UNIVERSITY OF GHANA 

COLLEGE OF HEALTH SCIENCES 

SCHOOL OF PHARMACY 

 

PROJECT TITLE: 

IN VITRO AND IN VIVO KINETIC CHARACTERISTICS OF CHITOSAN-

PECTIN-BASED MATRIX OF LEVODOPA AND CARBIDOPA 

BY 

EMELIA PRISCILLA IMBEAH 

(10339983) 

A THESIS SUBMITTED TO THE SCHOOL OF GRADUATE STUDIES 

IN PARTIAL FULFILMENT FOR THE AWARD OF A MASTER OF 

PHILOSOPHY DEGREE IN PHARMACOLOGY 

 

 

 

DEPARTMENT OF PHARMACOLOGY AND TOXICOLOGY 

 

DECEMBER 2021 

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DECLARATION 

I, Emelia Priscilla Imbeah, hereby declare that this project, aside duly cited literature, is the 

outcome of my own ideas under the supervision of Dr. Seth Kwabena Amponsah and Dr. 

Ofosua Adi-Dako. 

 

Emelia Priscilla Imbeah         

(Student) 

Signature……………………………                Date:   15/12/2021 

 

Dr. Seth Kwabena Amponsah                   

(Supervisor)  

Signature…………………………………       Date: 15/12/2021 

 

Dr. Ofosua Adi-Dako                       

(Supervisor)  

Signature…………………………………       Date: 15/12/2021 

 

 

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ABSTRACT 

Background: Parkinson's disease is a progressive neurodegenerative disorder that causes 

disability usually among the elderly. Levodopa remains the drug of choice in the management 

of Parkinson's disease. Levodopa is extensively metabolized in the periphery by aromatic 

amino acid decarboxylases; thus, it is routinely co-administered with carbidopa, a peripheral 

decarboxylase inhibitor. Although the aforementioned combination therapy is effective, there 

is variable absorption and fluctuating plasma levels of levodopa after oral administration. New 

oral levodopa plus carbidopa (levodopa/carbidopa) formulations are needed to overcome this 

irregular absorption and maintain near constant plasma concentrations. 

Aim: The aim of this study was to evaluate the kinetic characteristics of chitosan-pectin-based 

multiparticulate matrix of levodopa/carbidopa, using in vitro and in vivo models. 

Methodology: Pectin was extracted from cocoa pod husk with hot aqueous solution. 

Preparation of the chitosan-pectin-based matrix was done by the wet granulation. The 

formulations were evaluated for drug-excipient compatibility, drug content, flowability and 

precompression properties and in vitro release. In evaluating in vivo pharmacokinetic and 

biodistribution characteristics, male Sprague Dawley rats were administered either chitosan-

pectin based matrix of levodopa/carbidopa, Sinemet CR (a controlled release formulation of 

levodopa/carbidopa) or levodopa/carbidopa immediate release powder (20/5 mg/kg) via the 

oral route every 12 hours. After the third dose, tail vein samples and brain tissues were taken 

at predetermined times.  Pharmacokinetic parameters (Cmax, Tmax, AUC and t1/2) of levodopa 

were estimated for the various treatment, levels of levodopa in rat brains were estimated and 

compared.  

Results: The yield of cocoa pod husk pectin extracted with hot aqueous solution was 7.91%. 

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The excipients for drug formulation were compatible with levodopa/carbidopa. The  content of 

levodopa and carbidopa in the various formulations were within the acceptance criteria (not 

less than 90% and not more than 110% of the stated amount) with the exception of F5. There 

was controlled and sustained release of levodopa and carbidopa in vitro.  In vivo 

pharmacokinetic studies showed kinetic profiles of levodopa/carbidopa multiparticulate matrix 

as compared to the conventional control release formulation. The AUC0-24 for optimized 

levodopa/carbidopa multiparticulate matrix (F3: 484.98 ± 18.70; F4: 535.60 ± 33.04), and Cmax 

(F3: 36.28 ± 1.52; F4: 34.80 ± 2.19 μg/mL) were relatively higher than Sinemet CR (AUC0-24 

262.84 ± 16.73 and Cmax 30.62 ± 3.37 μg/mL).  

Conclusion:  Findings from the study suggest that chitosan-pectin based matrix of 

levodopa/carbidopa may have the potential to control and maintain therapeutic concentrations 

of levodopa in circulation over a period of time. 

 

 

 

 

 

 

  

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DEDICATION 

This work is dedicated to my dear husband for his immense support, encouragement, love 

and help throughout this Master’s program. 

 

 

 

 

 

 

 

 

 

 

 

 

  

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ACKNOWLEDGEMENT  

I am thankful to God for his grace, mercies, divine favor, guidance and protection. 

I wish to express my heartfelt gratitude to my supervisors, Dr. Seth Kwabena Amponsah and 

Dr. Ofosua Adi-Dako for their guidance, support and motivation throughout this project. I also 

appreciate their insightful assessments, comments, and contributions, which helped to improve 

the study's quality. Profound thanks also go to Prof Regina Appiah-Opong and Mr. Ebenezer 

Ofori-Attah for their immense support. God richly bless you all. 

Special appreciation goes to Mr. Ismaila Adams, all my lecturers, the entire staff of the 

Department of Clinical Pathology, Noguchi Memorial Institute for Medical Research 

(NMIMR), the entire staff of the Department of Pharmacology and Toxicology, University of 

Ghana School of Pharmacy and to Mr. Clement Sasu and Mr Samuel Otinkorang for their 

technical assistance. 

 

 

 

 

 

 

 

 

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TABLE OF CONTENTS 

 

DECLARATION ..................................................................................................................................... i 

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

DEDICATION ....................................................................................................................................... iv 

ACKNOWLEDGEMENT ...................................................................................................................... v 

TABLE OF CONTENTS ....................................................................................................................... vi 

LIST OF FIGURES ............................................................................................................................... ix 

LIST OF TABLES ................................................................................................................................. xi 

LIST OF ABBREVIATIONS ............................................................................................................... xii 

CHAPTER ONE   INTRODUCTION .................................................................................................... 1 

1.1 Background ......................................................................................................................... 1 

1.2 Problem Statement ............................................................................................................. 4 

1.3 Justification ......................................................................................................................... 6 

1.4  Hypothesis ........................................................................................................................... 7 

1.5  Aim ...................................................................................................................................... 7 

1.6  Specific Objectives .............................................................................................................. 8 

CHAPTER TWO   LITERATURE REVIEW ........................................................................................ 9 

2.1  Parkinson’s Disease ............................................................................................................. 9 

2.1.1 History and Background ............................................................................................ 9 

2.1.2 Epidemiology ........................................................................................................... 10 

2.1.3 Aetiology and Risk Factors ....................................................................................... 11 

2.1.4 Pathophysiology ...................................................................................................... 18 

2.1.5 Clinical Presentation and Diagnosis ......................................................................... 22 

2.1.6 Non-Motor Features of PD ...................................................................................... 25 

2.1.6 Diagnosis .................................................................................................................. 26 

2.1.7 Management of PD .................................................................................................. 28 

2.2 LEVODOPA/CARBIDOPA FOR MANAGING PD ................................................................... 29 

2.2.1 Levodopa ................................................................................................................. 29 

2.2.2 Carbidopa ................................................................................................................ 34 

2.2.3 Motor Fluctuations and Dyskinesia in Parkinson Disease ....................................... 35 

2.2.4 Levodopa Drug Delivery Systems ..................................................................................... 38 

2.3  BIOPOLYMERS AS DRUG DELIVERY SYSTEMS.................................................................... 41 

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2.3.1 Chitosan ................................................................................................................... 42 

2.3.2 Pectin ....................................................................................................................... 44 

2.3.4 Chitosan-Pectin Based PEC .............................................................................................. 46 

CHAPTER THREE   METHODS USED ............................................................................................. 48 

3.1  Materials and Methods ..................................................................................................... 48 

3.2  Study Design ...................................................................................................................... 48 

3.3  Study Location ................................................................................................................... 48 

3.4  Collection and Extraction of Cocoa Pod Husk (CPH) Pectin .............................................. 49 

3.4.1 Characterization of Extracted Hot Water Soluble CPH-Pectin ................................ 49 

3.5  Preparation of Chitosan-Pectin Based Composite Matrix of Levodopa and Carbidopa ... 50 

3.5.1 Fourier Transform Infrared (FTIR) Spectroscopy ............................................................. 51 

3.5.2 Flow Properties of Chitosan-Pectin Based Multiparticulate Matrix ................................ 52 

3.5.3  Content Analysis ...................................................................................................... 53 

3.6  High Performance Liquid Chromatography (HPLC) for Levodopa and Carbidopa Levels . 54 

3.6.1 Chromatographic Conditions ................................................................................... 54 

3.6.2  Preparation of Stock and Working Solutions ........................................................... 54 

3.7 In Vitro Drug Release Study .............................................................................................. 55 

3.8  In Vivo Pharmacokinetic Evaluation of Levodopa/Carbidopa Multiparticulate Matrix .... 56 

3.8.1  Animal Acquisition and Housing .............................................................................. 56 

3.8.2  Animal Groupings for Pharmacokinetic Study ......................................................... 57 

3.8.3  Drug Administration and Sample Collection ........................................................... 57 

3.8.4  Determination of Levels of Levodopa and Carbidopa in Plasma ............................. 57 

3.9 In Vivo Biodistribution Study ............................................................................................. 58 

3.9.1 Animal Grouping and Drug Administration ............................................................. 58 

3.9.2 Sample Collection and Preparation ......................................................................... 59 

3.9.3 HPLC Analysis of Levodopa in Brain Tissue .............................................................. 59 

3.10  Ethical Considerations ................................................................................................... 60 

3.11  Data Analysis ................................................................................................................. 60 

CHAPTER FOUR   RESULTS ............................................................................................................ 62 

4.1 Fourier Transform Infra-Red (FT-IR) Studies ..................................................................... 62 

4.2 Swelling Index of Hot Water Soluble (HWS) CPH Pectin ................................................... 62 

4.3 Characterization of Chitosan-Pectin Based Matrix of Levodopa/Carbidopa ...…………..    

623 

4.3.1 FTIR - Drug Excipient Compatibility Study ............................................................... 63 

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4.3.2 Flow and Precompression Parameters .................................................................... 64 

4.3.3 Drug Content Analysis ............................................................................................. 64 

4.4 HPLC Analysis of Levodopa and Carbidopa ……………………………………………….....……………   

625 

4.4.1 Chromatogram for Levodopa and Carbidopa .......................................................... 65 

4.4.2 Standard Calibration Curve for Levodopa and Carbidopa ..................................... 677 

4.5 In Vitro Drug Release Studies in Simulated Intestinal Fluid .............................................. 68 

4.6  In Vivo Pharmacokinetic Evaluation of Levodopa/Carbidopa Multiparticulate Matrix ... 74 

4.6.1  Concentration-time Curves of Levodopa in the Four Treatment Groups ............... 74 

4.6.2  Pharmacokinetic Parameters of Levodopa .............................................................. 75 

4.7 Biodistribution Study ........................................................................................................ 78 

CHAPTER FIVE   DISCUSSIONS, CONCLUSIONS AND RECOMMENDATIONS ..................... 80 

5.1 Discussion .......................................................................................................................... 80 

5.2 Conclusion ......................................................................................................................... 86 

5.3 Recommendations ............................................................................................................ 87 

REFERENCES ..................................................................................................................................... 88 

APPENDICES .................................................................................................................................... 101 

APPENDIX 1   REAGENTS AND EQUIPMENT ............................................................................ 102 

Appendix 1a: List of Reagents ..................................................................................................... 102 

Appendix 1b: List of Equipment .................................................................................................. 103 

APPENDIX 3   CALCULATION OF ANIMAL EQUIVALENT DOSE (AED) OF……………... 104  

LEVODOPA/CARBIDOPA 

APPENDIX 4   CALCULATION OF LEVODOPA/ CARBIDOPA CONTENT ............................. 106 

APPENDIX 5  CALCULATION FOR AVERAGE PERCENTAGE CUMULATIVE RELEASE ..111 

OF LEVODOPA 

APPENDIX 6  REPRESENTATIVE CHROMATOGRAMS GENERATED FROM THE HPLC...113     

ANALYSIS OF IN VITRO DISSOLUTION MEDIA, PLASMA SAMPLES AND BRAIN 

SAMPLES 

APPENDIX 7   POST HOC ANALYSIS WITH TUKEY’S MULTIPLE COMPARISON .............. 115 

APPENDIX 8   FT-IR SPECTRA FOR DRUG-EXCIPIENTS COMPATIBILITY STUDY ........... 118 

APPENDIX 9   TWO-WAY ANOVA AND POST HOC ANALYSIS OF BIODISTRIBUTION…120 

STUDY   

 

  

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LIST OF FIGURES 

Figure Title Page 

   

2.1 Diagram of the Brain showing the parts affected by Parkinson's 

Disease 

19 

2.2 Coronal Section at the Level of the Substantia Nigra Pars 

Compacta (Snpc) Showing Dopaminergic Neurons in a Control 

(A and B) and a PD Brain (C And D) Stained by Hematoxylin 

and Eosin 

20 

2.3 Proposed Mechanisms of α-Synuclein Pathology in PD 22 

2.4 Synthesis of Levodopa and Dopamine in Dopaminergic Neuron 30 

2.5 Chemical structure of Levodopa 31 

2.6 Levodopa metabolism in the periphery and the CNS 33 

2.7 Structure of Carbidiopa 34 

2.8 Changes in Motor Response Associated with Chronic Levodopa 

Therapy 

38 

2.9 Chemical Structure of Chitin and Chitosan 42 

2.10 Chemical Structure of Pectin 45 

4.1 FTIR of Pectin 62 

4.2 FT-IR Spectra of Levodopa, Carbidopa, Cocoa Pod Husk Pectin, 

Chitosan and Optimized Formulations F3 and F4 

63 

4.3 Representative Chromatograms of Levodopa only (a), Carbidopa 

only (b) and their respective Peaks when Standard Solutions were 

mixed (c) 

66 

4.4a Levodopa Standard Curve showing the Equation of the Line  

(y =26.845x + 54.502) and the Correlation Coefficient (R2 = 

0.994) 

67 

4.4b Carbidopa Standard Curve showing the Equation of the Line  

(y = 16.247x -25.681) and the Correlation Coefficient (R2 = 

0.9948) 

68 

4.5a Release Profile of Levodopa from Formulations in Phosphate 

Buffer pH 6.8 

71 

4.5b Release Profile of Carbidopa from Chitosan-Pectin based 

formulations in Phosphate Buffer pH 6.8 

71 

4.5c Release Profile of Levodopa from F3 and F4 at pH 4.5 72 

4.5d Release Profile of Carbidopa from Formulation F3 and F4 at pH 

4.5 

73 

4.6a Concentration-Time Curves of Levodopa for the Four Treatment 

Groups of SD Rats 

74 

4.6b Log Concentration-Time Curves of Levodopa for the Four 

Treatment Groups of Rats 

75 

4.7 A Chart of the Amount of Levodopa in Rat Brain (µg/G) One 

and Two Hours after Drug Administration 

79 

A6.1 Chromatograms showing the Peak Areas of (a) Levodopa and 

Carbidopa in Dissolution Media (0.1M Hcl), (b) Levodopa and 

Carbidopa in Rat Plasma, (c) Levodopa Standard in A Mixture 

114 

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of Methanol and Chloroform (4:1); and (d) Levodopa in Rat 

Brain Tissues 

A8.1 Individual FT-IR Spectra of Levodopa, Carbidopa, Chitosan, 

CPH Pectin and Optimized Formulations (F3 and F4) 

119 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

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LIST OF TABLES 

Table Title Page 

   

2.1 PARK-Designated Genes involved in Familial Parkinson’s 

Disease 

13 

3.1 Composition of Chitosan-Pectin based Multiparticulate 

Matrix of Levodopa and Carbidopa 

51 

4.1a Flow Properties of Chitosan-Pectin Based Formulations 64 

4.1b Reference Ranges for Hausner ratio, Carr’s Index and Angle 

of Repose 

64 

4.2a Content Analysis - Levodopa Portion 65 

4.2b Content Analysis - Carbidopa Portion 65 

4.3 Concentrations and Peak Areas of Serially Diluted Standard 

Levodopa and Standard Carbidopa Solutions 

67 

4.4a Cumulative Release of Levodopa in Phosphate Buffer pH 6.8 69 

4.4b Cumulative Carbidopa Release from formulations in 

Phosphate Buffer, pH 6.8 

    70 

4.4c Cumulative Release of Levodopa from Optimized 

Formulations, F4 and F5 in Phosphate Buffer at pH 4.5 

72 

4.4d Cumulative Release of Levodopa from Optimized 

Formulations, F4 and   F5 at pH 4.5 

73 

4.5 Pharmacokinetic Parameters of Levodopa in the 4 Treatment 

Groups (± SEM) 

76 

A1 List of Equipment 103 

A5 Calculated Values of Average Cumulative Drug Release at 

Different Time Points 

111 

A5 Two-Way Anova and Post Hoc Analysis of Biodistribution 

Study 

120 

 

 

 

 

 

  

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LIST OF ABBREVIATIONS 

ANOVA  Analysis of Variance 

AUC   Area Under the Curve 

BBB   Blood Brain Barrier 

CD   Carbidopa 

Cmax    Maximum Plasma Drug Concentration 

CNS   Central Nervous System 

COMT   Catechol-O-Methyl Transferase 

CR   Controlled Release 

DDI                             Dopa Decarboxylase Inhibitors 

EDTA   Ethylenediaminetetraacetic Acid 

GPi   Internal Globus Pallidus 

HCL   Hydrochloric acid 

HPLC   High Performance Liquid Chromatography 

Ke    Elimination Rate Constant 

LBs   Lewy Bodies 

LD   Levodopa 

LRRK2  Leucine-rich Repeat Kinase 2 gene 

MAO-B  Monoamine Oxidase-B 

MPTP   1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine 

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MP   Microparticles 

PD   Parkinson's Disease 

PEC                             Polyelectrolyte Complex 

PRKN   Parkin gene 

PINK1   PTEN-Induced Putative Kinase 1 gene 

PBS   Phosphate Buffered Saline 

SD   Sprague-Dawley 

SNCA   Alpha Synuclein 

SNpr   Substantia Nigra pars reticulata 

STDEV  Standard Deviation 

Tmax    Time to achieve maximum plasma drug concentration 

   

 

 

 

 

 

 

 

 

 

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CHAPTER ONE 

INTRODUCTION 

1.1 Background  

Parkinson’s disease (PD) is one of the most common age-related neurodegenerative disorders 

(Tysnes & Storstein, 2017).  PD is characterized by loss of dopaminergic neurons, and 

consequently low levels of dopamine in the brain (Beitz, 2014). Some cardinal symptoms 

associated with PD are: tremor at rest, rigidity, akinesia (or bradykinesia) and postural 

instability, which occasionally can be given the acronym “TRAP”. These symptoms begin 

gradually and worsen as the disease progresses (Kouli et al., 2018). Although less appreciated, 

non-motor symptoms such as dementia, autonomic dysfunction, sleep and sensory 

abnormalities, among others, also present in patients with PD.  

Levodopa, a biological precursor of dopamine, is the drug of choice in the treatment of PD.  

After absorption and transport across the blood-brain barrier (BBB), levodopa is converted into 

dopamine by dopa decarboxylases (also known as aromatic amino acid decarboxylase), thus, 

restoring the level of dopamine in the depleted striatum (Kouli et al., 2018; Zahoor et al., 2018). 

When administered orally, levodopa exhibits low bioavailability (30%) and very low brain 

uptake due to its extensive metabolism by aromatic amino acid decarboxylase in peripheral 

circulation (Arisoy et al., 2020). Furthermore, the systemic conversion of levodopa to 

dopamine leads to unwanted side effects such as nausea, vomiting, cardiac arrhythmias, and 

hypotension (Salat & Tolosa, 2013). Hence, levodopa is routinely co-administered with dopa 

decarboxylase inhibitors such as carbidopa or benserazide.  

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Usually, levodopa with carbidopa combination (levodopa/carbidopa) is effective. However, as 

the disease advances it becomes increasingly difficult to manage associated symptoms. 

Furthermore, motor fluctuations, that is, “end of dose wearing off” (periods with 

Parkinsonism), “on” (periods with near normal motor function and good antiparkinsonian 

effect) and “dyskinesia” (involuntary movement), may develop within months or years after 

initiating levodopa/carbidopa therapy (Salat & Tolosa, 2013). These motor complications are 

associated with the discontinuous or pulsatile stimulation of nigrostriatal dopaminergic neurons 

as a result of variable drug absorption and transit across the BBB, and the fluctuating plasma 

concentrations of levodopa due to its short half-life (Senek et al., 2017). 

Following the discovery that intravenous levodopa infusions could reduce response 

fluctuations by maintaining constant and adequate plasma drug concentrations, controlled-

release levodopa formulations were developed (Erni & Held, 1987; K. C. Yeh et al., 1989). 

Studies also suggest that maintaining constant dopamine levels in the central nervous system 

(CNS) lowers or prevents the emergence of motor fluctuations and dyskinesia in patients with 

Parkinson's disease (Gershanik & Jenner, 2012; Olanow et al, 2020; Wright & Waters, 2013). 

Thus, a number of studies have focused on the development of improved drug delivery systems 

in order to improve bioavailability of levodopa, maintain a near-constant plasma concentration 

of levodopa, and minimize unwanted motor complications of levodopa (Freitas et al., 2016; 

Garbayo et al., 2013). Among the various drug delivery systems includes the use of natural, 

biocompatible polymer matrices (Mohan et al., 2009; Ngwuluka et al., 2015; Sabel et al., 1990). 

Polymers like chitosan and pectin are promising biopolymers and candidates for modified drug 

delivery systems (MDDS). Chitosan and pectin have good physicochemical characteristics, are 

biodegradable, readily available and possess minimal toxicity (Morris et al., 2010). 

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Chitosan is a cationic polymer with outstanding mucoadhesive properties which makes it a 

perfect excipient for MDDS. The positively charged groups of chitosan readily interact with 

negatively charged mucous membranes of the gastrointestinal tract, thereby increasing 

adhesion, and thus improving contact time for drug absorption (Saikia et al., 2015). 

Furthermore, chitosan has been shown to have permeation enhancing properties (Bernkop-

Schnürch & Dünnhaupt, 2012; Soliman et al 2014). 

Despite afore-mentioned merits, chitosan tends to dissolve in acidic environment of the 

stomach, compromising its mucoadhesive capacity and resulting in an uncontrolled release of 

the active pharmaceutical ingredient. Studies suggest that in order to overcome this challenge, 

the structure of chitosan needs to be modified or combinations with other excipients have to be 

made (Bernkop-Schnürch and Dünnhaupt, 2012; Luo and Wang, 2014).  One of the excipients 

that can be successfully combined with chitosan is pectin. 

Pectin is a non-toxic, biodegradable, biocompatible, and an anionic polysaccharide present in 

the primary cell wall of plants (Cheikh et al., 2019; Morris et al., 2010). Recent studies have 

showed that coca pod husk could be a good source of pectins (Adi-Dako et al., 2018; Vriesmann 

et al. , 2012). Cocoa pod husk (CPH) pectin is extracted from pod husk waste after processing 

of cocoa beans. CPH pectin has the requisite physicochemical characteristics to be used as a 

multifunctional pharmaceutical excipient (Adi-Dako et al., 2016). 

As an anionic polymer, pectin interacts with chitosan to form a polyelectrolyte complex (PEC). 

The intermolecular interaction between these polysaccharides of opposite charges has been 

applied in the design of drug delivery systems (García et al., 2015). Studies have shown that 

PECs have the ability of encapsulating drugs in the polymeric matrix at the molecular level, 

thereby enhancing the physicochemical and pharmacokinetic characteristics of drugs (Lu et al., 

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2010; Ngwuluka et al., 2015).  Furthermore, pectin resists the action of digestive enzymes 

present in the upper part of the gastrointestinal tract and, in contrast with chitosan, is able to 

withstand low pH conditions (Cheikh et al., 2019). CPH pectin is reported to have the ability 

to swell at varying extents depending on the pH, ionic strength, and presence of salts in the 

medium. The swelling characteristics of CPH pectin makes it a suitable binder or matrix agent 

in controlled release formulations (Adi-Dako et al., 2018). 

Based on available literature, it is possible that a combination of chitosan and pectin may have 

many advantages. Composites of chitosan and pectin have been used previously as carriers in 

drug delivery systems of diclofenac sodium, vancomycin, curcumin, among others (Cheikh et 

al., 2019; García et al., 2015; Hwang & Shin, 2018; Marudova et al., 2005; Marudova et al., 

2004; Zambito & Di Colo, 2003). However, there is paucity of data on the in vitro and/or in 

vivo characteristics of chitosan-CPH pectin-based matrix of levodopa/carbidopa. Since the 

pharmacological effects of levodopa have been shown to correlate with its plasma 

concentration, this current study sought to formulate and evaluate the in vitro release and 

pharmacokinetic profile of chitosan and CPH-pectin-based composite of levodopa/carbidopa.  

 

1.2 Problem Statement  

Parkinson’s disease (PD) is a neurodegenerative disease that affects one’s ability to control the 

skeletal muscular system (Beitz, 2014). PD is estimated to affect over 6 million people 

worldwide (Dorsey et al., 2018). In Africa, reports suggest that prevalence ranges from 

7/100,000 - 67/100,000 (Williams et al., 2018).  

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Although the disease was discovered many years ago (1817), available therapies are unable to 

slowdown or stop the progression of the disease (Maiti et al., 2017). Therefore, treatment is 

aimed at relieving symptoms and improving the quality of life of patients. Levodopa, the gold 

standard in managing PD, may cause involuntary movements (dyskinesias) and motor 

fluctuations in patients (Salat & Tolosa, 2013). These motor complications have been 

associated with the discontinuous or pulsatile stimulation of dopaminergic neurons as a result 

of variable drug absorption and transit of levodopa across the BBB (Senek et al., 2017). It is 

widely believed that reducing the pulsatile stimulation of dopaminergic neurons lowers the risk 

of levodopa-induced motor complications (Schaeffer et al., 2014; Wright & Waters, 2013). 

In order to improve the release profile and bioavailability of levodopa in formulations, 

alternative routes of administration (such as intravenous, transdermal, pulmonary and 

intraduodenal) have been explored (Salat & Tolosa, 2013; Sharma et al., 2014).  

However, because of the chronic nature of the disease, oral administration remains the most 

convenient route (Ngwuluka et al., 2015). Several oral drug release systems including 

immediate release formulations, dual-release formulations, extended release, among others, 

have been developed, however, most of these are unable to provide constant and sustained 

delivery of levodopa (Freitas et al., 2016). 

In an attempt to address the aforementioned challenges with PD management, this study sought 

to develop a sustained release formulation of levodopa and carbidopa using chitosan and CPH 

pectin as release modifiers. 

 

 

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1.3 Justification 

Recent studies have tried to explore new strategies to improve oral delivery of previously 

existing drugs for the management of PD (Dankyi et al., 2020; Margolesky & Singer, 2018; 

Ngwuluka et al., 2015; Senek et al., 2017). One of the novel approaches is the use of 

biopolymer matrices which act as carriers for sustained and extended release of drugs 

(Bukhary, Williams, & Orlu, 2020; L. N. M. Ribeiro et al., 2017).  

Biopolymers like chitosan and pectin are readily available, eco-friendly immunocompatible, 

non-toxic and biodegradable. Also, their use as excipients for drug formulation is less 

expensive compared with synthetic polymers like polyglycolic acid (PGA), polylactic acid 

(PLA), among others. 

Moreover, chitosan consists of several positively charged groups which readily interact with 

the negatively charged mucous membranes of the gastrointestinal tract, thereby increasing 

adhesion, and thus improving contact time for drug absorption (Saikia et al., 2015). Cocoa pod 

husk (CPH) pectin, an anionic polysaccharide, also has requisite physicochemical 

characteristics to be used as a multifunctional pharmaceutical excipient with remarkable 

properties (Adi-Dako et al., 2016). 

As oppositely charged polymers, chitosan and pectin interact to form polyelectrolyte complex 

(PEC). Studies have shown that PECs have the ability to encapsulate drugs in a polymeric 

matrix at the molecular level thereby enhancing the physicochemical and pharmacokinetic 

characteristics of drugs (Lu et al., 2010; Ngwuluka et al., 2015). Chitosan-pectin based 

polyelectrolyte complexes have been employed in the design of modified drug delivery systems 

as well as site-specific drug delivery systems.  In recent studies conducted by Cheikh et al., 

2019 and Wang, 2017, chitosan-pectin based PECs were used to successfully encapsulate and 

sustain the release of aceclofenac and nisin, respectively. 

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Furthermore, pectin  resists the action of digestive enzymes present in the upper part of the 

gastrointestinal tract and, in contrast with chitosan, is able to withstand low pH conditions 

(Cheikh et al., 2019). Thus, combining chitosan and pectin in drug formulation could lead to 

products with enhanced characteristics. 

There is currently no known study that has evaluated the in-vitro release profile and 

pharmacokinetic characteristics of chitosan-pectin based composites of levodopa/carbidopa for 

oral drug delivery. Therefore, in the present investigation, an attempt has been made to increase 

therapeutic efficacy, reduce frequency of administration, and improve patient compliance, by 

developing modified release formulation of levodopa/carbidopa using varying amounts of 

chitosan and CPH pectin composites as drug release modifiers.  

 

1.4  Hypothesis 

There is no difference in pharmacokinetic characteristics between chitosan-pectin-based matrix 

of levodopa/carbidopa and the levodopa/carbidopa immediate release formulation. 

 

1.5  Aim  

To evaluate the in vitro release and in vivo pharmacokinetic characteristics of chitosan-pectin-

based matrix of levodopa/carbidopa. 

 

 

 

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1.6  Specific Objectives  

Below are the specific objectives of this research work: 

1. To formulate chitosan-pectin based matrix of levodopa/carbidopa 

2. To determine the physicochemical properties and in vitro release profile of chitosan-

pectin based matrix of levodopa/carbidopa. 

3. To estimate the pharmacokinetic and biodistribution profile of the chitosan-pectin-

based matrix of   levodopa/carbidopa using a rat model. 

   

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CHAPTER TWO 

LITERATURE REVIEW 

2.1  Parkinson’s Disease 

2.1.1 History and Background 

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by both 

motor and non-motor system manifestations (Beitz, 2014). Medically, the disease was first 

described as “Paralysis agitans (Shaking palsy)” by James Parkinson, an English surgeon, in 

1817. Long before Parkinson made his observations, fragments of Parkinsonism had been 

captured in earlier descriptions. For instance, ancient Chinese sources and traditional Indian 

texts from as far as 1000 BC provided descriptions that suggest PD. Sylvius de la Boë touched 

on rest tremor and Sauvages described festination (Goetz, 2011). Parkinson in his paper (An 

Essay on the Shaking Palsy) captured the condition as: “involuntary tremulous motion, with 

lessened muscular power, in parts not in action and even when supported; with a propensity to 

bend the trunk forward, and to pass from a walking to a running pace: the senses and intellects 

being uninjured” 

Later on, in the 19th century, Jean-Martin Charcot gave credit to James Parkinson by referring 

to the condition as “maladie de Parkinson” or Parkinson’s disease. Charcot, however, was more 

thorough in his descriptions and was able to distinguish between rigidity, bradykinesia and 

muscle weakness associated with the disease (Obeso et al., 2017).  Charcot’s contribution to 

PD include not only his studies but also that of his students. He and his students described in 

full detail the arthritic changes, dysautonomia, and pain that can accompany Parkinson's 

disease. They also identified two prototypes, the tremorous and the rigid/akinetic form of PD.  

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Ordenstein, one of Charcot’s students, wrote his medical thesis on Parkinson’s disease (1867) 

and introduced belladonna as a treatment option. Another student of his, Edouard Brissaud 

(1852-1909) was the first to describe midbrain lesions and propose damage to the subtantia 

nigra as the main anatomical change in Parkinson’s disease (Goetz, 2011) 

Based on his personal experience with 80 patients in the 1880s, William Gowers in his “Manual 

of Diseases of the Nervous System,” correctly identified that men were more prone to PD than 

women and also detailed the joint deformities typical of the disease. 

The findings of Brissaud, set the stage for other scientists like Trétiakoff and Foix and 

Nicolesco to further explore the pathologic studies of the midbrain in relationship to PD during 

the 1920s. These researchers observed that there were low levels of dopamine and degeneration 

of nerve cells in the substantia nigra. This made effective treatment of Parkinson’s disease 

with dopamine agonist a possibility (Goetz, 2011). 

Many clinicians from the 19th century to date, have attempted to further characterize and 

understand the nature of the disease, and have yielded incredible discoveries and advances in 

medical and surgical therapeutics (Obeso et al., 2017) 

2.1.2 Epidemiology 

PD is the most common age-related neurodegenerative disorder after Alzheimer’s disease, 

affecting the elderly and middle aged (Tysnes & Storstein, 2017). Several epidemiological data 

on PD exist. However, direct comparison of prevalence estimates of PD is impossible because 

of the methodological differences between such studies. Generally, PD affects more than 1% 

of the population above 60 years, and nearly 4% of the population in older year groups (Tysnes 

& Storstein, 2017). About 80 % of individuals develop PD between the ages of 40 and 70 years. 

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The average age at which PD presents is 60 years, with about 80 % of individuals developing 

the disorder between the ages of 40 and 70 years. However, young onset PD (developing 

symptoms before age 40 years) is reported in about 5 % of PD cases (Yao et al., 2013).  

2.1.3 Aetiology and Risk Factors 

Parkinson’s disease is multifactorial in nature. Environmental and genetic factors have been 

reported to play key roles. Age is by far the biggest risk factor for PD with a mean onset age 

of 60 years. Men have been shown to be at a greater risk of PD than women (Beitz, 2014). 

Although there are cross-cultural differences higher prevalence have been reported in Europe, 

South America, and North America compared with African, Arabic and Asian nations (Kalia 

& Lang, 2015).  

2.1.3.1 Genetics 

Studies have shown that about 10 -15% of PD patients have a very close relative who also has 

the disease and about 5% have Mendelian inheritance (Samii et al., 2004). Also, the likelihood 

of an individual developing PD has been associated with poorly defined polygenic risk factors. 

Genes found to potentially cause PD are assigned a “PARK” name in the order of identification. 

Currently, 23 PARK genes have been linked to PD. Mutations in these  PARK genes result in 

either autosomal recessive (e.g., PRKN, PINK1, and DJ-1) or autosomal dominant inheritance 

(e.g., SCNA, LRRK2, and VPS32)  as shown in Table 1.1. However, the involvement of some 

of these genes in PD is still not well understood.  

The most commonly inherited form of the disease is due to an autosomal dominant mutation 

in the leucine-rich repeat kinase 2 (LRRK2) protein. Mutations in LRRK2 have been associated 

with mitochondrial abnormalities as well as dysregulation of macro-autophagy. LRRK2 

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mutations have also been implicated in sporadic and idiopathic PD. Although the exact 

mechanism by which LRRK2 is implicated in the pathogenesis of PD remains unclear, it is 

believed that LRRK2 kinase inhibitors may be beneficial for at least some forms of PD. Other 

genes that have been closely linked to PD are parkin (PRKN), PTEN-induced putative kinase 

1 (PINK1), protein deglycase DJ-1 and alpha-synuclein (SNCA) (Davie, 2008; Lesage and 

Brice, 2009). More often than not, people carrying mutant forms of these genes end up 

developing PD. 

Parkin is an E3 ubiquitin ligase. Mutations in this gene has been associated with an autosomal 

recessive form of Parkinson’s disease. Mutations in PINK1, the protein responsible for 

recruiting Parkin to the mitochondrial membrane, also leads to an early-onset phenotype of 

Parkinson’s disease. Protein deglycase DJ-1, also known as Parkinson disease protein 7, is a 

protein which in human beings is encoded by the PARK7 gene. Mutations in DJ-1 have been 

reported to cause an autosomal recessive, early-onset form of PD (Bonifati et al., 2003). A 

point mutation in the α-synuclein gene as well as duplications or triplications of 

the wildtype gene have been shown to cause neurodegeneration. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Table 1.1: PARK-Designated Genes involved in Familial Parkinson’s Disease  

PARK Gene 
OMIM 

reference 
Inheritance Description Clinical features 

PARK1 

& 

PARK4 

SNCA 168601 AD α-synuclein 

Ranging from 

classical PD to 

early-onset cases 

with dementia, 

autonomic 

dysfunction, and 

rapid progression 

PARK2 PRKN 600116 AR 

parkin RBR E3 

ubiquitin 

protein ligase 

Early-onset PD, 

slow progression, 

often features of 

dystonia 

PARK5 UCHL1 613643 AD 

Ubiquitin C-

terminal 

hydrolase L1 

Classical PD—

only one family, 

findings not since 

replicated 

PARK6 PINK1 605909 AR 

PTEN-induced 

putative kinase 

1 

Early-onset PD, 

slow progression 

PARK7 DJ-1 606324 AR 

Parkinsonism-

associated 

deglycase 

Early-onset PD, 

slow progression 

PARK8 LRRK2 607060 AD 
Leucine-rich 

repeat kinase 2 

Classical PD with 

less frequent 

dementia and 

slower 

progression 

PARK9 ATP13A2 606693 AR 

Cation-

transporting 

ATPase 13A2 

Early-onset 

(adolescence), 

atypical 

parkinsonism 

with dementia, 

spasticity and 

supranuclear 

palsy (Kufor–

Rakeb syndrome)  

PARK11 GIGYF2 607688 AD 

GRB10 

interacting GYF 

protein 2 

Classical PD 

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PARK13 HTRA2 610297 AR 
HtrA serine 

peptidase 2 
Classical PD 

PARK14 PLA2G6 612593 AR 

Calcium-

independent 

phospholipase 

A2 enzyme 

Early onset with 

atypical features 

(dystonia 

parkinsonism) 

PARK15 FBX07 260300 AR F-box protein 7 

Early onset with 

atypical features 

(pallido-

pyramidal 

syndrome) 

PARK17 VPS35 614203 AD 

Vacuolar 

protein sorting-

associated 

protein 35 

Classical PD 

PARK18 EIF4G1 614251 AD 

Eukaryotic 

translation 

initiation factor 

4 gamma 1 

Classical PD 

PARK19 DNAJC6 615528 AR HSP40 Auxilin 
Early-onset PD, 

slow progression 

PARK20 SYNJ1 615530 AR Synaptojanin 1 

Parkinsonism 

with dystonia and 

cognitive decline 

PARK21  DNAJC13 616361 AD 

Receptor 

mediated 

endocytosis 8 

(RME-8) 

Classical PD 

PARK23 VPS13C 616840 AR 

Vacuolar 

protein sorting-

associated 

protein 13C 

Early-onset PD, 

rapid progression 

OMIM: Online Mendelian Inheritance in Man database, AD: autosomal dominant, AR: autosomal recessive. 

PARK3 PARK10, PARK12, PARK16, and PARK22 are considered risk factors or the genes that have not been 

identified yet and are not included in this table. 

 

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2.1.3.2 Environmental Factors 

2.1.3.2.1 Pesticides, herbicides and heavy metals 

In 1983, it was observed that several individuals after injecting themselves with a drug 

contaminated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), exhibited typical 

signs of PD. Further studies unveiled that in vivo, MPTP undergoes metabolism into the 

neurotoxin, MPP+ (1-methyl-4- phenylpyridinium), which is a mitochondrial complex-I 

inhibitor that selectively damages dopaminergic cells in the substantia nigra (Langston et al., 

1983). This finding led to the notion that exposure to some environmental toxins could be 

associated to developing PD. Several other studies have shown a link between exposure to 

some chemicals in pesticides (e.g. Rotenone) and herbicides (e.g. Paraquate), and the incidence 

of Parkinson's disease (Kouli et al., 2018). 

Many epidemiological studies have also shown a relationship between Parkinson’s disease and 

exposure to welding and heavy metals such as lead, mercury, manganese, iron, copper, 

bismuth, aluminum, zinc, thallium, among others. It is hypothesized that these heavy metals 

accumulate in the substantia nigra and increases oxidative stress which in turn leads to the 

neurodegeneration (Lai et al., 2002). Moreover, exposure to some of these heavy metals 

activate and trigger the expression of PARK genes (Bjorklund et al., 2018; Peng et al., 2010). 

These heavy metals have also been reported to have synergistic toxicity. A study conducted by 

Peng et al, 2007, demonstrate that combined environmental exposure to iron and paraquate (a 

herbicide) results in accelerated age-related degeneration of nigrostriatal dopaminergic 

neurons. 

 

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2.1.3.2.2 Cigarette smoking 

Several epidemiologic studies have shown a protective effect of smoking on PD. Although this 

theory is counter-intuitive, the results of these studies have been very consistent over the years, 

proving that cigarette smokers have a reduced risk of PD compared with non-smokers. This 

inverse relationship between cigarette smoking and PD have been reported to be dose 

dependent. (Kouli et al., 2018; Mappin-Kasirer et al., 2020; Tanner et al., 2002). A recent study 

conducted by Mappin-Kasirer et al, 2020 demonstrated that current smokers had 40% lower 

risk of PD compared with never smokers. Even among twin pairs (homozygotic and 

heterozygotic) who share the same DNA and often the similar environment, studies have shown 

that the twin without PD tended to smoke more than the twin with PD (Tanner et al., 2002; 

Wirdefeldt, Gatz, Pawitan, & Pedersen, 2005). 

The reasons underlying this associated reduced risk are not yet fully understood. However, 

nicotine, the principal psychoactive chemical in cigarette smoke, is a cholinergic agonist. It 

stimulates the nicotinic acetylcholine receptor (nAchR), thereby mimicking acetylcholine. 

Different animal studies have demonstrated that nicotine and its receptors are involved in 

dopamine signaling and that nicotine protects against cell damage in dopaminergic neurons. It 

has been shown to have beneficial effects on sporadic and genetic models of PD.  Nicotine has 

also been found to reduce MPTP-induced dopaminergic neurotoxicity (Costa et al., 2001; 

Maggio et al., 1998; Quik & Kulak, 2002).  

Nevertheless, because the level of dopamine, the main compound responsible for addiction is 

reduced in Parkinson’s disease, some researches have argued that PD patients are less likely to 

smoke cigarette (Ritz et al., 2014). Hence, it is difficult to ascertain whether smoking prevents 

PD or whether PD aids in preventing cigarette addiction.  

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2.1.3.2.3 Caffeine 

Accumulating evidence from epidemiological and animal studies suggest that caffeine has a 

protective effect on PD and that coffee drinkers have reduced risk of developing. A study by 

Noyce et al., 2012  reported a 25% risk reduction in developing PD among coffee drinkers. 

Several other studies have also firmly established that coffee drinkers have lower risk of 

developing PD than non-coffee drinkers (Ascherio et al., 2001; Hernán et al., 2002; Ren & 

Chen, 2020) 

Caffeine, an adenosine A2A receptor antagonist, has been shown to confer neuroprotection 

against dopaminergic neurodegeneration mediated by MPTP, 6-hydroxydopamind (6-OHD), 

rotenone and expression of α-synuclein (α-Syn) in PD models.  It is hypothesized that caffeine 

exerts its neuroprotective effects by modulating neuroinflammation, mitochondrial function 

and excitotoxicity (Ren & Chen, 20200. It has also been shown to modulate α-Syn degradation 

(Schepici et al., 2020).  

2.1.3.3 Infectious Organisms  

Studies have shown that patients with various viral (e.g., influenza virus, Coxsackie, Japanese 

encephalitis B, Herpes viruses, Hepatitis C virus, etc.), bacterial (e.g., Helicobactor pylori, 

Clamydophilia pneumoniae, Borrelia burgdorferi, among others) and fungal infections (e.g., 

Malassezia) might be at increased risk of Parkinson's disease. The risk of PD in these patients 

were however shown to vary with each infection (Smeyne et al., 2021; Wang et al., 2020). 

Although the pathogenic mechanisms by which these microorganisms cause PD remain 

incompletely understood, some of these pathogens have been reported to be neurotropic 

(tending to attack or affect the nervous system preferentially), causing neuroinflammation and 

neurodegeneration in the substantia nigra of the brain (Limphaibool et al., 2019). 

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2.1.4 Pathophysiology 

The pathology of Parkinson’s disease remained unclear until the early 20th century. In 1912, 

Friedrich Heinrich Lewy, a German-born American neurologist, identified “neuronal 

cytoplasmic inclusions in a variety of brain regions” later known as Lewy bodies (Engelhardt 

& Gomes, 2017). In 1919, Konstantin Tretiakoff, a Russian neuropathologist, pointed out that 

the loss of neurons in the substantia nigra pars compacta (SNc) of the brain was the most critical 

abnormality in PD. The role of dopamine and its depletion from the basal ganglia was 

discovered by researchers in the late 1950s to be very key in understanding the pathophysiology 

of PD (Hornykiewicz, 2006). A diagram of the brain and the parts affected in PD is shown in 

Figure 2.1. 

Several attempts have been made to possibly explain the underlying mechanisms of PD. The 

presence of α-synuclein-containing Lewy bodies (LBs) and the loss of dopamine producing 

neurons have been proposed to be the neuropathological hallmarks of PD (Beitz, 2014; Braak 

& Braak, 2000). Other processes implicated in the pathogenesis of PD include abnormal protein 

clearance, mitochondrial dysfunction, and neuroinflammation (Kouli et al., 2018).  

 

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Figure 2.1: Diagram of the Brain showing the parts affected by Parkinson's Disease 

(Source: Designua/ Shutterstock.com) 
 

 

2.1.4.1 Neurodegeneration 

The major morphological change that occurs in the PD brain, is the loss of the darkly pigmented 

area in the substantia nigra pars compacta (SNpc) and locus coeruleus as shown in Figure 2.2.  

 

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Figure 2.2: Coronal Section at the Level of the Substantia Nigra Pars Compacta (Snpc) 

Showing Dopaminergic Neurons in a Control (A and B) and a PD Brain (C And D) Stained 

by Hematoxylin and Eosin (Source: Kouli et al., 2018). 
 

 

This pigmentation loss is directly linked to the death of dopaminergic (DA) neuromelanin-

containing neurons in the SNpc and noradrenergic neurons in the locus coeruleus (Dickson, 

2012). As a result, denervation of the nigrostriatal pathway occurs, leading to diminished 

dopamine levels in the striatum. The reduction in dopaminergic signaling accounts for the 

manifestation of the cardinal motor symptoms in PD such as bradykinesia, distal tremor, and 

muscle rigidity (Kouli et al., 2018). Apart from the SNpc, neurodegeneration has also been 

seen in several subcortical nuclei such as the locus coereleus, the dorsal motor nucleus of the 

vagus nerve, the raphe nuclei, among others and also the hypothalamus and the olfactory bulb 

(Giguère et al., 2018). Other neurotransmitter systems affected in PD include; the cholinergic, 

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GABAergic, serotonergic, noradrenergic, adenosinergic, glutamatergic and histaminergic 

(Kalia et al., 2013). Degeneration in these pathways is thought to be responsible for some of 

the non-motor symptoms of PD that do not respond well to dopamine replacement therapies 

(Kouli et al., 2018) 

2.1.4.2 Lewy Bodies   

Lewy bodies (LBs) are intracellular cytoplasmic inclusions consisting of a granular and fibrillar 

core with a surrounding halo. LB are composed of number of proteins (such as ubiquitin, 

parkin, heat shock proteins, cytoskeletal proteins, etc.)  lipids, proteasomal and lysosomal 

elements, and other materials (Braak et al., 2003; Del and Braak, 2012). The principal structural 

constituent of LBs is filamentous α-synuclein, a protein ubiquitously expressed in the brain. 

Alpha synuclein in the brain is mostly unfolded without a defined tertiary structure. However, 

upon interaction with negatively charged lipids (e.g., phospholipids that make up cell 

membranes) α-synuclein misfolds into dimers, trimers and oligomers which further aggregate 

into protofibrils and amyloid fibrils found in Lewy bodies (Baba et al., 1998; Eliezer et al., 

2001). The formation and abnormal build-up of misfolded α-synuclein containing LBs cause 

neuronal damage and lesion patterns in the brain and is believed to be the cause of 

neurodegeneration in such regions of the brain. Lesions in the medulla, pons and dorsal nucleus 

are reported to be the cause of the early olfactory and rapid eye movement features of PD 

(Braak et al., 2004). The processes and mechanisms of α-synuclein mediated neuronal damage 

is described in Figure 2.3 

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Figure 2.3: Proposed Mechanisms of α-Synuclein Pathology in PD 

(Source: Researchgate.net, 3/10/21) 

2.1.5 Clinical Presentation and Diagnosis 

PD is characterized by four cardinal features under the acronym “TRAP”: tremor at rest, 

rigidity, akinesia (or bradykinesia) and postural instability. These symptoms begin gradually 

and become worse as the disease progresses (Kouli et al., 2018).  PD is also associated with 

non-motor symptoms (such as autonomic dysfunction, hyposmia, constipation, olfactory and 

sleep disorders, fatigue etc.)  which often manifest as early as 12-14 years before diagnosis is 

made and can last for 4 to 6 years on average (Postuma et al., 2012). As the disease progresses, 

thermoregulatory dysfunction, neuropsychiatric symptoms and other clinical signs may occur. 

Neuropathic and nociceptive pain may also occur at either the early or later stages of the disease 

(Maetzler & Hausdorff, 2012; Postuma et al., 2012). 

In majority of PD patients (about 90%), the disease begins in an insidious manner, for instance, 

difficulty while getting out of a chair, and is often unnoticed or misinterpreted. Sometimes 

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diagnosis of PD is delayed as the non-motor symptoms preceding the disease is mistaken for 

signs of normal ageing. Accumulating evidence suggest that PD may begin in the peripheral 

autonomic nervous system and/or the olfactory bulb, with the pathology then spreading through 

the CNS, affecting the lower brainstem structures before getting to the substantia nigra 

(Katzenschlager et al., 2008; Schrag et al., 2015). This may thus explain the occurrence of non-

motor symptoms in PD patients well before motor symptoms set in.  

2.1.5.1 Bradykinesia 

Bradykinesia, the most characteristic primary motor symptom of PD, has been defined as a 

reduction in the speed, gait and amplitude of a repetitive action involving voluntary movements 

(Grabli et al., 2012).  Bradykinesia is reported to be a hallmark of basal ganglia disorders and 

may also occur in other disorders such as depression (Jankovic, 2008). Initial manifestations 

involve slowness in performing daily activities, slow movement and reaction times, difficulties 

with performing simultaneous tasks, impaired swallowing, loss of gesturing, decreased 

blinking, among others (Berardelli et al., 2001). Bradykinesia is usually assessed by making 

patients perform rapid, repetitive, alternating movements of the hand and heel taps and 

observing not only slowness but also decreased amplitude. Patients with bradykinesia have 

difficulty in initiating movements and fail to implement fast movements. Bradykinesia has been 

shown to be influenced by the emotional state of the PD patient (Jankovic, 2008). 

2.1.5.2 Tremor 

Deuschi et al., defined tremor as “rhythmical, involuntary, oscillatory movement of a body part 

produced by alternating or synchronous contractions of antagonist muscles” (Deuschi et al., 

1998). It occurs as the initial symptom in about 60% of PD patients. Tremors have been 

classified into different types based on the position that underlines the tremor. Rest tremor 

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basically occurs when the body is relaxed and is defined as rhythmic muscle contraction and 

relaxation occurring when there is no voluntarily activated muscle contraction (Deuschl et al., 

1998). It is mostly seen in the distal part of an extremity but can also involve the jaw, chin, lips 

and legs. Typically, rest tremors tend to disappear with action and during sleep.  Postural tremor 

occurs when a patient maintains an outstretched position against gravity (Jankovic et al., 1999). 

It may be one of the first signs of PD and is reported to be more prominent than rest tremor. 

The tremor of PD is different from essential tremor (previously known as benign essential 

tremor or familial tremor), one of the most common movement disorders.  Both postural and 

rest tremors occur in the same (4–6 Hz) frequency range and are responsive to dopaminergic 

therapy in contrast to essential tremor (Váradi, 2020).  Also, essential tremor may involve the 

head, neck and voice and is often reduced by the intake of alcohol, beta-blockers and botulinum 

toxin. Early-age essential tremor is reported to be a potential risk factor in developing PD 

(Shahed & Jankovic, 2007). 

2.1.5.3 Rigidity 

Rigidity occurs as inflexibility of the neck, limbs or trunk and is described as tension in the 

muscle, which displays small jerks or a ratchet-like quality when moved passively. It is the 

second most characteristic primary motor symptom of PD. Unlike bradykinesia, where the 

speed of the motion is reduced, in rigidity, movement is limited to a reduced range because of 

muscle stiffness and lack of relaxation capability (Váradi, 2020). Rigidity of PD can also affect 

the face, being displayed as a “masked” look (hypomimia) (J. Jankovic, 2008; Xia & Mao, 

2012). Dopaminergic agonists have been shown to be efficient in reducing rigidity (Váradi, 

2020). 

 

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2.1.5.4 Postural Instability 

Postural instability occurs after the onset of other clinical features, usually at the late stages of 

the disease. It manifests as a result of the loss of postural reflexes. Postural instability (along 

with freezing of gait) is the main symptom responsible for the falls observed in PD patients 

and its attendant risk of hip fractures. Assessment of postural instability is done by the pull test. 

In this test, patients are quickly pulled forward or backward by the shoulders, in order to assess 

the degree of propulsion or retropulsion respectively. The absence of any postural response or 

taking more than two steps backwards suggests an abnormal postural response. 

 

2.1.6 Non-Motor Features of PD  

Although less appreciated, non-motor symptoms also present in PD patients. Studies in recent 

years have shown that Lewy body neurodegeneration affect the enteric and peripheral nervous 

systems (PNS) not only through dopaminergic pathways but, also, GABAergic, cholinergic, 

noradrenergic, glutamatergic, serotonergic and histaminergic nerves (Váradi, 2020). The 

involvement of these nerves is expressed in a wide range of nonmotor symptoms (NMS), such 

as cognitive impairment (e.g., dementia, confusion, impaired judgement), autonomic 

dysfunction (e.g., orthostatic hypotension, gastrointestinal disturbance, sexual dysfunction) 

sleep disturbances (e.g. sleep apnea, restless legs syndrome), sensory abnormalities (e.g. 

paresthesia, pain, olfactory dysfunction and anosmia), mood disturbances (e.g., anxiety, 

depression, apathy)  and neuropsychiatric symptoms. ((Beitz, 2014; Váradi, 2020). Generally, 

all PD patients experience some form of NMS, with an increased frequency observed as the 

disease progresses. Parkinson’s disease is therefore, a complex disorder expressing both motor 

and nonmotor symptoms throughout the progression of the disease.  

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2.1.6 Diagnosis 

The differential diagnosis of PD can be very challenging, especially in the early stages of the 

disease when non-motor features and signs and symptoms of different forms of parkinsonism 

overlap greatly. Studies report error rates as high as 24% in the diagnosis of PD, even with 

movement-disorder specialists attending to most of the patients in such studies (Tolosa et al., 

2006). Moreover, the cardinal motor features of PD may not manifest until approximately 50% 

to 80% of dopaminergic neurons are lost (Berg, 2012; Postuma et al., 2012).  There are no 

definitive tests for the diagnosis of PD, hence, the disease is often diagnosed based on clinical 

criteria. 

Over the years, several clinical diagnostic tools and guidelines have been produced to 

effectively identify symptoms, classify and appropriately diagnose PD, especially in the early 

stages of the disease. Hoehn and Yahr in 1967 made the first attempt to describe the onset and 

progression of PD by providing a five (5)-stage descriptive scale known as the Hoehn and Yahr 

scale (Hoehn & Yahr, 1967). Each stage has a well-defined motor impairment and disability 

by which patients can be classified during disease progression. The original scale has since 

been modified with the addition of stages 1.5 and 2.5 to account for the intermediate course of 

Parkinson disease. The Hoehn and Yahr scale is still one of the most commonly used rating 

scales in PD progression (Goetz et al., 2004) 

In 1988, the United Kingdom Parkinson’s Disease Society Brain Bank (UKPDSBB) provided 

its first form of clinical diagnostic criteria for PD. This guideline provides three different levels 

for classification including diagnostic, exclusion and supportive criteria. The diagnostic criteria 

involve the presence of bradykinesia and at least one of the following symptoms: muscular 

rigidity, 4–6 Hz rest tremor and postural instability (not caused by other disorders). The 

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exclusion criteria consist of a history of repeated strokes or head injury, encephalitis, early 

severe autonomic involvement or dementia, Babinski sign, negative response to levodopa 

treatment and MPTP(1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) exposure. The supportive 

criteria (at least three required) includes unilateral onset, rest tremor, progressive course, 

persistent asymmetry, excellent response to dopaminergic therapy, levodopa-induced 

dyskinesia, positive levodopa response five years or more and clinical course of ten years or 

more. 

In order to distinguish PD from other related conditions, Gelb and his colleagues in 1999 

described an improved criteria known as the Gelb criteria.  This guideline differentiated three 

levels of PD namely; definite, probable and possible. However, the Gelb criteria restricted the 

diagnosis of definite PD to neuropathologic confirmation. 

Subsequently, the importance of the non-motor features of PD and their effects on the quality 

of life of patients, necessitated the generation of newer, improved guidelines, that took into 

account nonmotor features.  In 2009, Lees and his colleagues published a modified version of 

the Queen Square Brain Bank (QSBB) clinical diagnostic criteria (Lees et al., 2009). This 

guideline, mainly based on the UKPDSBB criteria, was extended to include for the first time 

nonmotor features of PD, such as hyposmia and hallucinations (Váradi, 2020). 

The International Parkinson and Movement Disorder Society (MDS) task force in 2015, 

published a novel clinical diagnostic criteria intended for clinical practice and PD research 

known as MDS-PD (Postuma et al., 2015). The development of MDS-PD criteria was largely 

based on the UKPDSBB and Gelb criteria. Several nonmotor features of PD (such as sleep, 

autonomic, psychiatric and olfactory dysfunction) are captured as additional diagnostic 

features.  

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The differential diagnosis of PD must include a comprehensive history and physical 

examination. Clinicians should review the patient’s history to assess symptoms and to rule out 

alternative diagnoses, such as multiple-system atrophy, essential tremor, and other diseases that 

have presentations similar to those of PD. Also, a complete medication history and evaluation 

should be done to identify drug induced parkinsonism (DIP) and to avoid treating patients 

inappropriately. Moreover, laboratory studies may be done to rule out nutritional deficiencies 

and other abnormalities such as thyroid disease. When a patient’s history suggests possible 

exposure to a neurotoxin, toxin screening should be done (DeMaagd & Philip, 2015) . 

 

2.1.7 Management of PD 

Therapies currently employed in managing PD neither slowdown nor stop the progression of 

the disease. Therefore, the primary goal of medical management of PD is to control 

symptomatic motor and non-motor features of the disease, with the aim of minimizing adverse 

events (AEs) and improving the quality of life of patients (DeMaagd & Philip, 2015). 

Appropriate management of PD requires the services of a multidisciplinary team comprising 

of neurologists, movement disorder specialists, general practitioners, pharmacists, nurses, 

physiotherapists and social workers (Van der Marck & Bloem, 2014). The  patient and his or 

her relatives must also be actively involved in taking management decisions (Politis et al., 

2010)  

In order to maximize the clinical outcomes and ensure effective management, both 

pharmacological and non-pharmacological strategies need to be employed.  Pharmacologic 

treatment involve the use of  dopamine precursors (drugs metabolized to yield dopamine) such 

as levodopa; dopamine agonists (drugs that activate dopamine receptors) example ropinirole; 

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centrally acting antimuscarinic drugs (e.g., trihexyphenidyl, benztropine)  or drugs that prevent 

the breakdown of endogenous dopamine such as catechol-O-methyl transferase (COMT) 

inhibitors (e.g., entacapone) and monoamine oxidase B inhibitors, such as selegiline (Gunay et 

al., 2015).  

The choice of drugs depends on a number of factors, such as the stage of disease, age of the 

patient, level of functional disability, cognitive status, AEs associated with the agent, among 

others. Levodopa, compared with the other therapeutic agents, is more efficacious, less costly 

and better tolerated (Salat & Tolosa, 2013). Currently, levodopa, combined with a dopa 

decarboxylase (DDC) inhibitor such as carbidopa or benserazide, is the standard treatment for 

the motor symptoms of PD.  

 

2.2 LEVODOPA/CARBIDOPA FOR MANAGING PD 

2.2.1 Levodopa 

Levodopa, chemically known as L-3,4-di-hydroxyphenyl-alanine, is an aromatic amino acid 

synthesized and used in normal human biology. It is synthesized from L-tyrosine by the 

enzyme, tyrosine hydroxylase, as a biological precursor to dopamine. The schematic 

representation of the biosynthesis of levodopa by hydroxylation is shown in Figure 2.4 below. 

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Figure 2.4: Synthesis of Levodopa and Dopamine in Dopaminergic Neuron 

TH=Tyrosine hydroxylase, AADC= Aromatic amino acid decarboxylase, DAT=DA 

transporter, D1=D1-like DA receptor, D2=D2-like DA receptor. VMAT=Vesicular 

monoamine transporter. 

 

Levodopa is also manufactured as a prodrug and used as a dopamine replacement agent in the 

management of PD and other related conditions. Levodopa, classified as Class I agent, has a 

high solubility and high permeability, according to Biopharmaceutics Classification System 

(BCS). It is a white crystalline compound, shown to be slightly soluble in water, with solubility 

increasing below pH 3 and above pH 8. Its empirical formula is C9H11N04 and its structural 

formula is shown in Figure 2.5. 

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Figure 2.5: Chemical structure of Levodopa 

(Source: www.newdruginfo.com) 

Unlike dopamine, levodopa is able to cross the blood-brain barrier (BBB).  After transport 

across the BBB, levodopa is converted into the neurotransmitter dopamine by aromatic amino 

acid decarboxylases (AADC) also known as dopa decarboxylases (DDC) thus, increasing 

levels of dopamine in the depleted striatum (Kouli et al., 2018; Zahoor et al., 2018).  These 

enzymes are not only present in the CNS but are widely distributed in liver, gastrointestinal 

tract (GIT), kidneys, spleen, heart, adrenals and lungs.  

When administered orally, only 1% of the given dose of levodopa reaches the brain because of 

metabolism and rapid plasma clearance chiefly by peripheral AADC. Levodopa is also shown 

to undergo O-methylation, transamination, and oxidation into other metabolites (Elroby et al., 

2012). The peripheral conversion to dopamine and other metabolites is reported to greatly 

reduce the half-life and bioavailability of levodopa. Furthermore, the systemic conversion to 

dopamine leads to unwanted side effects such as nausea, vomiting, cardiac arrhythmias, and 

hypotension (Salat & Tolosa, 2013). 

 

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2.2.1.1 Pharmacokinetics of Levodopa 

Levodopa is almost completely absorbed following oral administration, with just about 2% of 

drug seen in faeces. Absorption of levodopa is facilitated through a saturable L-neutral amino 

acid transport system (Morgan et al., 1971). A high protein meal appears to affect the 

absorption of levodopa although this effect varies with different formulations. Evidence from 

several studies show that the clinical effect of levodopa is reduced by a daily diet containing 

protein in excess of 1.6 g/kg or a single protein load of approximately 28 g (Carter et al., 1989; 

Simon et al., 2004; Tsui et al., 1989). The findings of positron emission tomography study 

suggest that a protein-rich diet may compete with the uptake of levodopa into the brain, thereby, 

reducing the clinical effects of levodopa (Khor & Hsu, 2008). 

Although levodopa is well absorbed, only about 30% of an administered dose reaches systemic 

circulation and only 1% of the dose ultimately enter the brain because it is extensively 

metabolized in the periphery. Metabolism of levodopa occurs through four pathways; 

decarboxylation by aromatic amino acid decarboxylase (AAAD), 3-O-methylation by 

Catechol-O-methyltransferase (COMT), transamination by tyrosine aminotransferases and 

oxidation by tyrosinase. The decarboxylation pathway is reported to be the principal metabolic 

pathway for levodopa (Khor and Hsu, 2007). Dopamine, the first decarboxylation product may 

be broken down further to give 3,4-dihydroxyphenyl acetic acid (DOPAC), homovanillic acid 

(HVA), and to a lesser extent, norepinephrine and vanillylmandelic acid (Khor and Hsu, 2007) 

as shown in Figure 2.6. 

 

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Figure 2.6: Levodopa metabolism in the periphery and the CNS 

where COMT: -catechol O-methyl transferases, MAO: monoamine oxidases, 3-OMD: 3-O 

methyldopa, DOPAC: 3,4 dihydroxyphenyl acetic acid, HVA: homovanillic acid, 3-MT: 3-

methyldopa (Source: Palma et al., 2013). 

When given alone, levodopa has a plasma half-life of about 50 minutes but this may be 

increased to 90 minutes when co-administered with DDC inhibitors such as carbidopa and 

benserazide (Khor & Hsu, 2008). Levodopa has a high volume of distribution and is not highly 

bound to plasma protein (Hinterberger and Andrews, 1972). Levodopa is mainly excreted via 

urine.  

 

 

 

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2.2.2 Carbidopa 

Dopa decarboxylase inhibitors like carbidopa do not cross the blood-brain barrier even when 

high doses are administered (Lotti & Porter, 1970). These agents primarily stay in the periphery 

and block levodopa metabolism, thereby slowing the plasma clearance of levodopa, reducing 

the rate of the first-pass metabolism, increasing the bioavailability and prolonging its plasma 

half-life. Clinical studies suggest that, the peripheral half-life of levodopa increases from 30 

min to about 90 min when co-administered with DDC inhibitors. Also, the required levodopa 

dose is reduced by 60–80% (Cedarbaum, 1987; Hauser, 2009). Moreover, reduced peripheral 

decarboxylation of levodopa to dopamine decreases the characteristic peripheral side effects of 

dopamine (e.g., nausea, vomiting, anorexia) (Obeso et al., 2017).  

 

Figure 2.7: Structure of Carbidiopa 

(Source: enwikepedia.org) 

In 1975, combinations of levodopa with either carbidopa or benserazide were made 

commercially available (Tolosa et al., 1998) and till date, is approved by the Food and Drugs 

Authority (FDA) for the treatment of PD. 

 

 

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2.2.2.1 Pharmacokinetics of Carbidopa 

Compared with levodopa, carbidopa is absorbed quite slowly, taking about 2 hours (for an 

immediate release formulation) or close to 2.8 hours (for a controlled release formulation) to 

peak in plasma. About 40 to 70 % of an orally administered dose of carbidopa is absorbed 

(Vickers et al., 1974). The bioavailability of carbidopa is not affected by the co-administration 

of Levodopa (Khor & Hsu, 2008). Also, carbidopa is not highly protein bound. The percentage 

plasma protein binding is found to be 36±1.6% (Khor & Hsu, 2008). 

Carbidopa undergoes metabolism to give four metabolites namely; 2-methyl-3-methoxy-4-

hydroxy-phenylpropionic acid, 2-methyl-3,4-dihydroxy-phemnylpropionic acid, 3-hydroxy--

methyl-phenylpropionic acid, and 3,4-didydroxy-phenylacetone (Khor and Hsu, 2007). The 

half-life of carbidopa is about 2 hours when co-administered with levodopa. When 

administered alone, it has been shown to have a similar half-life of 2.08 (Vickers et al., 1974). 

Carbidopa is largely excreted in urine. 

 

2.2.3 Motor Fluctuations and Dyskinesia in Parkinson Disease  

Motor fluctuations and dyskinesia are major complications of levodopa therapy, affecting 

many patients especially as the disease progresses. 

In the 1960s, it became clinically apparent that majority of PD patients who responded to 

levodopa also developed dyskinesias and motor fluctuations. Studies have shown that about 

40% to 75% of PD patients develop these complications after 4–6 years of levodopa therapy 

(Hauser, 2009; Lloyd et al., 1975) although they may occasionally manifest just after few 

weeks or months of treatment.  

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Motor fluctuations refers to alterations between periods of positive response to levodopa 

("on"), and periods marked by reemergence of parkinsonian symptoms ("off") as the response 

to levodopa begins to wear off. Different types of motor fluctuations are observed in PD 

patients namely; wearing off, unpredictable “off”, failure of an “on” response, freezing of gait 

and acute akinesia (Jankovic, 2008; Obeso et al., 2017) . The “wearing off” effect is the first 

and most commonly encountered among patients with PD.  "Wearing off” is characterized by 

the recurrence of parkinsonian symptoms as the effect of exogenous levodopa reduces near the 

end of the dose interval.  "Wearing off" is often observed in patients usually three to four hours 

after a given dose (Liang, 2018). 

Levodopa induced dyskinesia (LID) is defined as abnormal involuntary movement occurring 

as a result of the use of levodopa. LID involves a variety of involuntary movements or postures, 

such as chorea, ballism, dystonia and myoclonus, which emerge at various times in relation to 

levodopa dosing. Levodopa induced dyskinesia is classified as peak-dose dyskinesia, wearing-

off or off-period dyskinesia, and diphasic dyskinesia (Pandey & Srivanitchapoom, 2017) 

2.2.3.1 Mechanism of Motor fluctuations and Levodopa Induced Dyskinesia 

Although PD is characterized by the progressive degeneration and loss of nigrostriatal 

dopaminergic neurons, studies have shown that in the early stage of the disease, there are still 

sufficient neurons to maintain consistent striatal dopamine concentrations and continuous 

activation of the striatal dopamine receptors (Pfeiffer, 2005; Olanow et al., 2006). The 

remaining dopaminergic neurons take up exogenous levodopa and convert it to dopamine, 

which is then stored and released slowly into the synapse over time. These neurons are also 

able to re-uptake, recycle and control the release of dopamine to ensure constant dopamine 

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concentrations. Thus, buffering the effects of the fluctuating plasma levels of levodopa due to 

its short half-life. 

However, as neurodegeneration progresses, this conversion, storage, and release mechanism 

becomes compromised. Also, the buffering capacity greatly reduces (Hauser, 2009). The 

conversion of exogenous levodopa to dopamine then takes place mainly at the non-

dopaminergic sites (e.g., glial cells, serotonergic neurons etc.) which lack the capacity of 

storing dopamine (Melamed et al., 2000). Hence, fluctuations in plasma levodopa 

concentration may result in fluctuations in striatal dopamine concentration and pulsatile 

stimulation of dopamine receptors, leading to motor complications such as dyskinesia and 

motor fluctuations (Olanow et al., 2006). Ultimately, patients become largely reliant on a 

continual in-flow of levodopa into the brain to obtain a clinical response as dopamine levels in 

the synapse begin to reflect levels of levodopa in the peripheral circulation. 

Moreover, the pulsatile stimulation of dopamine receptors by levodopa-derived dopamine have 

been proven to narrow the therapeutic window of levodopa over time (Salat & Tolosa, 2013). 

Eventually, patients require higher levodopa doses for symptom relief. Higher levodopa doses 

lead to higher peaks (Cmax) of levodopa concentration and this, together with the 

dopaminergic degeneration in the CNS, is believed to result in motor complications. 

Overstimulation of dopamine receptors following levodopa administration have been shown to 

cause dyskinesia. The development of motor complications has also been associated with 

variable absorption of levodopa in the small intestine as a result of poor gastric emptying, 

competing dietary protein, slow intestinal transit times, among others. 

 

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Figure 2.8: Changes in Motor Response Associated with Chronic Levodopa Therapy 

(Source: Longo et al., 2011) 

 

Studies have demonstrated that, continuous administration of levodopa leads to a reduction in 

dyskinesia and motor fluctuations(Gershanik & Jenner, 2012; Olanow et al., 2006). Similarly, 

administration of short-acting dopamine agonists has been shown to induce more dyskinesia 

than administration of the same agonist in a more continuous fashion (Stocchi et al., 2002). 

Based on these findings, research has focused on attempting to provide more sustained 

dopamine concentrations in the CNS. 

 

2.2.4 Levodopa Drug Delivery Systems 

In order to improve its bioavailability, maintain a near-constant plasma concentration and 

minimize the unwanted motor complications of levodopa, several studies have focused on the 

development of improved drug delivery systems for levodopa (Ngwuluka et al., 2010). 

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First, immediate release drug delivery systems composed of levodopa in combination with 

peripheral dopa decarboxylase (DDC) inhibitor such as carbidopa or benserazide were 

formulated. These combinations, namely Sinemet® and Madopar® respectively, were shown to 

greatly reduce the extracerebral metabolism of levodopa (increasing the half-life from 50min 

to 1.5hrs) and side-effects such as nausea and vomiting but were ineffective in controlling 

dyskinesias and motor fluctuations associated with long-term use of levodopa. 

Catechol-O-methyl transferase (COMT) inhibitors such as entacapone and tolcapone were then 

added to levodopa/carbidopa in a single tablet to block the second metabolic pathway (O-

methylation).  Although the addition of a COMT inhibitor increased the plasma level of 

levodopa by 35% and the half-life from 1.5h to 2.4h, dopaminergic side effects such as 

dyskinesias increased, thereby necessitating the levodopa dose to be reduced. 

Levodopa oral disintegrating tablets (ODTs) were also introduced to make up for the reduced 

duration of clinical response that occurred with the use of immediate release drug formulations. 

These tablets enabled patients to take smaller and more frequent doses. Drug dosages were also 

tailored to the needs of individual patients. However, due to the frequency of dosing, most 

patients fail to comply, therefore, making it difficult to achieve constant delivery of the drug. 

Additionally, liquid formulations of levodopa were developed to facilitate rapid onset of action. 

These formulations were shown to give a rapid onset of action (within 5 min) and are therefore 

given to reduce the delay in the On' effect which has been observed with the use of controlled 

release (CR) formulations. However, their effects only last for a very short period (1-2hrs) and 

requires frequent administration (Ngwuluka et al., 2010). Non-compliance is therefore, a major 

challenge with the use of this formulation. 

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In order to reduce the interval between doses and to solve the "wearing off” problem 

encountered with levodopa, controlled release (CR) formulations were introduced. A typical 

example is Sinemet CR, which currently is the most commonly prescribed medication for PD. 

Pharmacokinetic studies have shown that steady state levodopa plasma levels do not fluctuate 

as much with Sinemet CR compared to the immediate release formulation, Sinemet. However, 

the bioavailability of Sinemet CR is about 30% less than Sinemet (Yeh et al., 1989). 

Additionally, Sinemet CR is absorbed slowly, and although the absorption occurs over an 

extended period, there is a late onset of drug action. After administration, it takes about 2-4hrs 

to reach peak plasma concentration and the peak concentrations may be lower than that 

obtained with immediate release (IR) formulations.  Hence, patients may have to take an IR 

formulation in the morning and a CR formulation or combination IR and CR during the day in 

order to produce a rapid onset of action (Gasser et al., 1998). Furthermore, CR formulations 

are often associated with a problem of variable bioavailability and consequently variable 

efficacy (Goole & Amighi, 2009). 

Dual release (DR) formulations were also introduced in order to overcome the delayed action 

observed with the use of CR formulations (Rubin, 2000). These drug delivery systems combine 

the advantages of a rapid onset of action as well as a sustained effect. However, when DR 

formulations were compared with CR formulations, the mean Dyskinesia Rating Scale severity 

score was similar for both formulations (2.8±2.5 vs. 2.7±3.1) implying that there may be 

variable bioavailability with DR formulations as well. Furthermore, gastro-retentive drug 

delivery systems have been developed. However, these formulations are not recommended 

because of the risk of these systems staying longer than desired in the gastric region of humans 

(Ngwuluka et al., 2015). 

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Intravenous infusion of levodopa has also been developed. However, studies revealed that 

levodopa is irritating to the veins and could not be administered continuously for more than 7-

10 days via the intravenous route (Shoulson et al., 1975; Hardie et al., 1984). Intraduodenal 

levodopa infusion has also been proven to be a successful therapeutic approach for PD (Kurlan 

et al., 1988). However, its use is greatly limited because of the frequent dislocation of the distal 

part of the tube from the duodenum into the stomach resulting in sudden failure of clinical 

response with recurring motor fluctuations (Nyholm et al., 2005).  

Clearly, most of these drug delivery systems are unable to provide constant and sustained 

delivery of levodopa over a prolonged period to ensure its optimal absorption and subsequent 

CNS bioavailability. 

 

2.3  BIOPOLYMERS AS DRUG DELIVERY SYSTEMS 

The oral route is by far the most preferred route of drug administration especially for the 

management of chronic diseases. However, factors such as extensive presystemic metabolism, 

erratic gastric emptying and limited absorption via specific segments of the gastrointestinal 

tract, among others, restrict the therapeutic potential of many drugs (Hua, 2020). In order to 

enhance the absorption, bioavailability, pharmacokinetic and biodistribution profile of drugs 

following oral administration, current research has explored new strategies. One such strategy 

is to incorporate drugs into polymer matrices to form polymer composites. 

In recent years, biopolymers such as chitosan, pectin, alginate, guar gum, gelatin, dextran, 

xanthan, and other polymers have gained significant attention not only in the pharmaceutical 

industry, but also in the food and biomedical sectors (Martau, Mihai, & Vodnar, 2019). 

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Biopolymers are polymers derived from natural sources. They are either entirely 

biosynthesized by living organisms or chemically synthesized from biological material (Liu, 

Lin, Astruc, & Gu, 2019; Martau et al., 2019). Generally, three types of polymers have been 

classified namely; polysaccharide, protein and lipid biopolymers. 

Polysaccharide biopolymers like chitosan and pectin are abundant in nature and readily 

available, making them relatively less excipients. Furthermore, because these polymers are 

non-toxic, biocompatible, biodegradable, and flexible, they have significant potential in drug 

delivery systems. 

2.3.1 Chitosan 

Chitosan (CS) is a family of linear polysaccharides prepared from the partial deacetylation of 

chitin, the principal component of the exoskeletons of crustaceans such as crabs and shrimps, 

fungus cells walls and insect cuticles, by alkaline hydrolysis. It is composed of randomly 

distributed β-(1→4)-linked D-glucosamine (deacetylated unit) and N-acetyl-D-glucosamine 

(acetylated unit) as shown in Figure 2.9 

 

Figure 2.9: Chemical Structure of Chitin and Chitosan 

 

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The degree of acetylation (DA) and molecular weight of chitosan depends largely on the natural 

source, the reaction parameters and the conditions used to isolate 

and deacetylate chitin (Quiñones, Peniche, & Peniche, 2018). Hence, commercially, CS is 

available in a range of molecular weights, degrees of deacetylation and different types of salts 

such as glutamate, hydrochloride and lactate (Syed et al., 2014). 

CS has free hydroxyl (–OH) and amino (–NH2) groups in its structure that allow for hydrogen 

bonding and  chemical modifications that enhances some of its properties for certain 

applications.  

Chitosan is a biocompatible, biodegradable, non-toxic and non-immunogenic material with 

wound healing capacity, hemostatic and antimicrobial activity. It easily forms films and can be 

processed into gels, fibres, microspheres, microparticles and nanostructures (Morris et al , 

2010). These exceptional biological, physical and chemical properties make CS an excellent 

polymer for use not only in pharmaceutics but also in cosmetics and food industry (Morris et 

al., 2010). Generally, CS is preferred to other cationic polymers such as polylysine, 

polyarginin, or polyethyleneimine because it is comparatively less toxic. 

 The primary amine group in chitosan accounts for its various properties such as cationic 

nature, muco-adhesion, permeation enhancement, controlled drug release, in situ gelation, 

antimicrobial effects, among others (Bernkop-Schnürch & Dünnhaupt, 2012).  

Mucoadhesion refers to the adhesion between two materials, at least one of which is a mucosal 

surface (Phanindra et al., 2013). The cationic polyelectrolyte nature of chitosan provides a 

strong electrostatic interaction with negatively charged mucosal surfaces. This makes it a 

perfect excipient able to improve the drug residence time in a specific mucous tissue, enhance 

absorption at the site and provide sustained drug release. The significance of this mucoadhesive 

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property of chitosan and chitosan nanoparticles has been demonstrated in earlier work by 

Fernandes et al., (2013),  Hejjaji et al., (2018), Silva et al., (2017) and Ways et al., (2018).  

Furthermore, chitosan has been shown to have permeation enhancing properties (Bernkop-

Schnürch & Dünnhaupt, 2012; Soliman et al 2014). Studies have shown that its positive 

charges interact with the cell membrane resulting in a structural reorganization of tight 

junction-associated proteins thereby allowing the paracellular transport of macromolecular 

drugs (Yeh et al., 2011). Drug-loaded chitosan nanoparticles have also been used successfully 

to deliver drugs to the brain to treat diseases such as Alzheimer’s disease, Parkinson’s disease, 

epilepsy, stroke, among others (Fan et al., 2018). Its mucoadhesive property creates an interface 

of electrostatic interaction with the negative charges of the glycocalyx and the phospholipids 

of the epithelial membrane in the BBB (Peptu et al., 2014). Permeation of such drugs is also 

enhanced by the opening of tight junctions whereas some of these drug-bound nanoparticles 

cross the BBB into the brain due to their nanometric particle size (Cortés et al., 2020) 

Despite the above-mentioned useful properties, chitosan tends to dissolve in the acidic 

environment of the stomach, compromising its mucoadhesive capacity and therefore, resulting 

in an uncontrolled release of the carried drug. Studies suggest that in order to overcome this 

challenge, the structure of chitosan needs to be modified or combinations with other excipients 

be made (Bernkop-Schnürch and Dünnhaupt, 2012; Luo and Wang, 2014).  One of the 

excipients that can be successfully combined with chitosan is pectin. 

2.3.2 Pectin 

Pectin is a non-toxic, biodegradable, biocompatible, anionic polysaccharide present in the 

primary cell wall of plants (Cheikh et al., 2019). Pectin extracts are mainly made up of linear 

chains of (1, 4)-α-D-galacturonic acid residues partially esterified with methyl groups. 

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Depending on the degree of esterification DE (that is, the substitution degree of D-galacturonic 

carboxyl groups by methoxyl groups (–OCH3), pectins can be classified as low esterified (also 

known as low methoxyl) pectin (LEP, DE < 50%) or high esterified (high methoxyl) pectin 

(HEP, DE > 50%) (Cheikh et al., 2019).  

 

 

Figure 2.10: Chemical Structure of Pectin (Source: Researchgate.com) 

 

Cocoa pod husk (CPH) pectin is extracted from pod husk waste after processing of cocoa beans. 

Previous studies shows that CPH pectin has the requisite physicochemical characteristics to be 

used as a multifunctional pharmaceutical excipient with remarkable properties (Adi-Dako et 

al., 2016). 

As an anionic polymer, pectin interacts with chitosan to form a polyelectrolyte complex (PEC). 

The intermolecular interaction between these polysaccharides of opposite charges has been 

applied in the design of drug delivery systems (García et al., 2015). Studies have shown that 

PECs have the ability of encapsulating drugs in the polymeric matrix at molecular level thereby 

enhancing the physicochemical and pharmacokinetic characteristics of drugs (Ngwuluka et al., 

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2015).  Furthermore, pectin resists the action of digestive enzymes present in the upper part of 

the gastrointestinal tract and, in contrast with chitosan, is able to withstand the low pH 

conditions (Cheikh et al., 2019). 

In the last years, the properties of chitosan-pectin based polyelectrolyte complexes have been 

extensively investigated and used as carriers for specific drug delivery systems (Cheikh et al., 

2019; Ghaffari et al., 2007; Maciel et al., 2015; Syed et al., 2014; Wang, 2017).  

 

2.3.4 Chitosan-Pectin Based PEC 

Polyelectrolyte complexes (PECs) are multifunctional formulations formed when solutions of 

two oppositely charged biopolymers (i.e., a polycation and a polyanion or their corresponding 

salts) are mixed together. Coulomb’s (electrostatic) interactions between charged 

microdomains of the two oppositely charged polyelectrolytes lead to the formation of 

polyelectrolyte complexes (PECs). Hydrogen bonds, hydrophobic interactions, van der Waals 

interactions, and dipole interactions also contribute to complexing (Ghaffari et al., 2007; 

Kulkarni et al., 2016; Quiñones et al., 2018). The resulting complexes (also known as polysalts) 

precipitate or separate from the solution, forming a complex-rich liquid phase. However, under 

certain conditions, the polyelectrolytes with weak ionic groups and significantly different 

molecular weights at non-stoichiometric mixing ratios generate water-soluble PECs on a 

molecular level (Kulkarni et al., 2016). 

Studies have proven that the formation of PEC leads to the formation of stable nanodispersions 

with dimensions in a colloidal size range (Mao et al. 2006, Sun et al. 2008). Formation of PECs 

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is simple and easy.  PECs are able to maintain the activity and stability of embedded drugs 

under normal physiological conditions (Tsai et al., 2014; Wang, 2017). 

PECs are classified as stoichiometric (S-PECs; PECs generated by polymers in an equimolar 

ratio) or non-stoichiometric (N-PECs) (N-PECs generated when one polymer is in excess 

compared to another) (De Robertis et al., 2015; Kulkarni et al., 2016). The structure and 

stability of PECs formed depends on a number of factors such as polyelectrolytes 

concentration, the mixing order, mixing ratio (Z), the degree of ionization the polyions, their 

charge densities and charge distribution on the polymer chains, among others. The interaction 

time, ionic strength, temperature as well as the pH of the medium have also been reported to 

greatly affect the nature of PECs formed (Quiñones et al., 2018). 

As oppositely charged polymers, chitosan and pectin interact to form polyelectrolyte complex 

(PEC). Studies have shown that these PECs have the ability of encapsulating drugs in the 

polymeric matrix at molecular level thereby enhancing the physicochemical  and 

pharmacokinetic characteristics of drugs (Lu et al., 2010; Ngwuluka et al., 2015). Chitosan-

pectin based polyelectrolyte complexes have been employed in the design of modified drug 

delivery systems as well as site-specific drug delivery systems.  In recent studies conducted by 

Cheikh et al., 2019 and Wang, 2017 chitosan-pectin based PECs were used to successfully 

encapsulate and sustain the release of aceclofenac and nisin respectively. 

 

 

 

  

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CHAPTER THREE 

METHODS USED 

3.1  Materials and Methods 

Levodopa powder (99.6%), carbidopa powder (99.8%) and chitosan (low molecular weight) 

were purchased from Sigma-Aldrich (USA). Pectin was extracted from cocoa pod husk. 

Microcrystalline cellulose was purchased from Sigma Aldrich (USA). Sinemet CR tablet 

(100/25mg) (Merck) was purchased from Medimart Pharmacy, Accra. All solvents used for 

chromatographic assay were of HPLC purity. All other reagents used were of analytical grade 

and purchased from approved suppliers. 

 

3.2  Study Design  

The study design employed was experimental. It involved the extraction of CPH pectin, 

formulation of chitosan-CPH pectin-based composite of levodopa/carbidopa, in vitro assays, 

in vivo (rat model) pharmacokinetic and biodistribution evaluation.  

3.3  Study Location 

The formulation and characterization of composite matrix of levodopa and carbidopa were 

done at the Pharmaceutics Research Laboratory of the School of Pharmacy, University of 

Ghana, Legon. The pharmacokinetic aspect of this research was done at the Animal 

Experimentation Unit of the School of Biomedical and Allied Health Sciences, University of 

Ghana, Korle-Bu. Content analysis and determination of drug levels (in plasma and brain 

University of Ghana http://ugspace.ug.edu.gh 



49 
 

tissue) were done at Department of Clinical Pathology, Noguchi Memorial Institute for Medical 

Research, Legon, Ghana. 

 

3.4  Collection and Extraction of Cocoa Pod Husk (CPH) Pectin  

Ripe cocoa pods were harvested from Theobroma cacao L. trees in the experimental plantation 

of Cocoa Research Institute of Ghana (CRIG), Tafo, Ghana. The pulp and seeds were then 

removed, and the fresh whole pod husks peeled to avoid pigmentation. Afterwards, the peeled 

husks were minced with a mechanical blender and prepared for extraction. The extraction of 

pectin from fresh CPHs was done according to a procedure previously described by Vriesmann 

et al, (2012) with minor modifications. Hot aqueous extraction of the fresh peeled minced 

husks (1.05 g/mL) was carried out at 50℃ in a water bath. The extract was precipitated with 

90% (v/v) ethanol and filtered twice with two-fold linen cl