Mireille Hassoun1, Maria Malmlöf2,3, Otto Scheibelhofer4, Abhinav Kumar1, Sukhi Bansal1, Ewa Selg2, Mattias Nowenwik2, Per Gerde2,3, Snezana Radivojev4, Amrit Paudel4,5, Sumit Arora4, Ben Forbes1. 1. King's College London , Institute of Pharmaceutical Science , London SE1 9NH , U.K. 2. Inhalation Sciences Sweden AB , Hälsovägen 7-9 , 141 57 Huddinge , Sweden. 3. Institute of Environmental Medicine , Karolinska Institutet , 171 77 Stockholm , Sweden. 4. Research Centre Pharmaceutical Engineering GmbH , Inffeldgasse 13 , Graz 8010 , Austria. 5. Institute of Process and Particle Engineering , Graz University of Technology , Inffeldgasse 13 , Graz , 8010 , Austria.
Abstract
The dissolution of inhaled drug particles in the lungs is a challenge to model using biorelevant methods in terms of (i) collecting a respirable emitted aerosol fraction and dose, (ii) presenting this to a small volume of medium that is representative of lung lining fluid, and (iii) measuring the low concentrations of drug released. We report developments in methodology for each of these steps and utilize mechanistic in silico modeling to evaluate the in vitro dissolution profiles in the context of plasma concentration-time profiles. The PreciseInhale aerosol delivery system was used to deliver Flixotide aerosol particles to Dissolv It apparatus for measurement of dissolution. Different media were used in the Dissolv It chamber to investigate their effect on dissolution profiles, these were (i) 1.5% poly(ethylene oxide) with 0.4% l-alphaphosphatidyl choline, (ii) Survanta, and (iii) a synthetic simulated lung lining fluid (SLF) based on human lung fluid composition. For fluticasone proprionate (FP) quantification, solid phase extraction was used for sample preparation with LC-MS/MS analysis to provide an assay that was fit for purpose with a limit of quantification for FP of 312 pg/mL. FP concentration-time profiles in the flow-past perfusate were similar irrespective of the medium used in the Dissolv It chamber (∼0.04-0.07%/min), but these were significantly lower than transfer of drug from air-to-perfusate in isolated perfused lungs (0.12%/min). This difference was attributed to the Dissolv It system representing slower dissolution in the central region of the lungs (which feature nonsink conditions) compared to the peripheral regions that are represented in the isolated lung preparation. Pharmacokinetic parameters ( Cmax, Tmax, and AUC0-∞) were estimated from the profiles for dissolution in the different lung fluid simulants and were predicted by the simulation within 2-fold of the values reported for inhaled FP (1000 μg dose) administered via Flixotide Evohaler 250 μg strength inhaler in man. In conclusion, we report methods for performing biorelevant dissolution studies for orally inhaled products and illustrate how they can provide inputs parameters for physiologically based pharmacokinetic (PBPK) modeling of inhaled medicines.
The dissolution of inhaled drug particles in the lungs is a challenge to model using biorelevant methods in terms of (i) collecting a respirable emitted aerosol fraction and dose, (ii) presenting this to a small volume of medium that is representative of lung lining fluid, and (iii) measuring the low concentrations of drug released. We report developments in methodology for each of these steps and utilize mechanistic in silico modeling to evaluate the in vitro dissolution profiles in the context of plasma concentration-time profiles. The PreciseInhale aerosol delivery system was used to deliver Flixotide aerosol particles to Dissolv It apparatus for measurement of dissolution. Different media were used in the Dissolv It chamber to investigate their effect on dissolution profiles, these were (i) 1.5% poly(ethylene oxide) with 0.4% l-alphaphosphatidyl choline, (ii) Survanta, and (iii) a synthetic simulated lung lining fluid (SLF) based on human lung fluid composition. For fluticasone proprionate (FP) quantification, solid phase extraction was used for sample preparation with LC-MS/MS analysis to provide an assay that was fit for purpose with a limit of quantification for FP of 312 pg/mL. FP concentration-time profiles in the flow-past perfusate were similar irrespective of the medium used in the Dissolv It chamber (∼0.04-0.07%/min), but these were significantly lower than transfer of drug from air-to-perfusate in isolated perfused lungs (0.12%/min). This difference was attributed to the Dissolv It system representing slower dissolution in the central region of the lungs (which feature nonsink conditions) compared to the peripheral regions that are represented in the isolated lung preparation. Pharmacokinetic parameters ( Cmax, Tmax, and AUC0-∞) were estimated from the profiles for dissolution in the different lung fluid simulants and were predicted by the simulation within 2-fold of the values reported for inhaled FP (1000 μg dose) administered via Flixotide Evohaler 250 μg strength inhaler in man. In conclusion, we report methods for performing biorelevant dissolution studies for orally inhaled products and illustrate how they can provide inputs parameters for physiologically based pharmacokinetic (PBPK) modeling of inhaled medicines.
In vitro dissolution testing is well established
for enteral solid dosage forms for quality control purposes, for comparing
products under drug classification frameworks, and for predicting
drug pharmacokinetics in vivo.[1−4] The therapeutic effect of an inhaled
particulate aerosol is only realized after drug release into solution;
thus, investigating the dissolution of solid particle aerosol dosage
forms has attracted interest.[5−8] Dissolution testing for orally inhaled products (OIP)
is currently a “hot topic” with research groups adapting
a panoply of adaptations of pharmacopoeial apparatus for aerosol collection
and dissolution to function as in vitro tests for
discerning the quality attributes of inhaled medicines. The latest
developments in oral biopharmaceutics demonstrate convincingly that
biorelevant methods are important if dissolution testing is to be
used as an in vivo predictive tool and realize its
full potential in a regulatory context and to predict clinically relevant
performance.[3,4]The complexity of biorelevant
dissolution for inhaled products
derives from the need to capture representative aerosol particles
in a dispersed manner that reflects their deposition in the lungs,
to present the particles to low volumes of lung fluid-like dissolution
medium, and to measure reliably the low mass of drug delivered by
aerosol medicines. Of the systems reported to date,[5−11] none accommodates all these features. The disparate OIP dissolution
methods that have been studied tend to be nonintegrated and utilize
large volumes of dissolution medium, which precludes the use of a
dissolution medium that represents human lung lining fluid.[12,13] For some studies of poorly soluble drugs, the medium has been supplemented
by addition of protein or phospholipid components, e.g., surfactants
such as DPPC[6,14] or lung surfactant preparations
such as Survanta.[15] However, biorelevant
media are either expensive or difficult to prepare, and often represent
only the surfactant component of distal respiratory tract lining fluid,
with the highly abundant proteins absent.Recently, an integrated
apparatus has been developed by Inhalation
Sciences for depositing aerosols to a flow past dissolution cell,[16] comprising the PreciseInhale and DissolvIt systems, respectively. The PreciseInhale can deliver
carefully controlled doses of aerosols from powder inhalers or pressurized
metered dose inhalers to the DissolvIt system, in
which particle dissolution can be followed by simultaneous observation
of aerosol particles using microscopy and measurement of dissolved
drug transferred to a flow-past perfusate. Although DissolvIt addresses various limitation of dissolution systems used
for OIP, the dissolution vessel contains 5.7 μL of a poly(ethylene
oxide) (PEO) gel as the dissolution matrix rather than a biorelevant
medium. Due to the novelty of the system, there is little reported
data on the performance of the system in predicting dissolution.[16,17]To study clinically relevant scenarios, dissolution studies
to
date have focused on the dissolution of poorly soluble inhaled drugs,
in particular fluticasone proprionate (FP).[10,11,18] Delivery of FP to the DissolvIt with different biorelevant media in the chamber permits comparison
to FP dissolution–absorption profiles in other systems, e.g.,
isolated perfused lungs (IPL). To perform these experiments requires
accurate quantification of submicromolar concentrations of FP using
a sensitive assay and an efficient extraction method.[19,20] Liquid-chromatography with tandem mass spectrometric detection (LC–MS/MS)
provides selective and sensitive analysis of glucocorticoids in biological
fluids.[21−23] However, poor repeatability using reported methods[21−23] required development of a new solid phase extraction (SPE) method,
which was reliable and quick and required minimal sample preparation
and solvent use.The value of in vitro systems
is in providing
decision-making data, e.g., dissolution measurements for predicting
and modeling impacts on drug pharmacokinetics in the early stages
of the drug development process. Such data can expedite drug development
and prevent unexpected toxico-kinetics and ultimately avoid costly
end-stage failures.[24] Reliable predictive
models for pharmacokinetics depend on selecting appropriate mathematical
approaches, and more current studies tend to utilize in silico techniques.[25−27] For modeling dissolution, Backman et al. have described
how mechanistic models may aid in obtaining a better understanding
of dissolution, which can be used to predict systemic exposure (AUC)
and hence its influence on drug therapeutic effect.[28] For this study, a mechanistic model was developed to evaluate
the dissolution data derived from the biorelevant approach using the
DissolvIt system.In summary, the aim of the
present study was to develop a biorelevant
dissolution method by utilizing simulated lung fluid in the DissolvIt system. To measure the dissolution of FP, a LC–MS/MS
method was validated for measurement of low drug concentrations. The
effect of dissolution medium on FP aerosol particle dissolution was
investigated using three different media: (i) 1.5% poly(ethylene oxide)
+ 0.4% l-alphaphosphatidyl choline, (ii) Survanta , and (iii)
a synthetic simulated lung lining fluid (SLF), synthesized based on
human lung fluid composition.[29,30] Finally, an in silico model based on the method of Boger et al.[31] was adapted to explore the impact of the dissolution
rates derived on pharmacokinetics.
Experimental
Section
Materials
Flixotide 50 μg Evohaler
(GSK), poly(ethylene oxide) (PEO), and l-alphaphosphatidyl
choline were supplied by Sigma-Aldrich Limited (Dorset, UK), whereas
Survanta was obtained from Abbvie Ltd. (Berkshire, UK). The chemicals
required for the production of SLF and the preparation of SLF were
carried out according to a recently published method.[30] For solid phase extraction validation, the chemicals included
were micronized FP (USP grade, purity 98%) supplied by LGM Pharma
Inc. (Boca Raton, USA), pentadeuterated FP (FP-d5; USP grade, purity
97%) by Insight Biotechnology Limited (Wembley, UK), and rabbit serum,
purchased from Sigma-Aldrich Company Limited (Dorset, UK). Chemicals
needed for the extraction procedure were zinc sulfate powder, supplied
by VWR International Limited (Lutterworth, UK), HPLC-gradient grade
acetonitrile, 35% v/v ammonium hydroxide solution, and Analytical-Reagent
grade dichloromethane, which were all purchased from Fischer Chemical
(Loughborough, UK). The materials required for aerosolization, deposition,
and dissolution of FP were provided by Inhalation Sciences, Sweden.
For FP dissolution in rat IPL, female CDIGS (Sprague–Dawley)
rats were obtained from Charles River (Sulzfeld, Germany), and the
necessary equipment was provided by Inhalation Sciences, Sweden.
Preparation of Calibration Curve and Validation
of Assay
Primary stock solutions of FP and FP-d5 were prepared
by adding 1 mg of FP or FP-d5 into a 10 mL volumetric flask and filled
to the volume with pure acetonitrile, producing 100 μg/mL solutions,
and stored at −20 °C. A 1 μg/mL FP working solution
was prepared by the appropriate dilution of the stock with pure acetonitrile.
The calibration standards (156, 313, 625, 1250, 2500, 5000, and 10,000
pg/mL) were prepared from serial dilution of the working solution
with pure acetonitrile. Method validation was conducted in terms of
linearity, precision (intraday and interday), accuracy, limit of detection,
and limit of quantification. Linearity was evaluated by plotting a
calibration curve of mean peak area ratio of FP/FP-d5 (n = 9) against the concentrations of seven standards, using a weighted
(1/x) linear regression model. The coefficient of
variation (%CV) was calculated across three calibration sets prepared
on the same day for intraday precision. For interday precision, another
three fresh series of calibration standards prepared on days 2 and
3 were analyzed. Accuracy of the data was also evaluated across nine
determinants of each standard, ensuring it was within 15% of each
standard concentration. The limit of detection (LOD) and limit of
quantification (LOQ) were calculated based on eqs and 2, respectively.[19]where SD is the standard deviation of the y estimate
(peak area ratio) and slope is the gradient of
the line.
Deposition and Dissolution of FP Aerosol in
the DissolvIt System
The aerosolization
of Flixotide was carried out by connecting the Flixotide pMDI canister
to the US Pharmacopeia Induction Port No. 1 (standardized simulation
of the throat) of the PreciseInhale aerosol system from Inhalation
Sciences (Stockholm, Sweden) (Figure ). The aerosol particles were deposited on nine circular
microscope glass coverslips, 13 mm in diameter, and the dissolution
of the deposited particles was investigated by interfacing the particles
with the dissolution medium in the DissolvIt dissolution
system from Inhalation Sciences (Stockholm, Sweden),[16] thermostated to 37 °C. Prewarmed dissolution medium,
5.7 μL of PEO, Survanta, or SLF, was applied to the polycarbonate
membrane (pore size 0.03 μm) of each DissolvIt dissolution chamber, with the perfusate buffer streaming on the
other side. The flow past perfusate consisted of 0.1 M phosphate buffer
containing 4% w/v albumin solution, mixed using a magnetic stirrer.
The perfusate was degassed using helium to remove excess bubbles and
streamed at a flow rate of 0.4 mL/min over a period of 4 h with samples
collected by an automated fraction collector at 0, 3, 6, 9, 12, 15,
20, 25, 30, 40, 50, 60, 120, and 240 min.
Figure 1
Schematic diagram of
(a) fluticasone propionate aerosolization
and particle deposition and (b) the dissolution system.
Schematic diagram of
(a) fluticasone propionate aerosolization
and particle deposition and (b) the dissolution system.
Dissolution of FP Aerosol
in Rat Isolated
Perfused Lungs
Female rats with body weight 279 ± 20
g were euthanized with phenobarbital sodium (100 mg/kg, i.p.), and
their whole lungs were maintained ex vivo as described
in other reports.[32,33] The lungs were placed in the
artificial thoracic chamber. They were ventilated with room air at
75 breaths/min by creating an alternating negative pressure (−0.2
to −0.8 kPa)[3] inside the chamber,
using an Ugo Basile model 7025 animal respirator (Varese, Italy),
with a stroke volume of 6 mL, superimposed on a constant vacuum source
connected to the chamber. The tracheal air flow velocity and pressure
inside the chamber were measured with a heated Hans Rudolph 8430 series
pneumotachograph (Kansas City, USA) at 0–3 L/min and a differential
pressure transducer from EMKA Technologies (Paris, France), respectively.
The physiological lung-function variables: tidal volume (Vt), dynamic lung compliance (Cdyn),[34] and lung conductance (Gaw), which is inversely proportional to lung resistance
(RL),[34] were calculated from each breath
in real time and logged by a data acquisition system using the EMKA
Technologies software IOX v. 6.1a. The lungs were perfused via the
pulmonary artery in a single-pass mode, at a constant hydrostatic
pressure of approximately 12 cm H2O, and the perfusate
reservoir was continually overflowing into a recirculation drain pipe,
in order to keep a constant liquid pressure head. Throughout the experiments,
the perfusate flow rate after the passage through the lungs (Qperf) was measured gravimetrically using a custom-made
fraction collector with a balance. The perfusion medium consisted
of Krebs–Henseleit buffer, 5.5 mM glucose, 12.6 mM HEPES, and
4% w/v bovine serum albumin. The temperature of the perfusate and
the artificial thoracic chamber were maintained at 37 °C. The
lungs were left to stabilize for 30 min prior to aerosol exposures,
and only the lung preparations with stable baseline values for Vt, Cdyn, Gaw, and Qperf during
at least a 15 min period were used. The measured values were Vt = 1.8 ± 0.2 mL, Cdyn = 6.6 ± 1.0 mL/kPa; Gaw = 279 ± 20 mL/s/kPa, and Qperf = 32 ± 2 mL/min
(n = 6). Administration of Flixotide aerosol to the
IPL was carried out using the PreciseInhale system as described above,
where the aerosol was delivered to the lungs by the active dosing
system, and the system automatically terminated the exposure when
the inhaled target dose was reached. The perfusate was sampled using
an automatic fraction collector over a 2 h period from the start of
the aerosol exposure with sampling intervals of 4.5, 6, 7.5, 9, 12,
15, 30, 60, and 120 min. After the end of the perfusion period, the
lungs and trachea were harvested for analysis of the amount of FP
retained in the tissues after the perfusion period to enable mass
balance calculations. The experiments were approved by a local ethical
review board in Stockholm.
Sample Extraction
Samples were prepared
for analysis following a new solid phase extraction method. Each sample,
325 μL, was loaded into a deep-well sample plate from Thermo-Scientific
(Surrey, UK) followed by 50 μL of internal standard (0.1 μg/mL
FP-D5). Zinc sulfate 0.1 M, 300 μL, followed by 75 μL
of 10% ammonium hydroxide were added and mixed using a multichannel
pipet. The SPE plate was placed on an orbital shaker for 30 min followed
by centrifugation at 3700 rpm for 5 min. The samples were then transferred
to a preconditioned Evolute Express ABN 10 mg SPE 96-well plate by
Biotage (Uppsala, Sweden) and washed by applying low vacuum with 200
μL HPLC-grade water followed by 200 μL of 25% v/v methanol
in water. The analytes were eluted twice with 200 μL of pure
acetonitrile, once with 100 μL of dichloromethane then vacuum
centrifuged to dryness. Samples were reconstituted with 30 μL
of 55% v/v acetonitrile in water and sonicated rapidly for 10 min.
Finally, an aliquot of the sample (20 μL) was injected into
the LC–MS/MS system.
FP Quantification Using
LC–MS/MS
Quantification of FP was carried out by Waters
Xevo TQ tandem quadrupole
mass spectrometer by Waters (Elstree, UK) equipped with an ESI interface,
coupled with a Waters Acquity Ultra High Performance LC system (UPLC),
equipped with a binary solvent delivery system. Chromatographic separations
were carried out on a Waters Acquity UPLC BEH C18 column 130 Å,
1.7 μm, 2.1 × 50 mm. The mobile phase was a mix of mobile
phase A and mobile phase B, which were 0.1% ammonium hydroxide in
water and 1:1 v/v acetonitrile in water, respectively. The flow rate
of the mobile phase was 0.2 mL/min with a 2 min gradient from 50%
to 95% B. Argon was used as the collision gas and the collision energy
was set at 12 V. The LC–MS/MS operations were controlled by
the computer software, MassLynx 4.1, and analyte quantification was
performed with multiple reaction monitoring using the following transitions: m/z 501.4 > 313.1 for FP and m/z 506.4 > 313.1 for FP-d5.
Data Analysis
For the validation
process, peak integrations and data analysis were performed using
the MassLynx 4.1 computer software. The relationship between peak
area ratio and FP concentration (pg/mL) was calculated using the LINEST
function in Microsoft Excel. Data was expressed as the mean ±
standard deviation of replicate determinations, where n ≥ 3. For the DissolvIt system, the FP transferred
to the perfusate was expressed as a percent of the deposited amount
on the glass slide. For statistical analysis, one-way ANOVA was applied
to the data followed by Tukey post-hoc analysis, using the IBM SPSS
version 22 software. Data was identified as statistically significant
when p ≤ 0.05.
Mechanistic
Modeling
Simulation of Plasma Concentration–Time
Profiles of Fluticasone
A mechanistic physiologically based
pharmacokinetic (PBPK) model for predicting the fate of inhaled FP
(as illustrated in Figure ) was developed using Java (version 1.8.0_111, Oracle, Redwood
City, US). The integration of the system of ordinary differential
equations was performed via the 8(5,3) Dormand–Prince integrator[35] as realized in the Apache Commons Math library
version 3.6.1 from Apache Software Foundation (Forest Hill, US). The
model was adapted from that published by Boger et al.[31] Briefly, the model was based on the respiratory physiology
divided into three compartments; extra-thoracic, tracheobronchial
(central lung), and alveolar (peripheral lung) region (Figure ). The particles deposited
in the extra thoracic region were swallowed and transferred to gut,
where they were subjected to systemic absorption, based on their bioavailable
fraction (F). Particles deposited in the central
and peripheral lung regions were modeled for their dissolution in
epithelial lung lining fluid, using input from the in vitro dissolution experiments in DissolvIt system. The in vitro data were fitted to a Weibull function to extract
the shape and time scale parameters that were then used to model the
dissolution of particles in the model. FP permeation in lung tissues
and mucociliary clearance of particles deposited in the central lung
were modeled as described by Boger et al.[31] The central and peripheral lung areas were perfused by the bronchial
blood flow (Q_central lung) and entire cardiac output (Q_cardiac output),
respectively. Perfusion-rate limited distribution was assumed to apply
for all tissues. System-specific input parameters for central lung,
peripheral lung, blood flows, and volume of the tissue compartments
are provided as Supporting Information (Tables
S1 and S2).
Figure 2
Schematic diagram representing the whole body physiologically based
pharmacokinetic (PBPK) model.
Schematic diagram representing the whole body physiologically based
pharmacokinetic (PBPK) model.For regional lung deposition modeling, the particle size
distribution
of the tested formulations was determined using next generation impactor
(NGI), resulting in a discrete distribution of seven particle sizes
with corresponding mass fraction deposited (f0, ..., f6). Multiple-Path Particle
Dosimetry model MPPD V2.11 2009 from Applied Research Associates Inc.
(Albuquerque, US) was used to calculate the regional deposition of
particles from the tested formulations. A breathing pattern with 2
s inspiration, 1 s expiration, 10 s breath hold, and a tidal volume
of 625 mL was used.[36] The Yeh-Shum 5-lobe
lung model was chosen for the calculations of regional deposition
fraction.[37] The drug and formulation specific
parameters for FP inhaled in the model are provided as Supporting Information (Table S3).
Sensitivity Analysis of Dissolution Kinetics
A sensitivity
analysis of the pharmacokinetic parameters to the in vitro dissolution kinetics of FP was performed using
the mechanistic PBPK model (described in section ). Hypothetical in vitro dissolution profiles of FP were created by means of numerical approximation
with maximum cumulative percent dissolved fixed to mimic the cumulative
percent of FP in SLF. The numerical approximations were selected in
order to probe three different possible in vitro dissolution
scenarios: a profile where release greatly exceeded that observed
experimentally in SLF (case 1) and two profiles that are similar to
SLF but initially more rapid (case 2) or slower (case 3). The data
was fitted to a Weibull function to extract the shape (b) and time
scale (a) parameters of these profiles (Table ). The Weibull eq (eq ) was applied to describe the hypothetical
dissolution curves and used as an input to the PBPK model. It describes
the accumulated fraction of the drug (m) in solution
at time t. The location parameter (T) is the lag time before the onset of
the dissolution and, in all investigated cases, was zero.
Table 1
Fitted
Weibull Shape Factor (b) Together with Pharmacokinetic
Data of FP Following Its
Dissolution in SLF and Artificial Dissolution Profiles (Cases 1–3)a
parameter
SLF*
case 1**
case 2**
case 3**
Weibull shape parameter
1.5285 ± 0.08
3.0204
1.1508
1.8716
Cmax (μg/L)
0.74 ± 0.05
4.61
1.44
0.53
Tmax (h)
3.01 ± 0.58
0.50
0.75
6.00
AUC0-∞ (μg/L·h)
6.46 ± 0.08
6.92
6.87
6.04
*n = 3; **n = 1.
*n = 3; **n = 1.
Results
Extraction and Quantification
of Fluticasone
Propionate Using LC–MS/MS
As published methods for
FP analysis[21−23] proved difficult to replicate with adequate reproducibility
and sensitivity, a new SPE method for sample preparation was developed
for use with LC–MS/MS for the assay of FP in biorelevant media.
The methodology was easy to perform, and the relationship between
the mean peak area ratio of FP/FP-d5 and the concentration of FP in
the samples was linear (R2 value = 0.999)
with interday and intraday precision (CV) being <20% (in according
to ICH guidelines), except for 156 pg/mL. The accuracy for all FP
standard concentrations was within 85–115% (Figure ). The LOD and LOQ were 106
and 312 pg/mL, respectively. Since the FP concentrations in all dissolution
experiments fell within the upper range of the assay, the method was
fit for purpose.
Figure 3
Validation of the solid phase extraction and LC–MS/MS
assay
of fluticasone propionate (FP): (a) linearity of the mean peak area
ratio vs concentration; (b) FP concentration, precision, and accuracy.
Data expressed as mean ± SD (n = 9).
Validation of the solid phase extraction and LC–MS/MS
assay
of fluticasone propionate (FP): (a) linearity of the mean peak area
ratio vs concentration; (b) FP concentration, precision, and accuracy.
Data expressed as mean ± SD (n = 9).
Dissolution of FP in DissolvIt and IPL
The penetration of FP, manifested as
perfusate
concentration, was higher at all time points when the dissolution
medium was PEO or Survanta with lipid content lower than that of SLF
(Figure ), in good
agreement with the theoretical models. However, overall the influence
of medium on FP dissolution was limited since the difference in the
FP perfusate concentration values were not statistically significant
(one-way ANOVA, p > 0.05) between dissolution
in
any of three lung fluids at most time points, except the difference
in FP concentration for PEO and SLF at 20 min. The FP concentration–time
profile in perfusate was also similar between PEO and Survanta, both
reaching a Cmax at approximately 20 min.
The cumulative percent of FP transferred into the perfusate over time
in the DissolvIt system showed similar profiles in
each dissolution medium reflecting the ranking observed in the perfusate
concentrations, whereas administration to the rat IPL resulted in
concentrations of FP and cumulative % of FP in the perfusate that
were significantly higher at nearly all time points (Figure ).
Figure 4
(a) Protein and lipid
concentration in poly(ethylene oxide) in
phosphate buffer solution (PEO), simulated lung lining fluid (SLF),
and Survanta and (b) concentration of FP in the perfusate over time
following dissolution in PEO, SLF, and Survanta normalized to mass
deposited on the glass coverslips. **Difference in FP concentration
in PEO and SLF is statistically significant (one-way ANOVA, p < 0.05). Data expressed as mean ± SD (n = 3).
Figure 5
(a) Concentration of
FP in the perfusate over time following dissolution
in poly(ethylene oxide) in buffer solution (PEO), simulated lung lining
fluid (SLF), Survanta, and rat isolated perfused lung (IPL). *Difference
in FP concentration in IPL and SLF is statistically significant (one-way
ANOVA, p < 0.05). **Difference in FP concentration
in IPL and the remaining three lung fluids, PEO, SLF, and Survanta
is statistically significant (one-way ANOVA, p <
0.05). (b) Cumulative % of FP transferred into the perfusate over
time, following its dissolution in PEO, SLF, Survanta, and IPL. Data
expressed as mean ± SD (n = 3).
(a) Protein and lipid
concentration in poly(ethylene oxide) in
phosphate buffer solution (PEO), simulated lung lining fluid (SLF),
and Survanta and (b) concentration of FP in the perfusate over time
following dissolution in PEO, SLF, and Survanta normalized to mass
deposited on the glass coverslips. **Difference in FP concentration
in PEO and SLF is statistically significant (one-way ANOVA, p < 0.05). Data expressed as mean ± SD (n = 3).(a) Concentration of
FP in the perfusate over time following dissolution
in poly(ethylene oxide) in buffer solution (PEO), simulated lung lining
fluid (SLF), Survanta, and rat isolated perfused lung (IPL). *Difference
in FP concentration in IPL and SLF is statistically significant (one-way
ANOVA, p < 0.05). **Difference in FP concentration
in IPL and the remaining three lung fluids, PEO, SLF, and Survanta
is statistically significant (one-way ANOVA, p <
0.05). (b) Cumulative % of FP transferred into the perfusate over
time, following its dissolution in PEO, SLF, Survanta, and IPL. Data
expressed as mean ± SD (n = 3).
In Silico Modeling of FP
Dissolution
Pharmacokinetic parameters (Cmax, Tmax, and AUC0-∞), calculated from the simulated plasma concentration time profiles
for the different lung fluid simulants, predicted within two-folds
the observed pharmacokinetic parameters of inhaled FP (1000 μg
dose) administered via Flixotide Evohaler 250 μg strength inhaler[38] (Figure ). No significant difference was found between the clinically
observed and simulated pharmacokinetic parameters when in
vitro dissolution input from PEO and Survanta was used in
the developed PBPK model. However, differences (p > 0.05) in Cmax and AUC0-∞ compared to the clinical data were found when the slower in vitro dissolution of FP in SLF was modeled. The AUC0-∞ predicted by the model for all three media
were slightly underestimated owing to the underestimation of terminal
time points of plasma concentration–time profile of inhaled
FP suggesting that FP is retained for longer in the airways, which
if incorporated into the model would improve the simulation.
Figure 6
In
silico modeling. (a) Simulated plasma concentration
of FP over time, following its dissolution in poly(ethylene oxide)
in buffer solution (PEO), simulated lung lining fluid (SLF), and Survanta.
(b) Pharmacokinetic data of FP absorbed in plasma from healthy volunteers,
after inhalation of FP pMDI (in vivo) and of FP absorbed
in perfusate, following its dissolution in PEO, SLF, and Survanta.
Data expressed as mean ± SD (n = 3 or 9).
In
silico modeling. (a) Simulated plasma concentration
of FP over time, following its dissolution in poly(ethylene oxide)
in buffer solution (PEO), simulated lung lining fluid (SLF), and Survanta.
(b) Pharmacokinetic data of FP absorbed in plasma from healthy volunteers,
after inhalation of FP pMDI (in vivo) and of FP absorbed
in perfusate, following its dissolution in PEO, SLF, and Survanta.
Data expressed as mean ± SD (n = 3 or 9).To understand the sensitivity
of the predicted PK parameters toward
the dissolution profiles of FP, different hypothetical dissolution
profiles were created (Figure ). In the cases where the dissolution–time curves differed
from the SLF profile only in terms of faster or slower initial rate
(cases two and three), a similar shape parameter described the exponential
curves (b ≈ 1). Fitting of an immediate release
type hypothetical dissolution profile (case one) resulted in a value
describing a sigmoidal curve (b ≫ 1). Calculated
values of AUC for the cases were similar to the values generated for
SLF, which reflect the fixing of the cumulative percentage of dissolved
FP to 9.34% in 4 h. Differences were observed in terms of Cmax and Tmax with
profiles when drug dissolution was faster/slower than in vitro dissolution profile of FP in SLF. Dissolution profiles mimicking
the faster dissolution rates (case one and case two) predicted higher
values of Cmax (6- and 2-fold), and lower
values of Tmax (6- and 4-fold) compared
to the values observed in SLF.
Figure 7
Sensitivity testing using numerical approximation
to derive three
dissolution profiles that vary from the experimental observations
for dissolution of fluticasone in SLF (observed): a profile where
release greatly exceeded that observed experimentally in SLF (case
1) and two profiles that are similar to dissolution SLF but initially
more rapid (case 2) or slower (case 3).
Sensitivity testing using numerical approximation
to derive three
dissolution profiles that vary from the experimental observations
for dissolution of fluticasone in SLF (observed): a profile where
release greatly exceeded that observed experimentally in SLF (case
1) and two profiles that are similar to dissolution SLF but initially
more rapid (case 2) or slower (case 3).
Discussion
The use of different dissolution
media in the DissolvIt dissolution assay was investigated.
A PEO-based medium is used as
the “standard” solvent for the DissolvIt system and possesses a lipid content of 4 mg/mL, which was lower
than that of SLF (5.4 mg/mL; Figure a). Survanta is a lung surfactant extract concentrate
and was diluted (1:5 with water) to normalize the lipid concentration
to that of PEO. PEO has no biological relevance beyond providing a
viscosity that could be regarded as analogous to that provided by
respiratory mucus in the airways.[39] The
slower appearance of FP in the perfusate when using SLF compared to
PEO or Survanta may reflect slower dissolution or greater retention
of FP as a result of the drug preferentially residing or becoming
trapped within the more abundant lipid/lamellar structures in SLF,
which also contains cholesterol. Cholesterol can form tight nanodomain
complexes with DPPC, stabilizing DPPC in lipid structures in which
FP can be solubilized and retained.[40]Appearance of a low-soluble inhalant in perfusate or plasma is
a serial process of dissolution in lung lining fluid followed by diffusion
through the air-to-blood barrier. The second step is controlled by
barrier thickness and lipid content and distribution within the barrier.
While the mathematics of transport in such two-phase heterogeneous
barriers was established decades ago,[41,42] the concept
was later investigated for lipophilic toxicants in the airway lining
layer.[43] By adding a small amount of surfactant
to an aqueous model of the airway lining layer, the penetration of
lipophilic benzo(a)pyrene through the experimental barrier was greatly
reduced.[44] Thus, a higher content of disperse
lipids SLF would be expected to reduce penetration of lipophilic drugs.Although the simulations in this study were based entirely on human
parameters, including the ratio of central/peripheral aerosol deposition,
the ex vivo rat IPL model was used as a comparator
for experimentally determined dissolution–permeation profiles.
The PreciseInhale system provides the advantage of a common delivery
platform that can be used to deliver accurate dose and identical respirable
aerosol fractions from the pMDI to the in vitro dissolution
apparatus and ex vivo model. The concentration of
FP and cumulative proportion of FP in the perfusate was significantly
higher at nearly all time points following administration to the rat
IPL compared to DissolvIt. The higher rate of absorptive
clearance was attributed to the IPL possessing a comparatively rapid
peripheral (alveolar) dissolution–permeation component in addition
to slower central (airway) dissolution–permeation. In contrast,
the DissolvIt system is hypothesized to model better
the dissolution and absorptive clearance mechanisms in the central
airways. In the central regions of the lungs, nonsink conditions may
be expected as the dose is distributed over a smaller area compared
to the alveolar region, and dissolved FP molecules are required to
diffuse across the 5–20 μm pseudostratified epithelium,
compared to 1–2 μm in the alveoli of the lungs, to reach
the perfusate.[17] The DissolvIt system possesses an effective dissolution area of 0.95 cm2, and the penetration distance is approximately 60 μm. Despite
being an ex vivo nonhuman model, the IPL is an adaptable
tool for teasing out the contributions of dissolution and permeation
in different regions of the lungs to drug absorption and local exposure.As FP exhibits dissolution rate-limited absorption from the lungs
of humans,[31,45] modeling was carried out to understand
the sensitivity of simulated plasma concentration–time profiles
of inhaled FP to dissolution profiles. When faster dissolution rates
compared to the values observed in SLF were modeled (Figure ), the higher predicted higher
values of Cmax and lower values of Tmax were obtained as a result of higher drug
concentration in solution during the early stages of the dissolution
process. Where the initial rate of in vitro dissolution
was lower than that in SLF, a lower Cmax and higher Tmax value were predicted.
This showed clearly the ability of the developed PBPK model to respond
to the differences in the in vitro dissolution profiles
and translate the differences to the respective PK parameters despite
the rapid peripheral dissolution and absorption implied by the IPL
studies being unaccounted. These results illustrate how dissolution
profiles can have significant impact on the PK parameters of a poorly
soluble inhaled drug and demonstrate the application of biorelevant in vitro assays together with PBPK modeling.
Conclusion
We report the development of experimental methods
for performing
biorelevant dissolution studies for orally inhaled products illustrated
by a study into the impact of the dissolution of FP, an archetypal
poorly soluble inhaled drug, on plasma pharmacokinetics when the drug
was delivered using Flixotide. The in silico model
was able to translate the in vitro data for FP dissolution
in the lungs into impacts on physiologically relevant simulated plasma
concentration–time profiles. This approach can lead to enhanced
understanding regarding how dissolution processes of inhaled poorly
soluble drugs may influence absorptive clearance from the lungs.
Authors: Kyuhan Kim; Siyoung Q Choi; Zachary A Zell; Todd M Squires; Joseph A Zasadzinski Journal: Proc Natl Acad Sci U S A Date: 2013-07-30 Impact factor: 11.205
Authors: Abhinav Kumar; Wachirun Terakosolphan; Mireille Hassoun; Kalliopi-Kelli Vandera; Astrid Novicky; Richard Harvey; Paul G Royall; Elif Melis Bicer; Jonny Eriksson; Katarina Edwards; Dirk Valkenborg; Inge Nelissen; Dave Hassall; Ian S Mudway; Ben Forbes Journal: Pharm Res Date: 2017-05-30 Impact factor: 4.200
Authors: Tushar Saha; Shubhra Sinha; Rhodri Harfoot; Miguel E Quiñones-Mateu; Shyamal C Das Journal: Pharmaceutics Date: 2022-07-08 Impact factor: 6.525