Example Replicate Simulation Output of PK Exposure Metrics Across Covariate Scenarios

Raw replicate simulation output behind data_sad_pkforest: PK exposure metrics for a typical individual under six covariate scenarios, one row per scenario per replicate, with the metrics as columns. This is the shape a forest plot simulation produces before test/reference ratios are formed.

Usage

data_sad_pkforest_sim

Format

`data.frame` a data frame with 3000 rows and 9 columns:

ID: Scenario identifier (values: 1=reference, 2=fed, 3=50 kg, 4=60 kg, 5=80 kg, 6=90 kg)
SIM: Replicate identifier (1-500 per scenario); each replicate uses one sampled parameter set across all scenarios
WTBL: Scenario body weight (units: kg; 70 kg for the reference)
FOOD: Scenario food status (values: 0=fasted, 1=high-fat meal)
DOSE: Dose (units: mg; 200 mg once daily in every scenario)
CMAX: Maximum concentration over the steady-state dosing interval (units: ng/mL)
CMIN: Concentration at the end of the steady-state dosing interval (units: ng/mL)
AUC: Area under the concentration-time curve over the 24-hour dosing interval (units: ng*h/mL)
CAVG: Average concentration over the dosing interval, AUC / 24 (units: ng/mL)

Source

simulated

Details

Each scenario is a typical individual (inter-individual variability zeroed) receiving 200 mg once daily to steady state, simulated with the internal pkmodel. Each of the 500 replicates runs every scenario on its own parameter set, drawn by parametric bootstrap from a multivariate normal on the model's log typical values and covariate coefficients with an assumed variance-covariance matrix (the structure of sampling from a model's covariance step). Exposure metrics are derived over the 24-hour dosing interval at steady state. See data-raw/data_sad_raw.R.