rxode2 automatically assigns compartment numbers when parsing. For example, with the Mavoglurant PBPK model the following model may be used:
#> rxode2 3.0.4 using 2 threads (see ?getRxThreads)
#> no cache: create with `rxCreateCache()`
pbpk <- function() {
model({
KbBR = exp(lKbBR)
KbMU = exp(lKbMU)
KbAD = exp(lKbAD)
CLint= exp(lCLint + eta.LClint)
KbBO = exp(lKbBO)
KbRB = exp(lKbRB)
## Regional blood flows
# Cardiac output (L/h) from White et al (1968)
CO = (187.00*WT^0.81)*60/1000
QHT = 4.0 *CO/100
QBR = 12.0*CO/100
QMU = 17.0*CO/100
QAD = 5.0 *CO/100
QSK = 5.0 *CO/100
QSP = 3.0 *CO/100
QPA = 1.0 *CO/100
QLI = 25.5*CO/100
QST = 1.0 *CO/100
QGU = 14.0*CO/100
# Hepatic artery blood flow
QHA = QLI - (QSP + QPA + QST + QGU)
QBO = 5.0 *CO/100
QKI = 19.0*CO/100
QRB = CO - (QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI)
QLU = QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI + QRB
## Organs' volumes = organs' weights / organs' density
VLU = (0.76 *WT/100)/1.051
VHT = (0.47 *WT/100)/1.030
VBR = (2.00 *WT/100)/1.036
VMU = (40.00*WT/100)/1.041
VAD = (21.42*WT/100)/0.916
VSK = (3.71 *WT/100)/1.116
VSP = (0.26 *WT/100)/1.054
VPA = (0.14 *WT/100)/1.045
VLI = (2.57 *WT/100)/1.040
VST = (0.21 *WT/100)/1.050
VGU = (1.44 *WT/100)/1.043
VBO = (14.29*WT/100)/1.990
VKI = (0.44 *WT/100)/1.050
VAB = (2.81 *WT/100)/1.040
VVB = (5.62 *WT/100)/1.040
VRB = (3.86 *WT/100)/1.040
## Fixed parameters
BP = 0.61 # Blood:plasma partition coefficient
fup = 0.028 # Fraction unbound in plasma
fub = fup/BP # Fraction unbound in blood
KbLU = exp(0.8334)
KbHT = exp(1.1205)
KbSK = exp(-.5238)
KbSP = exp(0.3224)
KbPA = exp(0.3224)
KbLI = exp(1.7604)
KbST = exp(0.3224)
KbGU = exp(1.2026)
KbKI = exp(1.3171)
##-----------------------------------------
S15 = VVB*BP/1000
C15 = Venous_Blood/S15
##-----------------------------------------
d/dt(Lungs) = QLU*(Venous_Blood/VVB - Lungs/KbLU/VLU)
d/dt(Heart) = QHT*(Arterial_Blood/VAB - Heart/KbHT/VHT)
d/dt(Brain) = QBR*(Arterial_Blood/VAB - Brain/KbBR/VBR)
d/dt(Muscles) = QMU*(Arterial_Blood/VAB - Muscles/KbMU/VMU)
d/dt(Adipose) = QAD*(Arterial_Blood/VAB - Adipose/KbAD/VAD)
d/dt(Skin) = QSK*(Arterial_Blood/VAB - Skin/KbSK/VSK)
d/dt(Spleen) = QSP*(Arterial_Blood/VAB - Spleen/KbSP/VSP)
d/dt(Pancreas) = QPA*(Arterial_Blood/VAB - Pancreas/KbPA/VPA)
d/dt(Liver) = QHA*Arterial_Blood/VAB + QSP*Spleen/KbSP/VSP +
QPA*Pancreas/KbPA/VPA + QST*Stomach/KbST/VST +
QGU*Gut/KbGU/VGU - CLint*fub*Liver/KbLI/VLI - QLI*Liver/KbLI/VLI
d/dt(Stomach) = QST*(Arterial_Blood/VAB - Stomach/KbST/VST)
d/dt(Gut) = QGU*(Arterial_Blood/VAB - Gut/KbGU/VGU)
d/dt(Bones) = QBO*(Arterial_Blood/VAB - Bones/KbBO/VBO)
d/dt(Kidneys) = QKI*(Arterial_Blood/VAB - Kidneys/KbKI/VKI)
d/dt(Arterial_Blood) = QLU*(Lungs/KbLU/VLU - Arterial_Blood/VAB)
d/dt(Venous_Blood) = QHT*Heart/KbHT/VHT + QBR*Brain/KbBR/VBR +
QMU*Muscles/KbMU/VMU + QAD*Adipose/KbAD/VAD + QSK*Skin/KbSK/VSK +
QLI*Liver/KbLI/VLI + QBO*Bones/KbBO/VBO + QKI*Kidneys/KbKI/VKI +
QRB*Rest_of_Body/KbRB/VRB - QLU*Venous_Blood/VVB
d/dt(Rest_of_Body) = QRB*(Arterial_Blood/VAB - Rest_of_Body/KbRB/VRB)
})
}
If you look at the printout, you can see where rxode2 assigned the compartment number(s)
pbpk <- pbpk()
print(pbpk)
#> -- rxode2-based free-form 16-cmt ODE model -------------------------------------
#>
#> States ($state or $stateDf):
#> Compartment Number Compartment Name
#> 1 1 Lungs
#> 2 2 Heart
#> 3 3 Brain
#> 4 4 Muscles
#> 5 5 Adipose
#> 6 6 Skin
#> 7 7 Spleen
#> 8 8 Pancreas
#> 9 9 Liver
#> 10 10 Stomach
#> 11 11 Gut
#> 12 12 Bones
#> 13 13 Kidneys
#> 14 14 Arterial_Blood
#> 15 15 Venous_Blood
#> 16 16 Rest_of_Body
#> -- Model (Normalized Syntax): --
#> function() {
#> model({
#> KbBR = exp(lKbBR)
#> KbMU = exp(lKbMU)
#> KbAD = exp(lKbAD)
#> CLint = exp(lCLint + eta.LClint)
#> KbBO = exp(lKbBO)
#> KbRB = exp(lKbRB)
#> CO = (187 * WT^0.81) * 60/1000
#> QHT = 4 * CO/100
#> QBR = 12 * CO/100
#> QMU = 17 * CO/100
#> QAD = 5 * CO/100
#> QSK = 5 * CO/100
#> QSP = 3 * CO/100
#> QPA = 1 * CO/100
#> QLI = 25.5 * CO/100
#> QST = 1 * CO/100
#> QGU = 14 * CO/100
#> QHA = QLI - (QSP + QPA + QST + QGU)
#> QBO = 5 * CO/100
#> QKI = 19 * CO/100
#> QRB = CO - (QHT + QBR + QMU + QAD + QSK + QLI + QBO +
#> QKI)
#> QLU = QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI +
#> QRB
#> VLU = (0.76 * WT/100)/1.051
#> VHT = (0.47 * WT/100)/1.03
#> VBR = (2 * WT/100)/1.036
#> VMU = (40 * WT/100)/1.041
#> VAD = (21.42 * WT/100)/0.916
#> VSK = (3.71 * WT/100)/1.116
#> VSP = (0.26 * WT/100)/1.054
#> VPA = (0.14 * WT/100)/1.045
#> VLI = (2.57 * WT/100)/1.04
#> VST = (0.21 * WT/100)/1.05
#> VGU = (1.44 * WT/100)/1.043
#> VBO = (14.29 * WT/100)/1.99
#> VKI = (0.44 * WT/100)/1.05
#> VAB = (2.81 * WT/100)/1.04
#> VVB = (5.62 * WT/100)/1.04
#> VRB = (3.86 * WT/100)/1.04
#> BP = 0.61
#> fup = 0.028
#> fub = fup/BP
#> KbLU = exp(0.8334)
#> KbHT = exp(1.1205)
#> KbSK = exp(-0.5238)
#> KbSP = exp(0.3224)
#> KbPA = exp(0.3224)
#> KbLI = exp(1.7604)
#> KbST = exp(0.3224)
#> KbGU = exp(1.2026)
#> KbKI = exp(1.3171)
#> S15 = VVB * BP/1000
#> C15 = Venous_Blood/S15
#> d/dt(Lungs) = QLU * (Venous_Blood/VVB - Lungs/KbLU/VLU)
#> d/dt(Heart) = QHT * (Arterial_Blood/VAB - Heart/KbHT/VHT)
#> d/dt(Brain) = QBR * (Arterial_Blood/VAB - Brain/KbBR/VBR)
#> d/dt(Muscles) = QMU * (Arterial_Blood/VAB - Muscles/KbMU/VMU)
#> d/dt(Adipose) = QAD * (Arterial_Blood/VAB - Adipose/KbAD/VAD)
#> d/dt(Skin) = QSK * (Arterial_Blood/VAB - Skin/KbSK/VSK)
#> d/dt(Spleen) = QSP * (Arterial_Blood/VAB - Spleen/KbSP/VSP)
#> d/dt(Pancreas) = QPA * (Arterial_Blood/VAB - Pancreas/KbPA/VPA)
#> d/dt(Liver) = QHA * Arterial_Blood/VAB + QSP * Spleen/KbSP/VSP +
#> QPA * Pancreas/KbPA/VPA + QST * Stomach/KbST/VST +
#> QGU * Gut/KbGU/VGU - CLint * fub * Liver/KbLI/VLI -
#> QLI * Liver/KbLI/VLI
#> d/dt(Stomach) = QST * (Arterial_Blood/VAB - Stomach/KbST/VST)
#> d/dt(Gut) = QGU * (Arterial_Blood/VAB - Gut/KbGU/VGU)
#> d/dt(Bones) = QBO * (Arterial_Blood/VAB - Bones/KbBO/VBO)
#> d/dt(Kidneys) = QKI * (Arterial_Blood/VAB - Kidneys/KbKI/VKI)
#> d/dt(Arterial_Blood) = QLU * (Lungs/KbLU/VLU - Arterial_Blood/VAB)
#> d/dt(Venous_Blood) = QHT * Heart/KbHT/VHT + QBR * Brain/KbBR/VBR +
#> QMU * Muscles/KbMU/VMU + QAD * Adipose/KbAD/VAD +
#> QSK * Skin/KbSK/VSK + QLI * Liver/KbLI/VLI + QBO *
#> Bones/KbBO/VBO + QKI * Kidneys/KbKI/VKI + QRB * Rest_of_Body/KbRB/VRB -
#> QLU * Venous_Blood/VVB
#> d/dt(Rest_of_Body) = QRB * (Arterial_Blood/VAB - Rest_of_Body/KbRB/VRB)
#> })
#> }
You can also see this with the classic rxode2 model. In that case you
use the summary()
function:
pbpk <- pbpk$simulationModel
#> using C compiler: 'gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0'
summary(pbpk)
#> rxode2 3.0.4 model named rx_5ad3248c4a48650cb7e8ed5203e31a4a model (ready).
#> DLL: /tmp/RtmpYVi0z9/rxode2/rx_5ad3248c4a48650cb7e8ed5203e31a4a__.rxd/rx_5ad3248c4a48650cb7e8ed5203e31a4a_.so
#> NULL
#>
#> Calculated Variables:
#> [1] "KbBR" "KbMU" "KbAD" "CLint" "KbBO" "KbRB" "CO" "QHT" "QBR"
#> [10] "QMU" "QAD" "QSK" "QSP" "QPA" "QLI" "QST" "QGU" "QHA"
#> [19] "QBO" "QKI" "QRB" "QLU" "VLU" "VHT" "VBR" "VMU" "VAD"
#> [28] "VSK" "VSP" "VPA" "VLI" "VST" "VGU" "VBO" "VKI" "VAB"
#> [37] "VVB" "VRB" "fub" "KbLU" "KbHT" "KbSK" "KbSP" "KbPA" "KbLI"
#> [46] "KbST" "KbGU" "KbKI" "S15" "C15"
#> -- rxode2 Model Syntax --
#> rxode2({
#> param(lKbBR, lKbMU, lKbAD, lCLint, eta.LClint, lKbBO, lKbRB,
#> WT)
#> KbBR = exp(lKbBR)
#> KbMU = exp(lKbMU)
#> KbAD = exp(lKbAD)
#> CLint = exp(lCLint + eta.LClint)
#> KbBO = exp(lKbBO)
#> KbRB = exp(lKbRB)
#> CO = (187 * WT^0.81) * 60/1000
#> QHT = 4 * CO/100
#> QBR = 12 * CO/100
#> QMU = 17 * CO/100
#> QAD = 5 * CO/100
#> QSK = 5 * CO/100
#> QSP = 3 * CO/100
#> QPA = 1 * CO/100
#> QLI = 25.5 * CO/100
#> QST = 1 * CO/100
#> QGU = 14 * CO/100
#> QHA = QLI - (QSP + QPA + QST + QGU)
#> QBO = 5 * CO/100
#> QKI = 19 * CO/100
#> QRB = CO - (QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI)
#> QLU = QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI + QRB
#> VLU = (0.76 * WT/100)/1.051
#> VHT = (0.47 * WT/100)/1.03
#> VBR = (2 * WT/100)/1.036
#> VMU = (40 * WT/100)/1.041
#> VAD = (21.42 * WT/100)/0.916
#> VSK = (3.71 * WT/100)/1.116
#> VSP = (0.26 * WT/100)/1.054
#> VPA = (0.14 * WT/100)/1.045
#> VLI = (2.57 * WT/100)/1.04
#> VST = (0.21 * WT/100)/1.05
#> VGU = (1.44 * WT/100)/1.043
#> VBO = (14.29 * WT/100)/1.99
#> VKI = (0.44 * WT/100)/1.05
#> VAB = (2.81 * WT/100)/1.04
#> VVB = (5.62 * WT/100)/1.04
#> VRB = (3.86 * WT/100)/1.04
#> BP = 0.61
#> fup = 0.028
#> fub = fup/BP
#> KbLU = exp(0.8334)
#> KbHT = exp(1.1205)
#> KbSK = exp(-0.5238)
#> KbSP = exp(0.3224)
#> KbPA = exp(0.3224)
#> KbLI = exp(1.7604)
#> KbST = exp(0.3224)
#> KbGU = exp(1.2026)
#> KbKI = exp(1.3171)
#> S15 = VVB * BP/1000
#> C15 = Venous_Blood/S15
#> d/dt(Lungs) = QLU * (Venous_Blood/VVB - Lungs/KbLU/VLU)
#> d/dt(Heart) = QHT * (Arterial_Blood/VAB - Heart/KbHT/VHT)
#> d/dt(Brain) = QBR * (Arterial_Blood/VAB - Brain/KbBR/VBR)
#> d/dt(Muscles) = QMU * (Arterial_Blood/VAB - Muscles/KbMU/VMU)
#> d/dt(Adipose) = QAD * (Arterial_Blood/VAB - Adipose/KbAD/VAD)
#> d/dt(Skin) = QSK * (Arterial_Blood/VAB - Skin/KbSK/VSK)
#> d/dt(Spleen) = QSP * (Arterial_Blood/VAB - Spleen/KbSP/VSP)
#> d/dt(Pancreas) = QPA * (Arterial_Blood/VAB - Pancreas/KbPA/VPA)
#> d/dt(Liver) = QHA * Arterial_Blood/VAB + QSP * Spleen/KbSP/VSP +
#> QPA * Pancreas/KbPA/VPA + QST * Stomach/KbST/VST + QGU *
#> Gut/KbGU/VGU - CLint * fub * Liver/KbLI/VLI - QLI * Liver/KbLI/VLI
#> d/dt(Stomach) = QST * (Arterial_Blood/VAB - Stomach/KbST/VST)
#> d/dt(Gut) = QGU * (Arterial_Blood/VAB - Gut/KbGU/VGU)
#> d/dt(Bones) = QBO * (Arterial_Blood/VAB - Bones/KbBO/VBO)
#> d/dt(Kidneys) = QKI * (Arterial_Blood/VAB - Kidneys/KbKI/VKI)
#> d/dt(Arterial_Blood) = QLU * (Lungs/KbLU/VLU - Arterial_Blood/VAB)
#> d/dt(Venous_Blood) = QHT * Heart/KbHT/VHT + QBR * Brain/KbBR/VBR +
#> QMU * Muscles/KbMU/VMU + QAD * Adipose/KbAD/VAD + QSK *
#> Skin/KbSK/VSK + QLI * Liver/KbLI/VLI + QBO * Bones/KbBO/VBO +
#> QKI * Kidneys/KbKI/VKI + QRB * Rest_of_Body/KbRB/VRB -
#> QLU * Venous_Blood/VVB
#> d/dt(Rest_of_Body) = QRB * (Arterial_Blood/VAB - Rest_of_Body/KbRB/VRB)
#> })
In this case, Venous_Blood
is assigned to compartment
15
. Figuring this out can be inconvenient and also lead to
re-numbering compartment in simulation or estimation datasets. While it
is easy and probably clearer to specify the compartment by name, other tools only
support compartment numbers. Therefore, having a way to number
compartment easily can lead to less data modification between multiple
tools.
To add the compartments to the rxode2 model in the order you desire
you simply need to pre-declare the compartments with cmt
.
For example specifying is Venous_Blood
and
Skin
to be the 1st and 2nd compartments, respectively, is
simple:
pbpk2 <- function() {
model({
## Now this is the first compartment, ie cmt=1
cmt(Venous_Blood)
## Skin may be a compartment you wish to dose to as well,
## so it is now cmt=2
cmt(Skin)
KbBR = exp(lKbBR)
KbMU = exp(lKbMU)
KbAD = exp(lKbAD)
CLint= exp(lCLint + eta.LClint)
KbBO = exp(lKbBO)
KbRB = exp(lKbRB)
## Regional blood flows
# Cardiac output (L/h) from White et al (1968)m
CO = (187.00*WT^0.81)*60/1000;
QHT = 4.0 *CO/100;
QBR = 12.0*CO/100;
QMU = 17.0*CO/100;
QAD = 5.0 *CO/100;
QSK = 5.0 *CO/100;
QSP = 3.0 *CO/100;
QPA = 1.0 *CO/100;
QLI = 25.5*CO/100;
QST = 1.0 *CO/100;
QGU = 14.0*CO/100;
QHA = QLI - (QSP + QPA + QST + QGU); # Hepatic artery blood flow
QBO = 5.0 *CO/100;
QKI = 19.0*CO/100;
QRB = CO - (QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI);
QLU = QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI + QRB;
## Organs' volumes = organs' weights / organs' density
VLU = (0.76 *WT/100)/1.051;
VHT = (0.47 *WT/100)/1.030;
VBR = (2.00 *WT/100)/1.036;
VMU = (40.00*WT/100)/1.041;
VAD = (21.42*WT/100)/0.916;
VSK = (3.71 *WT/100)/1.116;
VSP = (0.26 *WT/100)/1.054;
VPA = (0.14 *WT/100)/1.045;
VLI = (2.57 *WT/100)/1.040;
VST = (0.21 *WT/100)/1.050;
VGU = (1.44 *WT/100)/1.043;
VBO = (14.29*WT/100)/1.990;
VKI = (0.44 *WT/100)/1.050;
VAB = (2.81 *WT/100)/1.040;
VVB = (5.62 *WT/100)/1.040;
VRB = (3.86 *WT/100)/1.040;
## Fixed parameters
BP = 0.61; # Blood:plasma partition coefficient
fup = 0.028; # Fraction unbound in plasma
fub = fup/BP; # Fraction unbound in blood
KbLU = exp(0.8334);
KbHT = exp(1.1205);
KbSK = exp(-.5238);
KbSP = exp(0.3224);
KbPA = exp(0.3224);
KbLI = exp(1.7604);
KbST = exp(0.3224);
KbGU = exp(1.2026);
KbKI = exp(1.3171);
##-----------------------------------------
S15 = VVB*BP/1000;
C15 = Venous_Blood/S15
##-----------------------------------------
d/dt(Lungs) = QLU*(Venous_Blood/VVB - Lungs/KbLU/VLU);
d/dt(Heart) = QHT*(Arterial_Blood/VAB - Heart/KbHT/VHT);
d/dt(Brain) = QBR*(Arterial_Blood/VAB - Brain/KbBR/VBR);
d/dt(Muscles) = QMU*(Arterial_Blood/VAB - Muscles/KbMU/VMU);
d/dt(Adipose) = QAD*(Arterial_Blood/VAB - Adipose/KbAD/VAD);
d/dt(Skin) = QSK*(Arterial_Blood/VAB - Skin/KbSK/VSK);
d/dt(Spleen) = QSP*(Arterial_Blood/VAB - Spleen/KbSP/VSP);
d/dt(Pancreas) = QPA*(Arterial_Blood/VAB - Pancreas/KbPA/VPA);
d/dt(Liver) = QHA*Arterial_Blood/VAB + QSP*Spleen/KbSP/VSP +
QPA*Pancreas/KbPA/VPA + QST*Stomach/KbST/VST + QGU*Gut/KbGU/VGU -
CLint*fub*Liver/KbLI/VLI - QLI*Liver/KbLI/VLI;
d/dt(Stomach) = QST*(Arterial_Blood/VAB - Stomach/KbST/VST);
d/dt(Gut) = QGU*(Arterial_Blood/VAB - Gut/KbGU/VGU);
d/dt(Bones) = QBO*(Arterial_Blood/VAB - Bones/KbBO/VBO);
d/dt(Kidneys) = QKI*(Arterial_Blood/VAB - Kidneys/KbKI/VKI);
d/dt(Arterial_Blood) = QLU*(Lungs/KbLU/VLU - Arterial_Blood/VAB);
d/dt(Venous_Blood) = QHT*Heart/KbHT/VHT + QBR*Brain/KbBR/VBR +
QMU*Muscles/KbMU/VMU + QAD*Adipose/KbAD/VAD + QSK*Skin/KbSK/VSK +
QLI*Liver/KbLI/VLI + QBO*Bones/KbBO/VBO + QKI*Kidneys/KbKI/VKI +
QRB*Rest_of_Body/KbRB/VRB - QLU*Venous_Blood/VVB;
d/dt(Rest_of_Body) = QRB*(Arterial_Blood/VAB - Rest_of_Body/KbRB/VRB);
})
}
You can see this change in the simple printout
pbpk2 <- pbpk2()
pbpk2
#> -- rxode2-based free-form 16-cmt ODE model -------------------------------------
#>
#> States ($state or $stateDf):
#> Compartment Number Compartment Name
#> 1 1 Venous_Blood
#> 2 2 Skin
#> 3 3 Lungs
#> 4 4 Heart
#> 5 5 Brain
#> 6 6 Muscles
#> 7 7 Adipose
#> 8 8 Spleen
#> 9 9 Pancreas
#> 10 10 Liver
#> 11 11 Stomach
#> 12 12 Gut
#> 13 13 Bones
#> 14 14 Kidneys
#> 15 15 Arterial_Blood
#> 16 16 Rest_of_Body
#> -- Model (Normalized Syntax): --
#> function() {
#> model({
#> cmt(Venous_Blood)
#> cmt(Skin)
#> KbBR = exp(lKbBR)
#> KbMU = exp(lKbMU)
#> KbAD = exp(lKbAD)
#> CLint = exp(lCLint + eta.LClint)
#> KbBO = exp(lKbBO)
#> KbRB = exp(lKbRB)
#> CO = (187 * WT^0.81) * 60/1000
#> QHT = 4 * CO/100
#> QBR = 12 * CO/100
#> QMU = 17 * CO/100
#> QAD = 5 * CO/100
#> QSK = 5 * CO/100
#> QSP = 3 * CO/100
#> QPA = 1 * CO/100
#> QLI = 25.5 * CO/100
#> QST = 1 * CO/100
#> QGU = 14 * CO/100
#> QHA = QLI - (QSP + QPA + QST + QGU)
#> QBO = 5 * CO/100
#> QKI = 19 * CO/100
#> QRB = CO - (QHT + QBR + QMU + QAD + QSK + QLI + QBO +
#> QKI)
#> QLU = QHT + QBR + QMU + QAD + QSK + QLI + QBO + QKI +
#> QRB
#> VLU = (0.76 * WT/100)/1.051
#> VHT = (0.47 * WT/100)/1.03
#> VBR = (2 * WT/100)/1.036
#> VMU = (40 * WT/100)/1.041
#> VAD = (21.42 * WT/100)/0.916
#> VSK = (3.71 * WT/100)/1.116
#> VSP = (0.26 * WT/100)/1.054
#> VPA = (0.14 * WT/100)/1.045
#> VLI = (2.57 * WT/100)/1.04
#> VST = (0.21 * WT/100)/1.05
#> VGU = (1.44 * WT/100)/1.043
#> VBO = (14.29 * WT/100)/1.99
#> VKI = (0.44 * WT/100)/1.05
#> VAB = (2.81 * WT/100)/1.04
#> VVB = (5.62 * WT/100)/1.04
#> VRB = (3.86 * WT/100)/1.04
#> BP = 0.61
#> fup = 0.028
#> fub = fup/BP
#> KbLU = exp(0.8334)
#> KbHT = exp(1.1205)
#> KbSK = exp(-0.5238)
#> KbSP = exp(0.3224)
#> KbPA = exp(0.3224)
#> KbLI = exp(1.7604)
#> KbST = exp(0.3224)
#> KbGU = exp(1.2026)
#> KbKI = exp(1.3171)
#> S15 = VVB * BP/1000
#> C15 = Venous_Blood/S15
#> d/dt(Lungs) = QLU * (Venous_Blood/VVB - Lungs/KbLU/VLU)
#> d/dt(Heart) = QHT * (Arterial_Blood/VAB - Heart/KbHT/VHT)
#> d/dt(Brain) = QBR * (Arterial_Blood/VAB - Brain/KbBR/VBR)
#> d/dt(Muscles) = QMU * (Arterial_Blood/VAB - Muscles/KbMU/VMU)
#> d/dt(Adipose) = QAD * (Arterial_Blood/VAB - Adipose/KbAD/VAD)
#> d/dt(Skin) = QSK * (Arterial_Blood/VAB - Skin/KbSK/VSK)
#> d/dt(Spleen) = QSP * (Arterial_Blood/VAB - Spleen/KbSP/VSP)
#> d/dt(Pancreas) = QPA * (Arterial_Blood/VAB - Pancreas/KbPA/VPA)
#> d/dt(Liver) = QHA * Arterial_Blood/VAB + QSP * Spleen/KbSP/VSP +
#> QPA * Pancreas/KbPA/VPA + QST * Stomach/KbST/VST +
#> QGU * Gut/KbGU/VGU - CLint * fub * Liver/KbLI/VLI -
#> QLI * Liver/KbLI/VLI
#> d/dt(Stomach) = QST * (Arterial_Blood/VAB - Stomach/KbST/VST)
#> d/dt(Gut) = QGU * (Arterial_Blood/VAB - Gut/KbGU/VGU)
#> d/dt(Bones) = QBO * (Arterial_Blood/VAB - Bones/KbBO/VBO)
#> d/dt(Kidneys) = QKI * (Arterial_Blood/VAB - Kidneys/KbKI/VKI)
#> d/dt(Arterial_Blood) = QLU * (Lungs/KbLU/VLU - Arterial_Blood/VAB)
#> d/dt(Venous_Blood) = QHT * Heart/KbHT/VHT + QBR * Brain/KbBR/VBR +
#> QMU * Muscles/KbMU/VMU + QAD * Adipose/KbAD/VAD +
#> QSK * Skin/KbSK/VSK + QLI * Liver/KbLI/VLI + QBO *
#> Bones/KbBO/VBO + QKI * Kidneys/KbKI/VKI + QRB * Rest_of_Body/KbRB/VRB -
#> QLU * Venous_Blood/VVB
#> d/dt(Rest_of_Body) = QRB * (Arterial_Blood/VAB - Rest_of_Body/KbRB/VRB)
#> })
#> }
The first two compartments are Venous_Blood
followed by
Skin
.
You can also append “compartments” to the model. Because of the ODE solving internals, you cannot add fake compartments to the model until after all the differential equations are defined.
For example this is legal:
ode.1c.ka <- function(){
model({
C2 = center/V
d / dt(depot) = -KA * depot
d/dt(center) = KA * depot - CL*C2
cmt(eff)
})
}
ode.1c.ka <- ode.1c.ka()
print(ode.1c.ka)
#> -- rxode2-based free-form 2-cmt ODE model --------------------------------------
#>
#> States ($state or $stateDf):
#> Compartment Number Compartment Name
#> 1 1 depot
#> 2 2 center
#> -- Model (Normalized Syntax): --
#> function() {
#> model({
#> C2 = center/V
#> d/dt(depot) = -KA * depot
#> d/dt(center) = KA * depot - CL * C2
#> cmt(eff)
#> })
#> }
You can see this more clearly with the underlying classic
rxode2
model:
ode.1c.ka$simulationModel
#> using C compiler: 'gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0'
#> rxode2 3.0.4 model named rx_b4f67ca17f8fe725f7bd606f1f61e765 model (ready).
#> x$state: depot, center
#> x$stateExtra: eff
#> x$params: V, KA, CL
#> x$lhs: C2
But compartments defined before all the differential equations is not supported; So the model below:
ode.1c.ka <- rxode2({
cmt(eff)
C2 = center/V;
d / dt(depot) = -KA * depot
d/dt(center) = KA * depot - CL*C2
})
will give an error:
Error in rxModelVars_(obj) :
Evaluation error: Compartment 'eff' needs differential equations defined.