Noncompartmental Analysis
Noncompartmental analysis (NCA) lets you compute pharmacokinetic (PK) parameters of a drug from the time course of measured drug concentrations. This approach does not require the assumption of a specific compartmental model. NCA is often used to determine the degree of exposure following administration of a drug, such as AUC, and other PK parameters, such as the clearance and the terminal half-life.
数据
SimBiology®lets you calculate NCA parameters from concentration–time data. The data must contain a time column, a concentration column, and a dose column that defines dose amounts. Three types of drug administration routes are supported: IV bolus, IV infusion, and Extravascular. You can have a column for each type. For infusion doses, an infusion rate column is also needed.
If you have data containing multiple groups of observations, you can define a group column. If needed, you can use two levels of hierarchy to specify grouping. Specify the outer level of grouping using the group column, and specify the inner level (subgroups) in the ID column. Consider data that contains three groups, where each group contains four patients. The group column labels the three groups, and the ID column labels each patient.
给药
Single-dosing data contains a single dose amount for each individual. Multiple-dosing data has several doses at different times for each individual. There are common parameters calculated for either type of dosing data, and parameters that are specific to single or multiple dosing.
Common Parameters for Single and Multiple Dosing
SimBiology computes some common parameters for single- or multiple-dosing data. This figure represents the concentration-time profile after a single dose. For multiple dosing, the same principles apply, except that SimBiology uses a steady state dosing period.
FigureAshows concentration–time data in a linear scale and illustrates how the AUC from time 0 to infinity is calculated. FigureBshows the same data in a semilogarithmic scale. To compute the terminal rate constant (Lambda_z), SimBiology执行一组线性回归of the log-transformed data using each of the lastn点(n=3, 4, 5, ...
) from the terminal portion of the curve.Lambda_zis chosen from the regression that uses the most points and has the maximumadjusted_R2。
This table describes the common parameters for single and multiple dosing.
Parameter | Description |
---|---|
AUC_0_last | Area under the measured concentration–time curve from time = 0 to the last time point. , whereC(t)是时间的血浆浓度t。 SimBiology uses the lineartrapezoidal method计算AUC。 |
AUC_infinity | 浓度 - 时间曲线的总面积外推到infusing the terminal rate constantLambda_z。 , whereC_lastis the last observed concentration andLambda_zis the terminal rate constant. |
AUC_infinity_dose | 。 |
AUCx_y | Partial AUC computed for a custom time range, where x and y are the start and end times, respectively. |
AUC_extrap_percent | Fraction of totalAUC_infinityobtained from extrapolation. 。 |
Lambda_z | To calculate the terminal rate constant (Lambda_z), SimBiology执行一组线性回归of the log(concentration)–time data using each of the lastn点( Lambda_zis chosen from the regression that uses the most points and has the maximumadjusted_R2among all regressions.
|
R2 | Coefficient of determination for thelinear regressions (Statistics and Machine Learning Toolbox)used in theLambda_zcalculation. |
Num_points | Number of data points from the profile used in the determination ofLambda_z。 |
C_0 | Extrapolated concentration at time = 0, computed using a regression of the first two data points in a profile. This parameter is for IV Bolus doses only. |
C_max | Maximum observed concentration. |
C_max_Dose | 。 |
C_MAX_X_Y | Maximum observed concentration within a given time range, specified by the start timexand the end timey。当您在指定自定义时间范围时,计算此参数CMAX时间范围box in the SimBiology Model Analyzer app or set theC_max_ranges property of the options object created bySbioncaoptions 。 |
Tlast | Time of the last observed concentration value above the lower limit of quantization (LOQ). |
T_HALF | Terminal half-life of the drug. 。 |
T_max | T_max是最大的农用地的时间点tration (C_max) is observed. |
T_max_x_y | Time point at which maximum concentration is observed within a given time range, specified by the start timexand the end timey。当您在指定自定义时间范围时,计算此参数CMAX时间范围Simbiology模型分析仪中的框或设置C_max_ranges property of the options object created bySbioncaoptions 。 |
V_ss | 平衡处的明显分布体积。此参数仅用于静脉注射剂量。 。 |
V_z | Volume of distribution during the terminal phase. 。 |
DM | 剂量量。对于多种剂量,报告了最后一次给药的剂量。 |
doseSchedule | Single- or multiple-dosing data. |
administrationRoute | Dose administration route. Supported routes areIVBolus ,IVInfusion ,ExtraVascular 。 |
Parameters for Single Dosing
In addition to the common parameters, SimBiology reports parameters for single-dosing data.
Parameter | Description |
---|---|
aumc_0_last | Area under the first moment of the concentration–time curve from time 0 to the last time pointTlast。 。 |
AUMC | Total area under the first moment of the concentration–time curve extrapolating toinfusingLambda_z。 。 |
AUMC_extrap_percent | Fraction of totalAUMCobtained from extrapolation. 。 |
CL | Total drug clearance. , whereDMis the dose amount. |
MRT | Mean residence time. 。 |
Parameters for Multiple Dosing
This figure shows the concentration-time profile after multiple doses. SimBiology uses a steady state dosing period to compute the following NCA parameters for multiple-dosing data, in addition to the common parameters listed previously. In the following figure, the last dosing period is used for illustration purposes.
Parameter | Description |
---|---|
AUC_Tau | Area under the concentration–time curve during a dosing period of lengthTau。SimBiology uses a steady-state dosing period (SS_period). 。 |
Tau | 给药间隔。 |
AUMC_Tau | Area under the first moment of the concentration–time curve during a steady-state dosing period of lengthTau。 。 |
C_avg | 一个时期的平均浓度。 。 |
C_min | Minimum observed concentration during the first period, that is, |
PTF_percent | Peak trough fluctuation over one dosing interval at steady state. 。 |
Accumulation_Index | Theoretical accumulation ratio. 。 |
T_min | Time at which the minimum concentration is reached in a dosing interval. |
MRT | Mean residence time. 。 Note that for drugs with prolonged half-lives, the extrapolation necessary to compute the term |
CL | Total drug clearance.
Here,DMis the dose amount. |
Sparse Sampling.为了计算PK参数,在药物给药后需要为每个个体的多个时间点进行测量的浓度。在某些情况下,获得有关单个主题的纵向数据是不可行的或不切实际的。在这种情况下,在每个时间点从多个个体收集浓度数据,然后平均以计算每个组的NCA参数。Simbiology通过在同一时间点获取所有个体的因变量的平均值来执行稀疏抽样。然后,它返回每个组的NCA参数值。一个组中每个个体(ID)的每个测量的时间值必须相同。
Calculating NCA Parameters
You can calculate NCA parameters using theSbionca
function in the command line or using theSimBiology Model Analyzer应用程序。
Using sbionca
Sbionca
provides command line functionality to compute NCA parameters. Define the data classification options and parameter calculation options using an option object created bySbioncaoptions
。For an example, seeCompute NCA Parameters from Concentration-Time Data。
Using SimBiology Model Analyzer
After you import the data, selectProgram>Non-Compartmental Analysison theHometab. You can classify your data column in theNCAstep of the program. If your data has a grouping column, specify it usingGroup。UseIDto specify the inner level of grouping. Specify the dosing data column (IV Bolus Dose或者Extravascular Dose).Lower limit of quantization (LOQ)is a threshold below which the values of dependent variables are truncated to zero.
Lambda Time Rangelets you specify a custom time range to compute the terminal rate constant (Lambda_z). The time range applies to all groups; you cannot specify a different time range for each group.
CMAX时间范围lets you specify a custom time range to report the maximum observed concentration within the range (C_max) and the time (T_max) when it is observed. You can specify a different time range for each group.
Partial AUClets you specify a custom time range to compute the partial AUC bounded by the start and end times. You can specify a different time range for each group.
You can export the NCA results to MATLAB workspace. By default, the data is exported as atable。将其转换为dataset
(Statistics and Machine Learning Toolbox), 利用table2dataset
(Statistics and Machine Learning Toolbox)。
For a workflow example, seeCalculate NCA Parameters and Fit Model to PK/PD Data Using SimBiology Model Analyzer App。