro-Hernández,Irasema
VargasArispuro Miguel Ángel Martínez-Téllez & Irasema Vargas-Arispuro (2012).
Plant
Cell Wall Polymers: Function, Structure and Biological Activity of Their Derivatives.
Chapter 4.http://dx.doi.org/10.5772/46094
177. Bubb. W. A. (2006). NMR Spectroscopy in the study of carbohydrates: Characterizating
the structural complexity. School of molecular and microbial biosciences, University of
Sydney, New South wales, Australia.
178. The Scientific World Journal (2003) 3, 105–121. ISSN 1537-744X; DOI
10.1100/tsw.2003.15.Rheology of Biopolymer Solutions and Gels David R. Picout and
Simon B. Ross-Murphy Biopolymers Group, Division of Life Sciences, King's College
London, Fran
179. Gómez-Díaz, D., Navaza, J. M. and Quintáns-Riveiro L.C; (2008). Intrinsic viscosity
and flow behavior of Arabic gum aqueous solutions. International
Journal of Food Properties, 11, 773–780.
180. Harding, S. E., Horton J. C. Cölfen, H.; (1997). The ELLIPS suite of macromolecular
conformation algorithms. European Biophysics Journal, 25, 47– 359.
181. Laidlaw, R. A., & Purcival, E. G. V. (1949). Studies on seed mucilages. Part III.
Examination of a polysaccharide extracted from the seeds of Plantago ovata Forsk.
Journal of the Chemical Society, 1600–1607.
182. Laidlaw, R. A., & Purcival, E. G. V. (1950). Studies of seed mucilages. Part V.
Examination of a polysaccharide extracted from the seeds of Plantago ovata Forsk by hot
water. Journal of the Chemical Society, 528–534.
211
183. Saghir, S. (2009). Isolation, modification, characterization and pharmacological
evaluation of gellable material from ispaghula husk. Ph.D. Thesis, Department of
Chemistry, University of Sargodha, Sargodha.
184. Wang, L., Liu, Li., Holmes, J., Kerry, J., F., & Kerry, J. P. (2007). Assessment of film
forming potential and properties of protein and polysaccharide-based biopolymer films.
International Journal of Food Science and Technology. 42, 1128–1138.
185. Lazaridou, A.; Biliaderis, C. G. (2002). Biodegradable polymer blends and composites
from renewable resources. Carbohydrate Polymers. 48, 179-190.
186. Peppas, N. A., Bures, P., Leobandung, W., & Ichikawa, H., (2000). Hydrogels in
pharmaceutical formulations. European Journal of Pharmaceutics and
Biopharmaceutics. 50 (1), 27-46.
187. Burns, S. A., & Gardella Jr. J. A. (2008). Quantitative ToF-SIMS studies of protein drug
release from biodegradable polymer drug delivery membranes. Applied Surface Science,
255, 1170–1173.
188. Vickerman, J. C., Briggs, D. (2001). ToF-SIMS: surface analysis by mass spectrometry;
IM: Chichester.
189. Lu, Y., Chen, S. C. (Rev.2004). Micro and nano-fabrication of biodegradable polymers
for drug delivery. Advanced Drug Delivery, 56, 1621-1633.
212
190. Ogaki, R., Gilmore, I. S. Alexander, M. R. Green, F. M., Davies, M. C., & Lee, J. L. S.
(2011). Analytical Chemistry, 83, 3627-3631.
191. Scoutaris, N., Hook, A. L., Gellert, P. R., Roberts, C. J., Alexander, M. R., &
Scurr, D. J. (2012) . Journal of Materials Science: Materials in Medicine, 23, 385-391.
192. Mains, J., Wilson, C. G., Urqubart, A. (2011). ToF-SIMS Analysis of
Dexamethasone Distribution in the Isolated Perfused Eye. Investigative Ophthalmology
and Visual Science. 52(11), 8413-8419.
193. Singh, K., Kumar, A., Langyan, N., & Ahuja. M. (2009). Evaluation of Mimosa pudica
Seed Mucilage as Sustained-Release Excipient. AAPS PharmSciTech.
10(4), 1121–1127.
194. Suppakul, P., Miltz, J., Sonneveld, K., & Bigger SW. (2003). Antimicrobial properties
of basil and its possible application in food packaging. Journal of
Agricultural and Food Chemistry, 51, 3197-207.
195. Akbar, J., Iqbal, M. S., Chaudhary, M. T., Yasin, T., & Massey, S. (2012). A QSPR study
of drug release from an arabinoxylan using ab initio optimization and neural networks.
Carbohydrate Polymers, 88(4), 1348-1357.
196. Jaya, S., Chowdary, K. P. R., Rao, P. R. (2012). Effect of binders on the dissolution rate
and dissolution efficiency of ritonavir tablets. International Research Journal of
Pharmaceutical and Applied Sciences, 2(4), 109-113.
197. Annual Meeting (2013). Pharmaceutical discovery,
development and
213
manufacturing forum (260c). An integrated model for the thermodynamics of the film
coating operation the mixing phenomena in the drum and the distribution of properties
in the coated tablet.
198. http://www.gyermed.hu/pdf/Sepischool_SEPPIC_Coating_training_2012_gb.pdf
(Accessed onMay01, 2014)
