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Pharmacokinetic Evaluation of Avicularin
Using a Model-Based Development Approach
Article in Planta Medica · March 2015
DOI: 10.1055/s-0035-1545728 · Source: PubMed
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Original Papers
373
Authors
Gabriela Amaral Buqui 1, Dayana Rubio Gouvea 1, Sherwin K. B. Sy 2, Alexander Voelkner 2, Ravi S. P. Singh 2,
Denise Brentan da Silva 1, Elza Kimura 3, Hartmut Derendorf 2, Norberto Peporine Lopes 1, Andrea Diniz 3
Affiliations
1
2
3
Key words
" avicularin
l
" pharmacokinetic
l
" translational research
l
" model‑based development
l
" pharmacognosy
l
NPPNS (Núcleo de Pesquisa em Produtos Naturais e Sintéticos), Departamento de Física e Química, Faculdade de Ciências
Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil
Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA
Departamento de Farmacia, Universidade Estadual de Maringá, Maringá, Paraná, Brazil
Abstract
!
The aim of this study was to use the pharmacokinetic information of avicularin in rats to project a
dose for humans using allometric scaling. A highly
sensitive and specific bioanalytical assay to determine avicularin concentrations in the plasma was
developed and validated for UPLC‑MS/MS. The
plasma protein binding of avicularin in rat plasma
determined by the ultrafiltration method was
64 %. The pharmacokinetics of avicularin in nine
rats was studied following an intravenous bolus
administration of 1 mg/kg and was found to be
best described by a two-compartment model using a nonlinear mixed effects modeling approach.
Introduction
!
received
revised
accepted
Dec. 11, 2014
January 21, 2015
January 29, 2015
Bibliography
DOI http://dx.doi.org/
10.1055/s-0035-1545728
Published online March 17,
2015
Planta Med 2015; 81: 373–381
© Georg Thieme Verlag KG
Stuttgart · New York ·
ISSN 0032‑0943
Correspondence
Prof. Andrea Diniz
Departamento de Farmacia
Universidade Estadual de
Maringá
Av. Colombo, 5790,
Bl. 68. Campus Universitario
Maringá, Paraná 87020070
Brazil
Phone: + 55 44 30 11 49 37
adiniz@uem.br
With an increasing awareness of a “healthy lifestyle” in todayʼs society, the consumption of nutraceutical and phytopharmaceutical supplements has also increased in the general population. This is further enhanced by media advertisement positioning these products as nonsynthetic
natural supplements. Many of the phytopharmaceuticals are phenolic compounds and among
them are flavonoids that are found in many vegetal species. With 3000 chemical structures already known for this class of phytopharmaceuticals, its development still lags behind pharmaceutical drug development in terms of utilizing tools
to enhance the understanding of the pharmacokinetic and safety properties of these compounds in
both animals and humans [1–3]. A reason could
be the lack of information on their metabolic
pathways, for example, the enzyme kinetic information of flavonoids. Most of the metabolic studies in the literature are drug-drug interactions of
these compounds with other pharmaceuticals
and very limited information is available on the
enzyme kinetic profile of the flavonoids [1]. Phar-
The pharmacokinetic parameters were allometrically scaled by body weight and centered to the
median rat weight of 0.23 kg, with the power coefficient fixed at 0.75 for clearance and 1 for volume parameters. Avicularin was rapidly eliminated from the systemic circulation within 1 h
post-dose, and the avicularin pharmacokinetic
was linear up to 5 mg/kg based on exposure comparison to literature data for a 5-mg/kg single
dose in rats. Using allometric scaling and Monte
Carlo simulation approaches, the rat doses of 1
and 5 mg/kg correspond to the human equivalent
doses of 30 and 150 mg, respectively, to achieve
comparable plasma avicularin concentrations in
humans.
maceutical drug discovery currently has many in
vitro and in silico tools at its disposal to investigate a new molecule. Adapting those available
tools in phytopharmaceutical development for
predictive purposes will be extremely valuable.
One such tool is utilizing population pharmacokinetic and allometric scaling to other species, including humans. This modeling approach can significantly improve pharmacognosy, particularly
in predicting the concentration of these plant
medicines in humans where they are used extensively in the context of traditional medicine.
Flavonoids, among the classes of phytopharmaceuticals, are one of the most consumed products
in the world, in terms of daily intake. Avicularin
" Fig. 1) is
(quercetin-3-O-α-arabinofuranoside; l
a flavone glycoside of quercetin, which was reported to be present in a variety of plant species,
including apple [4, 5], cranberry, and medicinal
plant species belonging to the Bidens and Hypericum genera [6]. Given that some of its biological
activities included suppression of lipid accumulation [7], inhibition of alpha-glicosidase [5] and
urease [8], as well as anti-inflammatory properties [9], investigators have proposed the potential
Buqui GA et al. Pharmacokinetic Evaluation of …
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Pharmacokinetic Evaluation of Avicularin Using a
Model-Based Development Approach
Original Papers
Fig. 1 Chemical structure of avicularin and
coumarin (internal
standard).
case, avicularin is a maker compound that is representative of
the aggregate activities of the extract.
In this study, we developed a bioanalytical method for avicularin,
which was prospectively used to quantify avicularin concentration-time profiles in rats. The pharmacokinetics of avicularin in
the rat was then characterized using a population pharmacokinetic approach. Its pharmacokinetic information was further utilized to extrapolate avicularin concentrations in humans using
allometry. This study represents an important shift in the development paradigm of phytopharmaceutical products to a more
structured and cost-effective model-based development approach.
Results
!
application of this compound for disease prevention. In phytopharmaceutical therapy, patients are administered medicinal
products containing either a single herbal extract or a combination of different extracts. The quantification of dose and dose optimization are considerably more difficult in this setting. One
methodology to quantify dose or exposure is to develop the relationship between pharmacodynamic effects and the pharmacokinetic of one or more compounds, which are called marker compounds. Therefore, marker compounds need to represent the
whole extract or the aggregate activities of the extract. In this
Fig. 2 Representative chromatograms of avicularin (1.41 min) and coumarin (1.81 min). A Blank rat plasma, B plasma spiked with IS in LLOQ, C plas-
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
The selectivity of the bioanalytical assay was evaluated by comparing the chromatograms of blank plasma, blank plasma spiked
with avicularin, and a rat plasma sample after intravenous ad" Fig. 2). The results showed
ministration of avicularin 1 mg/kg (l
that there was no endogenous interference of the matrix at the
retention times of avicularin and coumarin (IS).
The calibration curves of the peak area to the concentration were
constructed using a 1/x weighted linear regression model. The
calibration curves were prepared daily and showed good linearity in the corresponding range for avicularin (R2 > 0.996). The
current assay resulted in an LLOQ of 25 ng/mL for avicularin in
the plasma, which was considered adequate for the study of
pharmacokinetics following a single intravenous administration
ma spiked with avicularin, D, E plasma obtained after 15 min of the intravenous administration of avicularin (1 mg/kg) to rats.
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374
Original Papers
QC Avicularin conc. (ng/mL)
ME (%)
RE (%)
25
50
750
1500
108.8
125.4
123.6
117.2
105.2
107.5
114.2
110.2
375
Table 1 Matrix effect (ME) and
extraction recovery (RE) of avicularin in plasma samples. Reported
values are means from a total of
n = 5 per concentration.
Table 2 Precision and accuracy for determination of avicularin in rat plasma. Reported values are means from a total of n = 5 per concentration.
25
50
750
1500
Intraday
Interday
Precision (RSD, %)
Accuracy (mean, %)
Precision (RSD, %)
Accuracy (mean, %)
4.9
7.9
0.8
3.9
100.2
96.4
101.7
93.4
8.1
5.5
1.3
0.3
105.0
98.6
100.9
95.5
Table 3 Stability of avicularin in plasma samples. Reported values are means from a total of n = 5 per concentration.
QC avicularin conc. (ng/mL)
50
750
1500
Post preparative stability (24 h)
Long-term stablity (1 week)
Short-term stability (4 h)
Precision
Accuracy
Precision
Accuracy
Precision
Accuracy
(RSD, %)
(mean, %)
(RSD, %)
(mean, %)
(RSD, %)
(mean, %)
6.7
5.8
2.5
106.3
104.2
99.5
2.8
1.2
3.4
106.8
96.2
103.9
3.1
2.7
1.5
98.9
101.7
102.4
of avicularin (1 mg/kg). The extraction recovery and matrix effect
" Table 1. The results from the
data of avicularin are shown in l
study of the matrix effect showed that an ionization enhancement (> 100 %) was present, but no significant differences
between the matrix effect in the various concentrations were
found. Thus, the matrix effect for avicularin was not considered
significant. The data from the recovery study indicated that the
sample preparation method was satisfactory and resulted in no
appreciable matrix effect.
The validation results showed that the accuracy and precision of
this method were 95.5 to 105 % and 0.3 to 8.1 %, respectively, as
" Table 2. The evaluation of the assay for accuracy and
shown in l
precision in rat plasma indicated that this analytical method was
accurate and reproducible. Therefore, the analytical method using UPLC‑MS/MS was highly sensitive, specific, and suitable for
the pharmacokinetic study of avicularin in rats.
" Table 3) showed that the differences
The stability evaluation (l
were between 96.2 and 106.8 % of the original concentrations,
which were well within the 20 % relative standard deviation.
Short-term and long-term stabilities demonstrated no significant
degradation over all concentrations tested, as well as for postpreparative stability. These data indicated that avicularin was stable in the plasma for at least a week.
" Table 4. For the
Plasma protein binding results are shown in l
two higher concentrations (750 and 1500 ng/mL), the protein
binding was the same, around 69 %, but for the lower concentration (50 ng/mL), this proportion was significantly different (53 %),
suggesting a nonlinear protein binding effect. Given that plasma
protein binding has an impact on the drug pharmacokinetics and
drug-drug interactions, the plasma protein binding of avicularin
in the rat was evaluated to be 64 % using the ultrafiltration method; consequently, the free drug component of avicularin is approximately 36%.
Total plasma concentrations collected from rats after 1 mg/kg administration of avicularin were analyzed using the validated bio-
Table 4 Plasma protein binding of avicularin in the concentrations of 50, 750,
and 1500 ng/mL (n = 3 per concentration).
Concentration (ng/mL)
Protein binding (%) (mean ± SD)
50*
750
1500
53.2 ± 3.0
68.5 ± 0.6
69.8 ± 1.0
* p < 0.019
analytical assay described above. The pharmacokinetics of avicularin is best described by a two-compartment body model. There
is good agreement between the model-predicted concentrations
" Fig. 3). Conditional weighted
and the observed concentration (l
residuals were within the − 2 to 2 unit ordinate. The parameters
" Table 5.
of the population pharmacokinetic model are shown in l
Given that avicularin was dosed on the basis of body weight, the
estimated parameters were centered on the body weight of 230 g,
which was the median body weight of the nine rats. Avicularin is
rapidly cleared from the systemic circulation with a clearance of
17.1 mL/min; the volumes of distribution for the central and peripheral compartments were 200 and 760 mL, which translate to
a volume at steady state of 960 mL (VSS = VC + VP). The large volume of distribution indicates the likely distribution into the tissues. The corresponding half-lives were 3.3 and 59 min for the
α- and β-phases of the biexponential decline, respectively. The
ωP, which represents the approximate coefficients of variation
for the interindividual variability for CL, Q, and VC were 20, 49
and 32 %, respectively.
The accuracy of the final model was evaluated by a posterior visual predictive check from the simulation of 500 profiles from the
" Fig. 4).
rat population with the same body weight distribution (l
Bootstrap-estimated 95 % confidence intervals of the parameters
" Table 5).
contained the population mean values (l
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QC avicularin Conc. (ng/mL)
Original Papers
Fig. 3 Goodness-of-fit plot for the avicularin population pharmacokinetic model in rats.
Parameter
Structural model parameters
Volume of central compartment (VC; mL)
Volume of peripheral compartment (VP; mL)
Systemic clearance (CL; mL/min)
Intercompartmental clearance (Q; mL/min)
Interindividual variability
% CV of VC(ωVc)
% CV of CL (ωCL)
% CV of Q (ωQ)
Residual variability
Proportional residual error
Mean
RSE (%)
Median (95 % CI)*
200
760
17.1 (1.03 L/h)
23.3 (1.40 L/h)
25
17
9.9
16
205 (121, 321)
734 (478, 1124)
17.2 (14.5, 20.9)
22.1 (16.1, 30.0)
58
33
39
0.20
49
20
32
6
Table 5 Population pharmacokinetic estimated parameters of avicularin after intravenous administration (1 mg/kg) in rats (n = 9).
50 (8.6, 88)
30 (8.2, 47)
36 (15, 57)
0.19 (0.13, 0.25)
RSE, relative standard error; % CV, coefficient of variation values were obtained by taking the square root of the diagonal values of the
NONMEM omega (variance-covariance) matrix and multiplying by 100 %; * Median (95% CI) determined from 500 bootstrap resampling
procedures
For the purpose of scaling to larger animals including humans,
the allometric power coefficients were set to 0.75 and 1 for clearance and volume parameters, respectively. The mean pharmacokinetic parameters of avicularin in humans, assuming an average
body weight of 70 kg, were 309 L/h, 423 L/h, 64 L, and 245 L for CL,
Q, VC and VP, respectively. From equation 3, the estimated doses
in humans were 30 mg and 150 mg, which resulted in a comparable maximum concentration to that in the rats after 1 mg/kg and
" Table 6). The maximum concentration after 5 mg/kg
5 mg/kg (l
avicularin in the rat was obtained from Zhang et al. [10], which
" Fig. 5),
was 2324 ± 423.7 ng/mL. The extrapolation to humans (l
using allometry, indicates that avicularin is rapidly cleared. A
drop to 10 % of the initial concentration was predicted within
" Table 6).
the first half hour of administration (l
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
Discussion
!
After a single intravenous bolus administration of 1 mg/kg avicularin in rats, the plasma avicularin concentration decreased rapidly from approximately 700 ng/mL to less than 200 ng/mL in
10 min and reached approximately 100 ng/mL after an hour. This
biphasic concentration-time profile, which was observed in all
rats, was best characterized by a two-compartment pharmacokinetic model. The pharmacokinetic analysis showed that avicularin was rapidly cleared from the systemic circulation in rats. The
rapid clearance of 17.1 mL/min is much faster than the rat glomerular filtration, which is 1.8 mL/min [11], indicating the possibility of conversion to an active metabolite or several other metabolites. A study showed that human intestinal bacteria could
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376
Original Papers
377
Fig. 5 Prediction of plasma concentrations (mean
[line] and 95% prediction interval [shaded area]) in
70 kg humans based on allometric scaling after a
30-mg (light grey) and 150-mg (dark grey) single
dose of avicularin in both linear (left) and semi-log
(right) scales.
Dose (mg)
30
150
Post-dose time (h)
Median (ng/mL)
Min, max (ng/mL)
0
0.5
1
4
0
0.5
1
4
509
34.5
22.9
3.0
2540
173
115
15.2
287, 1010
14.1, 67.4
8.7, 49.8
0.5, 10.0
1440, 5050
70.4, 337
43.5, 249
2.7, 50.0
metabolize avicularin, and six metabolites were previously identified, including aglycone quercetin, quercetin-3-O-rhamnoside,
quercetin-3-O-glucoside, and quercetin-7-O-glucoside [12]. It is
still unclear whether these metabolites of avicularin are present
in rats or humans. More studies are required to elucidate the
metabolic pathway of avicularin in animals and humans.
The peak concentration after intravenous bolus administration of
a 1 mg/kg dose of avicularin in our study was proportional to that
observed in the study of Zhang et al. using a 5 mg/kg avicularin
dose [10]. The β-phase half-life of approximately 1 h from this
study was consistent with the terminal half-life of 0.75 ± 0.09 h
reported previously [10]. The rapid clearance of avicularin could
also indicate a rapid tissue distribution. The volume of distribution of avicularin in the rat was very large at 960 mL, which trans-
Table 6 Summary statistics of simulated human avicularin concentrations after intravenous administration of 30 mg and 150 mg avicularin from 500 simulated profiles
assuming a human body weight of
70 ± 5 kg.
lated to approximately 4.2 L/kg, given that the plasma volume of
the rat was only 0.03 L/kg [13]. The 150-fold difference suggested
an extensive distribution out of the plasma or the systemic circulation. Such a fold difference in the volume of distribution is not
uncommon. One example is largazole-thiol, which is a potent
histone deacetylase inhibitor derived from marine cyanobacterium and was shown to have a volume of distribution of 26.7 L/
kg in the rats [14].
We had attempted using a “buttom-up” approach with a physiologically based pharmacokinetic model to predict human exposure [15]. However, due to the lack of information on the human
metabolism of avicularin and the relative concentrations in the
various organs, we elected to use allometric scaling instead. The
allometric scaling approach compensates for the fact that larger
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Fig. 4 VPC plot for the avicularin plasma concentration population model in linear (left) and semilog scales (right), where the observed data are the
circles, the median is a solid line, and 2.5th and
97.5th percentiles of the prediction intervals are
dashed lines. The lighter grey shade represents the
90 % confidence interval of the median and the
darker grey shades are the 90 % confidence intervals
of the 2.5th and 97.5th percentiles.
Original Papers
animals normally have a slower metabolic rate and would require a lesser dose based on body weight compared to smaller
animals [16–19]. We utilized the mathematical power law expression
weight b
Y ¼að
Þ
median
where Y is the parameter of interest, weight refers to body weight
normalized by the median, a is the median weight-centered parameter value, and b is the allometric exponent) [20, 21]. Using
the allometric exponent of 0.75 for clearance relationship to body
weight is similar to scaling by body surface area since body surface area increases by a power of 0.75 in relation to weight increase. Similarly, the extrapolated dose in humans was increased
by the proportion of human weight to the rat weight to the same
power exponent to account for scaling by body surface area. The
simulation in humans indicated that avicularin was rapidly
cleared from the systemic circulation within the first half hour
of administration. We also showed that a 30- to 150-mg dose in
humans, assuming an ideal body weight of 70 kg, would result in
a similar exposure to that of a 1- to 5-mg/kg dose in rats. The simulated initial median concentration of 2540 ng/mL in humans
after a 150-mg dose was close to that reported for the maximal
concentrations of 2324 ± 423.7 ng/mL in rats administered a single dose of 5 mg/kg avicularin [10].
There are limitations to the allometric scaling approach as this
approach was previously shown to perform poorly for interspecies scaling, even after several types of correction [19, 22, 23].
One of the primary reasons is because of the significant differences in metabolic pathways and enzymatic activities between
species. Sharma and McNeil described properties of drugs that
may not be amenable to allometric scaling, including drugs that
are highly protein bound, drugs that undergo extensive metabolism and active transport, drugs that undergo significant biliary
excretion or renal secretion, drugs whose target are subject to
significant interspecies differences, and biological drugs that exhibit target-binding effects [16]. Wojcikowski and Gobe discussed the limitations of extrapolation to humans from animal
studies, not only from the pharmacokinetic perspective but from
pharmacodynamics and safety as well [17].
Avicularin could potentially exhibit extensive metabolism, given
that its clearance in the rat is much higher than the glomerular
filtration rate in the rat. Allometric scaling is the preferred choice
for scaling to human equivalent doses in the absence of information on the metabolic pathway of avicularin. Avicularin metabolic
information could potentially allow one to develop a physiologically based pharmacokinetic model and use the model for interspecies scaling. Another limitation of the study is that the simulations assuming intravenous administration may not realistically reflect the preferred route of administration in humans as
extracts containing avicularin are commonly taken via the oral
route. The difference in the route of administrations adds another
layer of complexity, as it is not known whether avicularin is a
substrate of intestinal transporters.
Extracts containing avicularin are already widely ingested in Brazilian traditional medicine as an herbal remedy for various ailments including inflammation. A recent study showed that avicularin suppressed adipogenesis using 3T3-L1 cells and demonstrated that this suppression occurred through the inhibition of
the CCAAT/enhancer-binding proteins (C/EBP alpha-activated)
GLUT4-mediated insulin-responsive glucose transporter, which
mediates glucose uptake [7]. The inhibitory concentration is re-
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
ported at 50 µM, which is approximately 22 ng/mL. In another
study, the anti-inflammatory properties of avicularin were
shown to be mediated by suppression of the secretion of proinflammatory cytokine IL-1β and also attenuated the activation of
the ERK signaling pathway and the degradation of Iκβ [9].
A study by Dost et al., who investigated the effect of a Hypericum
(St. Johnʼs wort) extract on the inflammatory and immune response in rats with induced inflammatory bowel disease [24],
have shown that the low human equivalent dose that some benefits corresponds to the low dose in rats. Their study indicated
that the beneficial effects observed in animals might be relevant
to humans at relatively low doses. Their study showed the value
of extrapolation to a human equivalent dose in the absence of any
information on humans in order to design the low dose in humans that was reasonably safe.
In this study, we utilized model-based development to extrapolate a dose in humans for avicularin with the pharmacokinetic information in rats. This approach is suitable for the extrapolation
of a human equivalent dose. We also noted that this approach using allometric scaling has its shortcomings, including some documented poor predictability across species due to significant differences in metabolic pathways and enzyme activities between
species [22]. This approach, nonetheless, brings us closer to
understanding the dose requirement in humans to achieve pharmacological effects.
Materials and Methods
!
Chemical reagents
Avicularin was isolated from the aerial parts of Bidens sulphurea
(Cav.) Sch. Bip. (Asteraceae) and purified in our laboratory with a
purity of 93.3 % [25, 26]. The structure was confirmed by comparing high-resolution mass spectrometry, and 1H and 13C nuclear
magnetic resonance data with previously reported data [5, 27].
Coumarin, as an internal standard (IS), was purchased from Sigma-Aldrich with a purity of 98 %.
Analytical studies
Chromatographic analysis was performed on an Acquity UPLC
system (Waters Corp.), and the separation was performed at 40 °
C using a Waters Acquity C 18 BEH column (2.1 mm × 50 mm,
1.7 µm) with a linear gradient elution, using water (containing
0.1 % acetic acid) and acetonitrile (containing 0.1% acetic acid) as
the mobile phase.
The elution program was as follows: 10 % (initial), 10–40 %
(1 min), 40–100 % (2.5 min), 100 % (3 min), and 100–10% (5 min)
acetonitrile with 0.1 % acetic acid. The flow rate was 0.3 mL/min,
the injection volume was 5 µL, and the autosampler temperature
was set to 20 °C.
Mass spectrometry detection was performed using a TQ detector
(Waters Corp.) equipped with an electrospray ionization (ESI)
source. Nitrogen was used as the desolvation gas (600 L/h) and
as a cone gas (50 L/h). For collision-induced dissociation, argon
was used as the collision gas at a flow rate of 0.15 L/h. The capillary voltage was set to 2.5 kV, the source temperature to 150 °C,
and the desolvation temperature to 350 °C. The cone voltage and
collision energy were optimized for each compound: 32 kV and
18 eV for avicularin, and 20 kV and 25 eV for IS, respectively.
Quantification was performed using multiple reaction monitoring and with the transitions of m/z 433 → 301 for avicularin and
m/z 147 → 91 for IS. The negative ESI mode for avicularin and pos-
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378
Original Papers
matrix effect (%) = B/A · 100 and recovery (%) = C/B · 100
Intraday precision was tested by analysis of the QC plasma samples at four concentrations (n = 5 for each concentration) in the
same day. Interday precision (n = 5 per concentration) was determined by repeated analysis of the QC samples over three consecutive days. The concentrations were calculated from the corresponding calibration curve. The relative standard deviation and
percentage difference between the amount spiked and determined were taken as the measures of precision and accuracy.
The stability studies were performed by evaluating the QC samples in three different conditions at concentrations of 50, 750,
and 1500 ng/mL of avicularin. Short-term stability was carried
out with samples at room temperature for 4 h. Post-preparative
stability was evaluated on the samples waiting for injection in
the autosampler at 20 °C for 24 h. Long-term stability was studied
by assaying samples following a period of one week of storage at
− 80 °C. The results were expressed by the precision and accuracy
obtained and compared with the initial content of avicularin in
the freshly treated samples.
Plasma protein binding
Protein binding of avicularin was evaluated in rat plasma at the
concentrations of 50, 750, and 1500 ng/mL using an ultrafiltration method as previously described [30]. The avicularin plasma
was incubated at 37 °C for 30 min, then the plasma containing the
drug was loaded onto the Centrifree Ultrafiltration Device (Millipore Corp.), and the filtrate device was centrifuged at 2000 × g for
25 min at 25 °C. The total drug before centrifugation and the free
drug present in the filtrate were assayed by direct injection into
the UPLC‑MS/MS, and the results were compared.
Pharmacokinetic studies in rats
Male Wistar rats, weighing 230 ± 20 g, were provided by the Central Animal Facility of the University of São Paulo, Ribeirão Preto,
Brazil. This study was approved by the Animal Use Ethics Committee (protocol number 058/2012). Nine male Wistar rats were
used in this study and had free access to water and food. The avicularin (1 mg/kg) solution was prepared in saline containing 1 %
DMSO and was administered to the rats by intravenous bolus administration via the left tail vein. 200 µL serial blood samples
were drawn in heparinized polythene microtubes from the right
tail vein at the following post-dose time points: 3, 6, 10, 15, 25,
35, 45, and 60 min. Samples were immediately centrifuged at
2000 × g for 5 min at room temperature, and the plasma was removed and stored at − 80 °C until analysis by UPLC‑MS/MS.
Population pharmacokinetic model
The final structural model was a two-compartment body model
assuming IV bolus administration, parameterized on clearance
(CL), intercompartmental clearance (Q), volumes of distribution
of the central (VC), and peripheral compartments (VP). Exponential interindividual variability terms were included in the pharmacokinetic parameters CL, Q, and VC.
Pi = P × exp (ηi)
(1)
where P represents the population mean and ηi describes the interindividual variability, which was assumed to be independently
and normally distributed with zero mean and variance ωP2. In order not to confound mixed interindividual variability to parameters VP and VC, no interindividual variability was included in the
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
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itive mode for IS were applied. All analyses were performed using
MassLynx V 4.1 Software (Waters Corp.)
" Fig. 1) due to the absence of enThe IS of choice was coumarin (l
dogenous interference and its improbable presence in the plant
material used for the extraction of avicularin. Furthermore, the
main reason for this choice was that its chromatographic behavior and extraction efficiency were similar to those of avicularin. A
UPLC‑MS/MS analytical method for avicularin was developed independently of the current method and utilized carbamazepine
as their internal standard [10]. Their chromatographic conditions
were different from the ones used in the current study.
Individual stock solutions of avicularin (400 µg/mL) and IS (2 mg/
mL) were accurately prepared in volumetric flasks, dissolved
with acetonitrile : water (80 : 20 v/v). The stock solutions were serially diluted in order to get the standard working solutions with
the desired concentrations. All stock solutions were stored at 4 °
C. Working solutions were prepared immediately before use.
For the stability analysis, quality control (QC) samples of four
concentrations at 25, 50, 750, and 1500 ng/mL were prepared in
plasma. QC samples were stored at − 80 °C until analysis.
For the sample preparation, 100 µL of the IS solution at 0.5 µg/mL
in acetonitrile were added to 100 µL of the rat plasma sample. To
this mixture, 100 µL of hexane were added. After vortexing for
2 min, the samples were centrifuged at 2140 × g and 4 °C for
15 min. After this process, 5 µL of the supernatant liquid was injected onto the column.
Selectivity was assessed by analyzing blank plasma samples from
six sources, blank plasma samples spiked with avicularin and IS,
and rat plasma samples after intravenous administration of avicularin; interfering substances in the biological matrix were
monitored as well.
An aliquot (50 µL) of appropriate avicularin standard working solution was spiked into the blank plasma samples to give concentrations of 25, 50, 100, 250, 500, 750, 1000, 1500, and 2000 ng/
mL. An aliquot of 50 µL of IS solution (0.5 µg/mL) was added to
all spiked samples, and then the sample solutions were prepared
and analyzed as described above. The results were fitted to linear
regression analysis using 1/x as the weighting factor. The concentration of avicularin in the plasma was directly calculated from
the corresponding calibration curve.
The lower limit of quantification (LLOQ) was defined as the lowest avicularin concentration that could be determined with an accuracy of 80–120 % and precision of 20%, and the analyte response 5 times greater than the response of the blank.
Recovery and the matrix effect were measured for LLOQ, and
low-, medium-, and high-concentration QC samples (25, 50, 750,
and 1500 ng/mL). The blank biological matrix was prepared without the addition of any standard. The extraction recovery was determined by comparing the analyte/internal standard peak area
ratios obtained from extracted plasma samples with those originally dissolved with the biological matrix extract.
The matrix effect was determined by comparing the analyte/internal standard peak area ratios dissolved with the blank matrix
extracted against those dissolved only with acetonitrile : water
(80 : 20 v/v). The ion suppression of the analytes was evaluated
[28, 29]. Each test was measured in triplicate.
The matrix effect and recovery of the extraction procedure were
measured by comparing the absolute peak areas obtained in the
solution standard (A), the corresponding peak areas for standards
spiked after extraction into plasma extracts (B), and the peak
areas for standards spiked before extraction (C), so the matrix effect and recovery values can be calculated such that
379
Original Papers
VP term. The subscript i represents the individual. The residual
variability was characterized by a proportional model.
The allometric size adjustment by weight was centered on
0.23 kg, which was the median weight of the rats. The relationship between body weight and parameters are described by the
following equation:
Acknowledgements
!
This work was supported by a scholarship from CNPq 136 255/
2011–6 and grants from FAPESP 2014/50 265–3 and INCT‑if.
Conflict of Interest
weight Þx
Pi ¼ Pð
median
!
(2)
where weight is the weight of the individual rat, and median is
the median weight of the study population; x is the power coefficient which was fixed to 0.75 for the clearance (both CL and Q)
and 1 for the volume of distribution (both VC and VP) parameters.
The same equation was used for the prediction of CL, Q,Vc, and Vp
in humans where the human body weight of 70 ± 5 kg (mean ±
SD) is used for the weight parameter.
The predictability of the final model was evaluated using the visual predictive check wherein plasma concentration-time profiles were simulated in 500 replicates using the final population
pharmacokinetic model. The median and 95% prediction interval
of the time course of avicularin plasma concentrations were computed and overlaid with the observed data to evaluate the predictive performance of the final model. The majority of the individual observations should be enclosed within the 2.5th and 97.5th
percentiles of the simulated data if the final model adequately
describes the original data. The 90 % confidence interval of the
prediction interval was generated based on a bootstrap procedure as previously described [31].
The model stability was evaluated by a bootstrap resampling
technique with 500 bootstrap procedures. Parameter uncertainty
was assessed by comparing the model parameter estimates with
the posterior distribution of the bootstrap estimates; the 2.5th
and 97.5th percentiles of the parameter estimates from the posterior distribution from the bootstrap estimates were used.
The population pharmacokinetic model of avicularin in rats was
developed using a nonlinear mixed effects model with a first-order conditional maximum likelihood estimation η-interaction in
NONMEM (version VII.2) and an NM-TRAN preprocessor (ICON
Development Solutions). The subroutine was ADVAN3 TRANS4.
The models were run using G-Fortran 95. Bootstrap resampling
and the visual predictive check were performed with Perlspeaks-NONMEM 3.5.5 running ActivePerl 5.12 (ActiveState)
and Xpose4 package in R 3.1.0.
Allometric scaling to humans
The doses for the simulations in humans were determined by the
following equation:
Weighthumans 0:75
Dosehumans ¼ ð
Þ Doserats
Weightrats
(3)
Where Dosehumans refers to the estimated dose in humans;
Doserats refers to the dose in rats; Weighthumans is the average
weight in humans; and Weightrats is the median rat weight of
0.23 kg. The human weight used in the simulation was 70 ± 5 kg.
A total of 500 concentration-time profiles were simulated.
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
There is no conflict of interest among the authors.
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Original Papers
Pharmacokinetic Evaluation of Avicularin
Using a Model-Based Development Approach
Article in Planta Medica · March 2015
DOI: 10.1055/s-0035-1545728 · Source: PubMed
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Original Papers
373
Authors
Gabriela Amaral Buqui 1, Dayana Rubio Gouvea 1, Sherwin K. B. Sy 2, Alexander Voelkner 2, Ravi S. P. Singh 2,
Denise Brentan da Silva 1, Elza Kimura 3, Hartmut Derendorf 2, Norberto Peporine Lopes 1, Andrea Diniz 3
Affiliations
1
2
3
Key words
" avicularin
l
" pharmacokinetic
l
" translational research
l
" model‑based development
l
" pharmacognosy
l
NPPNS (Núcleo de Pesquisa em Produtos Naturais e Sintéticos), Departamento de Física e Química, Faculdade de Ciências
Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil
Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA
Departamento de Farmacia, Universidade Estadual de Maringá, Maringá, Paraná, Brazil
Abstract
!
The aim of this study was to use the pharmacokinetic information of avicularin in rats to project a
dose for humans using allometric scaling. A highly
sensitive and specific bioanalytical assay to determine avicularin concentrations in the plasma was
developed and validated for UPLC‑MS/MS. The
plasma protein binding of avicularin in rat plasma
determined by the ultrafiltration method was
64 %. The pharmacokinetics of avicularin in nine
rats was studied following an intravenous bolus
administration of 1 mg/kg and was found to be
best described by a two-compartment model using a nonlinear mixed effects modeling approach.
Introduction
!
received
revised
accepted
Dec. 11, 2014
January 21, 2015
January 29, 2015
Bibliography
DOI http://dx.doi.org/
10.1055/s-0035-1545728
Published online March 17,
2015
Planta Med 2015; 81: 373–381
© Georg Thieme Verlag KG
Stuttgart · New York ·
ISSN 0032‑0943
Correspondence
Prof. Andrea Diniz
Departamento de Farmacia
Universidade Estadual de
Maringá
Av. Colombo, 5790,
Bl. 68. Campus Universitario
Maringá, Paraná 87020070
Brazil
Phone: + 55 44 30 11 49 37
adiniz@uem.br
With an increasing awareness of a “healthy lifestyle” in todayʼs society, the consumption of nutraceutical and phytopharmaceutical supplements has also increased in the general population. This is further enhanced by media advertisement positioning these products as nonsynthetic
natural supplements. Many of the phytopharmaceuticals are phenolic compounds and among
them are flavonoids that are found in many vegetal species. With 3000 chemical structures already known for this class of phytopharmaceuticals, its development still lags behind pharmaceutical drug development in terms of utilizing tools
to enhance the understanding of the pharmacokinetic and safety properties of these compounds in
both animals and humans [1–3]. A reason could
be the lack of information on their metabolic
pathways, for example, the enzyme kinetic information of flavonoids. Most of the metabolic studies in the literature are drug-drug interactions of
these compounds with other pharmaceuticals
and very limited information is available on the
enzyme kinetic profile of the flavonoids [1]. Phar-
The pharmacokinetic parameters were allometrically scaled by body weight and centered to the
median rat weight of 0.23 kg, with the power coefficient fixed at 0.75 for clearance and 1 for volume parameters. Avicularin was rapidly eliminated from the systemic circulation within 1 h
post-dose, and the avicularin pharmacokinetic
was linear up to 5 mg/kg based on exposure comparison to literature data for a 5-mg/kg single
dose in rats. Using allometric scaling and Monte
Carlo simulation approaches, the rat doses of 1
and 5 mg/kg correspond to the human equivalent
doses of 30 and 150 mg, respectively, to achieve
comparable plasma avicularin concentrations in
humans.
maceutical drug discovery currently has many in
vitro and in silico tools at its disposal to investigate a new molecule. Adapting those available
tools in phytopharmaceutical development for
predictive purposes will be extremely valuable.
One such tool is utilizing population pharmacokinetic and allometric scaling to other species, including humans. This modeling approach can significantly improve pharmacognosy, particularly
in predicting the concentration of these plant
medicines in humans where they are used extensively in the context of traditional medicine.
Flavonoids, among the classes of phytopharmaceuticals, are one of the most consumed products
in the world, in terms of daily intake. Avicularin
" Fig. 1) is
(quercetin-3-O-α-arabinofuranoside; l
a flavone glycoside of quercetin, which was reported to be present in a variety of plant species,
including apple [4, 5], cranberry, and medicinal
plant species belonging to the Bidens and Hypericum genera [6]. Given that some of its biological
activities included suppression of lipid accumulation [7], inhibition of alpha-glicosidase [5] and
urease [8], as well as anti-inflammatory properties [9], investigators have proposed the potential
Buqui GA et al. Pharmacokinetic Evaluation of …
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Pharmacokinetic Evaluation of Avicularin Using a
Model-Based Development Approach
Original Papers
Fig. 1 Chemical structure of avicularin and
coumarin (internal
standard).
case, avicularin is a maker compound that is representative of
the aggregate activities of the extract.
In this study, we developed a bioanalytical method for avicularin,
which was prospectively used to quantify avicularin concentration-time profiles in rats. The pharmacokinetics of avicularin in
the rat was then characterized using a population pharmacokinetic approach. Its pharmacokinetic information was further utilized to extrapolate avicularin concentrations in humans using
allometry. This study represents an important shift in the development paradigm of phytopharmaceutical products to a more
structured and cost-effective model-based development approach.
Results
!
application of this compound for disease prevention. In phytopharmaceutical therapy, patients are administered medicinal
products containing either a single herbal extract or a combination of different extracts. The quantification of dose and dose optimization are considerably more difficult in this setting. One
methodology to quantify dose or exposure is to develop the relationship between pharmacodynamic effects and the pharmacokinetic of one or more compounds, which are called marker compounds. Therefore, marker compounds need to represent the
whole extract or the aggregate activities of the extract. In this
Fig. 2 Representative chromatograms of avicularin (1.41 min) and coumarin (1.81 min). A Blank rat plasma, B plasma spiked with IS in LLOQ, C plas-
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
The selectivity of the bioanalytical assay was evaluated by comparing the chromatograms of blank plasma, blank plasma spiked
with avicularin, and a rat plasma sample after intravenous ad" Fig. 2). The results showed
ministration of avicularin 1 mg/kg (l
that there was no endogenous interference of the matrix at the
retention times of avicularin and coumarin (IS).
The calibration curves of the peak area to the concentration were
constructed using a 1/x weighted linear regression model. The
calibration curves were prepared daily and showed good linearity in the corresponding range for avicularin (R2 > 0.996). The
current assay resulted in an LLOQ of 25 ng/mL for avicularin in
the plasma, which was considered adequate for the study of
pharmacokinetics following a single intravenous administration
ma spiked with avicularin, D, E plasma obtained after 15 min of the intravenous administration of avicularin (1 mg/kg) to rats.
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374
Original Papers
QC Avicularin conc. (ng/mL)
ME (%)
RE (%)
25
50
750
1500
108.8
125.4
123.6
117.2
105.2
107.5
114.2
110.2
375
Table 1 Matrix effect (ME) and
extraction recovery (RE) of avicularin in plasma samples. Reported
values are means from a total of
n = 5 per concentration.
Table 2 Precision and accuracy for determination of avicularin in rat plasma. Reported values are means from a total of n = 5 per concentration.
25
50
750
1500
Intraday
Interday
Precision (RSD, %)
Accuracy (mean, %)
Precision (RSD, %)
Accuracy (mean, %)
4.9
7.9
0.8
3.9
100.2
96.4
101.7
93.4
8.1
5.5
1.3
0.3
105.0
98.6
100.9
95.5
Table 3 Stability of avicularin in plasma samples. Reported values are means from a total of n = 5 per concentration.
QC avicularin conc. (ng/mL)
50
750
1500
Post preparative stability (24 h)
Long-term stablity (1 week)
Short-term stability (4 h)
Precision
Accuracy
Precision
Accuracy
Precision
Accuracy
(RSD, %)
(mean, %)
(RSD, %)
(mean, %)
(RSD, %)
(mean, %)
6.7
5.8
2.5
106.3
104.2
99.5
2.8
1.2
3.4
106.8
96.2
103.9
3.1
2.7
1.5
98.9
101.7
102.4
of avicularin (1 mg/kg). The extraction recovery and matrix effect
" Table 1. The results from the
data of avicularin are shown in l
study of the matrix effect showed that an ionization enhancement (> 100 %) was present, but no significant differences
between the matrix effect in the various concentrations were
found. Thus, the matrix effect for avicularin was not considered
significant. The data from the recovery study indicated that the
sample preparation method was satisfactory and resulted in no
appreciable matrix effect.
The validation results showed that the accuracy and precision of
this method were 95.5 to 105 % and 0.3 to 8.1 %, respectively, as
" Table 2. The evaluation of the assay for accuracy and
shown in l
precision in rat plasma indicated that this analytical method was
accurate and reproducible. Therefore, the analytical method using UPLC‑MS/MS was highly sensitive, specific, and suitable for
the pharmacokinetic study of avicularin in rats.
" Table 3) showed that the differences
The stability evaluation (l
were between 96.2 and 106.8 % of the original concentrations,
which were well within the 20 % relative standard deviation.
Short-term and long-term stabilities demonstrated no significant
degradation over all concentrations tested, as well as for postpreparative stability. These data indicated that avicularin was stable in the plasma for at least a week.
" Table 4. For the
Plasma protein binding results are shown in l
two higher concentrations (750 and 1500 ng/mL), the protein
binding was the same, around 69 %, but for the lower concentration (50 ng/mL), this proportion was significantly different (53 %),
suggesting a nonlinear protein binding effect. Given that plasma
protein binding has an impact on the drug pharmacokinetics and
drug-drug interactions, the plasma protein binding of avicularin
in the rat was evaluated to be 64 % using the ultrafiltration method; consequently, the free drug component of avicularin is approximately 36%.
Total plasma concentrations collected from rats after 1 mg/kg administration of avicularin were analyzed using the validated bio-
Table 4 Plasma protein binding of avicularin in the concentrations of 50, 750,
and 1500 ng/mL (n = 3 per concentration).
Concentration (ng/mL)
Protein binding (%) (mean ± SD)
50*
750
1500
53.2 ± 3.0
68.5 ± 0.6
69.8 ± 1.0
* p < 0.019
analytical assay described above. The pharmacokinetics of avicularin is best described by a two-compartment body model. There
is good agreement between the model-predicted concentrations
" Fig. 3). Conditional weighted
and the observed concentration (l
residuals were within the − 2 to 2 unit ordinate. The parameters
" Table 5.
of the population pharmacokinetic model are shown in l
Given that avicularin was dosed on the basis of body weight, the
estimated parameters were centered on the body weight of 230 g,
which was the median body weight of the nine rats. Avicularin is
rapidly cleared from the systemic circulation with a clearance of
17.1 mL/min; the volumes of distribution for the central and peripheral compartments were 200 and 760 mL, which translate to
a volume at steady state of 960 mL (VSS = VC + VP). The large volume of distribution indicates the likely distribution into the tissues. The corresponding half-lives were 3.3 and 59 min for the
α- and β-phases of the biexponential decline, respectively. The
ωP, which represents the approximate coefficients of variation
for the interindividual variability for CL, Q, and VC were 20, 49
and 32 %, respectively.
The accuracy of the final model was evaluated by a posterior visual predictive check from the simulation of 500 profiles from the
" Fig. 4).
rat population with the same body weight distribution (l
Bootstrap-estimated 95 % confidence intervals of the parameters
" Table 5).
contained the population mean values (l
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QC avicularin Conc. (ng/mL)
Original Papers
Fig. 3 Goodness-of-fit plot for the avicularin population pharmacokinetic model in rats.
Parameter
Structural model parameters
Volume of central compartment (VC; mL)
Volume of peripheral compartment (VP; mL)
Systemic clearance (CL; mL/min)
Intercompartmental clearance (Q; mL/min)
Interindividual variability
% CV of VC(ωVc)
% CV of CL (ωCL)
% CV of Q (ωQ)
Residual variability
Proportional residual error
Mean
RSE (%)
Median (95 % CI)*
200
760
17.1 (1.03 L/h)
23.3 (1.40 L/h)
25
17
9.9
16
205 (121, 321)
734 (478, 1124)
17.2 (14.5, 20.9)
22.1 (16.1, 30.0)
58
33
39
0.20
49
20
32
6
Table 5 Population pharmacokinetic estimated parameters of avicularin after intravenous administration (1 mg/kg) in rats (n = 9).
50 (8.6, 88)
30 (8.2, 47)
36 (15, 57)
0.19 (0.13, 0.25)
RSE, relative standard error; % CV, coefficient of variation values were obtained by taking the square root of the diagonal values of the
NONMEM omega (variance-covariance) matrix and multiplying by 100 %; * Median (95% CI) determined from 500 bootstrap resampling
procedures
For the purpose of scaling to larger animals including humans,
the allometric power coefficients were set to 0.75 and 1 for clearance and volume parameters, respectively. The mean pharmacokinetic parameters of avicularin in humans, assuming an average
body weight of 70 kg, were 309 L/h, 423 L/h, 64 L, and 245 L for CL,
Q, VC and VP, respectively. From equation 3, the estimated doses
in humans were 30 mg and 150 mg, which resulted in a comparable maximum concentration to that in the rats after 1 mg/kg and
" Table 6). The maximum concentration after 5 mg/kg
5 mg/kg (l
avicularin in the rat was obtained from Zhang et al. [10], which
" Fig. 5),
was 2324 ± 423.7 ng/mL. The extrapolation to humans (l
using allometry, indicates that avicularin is rapidly cleared. A
drop to 10 % of the initial concentration was predicted within
" Table 6).
the first half hour of administration (l
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
Discussion
!
After a single intravenous bolus administration of 1 mg/kg avicularin in rats, the plasma avicularin concentration decreased rapidly from approximately 700 ng/mL to less than 200 ng/mL in
10 min and reached approximately 100 ng/mL after an hour. This
biphasic concentration-time profile, which was observed in all
rats, was best characterized by a two-compartment pharmacokinetic model. The pharmacokinetic analysis showed that avicularin was rapidly cleared from the systemic circulation in rats. The
rapid clearance of 17.1 mL/min is much faster than the rat glomerular filtration, which is 1.8 mL/min [11], indicating the possibility of conversion to an active metabolite or several other metabolites. A study showed that human intestinal bacteria could
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377
Fig. 5 Prediction of plasma concentrations (mean
[line] and 95% prediction interval [shaded area]) in
70 kg humans based on allometric scaling after a
30-mg (light grey) and 150-mg (dark grey) single
dose of avicularin in both linear (left) and semi-log
(right) scales.
Dose (mg)
30
150
Post-dose time (h)
Median (ng/mL)
Min, max (ng/mL)
0
0.5
1
4
0
0.5
1
4
509
34.5
22.9
3.0
2540
173
115
15.2
287, 1010
14.1, 67.4
8.7, 49.8
0.5, 10.0
1440, 5050
70.4, 337
43.5, 249
2.7, 50.0
metabolize avicularin, and six metabolites were previously identified, including aglycone quercetin, quercetin-3-O-rhamnoside,
quercetin-3-O-glucoside, and quercetin-7-O-glucoside [12]. It is
still unclear whether these metabolites of avicularin are present
in rats or humans. More studies are required to elucidate the
metabolic pathway of avicularin in animals and humans.
The peak concentration after intravenous bolus administration of
a 1 mg/kg dose of avicularin in our study was proportional to that
observed in the study of Zhang et al. using a 5 mg/kg avicularin
dose [10]. The β-phase half-life of approximately 1 h from this
study was consistent with the terminal half-life of 0.75 ± 0.09 h
reported previously [10]. The rapid clearance of avicularin could
also indicate a rapid tissue distribution. The volume of distribution of avicularin in the rat was very large at 960 mL, which trans-
Table 6 Summary statistics of simulated human avicularin concentrations after intravenous administration of 30 mg and 150 mg avicularin from 500 simulated profiles
assuming a human body weight of
70 ± 5 kg.
lated to approximately 4.2 L/kg, given that the plasma volume of
the rat was only 0.03 L/kg [13]. The 150-fold difference suggested
an extensive distribution out of the plasma or the systemic circulation. Such a fold difference in the volume of distribution is not
uncommon. One example is largazole-thiol, which is a potent
histone deacetylase inhibitor derived from marine cyanobacterium and was shown to have a volume of distribution of 26.7 L/
kg in the rats [14].
We had attempted using a “buttom-up” approach with a physiologically based pharmacokinetic model to predict human exposure [15]. However, due to the lack of information on the human
metabolism of avicularin and the relative concentrations in the
various organs, we elected to use allometric scaling instead. The
allometric scaling approach compensates for the fact that larger
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
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Fig. 4 VPC plot for the avicularin plasma concentration population model in linear (left) and semilog scales (right), where the observed data are the
circles, the median is a solid line, and 2.5th and
97.5th percentiles of the prediction intervals are
dashed lines. The lighter grey shade represents the
90 % confidence interval of the median and the
darker grey shades are the 90 % confidence intervals
of the 2.5th and 97.5th percentiles.
Original Papers
animals normally have a slower metabolic rate and would require a lesser dose based on body weight compared to smaller
animals [16–19]. We utilized the mathematical power law expression
weight b
Y ¼að
Þ
median
where Y is the parameter of interest, weight refers to body weight
normalized by the median, a is the median weight-centered parameter value, and b is the allometric exponent) [20, 21]. Using
the allometric exponent of 0.75 for clearance relationship to body
weight is similar to scaling by body surface area since body surface area increases by a power of 0.75 in relation to weight increase. Similarly, the extrapolated dose in humans was increased
by the proportion of human weight to the rat weight to the same
power exponent to account for scaling by body surface area. The
simulation in humans indicated that avicularin was rapidly
cleared from the systemic circulation within the first half hour
of administration. We also showed that a 30- to 150-mg dose in
humans, assuming an ideal body weight of 70 kg, would result in
a similar exposure to that of a 1- to 5-mg/kg dose in rats. The simulated initial median concentration of 2540 ng/mL in humans
after a 150-mg dose was close to that reported for the maximal
concentrations of 2324 ± 423.7 ng/mL in rats administered a single dose of 5 mg/kg avicularin [10].
There are limitations to the allometric scaling approach as this
approach was previously shown to perform poorly for interspecies scaling, even after several types of correction [19, 22, 23].
One of the primary reasons is because of the significant differences in metabolic pathways and enzymatic activities between
species. Sharma and McNeil described properties of drugs that
may not be amenable to allometric scaling, including drugs that
are highly protein bound, drugs that undergo extensive metabolism and active transport, drugs that undergo significant biliary
excretion or renal secretion, drugs whose target are subject to
significant interspecies differences, and biological drugs that exhibit target-binding effects [16]. Wojcikowski and Gobe discussed the limitations of extrapolation to humans from animal
studies, not only from the pharmacokinetic perspective but from
pharmacodynamics and safety as well [17].
Avicularin could potentially exhibit extensive metabolism, given
that its clearance in the rat is much higher than the glomerular
filtration rate in the rat. Allometric scaling is the preferred choice
for scaling to human equivalent doses in the absence of information on the metabolic pathway of avicularin. Avicularin metabolic
information could potentially allow one to develop a physiologically based pharmacokinetic model and use the model for interspecies scaling. Another limitation of the study is that the simulations assuming intravenous administration may not realistically reflect the preferred route of administration in humans as
extracts containing avicularin are commonly taken via the oral
route. The difference in the route of administrations adds another
layer of complexity, as it is not known whether avicularin is a
substrate of intestinal transporters.
Extracts containing avicularin are already widely ingested in Brazilian traditional medicine as an herbal remedy for various ailments including inflammation. A recent study showed that avicularin suppressed adipogenesis using 3T3-L1 cells and demonstrated that this suppression occurred through the inhibition of
the CCAAT/enhancer-binding proteins (C/EBP alpha-activated)
GLUT4-mediated insulin-responsive glucose transporter, which
mediates glucose uptake [7]. The inhibitory concentration is re-
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
ported at 50 µM, which is approximately 22 ng/mL. In another
study, the anti-inflammatory properties of avicularin were
shown to be mediated by suppression of the secretion of proinflammatory cytokine IL-1β and also attenuated the activation of
the ERK signaling pathway and the degradation of Iκβ [9].
A study by Dost et al., who investigated the effect of a Hypericum
(St. Johnʼs wort) extract on the inflammatory and immune response in rats with induced inflammatory bowel disease [24],
have shown that the low human equivalent dose that some benefits corresponds to the low dose in rats. Their study indicated
that the beneficial effects observed in animals might be relevant
to humans at relatively low doses. Their study showed the value
of extrapolation to a human equivalent dose in the absence of any
information on humans in order to design the low dose in humans that was reasonably safe.
In this study, we utilized model-based development to extrapolate a dose in humans for avicularin with the pharmacokinetic information in rats. This approach is suitable for the extrapolation
of a human equivalent dose. We also noted that this approach using allometric scaling has its shortcomings, including some documented poor predictability across species due to significant differences in metabolic pathways and enzyme activities between
species [22]. This approach, nonetheless, brings us closer to
understanding the dose requirement in humans to achieve pharmacological effects.
Materials and Methods
!
Chemical reagents
Avicularin was isolated from the aerial parts of Bidens sulphurea
(Cav.) Sch. Bip. (Asteraceae) and purified in our laboratory with a
purity of 93.3 % [25, 26]. The structure was confirmed by comparing high-resolution mass spectrometry, and 1H and 13C nuclear
magnetic resonance data with previously reported data [5, 27].
Coumarin, as an internal standard (IS), was purchased from Sigma-Aldrich with a purity of 98 %.
Analytical studies
Chromatographic analysis was performed on an Acquity UPLC
system (Waters Corp.), and the separation was performed at 40 °
C using a Waters Acquity C 18 BEH column (2.1 mm × 50 mm,
1.7 µm) with a linear gradient elution, using water (containing
0.1 % acetic acid) and acetonitrile (containing 0.1% acetic acid) as
the mobile phase.
The elution program was as follows: 10 % (initial), 10–40 %
(1 min), 40–100 % (2.5 min), 100 % (3 min), and 100–10% (5 min)
acetonitrile with 0.1 % acetic acid. The flow rate was 0.3 mL/min,
the injection volume was 5 µL, and the autosampler temperature
was set to 20 °C.
Mass spectrometry detection was performed using a TQ detector
(Waters Corp.) equipped with an electrospray ionization (ESI)
source. Nitrogen was used as the desolvation gas (600 L/h) and
as a cone gas (50 L/h). For collision-induced dissociation, argon
was used as the collision gas at a flow rate of 0.15 L/h. The capillary voltage was set to 2.5 kV, the source temperature to 150 °C,
and the desolvation temperature to 350 °C. The cone voltage and
collision energy were optimized for each compound: 32 kV and
18 eV for avicularin, and 20 kV and 25 eV for IS, respectively.
Quantification was performed using multiple reaction monitoring and with the transitions of m/z 433 → 301 for avicularin and
m/z 147 → 91 for IS. The negative ESI mode for avicularin and pos-
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378
Original Papers
matrix effect (%) = B/A · 100 and recovery (%) = C/B · 100
Intraday precision was tested by analysis of the QC plasma samples at four concentrations (n = 5 for each concentration) in the
same day. Interday precision (n = 5 per concentration) was determined by repeated analysis of the QC samples over three consecutive days. The concentrations were calculated from the corresponding calibration curve. The relative standard deviation and
percentage difference between the amount spiked and determined were taken as the measures of precision and accuracy.
The stability studies were performed by evaluating the QC samples in three different conditions at concentrations of 50, 750,
and 1500 ng/mL of avicularin. Short-term stability was carried
out with samples at room temperature for 4 h. Post-preparative
stability was evaluated on the samples waiting for injection in
the autosampler at 20 °C for 24 h. Long-term stability was studied
by assaying samples following a period of one week of storage at
− 80 °C. The results were expressed by the precision and accuracy
obtained and compared with the initial content of avicularin in
the freshly treated samples.
Plasma protein binding
Protein binding of avicularin was evaluated in rat plasma at the
concentrations of 50, 750, and 1500 ng/mL using an ultrafiltration method as previously described [30]. The avicularin plasma
was incubated at 37 °C for 30 min, then the plasma containing the
drug was loaded onto the Centrifree Ultrafiltration Device (Millipore Corp.), and the filtrate device was centrifuged at 2000 × g for
25 min at 25 °C. The total drug before centrifugation and the free
drug present in the filtrate were assayed by direct injection into
the UPLC‑MS/MS, and the results were compared.
Pharmacokinetic studies in rats
Male Wistar rats, weighing 230 ± 20 g, were provided by the Central Animal Facility of the University of São Paulo, Ribeirão Preto,
Brazil. This study was approved by the Animal Use Ethics Committee (protocol number 058/2012). Nine male Wistar rats were
used in this study and had free access to water and food. The avicularin (1 mg/kg) solution was prepared in saline containing 1 %
DMSO and was administered to the rats by intravenous bolus administration via the left tail vein. 200 µL serial blood samples
were drawn in heparinized polythene microtubes from the right
tail vein at the following post-dose time points: 3, 6, 10, 15, 25,
35, 45, and 60 min. Samples were immediately centrifuged at
2000 × g for 5 min at room temperature, and the plasma was removed and stored at − 80 °C until analysis by UPLC‑MS/MS.
Population pharmacokinetic model
The final structural model was a two-compartment body model
assuming IV bolus administration, parameterized on clearance
(CL), intercompartmental clearance (Q), volumes of distribution
of the central (VC), and peripheral compartments (VP). Exponential interindividual variability terms were included in the pharmacokinetic parameters CL, Q, and VC.
Pi = P × exp (ηi)
(1)
where P represents the population mean and ηi describes the interindividual variability, which was assumed to be independently
and normally distributed with zero mean and variance ωP2. In order not to confound mixed interindividual variability to parameters VP and VC, no interindividual variability was included in the
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Planta Med 2015; 81: 373–381
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itive mode for IS were applied. All analyses were performed using
MassLynx V 4.1 Software (Waters Corp.)
" Fig. 1) due to the absence of enThe IS of choice was coumarin (l
dogenous interference and its improbable presence in the plant
material used for the extraction of avicularin. Furthermore, the
main reason for this choice was that its chromatographic behavior and extraction efficiency were similar to those of avicularin. A
UPLC‑MS/MS analytical method for avicularin was developed independently of the current method and utilized carbamazepine
as their internal standard [10]. Their chromatographic conditions
were different from the ones used in the current study.
Individual stock solutions of avicularin (400 µg/mL) and IS (2 mg/
mL) were accurately prepared in volumetric flasks, dissolved
with acetonitrile : water (80 : 20 v/v). The stock solutions were serially diluted in order to get the standard working solutions with
the desired concentrations. All stock solutions were stored at 4 °
C. Working solutions were prepared immediately before use.
For the stability analysis, quality control (QC) samples of four
concentrations at 25, 50, 750, and 1500 ng/mL were prepared in
plasma. QC samples were stored at − 80 °C until analysis.
For the sample preparation, 100 µL of the IS solution at 0.5 µg/mL
in acetonitrile were added to 100 µL of the rat plasma sample. To
this mixture, 100 µL of hexane were added. After vortexing for
2 min, the samples were centrifuged at 2140 × g and 4 °C for
15 min. After this process, 5 µL of the supernatant liquid was injected onto the column.
Selectivity was assessed by analyzing blank plasma samples from
six sources, blank plasma samples spiked with avicularin and IS,
and rat plasma samples after intravenous administration of avicularin; interfering substances in the biological matrix were
monitored as well.
An aliquot (50 µL) of appropriate avicularin standard working solution was spiked into the blank plasma samples to give concentrations of 25, 50, 100, 250, 500, 750, 1000, 1500, and 2000 ng/
mL. An aliquot of 50 µL of IS solution (0.5 µg/mL) was added to
all spiked samples, and then the sample solutions were prepared
and analyzed as described above. The results were fitted to linear
regression analysis using 1/x as the weighting factor. The concentration of avicularin in the plasma was directly calculated from
the corresponding calibration curve.
The lower limit of quantification (LLOQ) was defined as the lowest avicularin concentration that could be determined with an accuracy of 80–120 % and precision of 20%, and the analyte response 5 times greater than the response of the blank.
Recovery and the matrix effect were measured for LLOQ, and
low-, medium-, and high-concentration QC samples (25, 50, 750,
and 1500 ng/mL). The blank biological matrix was prepared without the addition of any standard. The extraction recovery was determined by comparing the analyte/internal standard peak area
ratios obtained from extracted plasma samples with those originally dissolved with the biological matrix extract.
The matrix effect was determined by comparing the analyte/internal standard peak area ratios dissolved with the blank matrix
extracted against those dissolved only with acetonitrile : water
(80 : 20 v/v). The ion suppression of the analytes was evaluated
[28, 29]. Each test was measured in triplicate.
The matrix effect and recovery of the extraction procedure were
measured by comparing the absolute peak areas obtained in the
solution standard (A), the corresponding peak areas for standards
spiked after extraction into plasma extracts (B), and the peak
areas for standards spiked before extraction (C), so the matrix effect and recovery values can be calculated such that
379
Original Papers
VP term. The subscript i represents the individual. The residual
variability was characterized by a proportional model.
The allometric size adjustment by weight was centered on
0.23 kg, which was the median weight of the rats. The relationship between body weight and parameters are described by the
following equation:
Acknowledgements
!
This work was supported by a scholarship from CNPq 136 255/
2011–6 and grants from FAPESP 2014/50 265–3 and INCT‑if.
Conflict of Interest
weight Þx
Pi ¼ Pð
median
!
(2)
where weight is the weight of the individual rat, and median is
the median weight of the study population; x is the power coefficient which was fixed to 0.75 for the clearance (both CL and Q)
and 1 for the volume of distribution (both VC and VP) parameters.
The same equation was used for the prediction of CL, Q,Vc, and Vp
in humans where the human body weight of 70 ± 5 kg (mean ±
SD) is used for the weight parameter.
The predictability of the final model was evaluated using the visual predictive check wherein plasma concentration-time profiles were simulated in 500 replicates using the final population
pharmacokinetic model. The median and 95% prediction interval
of the time course of avicularin plasma concentrations were computed and overlaid with the observed data to evaluate the predictive performance of the final model. The majority of the individual observations should be enclosed within the 2.5th and 97.5th
percentiles of the simulated data if the final model adequately
describes the original data. The 90 % confidence interval of the
prediction interval was generated based on a bootstrap procedure as previously described [31].
The model stability was evaluated by a bootstrap resampling
technique with 500 bootstrap procedures. Parameter uncertainty
was assessed by comparing the model parameter estimates with
the posterior distribution of the bootstrap estimates; the 2.5th
and 97.5th percentiles of the parameter estimates from the posterior distribution from the bootstrap estimates were used.
The population pharmacokinetic model of avicularin in rats was
developed using a nonlinear mixed effects model with a first-order conditional maximum likelihood estimation η-interaction in
NONMEM (version VII.2) and an NM-TRAN preprocessor (ICON
Development Solutions). The subroutine was ADVAN3 TRANS4.
The models were run using G-Fortran 95. Bootstrap resampling
and the visual predictive check were performed with Perlspeaks-NONMEM 3.5.5 running ActivePerl 5.12 (ActiveState)
and Xpose4 package in R 3.1.0.
Allometric scaling to humans
The doses for the simulations in humans were determined by the
following equation:
Weighthumans 0:75
Dosehumans ¼ ð
Þ Doserats
Weightrats
(3)
Where Dosehumans refers to the estimated dose in humans;
Doserats refers to the dose in rats; Weighthumans is the average
weight in humans; and Weightrats is the median rat weight of
0.23 kg. The human weight used in the simulation was 70 ± 5 kg.
A total of 500 concentration-time profiles were simulated.
Buqui GA et al. Pharmacokinetic Evaluation of …
Planta Med 2015; 81: 373–381
There is no conflict of interest among the authors.
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