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Electronic Theses and Dissertations Graduate School

2019

Optimization and Characterization of Hot-Melt Extruded Anti-Optimization and Characterization of Hot-Melt Extruded Anti-

Inflammatory and Local Anesthetic Bio-Adhesive Semisolid Inflammatory and Local Anesthetic Bio-Adhesive Semisolid

Formulation Using Design of Experiments (DoE) Formulation Using Design of Experiments (DoE)

Rishi Chinmay Thakkar University of Mississippi

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“OPTIMIZATION AND CHARACTERIZATION OF HOT-MELT EXTRUDED ANTI-

INFLAMMATORY AND LOCAL ANESTHETIC BIO-ADHESIVE SEMISOLID

FORMULATION USING DESIGN OF EXPERIMENTS (DOE)”

A Thesis

Presented for the

Master of Science

Pharmaceutical sciences emphasis Pharmaceutics and Drug delivery

Degree

The University of Mississippi

Rishi Thakkar

May 2019

Copyright © 2019 by Rishi Thakkar

All rights reserved

ii

ABSTRACT

Hot melt extrusion is a versatile continuous manufacturing process extensively investigated for its

applications with production of oral solid dosage forms, the aim of this study was to venture the

applicability of HME in continuous manufacturing of topical semi-solid ointment formulations.

Novel combination of a topical corticosteroid (Triamcinolone Acetonide) and local anesthetic

(Lidocaine hydrochloride) were selected to be formulated with a water-soluble ointment base

consisting of PEG 4000, PEG 1500 and Propylene glycol after performing appropriate drug-

excipient compatibility studies. To determine the ratios of the solid to liquid components of the

macrogol base, ‘quality by design’ approach was employed by using design of experiments for

formulation selection. Three formulations were selected using texture (work of adhesion and

stiffness), pH and drug content uniformity as critical quality attributes from the design space of

the formulation. These three selected formulations were then produced by conventional fusion

method and simultaneously by HME using a modified screw configuration. Produced ointments

were subjected to further characterizations including texture analysis (work of adhesion and

stiffness), pH, drug content uniformity of the formulations, differential scanning calorimetry and

finally to exhibit the release profile of the formulation in vitro drug release testing was conducted.

All the final formulations depicted characteristics parallel to the set Quality Target Product Profile.

Moreover, Formulations prepared by HME displayed better texture, uniformity and drug release

characteristics in contrast with conventionally prepared ointments and hence HME can be

considered as a useful continuous manufacturing technique for semi-solid manufacturing.

iii

DEDICATION

I would like to dedicate this thesis to my great grandmother (Maa), grandmother (Shobhana

Thakkar) and mother (Anjana Thakkar), three generations of strong women who brought me up,

my father, Chinmay Thakkar and my siblings, Drona and Gautami.

iv

ACKNOWLEDGMENTS

I would like to express my deepest regards and gratitude to Dr. Michael Repka for taking me under

his wing, believing in me, training me and guiding me throughout my master’s degree. Dr. Repka

has extended his constant support, time and valuable advice to me to overcome all kinds of

obstacles I faced during my time here at Ole Miss.

I am grateful to Dr. Walter Chambliss for agreeing to be a part of my committee and lending me

his insights and support during my thesis project. I am extremely thankful to Dr. Eman Ashour for

her round the clock involvement in my thesis project and her faith in me as a graduate student.

I am grateful to all the faculty and staff in the School of Pharmacy, especially Dr. Suresh Bandari

and Ms. Deborah King for their advice and assistance. I am indebted to my supervisors and friends

at the Graduate school, especially Dr. Christy Wyandt and Dr. Robert Doerksen for their mentoring

and Ms. Michelle Dickson for letting me work on my thesis during office hours.

I would like to express my gratitude to Dr. Narasimha Murthy and his research group for their

involvement and assistance in my research project.

Special thanks to my friends Amit Pillai, Ashay Shukla, Rui Wang, Pranav Ponkshe, Ruchi

Thakkar and my lab mates especially senior graduate students for their kind support during my

research project.

v

TABLE OF CONTENTS

ABSTRACT .................................................................................................................................... ii

DEDICATION ............................................................................................................................... iii

ACKNOWLEDGMENTS ............................................................................................................. iv

LIST OF ABBREVIATIONS ....................................................................................................... vii

LIST OF TABLES ......................................................................................................................... ix

LIST OF FIGURES ....................................................................................................................... xi

CHAPTER I: INTRODUCTION .................................................................................................... 1

Hot Melt Extrusion.................................................................................................................... 1

Active Pharmaceutical Ingredients.......................................................................................... 2

Design of Experiments .............................................................................................................. 4

CHAPTER II: METHODOLOGY ................................................................................................. 7

Materials .................................................................................................................................... 7

Chemicals ............................................................................................................................... 7

Equipment and auxiliaries .................................................................................................... 7

Methods ...................................................................................................................................... 8

Drug-Excipient compatibility studies .................................................................................. 8

Design of Experiments........................................................................................................... 9

Manufacturing of selected formulations............................................................................ 10

pH .......................................................................................................................................... 12

Texture analysis ................................................................................................................... 12

Drug-content uniformity ..................................................................................................... 13

vi

Method of analysis ............................................................................................................... 13

Differential scanning calorimetry ...................................................................................... 14

In vitro release testing (IV-RT) ........................................................................................... 15

CHAPTER III: RESULTS AND DISCUSSION .......................................................................... 20

Drug-Excipient compatibility ................................................................................................. 20

Screening of formulations ....................................................................................................... 22

Analytical Method Validation ................................................................................................ 29

Optimization and Manufacturing processes ......................................................................... 30

Differential scanning calorimetry .......................................................................................... 31

In vitro release testing (IV-RT) .............................................................................................. 32

CHAPTER IV: CONCLUSION ................................................................................................... 40

LIST OF REFERENCES .............................................................................................................. 41

VITA ............................................................................................................................................. 45

vii

LIST OF ABBREVIATIONS

TAA Triamcinolone Acetonide

LDH Lidocaine Hydrochloride

PEG Polyethylene Glycol

PG Propylene glycol

ACN Acetonitrile

PBS Phosphate buffer solution/saline (0.1M, pH 7.4)

HME Hot Melt Extrusion

QbD Quality by Design

DoE Design of Experiments

TA Texture analysis

HPLC High pressure/performance liquid chromatography

UV/VIS Ultraviolet/Visible spectroscopic detection

FT-IR Fourier Transform Infrared Spectroscopy

HSM Hot Stage microscopy

DSC Differential Scanning Microscopy

RPM Rotations/revolutions/rate per minute

FDC Franz-Diffusion cells

IV-RT in vitro release testing

IV-RR in vitro release rate

viii

QTPP Quality target product profile

CQA Critical Quality Attribute

BCS Biopharmaceutical classification system

API Active pharmaceutical ingredient

DF Degree of freedom

ix

LIST OF TABLES

Table 1. QTPP and CQA for 0.1% TAA and 2% LDH Ointment. ................................................ 4

Table 2. Compositions of various vials exposed to accelerated stability storage conditions for the

determination of drug-drug/drug-excipient compatibility. ............................................................. 8

Table 3. I-optimal, coordinate exchange, randomized, 16 runs design with different compositions

PEG, PG and GantrezTM. ................................................................................................................ 9

Table 4. Processing parameters maintained for the manufacturing of ointment by Hot melt

extrusion. ....................................................................................................................................... 12

Table 5. Parameters and set values for the texture analysis of prepared semisolid formulations. 13

Table 6. Parameters for the modified HPLC method. .................................................................. 14

Table 7. Composition of various vials for solubility studies ....................................................... 15

Table 8. Composition of various sample tubes taken for analysis with respective membranes used

for the membrane inertness studies. .............................................................................................. 16

Table 9. Weight of the formulations placed in the individual cells ............................................. 18

Table 10. Preliminary screening of the formulations based on CQA .......................................... 22

Table 11. ANOVA of the tested formulation for work of adhesion ............................................ 22

Table 12. Fit statistics for the design............................................................................................ 23

Table 14. ANOVA of the tested formulations for stiffness ......................................................... 25

x

Table 15. Fit statistics for the design............................................................................................ 26

Table 16. Coefficients in terms of coded factors ......................................................................... 26

Table 17. Selected formulations and their characteristics. ........................................................... 31

Table 19. Membrane inertness studies. ........................................................................................ 33

xi

LIST OF FIGURES

Figure 1. Structure of Triamcinolone acetonide ............................................................................ 2

Figure 2. Structure of Lidocaine hydrochloride ............................................................................. 3

Figure 3. Modified screw design for manufacturing of the ointment formulation. ..................... 11

Figure 4. assembly of a vertical Franz-diffusion cell[28]. ............................................................. 17

Figure 5. a) Assembly of the dissolution apparatus and immersion, b) Packing of ointment into

the immersion cell[30] .................................................................................................................... 19

Figure 6. FT-IR of Triamcinolone acetonide with various excipients ......................................... 20

Figure 8. Two component mix plots with varying ratios of PEG and PG in the formulations .... 24

Figure 9. Predicted versus actual values of work of adhesion for the formulations .................... 25

Figure 10. Two component mix plots with varying ratios of PEG and PG in the formulations .. 27

Figure 11. Actual versus Predicted plot for the values of stiffness for various prepared

formulations .................................................................................................................................. 28

Figure 12. Manufacturing process of Ointment formulations using HME .................................. 30

Figure 13. DSC profiles of pure API, excipients and prepared Ointment formulations. ............. 32

Figure 14. Membrane validation for TAA ................................................................................... 34

Figure 15. IV-RR versus dose strength of TAA .......................................................................... 34

xii

Figure 16. Membrane validation of LDH .................................................................................... 35

Figure 17. IV-RR versus Dose strength of LDH ......................................................................... 36

Figure 18. Drug release profile of TAA from F2H and F2C ....................................................... 37

Figure 19. Drug release of LDH from F2H and F2C ................................................................... 37

Figure 20. Drug release profile of TAA from F3H and F3C ....................................................... 38

Figure 23. Drug release profile of LDH from F8H and F8C ....................................................... 39

1

CHAPTER I: INTRODUCTION

Hot Melt Extrusion

Hot melt extrusion is one of the most widely utilized techniques in the Plastic industry. It involves

melting, mixing and conveying of raw materials using rotating twin screws at a suitable processing

temperature. The process results in production of uniformly shaped product propelled out of the

die[1]. HME has been exploited by several pharmaceutical industries and research groups for its

versatility in the manufacturing of pharmaceutical products[2][3]. The technique has found

application in production of amorphous solid dispersions for improving the solubility and hence

bioavailability of BCS class II API[4], formulation of abuse deterrent formulations[5][6], Taste

masking of geriatric and pediatric formulation[7][8], topical, trans dermal and trans mucosal drug

delivery systems[9][10][11]. A key aspect of this process is ‘continuous manufacturing’ which reduces

the time and resources invested in batch manufacturing and hence enhances the productivity and

in turn efficiency of the process. In this research project, a manufacturing process using HME for

the Continuous manufacturing of a topical semi-solid ointment formulation was optimized. To

accomplish this, certain attributes of Quality by Design (QbD) which are extensively suggested by

the regulatory bodies for a process or product development were used. Specifically, Design of

Experiments (DoE) which is a statistical tool used to apply QbD was used for this research project.

By employing HME for Ointment manufacturing several objectives were accomplished i.e.

Attaining a high yield and minimizing material loss experienced during conventional

2

manufacturing, reducing the manufacturing time which in turn reducing the contact time of

thermolabile drugs with elevated temperature conditions and providing high shear and mixing

conditions which improves the texture and uniformity of the formulation of the formulations.

Active Pharmaceutical Ingredients

For this research a combination of a local corticosteroid (Triamcinolone acetonide) and a local

anesthetic (Lidocaine hydrochloride) which are responsible for the additive action against

inflammation were used. It has also been shown by previous research that Lidocaine HCl improves

the stability of Triamcinolone acetonide which enhances the shelf life of this combination[12].

Triamcinolone acetonide is a synthetic acetonide salt of triamcinolone which is a synthetic

glucocorticosteroid. The glucocorticoid mimicking is responsible for its immunosuppressive and

anti-inflammatory activity[13]. It controls or prevents inflammation by suppressing migration of

polynuclear leucocytes and fibroblasts and reversing capillary permeability. Corticosteroids

decrease inflammation by stabilizing leukocyte lysosomal membranes, preventing release of

destructive acid hydrolases from leukocytes, inhibiting macrophage accumulation in inflamed

areas, reducing leukocyte adhesion to capillary endothelium, reducing capillary wall permeability,

reducing edema formation, decreasing complement components, antagonizing histamine activity,

antagonizing release of kinin from substrates, reducing fibroblast proliferation, collagen

deposition, and subsequent scar tissue

formation[14].

TAA is generally degraded into two main

degradation products i.e. 2-aldehyde and

17-carboxylic acid. Both are produced by

Figure 1. Structure of Triamcinolone acetonide

3

oxidation reactions catalyzed by trace metals[15]. This makes 17-C substitution the main target for

TAA degradation. HME protects and minimizes the exposure of the product to oxygen because of

the enclosed processing conditions and minimal processing time. The Amide group present in

Lidocaine HCl might have a role in protecting the C-17 substitution from oxidation. Hence, Co-

formulation of the two involved APIs leads to improved anti-inflammatory activity and enhanced

stability of the formulation. The Melting range of TAA was found to be 273-275ºC which was

followed by the degradation of the API. Hence the processing temperature selected was below the

degradation temperature. The partial solubilization of TAA in the formulation gives sustained

release of the API at the site of inflammation and hence might provide an enhanced relief from

inflammation at the affected area.

Lidocaine hydrochloride is the Hydrochloride salt of the topical anesthetic Lidocaine, an

aminoethylamide and a prototypical member of the amide class anesthetics. Lidocaine interacts

with voltage-gated Na+ channels in the nerve cell membrane and blocks the transient increase in

permeability of excitable membranes to Na+. This prevents the generation and conduction of nerve

impulses and produces a reversible loss of sensation. Lidocaine hydrochloride also exhibits class

IB antiarrhythmic effects. The agent decreases the flow of sodium ions into myocardial tissue

especially on the Purkinje network during phase 0 of the action potential, thereby decreasing

depolarization, automaticity and excitability[16].

The melting point of LDH was found to be

73-75ºC and degradation temperature was

above 150ºC, hence the processing

conditions were maintained below the

degradation temperature to ensure the

Figure 2. Structure of Lidocaine hydrochloride

4

stability of the API. The solubility of LDH in Propylene glycol (aqueous phase) contributes to the

uniform distribution of the drug in the formulation and immediate release from the formulation on

application to give instant relieve from inflammation.

Design of Experiments

Quality is the measure of repeatability or reproducibility of a product or process in context with

its expressed attributes. The pharmaceutical Quality by Design (QbD) is a systematic approach to

development which begins with predefined objectives. It emphasizes on understanding product

and process control by using the sound science of quality risk management [17 ][18]. The quality

target product profile (QTPP) is generally accepted as a tool for setting the strategic foundation

for drug development. In the case of semisolids following parameters are considered critical for

the quality of the formulation [19][20].

Table 1. QTPP and CQA for 0.1% TAA and 2% LDH Ointment.

Elements Target Justification CQA items

Dosage Form Ointment Proprietary product

requirements

Route of

Administration

Topical Proprietary product

requirements

Dosage strength

(TAA)

0.1% Proprietary product

requirements

Dosage strength

(LDH)

2% Proprietary product

requirements

Dosage design Water soluble ointment

with macrogol base with

completely soluble LDH

and partly soluble TAA

Based on the

physiochemical

properties of the

constituent API

Appearance White, smooth, creamy

texture with API dispersed

in the cream base

Patient acceptability

Identification Positive for API (TAA and

LDH)

Needed for clinical

effectiveness

CQA

Assay 90.0-110.0 % Needed for clinical

effectiveness

CQA

5

pH Between 6.2-6.8 for the

stability of the formulation

Stability and patient

acceptability

CQA

Impurities No known impurities;

unknown impurities NMT

0.2%; total impurities

NMT 0.2%

Needed for safety CQA

Homogeneity and

uniformity of

content

Samples withdrawn from

three regions of the

container should be within

90.0-110.0% of the label

claim

Needed for clinical

effectiveness

CQA

Physical attributes

Work of Adhesion

Stiffness

Consistency in work of

adhesion to ensure

adherence of the

formulation to the skin

A function of viscosity;

should be consistent for

uniform manufacturing,

mass transfer and

application

Needed for patient

acceptability and

optimum activity.

Patient acceptability

CQA

CQA

In vitro release

testing

Rate of release of the drug

with respect to the square

root of time

Needed for clinical

effectiveness and a

regulatory

requirement.

CQA

Stability 3 month accelerated

stability

Clinical

effectiveness

Design of Experiments (DoE) is used to ensure the achievement of desired quality attributes in the

formulation. Various designs and statistical methods are usually considered for designing products

or processes. The variables in the product or process affecting the CQA can be determined and

optimized using this tool. For the current project DoE was used to optimize the formulation

components as they have a major effect on the physical attributes of the formulation i.e. work of

adhesion and stiffness. For this a 16 run, randomized, I-optimal design for mixtures was selected

as it gives a detailed idea of the interactions and effects of all the components in the

formulations[18]. The I-optimal design minimizes the average variances of prediction and therefore

6

seems more appropriate for mixture experiments as compared to the commonly used D-optimal

designs. Because I-optimal design provides minimum average variance and simultaneously

provides the effects of all the components in the formulation on the CQA. It was ideal to employ

it for this research project as the acquired data can be used for selection or prediction of optimized

combination of the components which demonstrate the required attributes.

7

CHAPTER II: METHODOLOGY

Materials

Chemicals

Triamcinolone acetonide (Frontier Scientific, Batch no. LH20Q91), Lidocaine hydrochloride (MP

Biomedicals, LLC Batch no. Q9114), Polyethylene glycol 1500 (PEG 1500), Polyethylene glycol

4000 (PEG 4000), Propylene glycol, GantrezTM MS 955 Aerosil®, dibasic potassium phosphate,

monobasic sodium phosphate, dibasic sodium phosphate, HPLC grade Acetonitrile, Methanol and

Deionized water were used for analysis.

Equipment and auxiliaries

11 mm Twin screw extruder (ThermoFisher Scientific), Waters alliance e2695 HPLC separation

module and Waters 2489 UV system, Waters 600 controller, Waters 2487 UV/VIS detector,

Waters 717 plus autosampler, Mettler Toledo InLab®Micro pH probe, Texture Analyzer model

TA.XT2i (Texture Technologies Corp. /Stable Micro Systems) along with a 1-inch diameter (TA-

3), Cary 600 series Fourier transform infrared spectrometer, DSC (TA DSC 25), Varian 620-IR,

FT-IR Imaging microscope, Franz-diffusion cells, Hanson 15 Immersion cells with tools,

Phenomenex Luna® 5 µm C18(2) 100 Å, LC Column 250 x 4.6 mm, Hanson SR 8 plus dissolution

test station, Hanson small volume assembly.

8

Methods

Drug-Excipient compatibility studies

Before proceeding to formulation development, it is of crucial importance to determine the Drug

Excipient compatibility i.e. the physical and chemical stability of the drug product with the

excipients on storage. Stability studies are usually performed to ensure the long-term stability of

the formulation but determination of the suitability of excipients as a part of Preformulation studies

is an essential part of formulation development. To determine the drug-drug and drug-excipient

compatibility binary mixtures of the drug substances with each component of the designed

formulations were prepared. For this 1:1 (w/w) ratio of drug-drug or drug-excipient were taken in

a glass mortar and pestle. This mixture was triturated for 5 minutes, vortexed and samples from

the bulk were analyzed using Cary 600 series Fourier transform infrared spectrometer, Agilent

technologies (FT-IR). The prepared mixtures as defined in Table 2 were then transferred to

scintillation vials and exposed to accelerated stability storage conditions (40±0.5ºC and 75±1

%RH) for one month using a validated stability chamber and then analyzed using FT-IR[21][22].

Table 2. Compositions of various vials exposed to accelerated stability storage conditions for the

determination of drug-drug/drug-excipient compatibility.

Vial code Components

*TAA **LDH ***PEG Propylene glycol GantrezTM Aerosil®

1 * *

2 * *

3 * *

4 * *

5 * *

6 * *

7 * *

8 * *\

9 * *

(*Triamcinolone acetonide, **Lidocaine hydrochloride, ***1:1 ratio of PEG 4000 to PEG 1500)

9

Design of Experiments

Quality by Design (QbD) is a systematic approach to development (manufacturing, formulation

etc.) that begins with predefined objectives and emphasizes product and process understanding

and process control, based on sound science and quality risk management. For semi solid

formulations quality target profile includes parameters such as texture (work of adhesion,

Spreadibility, viscosity, stiffness etc.), pH of the formulation, drug content uniformity and to

prepare a formulation that fits all these requirements it is important to analyze the effects of

concentrations and ratios of different components on these parameters. For this an I-optimal

coordinate exchange, randomized, 16 runs design was selected which is ideal for mixtures using

design expert 11 software with fixed amounts of drugs and Aerosil® and varying proportions of

PEGs (PEG 1500 and PEG 4000), Propylene glycol and GantrezTM MS 955. These prepared

formulations with compositions mentioned in table 3 were exposed to preliminary screening using

Work of Adhesion, Stiffness and pH as response parameters such as texture and pH are the primary

and essential requirements in a semisolid topical formulation. Further in the design, formulations

F1 and F4; F2, F5 and F6; F9 and F10 have identical formulae which are introduced by the software

to determine point prediction, i.e. predictability of the characteristics of a formula based on results

obtained by the software. A design with good point prediction can help pinpoint exact amounts of

components required for desirable characteristics.

Table 3. I-optimal, coordinate exchange, randomized, 16 runs design with different compositions

PEG, PG and GantrezTM.

Formulation code *Propylene glycol (A) PEG (B) GantrezTM (C)

F1 20.00 75.80 04.20

F2 38.70 51.70 09.60

F3 54.80 42.20 03.00

F4 20.00 75.80 04.20

F5 38.70 51.70 09.60

10

F6 38.70 51.70 09.60

F7 55.90 29.10 15.00

F8 31.90 65.10 03.00

F9 72.80 20.00 07.20

F10 72.80 20.00 07.20

F11 28.40 56.60 15.00

F12 65.40 31.60 03.30

F13 38.70 51.70 09.60

F14 45.50 39.50 15.00

F15 64.50 20.50 15.00

F16 20.00 65.00 15.00

(*represents 1:1 ratio of PEG 1500 and PEG 4000; all formulations had 0.1% Triamcinolone

acetonide and 2% Lidocaine hydrochloride which were fixed as per their prescription dose and

0.2% Aerosil®)

Manufacturing of selected formulations

The ointment was produced using two manufacturing processes i) Fusion method ii) Hot melt

extrusion.

Fusion method (Conventional)

All the required ingredients were carefully weighed and procured for preparation of the ointment.

First PEG 1500 and PEG 4000 were transferred into a glass mortar and pestle and triturated for 5

minutes. Then this mixture was transferred into a porcelain crucible which was placed on a hot

plate maintained at a temperature of 65±5ºC. Simultaneously, Aerosil®, GantrezTM, Triamcinolone

acetonide and Lidocaine hydrochloride were transferred into the liquid phase i.e. Propylene glycol

with appropriate mixing. On complete melting of PEG the liquid phase was fused with it and this

mixture was maintained at 65±5ºC for 5 minutes to equilibrate the temperature of the mixture. This

mixture was transferred to a glass mortar and pestle and triturated until solidification and

appearance of a clicking sound. The semisolid mass was then transferred into Ointment containers

and stored under refrigerated conditions for further use.

11

Hot-melt extrusion (continuous manufacturing process)

For the manufacturing of ointment with HME first, the volumetric feeder (Solid feed) and the

peristaltic pump (liquid feed) were calibrated by preparing a calibration curve of weight dispensed

per minute vs % output (feeder parameter) and weight dispensed per minute vs RPM of peristaltic

pump. A modified screw design was selected for the processing of the ointment through HME[10].

Figure 3. Modified screw design for manufacturing of the ointment formulation.

The liquid feed was introduced from zone 3 of the 11 mm hot melt extruder (ThermoFisher

scientific, 11 mm twin screw extruder). The screw design was modified (as shown in fig. 3) in

such a way that the liquid feed and the solid feed were exposed to proper mixing by the

incorporation of an extended mixing zone followed by a material conveying zone and a terminal

mixing zone before ejection of the processed semisolid into the collecting unit. The physical

mixtures of PEG 1500, PEG 4000, GantrezTM, Aerosil®, Triamcinolone acetonide and Lidocaine

hydrochloride were prepared and introduced at a predetermined feed rate depending on the ratio

of liquid to solid feed. Propylene glycol was introduced in zone 3 after 1 minute and 23 seconds

(time taken for solid feed to reach zone 3 with an RPM of 100) of introducing solid feed.

12

Table 4. Processing parameters maintained for the manufacturing of ointment by Hot melt

extrusion.

Parameters Description

Equipment Pharma 11mm twin screw extruder

Screw design Modified

Barrel temperature Zone 1-5 (65ºC)

Zone 5-8 (40ºC)

RPM 100

Torque 0-3%

pH

pH of the skin is considered to be around 5.5 and hence acceptable semisolid formulations should

have a pH ranging from 5.5-7.0 to be compatible with the skin. To determine the pH aqueous

concentrations of 1%, 5% and 10% w/v of the ointments were prepared in water[10]. The pH of the

solutions was analyzed using Mettler Toledo InLab®Micro pH probe (Electrolyte 3 mol/L KCl).

pH was considered as a critical quality attribute for the screening of the ointments.

Texture analysis

For texture analysis, Texture Analyzer model TA.XT2i (Texture Technologies Corp. /Stable Micro

Systems) along with a 1-inch diameter (TA-3), acrylic, cylindrical probe, and a soft matter kit (TA-

275) was used for the determination of texture properties i.e. the work of adhesion and stiffness[11]

using the parameters mentioned in table 5. Soft matter fixture was filled with the product, and it

was placed below the texture analyser’s probe. The test was performed by lowering the probe at

the pre-test speed to the product surface. The probe produced an additional deformation of 2mm

of the sample at the test speed of 0.50 mm/s after encountering the surface and sensing the trigger

force. The probe then withdrew from the sample at the speed of 5.00 mm/s. The same procedure

was repeated for each sample in triplicates after cleaning the probe and levelling the surface of the

sample. These two parameters are a representative of the force required by the probe to penetrate

13

the mass of the sample semisolid (Stiffness) and the force and time required for the probe to

withdraw from this mass of ointment (work of adhesion) which are recorded as peak positive force

and area of the negative slope respectively.

Table 5. Parameters and set values for the texture analysis of prepared semisolid formulations.

Parameters Set values

Test mode Compression

Pre-test speed 0.50 mm/sec

Test speed 0.50 mm/sec

Post-test speed 5.00 mm/sec

Target mode Distance

Force 100.0 g

Distance 2 mm

Trigger type Auto

Trigger force 5 g

Hold time 5 sec

Temperature Room temperature

Drug-content uniformity

Drug content uniformity was determined by dispersing 100 mg (Triamcinolone acetonide)

equivalent of the sample withdrawn from three different regions of the ointment container into 100

ml of Acetonitrile (common solvent for extraction Triamcinolone acetonide and Lidocaine

hydrochloride) and this mixture was subjected to sonication to facilitate the solubilization of the

API in the solvent [20]. After sonication the solution was subjected to centrifugation and 10 µl of

aliquot was withdrawn and diluted up to 1 ml with Acetonitrile. The concentration was analyzed

using Waters HPLC-UV (Waters corp.) system. For the analysis calibration curve of

Triamcinolone ranging from 5-80 µg/ml and of Lidocaine hydrochloride ranging from 50-800

µg/ml were used.

Method of analysis

For the analysis of Triamcinolone acetonide and Lidocaine hydrochloride simultaneously, Waters

14

alliance e2695 HPLC separation module and Waters 2489 UV system was used. An existing

method was modified[23], and the modified method was evaluated for its Capacity Factor,

Selectivity and Resolution[24]. Table 6 displays the parameters for the HPLC method used for the

simultaneous measurement of the drug substances.

Table 6. Parameters for the modified HPLC method.

Parameters Set values

Mobile Phase *Phosphate buffer (pH 6.8): Acetonitrile:

Methanol (50:40:10)

Column LC-18-DB, Stainless steel, 250 mm X 4.6

mm, 5µ particle size

Injection volume 20 µl

Detection wavelength **238 nm and 210 nm for Triamcinolone and

Lidocaine respectively

Flow rate 1 ml/min

Retention time

Lidocaine hydrochloride

Triamcinolone acetonide

6.4 minutes

8.9 minutes

Run time 12 minutes

*prepared by adding 8.75 g of dibasic potassium phosphate in 1000 ml of water and the adjusting

pH with O-phosphoric acid.

**For instruments with two detector channels two wavelengths can be used for better limit of

detection of Lidocaine hydrochloride. For single detector channels wavelength of 238 nm should

be used.

Differential scanning calorimetry

Differential scanning calorimetry presents various exothermic and endothermic events occurring

in the sample with an increase in temperature. These events could represent Tm (Melting point of

crystalline substances), Tg (Glass transition of amorphous polymers), Polymorphism and

degradation. For this study the DSC (TA DSC 25) of PEG (1500 & 4000), Gantrez, Triamcinolone

acetonide and Lidocaine hydrochloride at a ramp rate of 10ºC /min with the temperature ranging

from 25ºC to 300ºC[10][11] was conducted. Followed by the generation of DSC profiles of these

individual components, DSC of the formulations were performed to observe any degradation peaks

15

and assess the solubilization of the drug in formulation with a ramp rate of 20ºC/min to avoid the

distortion of peaks due to the presence of Aerosil® in the formulation and the same heating range.

In vitro release testing (IV-RT)

In vitro release testing (IV-RT) is a critical quality attribute for semi-solid formulations which

predicts the release kinetics of the drug substance from the product. For this study vertical Franz-

diffusion cells were used with suitable receiver media and release membrane. The protocol for

release studies was optimized using the following procedure and steps[27].

Drug solubility studies

To determine the composition of the release media, saturation solubilities of Triamcinolone

acetonide was determined by mixing 10 mg of the drug substance in 2 ml of various aqueous media

(mentioned in table 7) with varying composition using 2 ml centrifuge tubes (n=3). These mixtures

were transferred to a mechanical shaker and subjected to continuous agitation at a rate of 70 RPM

for 24 hours. Later the samples were subjected to centrifugation at 13000 RPM for 10 minutes.

The supernatant was collected and transferred to HPLC vials for analysis. The concentration was

determined using the mentioned method of analysis. Solubility studies for Lidocaine HCL were

not necessary as the drug substance was freely soluble in all considered medias[26].

Table 7. Composition of various vials for solubility studies

Sample no. Composition

1 (a, b, c) Milli Q water

2 (a, b, c) **0.1 M Phosphate buffer solution (pH 7.4)

3 (a, b, c) 0.1 % v/v Tween 60

4 (a, b, c) 0.1 % v/v PEG 400

5 (a, b, c) 0.1 % w/v BrijTM 98

6 (a, b, c) 0.1 % w/v BrijTM C-20 SO (AP)

7 (a, b, c) 0.1 % w/v BrijTM S-20 SO (mM)

8 (a, b, c) 0.1 % v/v BrijTM L4 LQ (AP)

*9 (a, b, c) 0.2 % w/v BrijTM C-20 SO (AP) in PBS

16

*10 (a, b, c) 0.2 % w/v BrijTM S-20 SO (mM) in PBS

*11 (a, b, c) 0.2 % v/v BrijTM L4 LQ (AP) in PBS

*These samples were a part of the secondary screening for selection of the receiver media rest of

the samples were used for preliminary screening.

**0.1M PBS was prepared using Monosodium Phosphate, monohydrate (2.795g/l) and Disodium

Phosphate, heptahydrate (21.37g/l).

Membrane inertness testing

This study was performed to select a membrane suitable for the release studies. For this study drug

solutions of Triamcinolone acetonide (5µg/ml), Lidocaine hydrochloride (5µg/ml) and a

combination of Triamcinolone acetonide & Lidocaine hydrochloride (5µg/ml) were prepared. 10

ml of each solution was taken in centrifuge tubes and labelled respectively as described in table 8.

Four selected membranes were cut into half. 0.5 ml of sample was withdrawn from the centrifuge

tube before soaking the membrane. Then the membrane was soaked in the centrifuge tube and

allowed to soak for 24 hours. After 24 hours, 1 ml of sample was withdrawn from each of the

centrifuge tubes and the before and after samples were analyzed using HPLC. A suitable inert

membrane would not absorb the drug from the drug solution. This study is performed to ensure no

retention of the drug on the membrane during the release studies.

Table 8. Composition of various sample tubes taken for analysis with respective membranes

used for the membrane inertness studies.

Sample no. Membrane Pore size Diameter Drug solution (5 µg/ml)

1 Nylon 0.22 µm 47 mm TAA

2 Sopor 0.20 µm 25mm TAA

3 Tuffryn 0.45 µm 25 mm TAA

4 Cyclopore 0.20 µm 25 mm TAA

5 Nylon 0.22 µm 47 mm LDH

6 Sopor 0.20 µm 25mm LDH

7 Tuffryn 0.45 µm 25 mm LDH

8 Cyclopore 0.20 µm 25 mm LDH

9 Nylon 0.22 µm 47 mm TAA+LDH

10 Sopor 0.20 µm 25 mm TAA+LDH

11 Tuffryn 0.45 µm 25 mm TAA+LDH

17

12 Cyclopore 0.20 µm 25 mm TAA+LDH

TAA=Triamcinolone acetonide; LDH=Lidocaine hydrochloride

Membrane validation studies

Three ointment formulations were prepared with the drug load of 50%, 100% and 200% of the

label claim (0.1% Triamcinolone acetonide and 2% Lidocaine hydrochloride) and the membrane

validation studies were performed using Franz-diffusion cells (1.77cm2). Rubber rings were used

to mount the membrane, the receiver compartment was filled with 7 ml of suitable receiver media

and a stir bar was inserted in the cell to facilitate diffusion. Before initiating the studies, the selected

membrane was soaked in the release media for 30 minutes and then mounted on the cell. Weighed

amounts of the ointment formulations were withdrawn and placed on the donor compartment

above the membrane and the sample was covered with parafilm, the assembly of the cell is shown

in fig.4. Receiver compartment was checked for air bubbles. 0.3 ml of the sample was drawn at

six different timepoints (0.5, 1, 2, 3, 4, 5 hours) and analyzed in HPLC. This experiment was

performed using 9 cells (n=3).

Figure 4. assembly of a vertical Franz-diffusion cell[28].

18

Table 9. Weight of the formulations placed in the individual cells

Cell number Drug load (%) Weight of the sample (grams)

1 50 0.75

2 100 1.06

3 200 1.05

4 50 0.95

5 100 0.83

6 200 0.84

Drug release testing

After performing the solubility studies (to determine the release media), membrane inertness

testing (to screen a suitable inert membrane) and membrane validation studies (to ensure that the

membrane does not act as a rate limiting barrier), the release studies of the three optimized

formulation prepared by both conventional and HME process were performed. Immersion cells

(Hanson, 15 mm) and 150 ml capacity dissolution cells were employed to determine the release of

the drugs from the formulations. Immersion cells can be used as an automated quality control tool

in the in vitro release testing procedure as a modification of USP II dissolution apparatus (paddle

type)[29]. To load the immersion cells with ointment, first the support ring was placed upside down

(larger opening face up) and then the membrane was locked in between the orifice washer and the

ointment washer in a way that the membrane has minimum wrinkles. The dose was then applied

to the circular area in the middle of the ointment washer and spread evenly. The ‘O’ ring was

placed on the washer and the glass washer was placed to seal the ointment compartment. The lock

ring was then placed on the support ring and sealed using the hand tool. These immersion cells

loaded with ointment formulations were then immersed in the dissolution vessels (inserted in the

dissolution apparatus using a conversion kit) with 150 ml of receiver media. Suitable paddles were

introduced to the cell and the temperature was adjusted to 32±0.1ºC (temperature of the skin). 1

ml of the sample was isolated and replaced with media at pre-determined time points (0.5, 1, 2, 3,

19

4 and 5 hours). The collected samples were then estimated using the developed HPLC method for

this combination of drug substances.

Figure 5. a) Assembly of the dissolution apparatus and immersion, b) Packing of ointment into

the immersion cell[30]

a b

20

CHAPTER III: RESULTS AND DISCUSSION

Drug-Excipient compatibility

The binary mixtures prepared were exposed to FT-IR analysis to determine the physical (H-

bonding) or chemical interactions between API and Excipients.

Figure 6. FT-IR of Triamcinolone acetonide with various excipients

From fig. 6 it can be seen that triamcinolone has prominent peaks on 3330 cm-1 which is because

of the ‘-OH’ stretching vibrations[31]. This is an important site of reaction and degradation for

triamcinolone and the intactness or slight shift in the peak shows no or weak physical interactions

in the compounds. Weak physical interactions like H-bonding are responsible for increasing the

21

solubility and stability of the API in the formulation. It can be observed in excipients like PEG and

PG having ‘-OH’ groups and interacting with the concerned API. A similar interaction was visible

between TAA and LDH which could be the reason for enhanced stability of the API in presence

of TAA. The potency of the API was retained after subjecting the binary mixtures for a 1-month

accelerated stability which ensures the compatibility of the API with the selected excipients.

Aerosil® displays strong intermolecular H-bonding which is responsible for the disappearance of

the ‘-OH’ peak in the binary mixture.

Figure 7. FT-IR of Lidocaine hydrochloride with various excipients

Fig. 7 shows the interactions of various excipients with LDH and similar to TAA, the potency of

LDH remains the same after storage with the excipients. The FT-IR shows that LDH is having

weak interactions with PEG, PG and Aerosil® which seem like weak H-bonding that don’t affect

the stability of LDH but enhance the solubilization of LDH in the formulation. This is the reason

for complete solubilization of LDH in the formulation.

22

Screening of formulations

The preliminary screening was performed based on CQA(s) like Texture (work of adhesion,

stiffness) and pH of the formulation as mentioned in table 10.

Table 10. Preliminary screening of the formulations based on CQA

Formulation code Work of adhesion Stiffness pH

F1 529.28 3823.2 6.04

F2 420.78 0834.7 6.11

F3 147.03 0202.7 6.05

F4 550.00 3820.0 6.25

F5 452.80 0814.8 6.12

F6 465.32 0792.6 6.11

F7 049.68 0056.4 5.99

F8 597.21 1059.8 6.21

F9 020.73 0030.4 6.13

F10 028.55 0021.9 6.13

F11 460.58 0826.5 5.98

F12 050.39 0051.9 6.33

F13 473.44 0750.3 6.12

F14 162.87 0193.4 5.92

F15 027.76 0035.6 6.03

F16 650.61 2038.2 5.98

All the formulations had a varying ratio of PEG:PG:GantrezTM and on analyzing the statistics it

was seen that there is a significant correlation between the components and their ratios on the

work of adhesion and stiffness.

Work of Adhesion

Table 11. ANOVA of the tested formulation for work of adhesion

Source Sum of

Squares

DF Mean

Square

F-Value P-Value Significance

Model 24.40 05 04.88 189.01 < 0.0001 significant

Linear Mixture 21.98 02 10.99 425.67 < 0.0001

AB 01.53 01 01.53 059.37 < 0.0001

AC 00.34 01 00.34 013.24 0.0045

BC 00.43 01 00.43 016.66 0.0022

Residual 00.26 10 00.03

23

Lack of Fit 00.19 05 00.04 03.30 0.1082 not

significant

Pure Error 00.06 05 00.01

Cor Total 24.66 15

Table 11 provides information about the impact of the ratios of the components on the work of

adhesion of the formulation. The Model F-value of 189.01 implies the model is significant. There

is only a 0.01% chance that an F-value this large could occur due to noise. P-values less than

0.0500 indicate model terms are significant. In this case A, B, C, AB, AC, BC are significant

model terms. Values greater than 0.1000 indicate the model terms are not significant. The Lack

of Fit F-value of 3.30 implies that the Lack of Fit is not significant relative to the pure error.

There is a 10.82% chance that a "Lack of Fit F-value" this large could occur due to noise. Non-

significant lack of fit is good as it displays that the model to fits.

Table 12. Fit statistics for the design

Fit statistics

Std. Dev. 0.16 R² 00.9895

Mean 5.23 Adjusted R² 00.9843

C.V. % 3.07 Predicted R² 00.9689 Adeq Precision 32.9603

Table 12 shows that the Predicted R² of 0.9689 is in reasonable agreement with the Adjusted

R² of 0.9843; i.e. the difference is less than 0.2. Adeq Precision measures the signal to noise ratio.

A ratio greater than 4 is desirable. The ratio of 32.960 indicates an adequate signal and hence the

model can be used to navigate the design space.

24

Table 13. Coefficients in terms of coded factors

Component Coefficient

Estimate

df Standard

Error

95% CI

Low

95% CI

High

VIF

A-PG 02.71 1 0.1596 02.36 03.07 004.37

B-PEG 06.25 1 0.1202 05.98 06.51 002.88

C-Gantrez -19.64 1 6.5300 -34.18 -05.10 473.40

AB 03.78 1 0.4903 02.69 04.87 002.66

AC 30.60 1 8.4100 11.86 49.33 190.38

BC 33.72 1 8.2600 15.31 52.12 184.09

The coefficient estimate (Table 13) represents the expected change in response per unit change in

factor value when all remaining factors are held constant. The intercept in an orthogonal design is

the overall average response of all the runs. The coefficients are adjustments around that average

based on the factor settings. When the factors are orthogonal the VIFs are 1; VIFs greater than 1

indicate multi-collinearity, the higher the VIF the more severe the correlation of factors. As a rough

rule, VIFs less than 10 are tolerable.

Figure 8. Two component mix plots with varying ratios of PEG and PG in the formulations

25

Figure 9. Predicted versus actual values of work of adhesion for the formulations

Stiffness

Table 14. ANOVA of the tested formulations for stiffness

Source Sum of

Squares

df Mean Square F-value p-value Significance

Model 45.4100 05 09.0800 306.07 < 0.0001 significant

Linear

Mixture 44.6500 02 22.3200 752.29 < 0.0001

AB 00.1236 01 00.1236 004.17 0.0686

AC 00.5791 01 00.5791 019.52 0.0013

BC 00.5966 01 00.5966 020.11 0.0012

Residual 00.2968 10 00.0297

Lack of Fit 00.2361 05 00.0472 003.89 0.0811

not

significant

Pure Error 00.0607 05 00.0121

Cor Total 45.71 15

The Model F-value of 189.01 (Table 14) implies the model is significant. There is only a 0.01%

26

chance that an F-value this large could occur due to noise. P-values less than 0.0500 indicate model

terms are significant. In this case A, B, C, AB, AC, BC are significant model terms. Values greater

than 0.1000 indicate the model terms are not significant. The Lack of Fit F-value of 3.30 implies

the Lack of Fit is not significant relative to the pure error. There is a 10.82% chance that a "Lack

of Fit F-value" this large could occur due to noise. Non-significant lack of fit is good as it displays

that the model to fit.

Table 15. Fit statistics for the design

Fit statistics

Std. Dev. 0.1723 R² 00.9935

Mean 5.8200 Adjusted R² 00.9803

C.V. % 2.9600 Predicted R² 00.9791 Adeq Precision 46.4605

The Predicted R² of 0.9689 shown in table 15 is in reasonable agreement with the Adjusted R² of

0.9843; i.e. the difference is less than 0.2. Adeq Precision measures the signal to noise ratio. A

ratio greater than 4 is desirable. The ratio of 32.960 indicates an adequate signal. This model can

be used to navigate the design space.

Table 16. Coefficients in terms of coded factors

Component Coefficient

Estimate

df Standard

Error

95% CI

Low

95% CI

High

VIF

A-PG 02.72 1 0.1711 02.3400 03.10 004.37

B-PEG 08.12 1 0.1289 07.8300 08.41 002.88

C-Gantrez -26.06 1 7.0000 -41.6500 -10.47 473.40

AB 01.07 1 0.5257 -00.0985 02.24 002.66

AC 39.83 1 9.0100 19.7400 59.91 190.38

BC 39.71 1 8.8600 19.9800 59.44 184.09

The coefficient estimates in table 16 represents the expected change in response per unit change

in factor value when all remaining factors are held constant. The intercept in an orthogonal design

is the overall average response of all the runs. The coefficients are adjustments around that average

27

based on the factor settings. When the factors are orthogonal the VIFs are 1; VIFs greater than 1

indicate multi-collinearity and the higher the VIF the more severe the correlation of factors. As a

rough rule, VIFs less than 10 are tolerable.

Figure 10. Two component mix plots with varying ratios of PEG and PG in the formulations

fig 10. Shows that stiffness of the formulation increases with an increase in the PEG concentration.

This shows that the PEG and the PG concentrations have a significant effect on the stiffness of the

formulation. Moreover formulation concentration for a desired stiffness can be predicted using the

software because of the high degree of regression and fit statistics displayed in table 15 and fig 11.

28

Figure 11. Actual versus Predicted plot for the values of stiffness for various prepared

formulations

pH

The pH of all the prepared formulations were within range. Though pH is considered as a CQA

for this formulation and will be used for evaluation of the formulations, it was no longer considered

a parameter for screening of the formulations as there was no significant correlation between the

ointment components and pH.

29

Analytical Method Validation

Four major descriptors are commonly used to report the characteristics of the chromatographic

column, system and particular separation i.e. Retention factor/Capacity factor (k’), selectivity (α)

and Resolution.

Length of time taken by the retarded compound to pass through the column depends on its capacity

factor. It is the measure of degree to which an analyte partitions into the stationary phase from the

mobile phase. This can be determined by using the following equation where tr is the retention

time of the analyte and t0 is the retention time of the non-retained sample i.e. solvent front.

𝑘′ =𝑉𝑟 − 𝑉0𝑉0

𝑘′ = (𝑡𝑟 − 𝑡𝑜)/𝑡0

The capacity factor for TAA (k’TAA) was found to be 4.99 (solvent front was seen at 1.5 minutes

and retention time of TAA is 8.99 minutes), for LDH (k’LDH) was found to be 3.26 (retention time

of LDH was observed to be 6.4 minutes). A capacity factor between 1-5 is ideal for analysis.

Selectivity (α) is the ability of the chromatographic system to discriminate between the two

analytes and can be determined by taking a ratio of the capacity factors of the two analytes.

∝=𝑘𝑇𝐴𝐴𝑘𝐿𝐷𝐻

α for the system was found to be 1.53 which is ideal for uninterrupted determination of two

analytes.

Finally, resolution of the system was determined using the following formulae.

𝑅 = 2𝑡𝑇𝐴𝐴 − 𝑡𝐿𝐷𝐻𝑤1 + 𝑤2

The resolution of system should be ≥1.5 and the resolution for this system was found to be 6.4

30

which is an excellent resolution for determination.

Optimization and Manufacturing processes

After preliminary screening of the formulations, three formulations (F2, F3 and F8) with desirable

properties were selected (Table 17) , manufactured using conventional and HME techniques and

characterized for Uniformity of Drug Content, Differential Scanning Calorimetry, Hot Stage

Microscopy and in vitro release testing.

Figure 12. Manufacturing process of Ointment formulations using HME

Three formulations were selected for further characterization with different Stiffness and Work of

Adhesion depending on the purpose of use. Formulation F2 was selected and intended for oral use

i.e. ulcers, burns etc. Formulation F3 was selected for skin infections, burns and allergic

manifestations because of better Spreadibility and Formulation F8 was selected for Hemorrhoids

treatment because of its stiff and adhesive nature which enhances the retention time of the

formulation and delays softening of the formulation which improves therapeutic efficiency and

SOLID

FEED

LIQUID

PHASE

31

patient compliance.

Table 17. Selected formulations and their characteristics.

Formulation

code

Work of

Adhesion

Stiffness pH Drug

Content

(TAA)

Drug

Content

(LDH)

F2C 498.223±52.988 0843.5600±30.67 6.11±0.04 098.9±0.017 107.9±1.018

F2H 488.618±03.550 0865.4445±03.15 6.22±0.01 104.7±0.008 108.4±0.999

F3C 159.808±27.460 0228.4200±25.77 6.05±0.07 108.5±0.002 106.6±0.954

F3H 148.372±03.450 0215.5470±02.02 6.27±0.05 101.5±0.003 097.7±0.890

F8C 615.104±68.780 1230.4500±80.26 6.21±0.03 095.3±0.010 101.3±1.090

F8H 596.154±08.920 1014.6400±06.12 6.30±0.03 094.8±0.006 101.9±0.988

C-Conventionally prepared; H-Hot-Melt Extruded.

From the above characterization of selected formulations, it can be observed that conventionally

prepared ointments have a larger standard deviation as compared to the ointments prepared using

HME. This could be due to the uncontrolled variables that participate in conventional

manufacturing such as material loss during mixing, mass transfer, rate of mixing or temperature

control during mixing which are in fact very well controlled during HME processing. During the

Hot Melt Extrusion process, parameters such as feed rate, mixing RPM, processing temperature

and torque are well under control which helps produce uniform products and minimize batch to

batch variation. The pH of all the formulations (HME and Conventional) was within the specified

range. All the formulations had drug content within the specified range and hence all the produced

Ointments were accepted and subjected to further characterization.

Differential scanning calorimetry

All the prepared Ointments were characterized using DSC to ensure the solubility of the API in

the formulation. The DSC plot shows complete disappearance of the drug peaks which suggests

that either both the drugs have been dissolved in the base or that the increase in temperature during

DSC experimentation has solubilized the drugs in the base. From the DSC curve shown in Fig. 13,

32

it can be seen that there has been complete solubilization of the drugs in the Ointment base both

in

HME and Conventionally prepared ointments.

Figure 13. DSC profiles of pure API, excipients and prepared Ointment formulations.

In vitro release testing (IV-RT)

Based on the saturation solubility of TAA in various release media, 0.2 % w/v BrijTM C-20 SO

(AP) in PBS was selected as it completely solubilized LDH and had the maximum solubility for

TAA (Table 18) with respect to the other tested release mediums with different surfactants.

Table 18. Solubilities of TAA in different release mediums.

Sample number Solubility (µg/ml)

1 Practically insoluble

2 Practically insoluble

3 3.65

4 Practically insoluble

5 3.44

6 7.71

7 7.30

8 6.74

9 9.08

33

10 6.63

11 8.45

Refer Table 7 for sample compositions

Tuffryn 0.45µm, 25mm membrane was selected amongst the tested membranes because of its

inertness to the API. There was negligible absorption of API on the membrane before and after

exposure to the drug solution.

Table 19. Membrane inertness studies.

Sample number % Absorbed (TAA) % Absorbed (LDH)

1 4.20 -

2 2.89 -

3 0.72 -

4 2.44 -

5 - 0.19

6 - 0.59

7 - 0.19

8 - 0.19

9 0.73 0.19

10 0.43 0.39

11 0.14 0.19

12 3.21 0.58

Refer Table 8 for sample composition

From the other values it can be seen that the Tuffryn membrane absorbed the least amount of

TAA and LDH from the drug solution which makes its use suitable for this study.

Finally, to see if the release of the API from the formulation is not hindered by the membrane

and is proportional to the concentration of the drug in the formulation, membrane validation

studies were conducted.

34

Figure 14. Membrane validation for TAA

Figure 15. IV-RR versus dose strength of TAA

R² = 0.9654

R² = 0.9896

R² = 0.9936

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2 2.5

µg.

/cm

2

√Time

50 % TAA 100 % TAA 200 % TAA

y = 0.0469x + 3.7509R² = 0.9994

0

2

4

6

8

10

12

14

0 50 100 150 200 250

IVR

R

% Dose strength

35

The membrane validation studies were performed using the topical product prepared at three

strengths (50% of the label claim, 100% label claim and 200% label claim). The release profile

(cumulative release versus square root of time) showed a linear profile as shown in figure 14 and

16. Figures 15 and 17 shows the relationship between the dose strength and IV-RR (Slope of

cumulative release versus square root of time). Liner correlation with excellent regression

coefficient (>0.9) shows that the membrane could be used for performing the release studies of

other formulations or form comparison of the formulated product with the reference product. The

membrane is not acting as a rate controlling barrier and the release is absolutely attributable to the

formulation properties.

Figure 16. Membrane validation of LDH

R² = 0.9972

R² = 0.9706

R² = 0.9983

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0 0.5 1 1.5 2 2.5

µg/

cm2

√Time

50 % LID 100 % LID 200 % LID

36

Figure 17. IV-RR versus Dose strength of LDH

Finally using the above selected release media, membrane release studies of the selected

formulations were performed. It can be seen from the release studies that the formulations prepared

by HME and the formulations prepared conventionally show comparable release rates. Moreover,

formulations F2 and F8 show better release rates and profiles as compared to conventionally

prepared formulation. This can be attributed to the enhanced and uniform mixing provided by Hot-

Melt extrusion which allows proper distribution and enhanced solubilization of TAA in the

ointment base which is not achieved conventionally. F3H exhibits a similar release profile as

compared to F3C, this could be because of a higher drug content in F3C as compared to F3H.

y = 26.854x - 627.07R² = 0.9736

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

0 50 100 150 200 250

IVR

R

% Dose strength

37

Figure 18. Drug release profile of TAA from F2H and F2C

Figure 19. Drug release of LDH from F2H and F2C

R² = 0.9901

R² = 0.9642

0.00

20.00

40.00

60.00

80.00

100.00

0.00 0.50 1.00 1.50 2.00 2.50

µg/

cm2

√Time

F2 TAA Drug release

F2 Conventional TAA F2 HME TAA

Linear (F2 Conventional TAA) Linear (F2 HME TAA)

R² = 0.999

R² = 0.997

0.00

1000.00

2000.00

3000.00

4000.00

5000.00

6000.00

7000.00

8000.00

0.00 0.50 1.00 1.50 2.00 2.50

µg/

cm2

√Time

F2 LDH Drug release

F2 Conventional LDH F2 HME LDH

Linear (F2 Conventional LDH) Linear (F2 HME LDH)

38

Figure 20. Drug release profile of TAA from F3H and F3C

Figure 21. Drug release profile of LDH from F3H and F3C

R² = 0.9767

R² = 0.9968

0.00

10.00

20.00

30.00

40.00

50.00

0.00 0.50 1.00 1.50 2.00 2.50

µg/c

m2

√Time

F3 TAA Drug release

F3 Conventional TAA" F3 HME TAA

Linear (F3 Conventional TAA") Linear (F3 HME TAA)

R² = 0.9989R² = 0.9997

0.00

1000.00

2000.00

3000.00

4000.00

5000.00

6000.00

7000.00

0.00 0.50 1.00 1.50 2.00 2.50

µg/c

m2

√Time

F3 LDH Drug release

F3 Conventional LDH F3 HME LDH

Linear (F3 Conventional LDH) Linear (F3 HME LDH)

39

Figure 22. Drug release profile of TAA from F8H and F8C

Figure 23. Drug release profile of LDH from F8H and F8C

R² = 0.9868

R² = 0.9777

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

0.00 0.50 1.00 1.50 2.00 2.50

µg/

cm2

√Time

F8 TAA Drug release

F8 Conventional TAA" F8 HME TAA

Linear (F8 Conventional TAA") Linear (F8 HME TAA)

R² = 0.9958

R² = 0.9814

0.00

1000.00

2000.00

3000.00

4000.00

5000.00

6000.00

7000.00

0.00 0.50 1.00 1.50 2.00 2.50

µg/

cm2

√Time

F8 LDH Drug release

F8 Conventional LDH F8 HME LDH

Linear (F8 Conventional LDH) Linear (F8 HME LDH)

40

CHAPTER IV: CONCLUSION

A series of statistical and experimental characterizations were conducted to optimize the

formulation and manufacturing variables for the production of three stable Ointment formulations.

Drug-Excipient compatibility studies demonstrated the absence of drug-drug and drug-excipient

interactions. Further, the I-optimal design provided a design space and platform which can be used

for prediction of the excipient ratios for a target texture profile. Selected formulations were

successfully manufactured using conventional and HME techniques. From the results of

comparison between the conventional and HME ointment formulations, it can be concluded that

HME shows a better control over the process variables and leads to the production of a more

uniform product. It can also be concluded that the controlled processing variables lead to a reduced

batch to batch variation and improved the consistency in the CQA(s) of the ointments.

Simultaneously, a protocol to evaluate the in vitro release rates of formulations containing either

TA, LDH or both were successfully developed and validated.

41

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42

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45

VITA

Rishi Thakkar was born in Radhanpur, India on 28th September 1995. He graduated cum-laude

from Gujarat Technological University with a Bachelor of Pharmacy degree. He was accepted by

the University of Mississippi for the MS in Pharmaceutical sciences program with an emphasis on

pharmaceutics and drug delivery in Spring 2017-18. After receiving his master’s degree, he will

be pursuing a PhD at the University of Texas at Austin.