In cacha0227/ncappc: NCA Calculation and Population PK Model Diagnosis
NCA metrics are eatimated according to traditional PK calculations. The names of the various NCA metrics estimated in this package are assigned mainly following the names used in WinNonlin. This package accepts any of the three different types of drug administration, (i) iv-bolus, (ii) iv-infusion and (iii) extravascular; ncappc also can accept both non-steady state and steady-state data. The NCa metric that are estimated and reported by ncappc are listed below.
C0
C0 is the initial concentration at the dosing time. It is the observed concentration at the dosing time, if available. Otherwise it is approximated using the following rules. For iv-bolus data, log-linear back-extrapolation (see "backExtrap" argument) is performed from the first two observations to estimate C0, provided the local slope is negative. However, if the slope is >=0 or at least one of the first two concentrations is 0, the first non-zero concentration is used as C0. For other types of administration, C0 is equal to 0 for non steady-state data and for steady-state data the minimum value observed between the dosing intervals is used to estimate C0, provided the "backExtrap" argument is set to "yes".
Cmax, Tmax and Cmax_D
Cmax and Tmax are the value and the time of maximum observed concentration, respectively. If the maximum concentration is not unique, the first maximum is used. For steady state data, The maximum value between the dosing intervals is considered. Cmax_D is the dose normalized maximum observed concentration.
Clast and Tlast
Clast and Tlast are the last measurable positive comcentration and the corresponding time, respectively.
AUClast
The area under the concentration vs. time curve from the first observed to last measurable concentration.
AUMClast
The area under the first moment of the concentration vs. time curve from the first observed to last measurable concentration.
MRTlast
Mean residence time from the first observed to last measurable concentration. For non-infusion models,
$MRTlast = \frac{AUMClast}{AUClast}$
For infusion models,
$MRTlast = \frac{AUMClast}{AUClast}-\frac{TI}{2}$
where TI is the infusion duration.
No_points_Lambda_z
No_points_Lambda_z is the number of observed data points used to determine the best fitting regression line in the elimination phase.
AUC_pBack_Ext_obs and AUC_pBack_Ext_pred
The percentage of AUC that is contributed by the back extrapolation to estimate C0. The rules to to estimate C0 is given above.
AUClower_upper
The AUC under the concentration-time profile within the user-specified window of time privided as the "AUCTimeRange" argument. In case of empty "AUCTimeRange" argument, AUClower_upper is equal to the AUClast.
Rsq, Rsq_adjusted and Corr_XY
Regression coefficient of the regression line used to estimate the elimination rate constant. Rsq_adjusted is the adjusted value of Rsq given by the following relation.
$Rsq_adjusted = 1-\frac{(1-Rsq^2)(n-1)}{n-2}$
where n* is the number of points in the regression line. Corr_XY is the square root of Rsq.
Lambda_z
Elimination rate constant estimated from the regression line representing the terminal phase of the concentration-time prifile. The relation between the slope of the regression line and Lambda_z is:
$Lambda_z = -(slope)$
Lambda_lower and Lambda_upper
Lower and upper limit of the time values from the concentration-time profile used to estimate Lambda_z, respectively, in case the "LambdaTimeRange" is used to specify the time range.
HL_Lambda_z
Terminal half-life of the drug:
$HL_Lambda_z = \frac{ln2}{\lambda_z}$
AUCINF_obs and AUCINF_obs_D
AUC estimated from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last observed concentration (${Clast_obs}$). The equiation used for the estimation is given below.
$AUCINF_obs = AUClast+\frac{Clast_obs}{\lambda_z}$
AUCINF_obs_D is the dose normalized AUCINF_obs.
AUC_pExtrap_obs
Percentage of the AUCINF_obs that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUC_pExtrap_obs = \frac{AUCINF_obs-AUClast}{AUCINF_obs}*100\%$
AUMCINF_obs
AUMC estimated from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last observed concentration. The equiation used for the estimation is given below.
$AUMCINF_obs = AUMClast+\frac{Tlast*Clast_obs}{\lambda_z}+\frac{Clast_obs}{\lambda_{z}^2}$
AUMC_pExtrap_obs
Percentage of the AUMCINF_obs that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUMC_pExtrap_obs = \frac{AUMCINF_obs-AUMClast}{AUMCINF_obs}*100\%$
Vz_obs
Volume of distribution estimated based on total AUC using the following equation.
$Vz_obs = \frac{Dose}{\lambda_z*AUCINF_obs}$
Cl_obs
Total body clearance.
$Cl_obs = \frac{Dose}{AUCINF_obs}$
AUCINF_pred and AUCINF_pred_D
AUC from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last predicted concentration obtained from the regression line used to estimate Lambda_z (${Clast_pred}$). The equiation used for the estimation is given below.
$AUCINF_pred = AUClast+\frac{Clast_pred}{\lambda_z}$
AUCINF_pred_D is the dose normalized AUCINF_pred.
AUC_pExtrap_pred
Percentage of the AUCINF_pred that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUC_pExtrap_pred = \frac{AUCINF_pred-AUClast}{AUCINF_pred}*100\%$
AUMCINF_pred
AUMC estimated from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last predicted concentration obtained from the regression line used to estimate Lambda_z (${Clast_pred}$). The equiation used for the estimation is given below.
$AUMCINF_pred = AUMClast+\frac{Tlast*Clast_pred}{\lambda_z}+\frac{Clast_pred}{\lambda_{z}^2}$
AUMC_pExtrap_pred
Percentage of the AUMCINF_pred that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUMC_pExtrap_pred = \frac{AUMCINF_pred-AUMClast}{AUMCINF_pred}*100\%$
Vz_pred
Volume of distribution estimated based on total AUC using the following equation.
$Vz_pred = \frac{Dose}{\lambda_z*AUCINF_pred}$
Cl_pred
Total body clearance.
$Cl_pred = \frac{Dose}{AUCINF_pred}$
MRTINF_obs
Mean residence time from the first sampled time extrapolated to ${\infty}$ based on the last observed concentration (${Clast_obs}$).
For non-infusion non steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs}{AUCINF_obs}$
For infusion non steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs}{AUCINF_obs}-\frac{TI}{2}$
where ${TI}$ is the infusion duration. For non-infusion steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs|{0}^{\tau}+\tau(AUCINF_obs-AUC|{0}^{\tau})}{AUCINF_obs|{0}^{\tau}}$
For infusion steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs|_{0}^{\tau}+\tau(AUCINF_obs-AUC|{0}^{\tau})}{AUCINF_obs|_{0}^{\tau}}-\frac{TI}{2}$
For steady-state data ${\tau}$ represents the dosing interval.
MRTINF_pred
Mean residence time from the first sampled time extrapolated to ${\infty}$ based on the last predicted concentration obtained from the regression line used to estimate Lambda_z (${Clast_pred}$).
For non-infusion non steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred}{AUCINF_pred}$
For infusion non steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred}{AUCINF_pred}-\frac{TI}{2}$
where ${TI}$ is the infusion duration.
For non-infusion steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred|{0}^{\tau}+\tau(AUCINF_pred-AUC|{0}^{\tau})}{AUCINF_pred|{0}^{\tau}}$
For infusion steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred|_{0}^{\tau}+\tau(AUCINF_pred-AUC|{0}^{\tau})}{AUCINF_pred|_{0}^{\tau}}-\frac{TI}{2}$
For steady-state data ${\tau}$ represents the dosing interval.
Vss_obs and Vss_pred
An estimate of the volume of distribution at steady-state.
$Vss_obs = MRTINF_obsCl_obs$
$Vss_pred = MRTINF_predCl_pred$
Tau
The dosing interval for steady-state data. This value is assumed equarion over multiple doses.
Cmin and Tmin
Cmin is the minimum concentration between 0 and Tau and Tmin is the corresponding time for steady-state data.
Cavg
The average concentration between 0 and Tau for steady-state data.
$Cavg = \frac{AUC|_{0}^{Tau}}{Tau}$
p_Fluctuation
Percentage of the fluctuation of the concentration between 0 and Tau for steady-state data.
$p_Fluctuation = \frac{Cmax-Cmin}{Cavg}*100\%$
Accumulation_Index
$Accumulation_Index = \frac{1}{1-e^{-\lambda_{z}*\tau}}$
Clss
An estimate of the total body clearance for steady-state data.
$Clss = \frac{Dose}{AUC|_{0}^{\tau}}$
cacha0227/ncappc documentation built on Nov. 14, 2020, 9:09 a.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
NCA metrics are eatimated according to traditional PK calculations. The names of the various NCA metrics estimated in this package are assigned mainly following the names used in WinNonlin. This package accepts any of the three different types of drug administration, (i) iv-bolus, (ii) iv-infusion and (iii) extravascular; ncappc also can accept both non-steady state and steady-state data. The NCa metric that are estimated and reported by ncappc are listed below.
C0
C0 is the initial concentration at the dosing time. It is the observed concentration at the dosing time, if available. Otherwise it is approximated using the following rules. For iv-bolus data, log-linear back-extrapolation (see "backExtrap" argument) is performed from the first two observations to estimate C0, provided the local slope is negative. However, if the slope is >=0 or at least one of the first two concentrations is 0, the first non-zero concentration is used as C0. For other types of administration, C0 is equal to 0 for non steady-state data and for steady-state data the minimum value observed between the dosing intervals is used to estimate C0, provided the "backExtrap" argument is set to "yes".
Cmax, Tmax and Cmax_D
Cmax and Tmax are the value and the time of maximum observed concentration, respectively. If the maximum concentration is not unique, the first maximum is used. For steady state data, The maximum value between the dosing intervals is considered. Cmax_D is the dose normalized maximum observed concentration.
Clast and Tlast
Clast and Tlast are the last measurable positive comcentration and the corresponding time, respectively.
AUClast
The area under the concentration vs. time curve from the first observed to last measurable concentration.
AUMClast
The area under the first moment of the concentration vs. time curve from the first observed to last measurable concentration.
MRTlast
Mean residence time from the first observed to last measurable concentration. For non-infusion models,
$MRTlast = \frac{AUMClast}{AUClast}$
For infusion models,
$MRTlast = \frac{AUMClast}{AUClast}-\frac{TI}{2}$
where TI is the infusion duration.
No_points_Lambda_z
No_points_Lambda_z is the number of observed data points used to determine the best fitting regression line in the elimination phase.
AUC_pBack_Ext_obs and AUC_pBack_Ext_pred
The percentage of AUC that is contributed by the back extrapolation to estimate C0. The rules to to estimate C0 is given above.
AUClower_upper
The AUC under the concentration-time profile within the user-specified window of time privided as the "AUCTimeRange" argument. In case of empty "AUCTimeRange" argument, AUClower_upper is equal to the AUClast.
Rsq, Rsq_adjusted and Corr_XY
Regression coefficient of the regression line used to estimate the elimination rate constant. Rsq_adjusted is the adjusted value of Rsq given by the following relation.
$Rsq_adjusted = 1-\frac{(1-Rsq^2)(n-1)}{n-2}$
where n* is the number of points in the regression line. Corr_XY is the square root of Rsq.
Lambda_z
Elimination rate constant estimated from the regression line representing the terminal phase of the concentration-time prifile. The relation between the slope of the regression line and Lambda_z is:
$Lambda_z = -(slope)$
Lambda_lower and Lambda_upper
Lower and upper limit of the time values from the concentration-time profile used to estimate Lambda_z, respectively, in case the "LambdaTimeRange" is used to specify the time range.
HL_Lambda_z
Terminal half-life of the drug:
$HL_Lambda_z = \frac{ln2}{\lambda_z}$
AUCINF_obs and AUCINF_obs_D
AUC estimated from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last observed concentration (${Clast_obs}$). The equiation used for the estimation is given below.
$AUCINF_obs = AUClast+\frac{Clast_obs}{\lambda_z}$
AUCINF_obs_D is the dose normalized AUCINF_obs.
AUC_pExtrap_obs
Percentage of the AUCINF_obs that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUC_pExtrap_obs = \frac{AUCINF_obs-AUClast}{AUCINF_obs}*100\%$
AUMCINF_obs
AUMC estimated from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last observed concentration. The equiation used for the estimation is given below.
$AUMCINF_obs = AUMClast+\frac{Tlast*Clast_obs}{\lambda_z}+\frac{Clast_obs}{\lambda_{z}^2}$
AUMC_pExtrap_obs
Percentage of the AUMCINF_obs that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUMC_pExtrap_obs = \frac{AUMCINF_obs-AUMClast}{AUMCINF_obs}*100\%$
Vz_obs
Volume of distribution estimated based on total AUC using the following equation.
$Vz_obs = \frac{Dose}{\lambda_z*AUCINF_obs}$
Cl_obs
Total body clearance.
$Cl_obs = \frac{Dose}{AUCINF_obs}$
AUCINF_pred and AUCINF_pred_D
AUC from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last predicted concentration obtained from the regression line used to estimate Lambda_z (${Clast_pred}$). The equiation used for the estimation is given below.
$AUCINF_pred = AUClast+\frac{Clast_pred}{\lambda_z}$
AUCINF_pred_D is the dose normalized AUCINF_pred.
AUC_pExtrap_pred
Percentage of the AUCINF_pred that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUC_pExtrap_pred = \frac{AUCINF_pred-AUClast}{AUCINF_pred}*100\%$
AUMCINF_pred
AUMC estimated from the first sampled data extrapolated to ${\infty}$. The extrapolation in the terminal phase is based on the last predicted concentration obtained from the regression line used to estimate Lambda_z (${Clast_pred}$). The equiation used for the estimation is given below.
$AUMCINF_pred = AUMClast+\frac{Tlast*Clast_pred}{\lambda_z}+\frac{Clast_pred}{\lambda_{z}^2}$
AUMC_pExtrap_pred
Percentage of the AUMCINF_pred that is contributed by the extrapolation from the last sampling time to ${\infty}$.
$AUMC_pExtrap_pred = \frac{AUMCINF_pred-AUMClast}{AUMCINF_pred}*100\%$
Vz_pred
Volume of distribution estimated based on total AUC using the following equation.
$Vz_pred = \frac{Dose}{\lambda_z*AUCINF_pred}$
Cl_pred
Total body clearance.
$Cl_pred = \frac{Dose}{AUCINF_pred}$
MRTINF_obs
Mean residence time from the first sampled time extrapolated to ${\infty}$ based on the last observed concentration (${Clast_obs}$).
For non-infusion non steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs}{AUCINF_obs}$
For infusion non steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs}{AUCINF_obs}-\frac{TI}{2}$
where ${TI}$ is the infusion duration. For non-infusion steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs|{0}^{\tau}+\tau(AUCINF_obs-AUC|{0}^{\tau})}{AUCINF_obs|{0}^{\tau}}$
For infusion steady-state data:
$MRTINF_obs = \frac{AUMCINF_obs|_{0}^{\tau}+\tau(AUCINF_obs-AUC|{0}^{\tau})}{AUCINF_obs|_{0}^{\tau}}-\frac{TI}{2}$
For steady-state data ${\tau}$ represents the dosing interval.
MRTINF_pred
Mean residence time from the first sampled time extrapolated to ${\infty}$ based on the last predicted concentration obtained from the regression line used to estimate Lambda_z (${Clast_pred}$).
For non-infusion non steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred}{AUCINF_pred}$
For infusion non steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred}{AUCINF_pred}-\frac{TI}{2}$
where ${TI}$ is the infusion duration.
For non-infusion steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred|{0}^{\tau}+\tau(AUCINF_pred-AUC|{0}^{\tau})}{AUCINF_pred|{0}^{\tau}}$
For infusion steady-state data:
$MRTINF_pred = \frac{AUMCINF_pred|_{0}^{\tau}+\tau(AUCINF_pred-AUC|{0}^{\tau})}{AUCINF_pred|_{0}^{\tau}}-\frac{TI}{2}$
For steady-state data ${\tau}$ represents the dosing interval.
Vss_obs and Vss_pred
An estimate of the volume of distribution at steady-state.
$Vss_obs = MRTINF_obsCl_obs$
$Vss_pred = MRTINF_predCl_pred$
Tau
The dosing interval for steady-state data. This value is assumed equarion over multiple doses.
Cmin and Tmin
Cmin is the minimum concentration between 0 and Tau and Tmin is the corresponding time for steady-state data.
Cavg
The average concentration between 0 and Tau for steady-state data.
$Cavg = \frac{AUC|_{0}^{Tau}}{Tau}$
p_Fluctuation
Percentage of the fluctuation of the concentration between 0 and Tau for steady-state data.
$p_Fluctuation = \frac{Cmax-Cmin}{Cavg}*100\%$
Accumulation_Index
$Accumulation_Index = \frac{1}{1-e^{-\lambda_{z}*\tau}}$
Clss
An estimate of the total body clearance for steady-state data.
$Clss = \frac{Dose}{AUC|_{0}^{\tau}}$
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