Title:	Model Based Bio-Equivalence
Version:	0.1.0
Description:	Uses several Nonlinear Mixed effect (NONMEM) models (as NONMEM control files) to perform bootstrap model averaging and Monte Carlo Simulation for Model Based Bio-Equivalence (MBBE). Power is returned as the fraction of the simulations with successful bioequivalence (BE) test, for maximum concentration (Cmax), Area under the curve to the last observed value (AUClast) and Area under the curve extrapolate to infinity (AUCinf). See Hooker, A. (2020) Improved bioequivalence assessment through model-informed and model-based strategies https://www.fda.gov/media/138035/download.
URL:	https://github.com/certara/mbbe
BugReports:	https://github.com/certara/mbbe/issues
License:	LGPL-3
Encoding:	UTF-8
Imports:	dplyr, stringr, xml2, PKNCA, magrittr, nlme, emmeans, future, furrr (≥ 0.3.1), processx, tictoc, ggplot2, ps, jsonlite
RoxygenNote:	7.2.3
Suggests:	knitr, rmarkdown, testthat
VignetteBuilder:	knitr
NeedsCompilation:	no
Packaged:	2024-02-01 14:38:04 UTC; jcraig
Author:	Mark Sale [aut, cre] (Funded by FDA/NIH grant 1U01FD007355), James Craig [aut], Michael Tomashevskiy [aut]
Maintainer:	Mark Sale <mark.sale@certara.com>
Repository:	CRAN
Date/Publication:	2024-02-03 11:20:02 UTC

Calculate Non-Compartmental Analysis (NCA) Parameters

Description

This function performs Non-Compartmental Analysis (NCA) to derive key pharmacokinetic parameters such as Cmax, AUCinf, and AUClast for specified time intervals.

Usage

calc_NCA(
  run_dir,
  ngroups,
  reference_groups,
  test_groups,
  NCA_end_time,
  samp_size
)

Arguments

Details

The calc_NCA function internally calls getNCA for each sample in the sequence from 1 to samp_size. Note that the function is currently executed in a serial manner and is not parallelized.

Value

The function returns a list containing the derived NCA parameters for each sample.

Examples

## Not run: 
run_dir <- "c:/Workspace/mbbe"
ngroups <- 4
reference_groups <- c(1,2)
test_groups <- c(3,4)
NCA_end_time <- 7
samp_size <- 6
calc_NCA(run_dir, ngroups, reference_groups, test_groups, NCA_end_time, samp_size)

## End(Not run)

Calculate Bioequivalence Power

Description

Computes the power for bioequivalence (BE) testing based on EMA standards statistics applied to each Monte Carlo simulation. The power is determined by the proportion of simulations that meet the BE criteria.

Usage

calc_power(run_dir, samp_size, alpha, model_averaging_by, NTID)

Arguments

Details

When the simulation is conducted by study (i.e., a unique model for each study), this results in model averaging at the study level. If model_averaging_by is set to "subject", data from different studies are merged. For each study dataset, subjects are randomly selected (without replacement) from across all studies.

The function iterates over each sample, reading the corresponding NCAresults (designated by the sample number). Subsequently, it determines if each sample meets or fails the BE testing criteria.

Value

A list containing the results for:

• Cmax_result: Power for the Cmax parameter.

• AUCinf_result: Power for the AUCinf parameter.

• AUClast_result: Power for the AUClast parameter. All power values range between 0 and 1.

Examples

calc_power(
 run_dir = system.file(package = "mbbe", "examples", "calc_power"),
 samp_size = 5,
 alpha = 0.05,
 model_averaging_by = "study",
 NTID = FALSE
)

run_example for Model-Based BE Assessment

Description

This function calls the example models (model1-5.mod), performs the bootstrap, model averaging and the Monte Carlo simulation.

Usage

run_example(run_dir, nmfe_path, Include_R_Code = FALSE, plan = "multisession")

Arguments

Details

The function executes the mbbe::run_mbbe_json() function. A user supplied installation of NONMEM is required run_dir is the parent folder where the models are to be run, nmfe_path is the path the nmfe??.bat where ?? is the version of NONMEM available plan is "sequential", "multisession","multicore", defining the plan for parallel execution (sequential is non-parallel execution) The function uses the included file mbbeargs.json as the options file for the run, and runs 5 supplied models for model averaging. Monte Carlo Simulation is then done, with the number of samples set in the mbbearg.json file, to 10 (probaby more would be appropriate for and actual power analysis) The model selection for the model averaging also includes a penalty calculate by the script RPenaltyCode.r for missing Cmax, AUCinf and AUClast Run time on 32 cores is ~3 minutes without the R code execution an 10 minutes with and the output should include:

Value

A list containing:

• Cmax_power: Power for Cmax

• AUClast_power: Power for AUClast

• AUCinf_power: Power for AUCinf

• run_dir: Directory where the function was executed

• Num_identifiable: Number of identifiable parameters

• BICS: Bayesian Information Criterion Scores

Examples

## Not run: 
run_dir <- tempdir()
mbbe::run_example(run_dir = run_dir,
  nmfe_path = "c:/nm74g64/util/nmfe74.bat",
  plan = "multisession")

## End(Not run)

Execute MBBE Analysis

Description

This function runs the MBBE analysis. It's typically called by run_mbbe_json which provides the necessary options via a JSON file.

Usage

run_mbbe(
  crash_value,
  ngroups,
  reference_groups,
  test_groups,
  num_parallel,
  samp_size,
  run_dir,
  model_source,
  nmfe_path,
  delta_parms,
  use_check_identifiable,
  NCA_end_time,
  rndseed,
  simulation_data_path,
  plan = c("multisession", "sequential", "multicore"),
  alpha_error = 0.05,
  NTID = FALSE,
  model_averaging_by = "study",
  user_R_code = FALSE,
  R_code_path = "",
  save_plots = FALSE,
  ...
)

Arguments

Details

This function is primarily intended to be called by run_mbbe_json, which provides input parameters through a JSON configuration.

Value

A list containing:

• Cmax_power: Power for Cmax

• AUClast_power: Power for AUClast

• AUCinf_power: Power for AUCinf

• run_dir: Directory where the function was executed

• Num_identifiable: Number of identifiable parameters

• BICS: Bayesian Information Criterion Scores

run_mbbe_json

Description

Runs MBBE from a json file of options e.g., calls run_mbbe

Usage

run_mbbe_json(Args.json)

Arguments

Value

A list containing:

• Cmax_power: Power for Cmax

• AUClast_power: Power for AUClast

• AUCinf_power: Power for AUCinf

• run_dir: Directory where the function was executed

• Num_identifiable: Number of identifiable parameters

• BICS: Bayesian Information Criterion Scores

Examples

## Not run: 
run_mbbe_json("Args.json")

## End(Not run)