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Citation: Dannhorn, A.; Kazanc, E.;
Hamm, G.; Swales, J.G.; Strittmatter,
N.; Maglennon, G.; Goodwin, R.J.A.;
Takats, Z. Correlating Mass
Spectrometry Imaging and Liquid
Chromatography-Tandem Mass
Spectrometry for Tissue-Based
Pharmacokinetic Studies. Metabolites
2022,12, 261. https://doi.org/
10.3390/metabo12030261
Academic Editor: Georgios
Theodoridis
Received: 14 February 2022
Accepted: 11 March 2022
Published: 18 March 2022
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metabolites
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Article
Correlating Mass Spectrometry Imaging and Liquid
Chromatography-Tandem Mass Spectrometry for
Tissue-Based Pharmacokinetic Studies
Andreas Dannhorn 1,2 , Emine Kazanc 1, Gregory Hamm 2, John G. Swales 2, Nicole Strittmatter 2,
Gareth Maglennon 3, Richard J. A. Goodwin 2,4 and Zoltan Takats 1,5,6,*
1Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK;
andreas.dannhorn1@astrazeneca.com (A.D.); e.kazanc17@imperial.ac.uk (E.K.)
2Imaging & Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca,
Cambridge CB4 0WG, UK; gregory.hamm@astrazeneca.com (G.H.); john.swales@astrazeneca.com (J.G.S.);
nicole.strittmatter@tum.de (N.S.); richard.goodwin@astrazeneca.com (R.J.A.G.)
3Oncology Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, UK;
garethadam.maglennon@astrazeneca.com
4Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences,
University of Glasgow, Glasgow G12 8TA, UK
5Laboratoire PRISM, Inserm U1192, University of Lille, Villeneuve d’Ascq, 59655 Lille, France
6The Rosalind Franklin Institute, Harwell OX11 0QG, UK
*Correspondence: z.takats@imperial.ac.uk
Abstract:
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a standard tool used
for absolute quantification of drugs in pharmacokinetic (PK) studies. However, all spatial information
is lost during the extraction and elucidation of a drugs biodistribution within the tissue is impossible.
In the study presented here we used a sample embedding protocol optimized for mass spectrometry
imaging (MSI) to prepare up to 15 rat intestine specimens at once. Desorption electrospray ionization
(DESI) and matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI)
were employed to determine the distributions and relative abundances of four benchmarking com-
pounds in the intestinal segments. High resolution MALDI-MSI experiments performed at 10
µ
m
spatial resolution allowed to determine the drug distribution in the different intestinal histological
compartments to determine the absorbed and tissue bound fractions of the drugs. The low tissue
bound drug fractions, which were determined to account for 56–66% of the total drug, highlight the
importance to understand the spatial distribution of drugs within the histological compartments of a
given tissue to rationalize concentration differences found in PK studies. The mean drug abundances
of four benchmark compounds determined by MSI were correlated with the absolute drug concen-
trations. Linear regression resulted in coefficients of determination (R
2
) ranging from 0.532 to 0.926
for MALDI-MSI and R
2
values ranging from 0.585 to 0.945 for DESI-MSI, validating a quantitative
relation of the imaging data. The good correlation of the absolute tissue concentrations of the bench-
mark compounds and the MSI data provides a bases for relative quantification of compounds within
and between tissues, without normalization to an isotopically labelled standard, provided that the
compared tissues have inherently similar ion suppression effects.
Keywords: DESI; MALDI; mass spectrometry imaging; DMPK; drug absorption; tissue imaging
1. Introduction
Quantification of drugs present in tissue samples by liquid chromatography followed
by tandem mass spectrometry (LC-MS/MS) is a standard tool in pharmacokinetics and
drug distribution studies [
1
–
3
]. The ability to use standardized sample preparation and
analysis protocols make liquid chromatography-tandem mass spectrometry (LC-MS/MS)
analysis quantitative and reproducible. However, the results always represent the average
Metabolites 2022,12, 261. https://doi.org/10.3390/metabo12030261 https://www.mdpi.com/journal/metabolites
Metabolites 2022,12, 261 2 of 14
concentration values for the entire analyzed specimen and all spatial information is lost
in the tissue homogenization step during sample preparation. Mass spectrometry imag-
ing (MSI) allows qualitative and quantitative, multiplexed detection of xenobiotics [
4
–
8
]
and endogenous small metabolites, lipids and peptides present in tissue sections [
9
,
10
].
Recent studies demonstrate near cellular resolution analysis allowing to resolve small
morphological tissue features [
11
–
13
]. The achievable high spatial resolution enables to fol-
low the distribution of endogenous metabolites and xenobiotics into small morphological
tissue compartments. The impact of high spatial resolution imaging could be demon-
strated in studies evaluating blood-brain barrier permeation in rodents [
14
] or studying
the distribution of endogenous metabolites and xenobiotics along the villi-crypt axis in rat
intestines [15]
. Laser capture microdissection (LCM) in conjunction with LC-MS/MS quan-
tification of drugs in the dissected tissues has been described as an alternative technique
leveraging the sensitivity and robustness of LC-MS/MS based drug quantification whilst
adding a spatial dimension to the data. However, whilst literature reports indicate higher
sensitivity compared to MALDI-MSI [
16
], LCM-LC-MS/MS has not found widespread use
for the determination of drug distributions and is preferentially used to evaluate changes
in the proteome or transcriptome of tissues in the context of drug treatment [
17
,
18
]. The
low uptake of the LCM approach is likely based on the complexity of the protocols and the
need for specialized equipment.
Absolute quantification is achieved in MS experiments by normalizing the abundance
of a given analyte to the abundance of an isotopically labelled standard with known con-
centration and use of a typically linear calibration function to derive the concentration
value. For such experiments, the isotopically labelled standard needs to be homogenously
distributed inside the sample. Since it is not possible for solid samples, the best approxi-
mation for MALDI-MSI experiments is to mix the standard into the matrix solution and
spray-deposit on the samples [
7
]. Analogously, spray-deposition of labelled standards
has been used for the absolute quantification in DESI-MSI experiments [
19
]. Translation
of the normalized abundances is most commonly achieved through integration against
tissue homogenates spiked with the analyte of interest [
4
] or disposition of a dilution
series onto control tissue sections [
5
]. In contrast, relative quantitation is often achieved
by comparing the relative abundances of a compound in different tissues or histological
compartments. When performing relative quantification of analytes across various tissues,
the use of a homogenously deposited labelled standard seems advisable as ion suppression
effects can vary considerably between tissues [
20
]. As the use of isotopically labelled
standards cannot be evenly distributed inside tissue samples for the absolute quantifica-
tion of endogenous metabolites or drugs during the early development phases, relative
quantification if often performed without the use of any internal standard to compensate
for local ion suppression effects. In the present study we aimed to compare the results of
LC-MS/MS quantification and MSI to study the distribution and absorption of four orally
co-administered drugs (terfenadine, losartan, dextromethorphan and diphenhydramine) in
the rat intestine. To facilitate the sample preparation, we applied our published sample
embedding and preparation protocol [
21
] to prepare 15 intestine specimens for MSI analysis
simultaneously. The spatial distributions of the cassette-dosed drugs within the specimens
were determined by desorption electrospray ionization-(DESI) and matrix-assisted laser
desorption/ionization-(MALDI) MSI. To evaluate the quantitative relation of the MSI data,
the mean drug abundances, determined by MSI, were correlated with the absolute concen-
trations determined by LC-MS/MS analysis. In contrast to LC-MS/MS based quantification,
high resolution MSI, performed at 10
µ
m spatial resolution, offered the ability to precisely
localize the drug disposition within the intestinal morphological features and to precisely
determine location and rate of drug absorption. The additional information about the
spatial distribution of drugs within the specimen could also be leveraged to differentiate
between the absorbed drug fraction and the residue remaining in the intestinal lumen.
Metabolites 2022,12, 261 3 of 14
2. Results
The intestine is a complex organ consisting of multiple morphological compartments
such as the muscularis, submucosa, the mucosa with the mucosal crypts and villi as well
as the intestinal lumen (Figure 1). Whilst high resolution MSI allows to determine the
spatial distribution of analytes and in correlation with small morphological features such
as mucosal villi, homogenization and extraction of the drugs for LC-MS/MS analysis
destroy the tissue morphology and retrospective linkage of the determined concentrations
to distinct compartments is impossible.
Metabolites 2022, 12, x FOR PEER REVIEW 3 of 15
differentiate between the absorbed drug fraction and the residue remaining in the intesti-
nal lumen.
2. Results
The intestine is a complex organ consisting of multiple morphological compartments
such as the muscularis, submucosa, the mucosa with the mucosal crypts and villi as well
as the intestinal lumen (Figure 1). Whilst high resolution MSI allows to determine the spa-
tial distribution of analytes and in correlation with small morphological features such as
mucosal villi, homogenization and extraction of the drugs for LC-MS/MS analysis destroy
the tissue morphology and retrospective linkage of the determined concentrations to dis-
tinct compartments is impossible.
Figure 1. Annotated H&E scan compared to combined ion image obtained from an adjacent tissue
section analyzed by MALDI-MSI (endogenous lipids PC (34:2) [M+K]
+
(m/z 796.53) (red) and PC
(34:1) [M+K]
+
(m/z 798.54) (blue). Histological annotation on the H&E stained tissue: arrows = serosa,
outside blue line = outer muscularis, between blue and green line = inner muscularis, between green
and yellow line = submucosa, between yellow and turquoise line = mucosal crypts, within turquoise
line = mucosal villi and intestinal lumen (lu).
MSI analysis allowed to elucidate the biodistribution of the dosed drugs in the intes-
tine specimens. Both MSI techniques allowed detection of all 4 dosed drugs. Whilst ter-
fenadine, diphenhydramine and dextromethorphan were detected as [M+H]
+
species (at
m/z 472.32, 256.17 and 272.20 respectively) with either technique. Losartan was however
detected as [M+H]
+
species at m/z 423.17 by MALDI-MSI and as [M+K]
+
species at m/z
461.129 by DESI-MSI. The control sections analyzed by DESI-MSI showed little interfer-
ence through chemical background signals. Overall, the highest drug abundances were
detected at 1 h post dose followed by a decline over time. The MALDI data followed the
trend with the difference that Losartan had some chemical background for the selected
mass window on control sections. A relatively low spatial resolution of 75 µm was chosen
for the performed DESI-MSI experiments as it allowed to analyze each slide, holding 15
specimens, in an overnight experiment of approximately 12 h (Figure 2a).
Figure 1.
Annotated H&E scan compared to combined ion image obtained from an adjacent tissue
section analyzed by MALDI-MSI (endogenous lipids PC (34:2) [M+K]
+
(m/z796.53) (red) and PC
(34:1) [M+K]
+
(m/z798.54) (blue). Histological annotation on the H&E stained tissue: arrows = serosa,
outside blue line = outer muscularis, between blue and green line = inner muscularis, between green
and yellow line = submucosa, between yellow and turquoise line = mucosal crypts, within turquoise
line = mucosal villi and intestinal lumen (lu).
MSI analysis allowed to elucidate the biodistribution of the dosed drugs in the intestine
specimens. Both MSI techniques allowed detection of all 4 dosed drugs. Whilst terfenadine,
diphenhydramine and dextromethorphan were detected as [M+H]
+
species (at m/z472.32,
256.17 and 272.20 respectively) with either technique. Losartan was however detected as
[M+H]
+
species at m/z423.17 by MALDI-MSI and as [M+K]
+
species at m/z461.129 by
DESI-MSI. The control sections analyzed by DESI-MSI showed little interference through
chemical background signals. Overall, the highest drug abundances were detected at 1 h
post dose followed by a decline over time. The MALDI data followed the trend with the
difference that Losartan had some chemical background for the selected mass window on
control sections. A relatively low spatial resolution of 75
µ
m was chosen for the performed
DESI-MSI experiments as it allowed to analyze each slide, holding 15 specimens, in an
overnight experiment of approximately 12 h (Figure 2a).
The spatial resolution of the DESI-MSI experiments demonstrated that the majority of
the drugs were in the mucosa/lumen and less in the submucosa/muscularis. However,
it does not allow to clearly distinguish between mucosal villi and the intestinal lumen
(Figure 2d). However, samples could be analyzed by MALDI-MSI with a spatial resolution
of 10
µ
m at which the differentiation between the intestinal lumen and mucosal villi was
made possible (Figure 2e).
Even though the data is limited to total concentrations, to date LC-MS/MS quan-
tification of tissue extracts remains the standard tool in drug pharmacodynamic studies
(alongside quantitative whole body autoradiography) [
22
–
24
]. Therefore LC-MS/MS was
performed to demonstrate the quantitative relationship in drug tissue concentrations and
MSI results. In agreement with the imaging data, the absolute drug concentration for all
Metabolites 2022,12, 261 4 of 14
four drugs showed overall a rapid decline from the 1 h to the 2 h post dose animals and a
slower decline for the later timepoints (Figure 2). Terfenadine shows a slower decline with
no remaining drug 4 h post dose in two out of three animals (Figure 2a). For all four drugs
the absolute intra and inter animal concentrations showed little variation with only single
specimens showing higher concentrations (Figure 3). Compared to the later time-points,
the inter animal variability 1 h post dose was much larger with around 5-fold higher for
diphenhydramine concentrations for animal 1 compared to animal 3 (Figure 3d).
Metabolites 2022, 12, x FOR PEER REVIEW 4 of 15
Figure 2. Representative spatial distribution of the cassette dosed drugs determined by DESI-MSI
and MALDI-MSI: (a) Panorama view on a whole post-DESI H&E stained slide (left) as it was ana-
lyzed in one experiment by DESI-MSI (middle) and MALDI-MSI (right). The scale bar in the DESI
insert is 2 mm wide. The spatial distribution of all four dosed drugs is shown in one representative
replicate for all timepoints in relation to endogenous species outlining the tissues. The left-hand side
of the figure shows the results of (b) DESI-MSI experiments performed with a spatial resolution of
75 µm whilst the right-hand side of the figure shows the results of (c) MADI-MSI experiments ac-
quired with a spatial resolution of 10 µm. The inserts (d,e) display the spatial distribution of dex-
tromethorphan in the highlighted tissue sections in (b,c) respectively.
The spatial resolution of the DESI-MSI experiments demonstrated that the majority
of the drugs were in the mucosa/lumen and less in the submucosa/muscularis. However,
it does not allow to clearly distinguish between mucosal villi and the intestinal lumen
(Figure 2d). However, samples could be analyzed by MALDI-MSI with a spatial resolu-
tion of 10 µm at which the differentiation between the intestinal lumen and mucosal villi
was made possible (Figure 2e).
Even though the data is limited to total concentrations, to date LC-MS/MS quantifi-
cation of tissue extracts remains the standard tool in drug pharmacodynamic studies
(alongside quantitative whole body autoradiography) [22–24]. Therefore LC-MS/MS was
performed to demonstrate the quantitative relationship in drug tissue concentrations and
MSI results. In agreement with the imaging data, the absolute drug concentration for all
four drugs showed overall a rapid decline from the 1 h to the 2 h post dose animals and a
slower decline for the later timepoints (Figure 2). Terfenadine shows a slower decline with
no remaining drug 4 h post dose in two out of three animals (Figure 2a). For all four drugs
the absolute intra and inter animal concentrations showed little variation with only single
specimens showing higher concentrations (Figure 3). Compared to the later time-points,
Figure 2.
Representative spatial distribution of the cassette dosed drugs determined by DESI-MSI
and MALDI-MSI: (
a
) Panorama view on a whole post-DESI H&E stained slide (left) as it was analyzed
in one experiment by DESI-MSI (middle) and MALDI-MSI (right). The scale bar in the DESI insert is
2 mm wide. The spatial distribution of all four dosed drugs is shown in one representative replicate
for all timepoints in relation to endogenous species outlining the tissues. The left-hand side of the
figure shows the results of (
b
) DESI-MSI experiments performed with a spatial resolution of 75
µ
m
whilst the right-hand side of the figure shows the results of (
c
) MADI-MSI experiments acquired with
a spatial resolution of 10
µ
m. The inserts (
d
,
e
) display the spatial distribution of dextromethorphan
in the highlighted tissue sections in (b,c) respectively.
In contrast, MSI data provided a spatial dimension which could be manipulated and
divided into the underlying histological tissue types [
25
,
26
]. Unsupervised, data-driven
segmentation, performed on the lipid-containing mass range between m/z750 and 850
allowed to “digitally dissect” the herein analysed intestinal sections into lumen, mucosa
and an unresolved mixture of mucosal crypts, submucosa and muscularis as identified
when compared to post-analysis haematoxylin and eosin (H&E) stained tissues (Figure 4).
The abundance information for any detected analyte such as of endogenous metabolites or
Metabolites 2022,12, 261 5 of 14
drugs could be extracted for each of the determined segments and subjected to statistical
analysis or evaluation of the tissue concentration-time profiles of the drugs.
Metabolites 2022, 12, x FOR PEER REVIEW 5 of 15
the inter animal variability 1 h post dose was much larger with around 5-fold higher for
diphenhydramine concentrations for animal 1 compared to animal 3 (Figure 3d).
Figure 3. Pharmacokinetic profiles of the drug tissue concentrations for (a) terfenadine, (b) losartan,
(c) dextromethorphan and (d) diphenhydramine for the different time points post-dosing obtained
by LC-MS/MS analysis. The data is presented as individual marker for the technical replicates and
mean ± SD of the animal. As the sample collection was terminal, animals 1–3 represent three differ-
ent animals for each timepoint except for animal 2, 2 h post dose as one of the specimens was lost
during the extraction process. One specimen from Animal 2, 4 h post dose was excluded as it ex-
ceeded the upper limit of the calibration range.
In contrast, MSI data provided a spatial dimension which could be manipulated and
divided into the underlying histological tissue types [25,26]. Unsupervised, data-driven
segmentation, performed on the lipid-containing mass range between m/z 750 and 850
allowed to “digitally dissect” the herein analysed intestinal sections into lumen, mucosa
and an unresolved mixture of mucosal crypts, submucosa and muscularis as identified
when compared to post-analysis haematoxylin and eosin (H&E) stained tissues (Figure
4). The abundance information for any detected analyte such as of endogenous metabo-
lites or drugs could be extracted for each of the determined segments and subjected to
statistical analysis or evaluation of the tissue concentration-time profiles of the drugs.
Figure 3.
Pharmacokinetic profiles of the drug tissue concentrations for (
a
) terfenadine,
(b) losartan
,
(c) dextromethorphan
and (
d
) diphenhydramine for the different time points post-dosing obtained
by LC-MS/MS analysis. The data is presented as individual marker for the technical replicates
and
mean ±SD
of the animal. As the sample collection was terminal, animals 1–3 represent three
different animals for each timepoint except for animal 2, 2 h post dose as one of the specimens was
lost during the extraction process. One specimen from Animal 2, 4 h post dose was excluded as it
exceeded the upper limit of the calibration range.
Metabolites 2022, 12, x FOR PEER REVIEW 6 of 15
Figure 4. Extraction of the region-specific drug abundances in the different morphological features
of the intestine: (a) The H&E stained tissue shows the typical morphology of a representative intes-
tine section. (b) Shows the tissue outline determined by MALDI-MSI performed on an adjacent tis-
sue section (endogenous lipids PC (34:2) [M+K]
+
(m/z 796.53) (red) and PC (34:1) [M+K]
+
(m/z 798.54)
(blue). (c) Shows the relative localization of dextromethorphan (m/z 272.20) within the tissue. (d)
Shows the result of the spatial segmentation bisecting K-means clustering of the tissue performed
on features detected between m/z 750 to 850. Yellow = intestinal lumen, blue = mucosa and red =
unresolved mixture of mucosal crypts, submucosa and muscularis respectively.
Extraction of the abundances of the four dosed drugs in the different segments of the
intestine allow to compare tissue exposure-time profiles in the different morphological
compartments of the intestine (Figure 5). The luminal tissue abundances follow a time
profile as expected after oral dosing, with rapid initial uptake manifesting in the rapid
decline between one and two hours post dosing and lower flux rates with decreasing lu-
minal drug concentrations. Both, losartan and dextromethorphan show an plateau, or
even increase, of the abundance in the lumen between two and four hours post dosing.
This is likely the result of active excretion of the unmetabolized drugs into the bile and re-
entering into the intestine as art of the enterohepatic recycling. The abundance-time pro-
files of the four drugs in the mucosa follow overall the drug abundances in the intestinal
lumen. The high degree of correlation between these two compartments highlights the
diffusion-driven, passive uptake of the drugs into the tissues. Interestingly, the tissue
abundances in the outermost segment, which was comprised of mucosal crypts, submu-
cosa and muscularis, showed overall similar profiles, albeit at much lower levels. The pro-
files show highest variability at datapoints closest to t
max
which appears to be prior to the
1 h post dose datapoint for terfenadine, dextromethorphan and diphenhydramine. How-
ever, losartan was detected with highest abundance at 2 h post dose (Figure 5b).
Figure 4.
Extraction of the region-specific drug abundances in the different morphological fea-
tures of the intestine: (
a
) The H&E stained tissue shows the typical morphology of a representative
intestine section. (
b
) Shows the tissue outline determined by MALDI-MSI performed on an adja-
cent tissue section (endogenous lipids PC (34:2) [M+K]
+
(m/z796.53) (red) and PC (34:1) [M+K]
+
(
m/z798.54
) (blue). (
c
) Shows the relative localization of dextromethorphan (m/z272.20) within the
tissue.
(d) Shows
the result of the spatial segmentation bisecting K-means clustering of the tissue
performed on features detected between m/z750 to 850. Yellow = intestinal lumen, blue = mucosa
and red = unresolved mixture of mucosal crypts, submucosa and muscularis respectively.
Metabolites 2022,12, 261 6 of 14
Extraction of the abundances of the four dosed drugs in the different segments of the
intestine allow to compare tissue exposure-time profiles in the different morphological
compartments of the intestine (Figure 5). The luminal tissue abundances follow a time
profile as expected after oral dosing, with rapid initial uptake manifesting in the rapid
decline between one and two hours post dosing and lower flux rates with decreasing
luminal drug concentrations. Both, losartan and dextromethorphan show an plateau, or
even increase, of the abundance in the lumen between two and four hours post dosing.
This is likely the result of active excretion of the unmetabolized drugs into the bile and
re-entering into the intestine as art of the enterohepatic recycling. The abundance-time
profiles of the four drugs in the mucosa follow overall the drug abundances in the intestinal
lumen. The high degree of correlation between these two compartments highlights the
diffusion-driven, passive uptake of the drugs into the tissues. Interestingly, the tissue
abundances in the outermost segment, which was comprised of mucosal crypts, submucosa
and muscularis, showed overall similar profiles, albeit at much lower levels. The profiles
show highest variability at datapoints closest to t
max
which appears to be prior to the 1 h
post dose datapoint for terfenadine, dextromethorphan and diphenhydramine. However,
losartan was detected with highest abundance at 2 h post dose (Figure 5b).
Metabolites 2022, 12, x FOR PEER REVIEW 7 of 15
Figure 5. Abundance-time profiles of the four dosed drugs in the resolved tissue segments for (a)
terfenadine, (b) losartan, (c) dextromethorphan and (d) diphenhydramine. Data is presented as
mean ± SD of the nine intestinal segments analysed for each timepoint. The datapoint for the vehicle
at T0 shows the mean background noise signal for the respective drug.
The spatial information provided by the MSI analysis, could also be leveraged to es-
timate the drug fractions in the lumen and the absorbed drug fraction which was detected
in the tissue (Table 1). This approach estimated the mean absorbed fraction of the drugs
to range from 56% for terfenadine up to 66% for Losartan (Table 1). The high variability
in the absorbed drug fraction was found to be primarily based on differences in the
amount of drug-containing bowel content present in the specimens, depending on the
thoroughness when removing the bowel content during necropsy. The interfering effect
of the bowel content in the present study is analogous to the commonly observed contam-
ination of tissues with blood, measuring drugs from the circulation [27,28] rather than
pure tissue concentrations. Such interferences highlight the value of spatially resolved
MSI experiments to enable precise localization of the drugs within even small morpho-
logical features of the tissue. The understanding of the drug distribution within the tissue
can help to build better understanding of a compound’s PK properties and draw the cor-
rect conclusions from extract-based quantification approaches.
Table 1. The absorbed fraction of the four different drugs. The drug abundance of the tissue was
extracted from the combined blue and red clusters seen in the spatial clustering. The data is pre-
sented as mean ± SD and range of all analyzed specimens. The individual values for each specimen
can be found in Supplementary Figure S2.
Absorbed Drug Fraction [%]
Drug Mean ± SD Min Max
Terfenadine 56 ± 23 8 89
Losartan 66 ± 24 12 93
Dextromethorphan 57 ± 22 10 92
Diphenhydramine 64 ± 21 18 93
Figure 5.
Abundance-time profiles of the four dosed drugs in the resolved tissue segments for
(a) terfenadine
, (
b
) losartan, (
c
) dextromethorphan and (
d
) diphenhydramine. Data is presented as
mean ±SD
of the nine intestinal segments analysed for each timepoint. The datapoint for the vehicle
at T0shows the mean background noise signal for the respective drug.
The spatial information provided by the MSI analysis, could also be leveraged to
estimate the drug fractions in the lumen and the absorbed drug fraction which was detected
in the tissue (Table 1). This approach estimated the mean absorbed fraction of the drugs to
range from 56% for terfenadine up to 66% for Losartan (Table 1). The high variability in the
absorbed drug fraction was found to be primarily based on differences in the amount of
drug-containing bowel content present in the specimens, depending on the thoroughness
when removing the bowel content during necropsy. The interfering effect of the bowel
content in the present study is analogous to the commonly observed contamination of
tissues with blood, measuring drugs from the circulation [
27
,
28
] rather than pure tissue
Metabolites 2022,12, 261 7 of 14
concentrations. Such interferences highlight the value of spatially resolved MSI experiments
to enable precise localization of the drugs within even small morphological features of
the tissue. The understanding of the drug distribution within the tissue can help to build
better understanding of a compound’s PK properties and draw the correct conclusions
from extract-based quantification approaches.
Table 1.
The absorbed fraction of the four different drugs. The drug abundance of the tissue was
extracted from the combined blue and red clusters seen in the spatial clustering. The data is presented
as mean
±
SD and range of all analyzed specimens. The individual values for each specimen can be
found in Supplementary Figure S2.
Absorbed Drug Fraction [%]
Drug Mean ±SD Min Max
Terfenadine 56 ±23 8 89
Losartan 66 ±24 12 93
Dextromethorphan 57 ±22 10 92
Diphenhydramine 64 ±21 18 93
A comparison was performed between the concentrations determined by LC-MS/MS
and the mean tissue abundances determined by DESI-MSI and MALDI-MSI respectively
to validate the visual agreement between the absolute concentrations and the ion images
obtained by MSI (Figure 6). For the linear regression, the concentration of each specimen
was compared to the mean tissue abundance of the corresponding section analyzed by
MSI. The data for all timepoints and replicates was pooled for the comparison to include a
wide range of tissue concentrations. The correlation of datasets obtained by using different
techniques can give interesting insights into the underlying analytical phenomena. A
positive shift of the x-axis intercept indicates a lower limit of detection (LOD) and lower
limit of quantification (LLOQ) of the technique plotted on the x-axis, whilst a positive shift
of the y-axis intercept indicates a lower LOD and LLOQ of the technique plotted on the
y-axis. When using raw data without baseline removal, a positive shift of the intercept
can be caused by unspecific background signals or chemical background as it is the case
for the data reported below. This will be reflected in a shift of the LOD. The slope of
the linear regression line will reflect the sensitivity of either method, with a 45
◦
angle
describing a “perfect” correlation in which both techniques have the same response factors.
A deviation indicates different sensitivities for the compared techniques. The coefficients
of determination (R
2
) describes the variance in the data explained by the correlation. It is
effectively a measure for the deviation of the data points from the regression line and can
indicate a deviation from a linear relationship or hint towards the presence of outlier in the
data when the computed R2values are low.
Overall, both techniques showed a comparable correlation between the drug abun-
dances determined by MSI and the absolute drug concentration across all samples deter-
mined by LC-MS/MS. Both imaging techniques had a strong correlation for terfenadine
(Figure 6a,e) and diphenhydramine (Figure 6d,h) with R
2
values ranging between 0.886
and 0.945. Dextromethorphan showed a slightly lower correlation with R
2
values of 0.636
for MALDI and 0.789 for DESI-MSI respectively (Figure 6c,g). Only losartan showed just
a moderate correlation (R
2
= 0.532 for MALDI and R
2
= 0.585 for DESI respectively) due
to the low sensitivity for the drug with either imaging technique (Figure 6b,f). The low
sensitivity for losartan arose from a poor detection of the compound with either MSI tech-
nique, but particularly for MALDI-MSI where numerous data points fall between the LOD
and LLOQ, which is reflected in the large variance of the data. The limited sensitivity for
the drug was also reflected in the large 95% confidence interval (CI) of the regression lines
for either technique, especially in the higher concentration range where a limited number
of datapoints defined the regression line. The correlation between tissue concentrations
and the MSI data proves a basis to use the MSI data for relative quantification of the drugs
Metabolites 2022,12, 261 8 of 14
within and between specimens even without spray-depositing internal standard across the
slide to compensate for local ion suppression effects. Some datapoints deviate substantially
from the regression lines. These outliers were often inconsistent between the different
benchmark compounds, even within the same tissue section, limiting the likelihood of
these being systematic artefacts of sample preparation or analysis. Furthermore, the same
pattern can be seen between the two imaging modalities, which provide independent data
obtained from separate sections. Even though efforts were made to match the specimen
fragments used for LC-MS/MS quantification and those used to generate thin sections
for MSI analysis as much as possible, several millimeters can be between the analyzed
specimens. We attributed some of the observed variation to differences in the analyte
distribution in the intestines and thus analyzed specimen.
Metabolites 2022, 12, x FOR PEER REVIEW 8 of 15
A comparison was performed between the concentrations determined by LC-MS/MS
and the mean tissue abundances determined by DESI-MSI and MALDI-MSI respectively
to validate the visual agreement between the absolute concentrations and the ion images
obtained by MSI (Figure 6). For the linear regression, the concentration of each specimen
was compared to the mean tissue abundance of the corresponding section analyzed by
MSI. The data for all timepoints and replicates was pooled for the comparison to include
a wide range of tissue concentrations. The correlation of datasets obtained by using dif-
ferent techniques can give interesting insights into the underlying analytical phenomena.
A positive shift of the x-axis intercept indicates a lower limit of detection (LOD) and lower
limit of quantification (LLOQ) of the technique plotted on the x-axis, whilst a positive shift
of the y-axis intercept indicates a lower LOD and LLOQ of the technique plotted on the y-
axis. When using raw data without baseline removal, a positive shift of the intercept can
be caused by unspecific background signals or chemical background as it is the case for
the data reported below. This will be reflected in a shift of the LOD. The slope of the linear
regression line will reflect the sensitivity of either method, with a 45° angle describing a
“perfect” correlation in which both techniques have the same response factors. A devia-
tion indicates different sensitivities for the compared techniques. The coefficients of de-
termination (R2) describes the variance in the data explained by the correlation. It is effec-
tively a measure for the deviation of the data points from the regression line and can in-
dicate a deviation from a linear relationship or hint towards the presence of outlier in the
data when the computed R2 values are low.
Figure 6. Comparison of drug tissue concentrations (terfenadine (a,d), losartan (b,f), dextrome-
thorphan (c,g), diphenhydramine (d,h)) determined by LC-MS/MS and MALDI-MSI (a–d) and
DESI-MSI (e–h), respectively. Each datapoint describes the measured data for one of the three intes-
tinal segments that were analyzed for each animal. Relative abundances for MSI data are repre-
sented by the mean abundance of the whole tissue section. — Indicate best-fit linear regression lines
… indicate the 95% confidence interval of the regression lines -·-indicate the LOD for the respective
MSI technique --- indicate the LLOQ for the respective imaging technique.
Overall, both techniques showed a comparable correlation between the drug abun-
dances determined by MSI and the absolute drug concentration across all samples deter-
mined by LC-MS/MS. Both imaging techniques had a strong correlation for terfenadine
(Figure 6a,e) and diphenhydramine (Figure 6d,h) with R2 values ranging between 0.886
and 0.945. Dextromethorphan showed a slightly lower correlation with R2 values of 0.636
for MALDI and 0.789 for DESI-MSI respectively (Figure 6c,g). Only losartan showed just
a moderate correlation (R2 = 0.532 for MALDI and R2 = 0.585 for DESI respectively) due to
the low sensitivity for the drug with either imaging technique (Figure 6b,f). The low sen-
sitivity for losartan arose from a poor detection of the compound with either MSI tech-
nique, but particularly for MALDI-MSI where numerous data points fall between the LOD
and LLOQ, which is reflected in the large variance of the data. The limited sensitivity for
Figure 6.
Comparisonof drugtissue concentrations(terfenadine (
a
,
d
), losartan (
b
,
f
),
dextromethorphan (c,g)
,
diphenhydramine (
d
,
h
)) determined by LC-MS/MS and MALDI-
MSI (a–d)
and DESI-
MSI (e–h)
,
respectively. Each datapoint describes the measured data for one of the three intestinal segments
that were analyzed for each animal. Relative abundances for MSI data are represented by the mean
abundance of the whole tissue section. — Indicate best-fit linear regression lines
. . .
indicate the 95%
confidence interval of the regression lines -
·
- indicate the LOD for the respective MSI technique —
indicate the LLOQ for the respective imaging technique.
A correlation analysis between the relative abundances for the four drugs was per-
formed to further delineate differences in the data obtained with the two MSI techniques
(Figure 7). The data obtained by the two MSI techniques is in good agreement for dex-
tromethorphan and diphenhydramine with R
2
values of 0.892 and 0.866 respectively.
Dextromethorphan showed a noticeable right shift of the x-axis intercept from the ori-
gin, highlighting a lower LOD for the compound by MALDI-MSI (Figure 7). Terfenadine
showed a slightly lower agreement between the two techniques with an R2value of 0.767.
As for the correlation of the drug tissue concentration and the imaging data, losartan
showed the lowest agreement between the two MSI techniques with an R
2
value of 0.554.
As seen above, either MSI technique seemed to have a limited sensitivity for the drug
under the analytical conditions. The noticeable positive shift of the y-intercept away from
the origin indicating increased chemical background for the compound by MALDI-MSI
(Figure 7b). Overall, both techniques showed comparable performance for the accuracy of
the obtained data, with slight deviation based on preferential desorption/ionization under
the specific analytical conditions dictated by the two techniques. The data obtained with
either technique shows a sufficient correlation with the underlying tissue concentrations to
justify “digital dissection” of the tissues and use of the extracted abundances for relative
quantification of analytes without the use of an isotopically labelled standard, as long as
the chosen spatial resolution allows to resolve the underlying morphological features in
a tissue.
Metabolites 2022,12, 261 9 of 14
Metabolites 2022, 12, x FOR PEER REVIEW 10 of 15
Figure 7. Correlation of the average drug abundances as detected by DESI-MSI and MALDI-MSI for
(a) terfenadine, (b) Losartan, (c) dextromethorphan and (d) diphenhydramine. — Indicate best-fit
linear regression lines … indicate the 95% confidence interval of the regression lines –·-indicate the
LOD for the respective MSI technique --- indicate the LLOQ for the respective imaging technique.
3. Discussion
We successfully co-embedded and prepared multiple intestine specimens which en-
abled simultaneous preparation of up to 15 specimens per mold, significantly reducing
the time required to process the samples without interfering with a quantitative evalua-
tion of the results. All samples analyzed in an experiment were prepared at the same time
and under the same conditions, reducing the possibility of time-course effects due to an-
alyte degradation/alteration observed when samples remain in the cryostat for extended
periods of time. Preservation of the tissue morphology allowed to use the obtained tissue
sections for high resolution MSI experiments and histological evaluation. Both, DESI-MSI
and MALDI-MSI performed overall comparably good, albeit DESI-MSI had a tendency to
show better sensitivity and lower limits of detection for the benchmarking compounds
used in this work The correlation between MSI and absolute drug concentrations demon-
strates minimal interference through the manipulation of the tissues during the embed-
ding process and allows determination of accurate, quantitative results. The correlation
also proves the basis for MSI-based relative quantification of the data after segmentation
of the resulting distribution maps into the underlying morphological tissue compart-
ments. Significantly, the correlation remains if the chemical composition of the different
morphological compartments is not vastly different. This justifies the relative quantifica-
tion of endogenous metabolites or of drug candidates during early development within
and between comparable tissues without normalization to an isotopically labelled stand-
ard. However, fundamental changes in the chemical composition of tissues are likely to
result in drastic changes in local ion suppression effects, distorting the elucidated biodis-
tributions. This becomes particularly important when performing relative quantification
across multiple tissue types or vastly different models, in which case the use of an isotop-
ically labelled standard should be considered to ensure delivery of accurate results. The
presented work also builds a foundation for a systematic evaluation of the changes in local
ion suppression effects based on differences in the chemical composition of the tissues.
Determination of intra- and inter-organ changes in ion suppression and consequences for
the segmentation of biodistributions will be explored in future studies, including evalua-
tion of normalization and compensation strategies.
Figure 7.
Correlation of the average drug abundances as detected by DESI-MSI and MALDI-MSI for
(
a
) terfenadine, (
b
) Losartan, (
c
) dextromethorphan and (
d
) diphenhydramine. — Indicate best-fit
linear regression lines
. . .
indicate the 95% confidence interval of the regression lines -
·
- indicate the
LOD for the respective MSI technique — indicate the LLOQ for the respective imaging technique.
3. Discussion
We successfully co-embedded and prepared multiple intestine specimens which en-
abled simultaneous preparation of up to 15 specimens per mold, significantly reducing the
time required to process the samples without interfering with a quantitative evaluation of
the results. All samples analyzed in an experiment were prepared at the same time and
under the same conditions, reducing the possibility of time-course effects due to analyte
degradation/alteration observed when samples remain in the cryostat for extended pe-
riods of time. Preservation of the tissue morphology allowed to use the obtained tissue
sections for high resolution MSI experiments and histological evaluation. Both, DESI-MSI
and MALDI-MSI performed overall comparably good, albeit DESI-MSI had a tendency
to show better sensitivity and lower limits of detection for the benchmarking compounds
used in this work The correlation between MSI and absolute drug concentrations demon-
strates minimal interference through the manipulation of the tissues during the embedding
process and allows determination of accurate, quantitative results. The correlation also
proves the basis for MSI-based relative quantification of the data after segmentation of the
resulting distribution maps into the underlying morphological tissue compartments. Signif-
icantly, the correlation remains if the chemical composition of the different morphological
compartments is not vastly different. This justifies the relative quantification of endoge-
nous metabolites or of drug candidates during early development within and between
comparable tissues without normalization to an isotopically labelled standard. However,
fundamental changes in the chemical composition of tissues are likely to result in drastic
changes in local ion suppression effects, distorting the elucidated biodistributions. This
becomes particularly important when performing relative quantification across multiple
tissue types or vastly different models, in which case the use of an isotopically labelled
standard should be considered to ensure delivery of accurate results. The presented work
also builds a foundation for a systematic evaluation of the changes in local ion suppression
effects based on differences in the chemical composition of the tissues. Determination of
intra- and inter-organ changes in ion suppression and consequences for the segmentation
of biodistributions will be explored in future studies, including evaluation of normalization
and compensation strategies.
Metabolites 2022,12, 261 10 of 14
4. Materials and Methods
4.1. Chemicals
Polyvinylpyrrolidone (PVP) (MW 360 kDa), (Hydroxypropyl)-methylcellulose (HPMC)
(viscosity 40–60 cP, 2% in H
2
O (20
◦
C)), 2,5-dihydroxybenzoic acid (DHB), trifluoroacetic
acid (TFA), terfenadine, terfenadine-d3, dextromethorphan hydrobromide, dextromethorp
han-d3, diphenhydramine hydrochloride and diphenhydramine-d3 were purchased from
Merck (Darmstadt, Germany). Methanol, water, iso-pentane (2-Methyl-butane), isopropanol
and acetonitrile (ACN) were obtained from Fisher Scientific (Waltham, MA, USA). Losartan-
potassium salt was obtained from Cambridge Bioscience (Cambridge, UK). Losartan-d4
was purchased from Toronto Research Chemicals (Toronto, ON, Canada). All solvents used
were of analytical grade or higher.
4.2. Animals and Dosing
Adult male Han Wistar rats (approximate weight 260 g) were obtained from Charles
River Laboratories (Margate, Kent, UK) and were acclimatized on site for a minimum
of 3 days prior to dosing. Compounds were administered by oral gavage as cassette of
terfenadine, losartan, diphenhydramine and dextromethorphan, formulated in 5% dimethyl
sulfoxide/95% (30% w/vCaptisol in water). Animals were dosed with 25 mg/kg/drug
and euthanized at 1, 2, 4 or 6 h post-dosing. Vehicle control animals were euthanized at the
latest sampling time at 6 h post dose. The first 20 cm of the small intestine were cut into
four pieces each and snap frozen free-floating in dry ice chilled isopentane. For each animal,
3 intestine pieces were randomly selected for this study. The pieces were each split into
half, one half was extracted for LC-MS/MS quantification, the other half was embedded
and subject to MSI analysis. All tissue dissection was performed by trained AstraZeneca
staff (project license 40/3484, procedure number 10).
4.3. Preparation of Intestine Specimens for MSI Analysis
The specimens were embedded and prepared according to a previously reported
sample preparation workflow [
21
]. Briefly, the intestine specimens were co-embedded in
a (Hydroxypropyl)-methylcellulose (HPMC) + Polyvinylpyrrolidone (PVP) hydrogel to
enable time-efficient sectioning under comparable conditions for all specimens analyzed in
one experiment. A total of 15 specimens was placed upright in peel-a-way molds (Thermo
Scientific, Waltham, MA, USA) pre-filled with ice-cold embedding medium. Snap freezing
of the filled mold was performed in dry ice-chilled isopropanol followed by a wash in dry
ice chilled iso-pentane to wash off the excess of isopropanol. The frozen molds were kept
on dry ice to allow evaporation of the adherent iso-pentane before they were sectioned
on a cryostat. Sections of 10
µ
m thickness were cut at
−
18
◦
C and thaw mounted on
either SuperFrost (Thermo Scientific, Waltham, MA, USA) or ITO coated (Bruker Daltonik,
Bremen, Germany) slides for DESI or MALDI experiments respectively. To preserve the
analyte integrity, samples were desiccated under nitrogen immediately after the thaw
mounting, packed in vacuum-sealed slide mailer and stored in a
−
80
◦
C freezer until
analysis [29].
4.4. DESI-MSI
Analysis was performed on a Q-Exactive mass spectrometer (Thermo Scientific,
Bremen
, Germany) equipped with an automated 2D-DESI ion source (Prosolia Inc., Indi-
anapolis, IN, USA) operated in positive ion mode between m/z100 to 900 with a nominal
mass resolution of 70,000 at m/z200. The injection time was fixed to 50 ms resulting in a
scan rate of 3.7 pixel/s. A home-built DESI sprayer [
30
] was operated with a mixture of 95%
methanol, 5% water delivered with a flow rate of 1.5
µ
L/min and nebulized with nitrogen
at a backpressure of 6 bar. The spatial resolution was set to 75
µ
m. The resulting .raw
files were converted into mzML files using ProteoWizard msConvert [
31
] (
version 3.0.4043
)
and subsequently compiled to an .imzML file (imzML converter [
32
] version 1.3). All
subsequent data processing was performed in SCiLS Lab (version 2019b, Bruker Daltonik,
Metabolites 2022,12, 261 11 of 14
Bremen, Germany). The LOD and LLOQ for the four drugs were calculated 3
×
and 10
×
the standard deviation of the abundance of the respective mass filter of each drug across
the vehicle tissues.
4.5. MALDI-MSI
Analysis was performed on a RapifleX Tissuetyper instrument (Bruker Daltonik, Bre-
men, Germany) operated in positive ion mode using 2,5-Dihydroxybenzoic acid (DHB) pre-
pared in 50:50:0.1 ACN:water:TFA and spray deposited using an automated spray system
(HTX technologies, Chapel Hill, NC, USA) following a previously reported
protocol [33]
.
Drug distribution studies on intestines were performed with a spatial resolution of 10
µ
m
in the mass range between m/z200 and 1000. A total of 100 laser shots were summed
up per pixel to give the final spectra. For all experiments the laser was operated with a
repetition rate of 10 kHz. All raw data was directly uploaded and processed in FlexImaging
(Bruker Daltonik, Bremen, Germany) or SCiLS lab software packages (Version 2019b). All
reported MALDI data and images were normalized to the total ion current (TIC) to compen-
sate for spectrum-to-spectrum variation [
34
]. The tissue segmentation for the estimation
of the absorbed drug fraction were performed using bisecting k-means clustering using
the build-in function in SCiLS lab with correlation distance as metric. The segmentation
was performed using peaks in the mass range between m/z750 and 850 which contains
structural lipids outlining the morphological features of the intestine and the output maps
visually compared to the underlying histology. The LOD and LLOQ for the four drugs
were calculated 3
×
and 10
×
the standard deviation of the abundance of the respective
mass filter of each drug across the vehicle tissues.
4.6. LC-MS/MS Sample Preparation and Analysis
Tissues were weighed into extraction tubes and 15
µ
L of mixed deuterium-labeled
drugs prepared in acetonitrile (ACN) (1
µ
mol/L/drug) were added as internal standards
into each tube. After addition of zirconia beads and 0.75 mL ice-cold ACN, tissues were
homogenized using a tissue homogenizer (Precelllys 24, Bertin Technologies SAS, Montigny-
le-Bretonneux, France). The homogenization was performed in 3 cycles, each consisted of
45 s of shaking at 4600 rpm followed by 30 s of pause and another 45 s of shaking. To allow
samples to cool down, tubes were stored on ice for 15 min in between cycles. Samples were
centrifuged at 14,000
×
gfor 20 min under refrigeration (PrismR, Labnet international Inc.,
Edison, NJ, USA) and the supernatant was transferred into a new extraction tube. The
residue was reconstituted in 0.75 mL ice-cold ACN followed by centrifugation for 20 min
at 14,000
×
gunder refrigeration. The supernatants for each sample were pooled. Aliquots
of the supernatant were diluted 3-fold with HPLC-MS grade water and further diluted 1:10
in 25% ACN in water. Calibration standards were prepared from vehicle dosed control
specimens as described above. Appropriate concentration of the drug standards prepared
in ACN were added to the extraction tube before homogenizing the tissues. The calibration
curves used for the drug quantification can be found in the Supplementary Information
(Figure S1).
Chromatographic separation was performed on an UPLC system (Waters Corp.,
Milford
, MA, USA) equipped with a BEH C18 column (Waters, Milford, MA, USA) with the
following dimensions: 100 mm
×
2.1 mm i.d. and a particle size of 1.7
µ
m. The column was
operated at a temperature of 55
◦
C. 0.1% formic acid in water was used as aqueous mobile
phase (A) whilst ACN was used as organic phase (B). The flow rate of the mobile phase
was 0.5 mL/min throughout the gradient. 5
µ
L of each sample were injected and separated
with the following gradient: T = 0 min 5% B, 0.5 min 5% B, 0.51 min 50% B,
4.5 min
80% B,
4.51 min 99% B till T = 5 min 99% B. The approximately 2 min lasting injection cycle of the
LC system was used to re-equilibrate the column to 5% B for the next injection.
A Xevo TQ-XS (Waters, Wexford, IE) triple quadrupole instrument was used for
mass spectrometric detection. Multiple Reaction Monitoring (MRM) transitions for all
compounds were optimized on standards using IntelliStart and used as provided by the
Metabolites 2022,12, 261 12 of 14
software (Table 2). The other instrument settings were used as followed: capillary voltage:
3.5 kV (+ve), nebulizing gas 1200 L/h, desolvation temperature 350 ◦C, cone gas 150 L/h.
Table 2.
MRM transitions for the drugs and respective internal standards. The peak area of the
quantifier trace was used for the quantification whilst the qualifier trace was used to verify the
identity of the integrated peak.
Quantifier Transition Qualifier Transition
Diphenhydramine 256.3 > 167.0 256.3 > 165.0
Diphenhydramine-d3 259.3 > 167.0 259.3 > 165.1
Dextromethorphan 272.4 > 147.0 272.4 > 215.1
Dextromethorphan-d3 275.4 > 215.1 275.4 > 147.0
Losartan 423.5 > 207.0 423.5 > 179.9
Losartan-d4 427.5 > 211.1 427.5 > 184.0
Terfenadine 472.1 > 91.0 472.7 > 436.3
Terfenadine-d3 475.7 > 91.0 475.7 > 438.4
Supplementary Materials:
The following are available online at https://www.mdpi.com/article/10
.3390/metabo12030261/s1, Figure S1: Linear regression lines for the internal standard (IS) normalized
peak areas over the standard concentration; Figure S2: Individual values for the estimated absorbed
drug fractions.
Author Contributions:
Conceptualization, A.D., R.J.A.G. and Z.T.; Formal analysis, A.D. and G.M.;
Funding acquisition, R.J.A.G. and Z.T.; Investigation, A.D., E.K., G.H., G.M., J.G.S. and N.S.; Resources,
R.J.A.G. and Z.T.; Supervision, R.J.A.G. and Z.T.; Writing—original draft, A.D.; Writing—review
& editing, E.K., G.H., J.G.S., N.S., G.M., R.J.A.G. and Z.T. All authors have read and agreed to the
published version of the manuscript.
Funding:
The authors would like to thank the Biotechnology and Biological Sciences Research
Council (BBSRC) for the case funding for A.D. [BB/N504038/1] and European Research Council
Consolidator Grant “MASSLIP” for supporting the research.
Institutional Review Board Statement:
The study was conducted according to the guidelines of the
Declaration of Helsinki, and approved by the Institutional Review Board of AstraZeneca (project
license 40/3484, procedure number 10).
Informed Consent Statement: Not applicable.
Data Availability Statement:
All relevant data is represented in the manuscript or the supplementary
materials. The MSI raw data was deposited in the Imperial College London Research Data Repository
under the DOI:10.14469/hpc/10255.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or
in the decision to publish the results.
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