Upload
others
View
0
Download
0
Embed Size (px)
Citation preview
Sarah Alexandra Pais Pereira
Development of automatic systems
to study the loading and release of
anticancer drugs from mesoporous
silica nanoparticles
Dissertation of the 2nd Cycle of Studies
Degree of Master in Quality Control in the Specialty of Drug Substances and
Medicinal Plants.
Supervisors: Professor Maria Lúcia Marques Ferreira de Sousa Saraiva and
Professor André Ricardo dos Santos Araújo Pereira
March, 2018
ii
THE COMPREHENSIVE REPRODUCTION OF THIS DISSERTATION
IS AUTHORIZED ONLY FOR RESEARCH EFFECTS, THROUGH A
WRITTEN STATEMENT BY THE INTERESTED PARTY THAT IT IS
COMMITTED TO THAT.
iii
Acknowledgments
This work was carried out at the Division of Applied Chemistry, Faculty of Pharmacy,
University of Porto during the years 2017-2018.
I am extremely grateful to my supervisor, Professor Lúcia Saraiva for supporting,
encouraging and believing in my abilities from the beginning and at every step. Her positive
attitude, enthusiasm, patience and generosity, both personally and scientifically, have
always inspired me and have paved the way of my accomplishments.
I would like to express my gratitude to my co-supervisor, Professor André Pereira for
supporting and encouraging me in the development of this work. Without him, I would not
have had the opportunity to meet all the people who are currently part of my day-to-day in
laboratory.
A special acknowledgement to Marieta who besides being my laboratory colleague, I
consider her a great friend and an example for me. Thank you for your patience, support
and thoughtfulness, both personally and scientifically and for sharing with me the best and
the worst of the last years, always cheering-me up.
I wish to thank to Mafalda and Jorge for being an example for me as a couple and for
their supporting and encouraging in the last years of my life.
I am very grateful to all my colleagues from the Divison of Appllied Chemistry for their
friendship and pleasant working atmosphere.
I would also like to express my sincere gratitude to Dr. Hélder A. Santos and
Alexandra Correia for helping me in the development of this work.
I wish to thank my parents Cristina and João for their love and unconditional support
with every decisions I have made, always encouraging me to pursue my dreams.
I would like to dedicate this work to my sister Ana Luísa for lighting up my life, for her
positive wishes, inspiration and love.
I wish to also thank my grandparents Emília and Elisio for their unlimited love and
support.
Last but not the least, I want to thank to my boyfriend António for his unconditional
love, constant motivation, patience and support. Thank you for always being there for me,
in good and bad times. You’re the pillar of my strength and nothing would have been
possible without you.
iv
Resumo
O cancro é uma das principais causas de morte em todo o mundo e representa um
grupo de doenças heterogéneas caracterizadas pelo crescimento descontrolado, divisão e
disseminação de células anormais.
Uma vez que as terapias convencionais, usadas atualmente, são limitadas e têm
demonstrado uma variedade de efeitos adversos, o desenvolvimento da nanotecnologia
baseada na medicina (nano medicina), permite um avanço na eficácia terapêutica de um
grande número de fármacos anticancerígenos bem como na redução do seu perfil de
toxicidade.
As nanopartículas de sílica mesoporosa (MSNs, do inglês “Mesoporous sílica
nanoparticles”) são materiais sólidos que contêm centenas de mesoporos vazios dispostos
numa rede bidimensional. Esta rede de poros com homogeneidade no tamanho, permite
uma elevada capacidade de encapsulação e a libertação controlada de fármacos
anticancerígenos.
Neste trabalho, foram desenvolvidos dois sistemas automáticos baseados na análise
por injeção sequencial (SIA, do inglês “Sequential Injection Analysis”), um para o ensaio de
encapsulação e o outro para o ensaio de libertação. O fármaco anticancerígeno usado foi
o 5-fluorouracilo (5-FU) que é um análogo da pirimidina e cuja atividade baseia-se na
inibição irreversível da enzima timidilato sintase. As MSNs foram usadas para os ensaios
de encapsulação e libertação deste fármaco.
No sistema SIA em que se realizaram os ensaios de encapsulação, foram otimizadas
condições, como por exemplo: o volume de 5-FU e de nanopartículas (NPs) usados, o
número de alíquotas e a sua ordem de aspiração, o caudal de aspiração da solução de 5-
FU e de NPs bem como o caudal de propulsão das NPs encapsuladas para o frasco. No
sistema SIA em que se realizaram os ensaios de libertação foram também otimizadas
condições como: o volume de 5-FU aspirado e o volume de reposição para o frasco no final
do ciclo analítico., bem como o caudal de propulsão para o detetor de fluorescência
Comparando os resultados obtidos nos sistemas SIA e os obtidos em modo discreto
provou-se que as metodologias automáticas podem ser usadas na encapsulação e no
traçado dos perfis de libertação do fármaco 5-FU a partir de MSNs.
Palavras-chave: cancro, nanopartículas de sílica mesoporosa, 5-fluorouracilo,
análise por injeção sequencial, encapsulação, libertação.
v
Abstract
Cancer is one of the leading cause of death worldwide and represent a group of
heterogeneous diseases characterized by uncontrolled growth, division and spread of
abnormal cells.
Since the conventional therapies currently used are limited and have shown a variety
of adverse effects, the development of nanotechnology based medicine (nanomedicine)
provides a great breakthrough in the therapeutic efficacy of a large number of anticancer
drugs as well as reduce their toxicity profile.
Mesoporous silica nanoparticles (MSNs) are solid materials which contain hundreds
of empty mesopores arranged in a two-dimensional network of porous structure. This
ordered pore network with size homogeneity, allows a high loading capacity and enables
the controlled-release of anticancer drugs.
In this work, it was developed two automatic sequential injection analysis (SIA)
systems, one to perform the loading assays and another one to the release assays. The
chemotherapeutic agent used was 5-fluorouracil (5-FU), a pyrimidine analogue, whose
activity is based on the irreversible inhibition of thymidylate synthase. MSNs were used to
load and release this drug.
In SIA developed for loading assays, optimized conditions were studied, such as: the
volume of 5-FU and of nanoparticles (NPs) suspension used, the number of the aliquots
and their order of aspiration, the aspiration flow rate of the 5-FU solution and NPs as well
as the flow rate to propel the loaded nanoparticles to the vessel. In SIA for release assays,
optimized conditions were also studied such as: the volume of 5-FU solution aspirated to
the system and replaced to the vessel of the NPs at the end of analytical cycle, the
propulsion flow rates to the fluorescence detector.
The results obtained in SIA systems compared with the ones obtained using batch
procedures proved that the automatic methodologies can be used to load and to plot the
release profiles of 5-FU from MSNs.
Keywords: cancer, mesoporous silica nanoparticles, 5-fluorouracil, sequential
injection analysis, loading, release.
vi
Table of Contents
Acknowledgments ...................................................................................................... iii
Resumo ....................................................................................................................... iv
Abstract ........................................................................................................................ v
Table of Contents ....................................................................................................... vi
List of Figures ........................................................................................................... viii
List of tables ................................................................................................................ x
List of abbreviations ................................................................................................... xi
Chapter 1 - Introduction .................................................................................................. 1
1. Flow techniques and sequential injection analysis (SIA) .................................. 2
1.1. Determination of pharmaceuticals in SIA systems 6
1.2. Nanoparticles and SIA systems 13
1.3. Mesoporous silica nanoparticles (MSNs) and SIA systems 15
2. Mesoporous silica nanoparticles (MSNs) synthesis and surface chemistry
modifications ............................................................................................................. 17
3. Chemotherapeutic agents used in treatment of cancer ................................... 18
4. Biomedical applications of MSNs: drug delivery ............................................. 21
5. Aims of the study ................................................................................................ 22
Chapter 2 - Materials and Methods .............................................................................. 24
1. Introduction ......................................................................................................... 25
2. Reagents and solutions ..................................................................................... 25
3. Instrumentation .................................................................................................. 25
3.1. Auxiliary equipment 25
3.2. Flow Apparatus 26
3.2.1. Aspiration/ propulsion device 28
3.2.2. Fluid selector valve 30
3.2.3. Tubing and other manifold components 31
3.2.4. Informatics’ control 32
3.2.5. Detection device 33
4. Experimental procedure ..................................................................................... 34
4.1. Loading batch procedure 34
4.2. Loading sequential injection procedure 35
vii
4.3. Release batch procedure 35
4.4. Release sequential injection procedure 35
Chapter 3 - Results and Discussion............................................................................. 37
1. Introduction ......................................................................................................... 38
2. Optimization of sequential injection procedure for the loading of NPs .......... 38
3. Optimization of release sequential injection procedure .................................. 42
4. Determination of % loading using SIA system and batch procedure ............. 45
5. 5-FU release profiles obtained in batch procedure and SIA system ............... 46
6. 5-FU release profiles using different loading methodologies ......................... 49
Chapter 4 - Conclusions ............................................................................................... 52
Chapter 5 - Bibliography ............................................................................................... 54
viii
List of Figures
Figure 1 - Basic schematic of an FIA assembly, where CS: carrier solution; R: reagent; P:
pump; IV: sample injection valve (sampling); RT: reaction tube; D: detector; W: waste ..... 2
Figure 2 - Schematic sequential aspiration and propulsion of aliquots of sample and
reagent, where S, P, and R are sample, product, and reagent, respectively. ..................... 3
Figure 3 - Schematic representation of axial and radial diffusion in SIA system. ............... 4
Figure 4 - Basic schematic of a SIA assembly where CS: carrier solution; PD: peristaltic
pump or syringe pump; HC: holding coil; SV: selection valve; R: reagent; S: sample; RT:
reaction tube; D: detector and W: waste. ........................................................................... 4
Figure 5 - Chemical structures of THCPSi, TCPSi, UnTHCPSi and APTES NPs. ........... 18
Figure 6 - Chemical structure of 5-FU. ............................................................................ 23
Figure 7 - (a) Schematic representation of the SIA manifold used in loading assays. C:
carrier (phosphate buffer 0.2 mol L-1 pH 7.4), S: syringe, HC: holding coil (2m), SV: selection
valve, 5-FU: 5-fluorouracil, NPs: nanoparticles, M: loaded NPs, W: waste. (b) Sequence of
aspiration of solutions into the holding coil of the flow system: NPs and 5-FU, repeated ten
times. .............................................................................................................................. 27
Figure 8 - Schematic representation of the SIA manifold used in release assays. C: carrier
(phosphate buffer 0.2 mol L-1 pH 7.4), PP: peristaltic pump, HC: holding coil, SV: selection
valve, F: filter, S: sample, D: detector, W: waste. ............................................................ 28
Figure 9 - Syringe pump module Bu1S from Crison Instruments S.A. ............................. 29
Figure 10 - Peristaltic pump Miniplus 3 from Gilson. ....................................................... 30
Figure 11 - Selector valve with 10-port multiposition from Valco®. .................................. 31
Figure 12 - PTFE tubing used in SIA systems (1) and PTFE tubing in an eight configuration
(2). .................................................................................................................................. 31
Figure 13 - Computer software in the SIA system where it was performed loading assays.
........................................................................................................................................ 32
Figure 14 - Computer software in the SIA system where it was performed release assays.
........................................................................................................................................ 33
Figure 15 - Photography of fluorescence detector device. .............................................. 33
Figure 16 - Calibration curve obtained in HPLC to determine the concentration of 5-FU in
loading assays. ............................................................................................................... 39
Figure 17 – Volume sample and flow rate optimization in SIA system for release studies.
........................................................................................................................................ 43
Figure 18 - Calibration curve used to determine the concentration values of 5-FU obtained
in release assays. ........................................................................................................... 44
ix
Figure 19 - Release profiles using SIA system for loading, where A are APTES NPs, B are
TCPSi NPs, C are THCPSi NPs, D are UnTHCPSi NPs, 1 corresponding to the release
using batch procedure and 2 corresponding to the release using SIA system. ................ 49
Figure 20 - Release profiles using different loading methodologies and batch release,
where A are APTES NPs, B are UnTHCPSi NPs, 1 corresponding to the loading and
release using batch methods and 2 corresponding to the loading in SIA system and release
in batch method. .............................................................................................................. 50
Figure 21 - Release profiles using different loading methodologies and SIA system release,
where A are TCPSi NPs, B are THCPSi NPs, 1 corresponding to the loading and release
using SIA methods and 2 corresponding to the loading in batch method and release in SIA
system. ............................................................................................................................ 51
x
List of tables
Table 1 - Basic comparisons between FIA and SIA. Adapted from (Santos & Masini, 2010)
.......................................................................................................................................... 6
Table 2 - Main anticancer drugs used in conventional therapy ........................................ 19
Table 3 - Results of the optimization of loading assay in the flow system. ....................... 39
Table 4 – Tested conditions and respective results of the optimization of loading assay in
SIA system. ..................................................................................................................... 40
Table 5 - Analytical cycle to perform loading assay in SIA system .................................. 41
Table 6 – Analytical cycle to the implementation of release assays in SIA system. ......... 44
Table 7 - Results of % loading obtained with both loading methodologies ...................... 45
xi
List of abbreviations
A – Area
ABC – ATP-binding cassette
APTES – 3-aminopropyltriethoxysilane
ATP – Adenosine triphosphate
C – Concentration
CS – Carrier solution
CTC – Chlortetracycline
D – Detector
DDS – Drug delivery systems
DMSO – Dimethyl sulfoxide
DNA – Deoxyribonucleic acid
EPR – Enhanced permeability and retention
FdUMP – 5-fluorodeoxyuridine monophosphate
FI – Fluorescence intensity
FIA – Flow injection analysis
H2 – Hydrogen
HC – Holding coil
HF – Hydrofluoric acid
HPLC – High performance liquid chromatography
IV – Injection valve
MDR – Multidrug resistance
MSN – Mesoporous Silica Nanoparticles
NPs – Nanoparticles
OTC – Oxytetracycline
P – Product
PBS – Phosphate buffer solution
PD – Propulsion device
POEGMA – poly (oligoethylene glycol) monomethyl ether methacrylate
PP – Peristaltic pump
PTFE – Polytetrafluoroethylene
PVC – Polyvinyl chloride
R – Reagent
RSD – Relative Standard Deviation
RT – Reaction tube
S – Sample
xii
Si – Silicon
SIA – Sequential Injection Analysis
SPE – Solid phase extraction
SPS – Solid phase spectroscopy
TC – Tetracycline
TCPSi – Thermally carbonized porous silicon
THCPSi – Thermally hydrocarbonized porous silicon
TS – Thymidylate synthase
UnTHCPSi – Undecylenic acid modified THCPSi
W – Waste
5-FU – 5-fluorouracil
2
1. Flow techniques and sequential injection analysis (SIA)
It is easy to see the increase of the analytical efficiency translated by the automation
of the different stages of an analytical process by means of continuous flow techniques.
Flow techniques rely on the introduction of an aliquot in a flow sample, where contact
occurs with one or more reagents. From this process, a reaction zone will be sent to a
detection system, giving rise to an analytical signal, whose intensity is related to the physical
and chemical properties of the analysed solution.
Flow injection analysis (FIA) was the first flow technique that emerged in 1975
(Ṙuz̆ic̆ka & Hansen, 1975) and has as its operating principle the injection of an aliquot of
liquid into a non-segmented, continuous flowing carrier fluid. FIA is a general solution-
handling technique, applicable to a variety of tasks ranging from pH or conductivity
measurements to colorimetry and enzymatic assays. The injected sample is transported
towards a detector. The sample and the reagent are mixed with the flowing stream mainly
by diffusion controlled processes, with a chemical reaction occurring. The detector
continuously records the absorbance, fluorescence, electrode potential or other physical
parameter, as it changes, as a result of the passage of the reaction product through the flow
cell. Despite the simplest FIA system has only a single-flow line, FIA systems may have a
variety of manifold configurations, by reconfiguration, to allow application to nearly any
chemical system (Christian, 2004).
A FIA system typically consists of a propulsion device (PD), an injection valve (IV),
whose loop dimensions determines the volume of sample to be injected, a portion of the
reaction tube (RT) where the chemical reaction occurs and a detector (D) device where the
product formed is measured, as shown in figure 1.
On the other hand, sequential injection analysis (SIA) emerged in 1990 (Jaromir
Ruzicka & Marshall, 1990) and, according to its authors, can be considered as the second
generation of non-segmented stream injection techniques. Its proposal was primarily aimed
.
Figure 1 - Basic schematic of an FIA assembly, where CS: carrier solution; R: reagent;
P: pump; IV: sample injection valve (sampling); RT: reaction tube; D: detector; W: waste
3
at satisfying certain requirements imposed on the implementation of routine analysis of
procedures based on continuous flow namely, versatility, robustness, and simplicity.
SIA is based on the sequential aspiration of accurate sample and reagent volumes
from a selection valve to a holding tube which, after reversal of the flow direction, are
propelled to the reaction tube and then monitored in the detector. In the SIA system, the
reproducible overlap of sample zones and reagents is checked by the combination of
stoppages and flow direction changes (Jaromir Ruzicka & Marshall, 1990), as can be seen
in Figure 2.
Figure 2 - Schematic sequential aspiration and propulsion of aliquots of sample and
reagent, where S, P, and R are sample, product, and reagent, respectively.
The mixing of the different zones aspirated sequentially depends on the operational
parameters of the assembly itself and affects the extent of the dispersion suffered by the
reaction zone. In this type of systems, the dispersion is also related with convex transport
processes that occur with the flow and molecular diffusion in the contact interfaces of the
adjacent zones that affect its interpenetration (Staden; & Botha, 1998)
Considering that the flow is predominantly laminar, a segment inserted in the system
will initially be subjected to a parabolic velocity profile, favouring the concentration gradients
responsible for radial and axial diffusion (Figure 3).
4
The reversal of the flow direction causes a decrease in the axial dispersion of the
segment, resulting in a relatively symmetrical concentration profile, which leads to an
analytical signal of approximately Gaussian shape, by passage through the detector
(Staden & Botha, 1998).
Contrary to the FIA system, in the SIA assembly, after the reversal of the flow
direction, the overlapping of adjacent sample zones and reagents is only partial. This fact
is actually one of the limitations of this type of technique since, despite the possibility of
sequentially aspirating a greater number of reagents, there is a limitation as to the number
of zones that can be mixed by reversing the flow in a tubular reactor.
However, the SIA technique, due to its enormous versatility and computer control
mode, has features that facilitate the implementation of complex analytical procedures
without the physical reconfiguration of the assembly (T. Gübeli, G.D. Christian, & Ruzicka,
1991).
A SIA system consists of a propulsion device (PD) that can be a peristaltic pump or a
syringe pump; a fluid selector valve, a detector system, a holding coil, which connects the
propellant device to the fluid selection valve (SV) and a reaction tube (RT), which connects
the fluid selector valve to the detector (D) system, as shown in Figure 4.
Figure 3 - Schematic representation of axial and radial diffusion in SIA system.
Figure 4 - Basic schematic of a SIA assembly where CS: carrier solution; PD: peristaltic
pump or syringe pump; HC: holding coil; SV: selection valve; R: reagent; S: sample; RT:
reaction tube; D: detector and W: waste.
PD
5
SIA is a computer-controlled, single-line, injection technique that simplifies the
manifold and is more robust than FIA. Once computer-controlled, the propulsion device and
the selection valve operate synchronously, allowing the definition of the volume, direction
and flow velocity of the various solutions.
SIA uses a multiport selection valve as shown in Figure 4. The circulation of the fluids
occurs from the central orifice of the selection valve which can access any of the other ports,
including to the holding coil, by electrical rotation of the valve.
The holding coil is placed between the propulsion device and the selection valve and
it is essential to ensure that the length of the holding coil is sufficient to prevent
contamination of the carrier solution with the aspirated solutions (J. Ruzicka & Gubeli,
1991). The different ports of the selection valve are connected to different solutions such
as sample, reagents, standards, waste (W) reservoir and detector.
In operation, all the tubes in the SIA system are first filled with carrier solution. The
selection valve is switched to the port of detector and the propulsion device propels the
carrier solution through the system until it exits at the waste end. The selection valve is then
switched to the sample position and a few microliters of sample are drawn in by reversing
the flow of the propulsion device using precision time (Christian, 2004)
The volumes are defined by the flow rate and time of aspiration or propulsion, whereby
the propulsion device must provide precise movements of start, stop and reverse direction
of the flow, which ensures that the aspiration and propulsion of the solutions are
reproducible (T. Gübeli et al., 1991).
The propulsion device is stopped during the rotation of the selection valve to avoid
pressure surges. After the introduction of the sample in holding coil, the reagent is aspirated.
Thus, the sample and reagent solutions are sequentially injected into the holding coil and,
finally, the selection valve is switched to the detector port. The propulsion device is changed
to forward flow and the aspirated solutions are propelled through the reaction coil to the
detector flow cell. The solutions merge via diffusion and secondary forces and react to form
a product that is detected, resulting in a transient signal as in conventional FIA (Christian,
2004)
The SIA system is a solution to the need of simplifying systems and to increase their
analytical versatility while allowing independence of the empirical knowledge of the user. Its
mode of operation, based on reversals of the flow direction, coupled with the operation of
the fluid selector valve, enables not only different chemical reactions but also all types of
sample pre-treatment to be performed online (Jaromir Ruzicka & Marshall, 1990).
SIA systems have some advantages comparing with FIA methodologies since SIA
readily allows a significant reduction in the solvents, samples, and reagents consumed and
6
in waste produced. SIA allows different methodologies to be implemented without manifold
modifications (Ṙuz̆ic̆ka & Hansen, 1975). Other characteristics can be analysed in the
following table (Table 1).
Table 1 - Basic comparisons between FIA and SIA. Adapted from (Santos & Masini, 2010)
Characteristics FIA SIA
Complexity of the system Bigger Smaller
Programming knowledge Optional Necessary
Reagent consumption Higher Lower
Computer control Optional Present
Purchase cost Smaller Bigger
Addition of reagent by confluence Present Absent
Frequency of sampling
(typical values)
>100 analysis per hour < 60 analysis per hour
Operating time without parameter
adjustment (robustness)
Smaller Bigger
In addition to the above, SIA presents more characteristics as robustness, reliability,
long-term stability and the maintenance routine that allow an increase in automation of the
analytical modules considered important attributes of the methodology to be implemented.
1.1. Determination of pharmaceuticals in SIA systems
SIA system, with its advantages, have been used in the determination of different
pharmaceuticals through release, permeation and dissolution studies. In this kind of studies,
different analytical methodologies can be used with the detection of pharmaceuticals or their
metabolites, recurring to spectrophotometry, fluorimetry, chemiluminescence,
electrochemistry and so on. (Al-Kindy, Suliman, Al-Wishahi, Al-Lawati, & Aoudia, 2007;
Fraihat, 2014; Molina-Garcia, Llorent-Martinez, Fernandez-de Cordova, & Ruiz-Medina,
2012; Tzanavaras, 2011).
The majority of the determinations of active ingredients in pharmaceutical
formulations are spectrophotometric-based methods and within this group, the most of
those described are based on chromogenic reactions or on the specific characteristics of
light absorption by analytes. On the other hand, fluorimetric determinations are the most
used widespread, since the sensitivity is higher than in the spectrophotometric
determinations both by the lower interference of the matrix and also due to the wide linear
range between the intensity of the radiation source and the analytical signal measured.
7
However, in this type of determinations, it was necessary to perform an appropriate
derivatization reaction of the desired compound, since many compounds are not
fluorescence. Chemiluminescent detection can be classified into two groups. In the first
group, the analyte is the emission specie through the direct action of common strong
oxidants and in another group the analyte interferes in some way in the oxidation reaction
of the chemiluminescent precursors. (Pimenta, Montenegro, Araujo, & Calatayud, 2006).
Numerous determination studies in several SIA system configurations have been
developed using different groups of pharmaceuticals.
Pinto et al. developed a pulsed flow sequential injection analysis (SIA) system to
determinate indomethacin in pharmaceutical preparations upon alkaline hydrolysis in
micellar medium and detection of the fluorescent formed products. This new methodology
took advantageous of the enhance mixture of solutions due to the use of solenoid micro-
pumps as impulsion devices and was favourably compared with the reference method being
though considered a good alternative to other already available proposals (Pinto, Saraiva,
Santos, & Lima, 2005).
Indomethacin was also assayed with another SIA methodology coupled with solid
phase spectroscopy (SPS). SPS is an alternative to the limitation of the spectroscopic
methods since their applicability to complex matrixes, such as biological samples, is difficult.
SPS is based on the direct measurement of the degree of light absorption or emission
shown by an active solid support on which the analyte or its derivative compound is retained,
thereby achieving an important improvement with respect to conventional solution
spectrophotometry in both sensitivity and selectivity. The method proposed by Molina-
Garcia et al. is suitable for the analysis of indomethacin not only in pharmaceuticals but also
in human urine at levels usually found in patients after administration. Hence, the method
could be useful for easy, rapid, selective, and highly sensitive analysis of indomethacin
using a low-cost analytical instrumentation (Molina-Garca, Crdova, & Ruiz-Medina, 2010).
Silva et al. developed a SIA spectrophotometric methodology for the determination of
metoclopramide in pharmaceutical preparations (de Souza Silva, Saraiva, Santos, & Lima,
2007). The approach was based on the reaction of metoclopramide with Folin–Ciocalteu
reagent. In this SIA system, it was incorporated an in-line mixing chamber to promote
reaction zone homogenization, to increase reaction time, and to attenuate the high
refractive index gradient generated by the utilization of concentrated solutions, thus
enabling the minimization of the Schlieren effect. In a conventional sequential injection
system, the reaction coil length and flow rate have a profound effect on sample/reagent
mixing and reaction time, therefore on sensitivity and sampling rate. However, their impact
was minimized due to the introduction of the mixing chamber. With this configuration, it was
8
possible to enhance the reaction zone, both by increasing sample and Folin–Ciocalteu
reagent volumes, while ensuring an adequate homogenization. So, the inclusion of a mixing
chamber in an SIA manifold was revealed to be an expeditious alternative to the commonly
used reaction coil, as it ensures enhanced sample/reagents mixing and provides the means
for increased reaction development when a stopped-flow approach is implemented (de
Souza Silva et al., 2007). Comparing the linear range and the detection limit of this study
and another one (Guo, Feng, & Fan, 2009), the results are different. In the first study, the
linear range obtained was of up to 100 mg L-1 and the detection limit was 2.0 mg L-1 while
in the second study, the linear range obtained was 20–250 μg mL-1 for metoclopramide with
a detection limit of 0.034 μg mL-1.
In another perspective, Llorent-Marínez et al. developed a SIA methodology coupled
with SPS as an alternative to conventional optosensors, that is, the coupling of FIA and
SPS. This methodology was used for the determination of paracetamol after appropriate
derivatization reaction. The fluorimetric SIA optosensor used in this study was based on the
continuous measurement of the fluorescence signal from the oxidation product of the
analyte directly retained on the solid sensing phase. The method has been satisfactorily
applied to the determination of paracetamol in pharmaceuticals, and an additional recovery
study had been also performed, obtaining good results (Llorent-Martínez, Šatínský, Solich,
Ortega-Barrales, & Molina-Díaz, 2007).
On the other hand, Passos et al. developed a SIA methodology with a
spectrophotometric detector capable of determining three pharmaceuticals: metoprolol,
acebutolol, and propranolol. Comparing this methodology with British Pharmacopeia, SIA
allowed a drastic reduction in the time necessary for each determination (10-90 minutes
using BP procedures to 5 minutes in the SIA procedure). This fact is a significant
disadvantage in the pharmaceutical quality control, which advocates the use of the SIA
methodology that consumes a small sample and the characteristics present to be used for
the on-line pre-treatment of the sample and an almost real-time monitoring of the processes
of dissolution (M. L. C. Passos, Saraiva, Lima, & Korn, 2008).
In the next study, a SIA spectrophotometric method was described for the
determination of tetracycline (TC), chlortetracycline (CTC) and oxytetracycline (OTC) in
different sample matrices. The proposed method has been satisfactorily applied for the
determination of tetracycline and its derivatives in pharmaceutical preparations together
with their residues in milk and honey samples collected in Chiang Mai Province. The method
was rapid with a sampling rate of over 60 samples h−1 for the three drugs. The described
SIA system proved to be accomplished to sensitivity and detection limit, simplicity,
reproducibility, and rapidity. The advantages of the proposed SIA method are cost-
9
effectiveness and less operator input requirements system that can be controlled by means
of the laboratory-made software which is relatively inexpensive. Therefore, this method is
suitable for routine analysis (Thanasarakhan et al., 2011).
Naheid et al. reported the optimization and validation of a new, rapid, reagent-saving
and environmentally-safe method for chlorpromazine assay in pharmaceutical formulations
utilizing a SIA technique. This new SIA system was compared with another SIA technique
and the authors concluded that the sampling frequency of the new method was 51.4
samples/h while in the previous method was 22 samples/h. Furthermore, the total disposed
volume in the new SIA method, including water as a propeller solution, was 1260 mL while
that of the previous method was 2290 mL. The drastic reduction of the consumed volumes
of reagents and samples does not only render analytical method reagent-saving but also
offers better safety for the environment (Naheid et al., 2013).
In another study, Šrámková et al. developed a SIA methodology allowing the
determination of propofol without the requirement of sample pre-treatment. The method was
based on spectrophotometric detection after the enzymatic oxidation catalysed by
horseradish peroxidase and subsequent coupling with 4-aminoantipyrine leading to a
coloured product with an absorbance maximum at 485 nm. This procedure was compared
with a simple fluorimetric method, which was based on the direct selective fluorescence
emission of propofol in ethanol at 347 nm. In the spectrophotometric method, the time of
analysis per run was longer which included the enzymatic reaction. However, this did not
lead to higher solvent and reagent consumption, compared to other flow methods.
Furthermore, comparing both methods, it can be seen that the spectrophotometric provided
a sensitivity comparable to the simple fluorimetric detection and higher selectivity is
expected due to the enzymatic reaction (Šrámková et al., 2014).
Vakh et al. developed a SIA system based on the sandwich technique for the
simultaneous separate determination of iron (II) and ascorbic acid in pharmaceuticals (Vakh
et al., 2015). The implementation of a sandwich technique assumed the strict order
aspiration of sample solution between two selective reagents and allowed the carrying out
in reaction coil two chemical reactions simultaneously: iron (II) with 1,10-phenanthroline and
ascorbic acid with sodium 2,6-dichlorophenolindophenol. Despite the need to use the
relatively large sample volume for preventing the overlapping of the coloured zones, the
sandwich technique is characterized by satisfactory sampling frequency because of the high
use. Moreover, due to the optimization of physical parameters of the flow systems, it
becomes possible to achieve the excellent repeatability of analysis and considerable
reagent saving. So, the implementation of this flow system based on sandwich technique,
10
allow the determination of the iron (II) and ascorbic acid giving rise to two analytical signals
at the wavelength 510 nm for iron (II) and 512 nm for ascorbic acid (Vakh et al., 2015).
Regarding permeation studies, Franz diffusion cells can be used for monitoring the
release of pharmaceuticals. In a few words, Franz diffusion cells consist of two
compartments, a donor compartment and an acceptor compartment, with a barrier between
them. The donor compartment maintains the preparation of the drug; the acceptor
compartment contains an acceptor medium, the composition of which is determined by the
solubility of the drug. When performing the experiments, samples from the acceptor medium
are drawn through the sampling port of the Franz cell. The entire apparatus is maintained
at constant temperature by a water bath. The receiver fluid is mixed by a magnetic stir bar
(Solich, Sklenarova, Huclova, Satinsky, & Schaefer, 2003).
The apparatus was used in a SIA system to monitoring release profiles of
Indomethacin 1% gel. In this study, the authors compared the release rates of gels and
ointment prepared by different technological procedures since they used membranes of
different materials (poly-carbonate, mixed esters of cellulose, teflon, silicon, poly-vinylidene
fluoride) and different pore diameters. After this studies, a poly-carbonate membrane with
a pore diameter of 0.4 µm was selected to compare the release rates of indomethacin. In
SIA system, the release profile of the three different pharmaceutical formulations tested was
monitored without any necessity of human control during the whole 6 hours per cycle. This
enables the measurement of a high number of experimental points of the profile in shorter
time periods and therefore allows calculating the release rate after 2 h of the liberation
experiment. Moreover, the results obtained with the SIA system were confirmed by
conventional batch UV measurement (Solich et al., 2003).
On the other hand, Klimundová et al. performed a SIA system for carrying out
simultaneous release tests with three or more Franz cells to examine Belosalic® ointment
containing 3% salicylic acid as the active substance. This SIA system did not require any
human control during the experiments and allowed simultaneous monitoring of the release
tests for up to six Franz diffusion cells, making this system a useful tool for the release tests
used during manufacturing process control, monitoring pre- and post-changes in product
properties, monitoring batch uniformity as well as pre-formulation screening and product
development (Klimundova, Mervartova, Sklenarova, Solich, & Polasek, 2006).
In a different way, a SIA system could be used in pharmaceuticals dissolution assays,
since this methodology enables the analysis of samples within a wide range of
concentrations without manifold reconfigurations and with the consumption of a low sample
volume. The dissolution assays are important for quality control of pharmaceuticals
formulations. These tests supply detailed information about the dynamic characteristics of
11
the dissolution process and they are also useful for the development of new dosage forms
(Pimenta et al., 2006).
The first SIA system developed for dissolution assays was described for Liu and Fang
in 1998 (Liu & Fang, 1998). This study evaluated the dissolution profiles of ibuprofen tablets
sustained-release capsules and controlled-release matrix tablets. In this system, the
samples were collected after on-line filtration and the ibuprofen determined by monitoring
at 222 nm. Every hour, seven samples run in hexa-replicates were processed with a total
of 42 measurements. The system was continuously run for 12 h with an overall relative
standard deviation of absorbance 2.18%. The excellent long-term precision demonstrated
the stability and robustness of the automated system (Liu & Fang, 1998).
Subsequently, the same authors taking the advantage of the versatility and flexibility
of the system developed, performed the simultaneous monitoring aspirin, phenacetin, and
caffeine in compound aspirin tablets. For the simultaneous determination of the three active
substances, a partial least squares calibration technique was used. Using this system, it
was possible to analyse a total of 45 measurements (15 samples h-1) and the sample
consumption per determination was 0.2 ml. This system did not require the separation of
the analytes, since was quick and easily adapted to monitoring various dissolution vessels
and allowed the attainment of results in real time, with an elevated resolution of the
dissolution kinetics in the three analytes (Liu, Liu, Wu, & Fang, 1999).
Paseková et al. developed an automated procedure for formulation assays and
dissolution tests based on a SIA system involving an ion-selective electrode as a sensing
device. A tubular salicylate selective electrode was constructed for potentiometric
determination of acetylsalicylic acid in pharmaceutical formulations. The electrode was used
for sensing acetylsalicylic acid after its on-line chemical hydrolysis to salicylate in the SIA
system. The sampling rate was 6 h-1 but for the dissolution tests, the frequency was
increased to 20 h-1. The SIA set-up was employed for the assay of acetylsalicylic acid in
plain tablets, composed tablets, and effervescent tablets and for performing dissolution
tests of normal and sustained-release tablets. The results obtained in the acetylsalicylic
acid dosage assays in various pharmaceutical formulations, including composed and
effervescent tablets, were in compliance with the reference HPLC methodology, described
in the American Pharmacopeia. These two methodologies selectively determined the
acetylsalicylic acid even in the presence of other active substances (Pasekova, Sales,
Montenegro, Araujo, & Polasek, 2001).
In another study, Legnerová et al. monitored the dissolution assay of ergotamine
tartare in pharmaceutical formulations using a SIA system (Legnerova, Sklenarova, &
Solich, 2002). The samples were filtered and aspirated by the system and then directed
12
towards the fluorescent detector. These dissolution assays had a duration of 20 min, a
sampling rate of 120 samples h-1 and a sample consumption per measurement of 50 µL.
Various dissolution tests of ergotamine tablets were carried out and the results obtained
were in compliance with the British Pharmacopeia reference methodology (Legnerova et
al., 2002). These authors also proposed the fully automated approach for monitoring the
profiles of prazosin hydrochloride by fluorescence. In this study, the dissolution tests had a
duration of 60 min, a sampling rate of 70 samples h-1 and a sample consumption per
measurement of 20 µL. The results obtained by SIA technique was compared well with
HPLC standard method (Legnerova, Huclova, Thun, & Solich, 2004).
In addition to the previous studies, Legnerová et al. developed a SIA system for the
separation and simultaneous determination of two active substances in combined
pharmaceutical formulation, composed of ascorbic acid and rutin trihydrate, using a solid
phase extraction (SPE) microcolumn coupled to the SIA system (Legnerova, Satinsky, &
Solich, 2003). The SPE microcolumn was used for retention of rutin trihydrate, while the
ascorbic acid was eluted with the solvent front phase. The proposed methodology based
on SIA system with spectrophotometric detection was successfully applied to the assays
and dissolution studies of these active pharmacological compounds. The SIA–SPE method
exhibited similar or slightly lower sensitivity than conventional separation techniques (liquid
chromatography and capillary electrophoresis). These two methods were reliable and
sensitive, but required expensive instrumentation, involving lengthy sample preparation
procedures, making the whole analysis relatively slow and complicated. On the other hand,
SIA–SPE was much more rapid (the frequency of injections of samples was 26 h−1) and
allowed on-line treatment of the samples without time consumption possible. Furthermore,
this new system exhibited the advantages of both methods with minimum drawbacks:
analytes separation, robustness, full automation and online performance of dissolution
studies, high sample throughput and non-continuous flow and a drastic decrease in the
organic waste generation (Legnerova et al., 2003).
Pinto et al. developed a SIA methodology with a fluorimetric detector for the
determination of aminocaproic acid in pharmaceutical formulations. Since aminocaproic
acid does not emit fluorescence, it was necessary to perform a derivatization reaction.
Comparing the results obtained with the recommended method (USP 24), the results were
in agreement with the imposed criteria by USP 24, which refers that not less than 75% of
the amount of aminocaproic acid should be dissolved in 45 minutes (Pinto, Saraiva, Santos,
& Lima, 2006).
13
1.2. Nanoparticles and SIA systems
Nowadays, nanoparticles (NPs) associated with analytical methodologies are the
most extensively exploited area of nanotechnology. The fact that NPs have peculiar
characteristics allow the improvement of well established analytical methods or the
development of new methodologies for new analytes or matrices (Kaur & Gupta, 2009).
Currently, automated flow analytical methods enable the incorporation of all types of
NPs for varied applications. The automation of all stages of the analytical process allows
the implementation of effective in-line pre-treatments of samples, guaranteeing the
reproducibility during the insertion of solutions and the implementation of the reaction and
transport zone for detection. Beyond this, the automation provides conditions to perform the
assays in a closed environment, with inherent advantages in terms of reaction control,
reagent consumption and analysis time, allowing the implementation of more complex
reaction schemes or multiparameter determinations (Marieta L. C. Passos, Pinto, Santos,
Saraiva, & Araujo, 2015).
Flow-based techniques present also adequate characteristics for the synthesis of
nanomaterials since they provide large surface areas and reduced diffusion resulting in fast
mass transport due to the downsized dimensions of tubing or channels, covering a wide
range of compositions and tunable sizes. These characteristics facilitate the attainment of
high synthesis yields by means of a precise control of the reaction environment while
reducing the consumption of expensive or toxic reactants as well as waste production
(Zhao, He, Qiao, & Middelberg, 2011).
Thus, the association of flow systems with NPs exhibits enormous potential due to
the combination of different factors such as the inherent advantageous properties of NPs,
the precise and reproducible control of NPs / chemical analyte detection mechanisms and
the simplicity, versatility and easy techniques of flow-based techniques.
In the last years, flow researchers have informed the scientific community about the
implementation of NPs-based assays in SIA systems, mainly for analytical purposes,
exploring the versatility of SIA systems that allows the incorporation of additional devices
such as sensors, reactors or pre-treatment devices of samples allowing the accomplishment
of several concomitant actions. In this way, the automation of NPs-based assays using the
SIA systems mainly explores the versatility of the selection valve and the computer-
controlled mode of operation which, in addition to allowing the implementation of parallel
events at the valve's lateral inlets, also allows the strict control of conditions of reaction in
terms of space and time. All these possibilities make this technique very suitable not only
for analytical applications but also for the implementation of synthetic processes in which
14
the assays conditions determine the properties of the resulting NPs (Marieta L. C. Passos
et al., 2015).
Alarfaj and El-Tohany determined naloxone and raloxifene, an opioid antagonist and
anticancer respectively, through two different SIA methodologies, both with
chemiluminescence detector. In the determination of naloxone, the authors used the gold
nanoparticles-luminol-ferricyanide system, while in the determination of raloxifene it also
included the synthesis gelatin-capped bimetallic Au–Ag nanoparticles in the SIA system
and determinate raloxifene. So, despite the different configurations of SIA systems, this
proves the versatility of SIA methodology (N. A. Alarfaj & M. F. El-Tohamy, 2015; Alarfaj &
El-Tohamy, 2016).
The same authors developed another study in which they performed two novel
sensitive sequential injection chemiluminescence analysis and fluorescence methods for
the antibiotic trovafloxacin mesylate detection. The methods were based on the
enhancement effect of gold nanoparticles on luminol–ferricyanide–trovafloxacin and
europium(III)–trovafloxacin complex systems. The fluorescence method gave a wide linear
concentration range, but use one reagent was more favorable than using three reagents in
fluorescence detection. Based to its characteristic advantages, for example, robustness,
versatility, automated sampling and analytical procedures, low consumption of sample and
reagents, short analysis time, and computer compatibility, SIA with chemiluminescence
detection is more sensitive than the fluorescence method and facilitates precise fluidic
handling of sample and reagents (Nawal A. Alarfaj & Maha F. El-Tohamy, 2015).
In addition to previous studies, Alarfaj et al. developed SIA chemiluminescence
detection method for the determination of cephalosporin antibiotic cefditoren pivoxil. In this
case, the developed method was based on the enhancement effect of silver nanoparticles
on the chemiluminescence signal arising from a luminol–potassium ferricyanide reaction in
the presence of cefditoren pivoxil. According to the results of this study, the method was
found to be sensitive, reproducible and accurate for the determination of the drug in its bulk
powder, dosage forms, and biological fluids. The enhancement effect of cefditoren pivoxil
on the employed system was proportional to its concentration, which showed good results
relevant to the linear concentration range 0.001–5000 ng mL-1. The proposed method has
been proved to be fast, inexpensive, highly sensitive and precise (Alarfaj, Aly, & El-Tohamy,
2015).
In another perspective, the synthesize of NPs could be performed inside a SIA
system. Passos et al. developed the first successful attempt to synthesis biosilica NPs. In
this study, there was synthesis the NPs and also the immobilization of an enzyme, laccase,
on the nanostructures. The results obtained showed some advantages, namely,
15
reproducibility between all the samples used when compared with the small-scale batch-
based process, and the absence of clogging due to the operational characteristics of the
SIA technique. Besides the good reaction conditions, such as ambient temperatures,
physiological pH range, and aqueous solvents, this SIA procedure was shown to be a rapid,
simple, and more sensitive alternative method for the enzyme immobilization that results in
the physical entrapment of enzymes within silica nanospheres as they are formed (M. L. C.
Passos, Lima, & Saraiva, 2013).
1.3. Mesoporous silica nanoparticles (MSNs) and SIA systems
One of the types of nanoparticles that have been associated with flow systems is
mesoporous silica nanoparticles (MSNs). MSNs are solid materials which contain hundreds
of empty mesopores arranged in a two-dimensional network of a porous structure. This
ordered pore network, with size homogeneity, allows a high loading capacity and enables
the controlled-release of anticancer drugs (Alvarez-Berrios, Sosa-Cintron, Rodriguez-Lugo,
Juneja, & Vivero-Escoto, 2016).
MSNs exhibit the typical characteristics of inorganic nano-biomaterials such as high
thermal/chemical stability, tunable biocompatibility/biodegradability and resistance to
corrosion under extreme conditions (Chen, Chen, & Shi, 2014b).
MSNs present a variety of successful characteristics that potentiate the application on
drug delivery such as: high drug loading efficiency, high degree of tunability regarding size,
controlling drug release, protecting cargoes and cell and tissue targeting to prevent the
premature release of anticancer drugs, biodistribution, biodegradation and excretion (Hu,
Xiao, & Zhang, 2016; Martinez-Carmona, Colilla, & Vallet-Regi, 2015).
Furthermore, MSNs have unique tunable properties such as high surface area (> 700
m2 g-1), large pore volume (> 0.9 cm3 g-1) and surface area (2-10 nm and recently until 50
nm). MSNs also present a stable and rigid framework with great chemical, mechanical and
thermal stability. Although they have demonstrated good properties, it is also possible to
easily perform surface functionalization on the internal or external pore surface, for the site-
specific delivery (Alvarez-Berrios et al., 2016; Beltran-Osuna & Perilla, 2016; Douroumis,
Onyesom, Maniruzzaman, & Mitchell, 2013).
The structural properties of MSNs enable the encapsulation of hydrophobic and
hydrophilic drugs, making MSNs a promising drug delivery carrier for cancer therapy
(Alvarez-Berrios et al., 2016).
MSNs can be synthesized by different methods such as modified Stöber method,
aerosol-assisted synthesis or spray drying method, soft and hard templating, and dissolving
reconstruction (S. H. Wu, Mou, & Lin, 2013)
16
In an ideal synthesis of MSNs, it is necessary that the nanoparticles present several
good characteristics to be desirable for versatile applications, such as well-suspended
stable solution, controllable pore size, controllable uniform particle size and large pore
volume (S. H. Wu et al., 2013).
A larger pore volume and surface area enable a higher amount of drug encapsulation
within them (Rosenholm, Zhang, Linden, & Sahlgren, 2016). The different MSN pore sizes
allow to effectively control the anticancer drug release inside the tumor (Huang, Cole, Cai,
& Cai, 2016).
Although these properties can be tunable for the controlled drug delivery and
multifunctional in cancer treatment, the cytotoxicity and the biocompatibility have been
studied in vitro and in vivo. The results of these studies demonstrated that MSNs are very
biocompatible and non-cytotoxic (Douroumis et al., 2013).
In addition, MSNs can be also used in catalysis (Dickschat et al., 2013; Fu, Li, Han,
Liu, & Yang, 2014; Lin, Ren, & Qu, 2014; Rimoldi, Fodor, van Bokhoven, & Mezzetti, 2013),
dye-doped imaging and sensing (Miletto et al., 2014; Montalti, Prodi, Rampazzo, &
Zaccheroni, 2014; Wang, Sun, Wang, Bai, & Wu, 2014), adsorption (Gibson, 2014; Rimola,
Costa, Sodupe, Lambert, & Ugliengo, 2013), detection (Panda, Dhar, Malvi, Bhattacharjee,
& Sen Gupta, 2013; Zhou, Zheng, & Wang, 2014) and biomedical and theranostic systems
(Chen, Chen, & Shi, 2014a; Q. J. He & Shi, 2014; Z. X. Li, Barnes, Bosoy, Stoddart, & Zink,
2012).
Furthermore, the surface of MSNs has been considered a key factor directly affecting
the interaction of the MSNs with cells and it has been widely studied in biomedical and
pharmaceutical fields (Shahabi et al., 2015).
MSNs have high amounts of silanol (Si-OH) on their surface that provide covalent
conjugations with different types of functionalization, mainly polar molecules, such as:
carboxylate, amine, amine/phosphonate, polyethylene glycol, octadecyl and
carboxylate/octadecyl groups (Bagwe, Hilliard, & Tan, 2006; Dou, Hu, Li, Qiao, & Hao,
2011).
Other functional groups such as aromatic rings induce hydrophobicity on the surface
of MSNs, thereby preventing the loading with hydrophilic compounds into the mesopores
(Manzano & Vallet-Regi, 2010).
Since these nanoparticles have all these advantageous characteristics, they have
been associated with other types of nanoparticles aiming at mainly the development of
sensing devices. Pan and Yang developed the first FIA assay based on NPs resorting to
MSNs associated to magnetic NPs for the immobilization of an anti-carcinoembryonic
antibody. This study demonstrated that the implementation of this flow system provides also
17
appropriate conditions for the automation of the steps of antigen-antibody interaction and
sensor regeneration (J. Pan & Yang, 2007).
2. Mesoporous silica nanoparticles (MSNs) synthesis and surface
chemistry modifications
The synthesis of MSNs is commonly carried out by the electrochemical dissolution of
bulk silicon (Si) in a hydrofluoric acid (HF) based electrolyte. For this, a Si wafer is placed
between two HF resistant electrolyte cells in which platinum electrodes are located on both
sides of the Si wafer and an electrical current is applied between them. The upper side of
the Si substrates acts as the anode, where the oxidation and chemical etching of the Si
surface takes place with the subsequent dissolution of Si and formation of a Si layer. The
lower side of the wafer is the cathode, which is in contact with a conductive metal. Here,
the proton reduction takes place, leading to the formation and evacuation of hydrogen (H2)
(J. Salonen, A. M. Kaukonen, J. Hirvonen, & V.-P. Lehto, 2008).
Usually, the surface of MSNs is stabilized through different methods such as
oxidation, hydrosilylation or carbonization (Salonen & Lehto, 2008).
The surface of the UnTHCPSi, THCPSi, and TCPSi NPs (Figure 5), used herein, are
stabilized by carbonization. Carbonization of the surface of this NPs refers to the
substitution of the Si-H bonds for Si-C bonds, providing to this NPs stability towards harsh
chemical conditions and oxidation. The most common method that is used is the thermal
carbonization of Si in the presence of acetylene. Since the small molecules of acetylene
rapid diffuse through the pores, a complete carbonization can be achieved. Two types of
surface chemistries are obtained, depending on the temperature used. So, these are, Si-
CH, when the treatment temperature is below 650 ºC, rendering thermally hydrocarbonized
Si (THCPSi) and hydrogen-free Si-C species, and when the treatment temperature is above
700 ºC, thermally carbonized MSNs (TCPSi) (Bjorkqvist, Paski, Salonen, & Lehto, 2006;
Salonen, Björkqvist, Laine, & Niinistö, 2004; Sarparanta et al., 2011) are generated.
Similarly to the hydrosilylation of native MSNs, the surface of THCPSi NPs has been
functionalized by thermal treatment of the particles in undecylenic acid for 16h at 120 ºC to
obtain undecylenic acid modified THCPSi (UnTHCPSi). The presence of –COOH groups
allows easy covalent attachment of other biopolymers, macromolecules, or fluorescent dyes
having a great impact on drug delivery applications (Kovalainen et al., 2012).
APTES NPs are 3-aminopropyltriethoxysilane functionalized TCPSi NPs, in order to
covalently attach a –NH2 termination on the surface. This NPs provide to TCPSi NPs a new
secondary functionalization with amine group termination (-NH2). In drug delivery, a
positively charged surface enables the adhesion of the particles onto the cell walls where
18
they may more effectively release the drug payload (Makila et al., 2012; Slowing, G. Trewyn,
& S.-Y. Lin, 2006). Moreover, the amine termination, is common in immobilization of
peptides and specific cells, making this property surface very beneficial for biosensing
purpose (Kim, Cho, Seidler, Kurland, & Yadavalli, 2010).
APTES NPs improve drug delivery and present, also, other advantages since there
are many studies that provide evidence that APTES can reduce the toxicity of MSNs both
in vitro and in vivo. It is believed that the amine groups on the silica surface help to decrease
the surface reactivity of exposed surface silanol groups on the NPs. In other words, linking
APTES to MSNs can increase its overall biocompatibility by effectively reducing the
production of damage levels of intracellular reactive oxygen species (ROS) (Lehman et al.,
2016).
3. Chemotherapeutic agents used in treatment of cancer
An important aspect of cancer therapy is the selection of the best chemotherapeutic
agent for the specific type of cancer.
Chemotherapy proposes to silence the cancerous cells in order to completely
eradicate cancer, promoting a healthy change of life.
A variety of anticancer drugs that have been used to induce apoptosis, interfere with
the cell cycle and gene transcription and inhibit angiogenesis and, are summarized in Table
2.
Figure 5 - Chemical structures of THCPSi, TCPSi, UnTHCPSi and APTES NPs.
19
Table 2 - Main anticancer drugs used in conventional therapy
Drug Mechanism of Action Side Effects References
Doxorubicin
Intercalates with DNA.
Disrupts the topoisomerase-II-
mediated DNA repairing
mechanism, which results in cell
death.
Generates free radicals that
lead to the rupture of DNA
strands and damage of cellular
membranes and proteins.
Cardiotoxicity: iron-
related free radicals and
formation of a doxorubicinol
metabolite, and
mitochondrial disruption
that leads to apoptosis.
(Clementi,
Giardina, Di
Stasio, Mordente,
& Misiti, 2003;
Pang et al., 2013)
Paclitaxel
A mitotic inhibitor that blocks
the cells G2/M phase of the cell
cycle.
Enhances the polymerization
of tubulin to stable microtubules.
Stabilizes microtubules and
prevents their depolymerization
by cold and calcium.
Causes oxidative stress
and mitochondrial damage
after accumulation in
neuronal tissues, leading to
neuropathic pain.
(Jordan & Wilson,
2004)
Cisplatin
This platinum compound
reacts with water molecules to
obtain an unstable intermediate
that quickly interacts with DNA to
prevent cell division, resulting in
the cellular apoptosis.
Nephrotoxicity and
neurotoxicity.
Associated with cells
resistant to the drug.
(Bugarcic,
Bogojeski,
Petrovic,
Hochreuther, &
van Eldik, 2012;
Florea &
Büsselberg, 2011)
Methotrexate
The folic acid antagonist that
acts on the S phase of the cell
cycle, inhibiting the cell division.
Hepatotoxicity caused by
oxidative stress in liver
tissue.
Nephrotoxicity due to the
precipitation of the drug and
its metabolites in the renal
tubules.
(Hagag, Elgamsy,
El-Asy, &
Mabrouk, 2016;
Sayilmaz,
Karabulut, &
Ozgorgulu, 2016)
5-Fluorouracil
Pyrimidine analog that causes
an irreversible inhibition of
thymidylate synthase.
Renal toxicity.
Production of the
reactive oxygen species
(ROS) that damages the
(Longley, Harkin,
& Johnston, 2003;
Xiong et al., 2016)
20
Into tumor cells, 5-FU is
converted into fluorodeoxyuridine
monophosphate which can mis-
incorporate into DNA and RNA
chains and ultimately lead to cell
apoptosis.
kidney and induces toxic
effects such as necrosis
and apoptosis.
However, the conventional therapies are limited and have shown a variety of adverse
effects, such as high toxicity, poor tumor-specific delivery and nonspecific distribution, low
water solubility and therapeutic index, possibility to induce multidrug resistance (MDR), as
well as nausea and low counts of white blood cells are still the predominant used one (Lim,
Phua, Xu, Sreejith, & Zhao, 2016; Masood, 2016; G. B. Yang, Liu, Wu, Feng, & Liu, 2016).
The MDR is a phenotype acquired by cancer cells that confers resistance to certain
chemotherapeutic drugs, being responsible for 90% of the chemotherapeutic failure in
patients with metastatic cancer (L. Z. He et al., 2014; Huang et al., 2016).
Usually, the MDR of cancer cells is associated with the overexpression of ATP-binding
cassette (ABC) transporters, but it can also be due to other mechanisms, including
decreased drug influx, increased drug efflux, tumor proliferation driven by a small population
of self-renewing cancer cells, activation of detoxifying systems, activation of DNA repair
mechanism, avoidance of drug-induced apoptosis or activation of the immune response
(Chen, Chen, & Shi, 2014c).
Taking all of these into account, it is imperative to develop new approaches for
targeted drug delivery, in order to precisely release the chemotherapeutics in the tumor site,
and therefore, reduce the tumor recurrence, metastasis, MDR and side effects caused by
the conventional therapies (Feng et al., 2016; Y. N. Yang & Yu, 2016). In this way,
nanotechnology has emerged as an effective tool for the development of targeted drug
delivery systems employed for diagnosis, monitoring, and treatment of cancer (L. L. Li et
al., 2014).
These nanomedicines promoted an increase in the therapeutic efficacy of a large
number of anticancer drugs and reduce their toxicity profile (Lim et al., 2016; Y. N. Yang &
Yu, 2016).
In general, drug delivery systems (DDS) should be biocompatible, present high
loading/encapsulation of drug molecules without leaking the drug molecules, specificity to
a certain cell or tissue and controlled release of drug molecules that allows an effective
concentration at the target site. Furthermore, DDS can improve the solubility of poorly
water-soluble drugs, enhance the bioavailability and pharmacokinetic profiles of anticancer
21
drugs and increase the drug's half-life by reducing immunogenicity, while minimizing their
side effects (Dianzani et al., 2014).
The nanoscale dimensions of DDS can alter the drug biodistribution by accumulating
the drug at the tumor site as a result of the enhanced permeability and retention (EPR)
effect (Mo & Gu, 2016). This effect is a unique anatomical and pathological characteristic
of solid tumors, triggered by an extensive vascular permeability and insufficient lymphatic
drainage (Mo & Gu, 2016).
Other important features of a DDS rely on the ability to modify the surface of the
nanocarriers with targeting ligands for active targeting of tumor cells, as well as to achieve
a stimuli-responsive drug release through the coating with microenvironment-sensitive
molecules of the surface of the DDS (Q. J. He, Guo, Qian, & Chen, 2015).
Therefore, targeted nanomedicine therapeutics that improve the pharmacokinetic
profile and decrease the toxicity of chemotherapeutic agents can decrease the resistance
of tumors against anticancer drugs to overcome the MDR problems (Dianzani et al., 2014;
Zhu & Liao, 2015).
4. Biomedical applications of MSNs: drug delivery
The beneficial biocompatibility and biodegradability of MSNs along with the vast
surface area-to-volume ratio and pore volume makes them ideal candidates as drug
delivery vehicles (Anglin, Cheng, Freeman, & Sailor, 2008; Bimbo et al., 2010; Godin et al.,
2010; Low, Voelcker, Canham, & Williams, 2009).
The drug loading capacity has been one of the key parameters for an efficient drug
delivery system (Couvreur, 2013).
The loading and adsorption of drugs into the pores of MSNs and their release is
controlled by many factors that can be tuned in order to successfully load and release a
different kind of cargos. Among these factors are the surface area and the pore volume,
which determine the amount of drug that can potentially be loaded; and the degradation
rate of MSNs itself. Moreover, the surface chemistry which determines the physicochemical
properties of the surface of the pores and the interactions between the pore wall, to load
the drug are also important. Beyond this, there are other parameters that have an impact
on the loading of drugs into the pores of MSNs that are related to the solvent used and the
properties of the drug. The surface properties of the pores, the surface tension, and the
viscosity of the drug solution interfere with the wettability of the pores. So, low viscosity and
surface tension allow better filtration of the solvent into the pores improving the drug loading.
Furthermore, the physicochemical properties and concentration of the drugs also play a role
in drug loading into MSNs (Lehto, Riikonen, & Santos, 2014; E. C. Wu et al., 2011).
22
Drug loading within MSNs can be achieved by immersion, impregnation, or covalent
attachment, however, the most common loading method is immersion method (Salonen et
al., 2005). This method consists of the immersion of MSNs in a drug solution for a certain
period of time, usually in the range of hours, to allow the solvent to diffuse into the pores
carrying the drug which is adsorbed on the pore walls driven by geometrical and chemical
interactions. The solvent is then removed and MSNs can be carefully washed with an
appropriate solvent to remove the drug bound to the external surface. In this method, it is
required a relatively high concentration of drug solutions, being immersion method not
optimal for the loading of valuable drugs (Salonen et al., 2005).
To overcome this disadvantage, other methods can be used to incorporate drugs into
MSNs, such as impregnation or covalent attachment. In the impregnation method, the drug
solution is mixed with MSNs and the solvent is dried, forcing the diffusion of the drug into
the pores (Limnell et al., 2011; Nieto et al., 2015). Thereby, this valuable drugs may be
efficiently loaded, although the adsorption of the drug on the surface is difficult to control (J.
Salonen, A. M. Kaukonen, J. Hirvonen, & V. P. Lehto, 2008)
The drug loading can be also affected by several factors involved in the process.
These include pH dependency, temperature and time but the most important factor is the
possible chemical reactivity of the drug loading solution with the MSNs surface
(Chakraborty, Dhakshinamurthy, & Misra, 2017).
The loading solvent is chosen according to the solubility of the drug and is in several
cases water, ethanol or dimethylsulfoxide (DMSO) solutions. The solvent has the function
to drive drug molecules into the pores (Kovalainen et al., 2012).
The release assays are usually performed in buffered salt solution with fixed pH in
order to simulate the stability of the delivery system in the different stages of the oral
administration route. For targeted drug delivery it is extremely important to always test the
release with other simulating mediums, especially in plasma in order to get a wider insight
of the drug release in the complex intravenous environment (Tay et al., 2004).
5. Aims of the study
In this study, it is our intention to shift the focus of the application of the SIA
methodology to assays using MSNs and to exploit the potential of this assembly to perform
drug loading and drug release studies. While for drug loading it will be explored the
reproducible characteristics of flow systems, in the second its versatility in accommodating
different dispositives around the valve will be tested.
23
As a chemotherapeutic agent it was used 5-fluorouracil, represented in figure 6,
because is one of the most frequently used chemotherapeutic drugs in the treatment of
cancer.
5-FU acts by blocking key enzymes in nucleotide synthesis and works during the S-
phase of cell division. This chemotherapeutic drug is metabolized to 5-fluorodeoxyuridine
monophosphate (FdUMP) which, in the presence of 5, 10-methylenetetrahydrofolate,
irreversibly inhibits thymidylate synthase (TS). TS inhibition results in nucleotide pool
imbalances, impaired DNA synthesis and a reduction in DNA repair (Eynali, Khoei, Khoee,
& Esmaelbeygi, 2017; Loc et al., 2017).
Despite 5-FU potency in treating cancers, its clinical applications are limited due to its
short half-life, disease resistance, and severe side effects such as myelosuppression,
dermatitis, cardiotoxicity, neurotoxicity, nausea and vomiting which is associated with its
high non-specific in vivo distribution (Tawfik, Ahamed, Almalik, Alfaqeeh, & Alshamsan,
2017). Since 5-FU presents severe systemic assays, and a poor accumulation in tumor
tissues with a low therapeutic response rate of cancer tissues with it is administrated in high
dosage for expected efficacy (Pico, Avila-Garavito, & Naccache, 1998; Viele, 2003).
So, it is advantageous for this chemotherapeutic drug to be loaded in a NP to
overcome these drawbacks. Different functionalized MSNs were used to evaluate the
differences in their behaviour. Batch and SIA procedures were tested and compared for the
different behaviours of the MSNs towards both methodologies.
Figure 6 - Chemical structure of 5-FU.
25
1. Introduction
In this chapter, it will be reported all techniques and experimental procedures applied
in this work, including the preparation of the solutions as well as the instrumentation and
the materials.
The schematic representation of SIA systems manifold will be also exposed.
Moreover, the apparatus used in SIA systems and their mode of operation and control will
be explained.
It will be also describe the preparation of the solutions and formula of the experimental
calculations used.
2. Reagents and solutions
All solutions were prepared using ultrapure water with a specific conductance less
than 0.1 µS cm-1 and chemicals of analytical grade.
5-fluorouracil (5-FU) and methanol were purchase to Sigma-Aldrich and Chem-Lab,
respectively.
A phosphate buffer solution (PBS) 0.2 mol L-1 (pH 7.4) was used as carrier solution of
both sequential injection procedures.
The mobile phase used in HPLC consists in PBS 0.2 mol L-1 (pH 6) and methanol
(90:10, v/v).
The mobile phase of column storage consists of water mixed and methanol (50:50,
v/v).
A solution of 5-fluorouracil (5-FU) 5mg mL-1 was daily prepared through the dissolution
of 5-FU (Sigma-Aldrich) in PBS 0.2 mol L-1 (pH 7.4).
The four types of MSNs used in this study were: 3-aminopropyltriethoxysilane
(APTES), thermally hydrocarbonized porous silicon (THCPSi), thermally carbonized porous
silicon (TCPSi) and undecylenic acid functionalized thermally hydrocarbonized porous
silicon nanoparticles (UnTHCPSi).
3. Instrumentation
3.1. Auxiliary equipment
According to the required precision, the reagents were weighed in Kern (Balingen,
Germany) ABT 120-5 DM analytical balance (precision of 1×10-6 g).
26
The solutions were stirred by Labbox MAGM-005-010 magnetic stirring bar. To degas
the mobile phase solution used in HPLC a VWR® USC 100T5 (VWR International, Radnor
USA) ultrasonic bath was used.
The pH of buffer solutions was measured using a Crison® model GLP 22 milivoltimeter
(Crison Instruments, Allela, Spain) coupled to a combined Ag/AgCl glass electrode (Crison®
52-02). The calibration of the combined electrode was daily performed with commercial
standards of pH = 4.00 (Riedel-de Haën, 33543), pH = 7.00 (Riedel-de Haën, 33546) and
pH = 9.00 (Riedel-de Haën, 9889).
The temperature of release assays was controlled by a stirrer with heating IKA® C-
MAG HS7 equipped with the sensor IKA® ETS-D5 (IKA-Werke GmbH & Co., Staufen,
Germany) was employed to control temperature and continuous stirring of the 5-FU
solution.
Automatic pipettes DiscoveryPro® with maximum capacities of 100, 1000 and 5000
μL were used, and calibrated regularly. All solutions were prepared in class A glassware,
suitably washed.
In loading and release batch procedure, a stirring plate (Velp Scientifica) an HPLC
equipment (Jasco PU-4180) with a C18 column (Grace Smart RP C18 50mm x 4.6mm), a
100µL syringe (Microsyringes borosilicate glass 3.3) and a photodiode array detector
(Jasco MD-4010) were used to determine the concentration of 5-FU.
3.2. Flow Apparatus
The SIA system used in loading assays (Figure 7) consisted of a syringe module Bu1S
from Crison Instruments S.A. (Allela, Barcelona, Spain) and a 10-port multiposition
CheminertTM selection valve. A glass syringe of 5 mL total dispense volume (Hamilton
Bonaduz AG, Switzerland) was coupled to the syringe equipment and driven by a stepper
motor. Solenoid head-valves allowed the commutation of the syringe either to the manifold
or to the carrier. The communication between the computer and the modules was done
resorting to a RS232C serial protocol. The software used for the instrumental control was
developed using visual basic and communication with instruments was accomplished by
means of RS-232C asynchronous protocols, using embedded dynamic libraries. A
sequential output of the commands and evaluation of the equipment status was performed
through the implementation of the control algorithm based on the use of a set of
interdependent timers. Computer control enabled the control of flow rate, flow direction,
valve position, stop flow duration, sample, enzyme and substrate volumes, as well as data
acquisition and processing. Manifold components were connected by means of 0.8 mm i.d.
PTFE tubing, which was also used for the holding coil (2m).
27
Figure 7 - (a) Schematic representation of the SIA manifold used in loading assays. C:
carrier (phosphate buffer 0.2 mol L-1 pH 7.4), S: syringe, HC: holding coil (2m), SV: selection
valve, 5-FU: 5-fluorouracil, NPs: nanoparticles, M: loaded NPs, W: waste. (b) Sequence of
aspiration of solutions into the holding coil of the flow system: NPs and 5-FU, repeated ten
times.
The SIA system used in the release assays (Figure 8) consisted of a Crison® module
that incorporates an 8-port selection valve and a Gilson® Minipuls 3 peristaltic pump
equipped with polyvinyl chloride pumping tube of 1.30 mm i.d. The pump responsible for
the propulsion of the carrier was connected to the holding coil and through this to the central
port of the SV.
Fluorescent measurements were performed in a Jasco® FP-2020 Plus fluorescence
detector, incorporating a 16 µL flow cell that was connected to the RC2.
The excitation and emission wavelengths were set at 301 and 345 nm, respectively.
A Microsoft QuickBasic 4.5 software was applied in the control of the flow system.
The analytical signals were recorded on a Kipp & Zonen BD 111 strip chart recorder
or acquired via computer.
28
3.2.1. Aspiration/ propulsion device
The aspiration/ propulsion device used in loading SIA system was a syringe pump
module Bu1S from Crison Instruments S.A. (Allela, Barcelona, Spain) (Figure 9). The
equipment included a glass syringe, a piston and connectors of polytetrafluoroethylene
(PTFE). The device was equipped with a syringe of 5mL total dispense volume (Hamilton
Bonaduz AG, Bonaduz, Switzerland), driven to a stepper motor. Solenoid head-valves
allowed the commutation of the syringe either to the manifold tubes or to the buffer
container, depending on the position “OUT” or “IN”, respectively, independently of the
movement assumed by the piston (aspiration or propulsion). The propulsion/aspiration
operation was controlled by computer, namely the beginning and the end of the operation,
velocity and direction of solutions movement. The complete movement of the piston
corresponded to 40,000 steps. The volume corresponding to one step depended on the
capacity of the selected syringe.
Figure 8 - Schematic representation of the SIA manifold used in release assays. C: carrier
(phosphate buffer 0.2 mol L-1 pH 7.4), PP: peristaltic pump, HC: holding coil, SV: selection
valve, F: filter, S: sample, D: detector, W: waste.
29
The aspiration/ propulsion device used in release SIA system was a peristaltic pump
Miniplus 3 from Gilson® with 4 channels (Figure 10). This device is controlled by a computer
taking into account the aspiration/ propulsion time, direction and rotation speed. In this work,
it was used polyvinyl chloride (PVC) impulsion tubes (Gilson®) with an internal diameter of
1.3 mm. A proper calibration of PVC tubes was carried out before starting the experimental
work, in order to confirm the flow rates to be used in the aspiration/ propulsion of the
solutions volumes. Basically, the mass of water aspirated or propelled in a determined
period of time was weighed, at different speeds of rotation of the peristaltic pump. So, a
relation was established between the speed of rotation of the pump and the time and,
inherently, between the flow rate and the time. This relation allowed to define the volumes
to be aspirated or propelled in terms of time.
These tubes substitution was accomplished when there were alterations of the flow
rate, loss of elasticity and increase of the number of pulses.
Figure 9 - Syringe pump module Bu1S from Crison Instruments S.A.
30
3.2.2. Fluid selector valve
In loading SIA system, a 10-port multiposition CheminertTM selection valve (Valco®
Instruments, Houston, EUA) was used as fluid selection valve device to perform the loading
assay of 5-FU into the NPs. The rotor moved in a two-way mode, which enables the access
to side port by shorter route.
The selection valve had a central channel which was connected to one of the ten side
ports, managing the fluids direction. The reagents and samples were aspirated by side ports
to system (holding coil) and one of the side ports was used to connect to detector.
In release SIA system, a 8-port multiposition from Valco® (Figure 11) was used as
fluid selection valve device to perform the release assay of 5-FU. As in previous described
selection valve, the rotor and the operation of the apparatus is similar.
The rotor in both selection valves are two-way mode. It is necessary to take into
account some features of these devices, such as: the number of peripheral ports and the
number of operations to be performed, the direction of valve rotation being selected to
correspond to the smallest path between two sequential ports, as well as consider that the
presence of some ports with no purpose can decrease the sampling rate.
Figure 10 - Peristaltic pump Miniplus 3 from Gilson.
31
3.2.3. Tubing and other manifold components
The different components of the SIA system were connected with PTFE tubing
(Omnifit), with 0.8 mm internal diameter and 1.6 mm external diameter. The holding coil and
reaction tube used in the SIA systems were made with the same type of PTFE tubing in an
eight configuration to promote radial diffusion and reduce laminar diffusion of solutions
throughout the systems (Figure 12). The holding coil length ensured, simultaneously, a
minimal dispersion of solutions and no contamination of buffer solution present in the
aspiration/propulsion device.
Although all holding coils used in both SIA systems, the eight configuration used in
loading SIA system was applied to promote the efficiency of the NPs and 5-FU solution
mixture.
2 1
Figure 11 - Selector valve with 10-port multiposition from Valco®.
Figure 12 - PTFE tubing used in SIA systems (1) and PTFE tubing in an eight
configuration (2).
32
3.2.4. Informatics’ control
SIA systems require an informatics control to enable the
synchronization between the aspiration/ propulsion device and the fluids selector valve, and
thus the automatization of the system. In this work, it was used two different informatics
control.
In the SIA system used to perform the loading assays the control by computer was
based in Visual Basic software that enabled the control of analytical parameters that may
influence the performance of the flow system. The experimental conditions, previously
established in a multi column table (Figure 13), describe the valve position, speed of the
piston movement (according the time and steps selected), the time to be spent in each step
and the possibility to repeat any step previously done. The computer program also allowed
the simultaneous control of piston movement (aspiration or propulsion) and commutation of
the syringe to the manifold or to the carrier container. The commutation to the manifold or
to the carrier container was represented as “OUT” or “IN”, respectively. The direction of the
piston movement was commanded by positive steps to propel and negative steps to
aspirate.
On the other hand, SIA system where it was performed the release assays was
controlled by a specific software, named Microsoft Quick-Basic which commanded the
analytical cycle according to the data entered. With the informatic programme used it was
selected (Figure 14) the valve position, the time and flow rate that determines the volume
Figure 13 - Computer software in the SIA system where it was performed loading
assays.
33
spent, the direction of the selector valve (aspiration or propulsion) and the length of stay in
this position.
3.2.5. Detection device
In automatic loading assays it wasn’t used a detection device, however, in automatic
release assays a FP-2020 Plus fluorescence detector, from Jasco® was used (Figure 15).
This device is equipped with a 16 µL internal volume flow cell and covers a wide
wavelength range both for excitation and emission from 220 to 700 nm with proven stability.
Figure 14 - Computer software in the SIA system where it was performed release assays.
Figure 15 - Photography of fluorescence detector device.
34
4. Experimental procedure
4.1. Loading batch procedure
The drug loading is affected by several factors involved in the process. These include
pH dependency, temperature, and time, but the most vital factor is the possible chemical
reactivity of the drug loading solution with the MSNs surface. The possible chemical
reactivity of the drug loading solution with MSNs surface can change the physicochemical
properties of MSNs materials.
The loading batch procedure of the model anticancer drug, 5-FU, into the NPs, was
performed by the immersion method using concentrated aqueous solutions of the drug.
The immersion method is the most commonly loading technique used since it is a
simple process and has the possibility to be performed at room temperature. This method
follows the principle of physical adsorption of the drug molecule onto the surface of the
pores of MSNs. The charge and hydrophobicity along with the concentration of the drug
loading solution, loading time and temperature are factors that influence the drug adsorption
onto MSNs (Haidary, Corcoles, & Ali, 2012). Basically, the MSNs is dispersed into the drug
solution at a suitable concentration in a chosen solvent. After reaching equilibrium, meaning
that the loading agent fills the pores' volume, the drug-loaded MSNs can be obtained by
filtration or centrifugation. The amount of drug molecules loaded is largely determined by
the pore volume and the concentration of the drug-loading solution that can also affect the
drug-loading degree in MSNs (Jarvis, Barnes, & Prestidge, 2012).
About the procedure, firstly 5 mg of 5-FU was dissolved in 1 mL of PBS (pH 7.4).
Then, 5-FU was added to the 200 µg of NPs. After 120 min stirring (300 rpm) at room
temperature (RT) 5-FU-loaded NPs were separated from the supernatant by centrifugation
at 13,500 rpm for 5 min (supernatant 1). To remove drug molecules loosely adsorbed on
the surface of the NPs, the NPs were gently washed with 500 µL of PBS pH 7.4 (supernatant
2).
Prior to HPLC analyses, the 5-FU-loaded NPs were re-suspended in 2 mL of PBS at
pH 7.4 and stirred (300 rpm) at RT for 60 min. The suspensions were then centrifuged at
13,500 rpm for 5 min and the supernatant was used for the detection of 5-FU using an
HPLC analysis (supernatant 3).
The calculation of percentage (%) of loading of 5-FU within each NPs was made
through the following equation:
%loading= HPLC conc. (mg mL−1) × final volume
weight NPs + ( HPLC conc. × final volume) (equation 1)
35
where HPLC conc. (mg mL -1) was the concentration of the supernatant 3, the final volume
was the last volume added to 5-FU loaded NPs (2mL) and the weight NPs was the weight
of NPs used in the assay (200 µg).
Each MSN was evaluated in triplicate.
4.2. Loading sequential injection procedure
In this assay, 5mg of 5-FU was dissolved in 450 µL of PBS pH 7.4. Also, it was
withdrawn from the suspension of NPs 85 µL which were placed in 250 µL of PBS pH 7.4.
The loading sequential injection procedure of 5-FU into the NPs was performed by the
sequential aspiration of 10 aliquots of 5-FU and NPs within the flow system. After that, the
aliquots are propelled to a glass bottle, resulting in a suspension of loaded NPs in a solution
of 5-FU not loaded.
Then, 5-FU-loaded NPs were separated from the supernatant by centrifugation at
13,500 rpm for 5 min (supernatant 1). To remove 5-FU molecules loosely adsorbed on the
surface of the NPs, these were gently washed with 500 µL of PBS pH 7.4 (supernatant 2).
Prior to HPLC analyses, the 5-FU-loaded NPs were re-suspended in 2 mL of PBS at
pH 7.4 and stirred (300 rpm) at RT for 60 min. The suspensions were then centrifuged at
13,500 rpm for 5 min and the supernatant was used for the detection of 5-FU using an
HPLC analysis (supernatant 3).
The calculation of percentage (%) of loading of 5-FU within each NPs was through
the equation 1 previously defined.
Each MSN was evaluated in triplicate.
4.3. Release batch procedure
In order to perform the 5-FU release assay of the NPs, it was necessary initially to
load the drug into the NPs, using the same assay described in points 4.1 or in 4.2. However,
instead of the NPs being re-suspended in 2 ml of PBS pH 7.4 in the last step, they are re-
suspended in 5 mL. Then 100 µL aliquots of the supernatant are withdrawn from the solution
at different time points: 5, 10, 15, 20, 25, 30, 60, 120, 180 minutes.
Each MSN was evaluated in triplicate.
4.4. Release sequential injection procedure
To perform the 5-FU release assay of the NPs, it was necessary initially to load the
drug into the NPs, using the same assay described in points 4.1 or 4.2. The only difference
is that after loading NPs, they were re-suspended in 10 mL. Then, before doing the analysis,
36
it was necessary to fill the tube where the NPs were aspirated in the different time points:
5, 10, 15, 20, 25, 30, 60, 120 and 180 minutes.
Each MSN was evaluate in duplicate.
38
1. Introduction
MSNs have been established as versatile platforms for drug delivery assays. The
loading of drugs into the porous structures of these NPs is a possibility to control drug
release or deliver the ideal concentration of therapeutic molecules to the suitable location
in a controlled manner (Makila et al., 2014). The implementation of the assays in the SIA
systems was accomplished through the optimization of several physical and chemical
parameters by the univariate method, where only one parameter is changed while others
are kept constant. The optimization of the process of loading of these kind of NPs with drugs
and at the same time the monitoring of the release of the same drug is detailed and
discussed.
2. Optimization of sequential injection procedure for the loading of NPs
The mesoporous particles may present different sizes and so the first stage involved
the selection of those that could be used in order to avoid the obstruction of the flow system
tubes.
Subsequently, the optimization of the loading assay was conducted in strictly aqueous
media with the purpose of reducing the time to load 5-FU into NPs, not affecting the % of
loading normally obtained in batch assays.
Previously, it was defined the total volume of the 5-FU solution and NPs that should
be aspirated to the system so as to have a final volume of loaded NPs of 1 mL inside the
glass bottle. This guaranteed a similar final volume used in the batch studies. So, a volume
of 450 µL of 5-FU and 67 µL of NPs were aspirated to the system and then propelled to the
glass bottle with PBS pH 7.4 until the volume of 1 mL.
All the optimization of this SIA system was done with the TCPSi NPs. The loading
percentage evaluation was carried on using the batch procedure referred in point 4.3 of
Materials and Methods – Release batch procedure. The concentration values used were
obtained by the conversion of the areas obtained in HPLC using the next calibration curve
(Figure 16).
39
The calibration curve was A=5×107 (±1.2×106) C + 4×104 (± 6×104); R2= 0.9987,
where A is the area obtained in HPLC and C is the concentration of 5-FU in mg mL-1,
respectively, with 95% confidence limits for the intercept and slope.
The optimized parameters comprised the study of aspiration order of the reagents,
aspiration, and propulsion flow rate as well as the aliquots number, presented in Table 3.
Table 3 - Results of the optimization of loading assay in the flow system.
Parameter Range Selected value
Aspiration order NPs-5-FU; 5-FU-NPs NPs-5-FU
NPs aspiration flow rate 0.075 mL/min ; 0.15 mL/min 0.15 mL/min
5-FU aspiration flow rate 0.5 mL/min ; 1 mL/min 1 mL/min
Propulsion flow rate 0.5 mL/min ; 1 mL/min 0.5 mL/min
Aliquots number 5 ; 10 10
For the choice of the better conditions, it was considered into account the values of
% loading obtained in the assays and the RSD obtained. So, in the next table (Table 4) it
was described the different conditions tested and the results obtained with the average
value, standard deviation and RSD (relative standard deviation). Each condition tested was
evaluated in triplicate.
As it was previously referred, an important feature affecting system performance is
the aliquots mixing and zone homogenisation. In a SIA system these aspects are, to a great
extent, determined by the sequence of insertion (or aspiration) which dictates how the
0
1000000
2000000
3000000
4000000
5000000
6000000
0 0.02 0.04 0.06 0.08 0.1 0.12
Are
a
concentration 5-FU (mg mL -1)
Figure 16 - Calibration curve obtained in HPLC to determine the concentration of 5-FU
in loading assays.
40
different zones will mutually inter-disperse or which zone will endure a higher degree of
dispersion.
The finest results, in terms of mixing efficiency were obtained when 10 aliquots of 6.7
µL of NPs and 45 µL of 5-FU were used being the first one of the mixture of reagents was
first introduced in the holding coil followed by the sample plug, which could be explained by
the lower sample dispersion and the greater reagents zone penetration.
Table 4 – Tested conditions and respective results of the optimization of loading assay in SIA system.
Tested conditions Results (average ± standard deviation and RSD)
NPs – 5- FU 0.15 mL/min aspiration NPs 1 mL/min aspiration 5-FU 1 mL/min propulsion 10 aliquots (6.7µL and 45 µL)
3.28 ± 0.90 ; 27.55 %
5- FU - NPs 0.15 mL/min aspiration NPs 1 mL/min aspiration 5-FU 1 mL/min propulsion 10 aliquots (45 µL and 6.7 µL)
4.61 ± 2.85 ; 61.88 %
NPs – 5- FU 0.075 mL/min aspiration NPs 0.5 mL/min aspiration 5-FU 1 mL/min propulsion 10 aliquots (6.7µL and 45 µL)
5.02 ± 5.62 ; 112 %
5- FU - NPs 0.075 mL/min aspiration NPs 0.5 mL/min aspiration 5-FU 1 mL/min propulsion 10 aliquots (45 µL and 6.7 µL)
4.68 ± 2.33 ; 50 %
NPs – 5- FU 0.15 mL/min aspiration NPs 1 mL/min aspiration 5-FU 1 mL/min propulsion 5 aliquots (13.4 µL and 90 µL)
9.73 ± 2.36 ; 24.23 %
NPs – 5- FU 0.15 mL/min aspiration NPs 1 mL/min aspiration 5-FU 0.5 mL/min propulsion 10 aliquots (6.7 µL and 40 µL)
7.88 ± 0.24 ; 3.11 %
NPs – 5- FU 2.11 ± 1.11 ; 52 %
41
0.15 mL/min aspiration NPs 1 mL/min aspiration 5-FU 0.5 mL/min propulsion 5 aliquots (13.4 µL and 90 µL)
The aspiration flow rate was fixed at 1.0 ml min-1 for the 5-FU solution and 0.15 mL/min
for the NPs suspension. The propulsion flow rate towards the detector was fixed at 0.5 ml
min-1 avoiding the dilution of the final compound.
The choice of the parameters previously described has been done accordingly not
only to the % loading obtained but also to the RSD obtained. So, although the % loading
obtained with the selected parameters wasn’t the % loading best result (7.88 ± 0.24; 3.11%),
the RSD is less than the others. This is important as it assures reproducibility between the
different loadings, with non-significant differences in the three assays done.
The analytical cycle established for the optimization and implementation of loading
assay in the SIA system is presented in Table 5.
Table 5 - Analytical cycle to perform loading assay in SIA system
Step Position valve
IN/OUT Volume (mL)
Time (s)
Flow rate (mL min-1)
Repeat Step Event
1 4 i 5 22 13.6 0 0 Filling the syringe
2 4 i 1.0625 21.25 3 0 0 Partial emptying of the syringe
3 9 o 6.7×10−3 2.7 0.15 0 0 Aspiration of NPs
4 8 o 4.5×10−2 2.5 1 9 3 Aspiration of 5-FU
5 10 o 1 120 0.5 0 0 Propulsion the loaded NPs to the glass bottle
6 4 o 0 2 0 0 0 End of the analytical cycle
In each cycle, the syringe was filled completely and next it was necessary to partial
emptying the syringe to enable the aspiration of the aliquots of NPs and 5-FU afterwards.
Then, it was aspirated sequentially 10 aliquots of 6.7 µL of NPs and 45 µL of 5-FU,
respectively. After this, the flow was reversed and the loaded NPs was propelled by the
42
carrier solution to the glass bottle. The following steps are explained in point 4.2. of Materials
and Methods - Loading sequential injection procedure .
For each NP, the assay was performed in triplicate.
3. Optimization of release sequential injection procedure
To obtain the release profile using the SIA system it was used a fluorescence detector
to monitorize the 5-FU released. For that it was necessary to evaluate first the conditions
that would give a linear interval range for the drug accordingly to the concentrations
expected. So, it were selected the volume of standard solution and the flow rate used
towards the detector. Then after its connection to the release vessel apparatus and the filter
support it was necessary to evaluate again the performance of the developed flow manifold.
The sample feeding tubing was immersed into the release medium in such a way as to
restrain the occurrence of hydrodynamic disturbances and the influence of the filter support
was also studied since it could impose a resistance to the flowing stream affecting the
aspiration flow rate.
It was observed that the performance of the developed system, including the
aspiration and propelling flow rates, was unaltered and that all of the previously optimised
analytical parameters were adequate and did not require any adjustment. The release
profiles resulting from periodic measurements showed that the release of 5-FU is very fast,
requiring no more than 3 h to obtain the release profile. Sample aliquots were collected at
pre-set time intervals through an in-line filter and analysed without further treatment.
The first stage of development the automated procedure involved the adaptation of
previously described batch release assays to the SIA format. Subsequently, the
optimization of the assay was conducted in strictly aqueous media with the purpose of
simulating physiological human conditions (pH 7.4 and 37 ºC) to further apply to the release
assay of 5-FU of the NPs.
The volume necessary to fill the tube between the filter and the valve was determined
using the blue dye of bromothymol. With this dye, it was possible to acknowledge the
volume for the complete filling of the tube, since the filter holder used had a considerable
dead volume.
The optimized parameters comprised the study of the 5-FU volume aspirated to the
system, the replacement volume to the release vessel and the flow rate to the detector. The
aspiration flow rate of the 5-FU solution from the tube with the filter was stablished as 0.5
mL min -1 and the flow rate to clean the holding coil was defined as 2 mL min -1, both as a
compromise between sensitivity and sampling rate.
43
5-FU aspirated volume was studied between 100 - 300 µL and the results showed
that there is an increase of sensibility with a volume of 300 µL, as it can be seen in Figure
17.
From the graphics, it is possible to verify the relationship between the volume
aspirated and the propulsion flow rate to the detector with an increase of fluorescence
signal. Although the better combination is a volume of 300 µL with a flow rate to the detector
of 1 mL min-1, the 5-FU aspirated volume in the release assays was 200 µL as a compromise
between the sensitivity and the replacement volume of fresh solution at the end of the assay
into the release vessel.
The replacement volume was also studied. It was tested an interval between 417 µL
– 750 µL and it was selected the volume of 500 µL as it was the one that didn´t originated
a dilution in the release vessel, confirmed by the maintenance of the fluorescence signal
along the successive aliquots analysed.
Figure 17 – Volume sample and flow rate optimization in SIA system for release studies.
44
The calibration curve used to determine the concentration values of 5-FU solution is
represented in the figure 18.
Figure 18 - Calibration curve used to determine the concentration values of 5-FU obtained
in release assays.
The calibration curve was FI = 69.146 (± 8.17) C + 0.0294 (± 0.041); R2 = 0.9959,
where FI is the fluorescence intensity and C is the concentration of 5-FU in mg mL-1,
respectively, with 95% confidence limits for the intercept and slope.
So, the analytical cycle established for the implementation of release assay in the SIA
system is presented in Table 6.
Table 6 – Analytical cycle to the implementation of release assays in SIA system.
SIA valve position (1-8)
Time (s) Flow rate (mL min -1)
Direction (a/b)
Event
5 90 0.5 a Filling the tube with the filter
6 10 2 b
Cleaning holding coil 7 10 2 b 8 10 2 b
1 10 2 b
5 24 0.5 a Aspiration of 5-FU solution
4 100 1 b Propulsion to the detector
5 30 1 b Replacing clean solution to the vessel
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 0.002 0.004 0.006 0.008 0.01 0.012
FI
concentration 5-FU (mg mL -1)
45
a- aspiration and b- propulsion
In each cycle, the tube with the filter (valve position number 5) is filled with a new 5-
FU solution, corresponding to the quantity released by NPs at that time. After this, the
holding coil is cleaned during 4 steps as it was used to relieve the back pressure created in
the SIA system due to the filter. Next, 200 µL of 5-FU solution was aspirated to the holding
coil and then it was propelled to the detector and the fluorescence signal is obtained.
The last step aims not only to return the solution that was aspirated to the filling tube
between the filter and the valve to the releasing vessel and at the same time fill this tube
with fresh carrier assuring that in the next time point, there is no 5-FU solution of the
previous time point.
For each NP, the assay is performed in duplicate.
4. Determination of % loading using SIA system and batch procedure
As previously mentioned, the drug loading degree of MSNs is affected by several
properties of the material, such as hydrophilicity/hydrophobicity, pore size, surface
chemistry, load drug (charge, chemical structure, shape and molecular size) and drug
loading method. Furthermore, the drug loading is affected also by several factors involved
in the process. These include pH dependency, temperature and time. However, the most
vital factor is the possible chemical reactivity of the drug loading solution with the MSNs
surface. So, the surface properties of the NPs, the chemical nature of the drug and the drug
loading solution determine the compound affinity towards the MSNs pores (Chakraborty et
al., 2017).
Taking into account the previously mentioned, in the next table (Table 7) it is
represented the % loading values obtained with both loading methodologies.
Table 7 - Results of % loading obtained with both loading methodologies
Nanoparticles % loading
batch % loading SIA RSD (%)
APTES 11.1mg/mL 3.03 ± 0.21 2.93 ± 1.40 3.3%
UnTHCPSi 17.3mg/mL 7.13 ± 4.13 6.13 ± 2.50 14.0%
THCPSi 13.8mg/mL 2.87 ± 1.38 2.78 ± 0.56 3.1%
TCPSi 20.1mg/mL 4.55 ± 1.55 3.95 ± 2.47 13.2%
46
Considering table 7, it was possible to verify that each MSNs studied presents
different % of loading and this results can be justified taking into account the characteristics
of these NPs.
The final characteristics of MSNs obtained such as pore size shape and porosity is
directly dependent on the conditions of the synthesis. Voltage and density of the electrical
current applied to the electrodes, the concentration of HF in the electrolyte solution, the
type, doping, resistivity, and crystallographic orientation of the Si wafer, the temperature
and the time are some conditions of synthesis that affect the final characteristics of this NPs
(Salonen & Lehto, 2008).
So, taking into account the temperature used in the synthesis, UnTHCPSi, THCPSi
and TCPSi NPs have different surface properties. THCPSi NPs have hydrophobic surface
properties and TCPSi NPs have hydrophilic surface properties. UnTHCPSi and APTES NPs
have also hydrophilic surface properties (Salonen et al., 2004).
UnTHCPSi, THCPSi, and TCPSi NPs have a negative charge while APTES NPs have
a positive charge (Makila et al., 2012) and this can be justified through the chemical groups
presented in the surface of each type of MSNs used.
From the results, the differences in % of loading for this NPs can be partially ascribed
to the different chemical structures and the solubility of the 5-FU. So, the % of loading of 5-
FU is better in UnTHCPSi and TCPSi NPs because they present hydrophilic surface
properties and negative cargo, improving the affinity of 5-FU to this type of functionalized
NPs.
It was possible to observe that the results obtained by both loading methodologies
are very similar between them. Agreement between both methods was evaluated using the
t-test, carried out as a bilateral coupled test (J.C. Miller & Miller, 1993). The tabulated t value
of 3.18 when compared to the calculated t value of 2.04 showed the absence of statistical
differences for those results obtained by the methodologies at the 95% confidence level.
SIA system presents some advantages comparing with the batch procedure adopted,
being the more significant the time spent in both methodologies, since the time spent in
batch procedure was 2 h and in SIA system was about 4 minutes. These differences in time
are justified by the efficiency in mixture of NPs and 5-FU solution inside the 0.8 mm internal
diameter of PTFE tubes used in SIA system. It was also avoided the use of a magnetic
stirrer as the mixture is performed inside the system with a decrease of costs.
5. 5-FU release profiles obtained in batch procedure and SIA system
47
A major drawback limitation of the application of MSNs for the delivery of drugs is the
uncontrolled release of the loaded cargo. The release of drugs from these type of NPs is
mediated by the cleavage of the covalent bond between the MSN and the drug or by the
degradation of the Si structure (Lehto et al., 2014).
In this subchapter it will be presented the 5-FU release profiles obtained in batch
procedure and SIA system. The release profile of the 5-FU loaded in the four different MSNs
used were studied in buffer with pH value of 7.4, for simulating the physiological human
conditions.
The next figure (Figure 19) represents the release profiles in batch procedure and SIA
system when NPs are loaded using the SIA system.
From the results, it was possible to compare all the release profiles obtained using
batch procedure, all the release profiles using SIA system and to compare the release
profiles of both methodologies used.
The release profiles obtained using batch procedure (A1, B1, C1 and D1) are very
similar to each other, since the total release of 5-FU from any of the four studied
nanoparticles occurs at the end of the first 5 minutes. It was also possible to verify that at
the end of the three hours of the release assays, a stabilization of the curve of the release
profile was achieved. However, in charts B1, C1 and D1, 1 h after the start of the assay the
release curve begins to decline, perhaps due to the dilution effect of the aliquots of clean
solution added in each time point.
Now, comparing the release profiles obtained using SIA system, some differences in
release profiles arise. In the four charts (A2, B2, C2, and D2), all 5-FU loaded in the NPs
were released in the first hour of the assays, but on the chart C2 the % of release decreased
between 10 minutes and 30 minutes of the begin of the assay. On all charts except A2, 1 h
after the start of the assay the % release slightly rise. The presence of the filter may justify
these differences in profiles as there are adsorbed NPs at the filter compared to batch
procedure.
Comparing the results obtained using batch procedure and SIA system, some
differences arise when the release profiles are analysed. While in the release profiles
obtained using batch procedure (A1, B1, C1 and D1), 5-FU release is immediate (after 5
minutes), when carrying out the release assay on the SIA system, the charts B2 and C2
give the 100% release at the end of 1 h and in the charts A2 and D2 are obtained to the
end of 10 minutes. This can be justified by the use of a filter in the SIA system to retain NPs
throughout the assay that might release the 5-FU later on but also by the detection method
used in the two methodologies (HPLC in batch procedure and fluorescence detector in SIA
system).
48
Another difference, previously justified, is the behaviour of the release curve at the
end of the release assay in both methodologies. While in release profiles obtained using
batch procedure, at the end of the assay the curves begin to decline, the release profiles
obtained in SIA system, at the end of the assay the curves begin to rise.
In general and taking into account a clinical approach, this four functionalization type
and also this type of MSNs are not the best way to use in therapy because the release of
the drug occurs very quickly. A controlled drug delivery system should ensure that the drug
is gradually released over time in order to reduce the drug-related adverse effects and
decrease the number of drug administrations.
There is only one article that associates 5-FU with this type of NPs in which Pan et al.
used MSNs anchored to a hydrophilic and biocompatible poly(oligo( ethylene glycol)
monomethyl ether methacrylate) (POEGMA) and tumor targeting peptide (RGD) onto the
MSNs to load 5-FU. With this functionalization and under simulated physiological conditions
(PBS, pH 7.4, 37 ºC), ~90 % cumulative 5-FU release was observed for free 5-FU in the
first 6 h. However, only ~55 % cumulative 5-FU release was observed for 5-FU@MSN-RGD
in the same period, exhibiting controlled release characteristics. At extended time period,
the release of 5-FU gradually increased and finally reached to ~94 % at 24 h (G. Pan et al.,
2017).
So, with the different features described in the paper by Pan et al., the release profile
of 5-FU is very different from that obtained in this work. This may be justified by the different
functionalities used in both studies, where in Pan et al., this functionalization allows the
controlled release of 5-FU over time, and in our case the functionalization didn´t give the
best results proven that functionalization influences the release of 5-FU over time.
49
Figure 19 - Release profiles using SIA system for loading, where A are APTES NPs, B are
TCPSi NPs, C are THCPSi NPs, D are UnTHCPSi NPs, 1 corresponding to the release
using batch procedure and 2 corresponding to the release using SIA system.
6. 5-FU release profiles using different loading methodologies
In this subchapter, it was analysed if using different loading methods (batch or SIA)
this affect the release profile of 5-FU.
50
Initially, it was used two different NPs (APTES and UnTHCPSi NPs) which were
tested in two different conditions: in the first (1), the loading and release assays were doing
in batch and in the second one (2), the loading was doing in SIA system and the release
using batch procedure.
Looking for Figure 20, it is possible to verify that with different loading, the release
profiles obtained using batch procedure presented few differences. In the first case (A1 and
A2), the only difference is that in the first time point in A1, the % of release is close to 85%
and in A2 is close to 95%. In the second case, the release profiles are very similar to each
other.
After this comparison, it was decided to do the same assay described below but with
other NPs and other conditions.
So, it was used the other two types of NPs (TCPSi and THCPSi NPs) but here it were
tested two different conditions: in the first (1), the loading and release assays were done in
SIA system and in the second (2), the loading was done using batch procedure and the
release was done in the SIA system.
Considering the figure 21, it is possible to verify that in the first case (A1 and A2),
although the behaviour of the curves are not similar to each other, the % of release in the
first time point is close to 80%. In the second case (B1 and B2), although in B1 the third and
Figure 20 - Release profiles using different loading methodologies and batch release, where
A are APTES NPs, B are UnTHCPSi NPs, 1 corresponding to the loading and release using
batch methods and 2 corresponding to the loading in SIA system and release in batch
method.
51
fourth time points will fall slightly in comparison with the first two time points, the % of release
in the first time point in both release curves are close than 90%.
Figure 21 - Release profiles using different loading methodologies and SIA system release,
where A are TCPSi NPs, B are THCPSi NPs, 1 corresponding to the loading and release
using SIA methods and 2 corresponding to the loading in batch method and release in SIA
system.
53
In this work, two SIA methodologies were developed to study two different
approaches. An SIA system for use in loading assays was developed to improve the loading
batch procedure, with an effective decrease of time spent while getting similar results.
Another perspective was the development of an SIA system to evaluate the release profiles
of a drug from MSNs and comparing if the release profiles obtained in batch procedure are
similar to the release profiles obtained using SIA system.
The % of loading obtained in both methodologies (batch and SIA) were compared
through Student's t-test, for a 95% confidence interval, showing that there were no
significant differences between them, attesting the agreement between the two
methodologies and, consequently, confirming the use of SIA system as a valid alternative
method. The use of SIA compared to batch for loading assays led to the decrease of time
spent to 4 minutes in comparison to 2 h of batch procedure.
Concerning the release assays, and comparing the release profiles obtained in both
methodologies, when the NPs are loaded using the SIA system for loading assays, some
differences arise mainly in the % of release obtained in the first time point as well as in the
behaviour of the curve at the end of the test. However, when the NPs are loaded by different
loading methods (batch and SIA) and the release assay was done using SIA system or
batch procedure, there are no such differences in release profiles.
The fact is that this functionalized NPs aren’t the better nanosystems to use as
controlled drug delivery of 5-FU, since this chemotherapeutic agent present hydrophilic
characteristics and has more affinity for the aqueous solution in which it is dissolved than
for loading this type of NPs. However, a change in the functionalization of this MSNs with
more hydrophobic characteristics probably it would enable the use of this type of
nanosystems in the delivery of this drug, and so can be used in the clinic in order to reduce
the effects of conventional chemotherapy.
When comparing SIA methodology used in loading assays with batch procedure, this
enabling the results in a short period (4 minutes in opposite to 2 h followed by batch
procedure) and in a reproducible manner, besides its environment friendly nature due to the
low volumes spent and effluents produced. With automation, there is also the prevention of
errors associated to human manipulation and an increase of cost-effectiveness. The SIA
methodology used in release assays present all the advantages described above.
55
Al-Kindy, S. M. Z., Suliman, F. E. O., Al-Wishahi, A. A., Al-Lawati, H. A. J., & Aoudia, M.
(2007). Determination of piroxicam in pharmaceutical formulations and urine
samples using europium-sensitized luminescence. Journal of Luminescence,
127(2), 291-296. doi: 10.1016/j.jlumin.2006.12.005
Alarfaj, N. A., Aly, F. A., & El-Tohamy, M. F. (2015). Application of silver nanoparticles to
the chemiluminescence determination of cefditoren pivoxil using the luminol–
ferricyanide system. Luminescence, 30(1), 91-97. doi: 10.1002/bio.2696
Alarfaj, N. A., & El-Tohamy, M. F. (2015). A high throughput gold nanoparticles
chemiluminescence detection of opioid receptor antagonist naloxone hydrochloride.
Chemistry Central Journal, 9. doi: 10.1186/s13065-015-0083-6
Alarfaj, N. A., & El-Tohamy, M. F. (2015). Utility of gold nanoparticles in luminescence
determination of trovafloxacin: comparison of chemiluminescence and fluorescence
detection. Luminescence, 30(8), 1403-1408. doi: 10.1002/bio.2914
Alarfaj, N. A., & El-Tohamy, M. F. (2016). <bold>Eco-friendly synthesis of gelatin-capped
bimetallic Au</bold>-<bold>Ag nanoparticles for chemiluminescence detection of
anticancer raloxifene hydrochloride</bold>. Luminescence, 31(6), 1194-1200. doi:
10.1002/bio.3089
Alvarez-Berrios, M. P., Sosa-Cintron, N., Rodriguez-Lugo, M., Juneja, R., & Vivero-Escoto,
J. L. (2016). Hybrid Nanomaterials Based on Iron Oxide Nanoparticles and
Mesoporous Silica Nanoparticles: Overcoming Challenges in Current Cancer
Treatments. Journal of Chemistry, 15. doi: 10.1155/2016/2672740
Anglin, E. J., Cheng, L. Y., Freeman, W. R., & Sailor, M. J. (2008). Porous silicon in drug
delivery devices and materials. Advanced Drug Delivery Reviews, 60(11), 1266-
1277. doi: 10.1016/j.addr.2008.03.017
Bagwe, R. P., Hilliard, L. R., & Tan, W. H. (2006). Surface modification of silica
nanoparticles to reduce aggregation and nonspecific binding. Langmuir, 22(9),
4357-4362. doi: 10.1021/la052797j
Beltran-Osuna, A. A., & Perilla, J. E. (2016). Colloidal and spherical mesoporous silica
particles: synthesis and new technologies for delivery applications. Journal of Sol-
Gel Science and Technology, 77(2), 480-496. doi: 10.1007/s10971-015-3874-2
Bimbo, L. M., Sarparanta, M., Santos, H. A., Airaksinen, A. J., Makila, E., Laaksonen, T., .
. . Salonen, J. (2010). Biocompatibility of Thermally Hydrocarbonized Porous Silicon
Nanoparticles and their Biodistribution in Rats. Acs Nano, 4(6), 3023-3032. doi:
10.1021/nn901657w
Bjorkqvist, M., Paski, J., Salonen, J., & Lehto, V. P. (2006). Studies on hysteresis reduction
in thermally carbonized porous silicon humidity sensor. Ieee Sensors Journal, 6(3),
542-547. doi: 10.1109/jsen.2006.874029
Bugarcic, Z. D., Bogojeski, J., Petrovic, B., Hochreuther, S., & van Eldik, R. (2012).
Mechanistic studies on the reactions of platinum(II) complexes with nitrogen- and
sulfur-donor biomolecules. Dalton Transactions, 41(40), 12329-12345. doi:
10.1039/c2dt31045g
Chakraborty, S., Dhakshinamurthy, G. S., & Misra, S. K. (2017). Tailoring of
physicochemical properties of nanocarriers for effective anti-cancer applications.
Journal of Biomedical Materials Research Part A, 105(10), 2906-2928. doi:
10.1002/jbm.a.36141
Chen, Y., Chen, H. R., & Shi, J. L. (2014a). Construction of Homogenous/Heterogeneous
Hollow Mesoporous Silica Nanostructures by Silica-Etching Chemistry: Principles,
Synthesis, and Applications. Accounts of Chemical Research, 47(1), 125-137. doi:
10.1021/ar400091e
Chen, Y., Chen, H. R., & Shi, J. L. (2014b). Drug delivery/imaging multifunctionality of
mesoporous silica-based composite nanostructures. Expert Opinion on Drug
Delivery, 11(6), 917-930. doi: 10.1517/17425247.2014.908181
Chen, Y., Chen, H. R., & Shi, J. L. (2014c). Inorganic Nanoparticle-Based Drug Codelivery
Nanosystems To Overcome the Multidrug Resistance of Cancer Cells. Molecular
Pharmaceutics, 11(8), 2495-2510. doi: 10.1021/mp400596v
Christian, G. D. (2004). Analytical Chemistry (W. I. Edition Ed. 6th ed.).
Clementi, M. E., Giardina, B., Di Stasio, E., Mordente, A., & Misiti, F. (2003). Doxorubicin-
derived metabolites induce release of cytochrome C and inhibition of respiration on
cardiac isolated mitochondria. Anticancer Research, 23(3B), 2445-2450.
Couvreur, P. (2013). Nanoparticles in drug delivery: Past, present and future. Advanced
Drug Delivery Reviews, 65(1), 21-23. doi: 10.1016/j.addr.2012.04.010
de Souza Silva, I., Saraiva, M. L. M., Santos, J. L., & Lima, J. L. (2007). Sequential injection
spectrophotometric determination of metoclopramide in pharmaceutical
preparations. Spectroscopy Letters, 40(1), 51-61.
Dianzani, C., Zara, G. P., Maina, G., Pettazzoni, P., Pizzimenti, S., Rossi, F., . . . Barrera,
G. (2014). Drug Delivery Nanoparticles in Skin Cancers. Biomed Research
International. doi: 10.1155/2014/895986
Dickschat, A. T., Behrends, F., Surmiak, S., Weiss, M., Eckert, H., & Studer, A. (2013).
Bifunctional mesoporous silica nanoparticles as cooperative catalysts for the Tsuji-
Trost reaction - tuning the reactivity of silica nanoparticles. Chemical
Communications, 49(22), 2195-2197. doi: 10.1039/c3cc00235g
Dou, B. J., Hu, Q., Li, J. J., Qiao, S. Z., & Hao, Z. P. (2011). Adsorption performance of
VOCs in ordered mesoporous silicas with different pore structures and surface
chemistry. Journal of Hazardous Materials, 186(2-3), 1615-1624. doi:
10.1016/j.jhazmat.2010.12.051
Douroumis, D., Onyesom, I., Maniruzzaman, M., & Mitchell, J. (2013). Mesoporous silica
nanoparticles in nanotechnology. Critical Reviews in Biotechnology, 33(3), 229-245.
doi: 10.3109/07388551.2012.685860
Eynali, S., Khoei, S., Khoee, S., & Esmaelbeygi, E. (2017). Evaluation of the cytotoxic
effects of hyperthermia and 5-fluorouracil-loaded magnetic nanoparticles on human
colon cancer cell line HT-29. International Journal of Hyperthermia, 33(3), 327-335.
doi: 10.1080/02656736.2016.1243260
Feng, Y., Panwar, N., Tng, D. J. H., Tjin, S. C., Wang, K., & Yong, K. T. (2016). The
application of mesoporous silica nanoparticle family in cancer theranostics.
Coordination Chemistry Reviews, 319, 86-109. doi: 10.1016/j.ccr.2016.04.019
Florea, A.-M., & Büsselberg, D. (2011). Cisplatin as an Anti-Tumor Drug: Cellular
Mechanisms of Activity, Drug Resistance and Induced Side Effects. Cancers, 3,
1351-1371. doi: 10.3390/cancers3011351
Fraihat, S. M. (2014). A sequential injection system for spectrophotometric determination of
ketoconazole. Maejo International Journal of Science and Technology, 8(3), 232-
239.
Fu, L. M., Li, S. R., Han, Z. Y., Liu, H. F., & Yang, H. Q. (2014). Tuning the wettability of
mesoporous silica for enhancing the catalysis efficiency of aqueous reactions.
Chemical Communications, 50(70), 10045-10048. doi: 10.1039/c4cc02988g
Gibson, L. T. (2014). Mesosilica materials and organic pollutant adsorption: part B removal
from aqueous solution. Chemical Society Reviews, 43(15), 5173-5182. doi:
10.1039/c3cs60095e
Godin, B., Gu, J. H., Serda, R. E., Bhavane, R., Tasciotti, E., Chiappini, C., . . . Ferrari, M.
(2010). Tailoring the degradation kinetics of mesoporous silicon structures through
PEGylation. Journal of Biomedical Materials Research Part A, 94A(4), 1236-1243.
doi: 10.1002/jbm.a.32807
Guo, Z., Feng, S., & Fan, J. (2009). Sequential injection technique for determination of
phenoxybenzamine hydrochloride and metoclopramide in pharmaceutical
formulations. Journal of Analytical Chemistry, 64(8), 847-852.
Hagag, A. A., Elgamsy, M. A., El-Asy, H. M., & Mabrouk, M. M. (2016). Protective Role of
Silymarin on Hepatic and Renal Toxicity Induced by MTX Based Chemotherapy in
Children with Acute Lymphoblastic Leukemia. Mediterranean Journal of Hematology
and Infectious Diseases, 8, 9. doi: 10.4084/mjhid.2016.043
Haidary, S. M., Corcoles, E. P., & Ali, N. K. (2012). Nanoporous Silicon as Drug Delivery
Systems for Cancer Therapies. Journal of Nanomaterials, 15. doi:
10.1155/2012/830503
He, L. Z., Huang, Y. Y., Zhu, H. L., Pang, G. H., Zheng, W. J., Wong, Y. S., & Chen, T. F.
(2014). Cancer-Targeted Monodisperse Mesoporous Silica Nanoparticles as Carrier
of Ruthenium Polypyridyl Complexes to Enhance Theranostic Effects. Advanced
Functional Materials, 24(19), 2754-2763. doi: 10.1002/adfm.201303533
He, Q. J., Guo, S. R., Qian, Z. Y., & Chen, X. Y. (2015). Development of individualized anti-
metastasis strategies by engineering nanomedicines. Chemical Society Reviews,
44(17), 6258-6286. doi: 10.1039/c4cs00511b
He, Q. J., & Shi, J. L. (2014). MSN Anti-Cancer Nanomedicines: Chemotherapy
Enhancement, Overcoming of Drug Resistance, and Metastasis Inhibition.
Advanced Materials, 26(3), 391-411. doi: 10.1002/adma.201303123
Hu, J. J., Xiao, D., & Zhang, X. Z. (2016). Advances in Peptide Functionalization on
Mesoporous Silica Nanoparticles for Controlled Drug Release. Small, 12(25), 3344-
3359. doi: 10.1002/smll.201600325
Huang, Y. H., Cole, S. P. C., Cai, T. G., & Cai, Y. (2016). Applications of nanoparticle drug
delivery systems for the reversal of multidrug resistance in cancer (Review).
Oncology Letters, 12(1), 11-15. doi: 10.3892/ol.2016.4596
J.C. Miller, & Miller, J. N. (1993). Estadística para Química Analítica.
Jarvis, K. L., Barnes, T. J., & Prestidge, C. A. (2012). Surface chemistry of porous silicon
and implications for drug encapsulation and delivery applications. Advances in
Colloid and Interface Science, 175, 25-38. doi:
https://doi.org/10.1016/j.cis.2012.03.006
Jordan, M. A., & Wilson, L. (2004). Microtubules as a target for anticancer drugs. Nature
Reviews Cancer, 4(4), 253-265. doi: 10.1038/nr1317
Kaur, A., & Gupta, U. (2009). A review on applications of nanoparticles for the
preconcentration of environmental pollutants. Journal of Materials Chemistry,
19(44), 8279-8289. doi: 10.1039/b901933b
Kim, J., Cho, J., Seidler, P. M., Kurland, N. E., & Yadavalli, V. K. (2010). Investigations of
Chemical Modifications of Amino-Terminated Organic Films on Silicon Substrates
and Controlled Protein Immobilization. Langmuir, 26(4), 2599-2608. doi:
10.1021/la904027p
Klimundova, J., Mervartova, K., Sklenarova, H., Solich, P., & Polasek, M. (2006).
Automated sequential injection fluorimetric set-up for multiple release testing of
topical formulation. Analytica Chimica Acta, 573, 366-370. doi:
10.1016/j.aca.2006.04.012
Kovalainen, M., Monkare, J., Makila, E., Salonen, J., Lehto, V. P., Herzig, K. H., & Jarvinen,
K. (2012). Mesoporous Silicon (PSi) for Sustained Peptide Delivery: Effect of PSi
Microparticle Surface Chemistry on Peptide YY3-36 Release. Pharmaceutical
Research, 29(3), 837-846. doi: 10.1007/s11095-011-0611-6
Legnerova, Z., Huclova, J., Thun, R., & Solich, P. (2004). Sensitive fluorimetric method
based on sequential injection analysis technique used for dissolution studies and
quality control of prazosin hydrochloride in tablets. Journal of Pharmaceutical and
Biomedical Analysis, 34(1), 115-121. doi: 10.1016/j.japna.2003.08.014
Legnerova, Z., Satinsky, D., & Solich, P. (2003). Using on-line solid phase extraction for
simultaneous determination of ascorbic acid and rutin trihydrate by sequential
injection analysis. Analytica Chimica Acta, 497(1-2), 165-174. doi:
10.1016/j.aca.2003.07.007
Legnerova, Z., Sklenarova, H., & Solich, P. (2002). Automated sequential injection
fluorimetric determination and dissolution studies of Ergotamine Tartrate in
pharmaceuticals. Talanta, 58(6), 1151-1155. doi: 10.1016/s0039-9140(02)00416-2
Lehman, S. E., Morris, A. S., Mueller, P. S., Salem, A. K., Grassian, V. H., & Larsen, S. C.
(2016). Silica nanoparticle-generated ROS as a predictor of cellular toxicity:
mechanistic insights and safety by design. Environmental Science-Nano, 3(1), 56-
66. doi: 10.1039/c5en00179j
Lehto, V., Riikonen, J., & Santos, H. A. (2014). Porous silicon for biomedical applications
Cambridge: Woodhead Publishing
Li, L. L., Liu, T. L., Fu, C. H., Liu, H. Y., Tan, L. F., & Meng, X. W. (2014). Multifunctional
Silica-Based Nanocomposites for Cancer Nanotheranostics. Journal of Biomedical
Nanotechnology, 10(9), 1784-1809. doi: 10.1166/jbn.2014.1886
Li, Z. X., Barnes, J. C., Bosoy, A., Stoddart, J. F., & Zink, J. I. (2012). Mesoporous silica
nanoparticles in biomedical applications. Chemical Society Reviews, 41(7), 2590-
2605. doi: 10.1039/c1cs15246g
Lim, W. Q., Phua, S. Z. F., Xu, H. V., Sreejith, S., & Zhao, Y. L. (2016). Recent advances
in multifunctional silica-based hybrid nanocarriers for bioimaging and cancer
therapy. Nanoscale, 8(25), 12510-12519. doi: 10.1039/c5nr07853a
Limnell, T., Santos, H. A., Makila, E., Heikkila, T., Salonen, J., Murzin, D. Y., . . . Hirvonen,
J. (2011). Delivery Formulations of Ordered and Nonordered Mesoporous Silica:
Comparison of Three Drug Loading Methods. Journal of Pharmaceutical Sciences,
100(8), 3294-3306. doi: 10.1002/jps.22577
Lin, Y. H., Ren, J. S., & Qu, X. G. (2014). Catalytically Active Nanomaterials: A Promising
Candidate for Artificial Enzymes. Accounts of Chemical Research, 47(4), 1097-
1105. doi: 10.1021/ar400250z
Liu, X. Z., & Fang, Z. L. (1998). Sequential-injection system for drug-dissolution studies of
ibuprofen tablets and sustained-release formulations. Analytica Chimica Acta,
358(2), 103-110. doi: 10.1016/s0003-2670(97)00602-8
Liu, X. Z., Liu, S. S., Wu, J. F., & Fang, Z. L. (1999). Simultaneous monitoring of aspirin,
phenacetin and caffeine in compound aspirin tablets using a sequential injection
drug-dissolution testing system with partial least squares calibration. Analytica
Chimica Acta, 392(2-3), 273-281. doi: 10.1016/s0003-2670(99)00235-4
Llorent-Martínez, E. J., Šatínský, D., Solich, P., Ortega-Barrales, P., & Molina-Díaz, A.
(2007). Fluorimetric SIA optosensing in pharmaceutical analysis: Determination of
paracetamol. Journal of Pharmaceutical and Biomedical Analysis, 45(2), 318-321.
doi: http://dx.doi.org/10.1016/j.jpba.2007.05.004
Loc, W. S., Linton, S. S., Wilczynski, Z. R., Matters, G. L., McGovern, C. O., Abraham, T., .
. . Adair, J. H. (2017). Effective encapsulation and biological activity of
phosphorylated chemotherapeutics in calcium phosphosilicate nanoparticles for the
treatment of pancreatic cancer. Nanomedicine-Nanotechnology Biology and
Medicine, 13(7), 2313-2324. doi: 10.1016/j.nano.2017.06.017
Longley, D. B., Harkin, D. P., & Johnston, P. G. (2003). 5-Fluorouracil: Mechanisms of
action and clinical strategies. Nature Reviews Cancer, 3(5), 330-338. doi:
10.1038/nrc.1074
Low, S. P., Voelcker, N. H., Canham, L. T., & Williams, K. A. (2009). The biocompatibility
of porous silicon in tissues of the eye. Biomaterials, 30(15), 2873-2880. doi:
10.1016/j.biomaterials.2009.02.008
Makila, E., Bimbo, L. M., Kaasalainen, M., Herranz, B., Airaksinen, A. J., Heinonen, M., . . .
Salonen, J. (2012). Amine Modification of Thermally Carbonized Porous Silicon with
Silane Coupling Chemistry. Langmuir, 28(39), 14045-14054. doi:
10.1021/la303091k
Makila, E., Ferreira, M. P. A., Kivela, H., Niemi, S. M., Correia, A., Shahbazi, M. A., . . .
Salonen, J. (2014). Confinement Effects on Drugs in Thermally Hydrocarbonized
Porous Silicon. Langmuir, 30(8), 2196-2205. doi: 10.1021/la404257m
Manzano, M., & Vallet-Regi, M. (2010). New developments in ordered mesoporous
materials for drug delivery. Journal of Materials Chemistry, 20(27), 5593-5604. doi:
10.1039/b922651f
Martinez-Carmona, M., Colilla, M., & Vallet-Regi, M. (2015). Smart Mesoporous
Nanomaterials for Antitumor Therapy. Nanomaterials, 5(4), 1906-1937. doi:
10.3390/nano5041906
Masood, F. (2016). Polymeric nanoparticles for targeted drug delivery system for cancer
therapy. Materials Science & Engineering C-Materials for Biological Applications,
60, 569-578. doi: 10.1016/j.msec.2015.11.067
Miletto, I., Massa, A., Ugazio, E., Musso, G., Caputo, G., & Berlier, G. (2014). The protective
effect of the mesoporous host on the photo oxidation of fluorescent guests: a UV-
Vis spectroscopy study. Physical Chemistry Chemical Physics, 16(24), 12172-
12177. doi: 10.1039/c4cp01143k
Mo, R., & Gu, Z. (2016). Tumor microenvironment and intracellular signal-activated
nanomaterials for anticancer drug delivery. Materials Today, 19(5), 274-283. doi:
10.1016/j.mattod.2015.11.025
Molina-Garca, L., Crdova, M., & Ruiz-Medina, A. (2010). Sensitive determination of
indomethacin in pharmaceuticals and urine by sequential injection analysis and
optosensing. Journal of AOAC International, 93(5), 1443-1449.
Molina-Garcia, L., Llorent-Martinez, E. J., Fernandez-de Cordova, M. L., & Ruiz-Medina, A.
(2012). Fluorimetric Determination of Ketorolac in Urine by Stopped-Flow
Sequential Injection Analysis. Spectroscopy Letters, 45(3), 219-224. doi:
10.1080/00387010.2011.605197
Montalti, M., Prodi, L., Rampazzo, E., & Zaccheroni, N. (2014). Dye-doped silica
nanoparticles as luminescent organized systems for nanomedicine. Chemical
Society Reviews, 43(12), 4243-4268. doi: 10.1039/c3cs60433k
Naheid, S. A., Idris, A. M., Elgorashe, R. E. E., Altayeb, M. A. H., Alnajjar, A. O., & Assubaie,
F. N. (2013). High-throughput sequential injection assay method for chlorpromazine.
Journal of Analytical Chemistry, 68(3), 233-240. doi: 10.1134/s1061934813030106
Nieto, A., Hou, H., Moon, S. W., Sailor, M. J., Freeman, W. R., & Cheng, L. Y. (2015).
Surface Engineering of Porous Silicon Microparticles for Intravitreal Sustained
Delivery of Rapamycin. Investigative Ophthalmology & Visual Science, 56(2), 1070-
1080. doi: 10.1167/iovs.14-15997
Pan, G., Jia, T. T., Huan, Q. X., Qiu, Y. Y., Xu, J., Yin, P. H., & Liu, T. (2017). Mesoporous
silica nanoparticles (MSNs)-based organic/inorganic hybrid nanocarriers loading 5-
Fluorouracil for the treatment of colon cancer with improved anticancer efficacy.
Colloids and Surfaces B-Biointerfaces, 159, 375-385. doi:
10.1016/j.colsurfb.2017.08.013
Pan, J., & Yang, Q. W. (2007). Antibody-functionalized magnetic nanoparticles for the
detection of carcinoembryonic antigen using a flow-injection electrochemical device.
Analytical and Bioanalytical Chemistry, 388(1), 279-286. doi: 10.1007/s00216-007-
1224-0
Panda, C., Dhar, B. B., Malvi, B., Bhattacharjee, Y., & Sen Gupta, S. (2013). Catalytic signal
amplification using Fe-III(biuret-amide) -mesoporous silica nanoparticles: visual
cyanide detection. Chemical Communications, 49(22), 2216-2218. doi:
10.1039/c3cc38932d
Pang, B. X., Qiao, X. H., Janssen, L., Velds, A., Groothuis, T., Kerkhoven, R., . . . Neefjes,
J. (2013). Drug-induced histone eviction from open chromatin contributes to the
chemotherapeutic effects of doxorubicin. Nature Communications, 4, 13. doi:
10.1038/ncomms2921
Pasekova, H., Sales, M. G., Montenegro, M. C., Araujo, A. N., & Polasek, M. (2001).
Potentiometric determination of acetylsalicylic acid by sequential injection analysis
(SIA) using a tubular salicylate-selective electrode. Journal of Pharmaceutical and
Biomedical Analysis, 24(5-6), 1027-1036. doi: 10.1016/s0731-7085(00)00537-9
Passos, M. L. C., Lima, J., & Saraiva, M. (2013). Laccase-biosilica nanostructures - A
miniaturized automatic approach. Canadian Journal of Chemistry-Revue
Canadienne De Chimie, 91(2), 113-119. doi: 10.1139/cjc-2012-0193
Passos, M. L. C., Pinto, P. C. A. G., Santos, J. L. M., Saraiva, M. L. M. F. S., & Araujo, A.
R. T. S. (2015). Nanoparticle-based assays in automated flow systems: A review.
Analytica Chimica Acta, 889, 22-34. doi: http://dx.doi.org/10.1016/j.aca.2015.05.052
Passos, M. L. C., Saraiva, M., Lima, J., & Korn, M. G. A. (2008). Determination of
metoprolol, acebutolol and propranolol in pharmaceutical formulations using the
same SIA system. Journal of the Brazilian Chemical Society, 19(3), 563-568. doi:
10.1590/s0103-50532008000300027
Pico, J.-L., Avila-Garavito, A., & Naccache, P. (1998). Mucositis: Its Occurrence,
Consequences, and Treatment in the Oncology Setting. The Oncologist, 3(6), 446-
451.
Pimenta, A. M., Montenegro, M., Araujo, A. N., & Calatayud, J. M. (2006). Application of
sequential injection analysis to pharmaceutical analysis. Journal of Pharmaceutical
and Biomedical Analysis, 40(1), 16-34. doi: 10.1016/j.jpba.2005.10.006
Pinto, P., Saraiva, M., Santos, J. L. M., & Lima, J. (2005). A pulsed sequential injection
analysis flow system for the fluorimetric determination of indomethacin in
pharmaceutical preparations. Analytica Chimica Acta, 539(1-2), 173-179. doi:
10.1016/j.aca.2005.03.037
Pinto, P., Saraiva, M., Santos, J. L. M., & Lima, J. (2006). Fluorimetric determination of
aminocaproic acid in pharmaceutical formulations using a sequential injection
analysis system. Talanta, 68(3), 857-862. doi: 10.1016/j.talanta.2005.06.008
Rimola, A., Costa, D., Sodupe, M., Lambert, J. F., & Ugliengo, P. (2013). Silica Surface
Features and Their Role in the Adsorption of Biomolecules: Computational Modeling
and Experiments. Chemical Reviews, 113(6), 4216-4313. doi: 10.1021/cr3003054
Rimoldi, M., Fodor, D., van Bokhoven, J. A., & Mezzetti, A. (2013). A stable 16-electron
iridium(III) hydride complex grafted on SBA-15: a single-site catalyst for alkene
hydrogenation. Chemical Communications, 49(96), 11314-11316. doi:
10.1039/c3cc47296e
Rosenholm, J. M., Zhang, J. X., Linden, M., & Sahlgren, C. (2016). Mesoporous silica
nanoparticles in tissue engineering - a perspective. Nanomedicine, 11(4), 391-402.
doi: 10.2217/nnm.15.212
Ruzicka, J., & Gubeli, T. (1991). PRINCIPLES OF STOPPED-FLOW SEQUENTIAL
INJECTION-ANALYSIS AND ITS APPLICATION TO THE KINETIC
DETERMINATION OF TRACES OF A PROTEOLYTIC-ENZYME. Analytical
Chemistry, 63(17), 1680-1685. doi: 10.1021/ac00017a006
Ṙuz̆ic̆ka, J., & Hansen, E. H. (1975). Flow injection analyses. Analytica Chimica Acta, 78(1),
145-157. doi: http://dx.doi.org/10.1016/S0003-2670(01)84761-9
Ruzicka, J., & Marshall, G. D. (1990). Sequential injection: a new concept for chemical
sensors, process analysis and laboratory assays. Analytica Chimica Acta, 237, 329-
343. doi: http://dx.doi.org/10.1016/S0003-2670(00)83937-9
Salonen, J., Björkqvist, M., Laine, E., & Niinistö, L. (2004). Stabilization of porous silicon
surface by thermal decomposition of acetylene. Applied Surface Science, 225(1),
389-394. doi: https://doi.org/10.1016/j.apsusc.2003.10.028
Salonen, J., Kaukonen, A. M., Hirvonen, J., & Lehto, V.-P. (2008). Mesoporous Silicon in
Drug Delivery Applications. Journal of Pharmaceutical Sciences, 97(2), 632-653.
doi: https://doi.org/10.1002/jps.20999
Salonen, J., Kaukonen, A. M., Hirvonen, J., & Lehto, V. P. (2008). Mesoporous silicon in
drug delivery applications. Journal of Pharmaceutical Sciences, 97(2), 632-653. doi:
10.1002/jps.20999
Salonen, J., Laitinen, L., Kaukonen, A. M., Tuura, J., Bjorkqvist, M., Heikkila, T., . . . Lehto,
V. P. (2005). Mesoporous silicon microparticles for oral drug delivery: Loading and
release of five model drugs. Journal of Controlled Release, 108(2-3), 362-374. doi:
10.1016/j.jconrel.2005.08.017
Salonen, J., & Lehto, V. P. (2008). Fabrication and chemical surface modification of
mesoporous silicon for biomedical applications. Chemical Engineering Journal,
137(1), 162-172. doi: 10.1016/j.cej.2007.09.001
Santos, A. C. V., & Masini, J. C. (2010). A ANÁLISE POR INJEÇÃO SEQUENCIAL (SIA):
VINTE ANOS EM UMA PERSPECTIVA BRASILEIRA. Quimica Nova, 33(9), 1949-
1956.
Sarparanta, M., Makila, E., Heikkila, T., Salonen, J., Kukk, E., Lehto, V. P., . . . Airaksinen,
A. J. (2011). F-18-Labeled Modified Porous Silicon Particles for Investigation of Drug
Delivery Carrier Distribution in Vivo with Positron Emission Tomography. Molecular
Pharmaceutics, 8(5), 1799-1806. doi: 10.1021/mp2001654
Sayilmaz, A., Karabulut, Y. Y., & Ozgorgulu, A. (2016). The histopathological evaluation of
healing effects of vitamin C administered before methotrexate therapy on testicular
injury induced by methotrexate. Turkish Journal of Urology, 42(4), 235-239. doi:
10.5152/tud.2016.63903
Shahabi, S., Doscher, S., Bollhorst, T., Treccani, L., Maas, M., Dringen, R., & Rezwan, K.
(2015). Enhancing Cellular Uptake and Doxorubicin Delivery of Mesoporous Silica
Nanoparticles via Surface Functionalization: Effects of Serum. Acs Applied
Materials & Interfaces, 7(48), 26880-26891. doi: 10.1021/acsami.5b09483
Slowing, I., G. Trewyn, B., & S.-Y. Lin, V. (2006). Effect of Surface Functionalization of
MCM-41-Type Mesoporous Silica Nanoparticles on the Endocytosis by Human
Cancer Cells. J. Am. Chem. Soc., 128(46), 14792–14793. doi: 10.1021/ja0645943
Solich, P., Sklenarova, H., Huclova, J., Satinsky, D., & Schaefer, U. F. (2003). Fully
automated drug liberation apparatus for semisolid preparations based on sequential
injection analysis. Analytica Chimica Acta, 499(1-2), 9-16. doi:
10.1016/j.aca.2003.09.002
Šrámková, I., Amorim, C. G., Sklenářová, H., Montenegro, M. C. B. M., Horstkotte, B.,
Araújo, A. N., & Solich, P. (2014). Fully automated analytical procedure for propofol
determination by sequential injection technique with spectrophotometric and
fluorimetric detections. Talanta, 118, 104-110. doi:
http://dx.doi.org/10.1016/j.talanta.2013.09.059
Staden, J. F. v., & Botha, A. (1998). South Afican Journal of Chemistry, 51, 100.
Staden;, J. F. v., & Botha, A. (1998). South Afican Journal of Chemistry, 51, 100.
T. Gübeli, G.D. Christian, & Ruzicka, J. (1991). Fundamentals of Sinusoidal Flow Sequential
Injection Spectrophotometry. Analytical Chemistry, 63, 2407.
Tawfik, E., Ahamed, M., Almalik, A., Alfaqeeh, M., & Alshamsan, A. (2017). Prolonged
exposure of colon cancer cells to 5-fluorouracil nanoparticles improves its anticancer
activity. Saudi Pharmaceutical Journal, 25(2), 206-213. doi:
10.1016/j.jsps.2016.05.010
Tay, L., Rowell, N. L., Poitras, D., Fraser, J. W., Lockwood, D. J., & Boukherroub, R. (2004).
Bovine serum albumin adsorption on passivated porous silicon layers. Canadian
Journal of Chemistry-Revue Canadienne De Chimie, 82(10), 1545-1553. doi:
10.1139/v04-129
Thanasarakhan, W., Kruanetr, S., Deming, R. L., Liawruangrath, B., Wangkarn, S., &
Liawruangrath, S. (2011). Sequential injection spectrophotometric determination of
tetracycline antibiotics in pharmaceutical preparations and their residues in honey
and milk samples using yttrium (III) and cationic surfactant. Talanta, 84(5), 1401-
1409.
Tzanavaras, P. D. (2011). Automated Determination of Captopril by Flow and Sequential
Injection Analysis: A Review. Analytical Letters, 44(1-3), 560-576. doi:
10.1080/00032719.2010.500792
Vakh, C., Freze, E., Pochivalov, A., Evdokimova, E., Kamencev, M., Moskvin, L., & Bulatov,
A. (2015). Simultaneous determination of iron (II) and ascorbic acid in
pharmaceuticas based on flow sandwich technique. Journal of Pharmacological and
Toxicological Methods, 73, 56-62. doi:
http://dx.doi.org/10.1016/j.vascn.2015.03.006
Viele, C. (2003). Overview of Chemotherapy-Induced Diarrhea (Vol. 19).
Wang, F., Sun, J. H., Wang, J. P., Bai, S. Y., & Wu, X. (2014). Eu3+-modification of
luminescent hybrid bimodal mesoporous silicas with various anions (NO3-,
CH3COO-, and Cl-). Materials Chemistry and Physics, 145(3), 471-475. doi:
10.1016/j.matchemphys.2014.02.050
Wu, E. C., Andrew, J. S., Cheng, L. Y., Freeman, W. R., Pearson, L., & Sailor, M. J. (2011).
Real-time monitoring of sustained drug release using the optical properties of porous
silicon photonic crystal particles. Biomaterials, 32(7), 1957-1966. doi:
10.1016/j.biomaterials.2010.11.013
Wu, S. H., Mou, C. Y., & Lin, H. P. (2013). Synthesis of mesoporous silica nanoparticles.
Chemical Society Reviews, 42(9), 3862-3875. doi: 10.1039/c3cs35405a
Xiong, Y., Shang, B. Z., Xu, S. Y., Zhao, R., Gou, H., & Wang, C. (2016). Protective effect
of Bu-zhong-yi-qi decoction, the water extract of Chinese traditional herbal medicine,
on 5-fluorouracil-induced renal injury in mice. Renal Failure, 38(8), 1240-1248. doi:
10.1080/0886022x.2016.1209380
Yang, G. B., Liu, J. J., Wu, Y. F., Feng, L. Z., & Liu, Z. (2016). Near-infrared-light responsive
nanoscale drug delivery systems for cancer treatment. Coordination Chemistry
Reviews, 320, 100-117. doi: 10.1016/j.ccr.2016.04.004
Yang, Y. N., & Yu, C. Z. (2016). Advances in silica based nanoparticles for targeted cancer
therapy. Nanomedicine-Nanotechnology Biology and Medicine, 12(2), 317-332. doi:
10.1016/j.nano.2015.10.018
Zhao, C. X., He, L. Z., Qiao, S. Z., & Middelberg, A. P. J. (2011). Nanoparticle synthesis in
microreactors. Chemical Engineering Science, 66(7), 1463-1479. doi:
10.1016/j.ces.2010.08.039
Zhou, Z., Zheng, Y. H., & Wang, Q. M. (2014). Extension of Novel Lanthanide Luminescent
Mesoporous Nanostructures to Detect Fluoride. Inorganic Chemistry, 53(3), 1530-
1536. doi: 10.1021/ic402524z
Zhu, Y. Y., & Liao, L. M. (2015). Applications of Nanoparticles for Anticancer Drug Delivery:
A Review. Journal of Nanoscience and Nanotechnology, 15(7), 4753-4773. doi:
10.1166/jnn.2015.10298