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_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 the analysis. Does not include missing or non-numeric observations, observations before dosing time, or interval observations where volume is zero. Does not include the point at dosing time if it was not observed but was 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 the collection interval prior to the first collection interval with measurable (positive) rate. Computed for all interval data models.
Tmax_Rate: Midpoint of the 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