Supplementary Material for:
Translating Human Effective Jejunal Intestinal Permeability to SurfaceDependent Intrinsic Permeability: a Pragmatic Method for a More
Mechanistic Prediction of Regional Oral Drug Absorption
Andrés Olivares-Morales1 (andres.olivaresmorales@manchester.ac.uk ), Hans
Lennernäs2(hans.lennernas@farmaci.uu.se ), Leon Aarons1(leon.aarons@manchester.ac.uk ) and
Amin Rostami-Hodjegan (amin.rostami@manchester.ac.uk )1,3.
1
Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, The University of
Manchester, Manchester, UK.
2
Department of Pharmacy, Uppsala University, Uppsala, Sweden
3
Certara, Blades Enterprise Centre, Sheffield, UK.
1
Table of contents
1. Non-linear regression for the data reported by Wilson (1967) ................................................... 3
2. Estimated segmental SA for the reference human intestine ....................................................... 4
3. Recalculation of the regional Peff values from their original references ..................................... 5
3.1 Triamcinolone acetonide and hydrocortisone (Schedl 1965) ............................................... 5
3.2 Hydrochlorothiazide, atenolol, furosemide, cimetidine and salicylic acid (Sutcliffe et al,
1988) ........................................................................................................................................... 6
3.3 Griseofulvin, ranitidine, paracetamol and talinolol (Gramatté, et al. 1994-1996) ................ 7
4. mSAT model development ......................................................................................................... 9
4.1 Structure of the mSAT model ............................................................................................... 9
4.2 Optimization of the small intestinal transit time for the mSAT model............................... 10
4.3 Comparison of the mSAT model with alternative transit models....................................... 11
5. Regional fabs predictions from the mSAT model for solution and MR formulation. ................ 15
6. Method for the application of the Peff,int approach to current mechanistic absorption models . 17
7. References ................................................................................................................................. 20
2
1. Non-linear regression for the data reported by Wilson (1967)
The data form Wilson’s work (1) was digitized using GetData Graph Digitizer v2.26
(http://getdata-graph-digitizer.com/) and fitted by an exponential model. This fitting was
performed by using the using the “lsqnonlin” function of the Optimization Toolbox within
Matlab 2014a (The Mathworks Inc., Natick, MA, USA). This process minimize the objective
function (objfun) described below, by using ordinary least squares (OLS)
n
objfun   (obs ( x)  y pred ( x, p )) 2
n 1
Equation 1
where, ypred(x,p) is the model prediction for a given x and a vector of parameters, p. The function
lsqnonlin finds the set of parameters (p) that minimize Equation 1. The result of the fitting is
shown in in Figure S1
Figure S1. Nonlinear fit of an exponential model to Wilson’s (1967) data (black solid circles).
The solid black line is the regression line; the dashed redline is the 95% confidence interval (CI);
3
and the dashed blue line represents the 95% prediction intervals (PI). The precision (CV) of the
coefficients, λ1 and λ2, was found to be 0.66% and 35%, respectively.
2. Estimated segmental SA for the reference human intestine
Table S 1. Segmental mSA estimated by the three different methods for a reference man.
Segment
Length
(cm)
Radius
(cm)
Duodenum
Jejunum
Ileum
Total SI (1)
Ascending Colon
Total Colon (2)
Total Intestine(1+2)
53.66
248.16
368.89
670.7
16.69
104.34
775.04
2.37
1.75
1.50
2.42
2.42
-
M1
7.99×102
2.73×103
3.48×103
7.00×103
2.54×102
1.59×103
8.59×103
mSA
(cm2)
M2
1.76×105
4.49×105
1.60×105
7.85×105
1.62×103
1.02×104
7.95×105
Volume
(cm3)
M3
7.50×104
5.19×105
3.86×105
9.80×105
1.62×103
1.02×104
9.90×105
9.47×102
2.39×103
2.61×103
3.07×102
1.92×103
-
4
3. Recalculation of the regional Peff values from their original references
3.1 Triamcinolone acetonide and hydrocortisone (Schedl 1965)
The absorption data informed by Schedl(2) was expressed in terms of the percentage absorbed or
fraction absorbed (fabs) from the given test segment (Equation 2)
f abs  1 
Cout
 PEGratio
Cin
Equation 2
where, Cout and Cin are the concentrations of drug leaving and entering the test segment,
respectively; PEGratio is the ratio of the non-absorbable marker, polyethylene glycol (PEG),
entering and leaving the test segment. This ratio was employed to correct the concentration for
any changes due to the net fluid transfer in the segment (absorption or secretion). Thus, the fluidcorrected concentration ratio (
Cout '
) can be defined as shown in Equation 3
Cin
Cout ' Cout

 PEGratio
Cin
Cin
Equation 3
This ratio was employed for the calculation of the regional absorption clearance (CLabs,i ) and
(Peff,i) according to Equation 4 and Equation 5, respectively.
5
CLabs ,i  Qin ln(
Cout '
)
Cin
Equation 4
Peff ,i  Qinln(
Cout '
1
)
Cin
SA
Equation 5
Qin was informed as 0.25 mL/s; the surface area (SA) term in Equation 5 can be either the
cylindrical SA or the mucosal SA (mSAT) in the test segment, calculated as described in the
methods section of the manuscript.
3.2 Hydrochlorothiazide, atenolol, furosemide, cimetidine and salicylic acid (Sutcliffe et al,
1988)
The absorption data informed by Sutcliffe and co-workers (3), was expressed in terms of the
drug lost (percentage ) from the intestinal segment. This was assumed as the percentage of drug
absorbed or fabs in the given segment. The values reported were corrected by fluid movements (
net secretion or reabsorption).This was determined by the use of a non-absorbable marker (PEG
4000). The calculations of CLabs,i and Peff,i, for each drug and each segment, were performed as
described above, using the reported Qin of 0.0833 mL/s.
6
3.3 Griseofulvin, ranitidine, paracetamol and talinolol (Gramatté, et al. 1994-1996)
The absorption data informed in the works by Gramatté, and co-workers (4-7), differs from the
data informed in the previous studies. In this case the reported absorption is expressed in term of
the net absorption rate (Δabs,
drug)
[µg (Li min)-1], where Li is the length of the test segment
employed during the perfusion experiment. The mass balance equation employed for such
calculations is described by Equation 6(8)
 abs ,drug  QinCin  Qout Cout
Equation 6
where, and Cin and Cout represent the drug concentrations entering and leaving the test segment,
respectively; Qin and Qout are the corresponding drug flow rates entering and leaving the test
segment, determined according to Equation 7 and Equation 8
Qin  Inf
[ PEG ] perf
[ PEG ] p
 Sp
Equation 7
Qout  Qin
[ PEG ] p
[ PEG ]d
Equation 8
where, Inf is the perfusate infusion rate (mL/min); [PEG]perf, [PEG]p, and [PEG]d are the
corresponding PEG concentrations in the perfusate, proximal, and distal collection ports of the
test segment; Sp is the sampling rate (mL/min) from the proximal collection port of the test
7
segment. By rearranging Equation 6 and combination with Equation 3 and Equation 8, the fluid
transfer-corrected concentration ratio (
Cout '
) can be derived (Equation 9),
Cin

Cout ' Cout

PEGratio  1  abs ,drug
Cin
Cin
QinCin
Equation 9
where, the denominator in the right hand side of Equation 9(QinCin) is the informed drug’s
perfusion rate. This ratio is needed to estimate CLabs,i and Peff,i , as per Equation 4 and Equation
5. For ranitidine, the perfusion rate [µg (Li min)-1] was not informed in the original reference (6),
therefore this was assumed as the informed initial perfusion rate (ml/s), multiplied by the drug
nominal concentration in the perfusate .
8
4. mSAT model development
4.1 Structure of the mSAT model
The mSAT model describes the gastrointestinal (GI) tract by means of five compartments. These
compartments are meant to represent the anatomical segments of the GI tract that are relevant for
drug absorption: stomach, duodenum, jejunum, ileum and ascending colon. A schematic
representation of the mSAT model is shown in Figure S2.
Figure S2. Schematic representation of the minimal Segment Absorption and Transit (mSAT)
model representing the human GI tract by five consecutive compartments: stomach, the small
intestine ( duodenum(duo), jejunum(jej) and ileum(ile)), and the large intestine ( ascending
colon). A detailed explanation of the model and model parameters can be found in the material
and methods section of the manuscript.
9
4.2 Optimization of the small intestinal transit time for the mSAT model
The intestinal transit time data form Yu and co-workers (9) was digitized using GetData Graph
Digitizer v2.26 (http://getdata-graph-digitizer.com/) and fitted simultaneously by the system of
differential equations shown in Equation 10.
dAduo
  kt ,duo (t )  Aduo
dt
dA jej
 kt ,duo (t )  Aduo  kt , jej (t )  A jej
dt
dAile
 kt , jej (t )  A jej  kt ,ile (t )  Aile
dt
dAcol
 kt ,ile (t )  Aile
dt
Equation 10
This system describes the transit of particles in along the small intestine where,
  t 
kt ,n (t )    
n  n 
 1
, is the segment-specific (and time dependent) transit rate between the
intestinal segments; β is the Weibull shape parameter, and αn is a the segment-dependent scale
parameter. The scale parameter was defined for the nth small intestinal segment as,
an  fn  SITT   ; where, fn is the fractional length of the intestinal segment (with respect to the
total length of the small intestine, Lsi); SITT, is the mean intestinal transit time, assumed as 199
min (9) ; and γ is a proportionality coefficient (assumed the same for all the segments) .The
fitting was performed following the same procedure as the one described for the fitting of
Wilson’s data , this time the estimated parameters were β and γ. The coefficients, β and γ, were
10
found to be 2.01 and 1.57, and the coefficients of variation (CV) associated to the parameter
estimates were relatively low, 5.6% and 2.90%, for β and γ, respectively.
4.3 Comparison of the mSAT model with alternative transit models
The ability to describe the SITT data of the mSAT model was contrasted with that of different
transit models. All the parameters employed for the mSAT transit model (Weibull), and the
alternative models, are described in
Table S2. The evaluated alternative models are described below:
1. The traditional compartmental transit model described by Yu and co-workers (CAT)(9).
This model describes the mean intestinal transit by series of 7 transit compartments, each
one with the same mean residence time (MRT). For this model a first order transfer rate
is assumed. The transit rate constant, kt, is assumed to be the same for all the transit
compartments and is defined as: kt = 7/SITT (9).
2. A similar model to the one described above but, instead of seven intestinal transit
compartments, the transit was described by only three compartments. For each intestinal
compartment the transit rate constant (kt) was given by 3/SITT.
11
The third model evaluated was similar to model described previously. However, the main
difference was the treatment of the transit rate constant between each intestinal compartment,
this was given by kt,n = (fn×SITT)-1, where, fn is the fractional length of the intestinal segment.
The fractional lengths of the duodenum, jejunum and ileum were assumed as 0.08, 0.37, and
0.55, respectively (
Table S2
Table S2). Therefore the MRT for each segment was assumed as 16, 74, and 109 minutes, for the
duodenum, jejunum and ileum, respectively.
The description of the SITT data by the different models is shown in Error! Reference source
not found.. Both the Weibull transit model and the full CAT model adequately described the
SITT data (9). The alternative transit models, on the other hand, tended to overestimate the
amount of drug reaching the colon prior to the first 210 minutes, while underestimating it from
after that time. Therefore the Weibull transit model was implemented in the full mSAT model.
12
Figure S3. Comparison between different small-intestinal transit models to describe SITT data.
The lines represent the cumulative fraction of dose reaching the colon for the different small
intestinal transit models. Red solid line, mSAT model (Weibull transfer between segments); dotdashed cyan line, full CAT model (seven transit compartments); dashed blue line, CAT model
with only three compartments ( same first-order rate constant for all the segments); Dotted green
line, CAT model only three compartments, where the transit was fractionally divided for each
segment ( based on the segment’s length). The solid dots are the observed cumulative percentage
of the dose reaching the colon, as per reference (9).
For a given dose, the simulated mass transfer along different intestinal segment of the mSAT
model in shown in Error! Reference source not found.
13
Figure S 4. Simulated mass transfer along the intestinal segments of the mSAT model. The lines
indicate the percentage of the dose in each segment as a function of time. Dashed blue line,
duodenum; dotted green line, jejunum; solid red line, ileum; and dot-dashed cyan line, colon.
The solid dots are the observed cumulative percentage of the dose reaching the colon, as per
reference (9).
Table S2. Physiological input parameters for the mSAT model.
Parameter
Value
Reference
14
Degrees of flatness (DF)
Stomach
Gastric emptying time
(rate constant, kge)
1.7
(10)
0.25 h
(4 h-1)
(11)
670.7 cm
3.32 h
(12)
(9)
0.08
2.37 cm
(13)
(13)
0.37
1.75 cm
(13)
(14)
0.55
1.50 cm
(13)
(14)
Colon
Total colonic length (Lcol)
104.34
See main
text
Ascending colon
Fractional length (facol)
Radius(racol)
Transit rate constant (kcol)
0.16
2.42 cm
0.0667 h-1
(13, 15)
(16)
(17)
Small intestine
Length (Lsi)
Mean intestinal transit time (SITT)
Duodenum
Fractional length (fduo)
Radius (rduo)
Jejunum
Fractional length (fjej)
Radius (rjej)
Ileum
Fractional length (file)
Radius (rile)
15
5. Regional fabs predictions from the mSAT model for solution and MR formulation.
Figure S5. Bar chart of the simulated overall and regional fabs using the mSAT model and the
permeability values from Table II (in the manuscript), when colonic absorption was allowed.
Each bar represent a different method for the estimation of the absorption (M1, M2, and M3),
whereas the shades of grey indicate the proportional contribution to the fabs from each intestinal
segment described in the mSAT model.
16
Figure S6. Bar chart of the simulated overall and regional fabs using the mSAT model and the
permeability values from Table II (in manuscript) for a hypothetical CR formulation, when
colonic absorption was allowed. Each bar represent a different method for the estimation of the
absorption (M1, M2, and M3), whereas the shades of grey indicate the proportional contribution
to the fabs from each intestinal segment described in the mSAT model.
17
6. Method for the application of the Peff,int approach to current mechanistic absorption
models
A simple method to apply the principles derived in this work to any multi-compartmental
intestinal absorption model (similar to the CAT model or any of its derivations) is described
below (18, 19).
To calculate Peff,int from Peff data the following steps are required:
Peff ,int 
Peff  SALoc  I Gut
mSALoc  I Gut

Peff  2  rjej  LLoc  I Gut
2  rjej  LLoc  I Gut  SAEFjejunum

Peff
SAEFjejunum
where SAEFjejunum, is the combined surface area expansion factor (SAEF) due to all the structures
that increase surface area in the upper jejunum (circular folds, intestinal villi and microvilli).
Using Peff,int and the available mSA, the intestinal drug absorption from any segment (n) of the
human intestine, can be estimated as follows:
Peff
Peff
dAn
mSAn
2  rn  Ln  SAEFn


 An  

 An  ...
dt
SAEF jejunum
Vn
SAEF jejunum
  rn 2  Ln

2  Peff
rn
where
SAEFn
 An
SAEF jejunum
dA
is the drug absorption rate in the nth intestinal segment, mSA is the segment’s mucosal
dt
surface area, and Vn is the segment’s cylindrical volume. The expression
2  Peff
rn
represents the
traditional segment-dependent absorption rate constant (ka,n), which is employed in the CAT
model and its derivations (18, 19). On the other hand, the ratio
SAEFn
can be readily derived
SAEFjejunum
18
from the data presented in this work, where M3 showed the to be the best for the prediction of
intestinal absorption (20). Therefore, by multiplying Peff by the aforementioned segmentdependent SAEF ratios, an estimate of regional intestinal permeability can be obtained. The
ratios are summarized in Table S3(derived from the data recently published by Helander and
Fandriks (20)).
Table S3. Mean (± standard deviation (SD)*) regional surface area expansion factors for
Method 3a
Segment
Duodenum
Jejunum
Ileum
Ascending colon
Circular
folds
1.57
1.57
1.57
-
Intestinal
villi
6.5 ± 0.87b
8.6 ± 1.77b
4.5 ± 0.49c
-
Microvilli
9.2 ± 4.11b
14.1 ± 6.75b
15.7 ± 2.20c
6.4 ± 2.69c
Combined
SAEFd
93.89 ± 27.92
190.38 ± 63.19
110.92 ± 12.55
6.4 ± 2.69
SAEF ratiod
(Segment/Jejunum)
0.49 ± 0.22
1.00 ± 0.47
0.58 ± 0.20
0.033 ± 0.018
*In the original reference the error data was informed as standard error of the mean (SEM), this
SD
SEM 
n
was converted to SD using the standard formula:
a
Expansion factors were extracted from reference (20).
b
based on 5 samples.
c
based on 6 samples.
d
SD calculated using standard propagation of error formulas (21).
Consequently, by applying the segmental SAEF ratios (Table S3) to the jejunal Peff values for the
drugs listed in Table II of the manuscript, a segmental Peff can be obtained, as shown in
Table S4. In addition, by performing Monte Carlo simulations using the derived SD for the
aforementioned SAEF ratio, an estimate of the variability around the regional Peff estimates can
be obtained (assuming a lognormal distribution), product of the variability of the SAEF ratios
applied. However, it should be kept in mind that these SAEF values were derived from a limited
19
number of samples and that the variability of the Peff values themselves is not accounted by the
SAEF values.
Table S4. Estimated mean regional Peff values (double balloon technique) for the drugs listed in
Table II using the SAEF method.
Compound
Mean regional intestinal effective permeability (Peff)a
(cm/h)
Duodenum
Jejunum
Ileum
Enalaprilat
0.039
0.079
Furosemide
0.054
0.11
Terbutaline
0.089
0.18
Atenolol
0.094
0.19
Metoprolol
0.27
0.54
Propranolol
0.48
0.97
Fluvastatin
0.50
1.01
Antipyrine
1.00
2.02
Naproxen
1.42
2.88
Ketoprofen
1.51
3.06
a
Jejunal Peff values extracted from reference (18).
0.046
0.064
0.10
0.11
0.31
0.57
0.59
1.18
1.68
1.78
Colon
0.0027
0.0037
0.0061
0.0064
0.018
0.033
0.034
0.068
0.10
0.10
20
Intestinal surface area, permeability and absorption: Supplementary material
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