Data structure: NCA for interval data (e.g., urine data) requires the following input data:
Starting and ending time of each collection interval
Concentrations
Volumes
From this data, models 210–212 compute the following for the analysis:
Midpoint of each collection interval=(Starting time+Ending time)/2
Excretion rate for each interval (amount eliminated per unit of time)=(Concentration*Volume)/(Ending time-Starting time)
Output: Interval data models (Models 210–212) estimate the following parameters.
The worksheet will include the Sort(s), Carry(ies), parameter names, units, and computed values. A User Defined Parameters Pivoted worksheet will include the pivoted form of the User Defined Parameters worksheet.
Interval (urine) parameters that do not depend on Lambda Z
Amount_Recovered: Cumulative amount eliminated.
= 
AURC_all: Area under the excretion rate curve from the time of dosing to the midpoint of the interval with the last rate. If the last rate is positive, AURC_last=AURC_all.
AURC_all_D: = AURC_all/Dose
AURC_last: Area under the excretion rate curve from time of dosing to Mid_Pt_last.
AURC_last_D: = AURC_last/Dose
Dose: Amount of last administered dose. This is assumed to be zero if not specified.
Dosing time: Available as ‘Time’ in the Dosing Used results. Time of last administered dose. It is assumed to be zero unless otherwise specified. This parameter is used mainly with steady-state data, where time may be coded as the time elapsed since the first dose, or the elapsed time since the time of the first dose.
Max_Rate: Maximum observed excretion rate, at time Tmax_Rate as defined below.
Mid_Pt_last: Midpoint of collection interval associated with last measurable (positive) observed excretion rate.
No_points_lambda_z: Number of points used in the computation of Lambda Z. If Lambda Z cannot be estimated, this is set to zero.
N_Samples: Number of observations in analysis. Does not include missing, non-numeric, or interval (where volume is zero) observations, or observations before dosing time. Does not include the point at dosing time if it was not observed but inserted by the engine.
Percent_Recovered: = 100(Amount_Recovered/Dose)
Rate_last: Last observed measurable (positive) rate at time Mid_Pt_last.
Tlag: Midpoint of collection interval prior to the first collection interval with measurable (positive) rate. Computed for all interval data models.
Tmax_Rate: Midpoint of collection interval associated with the maximum observed excretion rate. If the maximum observed excretion rate is not unique, then the first maximum is used.
Vol_UR: Sum of Volumes.
Interval (urine) parameters that are estimated when Lambda Z is estimated
The following list includes some parameters that are extrapolated to infinity. These parameters are calculated two ways: based on the last observed excretion rate: Rate_last (indicated by “_obs” appended to the parameter name), or based on the last predicted excretion rate: Rate_last_pred (indicated by “_pred” appended to the parameter name), where the predicted value is based on the linear regression performed to estimate Lambda Z.
AURC_%Extrap(_obs, _pred): Percent of AURC_INF(_obs, _pred) that is extrapolated.
AURC_INF(_obs, _pred): Area under the urinary excretion rate curve extrapolated to infinity, based on the last observed excretion rate (_obs) or the last predicted rate (_pred), i.e., the excretion rate at the final midpoint estimated using the linear regression for Lambda Z. Note that AURC_INF is theoretically equal to Amount_Recovered, but will differ due to experimental error.
Corr_XY: Correlation between midpoints and log excretion rates for the points used in the estimation of Lambda Z.
HL_Lambda_z: Terminal half-life=ln(2)/Lambda Z
Lambda_z: First-order rate constant associated with the terminal (log-linear) portion of the curve. This is estimated via linear regression of midpoints vs. log excretion rates.
Lambda_z_intercept: Intercept on log scale estimated via linear regression of midpoints vs. log excretion rates.
Lambda_z_lower: Lower limit on midpoint for values to be included in Lambda Z estimation.
Lambda_z_upper: Upper limit on midpoint for values to be included in Lambda Z estimation.
Rate_last_pred: Predicted rate at Mid_Pt_last.
= 
Rsq: Goodness of fit statistic for the terminal elimination phase.
Rsq_Adjusted: Goodness of fit statistic for the terminal elimination phase, adjusted for the number of points used in the estimation of Lambda Z.
Span: = (Lambda_z_upper – Lambda_z_lower)/HL_Lambda_z