| Title: | Noncompartmental Analysis for Pharmacokinetic Data |
|---|---|
| Description: | Conduct a noncompartmental analysis with industrial strength. Some features are 1) Use of CDISC SDTM terms 2) Automatic or manual slope selection 3) Supporting both 'linear-up linear-down' and 'linear-up log-down' method 4) Interval(partial) AUCs with 'linear' or 'log' interpolation method * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107). |
| Authors: | Kyun-Seop Bae [aut] |
| Maintainer: | Kyun-Seop Bae <[email protected]> |
| License: | GPL-3 |
| Version: | 0.7.0 |
| Built: | 2024-11-16 06:39:15 UTC |
| Source: | CRAN |
It conducts a noncompartmental analysis(NCA) with industrial strength.
The main functions are
tblNCA to perform NCA for many subjects. sNCA to perform NCA for one subject.
Kyun-Seop Bae <[email protected]>
Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.
# Theoph and Indometh data: dose in mg, conc in mg/L, time in h tblNCA(Theoph, key="Subject", colTime="Time", colConc="conc", dose=320, adm="Extravascular", doseUnit="mg", concUnit="mg/L") tblNCA(Indometh, key="Subject", colTime="time", colConc="conc", dose=25, adm="Infusion", dur=0.5, doseUnit="mg", concUnit="mg/L", R2ADJ=0.9) # For individual NCA iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC x = Theoph[Theoph$Subject=="1","Time"] y = Theoph[Theoph$Subject=="1","conc"] sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h", iAUC=iAUC) sNCA(x, y, dose=320, concUnit="mg/L", iAUC=iAUC)# Theoph and Indometh data: dose in mg, conc in mg/L, time in h tblNCA(Theoph, key="Subject", colTime="Time", colConc="conc", dose=320, adm="Extravascular", doseUnit="mg", concUnit="mg/L") tblNCA(Indometh, key="Subject", colTime="time", colConc="conc", dose=25, adm="Infusion", dur=0.5, doseUnit="mg", concUnit="mg/L", R2ADJ=0.9) # For individual NCA iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC x = Theoph[Theoph$Subject=="1","Time"] y = Theoph[Theoph$Subject=="1","conc"] sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h", iAUC=iAUC) sNCA(x, y, dose=320, concUnit="mg/L", iAUC=iAUC)
Calculate Area Under the Curve(AUC) and the first Moment Curve(AUMC) in two ways; 'linear trapezoidal method' or 'linear-up and log-down' method. Return a table of cumulative values.
AUC(x, y, down = "Linear")AUC(x, y, down = "Linear")
x |
vector values of independent variable, usually time |
y |
vector values of dependent variable, usually concentration |
down |
either of |
down="Linear" means linear trapezoidal rule with linear interpolation.
down="Log" means linear-up and log-down method.
Table with two columns, AUC and AUMC; the first column values are cumulative AUCs and the second column values cumulative AUMCs.
Kyun-Seop Bae <[email protected]>
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. pp687-689. 2011.
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log")AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log")
It sequentially fits (log(y) ~ x) from the last point of x to the previous points with at least 3 points. It chooses a slope the highest adjusted R-square. If the difference is less then 1e-4, it pickes longer slope.
BestSlope(x, y, adm = "Extravascular", TOL=1e-4, excludeDelta = 1)BestSlope(x, y, adm = "Extravascular", TOL=1e-4, excludeDelta = 1)
x |
vector values of x-axis, usually time |
y |
vector values of y-axis, usually concentration |
adm |
one of |
TOL |
tolerance. See Phoneix WinNonlin 6.4 User's Guide p33 for the detail. |
excludeDelta |
Improvement of R2ADJ larger than this value could exclude the last point. Default value 1 is for the compatibility with other software. |
Choosing the best terminal slope (y in log scale) in pharmacokinetic analysis is somewhat challenging, and it could vary by analysis performer.
Pheonix WinNonlin chooses a slope with highest adjusted R-squared and the longest one. The difference of adjusted R-Squared less than TOL considered to be 0.
This function uses ordinary least square method (OLS). Author recommends to use excludeDelta option with about 0.3.
R2 |
R-squared |
R2ADJ |
adjusted R-squared |
LAMZNPT |
number of points used for slope |
LAMZ |
negative of the slope, lambda_z |
b0 |
intercept of the regression line |
CORRXY |
correlation of log(y) and x |
LAMZLL |
earliest x for lambda_z |
LAMZUL |
last x for lambda_z |
CLSTP |
predicted y value at the last point, predicted concentration for the last time point |
Kyun-Seop Bae <[email protected]>
BestSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) BestSlope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"], adm="Bolus")BestSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) BestSlope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"], adm="Bolus")
You choose a slope for terminal half-life.
DetSlope(x, y, SubTitle="", sel.1=0, sel.2=0)DetSlope(x, y, SubTitle="", sel.1=0, sel.2=0)
x |
vector values of x-axis, usually time |
y |
vector values of y-axis, usually concentration |
SubTitle |
subtitle to be shown on the plot |
sel.1 |
default index of the first element to use |
sel.2 |
default index of the last element to use |
Sometimes BestSlope cannot find terminal slope satisfactorily. Then you can use this function to choose manually. It returns the same format result with BestSlope with an attribute indicating used points.
R2 |
R-squared |
R2ADJ |
adjusted R-squared |
LAMZNPT |
number of points used for the slope |
LAMZ |
negative of the slope, lambda_z |
b0 |
intercept of the regression line |
CORRXY |
correlation of log(y) and x |
LAMZLL |
earliest x for lambda_z |
LAMZUL |
last x for lambda_z |
CLSTP |
predicted y value at the last point, predicted concentration for the last time point |
Kyun-Seop Bae <[email protected]>
DetSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) DetSlope(Indometh[Indometh$Subject==2, "time"], Indometh[Indometh$Subject==2, "conc"])DetSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) DetSlope(Indometh[Indometh$Subject==2, "time"], Indometh[Indometh$Subject==2, "conc"])
General AUC function for Emax, TEmax and AUCs
gAUC(x, y, Ymax = "Emax", XofYmax = "TEmax", AUCname = "AUEClast", iAUC = "", Outer = "NEAREST")gAUC(x, y, Ymax = "Emax", XofYmax = "TEmax", AUCname = "AUEClast", iAUC = "", Outer = "NEAREST")
x |
usually time |
y |
usually concentration or effect. This can be negative/ |
Ymax |
usually Cmax or Emax |
XofYmax |
usually Tmax or TEmax |
AUCname |
usually AUClast or AUEClast |
iAUC |
a data.frame to calculate interval AUCs |
Outer |
indicates how to do the out of x range point |
This is a general purpose AUC function. It calculates only Cmax(Emax), Tmax(TEmax) and AUCs(AUECs). This can be used for effect(pharmacodynamic) data which has negative values. For concentration data, use IntAUC.
Column names can vary according to the options.
Emax |
maximum y value |
TEmax |
x value at the maximum y value |
AUEClast |
Area under the y versus x curve |
iAUCs |
Columns from iAUC input |
Kyun-Seop Bae <[email protected]>
# For one subject x = Theoph[Theoph$Subject=="1", "Time"] y = Theoph[Theoph$Subject=="1", "conc"] gAUC(x, y) iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) gAUC(x, y, iAUC=iAUC)# For one subject x = Theoph[Theoph$Subject=="1", "Time"] y = Theoph[Theoph$Subject=="1", "conc"] gAUC(x, y) iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) gAUC(x, y, iAUC=iAUC)
It calculates interval AUC of general form. This is useful for pharmacodynamic data.
gIntAUC(x, y, t1, t2, Outer = "NEAREST")gIntAUC(x, y, t1, t2, Outer = "NEAREST")
x |
vector values of independent variable, usually time |
y |
vector values of dependent variable, usually concentration |
t1 |
start time for AUC |
t2 |
end time for AUC |
Outer |
indicates how to do the out of x range point |
This calculates an interval (partial) AUC (from t1 to t2) with the given series of x and y.
If t1 and/or t2 cannot be found within x vector, it interpolates.
If t1 and/or t2 are out of x range, it uses the nearest value.
For concentration data, use IntAUC.
return interval AUC value (scalar)
Kyun-Seop Bae <[email protected]>
gIntAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], t1=0.5, t2=11)gIntAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], t1=0.5, t2=11)
It interpolates y value when a corresponding x value (xnew) does not exist within x vector
gInterpol(x, y, xnew, Outer="NEAREST")gInterpol(x, y, xnew, Outer="NEAREST")
x |
vector values of x-axis, usually time |
y |
vector values of y-axis, usually concentration |
xnew |
new x point to be interpolated, usually new time point |
Outer |
indicates how to do the out of x range point |
This function interpolate y value, if xnew is not in x vector.
If xnew is in the x vector, it just returns the given x and y vector.
This function usually is called by gIntAUC function
Returned vector is sorted in the order of increasing x values.
new x and y vector containing xnew and ynew point
Kyun-Seop Bae <[email protected]>
x = 1:10 + 0.1 y = -2*x + 40.2 gInterpol(x, y, 1.5) gInterpol(x, y, 0.5) # Out of range, Left gInterpol(x, y, 11) # Out of range, Leftx = 1:10 + 0.1 y = -2*x + 40.2 gInterpol(x, y, 1.5) gInterpol(x, y, 0.5) # Out of range, Left gInterpol(x, y, 11) # Out of range, Left
It calculates interval AUC
IntAUC(x, y, t1, t2, Res, down = "Linear")IntAUC(x, y, t1, t2, Res, down = "Linear")
x |
vector values of independent variable, usually time |
y |
vector values of dependent variable, usually concentration |
t1 |
start time for AUC |
t2 |
end time for AUC |
Res |
result from |
down |
either of |
This calculates an interval (partial) AUC (from t1 to t2) with the given series of x and y.
If t1 and/or t2 cannot be found within x vector, it interpolates according to the down option.
return interval AUC value (scalar)
Kyun-Seop Bae <[email protected]>
Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.
Res = sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320, concUnit="mg/L") IntAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], t1=0.5, t2=11, Res)Res = sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320, concUnit="mg/L") IntAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], t1=0.5, t2=11, Res)
It interpolates y value when a corresponding x value (xnew) does not exist within x vector
Interpol(x, y, xnew, Slope, b0, down = "Linear")Interpol(x, y, xnew, Slope, b0, down = "Linear")
x |
vector values of x-axis, usually time |
y |
vector values of y-axis, usually concentration |
xnew |
new x point to be interpolated, usually new time point |
Slope |
slope of regression log(y) ~ x |
b0 |
y value of just left point of xnew |
down |
either of |
This function interpolate y value, if xnew is not in x vector.
If xnew is in x vector, it just returns the given x and y vector.
This function usually is called by IntAUC function
Returned vector is sorted in the order of increasing x values.
new x and y vector containing xnew and ynew point
Kyun-Seop Bae <[email protected]>
x = 10:1 + 0.1 y = -2*x + 40.2 Interpol(x, y, 1.5) Interpol(x, y, 1.5, down="Log")x = 10:1 + 0.1 y = -2*x + 40.2 Interpol(x, y, 1.5) Interpol(x, y, 1.5, down="Log")
It calculates AUC and AUMC using the linear trapezoidal method
LinAUC(x, y)LinAUC(x, y)
x |
vector values of the independent variable, usually time |
y |
vector values of the dependent variable, usually concentration |
This function returns AUC and AUMC by the linear trapezoidal method.
AUC |
area under the curve |
AUMC |
area under the first moment curve |
Kyun-Seop Bae <[email protected]>
Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.
LinAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) # compare the last lineLinAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) # compare the last line
It calculates AUC and AUMC using the linear-up log-down method
LogAUC(x, y)LogAUC(x, y)
x |
vector values of the independent variable, usually time |
y |
vector values of the dependent variable, usually concentration |
This function returns AUC and AUMC by the linear-up log-down method.
AUC |
area under the curve |
AUMC |
area under the first moment curve |
Kyun-Seop Bae <[email protected]>
Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.
LogAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) # Compare the last line with the above AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log")LogAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) # Compare the last line with the above AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log")
It calculates the slope with linear regression of log(y) ~ x
Slope(x, y)Slope(x, y)
x |
vector values of the independent variable, usually time |
y |
vector values of the dependent variable, usually concentration |
With time-concentration curve, you frequently need to estimate slope in log(concentration) ~ time.
This function is usually called by BestSlope function, and you seldom need to call this function directly.
R2 |
R-squared |
R2ADJ |
adjusted R-squared |
LAMZNPT |
number of points used for slope |
LAMZ |
negative of the slope, lambda_z |
b0 |
intercept of the regression line |
CORRXY |
correlation of log(y) and x |
LAMZLL |
earliest x for lambda_z |
LAMZUL |
last x for lambda_z |
Kyun-Seop Bae <[email protected]>
Slope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"])Slope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"])
This is the work-horse function for NCA.
sNCA(x, y, dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", concUnit = "ug/L", iAUC = "", down = "Linear", R2ADJ = 0.7, MW = 0, SS = FALSE, Keystring="", excludeDelta = 1)sNCA(x, y, dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", concUnit = "ug/L", iAUC = "", down = "Linear", R2ADJ = 0.7, MW = 0, SS = FALSE, Keystring="", excludeDelta = 1)
x |
usually time |
y |
usually concentration |
dose |
given amount, not amount per body weight |
adm |
one of |
dur |
duration of infusion |
doseUnit |
unit of dose |
timeUnit |
unit of time |
concUnit |
unit of concentration |
iAUC |
interval AUCs to calculate |
down |
either of |
R2ADJ |
Minimum adjusted R-square value to determine terminal slope automatically |
MW |
molecular weight of the drug |
SS |
if steady-state, this should be TRUE. AUCLST (AUClast) is used instead of AUCIFO (AUCinf) for the calculation of Vz (VZFO, VZO), CL (CLFO, CLO), and Vdss (VSSO). |
Keystring |
a text string to be shown at the plot in case of manual selection of terminal slope |
excludeDelta |
Improvement of R2ADJ larger than this value could exclude the last point. Default value 1 is for the compatibility with other software. |
This replaced previous IndiNCA. Author recommends to use excludeDelta option with about 0.3.
CMAX |
maximum concentration, Cmax |
CMAXD |
dose normalized Cmax, CMAX / Dose, Cmax / Dose |
TMAX |
time of maximum concentration, Tmax |
TLAG |
time to observe the first non-zero concentration, for extravascular administration only |
CLST |
last positive concentration observed, Clast |
CLSTP |
last positive concentration predicted, Clast_pred |
TLST |
time of last positive concentration, Tlast |
LAMZHL |
half-life by lambda z, ln(2)/LAMZ |
LAMZ |
lambda_z negative of the best-fit terminal slope |
LAMZLL |
earliest time for LAMZ |
LAMZUL |
last time for LAMZ |
LAMZNPT |
number of points for LAMZ |
CORRXY |
correlation of log(concentration) and time |
R2 |
R-squared |
R2ADJ |
R-squared adjusted |
C0 |
back extrapolated concentration at time 0, for intravascular bolus administration only |
AUCLST |
AUC from 0 to TLST |
AUCALL |
AUC using all the given points, including trailing zero concentrations |
AUCIFO |
AUC infinity observed |
AUCIFOD |
AUCIFO / Dose |
AUCIFP |
AUC infinity predicted using CLSTP instead of CLST |
AUCIFPD |
AUCIFP / Dose |
AUCPEO |
AUC % extrapolation observed |
AUCPEP |
AUC % extrapolated for AUCIFP |
AUCPBEO |
AUC % back extrapolation observed, for bolus IV administration only |
AUCPBEP |
AUC % back extrapolation predicted with AUCIFP, for bolus IV administration only |
AUMCLST |
AUMC to the TLST |
AUMCIFO |
AUMC infinity observed using CLST |
AUMCIFP |
AUMC infinity determined by CLSTP |
AUMCPEO |
AUMC % extrapolated observed |
AUMCPEP |
AUMC % extrapolated predicted |
MRTIVLST |
mean residence time (MRT) to TLST, for intravascular administration |
MRTIVIFO |
mean residence time (MRT) infinity using CLST, for intravascular administration |
MRTIVIFP |
mean residence time (MRT) infinity using CLSTP, for intravascular administration |
MRTEVLST |
mean residence time (MRT) to TLST, for extravascular administration |
MRTEVIFO |
mean residence time (MRT) infinity using CLST, for extravascular administration |
MRTEVIFP |
mean residence time (MRT) infinity using CLSTP, for extravascular administration |
VZO |
volume of distribution determined by LAMZ and AUCIFO, for intravascular administration |
VZP |
volume of distribution determined by LAMZ and AUCIFP, for intravascular administration |
VZFO |
VZO for extravascular administration, VZO/F, F is bioavailability |
VZFP |
VZP for extravascular administration, VZP/F, F is bioavailability |
CLO |
clearance using AUCIFO, for intravascular administration |
CLP |
clearance using AUCIFP, for intravascular administration |
CLFO |
CLO for extravascular administration, CLO/F, F is bioavailability |
CLFP |
CLP for extravascular administration, CLP/F, F is bioavailability |
VSSO |
volume of distribution at steady state using CLST, for intravascular administration only |
VSSP |
volume of distribution at steady state using CLSTP, for intravascular administration only |
Kyun-Seop Bae <[email protected]>
Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
# For one subject x = Theoph[Theoph$Subject=="1","Time"] y = Theoph[Theoph$Subject=="1","conc"] sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h") sNCA(x, y, dose=320, concUnit="mg/L") iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h", iAUC=iAUC) MW = 180.164 # Molecular weight of theophylline sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h") sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y, dose=320/MW, doseUnit="mmol", concUnit="mg/L", timeUnit="h", MW=MW) sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y/MW, dose=as.numeric(NA), doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y, dose=320, concUnit="mg/L", timeUnit="hr") sNCA(x*60, y, dose=320, concUnit="mg/L", timeUnit="min")# For one subject x = Theoph[Theoph$Subject=="1","Time"] y = Theoph[Theoph$Subject=="1","conc"] sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h") sNCA(x, y, dose=320, concUnit="mg/L") iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h", iAUC=iAUC) MW = 180.164 # Molecular weight of theophylline sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h") sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y, dose=320/MW, doseUnit="mmol", concUnit="mg/L", timeUnit="h", MW=MW) sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y/MW, dose=as.numeric(NA), doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW) sNCA(x, y, dose=320, concUnit="mg/L", timeUnit="hr") sNCA(x*60, y, dose=320, concUnit="mg/L", timeUnit="min")
Do multiple AUCs and returns a result table. See gNCA for more detail i.e. iAUC
tblAUC(Data, key = "Subject", colX = "Time", colY = "Y", iAUC = "", Ymax = "Emax", XofYmax = "TEmax", AUCname = "AUEClast", Outer = "NEAREST")tblAUC(Data, key = "Subject", colX = "Time", colY = "Y", iAUC = "", Ymax = "Emax", XofYmax = "TEmax", AUCname = "AUEClast", Outer = "NEAREST")
Data |
data table name |
key |
column names of Data to be shown in the output table |
colX |
column name for x axis |
colY |
column name for y axis |
iAUC |
a data.frame to calculate interval AUCs |
Ymax |
usually Cmax or Emax |
XofYmax |
usually Tmax or TEmax |
AUCname |
usually AUClast or AUEClast |
Outer |
indicates how to do the out of x range point |
Tabular output of AUC with many subjects. This calculates only Cmax(Emax), Tmax(TEmax), AUCs
Basically same with gAUC
Kyun-Seop Bae <[email protected]>
tblAUC(Theoph, key="Subject", colX="Time", colY="conc") iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) tblAUC(Indometh, key="Subject", colX="time", colY="conc", iAUC=iAUC)tblAUC(Theoph, key="Subject", colX="Time", colY="conc") iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) tblAUC(Indometh, key="Subject", colX="time", colY="conc", iAUC=iAUC)
Do multiple NCA and returns a result table. See sNCA for more detail i.e. iAUC
tblNCA(concData, key = "Subject", colTime = "Time", colConc = "conc", dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", concUnit = "ug/L", down = "Linear", R2ADJ = 0, MW = 0, SS = FALSE, iAUC = "", excludeDelta = 1)tblNCA(concData, key = "Subject", colTime = "Time", colConc = "conc", dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", concUnit = "ug/L", down = "Linear", R2ADJ = 0, MW = 0, SS = FALSE, iAUC = "", excludeDelta = 1)
concData |
concentration data table |
key |
column names of concData to be shown in the output table |
colTime |
column name for time |
colConc |
column name for concentration |
dose |
administered dose |
adm |
one of |
dur |
duration of infusion |
doseUnit |
unit of dose |
timeUnit |
unit of time |
concUnit |
unit of concentration |
down |
method to calculate AUC, |
R2ADJ |
Lowest threshold of adjusted R-square value to do manual slope determination |
MW |
molecular weight of drug |
SS |
if steady-state, this should be TRUE. AUCLST (AUClast) is used instead of AUCIFO (AUCinf) for the calculation of Vz (VZFO, VZO), CL (CLFO, CLO), and Vdss (VSSO). |
iAUC |
data.frame for interval AUC |
excludeDelta |
Improvement of R2ADJ larger than this value could exclude the last point. Default value 1 is for the compatibility with other software. |
Tabular output of NCA with many subjects. Author recommends to use excludeDelta option with about 0.3.
Basically same with sNCA
Kyun-Seop Bae <[email protected]>
tblNCA(Theoph, key="Subject", dose=320, concUnit="mg/L") tblNCA(Indometh, key="Subject", colTime="time", colConc="conc", dose=25, adm="Infusion", dur=0.5, concUnit="mg/L")tblNCA(Theoph, key="Subject", dose=320, concUnit="mg/L") tblNCA(Indometh, key="Subject", colTime="time", colConc="conc", dose=25, adm="Infusion", dur=0.5, concUnit="mg/L")
It displays CDISC PP output units and multiplication factor for them.
Unit(code = "", timeUnit = "h", concUnit = "ng/mL", doseUnit = "mg", MW = 0)Unit(code = "", timeUnit = "h", concUnit = "ng/mL", doseUnit = "mg", MW = 0)
code |
vector of PPTESTCD |
timeUnit |
unit of time |
concUnit |
unit of concentration |
doseUnit |
unit of dose |
MW |
molecular weight of drug |
row names |
PPTESTCD |
Unit |
unit |
Factor |
internal mulitplication factor |
Kyun-Seop Bae <[email protected]>
Unit(concUnit="ug/L", doseUnit="mg") Unit(concUnit="ng/L", doseUnit="mg") Unit(concUnit="umol/L", doseUnit="mmol") Unit(concUnit="nmol/L", doseUnit="mmol") Unit(concUnit="mmol/L", doseUnit="mg", MW=500) Unit(concUnit="umol/L", doseUnit="mg", MW=500) Unit(concUnit="nmol/L", doseUnit="mg", MW=500) Unit(concUnit="nmol/mL", doseUnit="mg", MW=500) Unit(concUnit="ug/L", doseUnit="mmol", MW=500) Unit(concUnit="ug/L", doseUnit="mol", MW=500) Unit(concUnit="ng/L", doseUnit="mmol", MW=500) Unit(concUnit="ng/mL", doseUnit="mmol", MW=500) Unit(concUnit="nmol/L", doseUnit="mg") Unit(concUnit="ug/L", doseUnit="mmol")Unit(concUnit="ug/L", doseUnit="mg") Unit(concUnit="ng/L", doseUnit="mg") Unit(concUnit="umol/L", doseUnit="mmol") Unit(concUnit="nmol/L", doseUnit="mmol") Unit(concUnit="mmol/L", doseUnit="mg", MW=500) Unit(concUnit="umol/L", doseUnit="mg", MW=500) Unit(concUnit="nmol/L", doseUnit="mg", MW=500) Unit(concUnit="nmol/mL", doseUnit="mg", MW=500) Unit(concUnit="ug/L", doseUnit="mmol", MW=500) Unit(concUnit="ug/L", doseUnit="mol", MW=500) Unit(concUnit="ng/L", doseUnit="mmol", MW=500) Unit(concUnit="ng/mL", doseUnit="mmol", MW=500) Unit(concUnit="nmol/L", doseUnit="mg") Unit(concUnit="ug/L", doseUnit="mmol")
You can get a conversion factor for the multiplication: conc * vol * factor = amount in the given unit.
UnitUrine(conU = "ng/mL", volU = "mL", amtU = "mg", MW = 0)UnitUrine(conU = "ng/mL", volU = "mL", amtU = "mg", MW = 0)
conU |
concentration unit |
volU |
volume unit |
amtU |
amount unit |
MW |
molecular weight |
Factor |
conversion factor for multiplication with the unit in name |
Kyun-Seop Bae <[email protected]>
UnitUrine() UnitUrine("ng/mL", "mL", "mg") UnitUrine("ug/L", "mL", "mg") UnitUrine("ug/L", "L", "mg") UnitUrine("ng/mL", "mL", "g") UnitUrine("ng/mL", "mL", "mol", MW=500) UnitUrine("ng/mL", "mL", "mmol", MW=500) UnitUrine("ng/mL", "mL", "umol", MW=500)UnitUrine() UnitUrine("ng/mL", "mL", "mg") UnitUrine("ug/L", "mL", "mg") UnitUrine("ug/L", "L", "mg") UnitUrine("ng/mL", "mL", "g") UnitUrine("ng/mL", "mL", "mol", MW=500) UnitUrine("ng/mL", "mL", "mmol", MW=500) UnitUrine("ng/mL", "mL", "umol", MW=500)