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by

SARMAD SABAH NASSER AL-EDRESI

May 2009

FORMULATION, IN VITRO AND IN VIVO EVALUATION OF COSMETIC NANO-CREAM FROM VIRGIN COCONUT OIL,

KOJIC ACID DIPALMITATE AND EMULIUM KAPPA

Thesis submitted in fulfillment of the requirements for the degree of

Master of Science (Pharmacy)

In the name of Allah who is gracious and merciful

This thesis is dedicated to my wife, daughter, parents, brother and sisters

ACKNOWLEDGMENT

Thanks and holy prayers to Allah who created everything, including Prophets and Scientists, to discover the science of knowledge and to civilize the universe in such a unique and proper construction.

1 would like to take this opportunity to thank my supervisor, Professor Dr. Saringat Bin Baie, for his guidance and advices which have enabled me to conduct my research smoothly and successfully. My sincere appreciation also goes to Dr. Nurzalina Khan and Dr. Yvonne Tze Fung Tan for having provided me much of the basis for discussion and suggestion.

1 am grateful to Mr. Ibrahim and Mr. Samsudin and I am also grateful to my friends Muthanna, Omeed, Mohanad, Sandy and Samer for their cooperation and assistance.

Last but not least, I offer my gratitude to my wife and daughter and to my family in my beloved country, Iraq, especially my Mother and my father-in-law for his financial support. Without my family’s encouragement and support, it would have been an impossible task to complete the present work. Also, I would like to thank USM for financial support for the chemicals.

TABLE OF CONTENTS

Page TITLE

DEDICATIONS ii

ACKNOWLEDGMENT ⁱⁿ

TABLE OF CONTENTS

LIST OF TABLES

xiii LIST OF FIGURES

LIST OF PLATES xvii

LIST OF EQUATIONS ^xvm

LIST OF ABBREVIATIONS ^xix

xxiii LIST OF APPENDICES

ABSTRAK ^XXVI

ABSTRACT ^XXVIll

CHAPTER 1: INTRODUCTION 1

1.1 Emulsions 1

1.1.1 Emulsifiers 2

1.1.1.1 Types ofcommon emulsifiers 3

1.1.2 Emulsion stabilizers 4

1.1.3 The Hydrophile-Lipophile Balance (HLB) system 4

1.2 Cosmetics 5

1.2.1 Cosmeticpreparations 5

1.2.1.1 Emulsions in cosmetics 6 1.2.1.1 (a) Types of emulsion 6 1.2.1.1 (b) Hydrocolloids 7

1.2.1.2 Basic composition of cosmetic emulsion 7 1.2.1.3 Solutions 8

1.2.1.4 Gels 8

1.2.2 Preservation of cosmetics 8 1.3 Rheology 9

1.3.1 The elements of rheology 9 1.3.2 Elasticity and viscosity 10 1.3.3 Fluid flow behavior 11

1.3.3.1 Newtonian behavior 12 1.3.3.2 Non-newtonian behavior 12

1.3.3.2(a) Plastic flow 12

1.3.3.2(b) Pseudoplastic flow 13 1.3.3.2(c)Dilatant flow 13 1.3.3.3 Time-dependent behavior 13 1.3.4 Yield value 14

1.3.5 Apparent viscosity 14

1.4 Optimization in pharmaceutical formulation 15

1.4.1 Pharmaceutical experimental design 15

16 1.4.1.1 Experimental design protocol

1.4.1.2 Techniques of experimental design 16

1.4.1.3 Mixture design 17

1.4.1.3(a) Response surface methodology 17 1.4.1.3(b) Computer software 18

1.4.1.3(c) Ternary phase diagram 19 1.5 Stability study of cream formulation 19

1.5.1 Cream instabilities 20

1.5.2 Methods of stability evaluations 21 1.5.3 Factors affecting cream stability 21 1.5.4 Shelflife prediction 23

1.6 Nano-emulsions 23 1.6.1 Definition 23

1.6.2 Stability of nano-emulsions 24 1.6.3 Benefits of nano-emulsions 24 1.6.4 Method of preparations 25

1.6.5 Factors affecting nano-emulsion stability 26 1.6.6 Squalene oil 26

1.7 In vitro and in vivo evaluation of topical formulations 27

1.7.1 In vitro experimental model 27

1.7.2 In vivo experimental model 28

1.7.3 Human skin 29

1.7.3.1 Melanin synthesis 30

1.7.3.1(a) Inhibition of Melanin synthesis 31

1.7.3.1(b) Kojic acid dipalmitate 32

33

1.7.3.3 Skin reservoirs 34 1.7.4 Tape stripping technique 34 1.8 Objectives 35

CHAPTER 2: MATERIALS AND METHODS 36 2.1 Materials 36

2.2 Methods 37

2.2.1 Formulation of o/w cream base 37 2.2.1.1 Selection of oil phase 37

2.2.1.2 Selection of surfactant/cosurfactant mixture 38 2.2.1.3 Cream preparation 38

2.2.1.4 Construction of ternary phase diagram 39 2.2.1.5 Mixture Design 41

2.2.1.6 Optimization using Design-Expert® software 42 2.2.1.6(a) Apparent viscosity (K/) 44

2.2.1.6(b) Yield value (T?) 44 2.2.1.6(c) Spreadability (Kj) 45 2.2.2 Stability test 47

47 2.2.2.1 Stability testing protocol

48 2.2.2.1(a) Freeze-thaw storage test

2.2.2.1(b) Accelerated stability test 50 2.2.3 Formulation and stability of nano-cream 52

2.2.3.1 Nano-emulsion preparation 52

1.7.3.2 Mechanism of transportation of active ingredient through the skin

2.2.3.2 Stability of nano-cream 54

2.2.3.2(a) Determination of droplet size 54 2.2.3.2(b) Electrophoetic properties 54

55

2.2.4.1 Chromatographic condition 55

2.2.4.2 Preparation of stock and working standard solution 56 2.2.4.3 Preparation of calibration standards 56

2.2.4.4 Sample preparation procedure 56 2.2.4.5 Method validation 57

2.2.4.6 Prediction of shelf life 58

2.2.5 Determination of KDP solubility in THFiHiO solvent 59

60

61

62 2.2.7.1 In vivo study protocol

2.2.7.2 Application of cream 63

2.2.7.3 Differential stripping 65

2.3 Statistical analysis 67

CHAPTER 3: RESULTS 68

3.1 Formulation and optimization of o/w cream 68

3.1.1 Ternary phase diagram 68

3.1.2 Optimization of normal cream using Design-Expert® software 71 3.1.2.1 Effect of formulation variables on apparent viscosity 73 2.2.4 High performance liquid chromatographic (HPLC) method for

the determination of kojic acid dipalmitate

2.2.6 In vitro study of kojic acid dipalmitate release from cream preparation

2.2.7 In vivo study of storage behavior of kojic acid dipalmitate in normal and nano-cream

3.1.2.2 Effect of formulation variables on yield value 77

3.1.2.3 Effect of formulation variables on spreadability 77 3.1.3 Diagnostic plots of residual effects 78

3.1.4 Assessing factor effects with the trace plot 82 3.2 Stability study 86

3.2.1 Freeze-thaw storage test 86 3.2.1.1 Viscosity test 86

3.2.1.2 Oscillation stress sweep test 87 3.2.2 Accelerated test 93

3.2.2.1 Apparent viscosity 94 3.2.2.2 Particle size 96 3.2.2.3 pH 97

3.2.2.4 Conductivity 99

3.3 Formulation and stability of nano-cream 100 3.3.1 Pre-experimental condition 100 3.3.2 Nano-emulsion 101

3.3.3 Particle size 102

107 3.3.4 Zeta-potential

108

3.4.1 Study of interferences 108

3.4.2 Accuracy and precision 113

3.4.3 Prediction of shelflife 113

3.5 Determination of KDP solubility in THF:H2O solvent 115 3.4 High performance liquid chromatographic method for the

determination of KDP

116

3.7 In vivo study of kojic acid dipalmitate in normal and nano-cream 118

3.8 In vitro versus in vivo comparison 120

CHAPTER 4: DISCUSSION 122 CHAPTERS: CONCLUSION 141

CHAPTER 6: SUGGESTIONS FOR FURTHER WORK 143

REFERENCES 145 APPENDICES 162

253 PUBLICATION

3.6 In vitro study of kojic acid dipalmitate release from cream preparation

LIST OF TABLES

Page Some immiscible phases components (Rieger, 1996) 2 Table 1.1

Table 1.2 5

Factors included in formulations 70 Table 3.1

Pseudo components and measured responses 72

Table 3.2

Criteria of reference creams 73 Table 3.3

ANOVA table of apparent viscosity 74 Table 3.4

Table 3.5 74

ANOVA table of yield value 77 Table 3.6

78 ANOVA table of spreadability

Table 3.7

80 Table 3.8

Table 3.9 84

Table 3.10 87

Table 3.11 87

Table 3.12 93

Table 3.13 94

Results of standard deviation, mean, R2, adjusted R2, predicted R2 and adequate precision for apparent viscosity, yield value and spreadability

Predicted and observed responses for apparent viscosity, yield value and spreadability

Results of tan S, linear viscoelastic region (LVR) end point and crossing over points for fresh and freeze thawed FDI, FDW, FNW and FRW formulations (N= 3)

Statistical results of viscosity and oscillation stress sweep test in freeze thaw stability study

Results of particle size for the formulations FDI, FDW, FNW, and FRW at 5°C and 28°C for freshly prepared formulation and 6 months later

HLB values and its applications (Mollet and Grubenmann, 2001b)

Statistical results of formulations FDI, FDW, FNW and FRW together with viscosity, particle size, pH and conductivity at Solution given by Design-Expert® software with predicted parameter and the experimental (actual) results of optimized formulation

5°C and 28°C for 6 months Table 3.14 103

Within-day and Between-day accuracy and precision (N= 6) 113 Table 3.15

Table 3.16 115

Table 3.17 117

Composition of formulations, radius of droplets (nm), zeta potential and Ostwald ripening

Results of KDP solubility in different THF: H2O ratios using least-square method

The slope and the flux for KDP powder (N- 3), KDP released from Nano-cream (N= 4) and Normal cream (N= 3)

LIST OF FIGURES

Page Figure 1.1 11

Figure 1.2 20

Figure 1.3 30

Synthesis of kojic acid dipalmitate compound. R=13CH2 33 Figure 1.4

Figure 2.1 38

Ternary phase diagram 40

Figure 2.2

46 Figure 2.3

Figure 2.4 53

Figure 2.5 61

Figure 2.6 64

Figure 2.7 66

Figure 3.1 69

In vivo study steps, (a) Fixing Wistar rat to plat; (b) Shaving abdominal skin; (c) Marking area of study; (d) Placing formulation to the area; (e) Spreading and homogenizing the formulation; (f) Securing the application skin area with gauze and surgical tape

Chemical structure of sodium stearoyl lactylate. n has the average value of 2

Method of spreadability measurement, (a) Cut syringe to pre­

cast cream size; (b) Method of cream compression between glass plates

System used to prepare nano-emulsion by condensation method

Emulsion instabilities, (a) Coagulation; (b) Creaming; (c) Coalescence

Basic shear diagram of shear rate versus shear stress for flow behavior classification

Ternary phase diagram, (a) Screening. A-point=o/w emulsion;

B-point= w/o emulsion; C-point= gel, (b) Area of interest (o/w emulsion). X\= EK/PG; X?= VCO; Xj= water

Structure of the human skin (Skin Graft and Transplants, 2007)

Stripping technique, (a) Pressing skin with a roller; (b) Stripping with adhesive tape; (c) Pressing superglue with a ruler; (d) striped area (upper side)

The Franz Diffusion cell. A= Clipper; B= Donor compartment; C= Sampling port; D= membrane; E= Clipper;

F= Water jacket; G = Receiver compartment; H= Magnetic bar; 1= Magnetic stirrer

Figure 3.2 70

Figure 3.3 75

Figure 3.4 76

79 Figure 3.5

Figure 3.6 81

Figure 3.7 83

Figure 3.8 85

Figure 3.9 90

Figure 3.10 91

Figure 3.11 ₉₂

Figure 3.12 95

Figure 3.13 95

Viscosity (c.p.) versus time (month) for formulations FDI, FDW, FNW and FRW stored at 5°C for 6 months

Response Surface plots, (a) Apparent viscosity; (b) Yield value; (c) Spreadability as given by Design-Expert01’ software.

Xi= Emulium Kappa:Propylene glycol (9:1); VCO; %?=

De-ionized water

Normal probability plots of residuals, (a) Apparent viscosity;

(b) Yield value; (c) Spreadability

Contour plots, (a) Contour plots for apparent viscosity; (b) Contour plots for yield values; (c) Contour plots for spreadability; (d) Superimposed contour plots of three responses

Predicted versus actual values, (a) Apparent viscosity; (b) Yield value; (c) Spreadability

Storage modulus (G’) and Loss modulus (G”) versus Shear stress (Pa) for fresh and 2 week’s freeze-thawed formulations for (a) FNW and (b) FRW 04=3)

Storage modulus (G’) and Loss modulus (G”) versus Shear stress (Pa) for fresh and 2 week’s freeze-thawed formulations for (a) FDI and (b) FDW (N=3)

Factor and design area for formulation. X/=X’/= EK/PG;

Xi=X’2= VCO; deionized water

Shear rate versus shear stress for formulations, (a) FDI; (b) FDW; (c) FNW; (d) FRW. (FDI= formulation with de-ionized water, FDW= formulation with distilled water, FNW=

formulation with nano-water, FRW= formulation with reverse osmotic water)

Contour traces, (a) Apparent viscosity; (b) Yield value; (c) Spreadability; (d) Desirability. A= Emulium Kappa:

Propylene glycol (9:1); B= VCO; C= De-ionized water

Ternary phase with optimum combination optimized using Design-Expert'11’ software

Viscosity (c.p.) versus time (month) for formulations FDI, FDW, FNW and FRW stored at 28°C for 6 months

Figure 3.14 96

Figure 3.15 97

Figure 3.16 98

Figure 3.17 98

Figure 3.18 99

Figure 3.19 100

Figure 3.20 102

Figure 3.21 104

Figure 3.22 104

Figure 3.23 105

Figure 3.24 107

Figure 3.25 Chromatogram of KDP analysis in standard solution 109

Figure 3.26 109

Figure 3.27 110

Radius of droplet as a function of time for formulations with 14% (w/w) surfactant and 12.8% (w/w) oil with different Squalene proportions. (The formulation are listed in Table 3.14)

Stages of nano-emulsion formation of EK/PG /VCO/Squalene system by Emulsion Inversion Point method

Conductivity (ps) versus time (month) for formulations FD1, FDW, FNW and FRW stored at 28°C for 6 months

Conductivity (ps) versus time (month) for formulations FDI, FDW, FNW and FRW stored at 5°C for 6 months

pH versus time (month) for formulations FDI, FDW, FNW and FRW stored at 28°C for 6 months

pH versus time (month) for formulations FDI, FDW, FNW and FRW stored at 5°C for 6 months

Chromatogram of KDP analysis in sample solution of normal cream

Chromatogram of KDP analysis in sample solution of nano­

cream

Zeta-potential as a function of squalene concentration for formulation with 14% (w/w) surfactant and 12.8% (w/w) oil

Particle size D[3,4] (pm) versus time (month) for formulations FDI, FDW, FNW and FRW stored at 28°C for 6 months

Radius of droplet as a function of Squalene concentration for formulations with 14% (w/w) surfactant and 12.8% (w/w) oil

Particle size D[3,4] (pm) versus time (month) for formulations FDI, FDW, FNW and FRW stored at 5°C for 6 months

Ostwald ripening as a function of squalene concentration for formulation with 14% (w/w) surfactant and 12.8% (w/w) oil

Figure 3.28 Mean calibration curve of kojic acid dipalmitate 111 Figure 3.29 Linearity plot ofkojicacid dipalmitate 112

Figure 3.30 1 14

Figure 3.3 1 114

Figure 3.32 117

KDP release versus square root oftime(Min

Figure 3.33 118

Figure 3.34 Concentration of KDP (pg.mL1) against time (hr) for both 120 nano-cream and normal cream (N= 3)

Shelf life estimation of normal cream at room temperature with upper and lower acceptance criteria based on assay Shelflife estimation of nano-cream at room temperaturewith upper and lower acceptance criteria based on assay

Release profile of KDP powder (N= 3), KDP from nano­ cream (N= 4) and normal cream (N=3). Mean ± S.D.

°5)

LIST OF PLATES

Page Plate 3.1 SEM micrograph of VCO/w nano-emulsion prepared by 106

condensation method atdifferent magnifications

LIST OF EQUATIONS

Page

Equation (1.1) 4

Equation (1.2) 10

Equation (1.3) 1 1

Equation (1.4) 15

Equation (2.1) 42

Equation (2.2) 43

Equation (2.3) 43

Equation (2.4) 44

Equation (2.5) 44

Equation (2.6) 44

Equation (2.7) 45

Equation (2.8) 57

Equation (2.9) 57

LIST OF ABBREVIATIONS

Analysis of Variance ANOVA

Degree centigrade Centimeter

cm

Square centimeter Concentration cone.

Centipoises c.p.

Degree of freedom DF

Design-optimal D-optimal

Design of Experiment DOE

Emulsion Inversion Point EIP

Emulium kappa EK

Equation Eq.

Cream formulated with deionized water FDI

Cream formulated with distilled water FDW

Figure Fig

Cream formulated with nano-water FNW

Cream formulated with reverse osmotic water FRW

g Gram

Storage modulus

G’

G” Loss modulus

Hydrophile-lipophile balance HLB

HPLC High Performance Liquid Chromatography

hr Hour

cm2

°C

Hertz Hz

International Conference of Harmonization 1CH

Internal diameter i.d.

Kojic acid dipalmitate KDP

Permeation coefficient Kp

Liter L

pg.mL’1 Microgram per milliliter Microsiemens

gS

Minute min

Minutes mins

Milliliter mL

Millimeter mm

Methyl paraben MP

Millivolt mV

Number of replications N

Nanometer nm

Oil in water o/w

Probability P

Pascal Pa

Propylene glycol PG

Phase Inversion Temperature PIT

Propyl paraben PP

Correlation coefficient Residual Error

RE R2

Rotation per Minute time rpm

Residual Standard eviation RSD

Response Surface Methodology RSM

Second s

Standard deviation S.D.

Statistical Experimental Design SED

Scanning Electron Microscope SEM

Significant Sig.

Spreadability Sp.

Sum of squares SS

Stratum corneum SC

t. Time

Temperature T.

Tetrahydrofuran THF

United State Pharmacopoeia USP

Volt V

Virgin Coconut Oil VCO

Volume per volume v/v

Water in oil w/o

Weight per weight w/w

First component in mixture design (EK/PG) Xt

First pseudo-component in mixture design (EK/PG) Second component in mixture design (VCO)

X2

Second pseudo-component in mixture design (VCO) X'2

X't

Third componnt in mixture design (Deionized water)

Third pseudo-component in the mixture design (Deionized water) Response of apparent viscosity

Response of yield value Response of spreadability Y2

x 3

X’3

LIST OF APPENDICES

Page

Appendix 1 163

Appendix 2 164

Appendix 3 165

Appendix 4 166

Appendix 5 166

Appendix 6 Results of spreadability for commercial creams 167

Appendix 7 167

Appendix 8 Results of spreadability for the runs 172

Appendix 9 173

Appendix 10 Results of spreadability for solution 175

Appendix 11 176

Appendix 12 179

Appendix 13 181

Appendix 14 186

Results of oscillation stress sweep test of fresh and freeze- thawed formulations

Screening points; Xr- Emulium kappa: Propylen glycol (9:1);

AS: Virgin coconut oil; A): De-ionized water

Scanning points; Xr. Emulium kappa:Propylen glycol (9:1);

AS: Virgin coconut oil; Aj: De-ionized water

Rheometer results of solution (N= 3) at 0.1-100Pa of 50 linear steps shear stress, using cone and plate at 27°C

Rheometer results of the Runs (1-14 runs) at 0. l-100Pa of 50 linear steps shear stress, using cone and plate at 27°C

Results of independent t-test of apparent viscosity, yield value and spreadability of prediction and experiment

Rheometer results of formulations FDI, FDW, FNW and FRW freshly prepared and after 2 weeks of freeze-thawing

Boarder points; Xr- Emulium kappa:Propylen glycol (9:1);

AS: Virgin coconut oil; A): De-ionized water

Results of independent t-test of yield value, crossing over point, LVR end point and tan 8 for fresh FDI and after 2 weeks of freeze-thaw test

Rheometer results of Hazeline® cream at 0.1-200Pa of 50 linear steps shear stress using cone and plate at 27°C

Rheometer results of NIVEA® cream at 0.1-200Pa of 50 linear steps shear stress using cone and plate at 27°C

Appendix 15 190

Appendix 16 194

Appendix 17 198

Appendix 18 202

Appendix 19 214

Appendix 20 218

Appendix 21 238

Appendix 22 242

Appendix 23 246

Appendix 24 246

Appendix 25 247

Appendix 26 248

Appendix 27 Results of within-day and between-day validation 249 Results of one way ANOVA and Tukey-HSD test for pH of

freshly prepared FDI, FDW, FNW and FDW and after 6 months storage at 5°C and 28°C

Results of one way ANOVA and Tukey-HSD test for apparent viscosity of fresh FDI, FDW, FNW and FRW and after 6 months storage at 5°C and 28°C

Results of apparent viscosity, particle size (D(v, 0.1), D(v, 0.5), D(v, 0.9), D[4,3] and span), pH and conductivity of formulations FDI, FDW, FNW and FRW after six months storage at different temperature (5, 28 and 40°C)

Droplet diameter of formulations i, ii, iii, iv, v, vi and vii measured by zeta-sizer for 4 days at 28°C

Zeta-potential result of formulations i, ii, iii, iv, v vi and vii at 28°C

Results of independent t-test of yield value, crossing over point, LVR end point and tan 8 for fresh FDW and after 2 weeks of freeze-thaw test

Results of independent t-test of yield value, crossing over point, LVR end point and tan 8 for fresh FNW and after 2 weeks of freeze-thaw test

Results of independent t-test of yield value, crossing over point, LVR end point and tan 8 for fresh FRW and after 2 weeks of freeze-thaw test

Result of one way ANOVA and Tukey-HSD test for particle size (D(v, 0.1), D(v, 0.5,), D(v, 0.9), D[4,3] and span) of fresh FDI, FDW, FNW and FRW and after 6 months storage at 5°C and 28°C

Results of one way ANOVA and Tukey-HSD test for conductivity of freshly prepared FDI, FDW, FNW and FRW and after 6 months storage at 5°C and 28°C

Results of Within-day curve Results of Between-day curves

Appendix 28 250

Appendix 29 250

Appendix 30 251

Appendix 3 1 251

Appendix 32 252

Appendix 33 Results of the in vivo study for normal cream and nano­ 152 cream. The concentration (cone.) was measured using HPLC

analysis and the result was the mean of three runs (N=3) ± standard deviation (S.D.)

Results of KDP release from powder using Franz diffusion cell. The concentration (cone.) of KDP was measured using HPLC analysis and the result is the mean of three runs (N= 3)

± standard deviation (S.D.)

Results of shelf life data (peak high, concentration and percent) for normal and nano-cream

Mean calibration curve of KDP using spectrophotometer.

Mean ± S.D. (N= 3)

Results of KDP release from nano-cream using Franz diffusion cell. The concentration (cone.) of KDP was measured using HPLC analysis and the result is the mean of four runs (N= 4) ± standard deviation (S.D.)

Results of KDP release from normal cream using Franz diffusion cell. The concentration (cone.) of KDP was measured using HPLC analysis and the result was the mean of three runs (N= 3) ± standard deviation (S.D.)

ABSTRAK

Kappa® yang digunakan sebagai agen pengemulsi untuk menyediakan krim kosmetik.

Asid kojic dipalmitate [Kojic Acid Dipalmitale (KDP)] yang dilarutkan dalam VCO adalah suatu bahan pemutihan. Ciri terakhir formulas! krim bergantung pada nisbah fasa

pembolehubah utama. Rajah fasa ternari bersama grafik kontur digunakan untuk menilai

menggunakan model Scheffe. Kesan-kesan komponen pada kelikatan, nilai alah, dan keboleh sebaran {spreadability') yang jelas (kriteria utama) ditaksirkan melalui penggunaan perisian Design-Expert^. Penetapan kriteria formulas! terakhir dibuat berdasarkan ciri-ciri dua krim pemutih yang terdapat dalam pasaran. Kemudian, kestabilan formulas! terakhir ditaksirkan melalui penggunaan dua ujian kestabilan tercepatkan, iaitu ujian beku-nyahbeku selama dua minggu dan ujian tercepatkan klasik

penggunaan kaedah Emulsion Inversion Point (saiz partikel 300nm). Pertumbuhan Ostwald (Ostwald Ripening) adalah faktor yang mengurangkan kestabilan

Formulas!, Penilaian In vitro dan Penilaian In vivo terhadap Kosmetik Krim-Nano daripada Minyak Kelapa Tulen, Asid Kojik Dipalmitat dan Emulium

Kappa

{destabilizing) bagi emulsi nano yang boleh dikurangkan dengan cara menambahkan Minyak kelapa tulen {Virgin Coconut Oil-VCO) dalam air distabilkan oleh Emulium

{classical accelerated test) selama enam bulan. Krim nano disediakan melalui kesan-kesan perubahan pada pembolehubah. Sistem itu direka bentuk dengan minyak, agen pengemulsi/emulsi bersama dan air yang dianggapkan sebagai

minyak yang tidak boleh larut, iaitu skualena, kepada fasa minyak. VCO:skualena dengan nisbah 10:0, 9.8:0.2, 9.6:0.4, 9.4:0.6, 9.2:0.8, 9:1 dan 8:2 adalah dinilaikan.

Kestabilan emulsi nano dinilaikan melalui ciri-ciri elektroforesii- titisan-titisan emulsi.

Akhir sekali, KDP yang dimuatkan ke dalam krim nano dan krim biasa diuji untuk menentukan keupayaannya menembusi kulit tiruan dengan menggunakan sei pembauran Franz, sementara tingkah laku penyimpanan KDP dalam liang-liang bulu tikus Wistar dikaji dengan menggunakan teknik penanggalan pita {tape stripping technique').

Hasilnya menunjukkan bahawa Mixture Design, dengan dibantu oleh Design-Expert®, boleh digunakan untuk menambah baikkan formulas! krim yang terdiri daripada KDP, VCO dan EK. Tambahan pula, ujian freeze-thaw boleh dianggapkan sebagai ujian alternatif yang berkesan berbanding ujian-ujian klasik. Krim yang mengandungi air tanpa ion {de-ionized water - FDI) telah terbukti sebagai krim yang paling stabil.

Lagipun, pembahagian antara titisan-titisan secara berterusan adalah disebabkan oleh skualene dalam penurunan pertumbuhan Ostwald {Ostwald ripening). Nilai potensi zeta menjadi semakin bertambah apabila kadar peratusan skualena dipertingkatkan. Akhir sekali, tidak terdapat sebarang variasi yang signifikan pun antara krim nano dan krim biasa, dari segi pelepasan drug, pada nilai p 0.05, sementara KDP yang dimuatkan ke dalam krim nano menjadi terperangkap di dalam liang-liang bulu tikus selama > 7 hari dan KDP yang dimuatkan ke dalam krim biasa menjadi terperangkap selama < 3 hari, iaitu mengalami kadar pengurangan {depletion rate) yang lebih pantas.

ABSTRACT

® (EK) as an Virgin Coconut Oil (VCO)-in-water stabilized by Emulium Kappa

cosmetic cream. Kojic acid dipalmitate (KDP)

formulation depends on the ratio of the oil phase, emulsifier/coemulsifier and water which are considered as the main variables. Ternary phase diagram with contour graphics was used to assess the effects of variable changes. The system was designed by using Scheffe model. The effects of the components on the apparent viscosity, yield

software. The criteria of the final formulation were determined based on the properties of two commercially available whitening creams. Then, the stability of the final formulation was assessed by using two accelerated stability tests, namely the freeze­

thaw test for two weeks and classical accelerated tests for six months. Nano-cream was prepared by using Emulsion Inversion Point method (particle size 300nm). Ostwald ripening is the main destabilizing factor for nano-emulsion that can be reduced by the addition of non-soluble oil, namely squalene to the oil phase. VCO:squalene in the ratio of 10:0, 9.8:0.2, 9.6:0.4, 9.4:0.6, 9.2:0.8, 9:1, and 8:2 were evaluated. The stability of nano-emulsions was evaluated by the electrophoretic properties of the emulsion droplets.

Finally, KDP loaded into normal and nano-cream were tested for their capabilities to

Formulation, In vitro and In vivo Evaluation of Cosmetic Nano-cream from Virgin Coconut Oil, Kojic

Acid Dipalmitate and Emulium Kappa

emulsifier was used to prepare a

• • ®

value, and spreadability (the main criteria) were assessed by using Design-Expert dissolved in VCO was the whitening ingredient. The final characteristic of the cream

permeate through artificial skin using Franz diffusion cell, while the storage behavior of KDP in the hair follicles of Wistar rat was investigated using tape stripping technique.

The results indicated that the Mixture Design, with the aid of Design-Expert01’could be used successfully and efficiently to optimize cream formulation composed of KDP, VCO, and EK. Furthermore, freeze-thaw test could be considered as an efficient alternative test to the classical methods. Cream that contains deionized water (FDI) was proven to be the most stable. Moreover, continuous partitioning between the droplets due to squalene resulted in the decline of Ostwald ripening. The zeta-potential value increased as the percentage of squalene increased. Finally, no significant variation between normal and nano-cream, in terms of drug release, was found at p-value 0.05, while KDP loaded into nano-cream was trapped in the hair follicles for 7 days and KDP loaded into normal cream was trapped for < 3 days i.e. was subjected to a faster depletion rate.

CHAPTER 1: INTRODUCTION

1.1 Emulsions

A thermodynamically unstable dispersion of two immiscible liquid, such as water and oil, is called an emulsion (Imbert et al., 2002, Goodwin, 2004). The presentation of one of these two liquid is in the form of finely distributed spherical droplets in the second liquid i.e. the continuous phase. The emulsion is referred to as an oil-in-water (o/w) emulsion if the oil is dispersed in water (Frelichowska et al., 2009), while the reverse produces water-in-oil (w/o) emulsion. Table 1.1 lists a number of immiscible phase components (Mollet and Grubenmann, 2001b, Dickinson, 2009).

These disperse systems, in terms of free energy, are greater by the amount of surface energy if compared with that of macroscopically extended systems. Thus, coalescence

separation of the emulsion into different phases, which will be in a state of lower energy (Mollet and Grubenmann, 2001b, Goodwin, 2004). Furthermore, coalescence has greater practical significance than does sedimentation, in terms of stability issues, since droplets may exist collectively together for a long time without actually coalescing. Moreover, a third component is required, namely an emulsifier, in order to produce a stable emulsion i.e. a long lived technical emulsion (Rieger, 1996). A protective layer formed from the accumulation of the emulsifier at the interface must prevent the droplet from coalescing and this layer must be tough and elastic to enhance the stability of the emulsion.

Sometimes, mixtures of emulsifiers or emulsifier/co-emulsifiers emulsion properties (Block, 1996, Mollet and Grubenmann, 2001b).

are used to optimize can form as a result of droplet collisions in pure emulsions which can cause the

I

Table 1.1 Some immiscible phases components (Rieger, 1996)

Non polar ingredients

1.1.1 Emulsifiers

Rieger (1996) defined emulsifiers as “Amphiphilic compounds which are (i) soluble in at least one phase of the system, (ii) forming monolayers oriented at phase interfaces, (iii) exhibits equilibrium concentrations at phase interfaces higher than those in the bulk solution and forms micelles at specific concentrations and (iv) exhibits one or more of Phase_________

Polar ingredients

Examples__________ ___________________________________

Polyols

Butylene glycol Glycerin

Polyethylene glycol Propylene glycol Water

Esters Fats Lanolin

Synthetic e.g. isopropyl myristate and isopropyl palmitate Vegetable oil

Ethers

Perfluropolyether Polyoxypropylene Fatty acids

Fatty alcohols Hydrocarbons

Butane, propane Microcrystalline waxes Mineral oils

Petrolatum Squalene Miscellaneous

Halohydrocarbons e.g. perflurocarbons Waxes, plant and animal

Silicone fluids

the following characteristics: detergency, foaming, wetting, emulsifying, solubilizing and dispersing”.

1.1.1.1 Types of common emulsifiers

There are 4 types of common emulsifiers.

i) o/w emulsifiers (low molecular weight of hydrophilic nature):

a) Anionic: soaps e.g. (Na, K, NH4 and morpholinium salts of fatty acids), sodium lauryl sulfate, sodium mersolate,

laurylpyridinium chloride, positive charges

b) Cationic: they carry e.g.

lauryltrimethylammonium.

c) Nonionic e.g. polyoxyethylene fatty alcohol ethers.

ii) w/o emulsifiers (low molecular weight of lipophilic nature) such as magnesium stearate, magnesium oleate, aluminum stearate and calcium stearate.

iii) Less pronounced properties emulsifiers (low molecular weight) such as fatty acid esters of polyols and polyoxyethylene.

iv) High molecular weight emulsifiers: e.g. albumin, casein and gelatin.

(Rieger, 1996, Mollet and Grubenmann, 2001b).

1.1.2 Emulsion stabilizers

Emulsion creaming, droplet flocculation or coalescence can be inhibited after the emulsification process for the achievement of emulsion stabilization. This can be done by increasing the viscosity of continuous phase, equalizing phase densities and by adsorbing stabilizing substances at the oil-water interface (Rieger, 1996, Dickinson, 2009).

1.1.3 The Hydrophile-Lipophile Balance (HLB) system

Hydrophile-Lipophile Balance concept was introduced by Griffin in 1949 and developed in the 1950s. This concept has a mean of characterizing surfactant (Orafidiya and Oladimeji, 2002, Wu et al., 2004, Guo et al., 2006). HLB system provided the formulators with relevant information regarding emulsion formulation (Mollet and Grubenmann, 2001b, Ishii and Nii, 2005). A scale of surfactant lipophilicity (0-20) was provided by this HLB system that simplified the selection and blending of emulsifiers (Constantinides and Scalart, 1997). W/o emulsions can be obtained by using a surfactant with a low HLB (< 6), while o/w emulsions stabilization requires a higher HLB (> 8) (Table 1.2). Algebraic manipulation is necessary when a blend of surfactant, with a known HLB, is used for a particular emulsification (Rieger, 1996, Guo et al., 2006).

following equation:

HLBMixture-HLBi.g! + HLB2.g2 + Eq. (1.1)

are the mass fractions of the components.

gi, g2,

Thus, the HLB values of a mixture of emulsifiers, HLBMixture, are calculated by the

Table 1.2 HLB values and its applications (Mollet and Grubenmann, 2001b)

Lipophilic

hydrophilic

1.2 Cosmetics

Substances or preparations which are intended for external use or in the buccal cavity for

1991c, De Groot, 1997, Mitsui et al., 1997c, Kutting and Drexler, 2003). Cosmetics are used for curing, reducing and preventing physical damage and this is the difference from medicament in that every cosmetic treatment should start with cleansing that should

(Umbach, 1991b). Sometimes the distinction between cosmetics and medicament is difficult to interpret in terms of the above definitions e.g. sebum flow can be affected by skincare preparations (Mitsui et al., 1997c, Mollet and Grubenmann, 2001a).

1.2.1 Cosmetic preparations

be affected by cosmetics (Umbach, 1991a). This effect can be desirable or harmful, thus this factor must be considered carefully (Mitsui et al.,

Application Defoamers w/o emulsions Wetting agents o/w emulsions

Detergents Solubilizers HLB value

0-3 3-8 7- 9 8- 18 11-15 15-18

The physiology of the skin can

care, cleaning and to modify the appearance or odor are called cosmetics (Umbach,

remove germs, unwanted dirt and improve physiological and physical well-being

1997d). Emulsions, whether o/w or w/o, are particularly important in cosmetic

formulation. Due to the large number of raw materials, many combinations of emulsifiers can make up optimized products for particular applications such as (i) cosmetics for the skin, (ii) nail care, (iii) cosmetics for the hair and (iv) shaving aids (Rieger, 1996).

1.2.1.1 Emulsions in cosmetics

1.2.1.1(a) Types of emulsion

stable emulsion that is safe for the skin and meets modern

the hardest tasks to be accomplished in the field of cosmetics. Furthermore, it is very difficult to combine the stability and the modern requirements, thus the emulsion that

popular emulsions

evaporation of water, thus giving a good feeling to the skin (Miller et al., 1999, Sinko and Martin, 2006d). Moreover, o/w emulsions do not make the skin look very shiny and

consumers (Swarbrick and Boylan, 1996). On the other hand, w/o emulsion forms a thin film on the skin surface and this will control the dehydration of the cornified layer which makes this type of emulsion correspond closely to the physiological conditions of the skin since this is incorporated by the skin’s own fatty exudates (Mitsui et al., 1997a).

Finally, multiple emulsions, such as o/w/o or w/o/w, are those in which a dispersed requirements, which means higher stability and lower emulsifier concentration, is one of

soreness that might be caused from very stable emulsions (de Groot, 1998). The most tends to be unstable at higher temperature ranges may have good skin compatibility or

are o/w because these emulsions have initial cooling effects due to The development of a

are less likely to block pores. These properties will increase their acceptance by the

phase is contained within another dispersed phase and they contain at least two types of surfactants (Mollet and Grubenmann, 2001a).

1.2.1.1(b) Hydrocolloids

also act as protective colloids and consistency regulators (Mollet and Grubenmann,

gathering around the droplets and reinforcing their stabilizing layer (Sinko and Martin, 2006d).

1.2.1.2 Basic composition of cosmetic emulsion

The following ingredients are part of a cosmetic emulsion, (i) the oil phase, to which belongs the emulsifier system, consistency regulator, oil soluble preservatives and oil­

soluble antioxidant as well as the actual oil components (Mitsui et al., 1997d), (ip the aqueous phase, which makes up to 85-95% of the emulsion, containing water soluble preservatives and any humectants and thickeners and (iii) the remaining ingredients such as active substances, perfume oils and colorants (Mollet and Grubenmann, 2001a, Sinko and Martin, 2006d).

Hydrocolloids are gel-forming thickeners used to keep the emulsifier film firm, and can

2001a). Hydrocolloids are of two types, either organic or inorganic. Hydrocolloids are

1.2.1.3 Solutions

The defatting effect of washing can be counteracted by skin oils and fats which are used

lubricant for massaging (Mollet and Grubenmann, 2001a).

1.2.1.4 Gels

enclosed by a liquid forms gels (Gallegos and Franco, 1999, Sinko and Martin, 2006d).

Gels contain large amounts of glycerin (up to 20%). They are fat-free base used for plant extract and water. In addition, gels contain various gel formers such as gelatin and agar- agar.

1.2.2 Preservation of cosmetics

Contamination of cosmetics can be prevented by adding preservatives which suppress the proliferation of microorganisms and kill them in time (Soni et al., 2001, Atemnkeng et al., 2007). However, it is necessary to use as small amount of preservatives as possible to decrease their adverse effects on human beings (Mitsui et al., 1997b).

Routinely, parabens are first used as antimicrobial preservatives in the mid 1920s, with methyl and propyl-paraben being the most commonly used (Soni et al., 2005). Parabens are widely used in cosmetics and pharmaceutical products because they have no taste, no as solvents for active substances. These solutions are also intended to soften, smooth and

Gels are solid or semisolid systems of at least two components. As condensed mass protect the skin. They can also serve as

odor, low toxicity, broad spectrum of action, neutral pH, do not cause the discoloration of the product and are cheap (Soni et al., 2005, Polati et al., 2007).

1.3 Rheology

Rheological and mechanical properties reflect the response of pharmaceutical materials to an externally applied stress (Korhonen et al., 2000, Jimenez Soriano et al., 2001).

Rheology is the study of this response, while Rheometry or Viscometry is the application of measurement techniques and instrumentation. By definition, rheology is the study of the flow and deformation of matter (Barry, 1971, Khunawattanakul et al., 2008). When pharmaceutical materials are subjected to the externally applied stress, they undergo flow or deformation e.g. creams, ointments, foams and compacted powders.

The parameters which describe the viscoelastic properties of a system are of particular significance. There are two types of pharmaceutical system deformation: (i) flow (irreversible deformation) and (ii) elasticity (spontaneously reversible deformation) (Radebaugh, 1988, Tamburic et al., 1996, Korhonen et al., 2001).

1.3.1 The elements of rheology

its liquid equivalent (shear rate) and time can describe the elementary rheological properties of most materials.

Stress: is defined as the internal force acting on the area of the cube of the material. Since this force acts to balance out the applied force and keeps the Three parameters namely stress, strain in solids or

material cube in equilibrium, it is defined as an internal force. There are two types of stress, normal and shear stress. Pascal (Pa) is a unit of shear stress.

Strain: is the relative deformation of a solid body in response to a stress.

n.

Elongation or compression strain and shear strain are the two types of strain.

Shear strain is unitless.

Time: is the third parameter. Rheological properties of material can be affected iii.

by time. Reciprocal time is the unit for shear rate. The response to stress depends

magnitude of stress.

1.3.2 Elasticity and viscosity

The interaction between stress and either strain or shear rate yields a very important relationship. Elasticity is the proportionality constant between stress and strain and the unit of measure is Pascal (Pa) since strain is unitless. Elasticity can also be referred to as

known as viscosity which represents the relationship between shear stress and shear rate.

Viscous modulus is also known as loss modulus (G”) and has Pascal second unit (Pa.s).

Viscosity, q, is calculated using the following equation:

Eq. (1.2)

Where cr is shear stress and y is shear rate.

a

on both the length of time the material is subjected to the stress and the

storage moduli (G’). On the other hand, a measure of a liquid resistance to flow is

A combination of viscous and elastic properties is termed viscoelasticity (Radebaugh,

Eq. (1.3)

1.3.3 Fluid flow behavior

The basic shear diagram of shear rate versus shear stress is shown in Fig 1.1. Fluids for which viscosity remains consistent regardless of shear rate and shear stress are known as Newtonian fluids (Rao, 1999, Muller-Goymann, 2004). While fluids for which the viscosity depends on shear stress or shear rate are said to show non-Newtonian behavior and are classified as dilatants, peudoplastic and plastic as shown in Fig 1.1 (Radebaugh,

1988, Liang et al., 2008).

Bingham plastic

Shear stress

Figure 1.1 Basic shear diagram of shear rate versus shear stress for flow behavior classification

Shear thickening (Dilatants) e.g. beach sand

Newtonian fluids e.g. water

Shear thinning (pscudoplastic) e.g. paint

I

1988). The tangent between G” and G’ defines the phase angle as:

tan 5 = £

1.3.3.1 Newtonian behavior

In Newtonian behavior, the plot begins at the origin and there is a direct proportional relationship between shear rate and shear stress. Compounds of low molecular weight represent typical Newtonian fluids e.g. sugar solution (Rao, 1999, Muller-Goymann, 2004). Usually, there are very few true Newtonian fluids i.e. very few liquids exhibit a constant viscosity at all shear rates (Radebaugh, 1988).

1.3.3.2 Non-Newtonian behavior

A wide range of behavior is displayed by non-Newtonian fluid. In this type of fluid, viscosity is not directly proportional to the shear rate (Radebaugh, 1988, Liang et al., 2008).

1.3.3.2(a) Plastic flow

They termed plastic or viscoelastic flow because they only deform elastically and reversibility. Initial stress (yield value) is required to generate the flow. There are two types of plastic flow (i) Bingham behavior corresponds to that of a Newtonian liquid but the plot does not begins at the origin (Radebaugh, 1988) and (ii) Casson’s curve. The simplest non-Newtonian rheological behavior is exhibited by a pure Bingham liquid (Fig

1.1).

1.3.3.2(b) Pseudoplastic flow

Fig 1.1 presents pseudoplastic behavior of many emulsions, dispersions and polymeric solutions (Muller-Goymann, 2004). Commonly, pseudoplastic flow are called shear-

but it convexes upwards with shear-thinning fluids (Liang et al., 2008). Shear stress

shear stress increased and no yield value is required to start the flow. Most non­

Newtonian fluids exhibit shear thinning behavior.

1.3.3.2(c) Dilatant flow

Dilatant flow is also called shear-thickening behavior. The curve begins at the origin of the shear stress-shear rate plot but it concaves downwards. Shear stress increase gives a less proportional increase in shear rate. The viscosity increased as the shear stress increased. Dilatancy implies an increase in the volume of the sample during the test (Rao, 1999, Liang et al., 2008).

1.3.3.3 Time-dependent behavior

Emulsions are said to exhibit thixotropic flow behavior when they exhibit time­

dependent shear thinning behavior (Rao, 1999, Jimenez Soriano et al., 2001, Liang et al., 2008). Thus, a reversible time-dependent decrease in viscosity at constant shear rate is defined as thixotropy (Barry, 1971). The breakdown and the re-forming of gel- thinning (Rao, 1999). The curve begins at the origin of the shear stress-shear rate plot

increase gives a more proportional increase in shear rate. The viscosity decreased as the

solution-gel structure is the mechanism of thixotropy (Radebaugh, 1988). Gelatin, examples of thixotropic materials.

Thixotropy can be quantified by using several proposed methods. One of these proposed methods is the area of hysteresis loop (Barry, 1971, Jimenez Soriano et al., 2001).

Anti-thixotropy or negative thixotropy is the time-dependent increase in viscosity at 1-10% (v/v) solid shows negative thixotropy that is in contrast with dilatants systems which contain more than 50% (v/v) solid. A phenomenon in which a solution forms a gel when gently shaken or sheared is known as rheopexy which corresponds to negative thixotropy (Radebaugh, 1988).

1.3.4 Yield value

Yield value is a threshold value of stress after which the materials start to flow. Yield value only exists in Plastic flow while it is zero in Newtonian, Pseudoplastic and Dilatant flow. Yield stress value is a concept that is useful in pharmaceutical process design, modeling and sensory assessment (Rao, 1999).

1.3.5 Apparent viscosity

shear (shear stress-shear rate) diagram (Rao, 1999). Viscosity is not constant for non­

shear stress applied.

Apparent viscosity can also be calculated from equation 1.2 with some modifications:

Newtonian fluids because viscosities are changing depending on mayonnaise and many emulsion systems are

constant shear rate. Dispersion that contains

Apparent viscosity is a viscosity at any given shear rate that can be obtained from basic

1

Eq. (1.4)

Where rjj is the viscosity at a given shear rate py.

1.4 Optimization in pharmaceutical formulation

1.4.1 Pharmaceutical experimental design

The Design of Experiment (DOE) or Statistical Experimental Design (SED) is a concept for the planning of informatics experiments which can be used in many formulations (Martinello et al., 2006). In pharmaceutical technology, DOE is recommended greatly (Huisman et al., 1984). DOE requires prior knowledge of the procedure used so that a robust and valid statistical model, for the examined factors, can be achieved (Srinivasan et al., 2000) with a minimum number of experiments i.e. minimum time, resources and effort (Loukas, 1998, Petrovic et al., 2006, Raj in et al., 2007). For stable and effective dosage forms development, careful selections of integral components are essential which

cream formulations, DOE plays a vital role in product development, because it is not easy to predict the optimum values of the formulation properties, such as spreadability and viscosity (Contreras and Sanchez, 2002).

a

can be achieved through pre-formulation studies (Mura et al., 2005). In the cosmetic

1.4.1.1 Experimental design protocol

Screening is usually carried out at the first stage in order to reduce the number of factors and to determine the important outcomes under which both squared and interaction terms in the model are of interest; while optimization is mostly carried out after screening, thus the best setting for the important variables are determined. These two elements (i.e. screening and optimization) are considered as the main elements of the DOE concept (Martinello et al., 2006, Rispoli and Shah, 2007, Sayyad et al., 2007, Zivanovic et al., 2008). Due to the involvement of multivariable process parameter, the optimization process is considered as

Furthermore, optimization process involves three major steps (i) performing the statistically design experiments, (ii) estimating the coefficient in mathematical model and (iii) predicting the response and checking the adequacy of the model (Srinivasan et al., 2000).

1.4.1.2 Techniques of experimental design

There are several techniques of DOE used for formulation development, such as Cross Technique, Factorial Design and Mixture Design (Rajin et al., 2007). Factorial Design is the most popular experimental design used to study the systems having independent factors (Huisman et al., 1984, Loukas, 1998, Raj in et al., 2007) and to determine the relationship between two or more components (Contreras and Sanchez, 2002). In the mixture components, the ratios of the components are dependent on one another, where a tedious process (Sayyad et al., 2007).

the sum has to be equal to 1 or 100% (Huisman et al., 1984, Mura et al., 2005, Rajin et al., 2007, Rispoli and Shah, 2007). In addition, mathematical model has to be used too.

1.4.1.3 Mixture Design

Mixture Design has been used to explore how much change, in a mixture composition, will affect the properties of the mixture (Huisman et al., 1984, Mura et al., 2005, Martinello et al., 2006) and it has been adopted to optimize the composition of the systems to describe the response as a function of the mixture composition by means of a mathematical model (Huisman et al., 1984, Patel et al., 2007, Rajin et al., 2007, Rispoli

be represented by an equilateral triangle of two dimension space (Loukas, 1998, Patel et al., 2007, Zhu et al., 2008). The relationship between the formulation variables was investigated effectively by Statistical Mixture Design (Rajin et al., 2007).

1.4.1.3(a) Response surface methodology

It is important to obtain knowledge about potential physical and chemical interaction between mixture components so as to rapidly accelerate drug development (Mura et al., 2005) and this can be achieved by using Response Surface Methodology (RSM) (Martinello et al., 2006, Sayyad et al., 2007) in order to visualize and select optimal condition immediately (Martinello et al., 2006, Rispoli and Shah, 2007, Sayyad et al., 2007, Zivanovic et al., 2008). In the 1950s, Response Surface Methodology (RSM) was and Shah, 2007, Zhu et al., 2008). For a three-component system, Mixture Design can

developed by Box and Wilson (Khoo and Chen, 2001). Response surface contour can be

al., 1984). Response surface plots clearly show the influence of two factors on recovery value in the investigated area and are presented in three dimensional spaces (Zivanovic et al., 2008). The examination of these three dimension graphs may help to determine a region with acceptable values of responses (Huisman et al., 1984) because RSM combines experimental design and statistical technique for model optimization and building (Khoo and Chen, 2001). Moreover, linear or quadratic effect of experimental variables and the response can be mapped onto the surface contour plot (Khoo and Chen, 2001, Sayyad et al., 2007).

1.4.1.3(b) Computer software

In pharmaceutical industry, computer software can be used with DOE (Martinello et al., 2006, Ismail et al., 2008). An example of such software is Design-Expert® which has been much described by many authors (Srinivasan et al., 2000, Petrovic et al., 2006,

simultaneously, efficiently and very accurately (Khoo and Chen, 2001). Therefore, Design-Expert® was used in this study. Design-Expert® can screen for vital factors and locate ideal process settings to discover optimal product formulations.

depicted only after the discovery of acceptable statistical model function (Huisman et

Raj in et al., 2007). In reality, these software can analyze multi-responses

1.4.1.3(c) Ternary phase diagram

It is important to point out that most of the three components of Mixture Design employ ternary phase diagram in the pre-formulation study. This ternary phase diagram was described by many researchers (Wu et al., 2001, Minardi et al., 2002, Shafiq et al., 2007, Shah et al., 2007, Dixit and Nagarsenker, 2008, Zhu et al., 2008). Phase diagram

construction of ternary phase diagram is usually time consuming, particularly, to delineate a phase boundary. Pseudo-ternary phase diagram is useful for the identification of the region of interest e.g. o/w emulsion region (Shafiq et al., 2007).

1.5 Stability study of cream formulation

Cream is a liquid that is dispersed through external liquid phase in the form of small droplets either o/w or w/o containing one or more drug substances dissolved or dispersed in suitable base. Cream is complex and the thermodynamically unstable semisolids dosage forms a system, due to physicochemical interaction, hydrodynamic interaction, micelles formation and liquid crystalline formation (Block, 1996, Peramal et al., 1997, Jimenez Soriano et al., 2001, USP, 2005, Buhse et al., 2005, Masmoudi et al., 2005, Florence and Attwood, 2006, Salvador et al., 2007). Creams should be stabilized by emulsifiers (surfactants) with a range of oil (Miller et al., 1999, Korhonen et al., 2001).

The mechanism of surfactant stabilization is by forming monolayer at the droplet surface which reduces the interfacial tension that reduces the possibility of collision (Wu et al., 2004). Recently, cosmetics creams have been restricted to o/w emulsions because they can capture the relationship between a mixture phase behavior and its composition. The

aesthetically acceptable (USP, 2005, Sinko and Martin, 2006d).

1.5.1 Cream instabilities

Cream system instability may involve (i) creaming or sedimentation: as a result of disparities in densities (Manoj et al., 2000, Mollet and Grubenmann, 2001b, Masmoudi et al., 2005, Florence and Attwood, 2006, Sinko and Martin, 2006d), (ii) flocculation and coagulation of the dispersed liquid droplets (Miller et al., 1999, Masmoudi et al., 2005, Florence and Attwood, 2006), (iii) coalescence leading to the breaking of the emulsion: the emulsion is only disrupted and fused when the droplets coalesce (Block, 1996, Mollet and Grubenmann, 2001b, Masmoudi et al., 2005) and (vi) phase inversion (Sinko and Martin, 2006d). Some types of cream instabilities are shown in Fig 1.2.

Dispersed liquid phase

(a) (b) (c)

Continuous liquid phase

Figure 1.2 Emulsion instabilities, (a) Coagulation; (b) Creaming; (c) Coalescence are easily water washable; they do not stain clothes and they are more cosmetically and

1.5.2 Methods of stability evaluations

Cream stability, initially, can be evaluated by testing the samples from laboratory batches. They are usually based on the instability acceleration technique which may necessitate complex analytical methodologies (Mollet and Grubenmann, 2001b, COLIPA, 2004, Stiller et al., 2004, USP, 2005, Masmoudi et al., 2005, Florence and Attwood, 2006, Sinko and Martin, 2006d, Salvador et al., 2007) Many methods are

(Masmoudi et al., 2005). The manufacturer should develop proper stability data for his product and to consider many external conditions that can affect potency, purity and quality (COLIPA, 2004, USP, 2005). The stability of creams must be considered in terms of physical and chemical stability which are of practical consequences (Block, 1996, Di Mambro and Fonseca, 2007). It must be done to assure the (i) stability and physical integrity under appropriate condition of storage, transportation and use (ii) chemical stability, (iii) microbiological stability and (vi) the functions and aesthetics.

The stability of emulsion may be affected by additives (e.g. preservatives, coloring agents, etc.) (Florence and Attwood, 2006).

1.5.3 Factors affecting cream stability

The instability of cream depends heavily on temperature since temperature changes the interfacial tension between the phase, viscosity, solubility of emulsifier in both phases and the thermal motion of particle (Mollet and Grubenmann, 2001b). Therefore, accelerated stability tests like heating/cooling cycle and freeze-thaw cycle have been applied to evaluate the destabilization process but none is actually recognized

I

employed for stability testing of cream (Block, 1996). Freeze-thawed stability testing is the only predictive accelerated testing methodology being applied because the destabilizing process functions only during the freezing and thawing and not during the storage under frozen condition (Block, 1996). Due to the short development cycle of cosmetic product, this type of accelerated test

stability. However, it does not provide kinetic data necessary to estimate shelf life (Block, 1996, COLIPA, 2004). Combined analytical techniques, including HPLC methodology, are used to obtain chemical stability data over time (Guaratini et al., 2006). This is because rapid chemical and physical decomposition/changes in the formulation may happen due to thermal variation and can usually be detected by quantification of some parameters such as viscosity, solubility, particle size, pH and conductivity over time. Conductivity is the most sensitive technique applied for the physical changes (Bjerregaard et al., 1999, Stiller et al., 2004, Masmoudi et al., 2005, Guaratini et al., 2006). The duration of the stability test depends on the product storage period: usually 6 months stability study has to be carried out for products that stored > 6 months, but the storage period of stability study of 6 months is determined case-by-

relatively short and it is important that new products are marketed as quickly as possible

amenable to rapid, quantitative, measurement and can serve as the basis for quality control or stability indicating methodology (Block, 1996, Marquardt and Sucker, 1998, Florence and Attwood, 2006, Guaratini et al., 2006).

was developed to enable the prediction of

(COLIPA, 2004, Masmoudi et al., 2005). The viscoelastic properties of emulsion are case (Block, 1996, USP, 2005), for example, the development cycle of cosmetic is

I

1.5.4 Shelflife prediction

Shelf life is the suitability of a drug that could be determined by an acceptance criterion throughout its re-test period, i.e. the combination of chemical, physical, biological and microbiological tests. The expiration date is the date placed on a drug product container label to design the time after which it must not be used and prior to which (if stored under defined condition) a batch of the product is expected to remain within the approved shelflife specification. The acceptance criteria is usually a 5% change in assay from its initial value (1CH, 2003).

only chemical parameter is not comprehensive especially for cosmetic formulation where physical stability is of utmost importance and other parameters should be analyzed also (Guaratini et al., 2006).

1.6 Nano-emulsions

1.6.1 Definition

Nano-emulsions are oil-in-water (o/w) or water-in-oil (w/o) transparent or translucent colloidal dispersions, diameter of droplets usually in the 20-500nm size range (Santos- Magalhaes et al., 2000, Porras et al., 2004, Usn et al., 2004, Al-Edresi and Baie, 2009) ,

droplet (Fernandez et al., 2004, Solans et al., 2005, Maestro et al., 2006, Anton et al., 2007). The interest on studies of this type of emulsion began in the early 19th century, but it exploded recently due to cosmetic and pharmaceutical applications of novel formed by the dispersion of one liquid phase into the second liquid phase to form a The prediction of shelf lives on

systems generating nano-particles (Anton et al., 2007, Kamiya et al., 2008). Nano­

emulsions also are known as miniemulsions (Fernandez et al., 2004, Tadros et al., 2004, Solans et al., 2005, Liu et al., 2006, Maestro et al., 2006, Anton et al., 2007), fine disperse emulsions (Liu et al., 2006), submicron emulsions (Fernandez et al., 2004, Solans et al., 2005, Liu et al., 2006, Maestro et al., 2006), ultrafine emulsions (Fernandez et al., 2004, Solans et al., 2005, Porras et al., 2008), translucent emulsions (Fernandez et al., 2004, Ee et al., 2008), emulsoides (Maestro et al., 2006) and unstable microemulsions (Maestro et al., 2006).

1.6.2 Stability of nano-emulsions

Nano-emulsions have a long term kinetic stability due to their very small droplet sizes, (Tadros et al., 2004, Solans et al., 2005, Liu et al., 2006, Maestro et al., 2006) which result in a large reduction in the gravitational force. Thus, Brownian motion suffices to

prevent sedimentation and creaming during storage.

1.6.3 Benefits of nano-emulsions

Nano-emulsion is an attractive system for many industrial applications (Wang et al., 2007, Gutierrez et al., 2008) due to their purity, simplicity (Sonneville-Aubrun et al., 2004), the ability to sterilize them through filtration and the increased bioavailability of drugs solubilized in them (Wang et al., 2007, Kotyla et al., 2008). These properties overcome gravity (Betz et al., 2005, Solans et al., 2005, Maestro et al., 2006) and