WNL_Test_cases

Framework Tests

PHX Installation: Proper installation of all files in the correct location.

CSV File Comparison Success: Correct identification of identical CSV files by the comparison tool.

CSV File Comparison Failure: Correct identification of differing CSV files by the comparison tool.

WinNonlin Tests

PHX Desc Stats No Weighting: Descriptive Statistics with no weighting, including confidence intervals, specified number of SD, standard percentiles, and user-defined percentiles.

PHX Desc Stats Weighting: Descriptive Statistics with weighting, including confidence intervals and units.

PHX DW Transformation Arithmetic: Data Wizard Transformation with each of the predefined arithmetic transformations.

PHX DW Transformation Baseline: Data Wizard Baseline Transformations including change from fixed value, change from minimum per group, percent change from fixed value, and ratios using minimum per group.

PHX DW Transformation Functions: Data Wizard Transformation to perform inverse, absolute, exponential, ln, log10, and square root calculations.

PHX Indiv LM 501: Non-population Phoenix Model with constant linear model. This test case is not applicable when run on a 32-bit system.

PHX Indiv MM 301: Non-population Phoenix Model with one compartment, bolus input, and Michaelis-Menten output. This test case is not applicable when run on a 32-bit system.

PHX Indiv PD 103: Non-population Phoenix Model with an inhibitory effect E0 model. This test case is not applicable when run on a 32-bit system.

PHX Indiv PD 105: Non-population Phoenix Model with Sigmoid Emax model. This test case is not applicable when run on a 32-bit system.

PHX Indiv PK 1 Clearance: Non-population Phoenix Model with one compartment, IV bolus input, and first-order output with clearance parameterization. This test case is not applicable when run on a 32-bit system.

PHX Indiv PK 1 PD 101: Non-population Phoenix Model with an effect compartment PK/PD link model. This test case is not applicable when run on a 32-bit system.

PHX Indiv PK 12: Non-population Phoenix Model with two compartments, first-order input, first-order output, lag time, and with micro-constants as primary parameters. This test case is not applicable when run on a 32-bit system.

PHX Indiv PK 18: Non-population Phoenix Model with three compartments, IV bolus input, first-order output, and with macro-constants as primary parameters. This test case is not applicable when run on a 32-bit system.

PHX Indiv PK 6: Non-population Phoenix Model with one compartment, equal first-order input and output, and with lag time. This test case is not applicable when run on a 32-bit system.

PHX Indiv PK 9 Units: Non-population Phoenix Model with two compartments, constant IV infusion input, first-order output, and with micro-constants as primary parameters, with units for the primary and secondary parameter results. This test case is not applicable when run on a 32-bit system.

PHX Ratios and Differences: Ratios and Differences from one input worksheet, from two input worksheets, and using means of non-unique values.

WNL Bioeq Average Crossover 2x2: Average Bioequivalence using the default models for non-replicated two-period crossover data, both the fixed and random effects default model and the all fixed-effects default model.The fixed-effects model also specifies numerator and denominator for an additional F-test.

WNL Bioeq Average Crossover 2x4: Average Bioequivalence using the default model for replicated crossover data, in this case with four periods.

WNL Bioeq Average Parallel: Average Bioequivalence using the default model for parallel data.

WNL Bioeq Population Individual: Population and individual Bioequivalence using the predefined model.

WNL Crossover Separate: Crossover nonparametric analysis using separate input data columns.

WNL Crossover Stacked: Crossover nonparametric analysis using stacked input data columns.

WNL Deconv 1exp None TimesFromCol Units: Deconvolution using one-exponent unit impulse response (UIR) function, with no smoothing, output times from a worksheet, and units.

WNL Deconv 2exp User Rate Change ToLastPt: Deconvolution using two-exponent UIR function with specified smoothing parameter, initial rate and initial change in rate set to 0, and output times generated from 0 to the last observed time point.

WNL Deconv 3exp Auto Rate NumPts FromTo: Deconvolution using three-exponent UIR function, using the Phoenix-determined optimal smoothing parameter value, initial change in rate set to 0, and output times generated for specified time range.

WNL LinMix Ancova Options: Linear Mixed Effects using ANCOVA model (classification and regressors), with an interaction term, random intercept, dependent variable transformation, contrasts, and estimates.

WNL LinMix AR ARH CSH FA0: Linear Mixed Effects models with autoregressive, heterogeneous autoregressive, heterogeneous compound symmetry, and no-diagonal factor analytic types of covariance structure, one model tests no intercept for fixed effects.

WNL LinMix CS TOEP UN: Linear Mixed Effects models with compound symmetry, Toeplitz, and unstructured types of covariance structure, and with using a weight variable.

WNL LinMix VC Contrasts Estimates LSMs: Linear Mixed Effects models with variance components covariance structure type, contrasts, estimates, least squares means and pairwise differences, and residual DF.

WNL LM 501 Constant: Least-Squares Regression Modeling, Linear model 501 (constant).

WNL LM 502 Linear: Least-Squares Regression Modeling, Linear model 502 (linear).

WNL LM 503 Quadratic: Least-Squares Regression Modeling, Linear model 503 (quadratic).

WNL LM 504 Cubic: Least-Squares Regression Modeling, Linear model 504 (cubic).

WNL MM 301: Least-Squares Regression Modeling, one compartment model with IV bolus input and Michaelis-Menten output.

WNL MM 302: Least-Squares Regression Modeling, one compartment model with constant IV input and Michaelis-Menten output.

WNL MM 303: Least-Squares Regression Modeling, one compartment model with first-order input and Michaelis-Menten output.

WNL MM 304: Least-Squares Regression Modeling, one compartment model with first-order input, Michaelis-Menten output, and a time lag.

WNL NCA Extravascular NonSS PartialAUC: NonCompartmental Analysis for non-steady state, plasma, extravascular data, using the linear trapezoidal linear interpolation calculation method and including partial areas.

WNL NCA Infusion NonSS PartialAUC Rules: NonCompartmental Analysis for non-steady state, plasma, IV infusion data, using the linear trapezoidal linear interpolation calculation method and Lambda Z Best Fit rules, and including partial areas.

WNL NCA IV Bolus NonSS PartialAUC LinearLog Trap: NonCompartmental Analysis for non-steady state, plasma, IV bolus data using the linear log trapezoidal calculation method and including a partial area.

WNL NCA IV Bolus SS InsertC0 UserDefined: NonCompartmental Analysis for steady state, plasma, IV bolus data, using the linear trapezoidal linear interpolation calculation method and including methods for inserting C0, partial areas, user-defined parameters, and concentrations (computed at specified times).

WNL NCA PartialAUC LinearUpLogDown Units: NonCompartmental Analysis for plasma, extravascular data, using the linear up log down calculation method and including partial areas and units.

WNL NCA PartialAUC LinTrapLinLogInterp Units: NonCompartmental Analysis for plasma, extravascular data, using the linear trapezoidal linear/log interpolation calculation method and including partial areas and units.

WNL NCA PD UserDefined: NonCompartmental Analysis for drug effect data, using the linear trapezoidal linear interpolation calculation method, with baseline and threshold values, user-defined time ranges for slopes, partial area, user-defined parameter, and effects computed at specified x-values.

WNL NCA SparseSampling Extravascular: NonCompartmental Analysis for sparse-sampling, plasma, extravascular data, using the linear trapezoidal linear interpolation calculation method, includes case with missing values.

WNL NCA Urine TimeRange Flags Sort: NonCompartmental Analysis for urine data, using the linear trapezoidal linear interpolation calculation method, with Lambda Z acceptance criteria, user-defined time ranges for slopes, and a sort variable.

WNL NCA Weighting InsertC0: NonCompartmental Analysis for plasma, IV bolus data, using the linear trapezoidal linear interpolation calculation method, and including methods for inserting C0, partial areas, 1/Y weighting, and a sort variable.

WNL NPS Regular Linear BestFit: NonParametric Superposition with dosing at regular intervals and using linear interpolation.

WNL NPS Variable Log StartEnd: NonParametric Superposition with variable dosing intervals, a specified output time range, and using log interpolation.

WNL PD 101: Least-Squares Regression Modeling, simple Emax model.

WNL PD 102: Least-Squares Regression Modeling, simple Emax model with baseline effect.

WNL PD 103: Least-Squares Regression Modeling, inhibitory effect Emax model.

WNL PD 104: Least-Squares Regression Modeling, inhibitory effect model with a baseline effect parameter.

WNL PD 105: Least-Squares Regression Modeling, sigmoid effect model without a baseline effect parameter.

WNL PD 106: Least-Squares Regression Modeling, sigmoid Emax model with baseline effect.

WNL PD 107: Least-Squares Regression Modeling, sigmoid inhibitory effect model.

WNL PD 108: Least-Squares Regression Modeling, sigmoid inhibitory effect model with a baseline effect parameter.

WNL PK 1 Clearance: Least-Squares Regression Modeling, one compartment PK model with IV bolus input and first-order output with clearance parameterization.

WNL PK 1 PD 101 Linked: Least-Squares Regression Modeling, PK/PD linked model with effect compartment.

WNL PK 10: Least-Squares Regression Modeling, two compartment PK model with constant IV infusion input and first-order output, with macro-constants as primary parameters.

WNL PK 11: Least-Squares Regression Modeling, two compartment PK model with first-order input, first-order output, without lag time, with micro-constants as primary parameters.

WNL PK 12: Least-Squares Regression Modeling, two compartment PK model with first-order input, first-order output, with lag time, with micro-constants as primary parameters.

WNL PK 13: Least-Squares Regression Modeling, two compartment PK model with first-order input, first-order output, without lag time, with macro-constants as primary parameters.

WNL PK 14: Least-Squares Regression Modeling, two compartment PK model with first-order input, first-order output, with lag time, with macro-constants as primary parameters.

WNL PK 15: Least-Squares Regression Modeling, one compartment PK model with simultaneous IV bolus and constant IV infusion.

WNL PK 16: Least-Squares Regression Modeling, two compartment PK model with simultaneous IV bolus and constant IV infusion input, with micro-constants as primary parameters.

WNL PK 17: Least-Squares Regression Modeling, two compartment PK model with simultaneous IV bolus and constant IV infusion input, with macro-constants as primary parameters.

WNL PK 18: Least-Squares Regression Modeling, three compartment PK model with IV bolus input, first-order output, with macro-constants as primary parameters.

WNL PK 19: Least-Squares Regression Modeling, three compartment PK model with constant IV infusion, with macro-constants as primary parameters.

WNL PK 2: Least-Squares Regression Modeling, one compartment PK model with constant IV infusion input and first-order absorption.

WNL PK 3 Clearance: Least-Squares Regression Modeling, one compartment PK model with first-order input and output, without lag time but with clearance parameterization.

WNL PK 4 Clearance: Least-Squares Regression Modeling, one compartment PK model with first-order input and output, with lag time and clearance parameterization.

WNL PK 5: Least-Squares Regression Modeling, one compartment PK model with equal first-order input and output, without lag time.

WNL PK 6: Least-Squares Regression Modeling, one compartment PK model with equal first-order input and output, with lag time.

WNL PK 7 Clearance: Least-Squares Regression Modeling, two compartment PK model with IV bolus input and first-order output, with micro-constants as primary parameters and with clearance parameterization.

WNL PK 8: Least-Squares Regression Modeling, two compartment PK model with IV bolus input and first-order output, with macro constants as primary parameters.

WNL PK 9: Least-Squares Regression Modeling, two compartment PK model with constant IV infusion input and first-order output, with micro-constants as primary parameters.

WNL SCM Linear: Semicompartmental Modeling using a linear piecewise PK model.

WNL SCM LinearLog: Semicompartmental Modeling using a PK model that is linear to Tmax and then log-linear after Tmax.

WNL SCM Log: Semicompartmental Modeling using a log-linear piecewise PK model.