KAUNAS UNIVERSITY OF MEDICINE Faculty of Pharmacy
UNIVERSITY OF MONTPELLIER 1 Faculty of Pharmacy
Toma KEŽUTYTĖ
BIOANALYTICAL METHOD VALIDATION FOR QUANTITATIVE DETERMINATION OF TWO
ANTIMALARIAL THIAZOLIUM COMPOUNDS AND ITS APPLICATION TO A PHARMACOKINETIC STUDY IN RAT
Master’s thesis
CONFIDENTIAL
Supervisors: Prof. Dr. Vitalis BRIEDIS
Prof. Dr. Francoise BRESSOLLE
Kaunas Montpellier
2007
TABLE OF CONTENTS Introduction .......................................................................................................................................... 4 Part 1 – Literature review ................................................................................................................... 5 I. The Problem of Malaria in the World................................................................................................. 5 II. Brief Presentation of the Life Cycle of Plasmodium ........................................................................ 7 2.1. Asexual phase of development ......................................................................................... 7 2.1.1. Exoerythrocytic cycle ............................................................................................... 7 2.1.2. Intraerythrocytic cycle .............................................................................................. 8 2.2. Sexual phase of development ........................................................................................... 8 III. Currently Available Antimalarial Drugs.......................................................................................... 9 3.1. Quinolines......................................................................................................................... 9 3.1.1. Chemical structures................................................................................................... 9 3.1.2. Effects on the stages of parasite’s life cycle and mode of action.............................. 9 3.1.3. Mechanism of resistance ........................................................................................... 10 3.2. Antifolates......................................................................................................................... 11 3.2.1. Chemical structures................................................................................................... 11 3.2.2. Effects on the stages of parasite’s life cycle and mode of action.............................. 11 3.2.3. Mechanism of resistance ........................................................................................... 11 3.3. Atovaquone....................................................................................................................... 12 3.3.1. Chemical structure .................................................................................................... 12 3.3.2. Effects on the stages of parasite’s life cycle and mode of action.............................. 12 3.3.3. Mechanism of resistance ........................................................................................... 12 3.4. Artemisinins...................................................................................................................... 12 3.4.1. Chemical structures................................................................................................... 13 3.4.2. Effects on the stages of parasite’s life cycle and mode of action.............................. 13 3.4.3. Mechanism of resistance ........................................................................................... 14 3.5. Antibiotics......................................................................................................................... 14 3.5.1. Chemical structures................................................................................................... 14 3.5.2. Effects on the stages of parasite’s life cycle and mode of action.............................. 14 IV. Combinations of Antimalarial Drugs............................................................................................... 15 4.1. Artemisinin-based combination therapies (ACTs) ........................................................... 15 4.2. Non-artemisinin based combination therapies (non-ACTs) ............................................. 16 4.3. Synergistically acting combinations of antimalarial drugs............................................... 16 V. New Targets in Plasmodium for the Development of New Antimalarial Drugs ............................. 17 VI. Potential Inhibitors of Phospholipid Metabolism in Plamodium..................................................... 22 6.1. De novo synthesis of phosphatidylcholine in Plasmodium .............................................. 22 6.2. Potential inhibitors of PL metabolism .............................................................................. 23 6.3. Quaternary ammonium compounds exhibit dual mode of action against Plasmodium ... 24 6.4. Structure-activity relationship of quaternary ammonium compounds ............................. 25 6.5. Monothiazolium salts T1 and T2 ...................................................................................... 25 Part 2 – Experimental Part ................................................................................................................. 26 I. Different Steps in Bioanalytical Method Validation .......................................................................... 26 1.1. Different types of bioanalytical method validation .......................................................... 26 1.2. Methodology..................................................................................................................... 27 1.2.1. Relationship between concentration and response.................................................... 27 1.2.2. Specificity / selectivity.............................................................................................. 28 1.2.3. Accuracy and precision............................................................................................. 28 1.2.4. Lower limit of quantitation (LLOQ) ......................................................................... 29 1.2.5. Extraction recovery ................................................................................................... 29 1.2.6. Stability ..................................................................................................................... 30 1.2.7. Robustness / ruggedness ........................................................................................... 31
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1.2.8. Matrix effects ............................................................................................................ 31 1.3. Application of validated bioanalytical method to routine drug analysis .......................... 32 II. Assay for Simultaneous Determination of Two Antimalarial Monothiazolium Compounds in Biological Matrices by Liquid Chromatography – Electrospray Mass Spectrometry ........................... 33 2.1. Materials and methods ...................................................................................................... 33 2.1.1. Chemicals and reagents............................................................................................. 33 2.1.2. Equipment ................................................................................................................. 34 2.1.3. Liquid chromatography-mass spectrometry conditions ............................................ 36 2.1.4. Working standards .................................................................................................... 37 2.1.5. Preparation of calibration standards and quality control (QC) samples ................... 38 2.1.6. Sample preparation procedure................................................................................... 38 2.1.7. Data analysis ............................................................................................................. 39 2.1.8. Validation procedure................................................................................................. 39 2.1.9. Stability study ........................................................................................................... 40 2.1.10. Ion suppression / enhancement study...................................................................... 40 2.1.11. Pharmacokinetic study of T2 in rat ......................................................................... 40 2.2. Results of full validation in human plasma and whole blood........................................... 42 2.2.1. Drug / response relationship ..................................................................................... 42 2.2.2. Retention times and specificity ................................................................................. 44 2.2.3. Precision, accuracy, extraction efficiency and LLOQ .............................................. 47 2.2.4. Stability ..................................................................................................................... 49 2.2.5 Ion suppression / enhancement study......................................................................... 51 2.3. Results of partial validation in rat plasma and RBCs ....................................................... 51 2.3.1. Drug / response relationship ..................................................................................... 51 2.3.2. Retention times and specificity ................................................................................. 52 2.3.3. Precision, accuracy, extraction efficiency and LLOQ .............................................. 54 2.3.4. Stability ..................................................................................................................... 54 2.3.5 Ion suppression / enhancement study......................................................................... 54
2.4. Results of a pharmacokinetic study carried out after intravenous administration of T2 in rat ........................................................................................................................................... 54
Conclusion ............................................................................................................................................ 56 References ............................................................................................................................................. 57 Acknowledgements .............................................................................................................................. 63
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INTRODUCTION
Malaria remains one of the largest global health-care problems of the 21st century. Currently it
affects more than 40% of the world's population in tropical areas throughout sub-Saharan Africa,
South Africa, Southeast Asia, the Pacific Islands, India, and Central and South America.
The disaster of malaria is mainly due to the emergence of multi-drug resistant Plasmodium
strains. The current limited antimalarial drug repertoire, resistance of mosquitoes to various
insecticides and absence of efficient malaria vaccine indicate that new antimalarial compounds are
desperately needed.
In the first part of my work, the problem of malaria in the world, the complex life cycle of
Plasmodium spp., currently available antimalarial drugs (quinines, antifolates, atovaquone,
artemisinins and antibiotics) and their combinations are presented. The main attention is focused on
the new targets of Plasmodium and on the development of new potential antimalarial drugs. Among
them, mono- and bis-quaternary ammonium salts, mimicking the structure of choline and
inhibiting de novo phosphatidylcholine biosynthesis in the parasite have been developped. In
the Clinical Pharmacokinetic Laboratory (Faculty of Pharmacy, University Montpellier 1,
Montpellier, France), these compounds are being under investigation. I had an honour to contribute
to this research. My work has been focused on the development of monothiazolium compounds.
The goal of this work is to validate an analytical method to simultaneously quantify two
monothiazolium compounds (T1+ and T2+) in biological matrices and then to carry out
pharmacokinetic study in rat. In the experimental part of this work, the methodology of
bioanalytical method validation is documented. Then, the materials, methods and results of a full
validation in human plasma and whole blood and of a partial validation in rat plasma and red blood
cells by liquid chromatography-electrospray mass spectrometry (LC/ESI-MS) are presented. The
application of this validated bioanalytical method to a pharmacokinetic study carried out in rat is
highlighted.
The main tasks of this work are as follows:
• To show the problem of emergence of multi-drug resistant Plasmodium strains;
• To demonstrate potential Plasmodium targets for the development of new antimalarials;
• To present quaternary ammonium compounds as highly potential novel antimalarials;
• To validate bioanalytical methods in human plasma and whole blood as well as in rat
plasma and red blood cells for the simultaneous quantitation of monothiazolium compounds using
LC/ESI-MS;
• To use these validated bioanalytical methods to quantify the T2+ compound in biological
samples drawn during a pharmacokinetic study carried out in rat.
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PART 1 – LITERATURE REVIEW
I. THE PROBLEM OF MALARIA IN THE WORLD
Malaria is the world’s most important parasitic infection and one of the major causes of
morbidity and mortality in the third-world countries. There is an estimation of 500 million
infections (90% of them occurring in Africa) and 2.7 million deaths (75% of these deaths arising to
African children) from malaria each year – a death from malaria every 30 seconds [28, 17, 22, 26].
Malaria is a haematoprotozoan parasitic infection, caused by unicellular, apicomplexan
parasites of the genus Plasmodium and transmitted to human by female Anopheles mosquito. Four
species of Plasmodia are infectious to human and cause distinct disease patterns: Plasmodium
falciparum (malaria tropica), P.ovale (malaria quartana), P.vivax (malaria tertiana) and P.malariae
(malaria tertiana).
P.ovale and P.malariae are not lethal and are rare, most frequently found in parts of Africa
and Papua New Guinea. P.vivax and P.falciparum are the two most widespread species in the
world; P.falciparum is endemic in Africa, South and East Asia, South America, the Caribbean and
the Middle East, and is uniquely responsible for mortality and severe disease [28].
The common symptoms of uncomplicated malaria are headache, fatigue, abdominal
discomfort, joint and muscle aches, lassitude followed by fever, chills, perspiration, anorexia,
vomiting and worsening malaise. If not treated within few hours, uncomplicated malaria progresses
to coma (cerebral malaria), metabolic acidosis, severe anaemia, hypoglycaemia, acute renal failure
or acute pulmonary oedema. These are the common characteristics of severe disease, which is
almost always fatal, thus must be treated quickly [106].
The nature of the clinical disease depends on the pattern and intensity of the malaria
transmission in the area of residence. In areas with high malaria transmission rates (sub-Saharan
Africa, parts of Oceania) partial immunity is acquired early in childhood, therefore adolescents and
adults rarely suffer clinical disease and over 75% of deaths occur to children of less than 5 years
old. Reduced immunity and severe anaemia for pregnant women, exposed to malaria infection,
frequently result in low birthweight followed by roughly 25% of all neonatal mortality [112]. In
areas of unstable malaria (south and east of Asia, Latin America), where fluctuation of inoculation
rates over seasons and years retards the acquisition of immunity, people of all ages suffer from
clinical malaria [31, 106].
Malaria continues to affect public health, economic growth and livelihood in malaria endemic
areas of the world. Political instability, chronic regional economic difficulty, environmental impact,
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mosquito resistance to insecticides, Plasmodium resistance to established antimalarial drugs and
insufficient investment in the discovery of new drugs [112] have shattered the hope for rapid
malaria eradication and given rise to a very serious situation.
The increasing resistance of malaria parasites to the currently available antimalarial drugs,
absence of efficient malaria vaccine stress the importance of developing novel drugs and indicates
that drug development efforts should be geared towards obtaining compounds structurally unrelated
to existing antimalarial agents and with new independent mechanisms of action.
The completed genome sequence (in 2002) of P.falciparum
(http://www.plasmodb.org/plasmo/home.jsp) and the application of methods of modern drug design
promise to bring significant development in the fight against this disease.
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II. BRIEF PRESENTATION OF THE LIFE CYCLE OF PLASMODIUM
Plasmodium has a complex life cycle, involving both vertebrate and invertebrate hosts (Figure
1.1). The development of malaria parasites includes an asexual cycle in human host and a sexual
cycle in Anopheles mosquito.
Figure 1.1: The life cycle of malaria parasites in the human host and Anopheles
mosquito vector [33].
2.1. Asexual phase of development
2.1.1. Exoerythrocytic cycle:
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During a blood meal by female Anopheles mosquito, a few dozen of malaria sporozoites are
injected to human host subcutaneous tissues. Sporozoites enter the nearby blood vessel and reach
the liver. Once in the liver, parasite undergoes asymptomatic multiplication over a period of several
weeks. P.vivax and P.ovale can transform to hypnozoites (latent phase in the hepatocytes) that may
emerge years later. Inside the hepatocyte the sporozoite is converted to trophozoite, which
subsequently divides into several schizonts. The hepatic schizonts burst releasing thousands of
pathogenic merozoites into the bloodstream. This initiates intraerythrocytic phase, that gives rise to
malaria symptoms, morbidity and mortality [28, 11, 72].
2.1.2. Intraerythrocytic cycle:
Pathogenic merozoites gain entry into erythrocytes by a process that leaves the intracellular
parasite enclosed within parasitophorous vacuolar membrane (PVM). The parasite matures in the
erythrocyte through ring (0-24 h post-invasion), trophozoite (24-36 h post-invasion) and schizont
(36-48 h post-invasion) stages. At the end of 48 hours (72 hours in the case of P.malariae), the
schizont bursts and 8-32 merozoites are released, allowing the intraerythrocytic cycle to begin
again. A small percentage of the merozoites differentiate into sexual forms termed male and female
gametocytes. These stages are responsible for transmission through the mosquito [56].
2.2. Sexual phase of development
Gametocytes undergo sexual reproduction in the mosquito, when they are ingested through a
mosquito blood meal (3µl) that must contain both female and male gametocytes. Gamete fusion
(creating a zygote) and thus meiosis takes place in the mosquito’s mid gut. This brief diploid stage
in an otherwise haploid life cycle allows for sexual recombination of genetic material, including the
chromosomal genes responsible for most drug resistance. Within the mosquito mid gut the zygote
matures into an oocyst, which in turn releases sporozoites that then migrate to the mosquito salivary
glands, completing the life cycle [42].
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III. CURRENTLY AVAILABLE ANTIMALARIAL DRUGS
In this chapter the most extensively used antimalarial drugs (quinolines, antifolate drugs,
atovaquone, artemisinins, and antibiotics) are discussed, emphasizing their chemical structures,
mechanisms of action and resistance development.
3.1. Quinolines
This family of drugs includes (i) 4-amino quinolines: chloroquine (CQ) and amodiaquine
(Mannich base 4), (ii) aryl aminoalcohols: quinine, mefloquine, halofantrine and lumefantrine, and
(iii) 8-amino quinolines: primaquine.
3.1.1. Chemical structures:
Chloroquine Amodiaquine Quinine Mefloquine
Halofantrine Lumefantrine Primaquine
3.1.2. Effects on the stages of parasite’s life cycle and mode of action:
Quinolines are blood schizontocidal antimalarials [26], but chloroquine also acts against
young gametocytes. Primaquine is effective against intrahepatic stages of malaria parasites [106],
therefore it eradicates the liver hypnozoites of P.ovale and P.vivax [112]. Moreover, primaquine is
the only antimalarial drug known to act on mature infective gametocyte [28, 106].
The basic nature of quinolines allows them to be concentrated in the acidic food vacuole in
their membrane-impermeable protonated form [108].
Chloroquine and other quinoline derivatives act by joining with undimerized
ferriprotoporphyrin (FP) IX, which is released during the haemoglobin degradation process in the
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food vacuole [36; 37]. Thereby, chloroquine antagonises the polymerisation of FP IX into crystal
malaria pigment hemozoin [112, 35, 100]. This leads to intra-Plasmodium accumulation of highly
toxic chloroquine–FP IX complexes that are incorporated in the growing polymer hemozoin
resulting in the termination of chain extension [26]. Moreover, there are some evidences that
chloroquine inhibits glutathione that is responsible for the degradation of free FP IX [75].
There are available evidences that mefloquine and quinine inhibit the uptake of haemoglobin
from the host cell [108].
Primaquine’s mechanism of action is unknown [28], but treatment with primaquine causes
swelling and thickening of the mitochondria of intrahepatic parasites, suggesting that this drug
interferes with mitochondrial function [37].
3.1.3. Mechanism of resistance:
Resistance to chloroquine:
1st hypothesis: reduced concentration of chloroquine in the parasite vacuole can be attributed
to (i) an efflux of the drug from the vacuole due to an active verapamil-sensitive efflux pump (P-
glycoprotein 1 encoded by pfmdr1 gene) that extrudes chloroquine from the food vacuole (Figure
1.2, A) and/or (ii) a change in the structure of the transporter, importing the drug into the food
vacuole, due to mutations of the pfcrt gene encoding for this transporter (PfCRT) (Figure 1.2, B)
[63, 28, 115, 46].
A B C
Figure 1.2: Alternative models of the chloroquine (CQ) resistance [56].
2nd hypothesis: reduced passive diffusion of chloroquine into the vacuole due to elevation of
the vacuolar pH: this arises from a weakened vacuolar H+ pump, increased H+ leakage or perhaps
from an impaired Cl- conductance (Figure 1.2, C) [86, 56].
Resistance to mefloquine and other aryl-amino-alcohols results from amplifications in
Pfmdr1, which encodes an energy demanding P-glycoprotein 1 pump [106, 28, 37, 115].
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Chloroquine resistance appeares to be associated with mefloquine hypersensitivity and vice versa
[115].
3.2. Antifolates
The most commonly used antifolates are pyrimethamine (2,4-diaminopyrimidine), proguanil,
chlorproguanil, and the sulfa-drugs: sulfadoxine and dapsone.
3.2.1. Chemical structures:
R Pyrimethamine Proguanil (R=H) Sulfadoxine Dapsone Chlorproguanil (R=Cl)
3.2.2. Effects on the stages of parasite’s life cycle and mode of action:
Antifolates are active against schizont stages within erythrocytes and hepatocytes [26].
Proguanil also has sporontocidal activity, rendering the gametocytes non-infective to the mosquito
[106].
Antifolates are antimetabolites, inhibiting the folate pathway and subsequently pyrimidine
synthesis. Sulfadoxine and dapsone, analogues of p-aminobenzoic acid, inhibit dihydropteroate
synthase, DHPS (a bifunctional enzyme in Plasmodia coupled with 2-amino-4-hydroxy-6-
hydroxymethyl-dihydropteridine pyrophosphokinase PPPK). Pyrimethamine is a selective,
competitive inhibitor of dihydrofolate redutase (DHFR) domain in bifunctional PfDHFR-TS
(thymidylate synthetase), a key enzyme in the redox cycle for production of tetrahydrofolate [14,
82]. Proguanil and chlorproguanil are metabolised by human CYP2C19 and CYP3A4 to the active
metabolites cycloguanil and chlorcycloguanil, respectively, which further inhibit parasite DHFR
[108, 112, 68].
3.2.3. Mechanism of resistance:
Slow elimination (e.g. t1/2 of pyrimethamine is roughly 100 hours [112]) and monotherapy of
antifolates have facilitated the development of resistance [113, 26]. Point mutations (codons: 51, 59,
108, 164) in the Pfdhfr gene and point mutations (codons: 436, 437, 540, 581, 613) in the Pfdhps
gene give moderate to high level of resistance to antifolates [63, 42].
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3.3. Atovaquone
Atovaquone is used orally in fixed, synergistically acting combination with proguanil
(Malarone®) to treat and prevent (especially among travellers) chloroquine-resistant uncomplicated
falciparum malaria, but high cost of atovaquone limits the usage of Malarone® in Africa.
3.3.1. Chemical structure:
Atovaquone (hydroxynaphthoquinone)
3.3.2. Effects on the stages of parasite’s life cycle and mode of action:
Atovaquone is a blood schizontocidal antimalarial drug also inhibiting pre-erythrocytic
development of Plasmodium species in the liver and oocyst development in the mosquito [106].
Atovaquone mimics the natural substrate ubiquinone (CoQ) and selectively inhibitis electron
transport in plasmodial mitochondria respirotory chain at the cytochrome bc1 oxidoreductase
(complex III) [28]. This results in the collapse of mitochondrial membrane potential [63, 93] and
inhibition of dihydroorotate dehydrogenase (DHOD), which is required in the biosynthesis of
pyrimidines [8].
In the combination with atovaquone, proguanil rather than its metabolite (cycloguanil) acts as
a biguanide and enhances the effect of atovaquone on the collapse of mitochondrial membrane
potential [98].
3.3.3. Mechanism of resistance:
In vitro and in vivo resistance of P.falciparum to atovaquone or atovaquone-proguanil has
been associated to two point mutations in the parasite cytochrome b gene (Tyr268Ser and
Tyr268Asn) [44].
3.4. Artemisinins
Natural artemisinin (quinghaosu) was first isolated in 1971 in China. It is a sesquiterpene
lactone, extracted from the dry leaves of Artemisia annua - the sweet wormwood tree [114, 49]. In
addition to artemisinin, the semisynthetic artemisinin derivatives (modifications made at C10
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position) – dihydroartemisinin, artemether, arteether (artemotil) and artesunate are used for the
treatment of malaria [108, 114].
The artemisinins are remarkable for their (i) high potency (they kill all human Plasmodium
species and are effective against multidrug-resistant P.falciparum strains), (ii) high therapeutic
index and (iii) rapid reduction in gametocyte carriage, and possess such features as (i) absence of
clinically important resistance, (ii) relative safety (few side effects in extensive clinical trials) and
(iii) good tolerability [112, 11, 116, 66].
3.4.1. Chemical structures:
Artemisinin Dihydroartemisinin Artemether Arteether Artesunate
3.4.2. Effects on the stages of parasite’s life cycle and mode of action:
Artemisinins have a broad spectrum of rapid activity against all parasite phases within
erythrocytes, in particular younger ring forms [26]. Furthermore, artemisinins are the most potent
gametocytocidal drugs destroying immature gametocytes [106].
Artemisinin derivatives are metabolised to the main bioactive compound, dihydroartemisinin
[108, 112, 114]. Artemisinins contain an endoperoxide trioxane moiety that undergoes (i) reductive
scission: Fe2+ catalyzed (by ferrous haem or exogenous free iron) cleavage into O-centred and
subsequently C-centred free radicals and (ii) peroxide ring-opening by protonation (H+) or complex
formation with Fe2+, resulting in an open hydroperoxide or metal peroxide. Reductive scission leads
to alkylation of plasmodial macromolecules such as Hb-derived haem or parasite proteins (Figure
1.3) and free-radical damage of P.falciparum. Ring-opening of peroxide bond results in
hydroxylation and oxidation of biomolecules [83, 41].
Figure 1.3: Hypothetical mechanism for the radical alkylation of haem by artemisinin
[108].
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Recently it has been found that artemisinins accumulate in the cytosol of the parasite and
selectively, irreversibly inhibit an essential SERCA (sarco/endoplasmic reticulum Ca2+-ATPase)
orthologue of P.falciparum (PfATPase6) [106, 78, 114, 28].
3.4.3. Mechanism of resistance:
Although there has been no evidence for clinically relevant in vivo artemisinin resistance,
recently described emerging in vitro resistance to artemisinins in certain areas (French Guiana)
correlates with mutations in the SERCA-like sequence PfATP6 [115].
3.5. Antibiotics
The most commonly used are (i) tetracyclines: tetracycline, doxycycline and (ii)
lincosamides: clindamycin.
3.5.1. Chemical structures:
Tetracycline Doxycycline Clindamycin
3.5.2. Effects on the stages of parasite’s life cycle and mode of action:
Tetracycline and doxycycline are active against the asexual stages of all Plasmodium species
as well as against primary intrahepatic stages of P.falciparum. Clindamycin is a blood
schizontocide.
Antibiotics act through inhibition of protein synthesis in the parasite mitochondrion
(tetracyclines) and inside the apicoplast (tetracyclines, lincosamides). Inhibition of self-replication
of the apicoplast leads to the death of the parasite in the second replication cycle (‘delayed death’
phenomenon) [108, 89]. Thus, the action of antibiotics is slow and they are mainly combined with
quinine or other fast acting antimalarials [26, 64].
Tetracycline also depresses the activity of dihydroorototate dehydrogenase of the pyrimidine
pathway in P.falciparum [85].
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IV. COMBINATIONS OF ANTIMALARIAL DRUGS
As the resistance has been documented for Plasmodium falciparum (observed resistance to
amodiaquine, chloroquine, mefloquine, quinine, and sulfadoxine-pyrimethamine), Plasmodium
vivax (documented resistance to sulfadoxine-pyrimethamine and chloroquine) and, recently,
Plasmodium malariae (observed resistance to chloroquine), new approaches for the treatment of
malaria have been suggested [106]. The use of drug combinations is the current most important
strategy to fight developing resistance of Plasmodium to monotherapies and to improve the efficacy
of malaria treatment.
Artemisinin derivatives are the only antimalarial drugs to which clinically significant
resistance has not yet developed [11], therefore artemisinin-based combination therapy (ACT) has
been strongly suggested as the first-line treatment strategy of uncomplicated malaria to both
children and adults [106, 112, 114].
In this chapter different combinations of antimalarial drugs, used to treat uncomplicated
falciparum malaria are highlighted.
4.1. Artemisinin-based combination therapies (ACTs)
ACT comprises two or more blood schizontocidal antimalarial drugs that have different
mechanisms of action and therefore independent targets in Plasmodium [106].
Combinations with artemisinin derivatives have a strong impact on (i) rapid reduction of the
parasite biomass (by roughly 10000-fold per asexual cycle), that makes ACTs highly effective and
delays the possibility of the remaining parasite population to develop mutations to the second
partner drug [112, 111, 114], (ii) reduction of transmission of both drug-sensitive and drug-resistant
parasites as artemisinin derivatives have a gametocytocidal action [28].
ACTs present several drawbacks: (i) ACTs are not recommended for treatment of malaria
during the first three months of pregnancy because of embryolethality and dysmorphogenesis
observed in pregnant animals after artemisinin administration [67]; (ii) the use of ACT is
constrained due to high cost and limited availability in many regions of Africa.
Currently recommended ACTs are as follows [106]:
• Artemether-lumefantrine (Riamet®/Coartem®): the only fixed combination having the
advantage that one drug cannot be taken without the other [7]. It is not the case for other
combinations given below:
• Artesunate + amodiaquine (in areas where the cure rate of amodiaquine monotherapy is
greater than 80%);
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• Artesunate + mefloquine;
• Artesunate + sulfadoxine-pyrimethamine (in areas where the cure rate of sulfadoxine-
pyrimethamine is greater than 80%).
4.2. Non-artemisinin based combination therapies (non-ACTs)
Non-ACTs include amodiaquine + sulfadoxine-pyrimethamine (AQ+SP) and chloroquine +
sulfadoxine-pyrimethamine (CQ+SP). CQ+SP is no longer recommended for malaria treatment due
to high prevalence of CQ resistance. AQ+SP is an interim option in some Africa areas (especially
West Africa) that are unable to immediately use ACTs and where the efficacy of both compounds
remains high [69, 106, 50].
4.3. Synergistically acting combinations of antimalarial drugs
These combinations mainly include synergistic antifolate drug combinations, such as (i)
pyrimethamine-sulfadoxine (Fansidar®), (ii) chlorproguanil-dapsone (LapDap®) and (iii)
proguanil-atovaquone (Malarone®).
The parasite has already developed resistance to pyrimethamine-sulfadoxine. Both in vitro
and in vivo studies indicate that, despite the identical mechanism of action, chlorproguanil-dapsone
remains active against the Pfdhfr and Pfdhps genotypes in Africa that cause pyrimethamine-
sulfadoxine failure [42].
To further counteract the development and spreading of resistance, a fixed triple combination
of chlorproguanil-dapsone-artesunate is now being in phase III of clinical development [26, 17,
112].
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V. NEW TARGETS IN PLASMODIUM FOR THE DEVELOPMENT OF
NEW ANTIMALARIAL DRUGS
Due to emergence and spread of multidrug-resistant malaria parasites and unsuccessful efforts
to produce an effective vaccine, there is an urgent need for the identification and validation of new
drug targets in Plasmodium and for the development of novel antimalarial drugs.
The re-design of existing antimalarial drugs might result in cross-resistance within a short
period of time, thus effective and safe antimalarials with new mechanisms of action against new
targets are desperately needed [76, 84].
Metabolic pathways in Plasmodium, in particular those that do not occur or that are quite
different in human host, specific proteins that are unique and critical for cellular growth and
survival of the parasite provide important novel antimalarial drug targets [43, 26]. Figure 1.4
represents Plasmodium organelles and metabolic pathways as potential targets for antimalarial
compounds in development.
Figure 1.4: Potential drug targets in Plasmodium [14].
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Ideally novel antimalarial drug should have: (i) high efficacy against multi-drug resistant
Plasmodium strains, (ii) low toxicity especially in children and pregnant women, (iii) low risk of
emergence of resistance. Curative regimens should be short: 1-3 days in length. In addition, new
antimalarials should be dosed orally and be effective with single-daily dosing. Furthermore, they
should be very inexpensive and affordable in the developing world [17, 93, 65].
The parasite’s miscellaneous biology at each stage and the ability to select drug-resistant
strains present a great challenge for new antimalarial drug development [28]. Therefore the
knowledge about parasite-specific organelles, metabolic pathways and membrane transport
mechanisms, the detailed structural and functional analysis of parasite enzymes, and their
comparison with their isofunctional counterparts in the host are indispensable features for rational
antimalarial drug design [13].
Brief description of new targets and lead inhibitors of specific metabolic pathways in the
parasite is provided in Table 1.1.
18
Table 1.1: New targets in Plasmodium Organelles
in Plasmodium
Pathway Potential targets Lead inhibitors in development Details
β-ketoacyl-acyl-carrier protein synthase (FabH)
Thiolactomycin
Thiolactomycin is a fungal secondary metabolite, selectively inhibiting FabH [14].
Type II fatty acid biosynthesis (FAS-II) (type I fatty acid synthase (FAS-I) exists in human)
Trans-2-enoyl-acyl-carrier protein reductase (FabI)
Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol]
Triclosan is effective in vitro against CQ-sensitive and CQ-resistant strains, it invokes rapid death in parasites, but it has low bioavailability and share mechanisms of drug resistance with mefloquine [89, 77, 14].
Protein prenylation
Farnesyl transferase Peptidomimetics, biphenyl derivative FTI-2153, imidazole derivative FTI-2217, benzophenone based compounds (Schl-4116)
Farnesyl transferase is a heterodimeric zinc protein that catalyses the transfer of a farnesyl residue from farnesyl pyrophosphate to a cysteine side chain near the carboxy terminus of a number of G-proteins [39, 110, 55].
Isoprenoid synthesis via non-mevalonate pathway (mevalonate pathway is present in human)
1-deoxy-D-xylulose 5-phosphate (DOXP) reductoisomerase
Fosmidomycin (3-formylhydroxyamino-propylphosphonic acid mono-sodium salt), FR-900098 (N-acetyl homologue of fosmidomycin)
Fosmidomycin is a natural antibiotic isolated from Streptomyces lavendulae and currently being in a clinical development for the treatment of uncomplicated malaria. Advantages: low toxicity, activity against multiresistant strains. Limitations: short plasma half-life (2,5 h), moderate bioavailability, high recrudescence rate in monotherapy (evaluated synergistic combination with clindamycin). FR900098 is twice as effective as fosmidomycin [43, 107, 76, 65, 109].
Api
copl
ast
(chl
orop
last
-like
org
alle
with
a c
ircu
lar D
NA
of 3
5 kb
) ne
Shikimate pathway (absent in human)
Chorismate synthase; 5-enolpyruvyl shikimate 3-phosphate (EPSP) synthase
Glyphosate derivatives The shikimate pathway provides p-amino benzoic acid precursor (chorismate) for folate, ubiquinone, tryptophan, phenylalanine and tyrosine biosynthesis. Glyphosate is a well characterised herbicide that inhibits EPSP synthase [84, 38, 92].
Mio
-t
nd
cho
rion Electron
transport and de novo pyrimidine synthesis
Dihydroorotate dehydrogenase (DHODase); Ubiquinone (CoQ8)
2-amino-3-chloro-1,4-naphthoquinone, 2-nitro-3-methyl-benzamide, 2-phenyl quinoline-4-carboxylic acid derivatives, pyridones
Malarial DHODase active site and CoQ homolog (CoQ8) are different from the host. DHODase uses CoQ8 as an electron acceptor and catalyzes the reaction from dihydroorotate to orotate in de novo pyrimidine synthesis [10, 47, 20, 9, 53]. Pyridones show no cross-resistance with atovaquone [17].
19
Table 1.1 (continued): New targets in Plasmodium
Organelles in
Plasmodium Pathway Potential targets Lead inhibitors in development Details
Aspartic proteases (plasmepsins I and II)
Allophenylnorstatine (KNI-727), diphenylurea derivatives (WR268961), Ro 42-1118
Haemoglobin (Hb) hydrolysis
Cysteine proteases (falcipain 2, 2’ and 3)
Peptidyl fluoromethyl ketones, peptidyl vinyl sulfones, chalcones, phenothiazines, leupeptin
Undegraded Hb blocks parasite development. Peptidic inhibitors of cysteine proteases have some limitations: (i) susceptibility to hydrolysis by host proteases, (ii) low selectivity, (iii) irreversible mode of action. Synergistic effects are observed in vitro and in vivo when aspartic and cysteine protease inhibitors are combined [39, 108, 97].
Haem polymerization
Ferriprotoporphyrin IX (FP)
Triarylmethanol Ro 06-9075, benzophenone Ro 22-8014, N-desbutyl derivative of halofantrine, dihydroacridinedione WR243251; tafenoquine, isoquine, pyronaridine, diamidines (DB 289)
These compounds bound to FP IX and inhibit the formation of nontoxic hemozoin. Cardiotoxicity of halofantrine is eliminated in its N-desbutyl derivative. Pyronaridine shows synergistic effect in combination with artesunate. Tafenoquine also eliminated hypnozoites [108]. Hepatotoxicity of amodiaquine is eliminated in its analogue isoquine [17].
Food
vac
uole
Free radical generation, oxidative stress
Unknown
Artemisinin derivatives and peroxides: 1,2,4,5-tetraoxanes, oxazines, trioxaquines, Yingzahaosu A, artelinic acid
Carbon-centred radical formation is critical for the activity of these compounds. Artelinic acid is more stable than artesunate and is highly soluble in water; Yingzahaosu A is isolated from traditional Chinese medicinal plant Artabotrys uncinatus [108].
Membrane transport
Hexose transporter HT1, nucleoside transporter NT1, P-type Ca2+-ATPases, V-type H+-ATPases, H+-pumping pyrophosphatases
O-3 hexose derivatives inhibit PfHT1; cyclopiazonic acid inhibits endoplasmic reticulum P-type ATPases; Bafilomycin A1 inhibits V-type ATPases; aminomethylenediphosphonate inhibits H+-pumping pyrophosphatases
Inhibition of PfHT1 leads to ATP level decline and the loss of intracellular pH control in the parasite. PfNT1 transports purines from the erythrocyte to the parasite. Inhibition of PfNT1 or exploitation of PfNT1 ability to transport cytotoxic 3’-deoxynucleoside analogues (that are poor substrates for mammalian transporters) offer great promise in killing the parasite. P-type ATPases are responsible for the maintenance of Ca2+ and V-type ATPases - of H+ homeostasis [59, 18, 57, 19, 2, 32, 94].
Para
site
mem
bran
e
Phospholipid synthesis
Choline transporter Mono- and bisquaternary ammonium compounds
A detailed description of mono- and bisquaternary compounds participating in phospholipid metabolism is provided in the next chapter.
Cell cycle control
Cyclin-dependent protein kinases (CDKs): P.falciparum protein kinase (PfPK) 5, PfPK6, PfMRK and Pfnek-1
Purvalanol, hymenialdisine and indirubine-3’-monoxime inhibit PfPK5; phenylquinolinones, oxindoles, chalcones, tryptanthrins, thiophene sulfonamides inhibit PfMRK; Xestoquinone inhibits Pfnek-1
CDKs function as serine/threonine kinases and have crucial role in parasite growth and differentiation. Siginificant differences exist between Plasmodium and human CDKs [39, 38, 14]. Xestoquinone is isolated from Pacific marine sponges of the genus Xestospongia [62].
20
Table 1.1 (continued): New targets in Plasmodium
Organelles in
Plasmodium Pathway Potential targets Lead inhibitors in development Details
Purine salvage Adenosine deaminase (ADA), purine nucleoside phosphorylase (PNP) Hypoxanthine-guanine phosphoribosyl-transferase (HGPRT)
6-thioguanosine inhibits PfADA, 5’-methylthio-immucillin-H inhibits PfPNP, 6-thioguanine inhibits HGPRT
Plasmodium lacks de novo synthesis of purines and has to salvage purines from the host. PfADA, PfPNP and HGPRT permit the parasite to form hypoxanthine (precursor of all purines) from erythrocyte purine pools [102, 84].
Anaerobic glycolysis
Lactate dehydrogenase (LDH)
Gossypol derivatives – gossylic nitrile diacetate
NAD+ is regenerated by reduction of pyruvate to lactate by LDH that is variant from human LDH. The disesquiterpene gossypol is isolated from cotton seed, but is highly toxic; its derivatives show high efficacy against P.falciparum in vitro [81, 84, 90].
Folate metabolism
Dihydrofolate reductase - thymidylate synthase (DHFR-TS)
5-fluoroorotate, Eosin B (4’,5’-dibromo-2’,7’-dinitrofluorescein) derivatives
Even partial inhibition of either DHFR or TS leads to nucleotide imbalances and parasite death. DHFR domain significantly differs from its mammalian counterpart. Eosin B is a potent inhibitor of DHFR-TS as well as glutathione reductase and thioredoxin reductase in drug-resistant malaria strains [70]. 5-fluoroorotate is metabolised to 5-fluoro-2’-deoxyuridylate that binds to TS domain [48].
Cyt
osol
Polyamine biosynthesis
Bifunctional enzyme of ornithine decarboxylase (ODC) and S-adenosyl-methionine decarboxylase (AdoMetDC)
Difluoromethylornithine (DFMO), analogues of 3-amino-oxy-2-fluoro-1-propanamine inhibit ODC
Polyamines (putrescine, spermidine, spermine) that are essential for cell growth and differentiation are synthesized in the parasite. DFMO is incapable to inhibit parasitic growth in vivo due to newly expressed transporters of putrescine and spermidine in the infected erythrocytes. The potential compound therefore should inhibit polyamine biosynthesis and transport [68, 102, 88, 58].
New permeability pathways (NPP) - the intracellular parasite induces in the host erythrocyte membrane new permeation pathways that provide the major route of entry of some essential nutrients (glutamate, pantothenate) and they mediate the efflux of various metabolic wastes. NPPs are broadly anion selective, but with a significant permeability to both organic and inorganic cations [13, 40].
Furosemide analogues (H156, H158), niflumic acid, sulfo-NHS-LC-biotin (succinimidyl-6-(biotinamido)hexanoate), bioflavonoid glycoside phlorizin, sulfonyl ureas (glibenclamide, tolbutamide), several arylaminobenzoates; dinucleoside dimmers
Two approaches: (i) inhibition of the transport of nutrients essential for parasite development, (ii) selective transport of cytotoxic compounds - dinucleoside phosphate dimers are conjugated to antimalarial compounds to improve selective access to parasite targets [12, 18, 99, 14, 93].
21
VI. POTENTIAL INHIBITORS OF PHOSPHOLIPID METABOLISM IN
PLASMODIUM
The metabolic pathway that is targeted in Plasmodium needs to be essential for parasite
survival and its inhibition should cause a nonreversible cytotoxic effect that is crucial to the parasite
but not to the mammalian host [104]. Phospholipid synthesis in Plasmodium is a unique and vital
pathway in membrane biogenesis of the asexual stages of malaria parasites.
Intraerythrocytic malaria parasites, especially in most metabolically active trophozoite stages,
synthesize considerable amounts of membranes with quasi-absence of cholesterol. These
membranes are necessary to enclose the parasitophorous vacuole, cytosol and multiple subcellular
compartments [93]. Therefore the infected-erythrocyte phospholipid (PL) content increases by as
much as 500% with phosphatidylcholine (PC) and phosphatidylethanolamine (PE) representing
about 85% of total PL content [3].
Host choline is required for de novo synthesis of PC in the parasite, thus inhibition of the
choline transport has been identified as a promising therapeutic strategy [93, 3].
6.1. De novo synthesis of phosphatidylcholine in Plasmodium
60-80% of PC is synthesized from choline via the Kennedy pathway that is also essential in
mammalian cells. CCT (choline-phosphate cytidylyltransferase) catalyzes the conversion of
phosphocholine into CDP-choline, and is the rate-limiting enzyme presenting substantial
differences with respect to its mammalian counterpart. Moreover, PC is also obtained via the
phosphatidylethanolamine N-methyltransferase pathway and from serine, which is incorporated into
phosphatidylserine and then decarboxylated to phosphatidylethanolamine [81, 61]. In this pathway
of de novo PC synthesis, parasitic CCT and choline transport, which supplies the precursor, are the
rate-limiting steps [5]. Figure 1.5 represents the PC synthesis pathway in Plasmodium.
22
Figure 1.5: The metabolic pathway of PC biosynthesis in Plasmodium [77]. Abreviations
used are: PA, phosphatidic acid; DAG, diacylglycerol; Ino, inositol; Ser, serine; Cho, choline, P-Cho, phosphocholine;
P-Etn, phosphoethanolamine; PtdIno, phosphatidylinositol; PtdSer, phosphatidylserine; PtdEtn,
phosphatidylethanolamine; PtdMMeEtn, phosphatidylmonomethylethanolamine, CDS, CDP-DAG synthase; PSD,
phosphatidylserine decarboxylase; PEMT, phosphatidylethanolamine methyltransferase; EK and CK, ethanolamine and
choline kinase, ECT and CCT, ethanolamine and choline cytidylyltransferase; EPT and CTP, ethanolamine and choline
phosphotransferase.
6.2. Potential inhibitors of PL metabolism
Series of compounds that mimic choline structure (quaternary ammonium compounds) have
been synthesized and tested in vitro for their activity against the intraerythrocytic stage of
P.falciparum and P.vivax by Henri J.Vial and colleagues. Three generations of compounds
possessing one or two quaternary ammonium ions and long lipophilic alkyl chains were rationally
designed [5]:
1st generation: mono- and bisquaternary ammonium salts (lead compounds: E10 and G25,
respectively).
2nd generation: amidine and guanidine compounds (MS1).
3rd generation: mono- and bisthiazolium compounds (lead compound: T3) and their disulfide
and thioester prodrugs (TE3).
Bisquaternary ammonium salts showed powerful antimalarial activity, with IC50 in the
nanomolar range, but had a very low oral bioavailability due to their permanently charged
quaternary ammonium moiety. However, oral administration of antimalarial compounds is essential
for dispensaries in endemic countries (due to lack of adequate facilities to safely give drug
injections), and is indispensable for prophylactic or curative treatments for travellers. The good
23
bioavailability of orally delivered antimalarial compound is a prerequisite. Therefore, bioisosteric
analogues (bis-amidines), exhibiting similar powerful activities, and subsequently the third
generation of thiazolium salts and their non-ionic precursors (prodrugs) were synthesized [95].
Prodrugs are converted to active ionized bisthiazolium drugs in the presence of plasma esterases
[80].
The lead compound of bisthiazolium salt has potent in vitro as well as in vivo antimalarial
activities and its corresponding bioprecursor was found to completely cure P.cynomolgi infected
Rhesus monkeys after 4 days of treatment with daily oral doses of 3 mg/kg [80, 105].
6.3. Quaternary ammonium compounds exhibit dual mode of action against Plasmodium
Mono- and bisquaternary ammonium, mono- and bisthiazolium salts exert their antimalarial
activity by two ways: (i) inhibiting plasmodial PL metabolism via the blockage of choline
transporter, and (ii) interacting with FP IX and the parasite pigment hemozoin [18]. These two
distinct modes of action against Plasmodium should prevent the rapid development of resistance
[91].
Choline transporter constitutes a rate-limiting step in PC biosynthesis pathway and shows
specific biochemical properties that distinguish it from the high-affinity choline transporter
observed in neurons (P.falciparum choline transporter has a low sensitivity to hemicholinium-3
(HC-3) that is an inhibitor of the high-affinity choline transporter in neurons) [18]. Choline
penetrates infected erythrocyte membranes through the endogenous carrier and through parasite
induced NPP and then is delivered into the parasite via Plasmodium membrane choline transporter.
This transporter exhibits such properties: (i) it is inhibitor-sensitive, (ii) temperature-dependent, (iii)
Na+-independent, (iiii) it is driven by the proton-motive force and (iiiii) the Michaelis-Menten
constant for choline is Km = 25.0 ± 3.5 µM [16]. Competitive blockage of choline transporter in the
infected erythrocyte or parasite plasma membrane by quaternary ammonium compounds results in
PL metabolism inhibition.
The potential antimalarial activity of bisquaternary ammonium or bisthiazolium salts relies on
their high intracellular accumulation (CAR~500), which results from accumulation in the malarial
digestive vacuole and subsequent interaction with FP IX and hemozoin [91, 16]. Although this
mode of action correlates with the chloroquine mechanism of action, bis-quaternary compounds
have not shown any cross-resistance with chloroquine [15].
24
6.4. Structure-activity relationship of quaternary ammonium compounds
Over recent years, more than 600 compounds that are choline analogues have been rationally
synthesised. The cationic charges of mono- and bis-quaternary ammonium and the presence of a
long lipophilic chain on the nitrogen atom are crucial for in vitro antimalarial activity. This activity
was dramatically increased by 2 orders of magnitude when the quaternary ammonium was
duplicated and the alkyl chain between the two nitrogen atoms contained at least 12 methylene
groups (IC50 of 10-9 to 10-12 M) [4]. Recently designed thiazolium salts with cyclic quaternary
ammonium and their nonionic precursors are optimum structures for antimalarial activity, tolerance
and specificity [91].
6.5. Monothiazolium salts T1 and T2
Today the bisthiazolium salt (T3) is in development as very potential antimalarial compound
to treat severe malaria. However, the evaluation of monothiazolium salts T1 and T2 appeared
interesting. T1 could be a possible metabolite of T2 in the body. T1 and T2 have about 50-times
lower in vitro efficacy against Plasmodium falciparum than bisthiazolium salts, but their higher
hydrophobic features might result in increased oral absorption in vivo. Moreover, these two
compounds have shown more potent activity than T3 in the treatment of some other parasitoses
such as leishmaniasis and trypanosomiasis.
In order to evaluate pharmacokinetic parameters of monothiazolium salts, analytical methods
for the quantification of T1 and T2 in biological matrices have been developed and validated. The
chemical structures of T1 and T2 are given in Figure 1.6.
3-dodecyl-5-(2-hydroxyethyl)-4-methyl- 3-dodecyl-5-(2-methoxyethyl)-4-methyl-
1,3-thiazol-3-ium bromide 1,3-thiazol-3-ium bromide
Figure 1.6: The chemical structures of monothiazolium salts T1 and T2.
25
PART 2 – EXPERIMENTAL PART
Before the presentation of the methodology and results of this work, a summarized procedure
required to validate an analytical method in biological matrices according to the European and FDA
guidelines [103] is presented.
I. DIFFERENT STEPS IN BIOANALYTICAL METHOD VALIDATION
Analytical methods used for the quantitative analysis of drugs and their metabolites in
biological samples are the key determinants in generating reproducible and reliable data that in turn
are used in the evaluation and interpretation of bioavailability, bioequivalence, and pharmacokinetic
studies [96]. It is essential to use well-defined and fully validated analytical methods to obtain
reliable results that can be satisfactorily interpreted [23].
Bioanalytical method validation includes all of the procedures required to demonstrate that a
particular bioanalytical method used for the quantitative determination of analytes (or series of
analytes) in a particular biological matrix (such as blood, plasma, serum, or urine) is reliable and
reproducible for the intended application [103]. The ultimate objective of the method validation
process is to provide evidence that the method does what it is intended to do [23].
The bioanalytical method validation can be envisaged to consist of two distinct phases: (1) the
bioanalytical method development phase in which the assay is defined and validated and (2)
application to actual analysis of samples from pharmacokinetic, bioavailability, bioequivalence and
drug interaction studies [96].
The required extent of a validation must only go as far as it is needed for the goal of the
application of the method. This means that only the analytical parameters that are of importance for
the routine application need to be validated [45].
1.1. Different types of bioanalytical method validation
[96, 103]
Full validation: establishment of all acceptable validation parameters for the bioanalytical
method for each analyte in order to apply to sample analysis. This type of validation is performed
when developing and implementing a bioanalytical method for the first time, for a new drug entity,
or if metabolites are added to an existing assay for quantitation.
Partial validation: modifications of validated bioanalytical methods that do not necessarily
require full re-validation. Some of the typical bioanalytical method changes include: bioanalytical
26
method transfers between laboratories or analysts, change in analytical methodology (e.g., change
in detection system), change in matrix within species (e.g., human plasma to human urine), change
in species within matrix (e.g. human plasma to rat plasma), selectivity demonstration of an analyte
in the presence of specific metabolites or concomitant medications, change in sample processing
procedure(s), change in relevant concentration range. The decision of which parameters have to be
revalidated depends on the logical consideration of the specific validation parameters likely to be
affected by the change made to the bioanalytical method.
Cross validation: Cross validation is a comparison of validation parameters when two or more
bioanalytical methods are used to generate data within the same study or across different studies.
1.2. Methodology
[103, 51, 23, 45, 27, 96]
The criteria considered in the validation are as follows:
Relationship between concentration and response
Specificity / selectivity
Accuracy and precision
Lower limit of quantitation (LLOQ)
Extraction recovery
Stability
Robustness / ruggedness
Matrix effects
1.2.1. Relationship between concentration and response:
The choice of an appropriate calibration model is necessary for reliable quantitation.
Therefore, the relationship between the concentration of the analyte in the sample and the
corresponding detector response must be investigated. This can be done by analyzing spiked
calibration samples and plotting the resulting ratios of peak area or peak height (analyte/internal
standard) versus the corresponding concentrations.
A sufficient number of standards should be used to adequately define the relationship between
concentration and response, and to demonstrate that the relationship is continuous and reproducible.
Concentrations of standards should be chosen on the basis of the concentration range expected in a
particular study. In many cases, six to eight concentrations (excluding blank – matrix sample
processed without analytes) can define the standard curve. For the evaluation of repeatability, it is
recommended to analyse at least six replicates of calibration set within a day (the same analyst, the
same stock solution, the same material). Reproducibility can be evaluated if one set of calibration is
27
analysed per day following at least 6 different days (the same analyst, different stock solution,
different material).
Standard curve fitting is determined by applying the simplest model (unweighted or weighted
least-squares linear regression y = ax + b, quadratic equation y = ax² + bx + c, etc.) that adequately
describes the concentration-response relationship. Statistical tests must be used to verify goodness
of fit. The quality of fit can be determined (i) by comparing back-calculated concentrations (i.e.,
concentrations obtained by entering the measured response for each standard into the regression
equation) to the nominal ones, (ii) by evaluating the correlation coefficient, (iii) by calculating the
bias or mean residual value (i.e. difference between back-calculated and added concentrations; the
bias should not be statistically different from 0), (iv) by studying the distribution of the residuals
and etc. Selection of a weighing factor and use of a complex regression equation should be justified.
If the relationship between response and concentration is linear, the test of “lack of fit” can be used.
The following conditions should be met in developing a calibration curve: 20% deviation of
the lower limit of quantitation (LLOQ) from nominal concentration and 15% deviation of standards
other than LLOQ from nominal concentration. At least five non-zero standards should meet the
above criteria, including the LLOQ and the highest concentration of the calibration curve.
Excluding the standards (leaving at least 5 points in the calibration curve) should not change the
model used.
1.2.2. Specificity / selectivity:
Selectivity is the ability of an analytical method to differentiate and quantify the analyte in the
presence of other components (metabolites, impurities, degradation products, co-administered
drugs) in the sample. Specificity is the ability to assess unequivocally the analyte in the presence of
endogenous compounds.
The specificity of the assay methodology should be established using a minimum of six
independent sources of the same matrix (exceptions can be made for hyphenated mass
spectrometry-based methods as matrix effects should be investigated).
For chromatographic procedures, representative chromatograms should be used to
demonstrate that there is no interference across the time windows of peaks of interest (i.e.,
comparison of retention times of endogenous compounds of the matrix to those of the drugs to be
analysed).
1.2.3. Accuracy and precision:
Precision and accuracy are the most important factors in assessing the quality of an analytical
method. They are determined by analysing quality control (QC) samples against a calibration curve.
28
The accuracy of a bioanalytical method is a measure of the systematic error or bias and is
defined as the degree of closeness of the determined value to the nominal or known true value under
prescribed conditions. Accuracy is calculated as follows: [mean found concentration/nominal
concentration] x 100. Accuracy is best reported as percentage bias and is sometimes termed
trueness.
The precision of a bioanalytical method is a measure of the random error and expresses the
closeness of agreement (degree of scatter) between a series of measurements obtained from multiple
sampling of the same homogenous sample under the prescribed conditions. Precision is usually
measured in terms of imprecision expressed as the percentage coefficient of variation (% CV) or
relative standard deviation (R.S.D.) of the replicate measurements.
Accuracy and precision are further subdivided into: (i) within-run, intra-batch, intra-assay
precision or accuracy that are assessed under the same operating conditions (the same analyst, the
same reagents and material) over a short interval of time (intra-day) and (ii) between-run, inter-
batch, inter-assay precision or accuracy that are measured on different days, and may involve
different analysts, material, reagents, and laboratories.
The accuracy and precision should be determined with a minimum of 6 determinations per
QC sample. A minimum of three concentrations (one within 3x the LLOQ (low QC sample), one
near the center (middle QC), and one near the upper boundary of the standard curve (high QC)) in
the range of expected concentrations is recommended. The concentrations of QC samples are
determined against a calibration curve (n = 6). The precision around the mean value should not
exceed 15% CV and the accuracy should be between 85-115%. It is desirable that these tolerances
be provided both for intra-day and inter-day experiments. At the LLOQ, 20% of precision and 80-
120% of accuracy are acceptable limits.
1.2.4. Lower limit of quantitation (LLOQ):
LLOQ is the lowest amount of an analyte in a sample that can be quantitatively determined
with suitable precision and accuracy. The LLOQ should be determined using at least five samples
containing an analyte. The LLOQ should serve as the lowest concentration on the calibration curve.
The following conditions for LLOQ should be met: (i) the analyte response at the LLOQ
should be at least 5 times the response compared to blank response; (ii) analyte peak (response)
should be identifiable, discrete, and reproducible with a precision of 20% and accuracy of 80-120%.
1.2.5. Extraction recovery:
Absolute recovery of a bioanalytical method is measured as the response of a processed
spiked matrix standard, expressed as a percentage of the response of a pure standard, which has not
29
been subjected to sample pre-treatment. It indicates whether the method provides a response for the
entire amount of the analyte that is present in the sample. Generally, the absolute recovery is
calculated at each concentration of QC samples analysed in replicates (at least three times per
concentration).
In order to study the effect of co-extracted biological material, relative recovery is computed
by comparing responses of replicates of extracted QC samples with those of extracted blank matrix
to which analyte has been added at the same nominal concentration.
If an internal standard is used, its recovery should be determined independently at the
concentration level used in the method.
Recovery of the analyte need not to be 100%, but the extent of recovery of an analyte and of
the internal standard should be consistent, precise, and reproducible. It is most important to reach a
reproducible recovery, which is high enough to satisfy the requirements of quantifying low sample
concentrations, even when the recovery itself is low. Values of recovery not less than 50, 80 and
90% have been reported as numerical acceptance limits [54].
1.2.6. Stability:
Stability of pure analyte and/or solutions of the analyte must be studied in replicate (n > 3)
under normal laboratory conditions of heat, humidity, light and air exposure by comparison with
fresh solutions.
Drug stability in a biological matrix is function of the storage conditions, the chemical
properties of the drug, the type of matrix, and the type of container. Stability data are based on
replicate determinations (at least 3) of QC samples at two or three concentrations (low, medium and
high).
Two essential types of stability studies should be performed: 1) short term stability, including
bench-stop storage, +4°C, -20°C and stability during three freeze-thaw cycles, and 2) long-term
stability. Long-term stability must be proven over at least the maximum period of storage of study
samples under the temperature conditions to be used for study samples (i.e., -20°C, -80°C) and
using the exact type of container (e.g., glass, polypropylene) as for the study samples. Generally,
the assessment of long-term stability of frozen samples is achieved by comparing the responses of
frozen and freshly prepared (time 0) QC samples.
At least three aliquots of each of the low, middle and high concentrations (QCs) should be
investigated for each type of stability studies.
Stability of the analyte should be also evaluated during all steps of the analytical procedure
(solvent used for the extraction, light exposure, temperature, autosampler).
30
1.2.7. Robustness / ruggedness:
The robustness of an analytical procedure is a measure of its capacity to remain unaffected by
small, but deliberate variations in method parameters and provides an indication of its reliability
during normal use. Typical variations in the case of liquid chromatography are: variations of pH
values in a mobile phase, variations in mobile phase composition, different columns, temperature,
flow rate. Full validation must not necessarily include ruggedness testing; it can however be very
helpful during the method development/prevalidation phase, as problems that may occur during
validation are often detected in advance. Ruggedness should be tested, if a method is supposed to be
transferred to another laboratory.
1.2.8. Matrix effects:
Matrix effects are attributed to those organic and/or inorganic components of a sample that
co-elute with an analyte affecting the ionisation efficiency in the mass spectrometer and, therefore,
the response of the analyte [24]. Endogenous co-eluting components present in any biological
matrix (e.g., salts, amines, fatty acids, etc.), compounds deriving from the LC separation (e.g.
mobile phase additives, ion-pairing agents) and exogenous materials (e.g. polymers, contained in
different brands of plastic tubes, Li-heparin, a commonly used anticoagulant) can be responsible for
this phenomenon [52, 74].
The exact mechanism of matrix effects is unknown, but it probably originates from the
competition among analyte ions and the co-eluting undetected non-volatile matrix components for
access to the droplet surface for gas phase emission [101]. These competitive mechanisms in the
droplet can cause a positive (ion enhancement) or negative (ion suppression) influence on the
resulting signal and have deleterious impact on methods precision, accuracy and sensitivity [29].
Therefore, according to recent guidelines for bioanalytical method validation, there is a need to
evaluate matrix effects during development and validation of LC-MS or LC-MS-MS methods.
In most cases, method validations are performed using standard and quality control samples
prepared from unique source of pooled matrix (whole blood, urine, etc.). In such a case, the matrix
is homogenous and thus can be assumed that prepared samples will have the same absolute matrix
effects (the response of solutes to be measured will be modified in an identical way). The use of
homogenous samples for validation does not take into account the inter- and intra-patient matrix
variability (relative matrix effect) that is present in the clinical setting [101].
The two common ways to assess matrix effects are (i) the post-extraction addition method or
(ii) the post-column infusion method. The post-extraction addition technique requires sample
extracts with the analyte of interest added post-extraction compared with pure solutions prepared in
mobile phase and containing equivalent amounts of the analyte of interest. The response of post-
31
extraction sample / response of pure solution ratio determines the degree of matrix effect occurring
to the analyte in question under chromatographic conditions. This ratio should be close to 1 (a limit
of 0.85-1.15 is generally admitted). A more dynamic technique for determining matrix effects is
post-column infusion. An infusion pump is used to deliver a constant flow of the analyte into the
HPLC eluent at a point after the chromatographic column and before the mass spectrometer
ionization source. A sample extract (without added analyte) is injected into the HPLC portion of the
instrument under the desired chromatographic conditions and the response from the infused analyte
recorded. The post-infusion technique enables the influence of the matrix on analyte response to be
investigated over the entire chromatographic run [101].
A simple experimental approach to identify and study the relative (i.e., variation of absolute
matrix effect between different lots of matrix) matrix effect has been recently described by Bogdan
Matuszewski [73]. This author suggests to investigate the precision of standard line slopes
constructed in five different sources of matrix (n = 5). Both precision (i.e., CV of the slope) and
accuracy (difference between the highest and the lowest slope divided by the lowest slope) are
calculated. A slope precision value of <3-4% is a guide for reliable method that is free from relative
matrix effect and is applicable to support clinical studies [73].
1.3. Application of validated bioanalytical method to routine drug analysis
[103, 23]
A calibration curve should be generated to quantify each analyte in each analytical run and
should be used to calculate the concentration of the analyte in the unknown samples in the run. The
spiked samples can contain more than one analyte. The calibration curve should cover the expected
unknown sample concentration range and should consist of a minimum of six standard points,
excluding blanks. An analytical run should consist of QC samples (at least duplicated), calibration
standards, and the processed samples to be analysed. The QC samples should be used to accept or
reject the run. The same analyst prepares calibration curve and samples to be analysed.
Matrix-based standard calibration samples: 75%, or a minimum of six standards, when back-
calculated should fall within ±15%, except for LLOQ, when it should be ±20% of the nominal
value. At least 67% (4 out of 6) of the QC samples should be within ±15% of their respective
nominal values; 33% of the QC samples (not all replicates at the same concentration) may be
outside the ±15% respective nominal value.
If study samples are run singly, a single calibration curve should normally be performed. If
replicates of study samples are analysed, identical replication of standard curves is recommended.
However, in practice, calibration curves are performed in duplicate even if the samples are analysed
singly.
32
II. ASSAY FOR SIMULTANEOUS DETERMINATION OF TWO
ANTIMALARIAL MONOTHIAZOLIUM COMPOUNDS IN BIOLOGICAL
MATRICES BY LIQUID CHROMATOGRAPHY – ELECTROSPRAY MASS
SPECTROMETRY
2.1. Materials and methods
2.1.1. Chemicals and reagents:
T1 (3-dodecyl-5-(2-hydroxyethyl)-4-methyl-1,3-thiazol-3-ium bromide), T2 (3-dodecyl-5-(2-
methoxyethyl)-4-methyl-1,3-thiazol-3-ium bromide) and T3 (internal standard, 1,12-bis[4-methyl-
5-(2-hydroxyethyl)-thiazol-3-ium-3-yl]dodecane dibromide, MW 614.7) were obtained from the
Laboratoire des Aminoacides, Peptides et Proteines (University Montpellier I and II). The purity of
these standards was evaluated by elemental analysis; results were within ± 0.4 of calculated values.
They were stored at ambient temperature with protection from light.
Trifluoroacetic acid (TFA) was obtained from Sigma (St Louis, MO, USA). Acetonitrile,
methanol, ammonium formate, formic acid and trimethylamine were purchased from Merck
(Darmstadt, Germany). All chemicals were of analytical grade. In-house deionised water was
further purified with a Milli-Q water-purifying system (Millipore, Bedford, MA, USA). Oasis HLB
cartridges (30 mg of sorbent, average particle diameter 30 µm) were supplied by Waters (Saint
Quentin, France).
For method validation, human whole blood and plasma were obtained from pooled blood
samples collected from healthy volunteers not undergoing drug therapy (Etablissement Français du
sang, Montpellier, France). Coagulation was prevented by adding EDTA-sodium salt. Blood
samples from Sprague-Dawley rats (Charles River Laboratories) were collected with sodium
heparin. The blood was centrifuged at 2000 x g for 10 min to obtain plasma. Red blood cells
(RBCs) were washed twice with an equal volume of 0.9% sodium chloride before storage. The
drug-free whole blood, RBCs and plasma were aliquoted, stored at -80°C and then used during the
study for the preparation of standards and quality control (QC) samples.
Individual stock solutions of T1 (45 mg/L), T2 (45 mg/L) and T3 (65 mg/L), expressed in the
form of charged compounds, were prepared by accurately weighing the required amounts in
separate volumetric flasks and dissolving in purified water. For each compound, two separate stock
standard solutions were prepared: one was used for the preparation of the calibration curve
standards and the second was used for the preparation of quality control (QC) samples.
33
2.1.2. Equipment:
The liquid chromatography – mass spectrometry (LC-MS) analysis was performed using an
Agilent 1100 quadrupole mass spectrometer (Agilent Technologies, Lesulis, France) (mass range:
m/z 50-2000) working with an electrospray ionisation (ESI) source in the positive mode.
The main parts of the mass spectrometer are the ion source, where the molecules are ionized,
the mass analyzer, where molecules are separated according to their mass-to-charge (m/z) ratio, and
the detector, where the ion signal is transferred to qualitative and quantitative data [87].
Electrospray is currently the most widely used ionisation source. ESI is a “soft” ionisation
technique (producing primarily molecular species with little fragmentation), forming protonated
[M+zH]z+or de-protonated [M-zH]z- ions for positive and negative ionisation mode, respectively
[60]. Positively charged ions such as inorganic cations and protonated organic bases are analyzed in
the positive ion mode, whereas negatively charged ions such as inorganic anions and deprotonated
organic acids are analyzed in the negative ion mode.
ESI is an interface that: (i) is relatively easy to use, (ii) exhibits low solvent consumption, (iii)
is applicable to a wide range of polar and thermally labile analytes of both low and high molecular
weight (up to 100 kDa) and (iv) is compatible with a wide range of HPLC conditions (mobile phase
flow rates from 20 nL/min to in excess of 1 mL/min). The electrospray interface produces singly or
multiply charged ions directly from an aqueous–organic solvent system. For analysis in the positive
ion mode (the most frequently used), solutions of water with a high percentage of either methanol
or acetonitrile are generally preferred. A volatile, weak acid, such as acetic acid, is added to this
solvent to increase conductivity and to facilitate the protonation of the analyte [25, 1].
The compounds that may be studied are as follows: (i) ionic compounds that are intrinsically
charged in solution; (ii) neutral/polar compounds that may be protonated (for positive-ion mass
spectra) or deprotonated (for negative-ion mass spectra) under the solution conditions employed,
e.g. appropriate pH; (iii) non-polar compounds that undergo oxidation (positive-ion mass spectra) or
reduction (negative-ion mass spectra) at the electrospray capillary tip.
The mechanism of electrospray ionisation includes three main steps [21, 25, 6] that are
presented in Figure 2.1:
1. The formation of charged droplets at the tip of the spray needle. A liquid, in which the
analyte(s) of interest has been dissolved, is passed at atmospheric pressure through a metal needle,
maintained at high voltage (2–5 kV). This voltage can be either negative or positive, depending on
the analytes chosen. The applied voltage provides the electrical field gradient (between the needle
tip and a counter electrode) required to charge the surface of the liquid and produce charge
separation. As a result, a so-called Taylor cone protrudes. Consequently, a small liquid filament is
34
established and small highly charged droplets are generated in a fine mist. A concentric flow of
nitrogen gas assists in the nebulization process.
2. Evaporation of solvent from the droplets. When the charged droplets travel towards the
counter electrode, their radius decreases as the solvent evaporates, but their charge remains
constant. At a certain point, called the Rayleigh limit, the Coulombic force overcomes the surface
tension of the liquid and the droplet undergoes fission into several smaller droplets with a radius
approximately 10% of that of the parent droplet. This so-called Coulombic fission can be repeated
in several cycles, leading to very small highly charged droplets. These droplets move through the
atmosphere towards the capillary sampling orifice and subsequently into the mass analyzer (e.g.,
quadrupole). There is a counterflow of heated nitrogen drying gas that shrinks the droplets and
carries away the uncharged material.
Figure 2.1: Schematic representation of electrospray ionization process [25].
3. The formation of gas phase ions. The actual mechanism for the transfer from solvated ions
to gas phase ions is not fully understood and has been under discussion for a long time. Two main
theories have been suggested: the charged residue mechanism (CRM) and the ion evaporation
mechanism (IEM).
The CRM mechanism implies that the gas-phase ions are produced when solvent evaporation
causes a series of Coulomb fission events that ultimately leads to the production of final small
droplets bearing one or more excess charges, but only a single analyte molecule. This analyte
molecule retains the ‘residual’ droplet charge, also when the last solvent molecule evaporates thus
forming a free gas-phase ion (Figure 2.2, A). On the other hand, the IEM mechanism asserts that
solvated ions are emitted directly from the charged droplets when the electric field on the surface of
35
the charged droplets is sufficiently high, well before the Rayleigh limit (radius <10 nm) is reached
(Figure 2.2, B) [30].
A B
Figure 2.2: Formation of gas phase ions. A – the charged residue mechanism (CRM); B -
the ion evaporation mechanism (IEM).
The mass spectrometer, used in the studies, was coupled to a Hewlett Packard LC system
equipped with a quaternary pump, a degasser and an autosampler set at 4°C. HPChem software
(version 8.04) from Agilent Technologies was used for data acquisition and handling.
Separation of the analytes was performed on a Zorbax Eclipse XD8 C8 column 150 x 4.6 mm,
i.d., packed with particles of 5 µm size (Agilent technologies). A C8 symmetry column (20 x 3.9
mm, i.d., 5 µm-size) from Waters Corporation was used as a guard column. The column was
thermostated at 20 °C.
2.1.3. Liquid chromatography-mass spectrometry conditions:
Chromatography was carried out using the gradient system of two solvents: A, 130 µL/L
trimethylamine in acetonitrile, and B, 2 mM ammonium formate buffer (126 mg/L of ammonium
formate were dissolved in purified water, the pH was adjusted to 3 ± 0.05 with formic acid). The
starting eluent consisted of 15% A and 85% B; during the first 10 min the proportion of eluent A
was increased linearly to 100% and then held for 2 min in order to wash the column. Initial
composition of eluent A (15%) and B (85%) was returned in subsequent 2 min and then held for 5
min in order to re-equilibrate the column.
The flow rate was 800 µL/min and the injection volume was 10 µL.
The mass spectrometer was calibrated in the positive ion mode using a mixture of NaI and CsI
(peak width of the mass: 0.6-0.7 amu). The MS system was operated with a capillary voltage of 4.0
kV. The sampling cone voltage was set at 60 V for T1 and T2, and at 80 V for T3. The drying gas
temperature and flow were maintained at 350°C and 12.0 L/min, respectively, and the nebulizer
pressure was set at 35 psig.
Mass spectrometric data were acquired using selected ion monitoring (SIM) mode (SIM dwell
time: 98 ms). T1 and T2 were detected through the (M+) ions at m/z 312 and m/z 326, respectively.
36
The T3 compound was detected by use of the quaternary ammonium salt (M²+/2) at m/z 227.3. The
mass spectra (scan mode) of T1, T2 and T3 are shown in Figure 2.3.
Figure 2.3: Mass spectra (scan mode) for T1 (A), T2 (B) and T3 (C).
2.1.4. Working standards:
Stock solutions of T1 and T2 were appropriately diluted in purified water to obtain the 14
working standard solutions (0.056, 0.111, 0.223, 0.56, 1.113, 2.225, 5.56, 11.125, 22.5 mg/L) used
to spike calibrators and QC samples. The stock solution of T3 was diluted 8-fold (8.125 mg/L) in
purified water before use. A reference standard solution containing T1, T2 (2.25 mg/L of each compound), and the
internal standard T3 (1.62 mg/L) was prepared daily in a mixture of 1 mL/L TFA in water and 1
mL/L TFA in acetonitrile (50:50, v/v). This solution was injected before each run to verify the
performance of the LC/ESI-MS system.
2.1.5. Preparation of calibration standards and quality control (QC) samples:
Calibration standards were prepared in drug-free plasma (0.5 mL), drug-free whole blood or
drug-free RBCs (0.25 g diluted with 0.25 mL of purified water). The calibration set consisted of 7-9
concentrations, prepared by adding 20 µL of the relevant working standard solution to drug-free
matrices. Concentrations across the range of 2.25 to 900 µg/L (expressed in the form of charged
compound) for T1 and T2 in plasma (2.25, 4.5, 9.0, 22.5, 45, 90, 225, 450 and 900 µg/L) and of 4.5
to 900 µg/kg for T1 and T2 in whole blood and RBCs (4.5, 9, 18, 45, 90, 450 and 900 µg/kg) were
obtained. A calibration set also included a blank matrix. QC samples at four different levels (3.75,
11.2, 112 and 675 µg/L in plasma; 7.5, 22.5, 225 and 600 µg/kg in whole blood and RBCs) were
37
prepared in the same way as the calibration standards by mixing drug-free matrices with 20 µL of
appropriate working solutions.
2.1.6. Sample preparation procedure:
Plasma, whole blood and RBC samples were subjected to a solid-liquid extraction for the
removal of proteins and interfering components. The 1 cm3 Waters Oasis HLB cartridges (sorbent:
N-vinylpyrrolidone-divinylbenzene copolymer, that retains both ionised and non-ionised
compounds) were conditioned with 1 mL of methanol followed by 1 mL of purified water before
use.
In a 5 mL polypropylene tube, after adding 20 µL of internal standard solution (8.125 mg/L)
and 0.5 mL of water containing 10 ml/L TFA (to precipitate the proteins) to 0.5 mL plasma sample
aliquot, the mixture was vortex-mixed for 15 s and then centrifuged for 10 min at 1500 g (4°C). The
supernatant was loaded onto the conditioned cartridge under a light vacuum (approximately 86 kPa)
using a Vac Elut 20® (Varian). The cartridge was then rinsed with 1 mL of purified water and dried
for 2 min by vacuum aspiration (approximately 27 kPa). The elution was carried out with 2 x 1 mL
of acetonitrile containing 1 mL/L TFA under a light vacuum (approximately 86 kPa). The eluate
fractions were collected in a 5 mL polypropylene tube and evaporated to dryness under the stream
of nitrogen using a Zymark Turbovap LV evaporator (Zymark Corporation, Roissy, France):
thermostatically controlled water-bath was maintained at 40°C and the evaporation process lasted
for about 40 min. The dried residue was reconstituted in 100 µL of a mixture of water containing 1
mL/L TFA and acetonitrile containing 1 mL/L TFA (50:50, v/v).
20 µL of internal standard (8.125 mg/L) were added to 0.5 mL of diluted whole blood or RBC
samples (0.25 g of whole blood or RBCs plus 0.25 mL of purified water) and mixed with 0.5 ml of
water containing 10 mL/L TFA. The acidic solution was added drop-wise while the mixture was
vortex-mixed in order to obtain smaller precipitate particles. The mixture was centrifuged for 20
min at 17,562 g (4°C). Thereafter, the assay procedure was as described above for the plasma
samples except that the cartridge was washed with 1.5 mL of purified water instead of 1 mL.
2.1.7. Data analysis:
From recorded peak areas, the ratios of each analyte and internal standard were calculated.
The obtained ratios were linked to the theoretical concentrations of each analyte in the matrix
according to a quadratic relationship (Y=ax2+bx+c, where Y is the peak area ratio and x is the
concentration of the analyte) using the PK-fit program [34]. The regression curve was not forced
through zero. The resulting equation parameters (a, b and c) were used to calculate the ‘back-
calculated’ concentrations and the obtained values were statistically evaluated. The normal
38
distribution of the residuals (i.e. difference between nominal and back-calculated concentrations)
was verified. For the comparison of the back-calculated concentrations (Ccal) and the theoretical
concentrations (Cref), the bias (mean predictor error; formula 2.1) was computed and compared to
zero (Student t-test).
Bias = ∑=
=
−ni
iREFCALC CC
n 1][1 (2.1)
Where n - the number of values; Ccal – the back-calculated concentration; Cref - the theoretical
concentration.
The 95% confidence interval for bias was also computed.
2.1.8. Validation procedure:
The validation criteria considered here are specificity, accuracy, precision, extraction recovery
and lower limit of quantitation.
The specificity of the analytical method was determined by the analysis of ten different
independent sources of the same biological matrix. The retention times of endogenous compounds
in the matrices were compared with those of the compounds of interest.
Both intra- and inter-assay precision and accuracy by analysing QC samples at four
concentrations (3.75, 11.2, 112 and 675 µg/L in plasma; 7.5, 22.5, 225 and 600 µg/kg in whole
blood and RBCs) were assessed. For intra-assay, replicate analyses (n = 6) of each QC sample were
performed the same day. For inter-assay, a set of QC samples was analysed once a day following 6
different days (n = 6). The back-calculated concentrations of QC samples were determined from a
calibration curve prepared for each set of QC samples. The accuracy was evaluated as [mean found
concentration/nominal concentration] x 100. Precision was given by the percent relative standard
deviation (R.S.D.).
Extraction recoveries of T1 and T2 in plasma, whole blood and RBCs were measured six
times at each concentration of QC samples. The areas under the peaks of extracted QC samples
were compared with those of the authentic (unextracted) standards in the relevant concentration
range prepared in a mixture containing 1 mL/L TFA in water and 1 mL/L TFA in acetonitrile
(50:50, v/v). The extraction recovery was also determined for the internal standard.
The LLOQ was defined as the lowest concentration that could be determined with accuracy
within 80-120% and precision < 20% on a day-to-day basis. To determine the analytical error in the
LLOQ, QC samples containing compounds of interest were used.
39
2.1.9. Stability study:
The stability of stock solutions was determined at 4°C. Appropriately diluted stock solutions
were injected in triplicate into LC-MS system immediately after preparation (time 0) and at periodic
intervals after the storage at 4°C over a span of 1 month.
For stability studies in plasma, whole blood and RBCs, QC samples (3.75, 11.2, 112 and 675
µg/L in plasma; 7.5, 22.5, 225 and 600 µg/kg in whole blood and RBCs) were used. The short-term
stability study included the stability of samples stored at 4°C and 20°C during 6 hours and the
stability during three freeze-thaw cycles. The long-term stability study was carried out after 1
month of storage at -20°C and -80°C.
Spiked QC samples were analyzed immediately after preparation (reference values – T0) and
after storage. The back–calculated concentrations (according to freshly prepared calibration curve)
were computed; precision (%) and accuracy (%) were determined.
Each result represented the mean of three separate samples. Compounds were considered
stable when losses were < 15%.
2.1.10. Ion suppression / enhancement study:
The absence of ion suppression / enhancement attributable to the matrix effects was
demonstrated by the method of Matuszewski et al. [71].
For this procedure, six different batches of each drug-free matrix were treated as described
above in duplicate (n = 12 per matrix and per concentration studied).
A set of QC samples (4 concentrations) was prepared using extracted blank matrices (the
blank matrix was mixed with 0.5 mL of water containing 1% TFA and then centrifuged, extracted
and evaporated). The appropriate working solutions of T1, T2 and the internal standard T3,
prepared in 1 mL/L TFA in water and 1 mL/L TFA in acetonitrile (50:50, v/v), were added to the
extracted blank plasma, whole blood or RBCs.
The reference samples were prepared by adding the drugs to the solvent (1 mL/L TFA in
water and 1 mL/L TFA in acetonitrile (50:50, v/v)) to obtain the same final concentrations.
The reconstituted extracts (in 100 µL of a mixture of 1 mL/L TFA in water and 1 mL/L TFA
in acetonitrile (50:50, v/v)) and reference solutions were injected onto the analytical column. Peak
areas obtained from the reconstituted extracts were compared with the corresponding peak areas
produced by the reference solutions. The CV% at each concentration level was calculated.
2.1.11. Pharmacokinetic study of T2 in rat:
The pharmacokinetic study was carried out according to the Principles of Laboratory Animal
Care [79] and was approved by the local Animal Use Committee.
40
Before initiation of the study, Sprague-Dawley male rats were housed in cages (6 rats per
cage) and given rodent food and free access to water. Acclimatisation and stabilisation in the
environment of 20-24ºC and 40-70% of humidity lasted for one week. Just before the study rats
were weighted (approximately 220-250 g) and identified by the number.
The formulation of T2 for intravenous administration was prepared as follows: T2 was
dissolved in 0.9% NaCl solution to obtain 0.5 mg/ml solution.
The T2 doses of 2.1 mg/kg (expressed in the form of charged compound) for single
intravenous administration was adjusted according to the exact body weight of rats. Intravenous
administration was carried out to anesthetized (with diethyl ether) rats in the vein of penis.
Blood samples (one sample per rat) were drawn in lithium-heparinized polypropylene tubes at
the following time-points (3 animals per time-point): before drug administration, 5, 10, 30 minutes
and 1, 2, 4, 8, 12, 24 and 36 hours after drug administration. Blood samples were collected after the
sacrifice of the animal by the section of the carotid artery. Animals were anesthetized with diethyl
ether 2 minutes before sampling.
Obtained blood samples were centrifuged at 4°C (2000 g for 10 min). Plasma samples were
transferred into polypropylene tubes and stored at -80°C until assay. RBCs were washed twice with
an equal volume of 0.9% NaCl to limit plasma contamination before storage at –80°C.
The samples were processed and T2 quantified following the procedure of validated method
for the quantification of T2 in the biological matrices.
Pharmacokinetic parameters were computed using a compartmental approach from the
average concentration values at each time points using the Pk-fit software.
41
2.2. Results of full validation in human plasma and whole blood
2.2.1. Drug / response relationship:
For each analyte, peak area ratios (analyte / internal standard) were linked to concentrations
using a quadratic equation. Mean coefficients of determination (r2) were 0.991 (R.S.D., 0.4%) for
T1 and 0.995 (R.S.D., 0.4%) for T2. For each compound, mean parameters of the quadratic
equation are presented in Table 2.1.
Table 2.1: Mean parameters of the quadratic equation
Analyte a (mean) ± S.D. b (mean) c (mean) ± S.D.
Human plasma (n=6)
T1 -1.90 x 10-6 ± 6.5 x 10-7 0.0060 (R.S.D., 6.1%) -0.0105 ± 0.0048 intra-day
T2 -2.16 x 10-6 ± 6.4 x 10-7 0.00815 (R.S.D., 9.3%) -0.0136 ± 0.0045
T1 -1.39 x 10-6 ± 2.01 x 10-7 0.00487(R.S.D., 6.6%) -0.00773 ± 0.0077 inter-day
T2 -1.65 x 10-6 ± 2.56 x 10-7 0.00627(R.S.D., 7.2%) -0.0123 ± 0.0101
Human whole blood (n=6)
T1 -3.13 x 10-7± 2.18 x 10-8 0.0034 (R.S.D., 10.4%) -0.000184 ± 0.0032 intra-day
T2 -6.97 x 10-7± 4.89 x 10-8 0.00498 (R.S.D., 12.5%) -0.010183 ± 0.0053
T1 -6.09 x 10-7± 4.74 x 10-8 0.00305 (R.S.D., 11.7%) -0.00506± 0.0070 inter-day
T2 -5.84 x 10-7± 6.44 x 10-8 0.00395 (R.S.D., 7.6%) -0.00780 ± 0.0056
For each point on the calibration curve, the concentrations were back-calculated from the
corresponding quadratic equation parameters. Mean back-calculated concentrations together with
precision and recovery (computed from mean back-calculated concentrations) are presented in
Tables 2.2 (human plasma data) and 2.3 (human whole blood data).
42
Back-calculated concentrations from calibration curves constructed in human whole blood
Inter-day (n=6) T1+ T2+
Nominal conc. µg/kg
Mean back-calcul.
conc. µg/kg
R.S.D. (%)
Recovery (%)
Mean back-calcul.
conc. µg/kg
R.S.D. (%)
Recovery (%)
4.50 4.24 14.3 94.3 4.59 11.7 1029.0 8.92 12.0 99.1 8.60 9.9 95.6
18.0 17.2 7.3 95.3 17.8 7.2 98.945.0 43.0 6.7 95.7 42.1 7.4 93.690.0 89.2 12.5 99.1 88.7 10.4 98.6180 179 3.4 99.4 181 4.0 101450 415 8.7 92.2 434 9.9 96.5900 899 1.9 99.9 898 2.0 99.8
43
Table 2.2: Mean back-calculated concentrations from calibration curves in human plasma
Back-calculated concentrations from calibration curves constructed in human plasma Intra-day (n=6)
T1+ T2+ Nominal
conc. µg/L
Mean back-calcul.
conc. µg/L
R.S.D. (%)
Recovery (%)
Mean back-calcul.
conc. µg/L
R.S.D. (%)
Recovery (%)
2.25 2.28 15.4 101 2.35 14.2 1054.5 4.13 12.1 91.7 4.08 7.1 90.79.0 8.62 5.0 95.7 8.37 4.2 93.0
22.5 22.8 4.2 101 22.4 6.1 99.545 43.9 6.8 97.5 44.2 6.1 98.190 90.6 4.0 101 90.1 4.0 100
225 228 5.7 101 216 6.0 96.4450 437 5.2 97.3 431 4.2 95.7900 895 2.7 99.5 878 4.4 97.6
Back-calculated concentrations from calibration curves constructed in human plasma Inter-day (n=6)
T1+ T2+Nominal
conc. µg/L
Mean back-calcul.
conc. µg/L
R.S.D. (%)
Recovery (%)
Mean back-calcul.
conc. µg/L
R.S.D. (%)
Recovery (%)
2.25 2.02 10.1 89.8 2.34 19.3 1044.5 4.55 15.4 109 4.73 14.0 1059.0 8.98 3.8 99.7 9.23 9.0 103
22.5 22.3 2.7 98.9 22.6 3.8 10145 45.6 3.3 101 46.0 2.9 10290 89.5 2.5 99.4 91.6 1.7 102
225 221 3.9 98.1 225 3.9 99.9450 444 3.5 98.6 448 6.6 99.5900 896 1.3 99.5 904 0.9 100
Table 2.3: Mean back-calculated concentrations from calibration curves in human whole blood
Back-calculated concentrations from calibration curves constructed in human whole blood
Intra-day (n=6) T1+ T2+
Nominal conc. µg/kg
Mean back-calcul.
conc. µg/kg
R.S.D. (%)
Recovery (%)
Mean back-calcul.
conc. µg/kg
R.S.D. (%)
Recovery (%)
4.50 4.24 12.3 94.2 4.82 12.1 1079.0 8.60 4.9 95.7 9.07 11.3 101
18.0 17.6 5.5 97.5 17.4 9.6 96.545.0 44.8 3.6 99.4 40.5 7.0 90.290.0 93.9 13.2 104 90.9 9.7 101180 178 3.1 98.7 177 4.7 98.2450 462 6.4 103 456 6.8 101900 891 0.7 99.1 908 1.0 101
For each analyte, the goodness of fit between back-calculated concentrations and nominal
concentrations was statistically evaluated (i) by comparing the regression line of back-calculated
versus nominal concentrations to the reference line (slope = 1 and intercept = 0); no significant
difference was observed; (ii) by studying the frequency distribution histogram of the residuals,
which were normally distributed and centered around zero, the number of positive and negative
values being approximately equal; and (iii) by comparing the bias to zero; a t-test showed that this
parameter was not statistically different from zero; moreover, the 95% confidence interval included
the zero value.
2.2.2. Retention times and specificity:
Figures 2.4 and 2.5 show typical chromatograms obtained from extracts of drug-free human
matrices spiked with the three analytes. Under the chromatographic conditions described above,
peaks were adequately separated. Observed retention times (n = 30) were 9.03 min (R.S.D. =
0.12%) for T1, 9.98 min (R.S.D. = 0.14%) for T2 and 5.11 min (R.S.D. = 0.09%) for the internal
standard T3.
The values of capacity factor (k’) were 3.1, 3.5 and 0.22 for T1, T2 and T3, respectively, and
selectivity factors were αT1, T2 = 1.13, αT3, T1 = 2.38. T1, T2 and T3 exhibited well-separated (R T1, T2
= 2.33, R T3, T1 = 9.12), narrow (wT1 = 0.25 min, wT2 = 0.23 min, wT3 = 0.18 min) and symmetrical
peaks under the chromatographic conditions described. The peak skew was evaluated using the
asymmetry coefficient As = b / a, where b is the distance from the center line of the peak to the back
slope and a is the distance from the center line of the peak to the front slope, both a and b being
measured at 10% of the total peak height. The asymmetry coefficient was 0.96 for T1, 0.87 for T2
and 0.90 for T3. The number of theoretical plates (calculated from the T3 peak) was approximately
23,600. The guard column was exchanged every 200 sample runs and the column was replaced
when the number of theoretical plates decreased below 10,000 (approximately after 1000 analyses).
44
min5 6 7 8 9 10 11
0
200000
400000
600000
800000
A
min9.1
2
10.0
3
min
TIC 1
mi5 6 7 8 9 1 1
0
20000
40000
60000
80000
100000
120000
140000B3
21
TIC
mi5 6 7 8 9 1 1
0
20000
40000
60000
80000
3m/z 326SIM
0
20000
40000
60000
800002
m/z 312SIM
min5 6 7 8 9 10 11
SIM
2
m/z 31212000
1400010000
12000
800010000
6000
4000
2000
0
Figure 2.4: Typical chromatograms of blank human plasma spiked with T1 and T2 at the following concentrations: (A) 2.25 µg/L
(LLOQ); (B) 450 µg/L. Peak 1 = T3 (internal standard); peak 2 = T1 and peak 3 = T2 (TIC, total ion current; SIM, single ion monitoring).
min5 6 7 8 9 10 11
SIM17500
14000m/z 326
1500012000
12500
0
2500
5000
7500
100003 10000
5 6 7 8 9 1 1 mi
min5 6 7 8 9 10 11
SIM 1m/z 227.3
mi5 6 7 8 9 1 1
20000
40000
60000
800001
m/z 227.3SIM 14000
800000
12000
600000 10000
400000
200000
0
0
45
Figure 2.5: Typical chromatograms of blank human whole blood spiked with T1 and T2 at the following concentrations: (A) 4.5 µg/kg
(LLOQ); (B) 450 µg/kg. Peak 1 = T3 (internal standard); peak 2 = T1 and peak 3 = T2 (TIC, total ion current; SIM, single ion monitoring).
mi5 6 7 8 9 1 1
0
200
400
600
800
1000
1200
1400
mi5 6 7 8 9 1 1
0
10000
20000
30000
40000
50000
60000TIC
SIM
3
1
mi mi0
2 3
9.1 10.0
mi5 6 7 8 9 1 1
0
200
400
600
800
1000
1200
1400SIM
2
m/z 312
m/z 326
mi5 6 7 8 9 1 1
0
10000
20000
30000
40000
50000
60000SIM 1
m/z 227.3
A
min5 6 7 8 9 10 11
0
100000
200000
300000
400000
500000
600000
B1
3
2
TIC
min5 6 7 8 9 10 11
0
100000
200000
300000
400000
500000
600000
2
m/z 312
SIM
min5 6 7 8 9 10 11
0
100000
200000
300000
400000
500000
600000 3m/z 326
SIM
min5 6 7 8 9 10 11
0
100000
200000
300000
400000
500000
600000 1m/z 227.3
SIM
46
The specificity of this method was demonstrated by representative chromatograms of blank
matrices (Figure 2.6), which indicated that each analyte was well resolved from the matrix
endogenous peaks.
Figure 2.6: Chromatograms of blank human matrices A) plasma, B) whole blood.
2.2.3. Precision, accuracy, extraction efficiency and LLOQ:
Results for intra-day and inter-day precision and accuracy are presented in Table 2.4. All
values of accuracy and precision were within recommended limits. For all matrices, the precision
values were less than 15%. The percent recoveries from the nominal values for accuracy were
between 92.7-111% for T1, and between 95.1-108% for T2.
For T1 and T2, the mean extraction recoveries were i) 87% (R.S.D. = 10%, n = 24) and 85%
(R.S.D. = 9.5%, n = 24) from human plasma, ii) 53% (R.S.D. = 14%, n = 24) and 56% (R.S.D. =
8.6%, n = 24) from human whole blood, respectively. They were not statistically different over the
range of concentrations studied. The extraction recovery of the internal standard was 89% (R.S.D. =
4.6%, n = 24) from human plasma and 51% (R.S.D. = 8%, n = 24) from human whole blood.
min5 6 7 8 9 1
ATIC
3 21
1
1750
1500
1250
1000
750
500
250
0
mi5 6 7 8 9 1 1
0
B
12
3
TIC 1400
1200
1000
800
600
400
200
47
Table 2.4: Precision and accuracy of the method
Accuracy and precision of the method in human plasma Intra-day (n=6)
T1+ T2+
Theoretical concentration
µg/L
Mean back-calculated
concentration µg/L
Precision (%)
Accuracy (%)
Mean back-calculated
concentration µg/L
Precision (%)
Accuracy (%)
3.75 3.96 8.0 106 3.90 8.6 104 11.2 12.4 4.9 111 12.12 10.4 108 112 114 5.8 102 111 9.6 99.1 675 684 6.3 101 647 9.9 95.9
Accuracy and precision of the method in human plasma Inter-day (n=6)
T1+ T2+
Theoretical concentration
µg/L
Mean back-calculated
concentration µg/L
Precision (%)
Accuracy (%)
Mean back-calculated
concentration µg/L
Precision (%)
Accuracy (%)
3.75 3.71 8.5 98.9 3.66 12.7 97.6 11.2 11.4 5.3 102 10.9 4.3 97.3 112 112 4.9 100 114 2.9 102 675 689 6.1 102 674 2.8 99.9
Accuracy and precision of the method in human whole blood Intra-day (n=6)
T1+ T2+
Theoretical concentration
µg/kg
Mean back-calculated
concentration µg/kg
Precision (%)
Accuracy (%)
Mean back-calculated
concentration µg/kg
Precision (%)
Accuracy (%)
7.5 7.45 9.0 99.3 7.57 7.2 101 22.5 21.3 12.3 94.7 21.4 9.8 95.1 225 214 7.6 95.1 215 11.0 95.6 600 577 9.0 96.2 591 9.2 98.5
Accuracy and precision of the method in human whole blood Inter-day (n=6)
T1+ T2+
Theoretical concentration
µg/kg
Mean back-calculated
concentration µg/kg
Precision (%)
Accuracy (%)
Mean back-calculated
concentration µg/kg
Precision (%)
Accuracy (%)
7.5 7.41 14.3 98.8 7.58 9.8 101 22.5 22.4 11.6 99.5 22.3 9.6 99.1 225 213 12.4 94.7 226 10.0 100 600 556 10.0 92.7 583 9.0 97.2
48
Based upon the analysis of low concentration replicate standards in each validation run, the
LLOQ value was 2.25 µg/L for both T1 and T2 in human plasma when using a 0.5 mL plasma
sample for extraction and a 10 µL injection volume for LC/ESI-MS analysis. In human whole
blood, the corresponding values were 4.5 µg/kg when using a 0.25 g whole blood for extraction and
the same injection volume. At these levels, the precision was <19.5% R.S.D. and accuracy was
89.8-107%.
2.2.4. Stability:
When stored at 4°C in the refrigerator for a period of 1 month, stock solutions of T1 and T2
did not reveal any appreciable degradation.
Human plasma and whole blood samples spiked with T1 and T2 were stored at room
temperature (20°C) or at 4°C for 6 h; no sign of decrease in the nominal starting concentration
(Table 2.5) was shown.
Both in human plasma and whole blood at least three freeze-thaw cycles can be tolerated
without losses higher than 10%. After the third freezing-thawing process, mean percent recoveries
ranged from 95.5 to 109% for T1 and from 94.7 to 113% for T2 (Table 2.5).
Frozen QC human plasma and whole blood (-20 and -80°C) samples, tested over 1 month
period, showed no sign of either degradation or losses (Table 2.5).
49
Table 2.5: Stability studies in human plasma and whole blood Stability studies in human plasma (n=3)
T1+ T2+Nominal conc.
µg/L Mean back-calcul. conc. µg/L
Precision (%)
Accuracy (%)
Mean back-calcul. conc. µg/L
Precision (%)
Accuracy (%)
After 6 h storage at 4°C 3.75 3.60 11.7 96.0 4.09 4.8 109 11.2 11.3 9.3 101 11.9 8.9 106 112 108 7.0 96.4 111 3.7 99.1 675 682 9.8 101 667 7.7 98.8
After 6 h storage at 20°C 3.75 3.86 4.2 103 4.13 4.1 110 11.2 10.5 3.9 93.7 11.3 3.0 101 112 115 8.9 103 114 9.9 102 675 694 9.2 103 659 7.5 97.6
After three freeze/thaw cycles 3.75 3.58 11.3 95.5 4.18 2.2 111 11.2 12.2 2.4 109 12.6 1.1 113 112 116 7.1 104 122 1.7 109 675 694 12.1 103 656 7.7 97.2
After 1 month storage at -20°C 3.75 3.97 15.6 106 3.78 4.3 101 11.2 11.3 7.3 101 11.0 8.5 98.2 112 115 1.2 103 116 4.0 104 675 699 9.7 104 702 3.6 104
After 1 month storage at -80°C 3.75 3.77 8.6 101 4.22 5.4 113 11.2 11.8 2.7 105 12.1 2.9 108 112 115 8.1 103 117 9.6 104 675 710 5.4 105 709 7.2 105
Stability studies in human whole blood (n=3)T1+ T2+
Nominal conc. µg/kg Mean back-calcul.
conc. µg/kg Precision
(%) Accuracy
(%) Mean back-calcul.
conc. µg/kg Precision
(%) Accuracy
(%) After 6 h storage at 4°C
7.5 7.97 8.0 106 7.82 6.8 104 22.5 23.1 1.6 103 21.9 9.8 97.3 225 234 11 104 204 6.6 90.7 600 639 6.2 107 593 9.6 98.8
After 6 h storage at 20°C 7.5 7.16 7.3 95.4 7.66 8.1 102
22.5 20.5 4.5 91.0 22.2 8.3 98.6 225 210 6.1 93.3 201 0.6 89.3 600 584 6.4 97.3 571 4.4 95.1
After three freeze/thaw cycles 7.5 8.16 4.5 109 7.99 3.9 107
22.5 23.9 4.8 106 23.8 8.5 106 225 228 6.8 101 213 5.5 94.7 600 649 6.3 108 649 5.9 108
After 1 month storage at -20°C 7.5 7.68 5.1 102 6.94 11.0 92.5
22.5 21.5 10.0 95.6 22.4 2.8 99.6 225 230 13.5 102 226 11.2 100 600 591 2.9 98.5 622 1.6 104
After 1 month storage at -80°C 7.5 7.86 7.3 105 7.12 7.8 94.9
22.5 20.6 11.5 91.6 19.4 14.4 86.2 225 223 4.5 99.1 227 1.1 101 600 596 5.0 99.3 653 3.5 109
50
2.2.5 Ion suppression / enhancement study:
The results of ion suppression / enhancement study for T1, T2 and the internal standard T3 are
presented in Table 2.6.
Table 2.6: Data of ion suppression/enhancement study
Ion suppression / enhancement
T1+ T2+Theoretical concentration Response (%) * CV (%) Response (%)* CV (%)
In human plasma (n=12 per concentration level) 3.75 µg/L 104 2.2 92.8 4.8 11.2 µg/L 107 1.1 104 1.1 112 µg/L 105 2.2 93.7 2.1 675 µg/L 106 2.2 97.0 0.8
In human whole blood (n=12 per concentration level) 7.5 µg/kg 102 3.0 93.5 5.9 22.5 µg/kg 110 2.5 92.8 3.8 225 µg/kg 102 3.2 102 4.5 600 µg/kg 94.5 1.5 99.3 4.0 * [peak area extract / peak area reference] x 100
T3++: 93% (CV 5%) (n=48) in human plasma and 113% (CV 6%) (n=48) in human whole
blood.
These findings confirmed that human plasma and whole blood had no influence on the
detection of T1, T2 and the internal standard T3.
2.3. Results of partial validation in rat plasma and RBCs
Only the results of partial validation carried out in rat RBCs are reported below.
2.3.1. Drug / response relationship:
Mean parameters of the quadratic equation, used to link peak area ratios (analyte / internal
standard) and analyte concentrations, are presented in Table 2.7.
Table 2.7: Mean parameters of the quadratic equation
Analyte a (mean) ± S.D. b (mean) c (mean) ± S.D.
Rat RBCs (n=7)
T1 -6.43 x 10-8 ± 9.75 x 10-7 0.00396 (R.S.D., 7.5%) 0.0113 ± 0.0147 Inter-day
T2 -1.45 x 10-6 ± 1.52 x 10-6 0.00860 (R.S.D., 7.6%) -0.0264 ± 0.0437
Mean back-calculated concentrations and percent recovery are reported in Table 2.8.
51
Table 2.8: Back-calculated concentrations from calibration curves performed in rat
RBCs
Back-calculated concentrations from calibration curves constructed in rat RBCs
Inter-day (n=7)
T1+ T2+Nominal conc.
µg/kg R.S.D. (%) Recovery (%) R.S.D. (%) Recovery (%) 4.50 8.4 108 18.1 101 9.0 10.2 97.5 10.8 101
18.0 12.6 96.2 11.3 102 45.0 10.9 100 8.8 104 90.0 8.5 92.3 11.5 96.8 180 9.7 102 13.2 93.3 450 7.8 106 4.4 100 900 7.5 95.5 1.2 101
From 9 to 900 µg/kg, R.S.D. values did not exceed 15% (1.2 to 13.2%) and recoveries were
between 93.3 and 106%. At the lowest concentrations (4.5 µg/kg), R.S.D. values were 8.4% for T1+
and 18.1% for T2+. The good adjustment between back-calculated and added concentrations has
been statistically proven: (i) a linear regression of the back-calculated concentrations versus the
nominal ones provided a unit slope and an intercept equal to 0; (ii) the distribution of the residuals
showed random variations, the number of positive and negative values being approximately equal;
and (iii) residuals were normally distributed and centred around zero.
2.3.2. Retention times and specificity:
The specificity of the method was demonstrated by representative chromatograms of blank rat
matrix (Figure 2.7). Each analyte was well resolved from the matrix endogenous peaks.
Figure 2.8 shows typical chromatograms obtained from extracts of drug-free RBCs spiked
with the three analytes at 4.5 µg/kg (LLOQ) and 450 µg/kg.
3 2
1
TIC
Figure 2.7: Chromatogram of a blank rat RBCs.
52
1 SIM m/z 227
SIM
SIM
TIC
m/z 326
m/z 312
3
2
2 3
1
1 SIM m/z 227
SIM
SIM
TIC
m/z 326
m/z 312
3
2
2 3
1 A
2
SIMm/z 312
3SIM m/z 326
1SIM
m/z 227
31
2
TIC B
2
SIMm/z 312
3SIM m/z 326
1SIM
m/z 227
31
2
TIC
2
SIMm/z 312
3SIM m/z 326
2
SIMm/z 312
2
SIMm/z 312
3SIM m/z 326
3SIM m/z 326
1SIM
m/z 2271SIM
m/z 227
31
2
31
2
TIC B
Figure 2.8: Typical chromatograms of blank rat RBCs spiked with T1 and T2 at the following concentrations: (A) 4.5 µg/kg; (B) 450
µg/kg. Peak 1 = T3 (internal standard); peak 2 = T1 and peak 3 = T2 (TIC, total ion current; SIM, single ion monitoring).
53
2.3.3. Precision, accuracy, extraction efficiency and LLOQ:
Inter-day precision and accuracy of the method are presented in Table 2.9. Obtained values for
accuracy (97.8-103% for T1 and 98.7-102% for T2) and precision (<10.4%) are in agreement with
the recommendation limits [103].
Table 2.9: Precision and accuracy of the method Accuracy and precision of the method in rat RBCs
Inter-day (n=7)
T1+ T2+Nominal conc.
µg/kg Precision (%) Accuracy (%) Precision (%) Accuracy (%) 7.5 10.4 101 10.0 102
22.5 10.0 97.8 9.1 98.7 225 6.8 103 8.5 101 600 9.0 98.8 9.4 101
The mean extraction recoveries from rat RBCs were 53.5% (R.S.D., 9.2%, n = 24) and 55.3%
(R.S.D., 9.4%, n = 24) for T1 and T2, respectively. The mean extraction recovery of the internal
standard T3 was 51.8% (R.S.D., 8.7%, n = 24).
The LLOQ in rat RBCs was 4.5 µg/kg for both T1 and T2 when using 0.25 g of RBCs for the
extraction and 10 µL of the reconstituted extract for the injection onto LC/ESI-MS.
2.3.4. Stability:
QC samples of rat RBCs (i) stored at room temperature (20°C) or at 4°C for 6 h, (ii) stored
frozen at -20 and -80°C and tested over a span of one month or (iii) frozen-and-thawed for three
times, showed no sign of either degradation or losses >15%.
2.3.5 Ion suppression / enhancement study:
In rat RBCs, the peak area ratios of the reconstituted extracts and the reference solutions
ranged from 0.9 to 1.1. This ratio is close to 1, therefore matrix had no effect on the detection of the
analytes.
2.4. Results of a pharmacokinetic study carried out after intravenous administration of
T2 in rat
Semilogarithmic plots of the mean (± SD) T2 plasma and RBC concentration-time profiles
after intravenous administration (2.1 mg/kg) of T2 in rat are shown in Figure 2.9.
54
0.001
0.010
0.100
1.000
10.000
0 2 4 6 8 10
Time (hours)
T2 mg/L
Plasma RBCs
Figure 2.9: Mean (SD; error bars) plasma and RBCs concentration-time curves after
single intravenous administration of 2.1 mg/kg T2 in rat.
Five minutes after intravenous administration of T2, concentrations were 0.332 ± 0.056 mg/L
in rat plasma and 2.05 ± 0.19 mg/kg in rat RBCs. Data were consistent with a two-compartment
model following first order kinetics. The half-lives of the terminal part of the curves were 2.33 h
from plasma data and 2.62 h from RBC data. The total plasma clearance was 10 L/h/kg and the
volume of distribution at steady state was 33.8 L/kg. The RBC/plasma AUC ratio was 7.9.
In opposite to the bisquaternary ammonium salts, T2 accumulated strongly within
unparasitized RBCs. In rat, T1 was the main metabolite of T2.
55
CONCLUSION
Liquid chromatography / electrospray ionisation – mass spectrometry methods with good
precision and accuracy have been developed for the simultaneous determination of two antimalarial
monothiazolium compounds, T1 and T2, in biological matrices. Full validation of T1 and T2 in
human plasma and whole blood as well as partial validation in rat plasma and RBCs have been
carried out. Distinct advantages of the method include simplicity and rapidity of sample
preparation, good resolution between the analytes, high sensitivity, reliability and specificity.
This highly sensitive, accurate and precise method was suitable to analyse plasma and RBC
samples, collected during preclinical pharmacokinetic study carried out after intravenous
administration of T2 in rat.
The study of monothiazolium compounds in the context of developmental work of
Plasmodium phospholipid metabolism inhibitors is definitely significant. Strong accumulation of
T2 in unparasitized rat RBCs indicate that further development of this potential class of antimalarial
drugs is needed.
56
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ACKNOWLEDGEMENTS
First of all I would like to deeply thank my supervisors for all support during the work on this
thesis. From start, Prof. Dr. Francoise Bressolle accepted me to join the team in the Clinical
Pharmacokinetic Laboratory (Faculty of Pharmacy, University Montpellier 1, Montpellier, France),
showed never-ending enthusiasm in the performance of experimental projects, encouraged in
writing my thesis and helped to find new solutions to various problems. I am very grateful for your
professional guidance. Prof. Dr. Vitalis Briedis suggested and encouraged to carry out the
experiments of my thesis in foreign country, advised in the field of science and showed
unbelievable understanding. I am very glad I could realize some of your many ideas.
Secondly, I am very thankful to Nicolas Taudon for fruitful scientific collaborations, advises
and consultations. I have really appreciated all lovely and good-natured support from Delphine
Margout, her kindness and willingness to teach the subtleties of laboratory work and correct French
language. I am very happy that I could join your team!
I would like to thank my colleagues of university for your friendship and collaboration.
Finally, I want to thank my family: my parents and my sister for all enormous support. And
my beloved Mindaugas: for understanding, support, care and happiness you bring into my life.
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