Creates a list of the initialized module state
Examples
# Within shiny both session and input variables will exist,
# this creates examples here for testing purposes:
sess_res = MB_test_mksession()
#> → ASM: including file
#> → ASM: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → ASM: dest: file.path("config","report.docx")
#> → ASM: including file
#> → ASM: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → ASM: dest: file.path("config","report.pptx")
#> → ASM: including file
#> → ASM: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → ASM: dest: file.path("config","report.yaml")
#> → ASM: State initialized
#> → ASM: module isgood: TRUE
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → MB: dest: file.path("config","report.docx")
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → MB: dest: file.path("config","report.pptx")
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → MB: dest: file.path("config","report.yaml")
#> ! MB: User-defined model: /Users/jmh/projects/ruminate/github/ruminate/docs/reference/user_model.R not found (skipping)
#> ! MB: User-defined model: /Users/jmh/projects/ruminate/github/ruminate/docs/reference/user_model.ctl not found (skipping)
#> → MB: module checksum updated:24933f86b657b9503f22440e8c4d3cac
#> → MB: State initialized
#> → MB: loading model idx: 1
#>
#>
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → MB: model checksum updated: ea755ef125efac5ee7c63278746f755b
#> → MB: module checksum updated:4384a4b237a13dcf1336aa17d775eaba
#>
#>
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → MB: model checksum updated: 85045ec199c6740c2db16ac29e78d45e
#> → MB: module checksum updated:2fbe750710c93056cec56f103b8ea2a8
#> → MB: -> setting name: One compartment model
#> → MB: -> setting time scale: hours
#> → MB: -> setting base from: user
#> → MB: -> setting catalog selection:
#> → MB: -> setting base model id: manual
#> → MB: -> setting base model name: manual
#> → MB: model checksum updated: 89a81406b74e064e3b6900ddd55b4fc4
#> → MB: module checksum updated:d38d5ad2d937598ab9de9eee9a6373f8
#> → MB: added element idx: 1
#> → MB: loading model idx: 2
#>
#>
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → MB: model checksum updated: 760e9e8b79d3ed74d07e5292550602ee
#> → MB: module checksum updated:f53f16d61b4b3e06e914e9708d695b03
#> → MB: -> setting name: PK Biomarker
#> → MB: -> setting time scale: days
#> → MB: -> setting base from: user
#> → MB: -> setting catalog selection:
#> → MB: -> setting base model id: manual
#> → MB: -> setting base model name: manual
#> → MB: model checksum updated: 733d2a99d8aedb3dc652ebab2886310e
#> → MB: module checksum updated:da0eb5564092da700f999b139d202cee
#> → MB: added element idx: 2
#> → MB: module isgood: TRUE
session = sess_res$session
input = sess_res$input
state = MB_init_state(
FM_yaml_file = system.file(package = "formods",
"templates",
"formods.yaml"),
MOD_yaml_file = system.file(package = "ruminate",
"templates",
"MB.yaml"),
id = "MB",
session = session)
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → MB: dest: file.path("config","report.docx")
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → MB: dest: file.path("config","report.pptx")
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → MB: dest: file.path("config","report.yaml")
#> ! MB: User-defined model: /Users/jmh/projects/ruminate/github/ruminate/docs/reference/user_model.R not found (skipping)
#> ! MB: User-defined model: /Users/jmh/projects/ruminate/github/ruminate/docs/reference/user_model.ctl not found (skipping)
#> → MB: module checksum updated:24933f86b657b9503f22440e8c4d3cac
#> → MB: State initialized
state
#> $yaml
#> $yaml$FM
#> $yaml$FM$include
#> $yaml$FM$include$files
#> $yaml$FM$include$files[[1]]
#> $yaml$FM$include$files[[1]]$file
#> $yaml$FM$include$files[[1]]$file$source
#> [1] "file.path(system.file(package=\"onbrand\"), \"templates\", \"report.docx\")"
#>
#> $yaml$FM$include$files[[1]]$file$dest
#> [1] "file.path(\"config\",\"report.docx\")"
#>
#>
#>
#> $yaml$FM$include$files[[2]]
#> $yaml$FM$include$files[[2]]$file
#> $yaml$FM$include$files[[2]]$file$source
#> [1] "file.path(system.file(package=\"onbrand\"), \"templates\", \"report.pptx\")"
#>
#> $yaml$FM$include$files[[2]]$file$dest
#> [1] "file.path(\"config\",\"report.pptx\")"
#>
#>
#>
#> $yaml$FM$include$files[[3]]
#> $yaml$FM$include$files[[3]]$file
#> $yaml$FM$include$files[[3]]$file$source
#> [1] "file.path(system.file(package=\"onbrand\"), \"templates\", \"report.yaml\")"
#>
#> $yaml$FM$include$files[[3]]$file$dest
#> [1] "file.path(\"config\",\"report.yaml\")"
#>
#>
#>
#>
#>
#> $yaml$FM$deployed
#> [1] FALSE
#>
#> $yaml$FM$code
#> $yaml$FM$code$theme
#> [1] "vibrant_ink"
#>
#> $yaml$FM$code$showLineNumbers
#> [1] TRUE
#>
#> $yaml$FM$code$gen_file
#> [1] "run_analysis.R"
#>
#> $yaml$FM$code$gen_preamble
#> [1] "# formods automated output ------------------------------------------------\n# https://formods.ubiquity.tools/\nrm(list=ls())"
#>
#> $yaml$FM$code$packages
#> [1] "onbrand" "writexl"
#>
#>
#> $yaml$FM$notifications
#> $yaml$FM$notifications$config
#> $yaml$FM$notifications$config$success
#> $yaml$FM$notifications$config$success$useFontAwesome
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$success$useIcon
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$success$background
#> [1] "#5bb85b"
#>
#>
#> $yaml$FM$notifications$config$failure
#> $yaml$FM$notifications$config$failure$useFontAwesome
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$failure$useIcon
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$failure$background
#> [1] "#d9534f"
#>
#>
#> $yaml$FM$notifications$config$info
#> $yaml$FM$notifications$config$info$useFontAwesome
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$info$useIcon
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$info$background
#> [1] "#5bc0de"
#>
#>
#> $yaml$FM$notifications$config$warning
#> $yaml$FM$notifications$config$warning$useFontAwesome
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$warning$useIcon
#> [1] FALSE
#>
#> $yaml$FM$notifications$config$warning$background
#> [1] "#f0ac4d"
#>
#>
#>
#>
#> $yaml$FM$reporting
#> $yaml$FM$reporting$enabled
#> [1] TRUE
#>
#> $yaml$FM$reporting$content_init
#> $yaml$FM$reporting$content_init$xlsx
#> [1] "rpt = list(summary = NULL,\n sheets = list())"
#>
#> $yaml$FM$reporting$content_init$docx
#> [1] "rpt = onbrand::read_template(\n template = file.path(\"config\", \"report.docx\"),\n mapping = file.path(\"config\", \"report.yaml\"))"
#>
#> $yaml$FM$reporting$content_init$pptx
#> [1] "rpt = onbrand::read_template(\n template = file.path(\"config\", \"report.pptx\"),\n mapping = file.path(\"config\", \"report.yaml\"))"
#>
#>
#> $yaml$FM$reporting$phs
#> $yaml$FM$reporting$phs[[1]]
#> $yaml$FM$reporting$phs[[1]]$name
#> [1] "HEADERLEFT"
#>
#> $yaml$FM$reporting$phs[[1]]$location
#> [1] "header"
#>
#> $yaml$FM$reporting$phs[[1]]$value
#> [1] ""
#>
#> $yaml$FM$reporting$phs[[1]]$tooltip
#> [1] "left header text"
#>
#>
#> $yaml$FM$reporting$phs[[2]]
#> $yaml$FM$reporting$phs[[2]]$name
#> [1] "HEADERRIGHT"
#>
#> $yaml$FM$reporting$phs[[2]]$location
#> [1] "header"
#>
#> $yaml$FM$reporting$phs[[2]]$value
#> [1] ""
#>
#> $yaml$FM$reporting$phs[[2]]$tooltip
#> [1] "right header text"
#>
#>
#> $yaml$FM$reporting$phs[[3]]
#> $yaml$FM$reporting$phs[[3]]$name
#> [1] "FOOTERLEFT"
#>
#> $yaml$FM$reporting$phs[[3]]$location
#> [1] "footer"
#>
#> $yaml$FM$reporting$phs[[3]]$value
#> [1] ""
#>
#> $yaml$FM$reporting$phs[[3]]$tooltip
#> [1] "left footer text"
#>
#>
#>
#> $yaml$FM$reporting$phs_formatting
#> $yaml$FM$reporting$phs_formatting$width
#> [1] "100%"
#>
#> $yaml$FM$reporting$phs_formatting$tt_position
#> [1] "left"
#>
#> $yaml$FM$reporting$phs_formatting$tt_size
#> [1] "medium"
#>
#>
#>
#> $yaml$FM$ui
#> $yaml$FM$ui$button_style
#> [1] "fill"
#>
#> $yaml$FM$ui$select_size
#> [1] 10
#>
#> $yaml$FM$ui$color_green
#> [1] "#00BB8A"
#>
#> $yaml$FM$ui$color_red
#> [1] "#FF475E"
#>
#> $yaml$FM$ui$color_blue
#> [1] "#0088FF"
#>
#> $yaml$FM$ui$color_purple
#> [1] "#bd2cf4"
#>
#>
#> $yaml$FM$data_meta
#> $yaml$FM$data_meta$data_header
#> [1] "<span style='color:===COLOR==='><b>===NAME===</b><br/><font size='-3'>===LABEL===</font></span>"
#>
#> $yaml$FM$data_meta$subtext
#> [1] "===LABEL===: ===RANGE==="
#>
#> $yaml$FM$data_meta$many_sep
#> [1] ",...,"
#>
#> $yaml$FM$data_meta$data_types
#> $yaml$FM$data_meta$data_types$character
#> $yaml$FM$data_meta$data_types$character$color
#> [1] "#DD4B39"
#>
#> $yaml$FM$data_meta$data_types$character$label
#> [1] "text"
#>
#>
#> $yaml$FM$data_meta$data_types$double
#> $yaml$FM$data_meta$data_types$double$color
#> [1] "#3C8DBC"
#>
#> $yaml$FM$data_meta$data_types$double$label
#> [1] "num"
#>
#>
#> $yaml$FM$data_meta$data_types$integer
#> $yaml$FM$data_meta$data_types$integer$color
#> [1] "#3C8DBC"
#>
#> $yaml$FM$data_meta$data_types$integer$label
#> [1] "num"
#>
#>
#> $yaml$FM$data_meta$data_types$other
#> $yaml$FM$data_meta$data_types$other$color
#> [1] "black"
#>
#> $yaml$FM$data_meta$data_types$other$label
#> [1] "other"
#>
#>
#>
#>
#> $yaml$FM$labels
#> $yaml$FM$labels$default_ds
#> [1] "Original data set"
#>
#>
#> $yaml$FM$user_files
#> $yaml$FM$user_files$use_tmpdir
#> [1] TRUE
#>
#>
#> $yaml$FM$logging
#> $yaml$FM$logging$enabled
#> [1] TRUE
#>
#> $yaml$FM$logging$timestamp
#> [1] TRUE
#>
#> $yaml$FM$logging$timestamp_fmt
#> [1] "%Y-%m-%d %H:%M:%S"
#>
#> $yaml$FM$logging$log_file
#> [1] "formods_log.txt"
#>
#> $yaml$FM$logging$console
#> [1] TRUE
#>
#>
#>
#>
#> $MC
#> $MC$module
#> $MC$module$type
#> [1] "MB"
#>
#> $MC$module$depends
#> $MC$module$depends$id_ASM
#> [1] "ASM"
#>
#>
#>
#> $MC$element_object_name
#> [1] "MB_obj"
#>
#> $MC$sources
#> $MC$sources[[1]]
#> $MC$sources[[1]]$source
#> $MC$sources[[1]]$source$group
#> [1] "User-defined Models"
#>
#> $MC$sources[[1]]$source$name
#> [1] "rxode2 User model"
#>
#> $MC$sources[[1]]$source$description
#> [1] "User-defined rxode2 model"
#>
#> $MC$sources[[1]]$source$type
#> [1] "rxode2"
#>
#> $MC$sources[[1]]$source$obj
#> [1] "my_fcn"
#>
#> $MC$sources[[1]]$source$file
#> [1] "file.path(getwd(),\"user_model.R\")"
#>
#>
#>
#> $MC$sources[[2]]
#> $MC$sources[[2]]$source
#> $MC$sources[[2]]$source$group
#> [1] "User-defined Models"
#>
#> $MC$sources[[2]]$source$name
#> [1] "NONMEM User model"
#>
#> $MC$sources[[2]]$source$description
#> [1] "User-defined NONMEM model"
#>
#> $MC$sources[[2]]$source$type
#> [1] "NONMEM"
#>
#> $MC$sources[[2]]$source$file
#> [1] "file.path(getwd(),\"user_model.ctl\")"
#>
#>
#>
#> $MC$sources[[3]]
#> $MC$sources[[3]]$source
#> $MC$sources[[3]]$source$group
#> [1] "Model Library"
#>
#> $MC$sources[[3]]$source$type
#> [1] "nlmixr2lib"
#>
#> $MC$sources[[3]]$source$name
#> [1] "nlmixr2 Model Library"
#>
#>
#>
#>
#> $MC$code
#> $MC$code$packages
#> [1] "rxode2" "nonmem2rx" "nlmixr2lib"
#>
#> $MC$code$readOnly
#> [1] TRUE
#>
#> $MC$code$mode
#> [1] "r"
#>
#>
#> $MC$compact
#> $MC$compact$code
#> [1] TRUE
#>
#> $MC$compact$clip
#> [1] TRUE
#>
#>
#> $MC$reporting
#> $MC$reporting$enabled
#> [1] TRUE
#>
#> $MC$reporting$priority
#> [1] 1
#>
#>
#> $MC$formatting
#> $MC$formatting$code
#> $MC$formatting$code$width
#> [1] 800
#>
#> $MC$formatting$code$height
#> [1] 300
#>
#>
#> $MC$formatting$preview
#> $MC$formatting$preview$width
#> [1] "800px"
#>
#> $MC$formatting$preview$height
#> [1] "500px"
#>
#>
#> $MC$formatting$input
#> NULL
#>
#> $MC$formatting$current_element
#> $MC$formatting$current_element$width
#> [1] "200px"
#>
#> $MC$formatting$current_element$tooltip
#> [1] "Change the current model."
#>
#> $MC$formatting$current_element$tooltip_position
#> [1] "right"
#>
#>
#> $MC$formatting$element_name
#> $MC$formatting$element_name$width
#> [1] "200px"
#>
#>
#> $MC$formatting$button_clk_run
#> $MC$formatting$button_clk_run$size
#> [1] "sm"
#>
#> $MC$formatting$button_clk_run$block
#> [1] TRUE
#>
#>
#> $MC$formatting$button_clk_del
#> $MC$formatting$button_clk_del$size
#> [1] "sm"
#>
#> $MC$formatting$button_clk_del$block
#> [1] TRUE
#>
#> $MC$formatting$button_clk_del$tooltip
#> [1] "Delete the current model."
#>
#> $MC$formatting$button_clk_del$tooltip_position
#> [1] "right"
#>
#>
#> $MC$formatting$button_clk_save
#> $MC$formatting$button_clk_save$size
#> [1] "sm"
#>
#> $MC$formatting$button_clk_save$block
#> [1] TRUE
#>
#> $MC$formatting$button_clk_save$tooltip
#> [1] "Save the name for the current model."
#>
#> $MC$formatting$button_clk_save$tooltip_position
#> [1] "right"
#>
#>
#> $MC$formatting$button_clk_clip
#> $MC$formatting$button_clk_clip$size
#> [1] "sm"
#>
#> $MC$formatting$button_clk_clip$block
#> [1] TRUE
#>
#> $MC$formatting$button_clk_clip$tooltip
#> [1] "Copy the code to generate the current model to the clipboard."
#>
#> $MC$formatting$button_clk_clip$tooltip_position
#> [1] "right"
#>
#>
#> $MC$formatting$button_clk_copy
#> $MC$formatting$button_clk_copy$size
#> [1] "sm"
#>
#> $MC$formatting$button_clk_copy$block
#> [1] TRUE
#>
#> $MC$formatting$button_clk_copy$tooltip
#> [1] "Make a copy of the current model."
#>
#> $MC$formatting$button_clk_copy$tooltip_position
#> [1] "right"
#>
#>
#> $MC$formatting$button_clk_append_model
#> $MC$formatting$button_clk_append_model$size
#> [1] "sm"
#>
#> $MC$formatting$button_clk_append_model$block
#> [1] TRUE
#>
#> $MC$formatting$button_clk_append_model$tooltip
#> [1] "Append to current model."
#>
#> $MC$formatting$button_clk_append_model$tooltip_position
#> [1] "right"
#>
#>
#> $MC$formatting$button_clk_new
#> $MC$formatting$button_clk_new$size
#> [1] "sm"
#>
#> $MC$formatting$button_clk_new$block
#> [1] TRUE
#>
#> $MC$formatting$button_clk_new$tooltip
#> [1] "Create a new model."
#>
#> $MC$formatting$button_clk_new$tooltip_position
#> [1] "right"
#>
#> $MC$formatting$button_clk_new$width
#> [1] 100
#>
#>
#> $MC$formatting$export_nonmem
#> $MC$formatting$export_nonmem$size
#> [1] "sm"
#>
#> $MC$formatting$export_nonmem$block
#> [1] TRUE
#>
#> $MC$formatting$export_nonmem$color
#> [1] "primary"
#>
#> $MC$formatting$export_nonmem$tooltip
#> [1] "Download the current model in NONMEM format."
#>
#> $MC$formatting$export_nonmem$tooltip_position
#> [1] "right"
#>
#> $MC$formatting$export_nonmem$width
#> [1] 100
#>
#>
#> $MC$formatting$export_monolix
#> $MC$formatting$export_monolix$size
#> [1] "sm"
#>
#> $MC$formatting$export_monolix$block
#> [1] TRUE
#>
#> $MC$formatting$export_monolix$color
#> [1] "primary"
#>
#> $MC$formatting$export_monolix$tooltip
#> [1] "Download the current model in Monolix format."
#>
#> $MC$formatting$export_monolix$tooltip_position
#> [1] "right"
#>
#> $MC$formatting$export_monolix$width
#> [1] 100
#>
#>
#> $MC$formatting$catalog_selection
#> $MC$formatting$catalog_selection$width
#> [1] "200px"
#>
#> $MC$formatting$catalog_selection$truncate
#> [1] 65
#>
#> $MC$formatting$catalog_selection$tooltip
#> [1] "Select base model from the catalog."
#>
#> $MC$formatting$catalog_selection$tooltip_position
#> [1] "top"
#>
#>
#> $MC$formatting$model_type_selection
#> $MC$formatting$model_type_selection$width
#> [1] "200px"
#>
#> $MC$formatting$model_type_selection$tooltip
#> [1] "Select the type of the model being uploaded."
#>
#> $MC$formatting$model_type_selection$tooltip_position
#> [1] "right"
#>
#> $MC$formatting$model_type_selection$choices
#> $MC$formatting$model_type_selection$choices$rxode2
#> [1] "rxode2 function"
#>
#> $MC$formatting$model_type_selection$choices$NONMEM
#> [1] "NONMEM (XML, lst, or ctl)"
#>
#>
#> $MC$formatting$model_type_selection$default
#> [1] "rxode2"
#>
#>
#> $MC$formatting$upload_model_file
#> $MC$formatting$upload_model_file$width
#> [1] "400px"
#>
#>
#> $MC$formatting$append_model
#> $MC$formatting$append_model$tooltip
#> [1] "Append the selected sub-model to the current model."
#>
#> $MC$formatting$append_model$tooltip_position
#> [1] "bottom"
#>
#> $MC$formatting$append_model$no_models
#> [1] "None available"
#>
#> $MC$formatting$append_model$width
#> [1] "200px"
#>
#>
#> $MC$formatting$base_from
#> $MC$formatting$base_from$size
#> [1] "normal"
#>
#> $MC$formatting$base_from$status
#> [1] "primary"
#>
#> $MC$formatting$base_from$tooltip
#> [1] "You can select the base model from a catalog or upload your own"
#>
#> $MC$formatting$base_from$tooltip_position
#> [1] "bottom"
#>
#> $MC$formatting$base_from$choices
#> $MC$formatting$base_from$choices$catalog
#> [1] "Model Catalog"
#>
#> $MC$formatting$base_from$choices$user
#> [1] "User-defined model"
#>
#>
#> $MC$formatting$base_from$default
#> [1] "catalog"
#>
#>
#> $MC$formatting$time_scales
#> $MC$formatting$time_scales$width
#> [1] "200px"
#>
#> $MC$formatting$time_scales$default
#> [1] "weeks"
#>
#> $MC$formatting$time_scales$tooltip
#> [1] "Choose the timescale of the model."
#>
#> $MC$formatting$time_scales$tooltip_position
#> [1] "top"
#>
#> $MC$formatting$time_scales$choices
#> $MC$formatting$time_scales$choices$months
#> $MC$formatting$time_scales$choices$months$conv
#> [1] "1/(60*60*24*7*4)"
#>
#> $MC$formatting$time_scales$choices$months$verb
#> [1] "Months"
#>
#> $MC$formatting$time_scales$choices$months$match
#> [1] "mo"
#>
#>
#> $MC$formatting$time_scales$choices$weeks
#> $MC$formatting$time_scales$choices$weeks$conv
#> [1] "1/(60*60*24*7)"
#>
#> $MC$formatting$time_scales$choices$weeks$verb
#> [1] "Weeks"
#>
#> $MC$formatting$time_scales$choices$weeks$match
#> [1] "wk" "weeks"
#>
#>
#> $MC$formatting$time_scales$choices$days
#> $MC$formatting$time_scales$choices$days$conv
#> [1] "1/(60*60*24)"
#>
#> $MC$formatting$time_scales$choices$days$verb
#> [1] "Days"
#>
#> $MC$formatting$time_scales$choices$days$match
#> [1] "d" "day" "days"
#>
#>
#> $MC$formatting$time_scales$choices$hours
#> $MC$formatting$time_scales$choices$hours$conv
#> [1] "1/(60*60)"
#>
#> $MC$formatting$time_scales$choices$hours$verb
#> [1] "Hours"
#>
#> $MC$formatting$time_scales$choices$hours$match
#> [1] "hr" "hours" "hrs"
#>
#>
#>
#>
#>
#> $MC$labels
#> $MC$labels$current_element
#> NULL
#>
#> $MC$labels$element_name
#> NULL
#>
#> $MC$labels$upload_model_file
#> NULL
#>
#> $MC$labels$base_from
#> NULL
#>
#> $MC$labels$catalog_selection
#> NULL
#>
#> $MC$labels$export_nonmem
#> [1] "NONMEM"
#>
#> $MC$labels$export_monolix
#> [1] "Monolix"
#>
#> $MC$labels$export_pause
#> [1] "Exporting model."
#>
#> $MC$labels$model_type_selection
#> NULL
#>
#> $MC$labels$time_scale
#> NULL
#>
#> $MC$labels$catalog_empty
#> [1] "No models were found, the catalog is empty"
#>
#> $MC$labels$save_btn
#> [1] "Save"
#>
#> $MC$labels$clip_btn
#> [1] "Code"
#>
#> $MC$labels$copy_btn
#> [1] "Copy"
#>
#> $MC$labels$del_btn
#> [1] "Delete"
#>
#> $MC$labels$new_btn
#> [1] "New"
#>
#> $MC$labels$append_model_btn
#> [1] "Append Model"
#>
#> $MC$labels$append_model
#> [1] "Available Sub-Models"
#>
#> $MC$labels$building_model
#> [1] "Building model, be patient."
#>
#> $MC$labels$appending_model
#> [1] "Appending sub-model, be patient."
#>
#> $MC$labels$element_name_diff
#> [1] "The model name has changed."
#>
#> $MC$labels$model_code_diff
#> [1] "Manual changes have been made to the model."
#>
#> $MC$labels$save_change_detected
#> [1] "You need to click on the save button for these changes to take effect."
#>
#> $MC$labels$head_base_model
#> [1] "Starting model"
#>
#> $MC$labels$head_model_code
#> [1] "Model code"
#>
#> $MC$labels$head_time_scale
#> [1] "Model time-scale"
#>
#>
#> $MC$errors
#> $MC$errors$no_model_found
#> [1] "No model was found."
#>
#> $MC$errors$base_model_build_failed
#> [1] "The base model build failed."
#>
#> $MC$errors$manual_model_update_failed
#> [1] "Manual model update failed."
#>
#> $MC$errors$user_file_upload_failed
#> [1] "User-defined model failed."
#>
#> $MC$errors$nlmixr2lib_not_found
#> [1] "The nlmixr2lib package was not found. This library will not be available."
#>
#> $MC$errors$selected_id_bad_list
#> [1] "Unable to find a list for the selected component."
#>
#> $MC$errors$selected_id_bad_row
#> [1] "Selected component should have 1 row."
#>
#> $MC$errors$fetch_catalog_failed
#> [1] "Unable to fetch model catalog."
#>
#> $MC$errors$fetch_appends_failed
#> [1] "Unable to fetch appendable models"
#>
#> $MC$errors$append_failed
#> [1] "Unable to append sub-model"
#>
#>
#> $MC$tooltips
#> $MC$tooltips$include
#> [1] TRUE
#>
#> $MC$tooltips$elements
#> [1] "Show model components"
#>
#> $MC$tooltips$show_code
#> [1] "Show model code"
#>
#> $MC$tooltips$url_rxode
#> [1] "https://nlmixr2.github.io/rxode2/articles/rxode2-syntax.html"
#>
#> $MC$tooltips$url_model_types
#> [1] "https://ruminate.ubiquity.tools/articles/model_builder.html#model-catalog"
#>
#> $MC$tooltips$components
#> $MC$tooltips$components$input_tip
#> [1] "My tool tip"
#>
#>
#>
#>
#> $MB
#> $MB$button_counters
#> $MB$button_counters$button_clk_save
#> [1] 0
#>
#> $MB$button_counters$button_clk_clip
#> [1] 0
#>
#> $MB$button_counters$button_clk_del
#> [1] 0
#>
#> $MB$button_counters$button_clk_copy
#> [1] 0
#>
#> $MB$button_counters$button_clk_new
#> [1] 0
#>
#> $MB$button_counters$button_clk_append_model
#> [1] 0
#>
#>
#> $MB$ui_hold
#> $MB$ui_hold$button_clk_save
#> [1] FALSE
#>
#> $MB$ui_hold$button_clk_clip
#> [1] FALSE
#>
#> $MB$ui_hold$button_clk_del
#> [1] FALSE
#>
#> $MB$ui_hold$button_clk_copy
#> [1] FALSE
#>
#> $MB$ui_hold$button_clk_new
#> [1] FALSE
#>
#> $MB$ui_hold$button_clk_append_model
#> [1] FALSE
#>
#> $MB$ui_hold$catalog_selection
#> [1] FALSE
#>
#> $MB$ui_hold$base_from
#> [1] FALSE
#>
#> $MB$ui_hold$element_name
#> [1] FALSE
#>
#> $MB$ui_hold$time_scale
#> [1] FALSE
#>
#> $MB$ui_hold$model_type_selection
#> [1] FALSE
#>
#> $MB$ui_hold$ui_select_element
#> [1] FALSE
#>
#> $MB$ui_hold$ui_mb_model
#> [1] FALSE
#>
#> $MB$ui_hold$uploaded_model
#> [1] FALSE
#>
#> $MB$ui_hold$append_model
#> [1] FALSE
#>
#> $MB$ui_hold$element_selection
#> [1] FALSE
#>
#>
#> $MB$ui_ids
#> [1] "button_clk_save" "button_clk_clip"
#> [3] "button_clk_del" "button_clk_copy"
#> [5] "button_clk_new" "button_clk_append_model"
#> [7] "catalog_selection" "base_from"
#> [9] "element_name" "time_scale"
#> [11] "model_type_selection" "ui_select_element"
#> [13] "ui_mb_model" "model_type_selection"
#> [15] "uploaded_model" "append_model"
#> [17] "element_selection"
#>
#> $MB$isgood
#> [1] TRUE
#>
#> $MB$ui_ele
#> [1] "catalog_selection" "base_from" "element_name"
#> [4] "time_scale"
#>
#> $MB$element_cntr
#> [1] 1
#>
#> $MB$model_type_selection
#> [1] "rxode2"
#>
#> $MB$suggested
#> $MB$suggested$found
#> [1] TRUE
#>
#> $MB$suggested$pkgs
#> $MB$suggested$pkgs$rxode2
#> $MB$suggested$pkgs$rxode2$found
#> [1] TRUE
#>
#> $MB$suggested$pkgs$rxode2$msg
#> [1] ""
#>
#>
#> $MB$suggested$pkgs$nonmem2rx
#> $MB$suggested$pkgs$nonmem2rx$found
#> [1] TRUE
#>
#> $MB$suggested$pkgs$nonmem2rx$msg
#> [1] ""
#>
#>
#> $MB$suggested$pkgs$nlmixr2lib
#> $MB$suggested$pkgs$nlmixr2lib$found
#> [1] TRUE
#>
#> $MB$suggested$pkgs$nlmixr2lib$msg
#> [1] ""
#>
#>
#>
#>
#> $MB$model_catalog
#> $MB$model_catalog$sources
#> $MB$model_catalog$sources[[1]]
#> $MB$model_catalog$sources[[1]]$source
#> $MB$model_catalog$sources[[1]]$source$group
#> [1] "User-defined Models"
#>
#> $MB$model_catalog$sources[[1]]$source$name
#> [1] "rxode2 User model"
#>
#> $MB$model_catalog$sources[[1]]$source$description
#> [1] "User-defined rxode2 model"
#>
#> $MB$model_catalog$sources[[1]]$source$type
#> [1] "rxode2"
#>
#> $MB$model_catalog$sources[[1]]$source$obj
#> [1] "my_fcn"
#>
#> $MB$model_catalog$sources[[1]]$source$file
#> [1] "file.path(getwd(),\"user_model.R\")"
#>
#>
#>
#> $MB$model_catalog$sources[[2]]
#> $MB$model_catalog$sources[[2]]$source
#> $MB$model_catalog$sources[[2]]$source$group
#> [1] "User-defined Models"
#>
#> $MB$model_catalog$sources[[2]]$source$name
#> [1] "NONMEM User model"
#>
#> $MB$model_catalog$sources[[2]]$source$description
#> [1] "User-defined NONMEM model"
#>
#> $MB$model_catalog$sources[[2]]$source$type
#> [1] "NONMEM"
#>
#> $MB$model_catalog$sources[[2]]$source$file
#> [1] "file.path(getwd(),\"user_model.ctl\")"
#>
#>
#>
#> $MB$model_catalog$sources[[3]]
#> $MB$model_catalog$sources[[3]]$source
#> $MB$model_catalog$sources[[3]]$source$group
#> [1] "Model Library"
#>
#> $MB$model_catalog$sources[[3]]$source$type
#> [1] "nlmixr2lib"
#>
#> $MB$model_catalog$sources[[3]]$source$name
#> [1] "nlmixr2 Model Library"
#>
#>
#>
#>
#> $MB$model_catalog$summary
#> ana_sol depends mod_id Name
#> 1 yes <NA> mod_1 PK_1cmt
#> 2 no <NA> mod_2 PK_1cmt_des
#> 3 yes <NA> mod_3 PK_2cmt
#> 4 no <NA> mod_4 PK_2cmt_des
#> 5 no <NA> mod_5 PK_2cmt_no_depot
#> 6 no <NA> mod_6 PK_2cmt_tdcl_des
#> 7 yes <NA> mod_7 PK_3cmt
#> 8 no <NA> mod_8 PK_3cmt_des
#> 9 no <NA> mod_9 phenylalanine_charbonneau_2021
#> 10 no <NA> mod_10 indirect_0cpt_transitEx
#> 11 no <NA> mod_11 indirect_1cpt_inhi_kin
#> 12 no <NA> mod_12 indirect_1cpt_inhi_kin_CLV
#> 13 no <NA> mod_13 indirect_1cpt_inhi_kin_r0rmaxcrmax
#> 14 no <NA> mod_14 indirect_1cpt_inhi_kout
#> 15 no <NA> mod_15 indirect_1cpt_inhi_kout_CLV
#> 16 no <NA> mod_16 indirect_1cpt_inhi_kout_r0rmaxcrmax
#> 17 no <NA> mod_17 indirect_1cpt_stim_kin
#> 18 no <NA> mod_18 indirect_1cpt_stim_kin_CLV
#> 19 no <NA> mod_19 indirect_1cpt_stim_kin_r0rmaxcrmax
#> 20 no <NA> mod_20 indirect_1cpt_stim_kout
#> 21 no <NA> mod_21 indirect_1cpt_stim_kout_CLV
#> 22 no <NA> mod_22 indirect_1cpt_stim_kout_r0rmaxcrmax
#> 23 no <NA> mod_23 indirect_circ_1cpt_inhi_kin_kin_t
#> 24 no <NA> mod_24 indirect_circ_1cpt_inhi_kin_kout_t
#> 25 no <NA> mod_25 indirect_circ_1cpt_inhi_kout_kin_t
#> 26 no <NA> mod_26 indirect_circ_1cpt_inhi_kout_kout_t
#> 27 no <NA> mod_27 indirect_circ_1cpt_stim_kin_kin_t
#> 28 no <NA> mod_28 indirect_circ_1cpt_stim_kin_kout_t
#> 29 no <NA> mod_29 indirect_circ_1cpt_stim_kout_kin_t
#> 30 no <NA> mod_30 indirect_circ_1cpt_stim_kout_kout_t
#> 31 no <NA> mod_31 indirect_prec_1cpt_inhi_CLV
#> 32 no <NA> mod_32 indirect_prec_1cpt_inhi_r0rmaxcrmax
#> 33 no <NA> mod_33 indirect_prec_1cpt_stim_CLV
#> 34 no <NA> mod_34 indirect_prec_1cpt_stim_r0rmaxcrmax
#> 35 yes <NA> mod_35 PK_2cmt_mAb_Davda_2014
#> 36 no <NA> mod_36 PK_double_sim_01
#> 37 no <NA> mod_37 PK_double_sim_10
#> 38 no <NA> mod_38 PK_double_sim_11
#> 39 yes <NA> mod_39 CarlssonPetri_2021_liraglutide
#> 40 no <NA> mod_40 Cirincione_2017_exenatide
#> 41 no <NA> mod_41 Kovalenko_2020_dupilumab
#> 42 yes <NA> mod_42 Soehoel_2022_tralokinumab
#> 43 yes <NA> mod_43 Zhu_2017_lebrikizumab
#> 44 no Cc mod_44 oncology_sdm_lobo_2002
#> 45 no Cc mod_45 oncology_xenograft_simeoni_2004
#> 46 no <NA> mod_46 tgi_no_sat_Koch
#> 47 no <NA> mod_47 tgi_no_sat_expo
#> 48 no <NA> mod_48 tgi_no_sat_linear
#> 49 no <NA> mod_49 tgi_no_sat_powerLaw
#> 50 no <NA> mod_50 tgi_sat_VonBertalanffy
#> 51 no <NA> mod_51 tgi_sat_genVonBertalanffy
#> 52 no <NA> mod_52 tgi_sat_logistic
#> Object Type
#> 1 PK_1cmt rxode2
#> 2 PK_1cmt_des rxode2
#> 3 PK_2cmt rxode2
#> 4 PK_2cmt_des rxode2
#> 5 PK_2cmt_no_depot rxode2
#> 6 PK_2cmt_tdcl_des rxode2
#> 7 PK_3cmt rxode2
#> 8 PK_3cmt_des rxode2
#> 9 phenylalanine_charbonneau_2021 rxode2
#> 10 indirect_0cpt_transitEx rxode2
#> 11 indirect_1cpt_inhi_kin rxode2
#> 12 indirect_1cpt_inhi_kin_CLV rxode2
#> 13 indirect_1cpt_inhi_kin_r0rmaxcrmax rxode2
#> 14 indirect_1cpt_inhi_kout rxode2
#> 15 indirect_1cpt_inhi_kout_CLV rxode2
#> 16 indirect_1cpt_inhi_kout_r0rmaxcrmax rxode2
#> 17 indirect_1cpt_stim_kin rxode2
#> 18 indirect_1cpt_stim_kin_CLV rxode2
#> 19 indirect_1cpt_stim_kin_r0rmaxcrmax rxode2
#> 20 indirect_1cpt_stim_kout rxode2
#> 21 indirect_1cpt_stim_kout_CLV rxode2
#> 22 indirect_1cpt_stim_kout_r0rmaxcrmax rxode2
#> 23 indirect_circ_1cpt_inhi_kin_kin_t rxode2
#> 24 indirect_circ_1cpt_inhi_kin_kout_t rxode2
#> 25 indirect_circ_1cpt_inhi_kout_kin_t rxode2
#> 26 indirect_circ_1cpt_inhi_kout_kout_t rxode2
#> 27 indirect_circ_1cpt_stim_kin_kin_t rxode2
#> 28 indirect_circ_1cpt_stim_kin_kout_t rxode2
#> 29 indirect_circ_1cpt_stim_kout_kin_t rxode2
#> 30 indirect_circ_1cpt_stim_kout_kout_t rxode2
#> 31 indirect_prec_1cpt_inhi_CLV rxode2
#> 32 indirect_prec_1cpt_inhi_r0rmaxcrmax rxode2
#> 33 indirect_prec_1cpt_stim_CLV rxode2
#> 34 indirect_prec_1cpt_stim_r0rmaxcrmax rxode2
#> 35 PK_2cmt_mAb_Davda_2014 rxode2
#> 36 PK_double_sim_01 rxode2
#> 37 PK_double_sim_10 rxode2
#> 38 PK_double_sim_11 rxode2
#> 39 CarlssonPetri_2021_liraglutide rxode2
#> 40 Cirincione_2017_exenatide rxode2
#> 41 Kovalenko_2020_dupilumab rxode2
#> 42 Soehoel_2022_tralokinumab rxode2
#> 43 Zhu_2017_lebrikizumab rxode2
#> 44 oncology_sdm_lobo_2002 rxode2
#> 45 oncology_xenograft_simeoni_2004 rxode2
#> 46 tgi_no_sat_Koch rxode2
#> 47 tgi_no_sat_expo rxode2
#> 48 tgi_no_sat_linear rxode2
#> 49 tgi_no_sat_powerLaw rxode2
#> 50 tgi_sat_VonBertalanffy rxode2
#> 51 tgi_sat_genVonBertalanffy rxode2
#> 52 tgi_sat_logistic rxode2
#> Model
#> 1 PK_1cmt <- function() {\n description <- "One compartment PK model with linear clearance"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n\n Cc <- linCmt()\n Cc ~ prop(propSd)\n })\n}
#> 2 PK_1cmt_des <- function() {\n description <- "One compartment PK model with linear clearance using differential equations"\n dosing<-c("central", "depot")\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n\n kel <- cl / vc\n\n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n\n Cc <- central / vc\n Cc ~ prop(propSd)\n })\n}
#> 3 PK_2cmt <- function() {\n description <- "Two compartment PK model with linear clearance"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n lvp <- 5 ; label("Peripheral volume of distribution (Vp)")\n lq <- 0.1 ; label("Intercompartmental clearance (Q)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n vp <- exp(lvp)\n q <- exp(lq)\n\n Cc<- linCmt()\n Cc ~ prop(propSd)\n })\n}
#> 4 PK_2cmt_des <- function() {\n description <- "Two compartment PK model with linear clearance using differential equations"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n lvp <- 5 ; label("Peripheral volume of distribution (Vp)")\n lq <- 0.1 ; label("Intercompartmental clearance (Q)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n vp <- exp(lvp)\n q <- exp(lq)\n\n kel <- cl/vc\n k12 <- q/vc\n k21 <- q/vp\n\n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot - kel*central - k12*central + k21*peripheral1\n d/dt(peripheral1) <- k12*central - k21*peripheral1\n Cc <- central / vc\n\n Cc ~ prop(propSd)\n })\n}
#> 5 PK_2cmt_no_depot <- function() {\n description <- "Two compartment PK model with linear clearance using differential equations"\n ini({\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n lvp <- 5 ; label("Peripheral volume of distribution (Vp)")\n lq <- 0.1 ; label("Intercompartmental clearance (Q)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n cl <- exp(lcl)\n vc <- exp(lvc)\n vp <- exp(lvp)\n q <- exp(lq)\n \n kel <- cl/vc\n k12 <- q/vc\n k21 <- q/vp\n \n \n d/dt(central) <- - kel*central - k12*central + k21*peripheral1\n d/dt(peripheral1) <- k12*central - k21*peripheral1\n Cc <- central / vc\n \n Cc ~ prop(propSd)\n })\n}
#> 6 PK_2cmt_tdcl_des <- function() {\n description <- "Two compartment PK model with time-dependent clearance using differential equations (structured like nivolumab PK model)"\n reference <- "C Liu, J Yu, H Li, J Liu, Y Xu, P Song, Q Liu, H Zhao, J Xu, V E Maher, B P Booth, G Kim, A Rahman, Y Wang; Association of time-varying clearance of nivolumab with disease dynamics and its implications on exposure response analysis. Clin Pharmacol Ther May 2017; 101(5): 657-666. https://doi.org/10.1002/cpt.656"\n ini({\n lcl <- log(0.2) ; label("Time-stationary clearance (CLTS)")\n lcltmax <- log(0.22) ; label("Typical value of the maximal change of clearance relative to baseline (Tmax)")\n lclgamma <- log(1) ; label("Hill coefficient for time-dependent clearance")\n lclt50 <- log(30) ; label("Time for 50% of maximal CL change")\n lvc <- log(20) ; label("Central volume of distribution (V)")\n lvp <- log(150) ; label("Peripheral volume of distribution (Vp)")\n lq <- log(0.75) ; label("Intercompartmental clearance (Q)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n clts <- exp(lcl)\n cltmax <- exp(lcltmax)\n clgamma <- exp(lclgamma)\n clt50 <- exp(lclt50)\n vc <- exp(lvc)\n vp <- exp(lvp)\n q <- exp(lq)\n\n cl <- clts*exp(cltmax*time^clgamma/(clt50^clgamma+time^clgamma))\n\n kel <- cl/vc\n k12 <- q/vc\n k21 <- q/vp\n\n d/dt(central) <- - kel*central - k12*central + k21*peripheral1\n d/dt(peripheral1) <- k12*central - k21*peripheral1\n Cc <- central / vc\n\n Cc ~ prop(propSd)\n })\n}
#> 7 PK_3cmt <- function() {\n description <- "Three compartment PK model with linear clearance"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n lvp <- 5 ; label("Peripheral volume of distribution (Vp)")\n lvp2 <- 8 ; label("Second peripheral volume of distribution (Vp2)")\n lq <- 0.1 ; label("Intercompartmental clearance (Q)")\n lq2 <- 0.5 ; label("Second intercompartmental clearance (Q2)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n vp <- exp(lvp)\n vp2 <- exp(lvp2)\n q <- exp(lq)\n q2 <- exp(lq2)\n\n Cc <- linCmt()\n Cc ~ prop(propSd)\n })\n}
#> 8 PK_3cmt_des <- function() {\n description <- "Three compartment PK model with linear clearance using differential equations"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n lvp <- 5 ; label("Peripheral volume of distribution (Vp)")\n lvp2 <- 8 ; label("Second peripheral volume of distribution (Vp2)")\n lq <- 0.1 ; label("Intercompartmental clearance (Q)")\n lq2 <- 0.5 ; label("Second intercompartmental clearance (Q2)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n vp <- exp(lvp)\n vp2 <- exp(lvp2)\n q <- exp(lq)\n q2 <- exp(lq2)\n\n kel <- cl/vc\n k12 <- q/vc\n k21 <- q/vp\n k13 <- q2/vc\n k31 <- q2/vp2\n\n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot - kel*central - k12*central + k21*peripheral1 - k13*central + k31*peripheral2\n d/dt(peripheral1) <- k12*central - k21*peripheral1\n d/dt(peripheral2) <- k13*central - k31*peripheral2\n Cc <- central / vc\n\n Cc ~ prop(propSd)\n })\n}
#> 9 phenylalanine_charbonneau_2021 <- function() {\n description <- "Phenylalanine model for absorption and metabolism in healthy subjects and patients with PKU"\n reference <- "Charbonneau, M.R., Denney, W.S., Horvath, N.G. et al. Development of a mechanistic model to predict synthetic biotic activity in healthy volunteers and patients with phenylketonuria. Commun Biol 4, 898 (2021). https://doi.org/10.1038/s42003-021-02183-1"\n covariates <-\n list(\n WT = "Body weight in kg",\n time = "Time in hours",\n f_pah = "Fraction of healthy PAH activity (healthy = 1; PKU patient = 0 to 0.03)",\n bl_phe = "Typical values are about 0.075 mmol/L in healthy subjects and 1.18 mmol/L in patients"\n )\n # parameters come from Table 4 in paper\n ini({\n bl_phe <- 1.18; label("Baseline Phenylalanine (Phe) concentration (mmol/L)")\n bl_gut <- 0; label("Baseline Phe in the gut (mg)")\n\n ka_gut <- 0.25; label("Absorption rate from gut to plasma")\n v_npd <- 0.015; label("Rate of net protein breakdown ((mmol/L)/hr)")\n\n vmax_pah <- 0.9; label("Maximum rate of Phe breakdown by PAH in a healthy subject ((mmol/L)/hr)")\n f_pah <- 0; label("Fraction of healthy PAH activity (PKU patient = 0 to 0.02)")\n km_pah <- 0.51; label("Michaelis-Menten constant for Phe with PAH (mmol/L)")\n kact_pah <- 0.54; label("Phe activation constant for PAH")\n\n vmax_trans <- 0.063; label("Maximum rate of Phe breakdown by transaminase ((mmol/L)/hr)")\n km_trans <- 1.37; label("Michaelis-Menten constant for Phe with transaminase (mmol/L)")\n\n cl_renal <- 5.696e-4; label("Renal clearance of Phe per body weight ((L/kg)/hr)")\n\n vd <- 0.5; label("Body-weight normalized volume distribution of Phe (L/kg)")\n })\n model({\n # Molecular weight of Phe (g/mol)\n mw_phe <- 165.19\n # Unit conversion adjustment from Gut to Plasma concentrations (mmol/L)/mg\n f_gut_plasma <- 1/(mw_phe * vd_phe * WT)\n\n v_pah <- vmax_pah*f_pah / (1 + km_pah/phe + km_pah*kact_pah/(phe^2)) # units: (mmol/L)/hr\n v_trans <- vmax_trans / (1 + km_trans/phe) # units: (mmol/L)/hr\n v_renal <- phe * cl_renal * vd # units: (mmol/L)/hr\n\n d/dt(gut) <- -ka_gut*gut\n d/dt(phe) <- ka*gut*f_gut_plasma + v_npd - v_pah - v_trans - v_renal\n gut(0) <- bl_gut\n phe(0) <- bl_phe\n phe_umol <- phe * 1000 # units: umol/L (more commonly used in clinical laboratories)\n\n # The following is an augmentation of the model reported in the paper. It\n # indicates the approximate daily Phe intake (in mg) to achieve\n # steady-state.\n daily_phe_intake <- 24 * vd * (v_pah + v_trans + v_renal - v_npd) / f_gut_plasma\n })\n}
#> 10 indirect_0cpt_transitEx <- function() {\n description <- "Two compartment PK model with Michealis-Menten clearance using differential equations"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lktr1 <- c(0, 0.05)\n lktr2 <- c(0, 0.05)\n lktr3 <- c(0, 0.05)\n lktr4 <- c(0, 0.05)\n lktr5 <- c(0, 0.05)\n lktr6 <- c(0, 0.05)\n lktr7 <- c(0, 0.05)\n lktr8 <- c(0, 0.05)\n lktr9 <- c(0, 0.05)\n lktr10 <- c(0, 0.05)\n lvm <- 0.04\n label("maximum target-mediated rate of elimination (mg/L/d)")\n lkm <- 0.01\n label("Michaelis-Menten constant (mg/L)")\n lvc <- 3\n label("central volume of distribution (Vc)")\n lvp <- 5\n label("Peripheral volume of distribution (Vp)")\n lq <- 0.1\n label("Intercompartmental clearance (Q)")\n propSd <- c(0, 0.5)\n label("Proportional residual error (fraction)")\n\n })\n model({\n ka <- exp(lka)\n ktr1 <- exp(lktr1)\n ktr2 <- exp(lktr2)\n ktr3 <- exp(lktr3)\n ktr4 <- exp(lktr4)\n ktr5 <- exp(lktr5)\n ktr6 <- exp(lktr6)\n ktr7 <- exp(lktr7)\n ktr8 <- exp(lktr8)\n ktr9 <- exp(lktr9)\n ktr10 <- exp(lktr10)\n km <- exp(lkm)\n vm <- exp(lvm)\n vc <- exp(lvc)\n vp <- exp(lvp)\n q <- exp(lq)\n k12 <- q/vc\n k21 <- q/vp\n d/dt(depot) <- -ka*depot\n d/dt(transit1) <- ka * depot - ktr1 * transit1\n d/dt(transit2) <- ktr1 * transit1 - ktr2 * transit2\n d/dt(transit3) <- ktr2 * transit2 - ktr3 * transit3\n d/dt(transit4) <- ktr3 * transit3 - ktr4 * transit4\n d/dt(transit5) <- ktr4 * transit4 - ktr5 * transit5\n d/dt(transit6) <- ktr5 * transit5 - ktr6 * transit6\n d/dt(transit7) <- ktr6 * transit6 - ktr7 * transit7\n d/dt(transit8) <- ktr7 * transit7 - ktr8 * transit8\n d/dt(transit9) <- ktr8 * transit8 - ktr9 * transit9\n d/dt(transit10) <- ktr9 * transit9 - ktr10 * transit10\n d/dt(central) <- ktr10 * transit10 - (vm/(km + central/vc)) * \n central - k12 * central + k21 * peripheral1\n d/dt(peripheral1) <- k12 * central - k21 * peripheral1\n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 11 indirect_1cpt_inhi_kin <- function() {\n description <- "One compartment indirect response model with inhibition of kin."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- log(90) ; label("Central volume of distribution (Vc)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n limax <- 0.56; label("Maximum inhibitory factor attributed to drug (Imax)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n kel <- exp(lkel)\n IC50 <- exp(lIC50)\n imax <- exp(limax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -kel*central\n Cc <- central/vc\n \n d/dt(effect) <- kin*(1-imax*Cc/(Cc + IC50)) - kout*effect\n Cc ~ prop(propSd)\n })\n}\n
#> 12 indirect_1cpt_inhi_kin_CLV <- function() {\n description <- "One compartment indirect response model with inhibition of kin."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- log(90) ; label("Central volume of distribution (Vc)")\n lcl <- 1 ; label("Clearance (Cl)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n limax <- 0.56; label("Maximum inhibitory factor attributed to drug (Imax)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n IC50 <- exp(lIC50)\n imax <- exp(limax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n Cc <- central/vc\n \n d/dt(effect) <- kin*(1-imax*Cc/(Cc + IC50)) - kout*effect\n \n Cc ~ prop(propSd)\n })\n}\n
#> 13 indirect_1cpt_inhi_kin_r0rmaxcrmax <- function() {\n description <- "One compartment indirect response model with inhibition of kin."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.85 ; label("Clearance (Cl)")\n lr0 <- 0.2 ; label("Baseline response prior to drug administration (R0)")\n lrmax <- 0.9 ; label("Maximal response (CRmax)")\n ls1 <- 1.0 ; label("Initial slope of the response versus time curve (S1)")\n limax <- 0.56 ; label("Maximum inhibitory factor attributed to drug (Imax)")\n lcrmax <- 0.67 ; label("Plasma concentration of drug at the time of maximal response (CRmax)")\n lfdepot <- 0.4 ; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n r0 <- exp(lr0)\n rmax <- exp(lrmax)\n s1 <- exp(ls1)\n imax <- exp(limax)\n crmax <- exp(lcrmax)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n imax <- (r0-rmax)/r0\n kin <- -s1/imax\n kout <- kin/r0\n IC50 <- crmax*(rmax-(1-imax)*r0)/(r0-rmax)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n Cc <- central/vc\n \n d/dt(effect) <- kin*(1-imax*Cc/(Cc + IC50)) - kout*effect\n \n Cc ~ prop(propSd)\n })\n}
#> 14 indirect_1cpt_inhi_kout <- function() {\n description <- "One compartment indirect response model with inhibition of kout."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- log(90) ; label("Central volume of distribution (Vc)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n kel <- exp(lkel)\n IC50 <- exp(lIC50)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(cl/vc)*central\n \n Cc <- central/vc\n \n d/dt(effect) <- kin - kout*(1-Cc/(Cc + IC50))*effect\n \n \n Cc ~ prop(propSd)\n })\n}
#> 15 indirect_1cpt_inhi_kout_CLV <- function() {\n description <- "One compartment indirect response model with inhibition of kout."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 1 ; label("Clearance (Cl)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n IC50 <- exp(lIC50)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n Cc <- central/vc\n \n d/dt(effect) <- kin - kout*(1-Cc/(Cc + IC50))*effect\n \n Cc ~ prop(propSd)\n })\n}
#> 16 indirect_1cpt_inhi_kout_r0rmaxcrmax <- function() {\n description <- "One compartment indirect response model with inhibition of kout."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.85 ; label("Clearance (Cl)")\n lr0 <- 0.2 ; label("Baseline response prior to drug administration (R0)")\n lrmax <- 0.9 ; label("Maximal response (CRmax)")\n ls1 <- 1.0 ; label("Initial slope of the response versus time curve (S1)")\n limax <- 0.56 ; label("Maximum inhibitory factor attributed to drug (Imax)")\n lcrmax <- 0.67 ; label("Plasma concentration of drug at the time of maximal response (CRmax)")\n lfdepot <- 0.4 ; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n r0 <- exp(lr0)\n rmax <- exp(lrmax)\n s1 <- exp(ls1)\n imax <- exp(limax)\n crmax <- exp(lcrmax)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n imax <- (rmax-r0)/rmax\n kin <- s1/imax\n kout <- kin/r0\n IC50 <- crmax*(r0-(1-imax)*rmax)/(rmax-r0)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n d/dt(effect) <- kin - kout*(1-imax*Cc/(Cc + IC50))*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 17 indirect_1cpt_stim_kin <- function() {\n description <- "One compartment indirect response model with stimulation of kin.Parameterized using rate cosntants"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- log(90) ; label("Central volume of distribution (Vc)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n kel <- exp(lkel)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -kel*central\n \n Cc <- central/vc\n \n d/dt(effect) <- kin*(1+Emax*Cc/(Cc + IC50)) - kout*effect\n \n Cc ~ prop(propSd)\n })\n}
#> 18 indirect_1cpt_stim_kin_CLV <- function() {\n description <- "One compartment indirect response model with stimulation of kin."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 1 ; label("Clearance (Cl)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -kel*central\n \n Cc <- central/vc\n \n d/dt(effect) <- kin*(1+Emax*Cc/(Cc + IC50)) - kout*effect\n \n \n Cc ~ prop(propSd)\n })\n}
#> 19 indirect_1cpt_stim_kin_r0rmaxcrmax <- function() {\n description <- "One compartment indirect response model with stimulation of kin."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.85 ; label("Clearance (Cl)")\n lr0 <- 0.2 ; label("Baseline response prior to drug administration (R0)")\n lrmax <- 0.9 ; label("Maximal response (CRmax)")\n ls1 <- 1.0 ; label("Initial slope of the response versus time curve (S1)")\n lemax <- 0.56 ; label("Maximum inhibitory factor attributed to drug (Imax)")\n lcrmax <- 0.67 ; label("Plasma concentration of drug at the time of maximal response (CRmax)")\n lfdepot <- 0.4 ; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n r0 <- exp(lr0)\n rmax <- exp(lrmax)\n s1 <- exp(ls1)\n emax <- exp(lemax)\n crmax <- exp(lcrmax)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n emax <- (rmax-r0)/rmax\n kin <- s1/emax\n kout <- kin/r0\n IC50 <- crmax*(r0*(1+emax)-rmax)/(rmax-r0)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n \n Cc <- central/vc\n \n d/dt(effect) <- kin*(1+Emax*Cc/(Cc + IC50)) - kout*effect\n \n Cc ~ prop(propSd)\n })\n}
#> 20 indirect_1cpt_stim_kout <- function() {\n description <- "One compartment indirect response model with stimulation of kout.Parameterized using rate cosntants"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n \n Cc <- central/vc\n \n d/dt(effect) <- kin - kout*(1+Emax*Cc/(Cc + EC50))*effect\n \n \n Cc ~ prop(propSd)\n })\n}
#> 21 indirect_1cpt_stim_kout_CLV <- function() {\n description <- "One compartment indirect response model with stimulation of kout."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 1 ; label("Clearance (Cl)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkin <- 0.48; label("Zero-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n Cc <- central/vc\n \n d/dt(effect) <- kin - kout*(1+Emax*Cc/(Cc + EC50))*effect\n \n \n Cc ~ prop(propSd)\n })\n}
#> 22 indirect_1cpt_stim_kout_r0rmaxcrmax <- function() {\n description <- "One compartment indirect response model with stimulation of kout."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.85 ; label("Clearance (Cl)")\n lr0 <- 0.2 ; label("Baseline response prior to drug administration (R0)")\n lrmax <- 0.9 ; label("Maximal response (CRmax)")\n ls1 <- 1.0 ; label("Initial slope of the response versus time curve (S1)")\n lemax <- 0.56 ; label("Maximum inhibitory factor attributed to drug (Imax)")\n lcrmax <- 0.67 ; label("Plasma concentration of drug at the time of maximal response (CRmax)")\n lfdepot <- 0.4 ; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n r0 <- exp(lr0)\n rmax <- exp(lrmax)\n s1 <- exp(ls1)\n emax <- exp(lemax)\n crmax <- exp(lcrmax)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n emax <- (r0-rmax)/rmax\n kin <- -s1/emax\n kout <- kin/r0\n IC50 <- crmax*(rmax*(1+emax)-r0)/(r0-rmax)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(kel)*central\n Cc <- central/vc\n \n \n d/dt(effect) <- kin - kout*(1+Emax*Cc/(Cc + EC50))*effect\n \n \n Cc ~ prop(propSd)\n })\n}
#> 23 indirect_circ_1cpt_inhi_kin_kin_t <- function() {\n description <- "One compartment indirect response model with inhibition of kin and circadian kin_t."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n limax <- 0.56; label("Maximum inhibitory factor attributed to drug (Imax)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n vc <- exp(lvc)\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n imax <- exp(limax)\n IC50 <- exp(lIC50)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kin_t <- kout*rm+kout*ra*cos(0.2616*(t-tz))-0.2616*ra*sin(0.2616*(t-tz))\n \n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(cl/vc)*central\n d/dt(effect) <- kin_t*(1-imax*Cc/(Cc + IC50)) - kout*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 24 indirect_circ_1cpt_inhi_kin_kout_t <- function() {\n description <- "One compartment indirect response model with inhibition of kin and circadian kin_t."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n limax <- 0.56; label("Maximum inhibitory factor attributed to drug (Imax)")\n lkin <- 0.34; label("Zero-order rate constant for production of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n imax <- exp(limax)\n IC50 <- exp(lIC50)\n kin <- exp(lkin)\n fdepot <- exp(lfdepot)\n \n kout_t <- kin + 0.2616*ra*sin(0.2616*(t-tz))/(rm+ra*cos*(0.2616*(t-tz)))\n \n \n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(cl/vc)*central\n d/dt(effect) <- kin - kout_t*(1-imax*Cc/(Cc + IC50))*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 25 indirect_circ_1cpt_inhi_kout_kin_t <- function() {\n description <- "One compartment indirect response model with inhibition of kout and circadian kin_t."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n limax <- 0.56; label("Maximum inhibitory factor attributed to drug (Imax)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n imax <- exp(limax)\n IC50 <- exp(lIC50)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kin_t <- kout*rm+kout*ra*cos(0.2616*(t-tz))-0.2616*ra*sin(0.2616*(t-tz))\n \n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(cl/vc)*central\n d/dt(effect) <- kin_t - kout*(1-imax*Cc/(Cc + IC50))*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 26 indirect_circ_1cpt_inhi_kout_kout_t <- function() {\n description <- "One compartment indirect response model with inhibition of kout and circadian kin_t."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n limax <- 0.56; label("Maximum inhibitory factor attributed to drug (Imax)")\n lkin <- 0.34; label("Zero-order rate constant for production of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n imax <- exp(limax)\n IC50 <- exp(lIC50)\n kin <- exp(lkin)\n fdepot <- exp(lfdepot)\n \n kout_t <- kin + 0.2616*ra*sin(0.2616*(t-tz))/(rm+ra*cos*(0.2616*(t-tz)))\n \n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -(cl/vc)*central\n d/dt(effect) <- kin - kout_t*(1-imax*Cc/(Cc + IC50))*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 27 indirect_circ_1cpt_stim_kin_kin_t <- function() {\n description <- "One compartment indirect response model with stimulation of kin and circadian kin_t.Parameterized using rate cosntants"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kin_t <- kout*rm+kout*ra*cos(0.2616*(t-tz))-0.2616*ra*sin(0.2616*(t-tz))\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -kel*central\n d/dt(effect) <- kin_t*(1+Emax*Cc/(Cc + IC50)) - kout*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 28 indirect_circ_1cpt_stim_kin_kout_t <- function() {\n description <- "One compartment indirect response model with stimulation of kin and circadian kout_t.Parameterized using rate constants"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkin <- 0.34; label("Zero-order rate constant for production of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kin <- exp(lkin)\n fdepot <- exp(lfdepot)\n \n kout_t <- kin + 0.2616*ra*sin(0.2616*(t-tz))/(rm+ra*cos*(0.2616*(t-tz)))\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -kel*central\n d/dt(effect) <- kin*(1+Emax*Cc/(Cc + IC50)) - kout_t*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 29 indirect_circ_1cpt_stim_kout_kin_t <- function() {\n description <- "One compartment indirect response model with stimulation of kout and circadian kin_t.Parameterized using rate cosntants"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kout <- exp(lkout)\n fdepot <- exp(lfdepot)\n \n kin_t <- kout*rm+kout*ra*cos(0.2616*(t-tz))-0.2616*ra*sin(0.2616*(t-tz))\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -kel*central\n d/dt(effect) <- kin_t - kout*(1+Emax*Cc/(Cc + IC50))*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 30 indirect_circ_1cpt_stim_kout_kout_t <- function() {\n description <- "One compartment indirect response model with stimulation of kout and circadian kout_t.Parameterized using rate cosntants"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lkel <- 0.534; label("elimination rate (1/d)")\n lrm <- 0.62; label ("Mean Baseline for drug response (mesor)(Rm)")\n lra <- 0.62; label ("Amplitude of drug response (Ra)")\n ltz <- 0.62; label ("peak time (Acrophase) (Tz)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum stimulation at effect site (EC50)")\n lEmax <- 0.85; label("Maximum effect attributed to drug (Emax)")\n lkin <- 0.34; label("Zero-order rate constant for production of drug response")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n kel <- exp(lkel)\n rm <- exp(lrm)\n ra <- exp(lra)\n tz <- exp(ltz)\n EC50 <- exp(lEC50)\n Emax <- exp(lEmax)\n kin <- exp(lkin)\n fdepot <- exp(lfdepot)\n \n kout_t <- kin + 0.2616*ra*sin(0.2616*(t-tz))/(rm+ra*cos*(0.2616*(t-tz)))\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot -kel*central\n d/dt(effect) <- kin_t - kout*(1+Emax*Cc/(Cc + IC50))*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 31 indirect_prec_1cpt_inhi_CLV <- function() {\n description <- "One compartment precursor-dependent indirect response model with inhibition of drug response. Parameterized with clearance and volume. (effect)."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.04 ; label("Clearance (CL)")\n limax <- 0.56 ; label("Maximum inhibitory factor attributed to drug (Imax)")\n lIC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n lkin <- 0.48; label("First-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lkpin <- 0.45 ; label("Zero order rate constant for production of precursor (kpin)")\n lkpout <- 0.45 ; label("First order rate constant for loss of precursor (kpout)")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n IC50 <- exp(lIC50)\n imax<- exp(limax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n kpin <- exp(lkpin)\n kpout <- exp(lkpout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot-kel*central\n d/dt(precursor) <- kpin -(kin + kpout)*(1-imax*Cc/(Cc + IC50))*precursor\n d/dt(effect) <- kin*(1-imax*Cc/(Cc + IC50))*precursor-kout*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 32 indirect_prec_1cpt_inhi_r0rmaxcrmax <- function() {\n description <- "One compartment precursor-dependent indirect response model with inhibition of drug response (effect)."\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.04 ; label("Clearance (CL)")\n lr0 <- 0.2 ; label("Baseline response prior to drug administration (R0)")\n lrmax <- 0.9 ; label("Maximal response (CRmax)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lkpin <- 0.45 ; label("Zero order rate constant for production of precursor (kpin)")\n lkpout <- 0.45 ; label("First order rate constant for loss of precursor (kpout)")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n r0<- exp(lr0)\n rmax<- exp(lrmax)\n kout <- exp(lkout)\n kpin <- exp(lkpin)\n kpout <- exp(lkpout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n imax <- (r0-rmax)/r0\n kin <- (kout*(kin+kpout)*r0)/kpin\n IC50 <- crmax*(rmax-(1-imax)*r0)/(r0-rmax)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot-kel*central\n d/dt(precursor) <- kpin -(kin + kpout)*(1-imax*Cc/(Cc + IC50))*precursor\n d/dt(effect) <- kin*(1-imax*Cc/(Cc + IC50))*precursor-kout*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 33 indirect_prec_1cpt_stim_CLV <- function() {\n description <- "One compartment precursor-dependent indirect response model with inhibition of drug response (effect). Parameterized with clearance and volume"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.534; label("clearance (CL)")\n lemax <- 0.56 ; label("Maximum inhibitory factor attributed to drug (Imax)")\n lEC50 <- 0.67; label("Drug concentration producing 50% of maximum inhibition at effect site (IC50)")\n lkin <- 0.48; label("First-order rate constant for production of drug response(1/d)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lkpin <- 0.45 ; label("Zero order rate constant for production of precursor (kpin)")\n lkpout <- 0.45 ; label("First order rate constant for loss of precursor (kpout)")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n EC50 <- exp(lEC50)\n emax<- exp(lemax)\n kin <- exp(lkin)\n kout <- exp(lkout)\n kpin <- exp(lkpin)\n kpout <- exp(lkpout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot-kel*central\n d/dt(precursor) <- kpin -(kin + kpout)*(1+emax*Cc/(Cc + EC50))*precursor\n d/dt(effect) <- kin*(1+emax*Cc/(Cc + EC50))*precursor-kout*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 34 indirect_prec_1cpt_stim_r0rmaxcrmax <- function() {\n description <- "One compartment precursor-dependent indirect response model with inhibition of drug response (effect). Parameterized with clearance and volume"\n ini({\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lvc <- 3.45 ; label("Central volume of distribution (Vc)")\n lcl <- 0.534; label("clearance (CL)")\n lr0 <- 0.2 ; label("Baseline response prior to drug administration (R0)")\n lrmax <- 0.9 ; label("Maximal response (CRmax)")\n lkout <- 0.34; label("First-order rate constant for loss of drug response")\n lkpin <- 0.45 ; label("Zero order rate constant for production of precursor (kpin)")\n lkpout <- 0.45 ; label("First order rate constant for loss of precursor (kpout)")\n lfdepot <- 0.4; label("Bioavailability (F)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n vc <- exp(lvc)\n cl <- exp(lcl)\n r0<- exp(lr0)\n rmax<- exp(lrmax)\n kout <- exp(lkout)\n kpin <- exp(lkpin)\n kpout <- exp(lkpout)\n fdepot <- exp(lfdepot)\n \n kel <- cl/vc\n emax <- (rmax-r0)/rmax\n kin <- (kout*(kin+kpout)*r0)/kpin\n EC50 <- crmax*(r0*(1+emax)-rmax)/(rmax-r0)\n \n d/dt(depot) <- -ka*depot\n f(depot) <- fdepot\n d/dt(central) <- ka*depot-kel*central\n d/dt(precursor) <- kpin -(kin + kpout)*(1+emax*Cc/(Cc + EC50))*precursor\n d/dt(effect) <- kin*(1+emax*Cc/(Cc + EC50))*precursor-kout*effect\n \n Cc <- central/vc\n Cc ~ prop(propSd)\n })\n}
#> 35 PK_2cmt_mAb_Davda_2014 <- function() {\n description <- "Two compartment PK model with linear clearance for average monoclonal antibodies (Davda 2014)"\n reference <- "Davda JP, Dodds MG, Gibbs MA, Wisdom W, Gibbs JP. A model-based meta-analysis of monoclonal antibody pharmacokinetics to guide optimal first-in-human study design. MAbs. 2014;6(4):1094-1102. doi:10.4161/mabs.29095"\n units = list(time = "day", dosing = "mg")\n ini({\n lfdepot <- log(0.744) ; label("Subcutaneous bioavailability (fraction)")\n lka <- log(0.282) ; label("Absorption rate (Ka, 1/day)")\n lcl <- log(0.200) ; label("Clearance (CL, L/day)")\n lv <- log(3.61) ; label("Central volume of distribution (V, L)")\n lvp <- log(2.75) ; label("Peripheral volume of distribution (Vp, L)")\n lq <- log(0.747) ; label("Intercompartmental clearance (Q, L/day)")\n\n allocl <- 0.865 ; label("Allometric exponent on clearance and intercompartmental clearance (unitless)")\n allov <- 0.957 ; label("Allometric exponent on volumes of distribution (unitless)")\n\n etafdepot ~ 0\n etaka ~ 0.416\n etacl + etav + etavp ~ c(0.0987,\n 0.0786, 0.116,\n 0.0377, 0.0619, 0.0789)\n etaq ~ 0.699\n\n prop.err <- 0.144 ; label("Proportional residual error (fraction)")\n })\n model({\n # WT is body weight in kg\n fdepot <- exp(lfdepot + etafdepot)\n ka <- exp(lka + etaka)\n wtnorm <- log(WT/70)\n cl <- exp(lcl + allocl*wtnorm + etacl)\n q <- exp(lq + allocl*wtnorm + etaq)\n v <- exp(lv + allov*wtnorm + etav)\n vp <- exp(lvp + allov*wtnorm + etavp)\n\n Cc <- linCmt()\n \n f(depot) <- fdepot # Units are dosing units/L (typically mg/L = ug/mL)\n Cc ~ prop(prop.err)\n })\n}
#> 36 PK_double_sim_01 <- function() {\n description <- "PK double absorption model with simultaneous zero order and first order absorptions"\n ini({\n tk01 <- 0.4 ; label("Zero order absorption rate from first site (K01)")\n lka2 <- 0.45 ; label("First order Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n lgfdepot1 <- logit(0.8);\n lalag <- log (9); \n })\n model({\n k01 <- exp(tk01)\n ka2 <- exp(lka2)\n cl <- exp(lcl)\n vc <- exp(lvc)\n fdepot1 <- expit(lgfdepot1)\n alag <- exp(lalag)\n \n kel <- cl/vc\n \n d/dt(depot1) <- -k01\n f(depot1) <- fdepot1\n d/dt(depot2) <- -ka2*depot2\n lag(depot2) <- alag\n f(depot2) <- 1-fdepot1\n d/dt(central) <- k01+ka2*depot2-kel*central \n \n Cc <- central / vc\n \n Cc ~ prop(propSd)\n })\n}
#> 37 PK_double_sim_10 <- function() {\n description <- "PK double absorption model with simultaneous first order and zero order absorptions"\n ini({\n lka1 <- 0.45 ; label("First order Absorption rate (Ka)")\n tk02 <- 0.4 ; label("Zero order absorption rate from second site (K02)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n lgfdepot1 <- logit(0.8);\n lalag <- log (9); \n })\n model({\n ka1 <- exp(lka1)\n k02 <- exp(tk02)\n cl <- exp(lcl)\n vc <- exp(lvc)\n fdepot1 <- expit(lgfdepot1)\n alag <- exp(lalag)\n \n kel <- cl/vc\n \n d/dt(depot1) <- -ka1*depot1\n f(depot1) <- fdepot1\n d/dt(depot2) <- -k02\n lag(depot2) <- alag\n f(depot2) <- 1-fdepot1\n d/dt(central) <- ka1*depot1+ k02- kel*central \n \n Cc <- central / vc\n \n Cc ~ prop(propSd)\n })\n}
#> 38 PK_double_sim_11 <- function() {\n description <- "PK double absorption model with simultaneous first order absorptions"\n ini({\n lka1 <- 0.45 ; label("First order Absorption rate from first site (Ka)")\n lka2 <- 0.45 ; label("First order Absorption rate from second site (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3 ; label("Central volume of distribution (V)")\n propSd <- 0.5 ; label("Proportional residual error (fraction)")\n lgfdepot1 <- logit(0.7);\n lalag <- log (9); \n })\n model({\n ka1 <- exp(lka1)\n ka2 <- exp(lka2)\n cl <- exp(lcl)\n vc <- exp(lvc)\n fdepot1 <- expit(lgfdepot1)\n alag <- exp(lalag)\n \n kel <- cl/vc\n \n d/dt(depot1) <- -ka1*depot1\n f(depot1) <- fdepot1\n d/dt(depot2) <- -ka2*depot2\n lag(depot2) <- alag\n f(depot2) <- 1-fdepot1\n d/dt(central) <- ka1*depot1+ka2*depot2 - kel*central \n \n Cc <- central / vc\n \n Cc ~ prop(propSd)\n })\n}\n\n\n
#> 39 CarlssonPetri_2021_liraglutide <- function() {\n description <- "Liraglutide PK model in adolescents (Carlsson Petri 2021)"\n reference <- "Carlsson Petri KC, Hale PM, Hesse D, Rathor N, Mastrandrea LD. Liraglutide pharmacokinetics and exposure-response in adolescents with obesity. Pediatric Obesity. 2021;16(10):e12799. doi:10.1111/ijpo.12799"\n units <-list(time="hr", dosing="mg")\n covariateData <-\n list(\n WT = "Baseline body weight in kg",\n CHILD = "Is the subject a child? (1 for yes, 0 for no)",\n ADOLESCENT = "Is the subject an adolescent? (1 for yes, 0 for no)",\n SEXM = "1 for male, 0 for female"\n )\n ini({\n lka <- fixed(log(0.0813)) ; label("Absorption rate (1/hr)")\n lcl <- log(1.01) ; label("Apparent clearance (L/h)")\n e_wt_cl <- 0.762; label("Body weight exponent on CL/F")\n e_sex_cl <- 1.12; label("Sex contrast (male/female) on CL/F")\n e_age_child_cl <- 1.11; label("Age contrast (child/adult) on CL/F")\n e_age_adolescent_cl <- 1.06; label("Age contrast (adolescent/adult) on CL/F")\n lvc <- fixed(log(13.8)) ; label("Apparent central volume of distribution (L)")\n e_wt_vc <- 0.587; label("Body weight exponent on Vc/F")\n \n etalcl ~ log(1.312)\n etalvc ~ log(1.317)\n propSd <- 0.433 ; label("Proportional residual error (fraction)")\n })\n model({\n ka <- exp(lka)\n cl_wt <- (WT/100)^e_wt_cl # Equation 2 in the paper\n cl_sex <- SEXM^e_sex_cl # Equation 3 in the paper\n cl_age <- CHILD^e_age_child_cl * ADOLESCENT^e_age_adolescent_cl # Equation 4 in the paper\n cl <- exp(lcl + etalcl)*cl_wt*cl_sex*cl_age # Equation 1 in the paper\n vc_wt <- (WT/100)^e_wt_vc # Not in the paper, based on Equation 2 in the paper\n vc <- exp(lvc + etalvc)*vc_wt # Equation 5 in the paper\n \n Cc <- linCmt()\n Cc ~ prop(propSd)\n })\n}
#> 40 Cirincione_2017_exenatide <- function() {\n description <- "Exenatide immediate-release PK model (Cirincione 2017)"\n reference <- "Cirincione B, Mager DE. Population pharmacokinetics of exenatide. British Journal of Clinical Pharmacology. 2017;83(3):517-526. doi:10.1111/bcp.13135"\n covariateData <-\n list(\n AMT = "Dose (ug)",\n DV = "Exenatide plasma concentration (pg/mL)",\n eGFR = "Modification of Diet in Renal Disease estimate of glomerular filtration rate (mL/min/(1.73m^2))",\n WT = "Baseline body weight (kg)",\n DVID = "Was the subject in Study 1 ('study1'), Study 5 ('study5'), or another study ('otherStudy')? Typically 'otherStudy'"\n )\n # parameters are from Table 2 in the paper\n ini({\n lcl <- log(4.58) ; label("Linear clearance rate (L/hr)")\n etalcl ~ log(1.339)\n e_cl_gfr <- 0.838; label("Effect of eGFR on clearance (unitless)")\n\n lq <- log(3.72); label("Intercompartmental clearance (L/hr)") # written as Cld in the model table\n\n lkm <- log(567); label("Michaelis-Menten constant for clearance (pg/mL)")\n etalkm ~ log(1.957)\n\n lvmax <- log(1.55); label("Maximum Michaelis-Menten clearance (ug/hr)")\n\n lvp <- log(7.04); label("Peripheral compartment volume (L)")\n\n lvc <- log(7.03); label("Typical central compartment clearance (L)")\n etalvc ~ log(1.805)\n e_vc_wt <- 2.67; label("Effect of body weight on central volume (unitless)")\n\n lkamax <- log(0.0813); label("Maximum first-order absorption rate (1/hr)")\n lkmka <- log(16.9); label("Michaelis-Menten constant for absorption (ug)")\n ttau <- fixed(1.35); label("Duration of zero-order absorption")\n fdepot <- fixed(1); label("Bioavailability (fraction)")\n logitfr <- logit(0.628); label("Fraction of dose with first-order absorption")\n\n expSdOther <- 0.373 ; label("Exponential residual error for all other studies")\n expSdStudy1 <- 0.39 ; label("Exponential residual error for Study 1")\n expSdStudy5 <- 0.08 ; label("Exponential residual error for Study 5")\n })\n model({\n # declare compartment order\n cmt(depot)\n cmt(central)\n cmt(peripheral1)\n # cl equation is from table 2 in the paper\n cl <- exp(lcl + etalcl)*(eGFR/80)^e_cl_gfr\n q <- exp(lq)\n km <- exp(lkm + etalkm)\n vmax <- exp(lvmax)\n vp <- exp(lvp)\n # vc equation is from table 2 in the paper\n vc <- exp(lvc + etalvc)*(WT/84.8)^e_vc_wt\n kamax <- exp(lkamax)\n kmka <- exp(lkmka)\n fr <- expit(logitfr)\n\n kel <- cl/vc + vmax/(km*vc + central)\n k12 <- q/vc\n k21 <- q/vp\n\n # Need to turn k0 off at time > tau\n mtime(tau) <- ttau\n\n kzero <- (1-fr)*podo(depot)/tau\n if (tad(depot) > tau) kzero <- 0.0\n\n # Need to turn ka on at time > tau\n ka <- fr*kamax/(kmka + depot)\n if (tad(depot) <= tau) ka <- 0.0\n\n d/dt(depot) <- -ka*depot - kzero\n d/dt(central) <- ka*depot + kzero - kel*central - k12*central + k21*peripheral1\n d/dt(peripheral1) <- k12*central - k21*peripheral1\n f(depot) <- fdepot\n\n cp <- central/vc\n\n cp1 <- cp\n cp5 <- cp\n \n cp ~ lnorm(expSdOther) | otherStudy\n cp1 ~ lnorm(expSdStudy1) | study1\n cp5 ~ lnorm(expSdStudy5) | study5\n })\n}
#> 41 Kovalenko_2020_dupilumab <- function() {\n description <- "Dupilumab PK model (Kovalenko 2020)"\n reference <- "Kovalenko P, Davis JD, Li M, et al. Base and Covariate Population Pharmacokinetic Analyses of Dupilumab Using Phase 3 Data. Clinical Pharmacology in Drug Development. 2020;9(6):756-767. doi:10.1002/cpdd.780"\n units<-list(time="day", dosing="mg")\n # Model 1 from table 1 and supplementary Table 2 in the publication and its\n # supplement.\n covariateData <-\n list(\n WT = "Body weight in kg"\n )\n ini({\n lvc <- log(2.48); label("central volume (L)")\n lke <- log(0.0534); label("elimination rate (1/d)")\n lkcp <- log(0.213); label("central-to-peripheral rate (1/d)")\n Mpc <- 0.686; label("ratio of kcp and kpc (kpc is peripheral to central rate with units of 1/d)")\n lka <- log(0.256); label("absorption rate (1/d)")\n lMTT <- log(0.105); label("mean transit time (d)")\n lVm <- log(1.07); label("maximum target-mediated rate of elimination (mg/L/d)")\n Km <- fixed(0.01); label("Michaelis-Menten constant (mg/L)")\n lfdepot <- log(0.643); label("Bioavailability (fraction)")\n e_wt_vc <- 0.711; label("Exponent of weight on central volume (unitless)")\n\n etalvc ~ 0.192\n etalke ~ 0.285\n etalka ~ 0.474\n etalvm ~ 0.236\n etamtt ~ 0.525 # etamtt is assumed to be on log-scale MTT to prevent negative values; this is a difference relative to Supplementary Table 2\n\n CcpropSd <- 0.15; label("Proportional residual error (fraction)")\n CcaddSd <- fixed(0.03); label("Additive residual error (mg/L)")\n })\n model({\n # Weight normalization to 75 kg is assumed based on prior publication. It\n # is not specified in the current publication:\n # Kovalenko P, DiCioccio AT, Davis JD, et al. Exploratory Population PK\n # Analysis of Dupilumab, a Fully Human Monoclonal Antibody Against\n # IL-4Ralpha, in Atopic Dermatitis Patients and Normal Volunteers. CPT\n # Pharmacometrics Syst Pharmacol. 2016;5(11):617-624. doi:10.1002/psp4.12136\n vc <- exp(lvc + etalvc)*(WT/75)^e_wt_vc\n ke <- exp(lke + etalke)\n kcp <- exp(lkcp)\n ka <- exp(lka + etalka)\n MTT <- exp(lMTT + etamtt)\n Vm <- exp(lVm + etalvm)\n\n # Derived parameters\n kpc <- kcp/Mpc\n ktr <- (3 + 1)/MTT\n\n d/dt(depot) <- -ktr*depot\n d/dt(transit1) <- ktr*(depot - transit1)\n d/dt(transit2) <- ktr*(transit1 - transit2)\n d/dt(transit3) <- ktr*transit2 - ka*transit3\n # Linear and Michaelis-Menten clearance\n d/dt(central) <- ka*transit3 - ke*central - kcp*central + kpc*periph - central*(Vm/(Km + central/vc))\n d/dt(periph) <- kcp*central - kpc*periph\n\n f(depot) <- exp(lfdepot)\n # No unit conversion is required to change mg/L (dosing amount/central\n # volume unit) to mg/L (measurement unit)\n Cc <- central/vc\n Cc ~ add(CcaddSd) + prop(CcpropSd)\n })\n}
#> 42 Soehoel_2022_tralokinumab <- function() {\n description <- "Tralokinumab PK model (Soehoel 2022)"\n reference <- "Soehoel A, Larsen MS, Timmermann S. Population Pharmacokinetics of Tralokinumab in Adult Subjects With Moderate to Severe Atopic Dermatitis. Clinical Pharmacology in Drug Development. 2022;11(8):910-921. doi:10.1002/cpdd.1113"\n units<-list(time="day",dosing="mg") \n # From Table 2 footnotes\n covariateData <-\n list(\n nonECZTRA = "1 = any study other than ECZTRA; 0 = ECZTRA study",\n WT = "Body weight in kg",\n dilution = "Was the drug diluted as it was in study D2213C00001? 1 = yes, 0 = no (0 is typical)"\n )\n ini({\n lka <- log(0.184); label("Absorption rate (1/day)")\n lvc <- log(2.71); label("Central volume of distribution (L)")\n lcl <- log(0.149); label("Clearance (L/day)")\n lvp <- log(1.44); label("Peripheral volume of distribution (L)")\n lq <- log(0.159); label("Intercompartmental clearance (L/day)")\n lfdepot <- log(0.761); label("Subcutaneous bioavailability (fraction)")\n CcaddSd <- 0.238; label("Additive residual error (ug/mL)")\n CcpropSd <- 0.216; label("Proportional residual error (fraction)")\n\n e_wt_vcvp <- 0.793; label("Effect of body weight on central and peripheral volumes (unitless)")\n e_wt_clq <- 0.873; label("Effect of body weight on clearance and intercompartmental clearance (unitless)")\n e_nonECZTRA_cl <- 0.344; label("Effect of non-ECZTRA trials on clearance (unitless)")\n e_nonECZTRA_vc <- 0.258; label("Effect of non-ECZTRA trials on central volume (unitless)")\n e_f_dilution <- 0.354; label("Effect of dilution on bioavailability (unitless)")\n e_ka_dilution <- -0.519; label("Effect of dilution trials on absorption rate (unitless)")\n\n etavc + etacl ~ c(0.386148, 0.2683494, 0.3057157)\n })\n model({\n fdepot <- exp(lfdepot)*(1 + e_f_dilution*dilution)\n ka <- exp(lka)*(1 + e_ka_dilution*dilution)\n cl <- exp(lcl + etacl)*(WT/75)^e_wt_clq * (1 + e_nonECZTRA_cl*nonECZTRA)\n vc <- exp(lvc + etavc)*(WT/75)^e_wt_vcvp * (1 + e_nonECZTRA_vc*nonECZTRA)\n q <- exp(lq)*(WT/75)^e_wt_clq\n vp <- exp(lvp)*(WT/75)^e_wt_vcvp\n\n # No unit conversion is required to change mg/L (dosing amount/central\n # volume unit) to ug/mL (measurement unit)\n Cc <- linCmt()\n f(depot) <- fdepot\n Cc ~ add(CcaddSd) + prop(CcpropSd)\n })\n}\n\n# etavc, etacl, and the covariance were calculated from the Table 2 footnotes\n# as:\n# etavc: sqrt(log(0.313^2 + 1)) = 0.386148\n# etacl: sqrt(log(0.401^2 + 1)) = 0.3057157\n# cov(etavc, etacl): sqrt(0.61*0.386148*0.3057157)
#> 43 Zhu_2017_lebrikizumab <- function() {\n description <- "Lebrikizumab PK model (Zhu 2017)"\n reference <- "Zhu R, Zheng Y, Dirks NL, et al. Model-based clinical pharmacology profiling and exposure-response relationships of the efficacy and biomarker of lebrikizumab in patients with moderate-to-severe asthma. Pulmonary Pharmacology & Therapeutics. 2017;46:88-98. doi:10.1016/j.pupt.2017.08.010"\n units <- list(time="day", dosing="mg")\n covariateData <-\n list(\n WT = "Baseline body weight in kg",\n AGE = "Age in years",\n SEXF = "1 for female, 0 for male",\n FORM_NS0 = "Is the formulation NS0? 1 for yes, 0 for no (typically no)",\n FORM_CHO_PHASE2 = "Is the formulation CHO from Phase 2? 1 for yes, 0 for no (typically no)",\n ADA = "Is the subject ADA positive ever? 1 for yes, 0 for no",\n RACE_BLACK = "Is the race of the subject black or African American? 1 for yes, 0 for no",\n RACE_ASIAN = "Is the race of the subject Asian? 1 for yes, 0 for no",\n RACE_OTHER = "Is the race of the subject 'other'? 1 for yes, 0 for no"\n )\n ini({\n lcl <- log(0.156); label("Clearance (L/day)")\n lvc <- log(4.10); label("Central volume of distribution (L)")\n lvp <- log(1.45); label("Peripheral volume of distribution (L)")\n lq <- log(0.284); label("Intercompartmental clearance (L/day)")\n lka <- log(0.239); label("Absorption rate (1/day)")\n lfdepot <- log(0.856); label("Subcutaneous bioavailability (fraction)")\n\n e_cl_wt <- 1.00; label("Effect of body weight on clearance (unitless)")\n e_vc_wt <- 0.814; label("Effect of body weight on central volume (unitless)")\n e_vp_wt <- 0.692; label("Effect of body weight on peripheral volume (unitless)")\n e_q_wt <- 0.479; label("Effect of body weight on intercompartmentl clearance (unitless)")\n e_cl_age <- 0.0241; label("Effect of age on clearance (unitless)")\n e_cl_sexf <- 1.06; label("Effect of sex on clearance (unitless)")\n e_cl_race_black <- 1.07; label("Effect of race (black or African American) on clearance (unitless)")\n e_cl_race_asian <- 1.09; label("Effect of race (Asian) on clearance (unitless)")\n e_cl_race_other <- 1.11; label("Effect of race (other) on clearance (unitless)")\n e_ka_form_nso <- 0.981; label("Effect of NSO formulation on absorption rate (unitless)")\n e_ka_form_cho_phase2 <- 0.989; label("Effect of CHO formulation used during Phase 2 on absorption rate (unitless)")\n e_f_form_nso <- 1.00; label("Effect of NSO formulation on bioavailability (unitless)")\n e_f_form_cho_phase2 <- 0.973; label("Effect of CHO formulation used during Phase 2 on bioavailability (unitless)")\n e_cl_ada_positive<- 1.04; label("Effect of anti-drug antibody (ADA) positivity on clearance (unitless)")\n\n # converted from covariance matrix reported in Table 3\n etacl + etavc + etaka ~\n c(\n 0.32403703,\n 0.28844410, 0.35213634,\n 0.04505552, 0.06625708, 0.39242834\n )\n\n CcpropSd <- 0.0490; label("Proportional residual error (fraction)")\n CcaddSd <- 0.00154; label("Additive residual error (ug/mL)")\n })\n model({\n # Normalized continuous covariate values based on footnote to Table 3\n WTNORM <- WT/70\n AGENORM <- AGE/40\n\n cl <-\n exp(lcl + etacl) *\n WTNORM^e_cl_wt * AGENORM^e_cl_age * e_cl_sexf^SEXF *\n e_cl_race_black^RACE_BLACK * e_cl_race_asian^RACE_ASIAN * e_cl_race_other^RACE_OTHER *\n e_cl_ada_positive^ADA\n vc <- exp(lvc + etavc) * WTNORM^e_vc_wt\n vp <- exp(lvp) * WTNORM^e_vp_wt\n q <- exp(lq) * WTNORM^e_q_wt\n ka <- exp(lka + etaka) * e_ka_form_nso^FORM_NSO * e_ka_form_cho_phase2^FORM_CHO_PHASE2\n fdepot <- exp(lfdepot) * e_f_form_nso^FORM_NSO * e_f_form_cho_phase2^FORM_CHO_PHASE2\n Cc <- linCmt()\n f(depot) <- fdepot\n Cc ~ add(CcaddSd) + prop(CcpropSd)\n })\n}
#> 44 oncology_sdm_lobo_2002 <- function() {\n description <- "Signal transduction model for delayed concentration effects on cancer cell growth"\n reference <- "Lobo ED, Balthasar JP. Pharmacodynamic modeling of chemotherapeutic effects: Application of a transit compartment model to characterize methotrexate effects in vitro. AAPS J. 2002;4(4):212-222. doi:10.1208/ps040442"\n depends<-"Cc"\n units<-list(time="hr")\n # Values for lkng, ltau, lec50, and kmax are for methotrexate from Lobo 2002,\n # Table 2. propErr and addErr are added as reasonable values though not from\n # Lobo 2002 where no value is apparent in the paper.\n ini({\n lkng <- log(0.02) ; label("Cell net growth rate (growth minus death) (1/hr)")\n ltau <- log(34.1) ; label("Mean transit time of each transit compartment (hr)")\n lec50 <- log(0.1) ; label("Drug concentration reducing the cell growth by 50% (ug/mL)")\n kmax <- 0.29 ; label("Maximum drug-related reduction in cell growth (1/hr)")\n\n tumorVolpropSd <- c(0, 0.3) ; label("Proportional residual error (fraction)")\n tumorVoladdSd <- c(0, 50, 1000) ; label("Additive residual error (tumor volume units)")\n })\n model({\n # Cc is the drug concentration\n kng <- exp(lkng)\n tau <- exp(ltau)\n ec50 <- exp(lec50)\n\n drugEffectTumorVol <- kmax*Cc/(ec50 + Cc)\n\n tumorVol(0) <- tumorVol0\n d/dt(tumorVol) <- kng*tumorVol - transit4*tumorVol\n d/dt(transit1) <- (drugEffectTumorVol - transit1)/tau\n d/dt(transit2) <- (transit1 - transit2)/tau\n d/dt(transit3) <- (transit2 - transit3)/tau\n d/dt(transit4) <- (transit3 - transit4)/tau\n tumorVol ~ prop(tumorVolpropSd) + add(tumorVoladdSd)\n })\n}
#> 45 oncology_xenograft_simeoni_2004 <- function() {\n description <- "Oncology tumor growth model in xenograft models"\n reference <- "Monica Simeoni, Paolo Magni, Cristiano Cammia, Giuseppe De Nicolao, Valter Croci, Enrico Pesenti, Massimiliano Germani, Italo Poggesi, Maurizio Rocchetti; Predictive Pharmacokinetic-Pharmacodynamic Modeling of Tumor Growth Kinetics in Xenograft Models after Administration of Anticancer Agents. Cancer Res 1 February 2004; 64 (3): 1094–1101. https://doi.org/10.1158/0008-5472.CAN-03-2524"\n depends<- "Cc"\n units<-list(time="day")\n # Values for damageTransit (k1), drugSlope (k2), tumorExpGrowth (lambda0),\n # tumorLinGrowth (lambda1) are from paclitaxel experiment 1 reported in Table\n # 2 from the reference (limits are not from the reference). The values from\n # Table 2 will be estimated on the log scale to ensure positive values.\n # Residual errors are not in the original reference.\n ini({\n ldamageTransit <- log(c(0.1, 0.968, 10)) ; label("Transit rate through damage (1/day)")\n ldrugSlope <- log(c(0.00001, 0.000629, 0.1)) ; label("Linear drug effect on cycling cells (1/(day*ng/mL))")\n ltumorExpGrowth <- log(c(0.001, 0.273, 2)) ; label("Tumor exponential growth rate (1/day)")\n ltumorLinGrowth <- log(c(0.01, 0.814, 5)) ; label("Tumor linear growth rate (tumor volume/day)")\n tumorVolpropSd <- 0.2 ; label("Proportional residual error (fraction)")\n tumorVoladdSd <- 30 ; label("Additive residual error (tumor volume)")\n })\n model({\n damageTransit <- exp(ldamageTransit)\n drugSlope <- exp(ldrugSlope)\n tumorExpGrowth <- exp(ltumorExpGrowth)\n tumorLinGrowth <- exp(ltumorLinGrowth)\n\n # tumorVol0 is provided in the data as the initial volume of the tumor. It\n # can also be estimated.\n cyclingCells(0) <- tumorVol0\n psi <- 20 # psi is defined in the paper to cause a rapid switch between exponential and linear regimes\n tumorVol <- cyclingCells + damagedCells1 + damagedCells2 + damagedCells3\n # Cc is provided in the data (or in an appended model) as the drug\n # concentration. Units for Cc will be apply to k2.\n drugEffectCyclingCells <- drugSlope*Cc\n d/dt(cyclingCells) <- tumorExpGrowth*cyclingCells/(1 + (tumorExpGrowth/tumorLinGrowth * tumorVol)^psi)^(1/psi) - drugEffectCyclingCells*cyclingCells\n d/dt(damagedCells1) <- drugEffectCyclingCells*cyclingCells - damageTransit*damagedCells1\n d/dt(damagedCells2) <- damageTransit*(damagedCells1 - damagedCells2)\n d/dt(damagedCells3) <- damageTransit*(damagedCells2 - damagedCells3)\n tumorVol ~ prop(tumorVolpropSd) + add(tumorVoladdSd)\n })\n}\n\nattr(oncology_xenograft_simeoni_2004, "message") <- "You can modify the number of damaged cell compartments in the model using the function updateOncologyXenograftSimeoni2004(model, ncmt)"\noncology_xenograft_simeoni_2004
#> 46 tgi_no_sat_Koch <- function() {\n description <- "One compartment TGI model with with exponential tumor growth, without saturation."\n ini({\n lts0 <- 0.8; label("Initial tumor size (TS0)")\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n lkgl <- 0.7; label("Zero-order linear growth rate")\n lkge <- 0.7; label("First-order exponential growth rate")\n CcpropSd <- 0.5 ; label("PK proportional residual error (fraction)")\n tumorSizepropSd <- 0.5 ; label("Tumor size proportional residual error (fraction)")\n tumorSizeaddSd <- 30 ; label("Tumor size additive residual error (tumor volume)")\n })\n model({\n ts0 <- exp(lts0)\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n kge <- exp(lkge)\n kgl <- exp(lkgl)\n \n kel <- cl / vc\n tumorSize(0) <- ts0\n \n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n d/dt(tumorSize) <- (2*kge*kgl*tumorSize)/(kgl+2*kge*tumorSize)\n \n Cc <- central / vc\n Cc ~ prop(CcpropSd)\n tumorSize ~ prop(tumorSizepropSd) + add(tumorSizeaddSd)\n })\n}
#> 47 tgi_no_sat_expo <- function() {\n description <- "One compartment TGI model with with exponential tumor growth, without saturation."\n ini({\n lts0 <- 0.8; label("Initial tumor size (TS0)") \n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n lkge <- 0.7; label("FIrst-order exponential growth rate")\n CcpropSd <- 0.5 ; label("PK proportional residual error (fraction)")\n tumorSizepropSd <- 0.5 ; label("Tumor size proportional residual error (fraction)")\n tumorSizeaddSd <- 30 ; label("Tumor size additive residual error (tumor volume)")\n })\n model({\n ts0 <- exp(lts0)\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n kge <- exp(lkge)\n \n kel <- cl / vc\n tumorSize(0) <- ts0\n \n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n d/dt(tumorSize) <- kge*tumorSize\n \n Cc <- central / vc\n Cc ~ prop(CcpropSd)\n tumorSize ~ prop(tumorSizepropSd) + add(tumorSizeaddSd)\n })\n}
#> 48 tgi_no_sat_linear <- function() {\n description <- "One compartment TGI model with with linear tumor growth, without saturation."\n ini({\n lts0 <- 0.8; label("Initial tumor size (TS0)") \n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n lkgl <- 0.7; label("Zero-order linear growth rate")\n CcpropSd <- 0.5 ; label("PK proportional residual error (fraction)")\n tumorSizepropSd <- 0.5 ; label("Tumor size proportional residual error (fraction)")\n tumorSizeaddSd <- 30 ; label("Tumor size additive residual error (tumor volume)")\n })\n model({\n ts0 <- exp(lts0)\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n kgl <- exp(lkgl)\n \n kel <- cl / vc\n tumorSize(0) <- ts0\n \n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n d/dt(tumorSize) <- kgl\n \n Cc <- central / vc\n Cc ~ prop(CcpropSd)\n tumorSize ~ prop(tumorSizepropSd) + add(tumorSizeaddSd)\n })\n}
#> 49 tgi_no_sat_powerLaw <- function() {\n description <- "One compartment TGI model with with exponential tumor growth, without saturation."\n ini({\n lts0 <- 0.8; label("Initial tumor size (TS0)")\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n lgamma <- 0.95; label("proliferative cells as a fraction of the full tumor volume (gamma)")\n lkgl <- 0.7; label("Zero-order linear growth rate")\n lkge <- 0.7; label("First-order exponential growth rate")\n CcpropSd <- 0.5 ; label("PK proportional residual error (fraction)")\n tumorSizepropSd <- 0.5 ; label("Tumor size proportional residual error (fraction)")\n tumorSizeaddSd <- 30 ; label("Tumor size additive residual error (tumor volume)")\n })\n model({\n ts0 <- exp(lts0)\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n gamma<- exp(lgamma)\n kge <- exp(lkge)\n kgl <- exp(lkgl)\n \n kel <- cl / vc\n tumorSize(0) <- ts0\n \n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n d/dt(tumorSize) <- kge*tumorSize^gamma\n \n Cc <- central / vc\n Cc ~ prop(CcpropSd)\n tumorSize ~ prop(tumorSizepropSd) + add(tumorSizeaddSd)\n })\n}
#> 50 tgi_sat_VonBertalanffy <- function() {\n description <- "One compartment TGI model where tumor growth is limited by a loss term, with saturation."\n ini({\n lts0 <- 0.3; label("Initial tumor size (TS0)") \n ltsmax <- 0.9; label("Maximum tumor size at saturation (TSmax)")\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n lkg <- 0.7; label("Birth rate")\n lkd <- 0.7; label ("Death rate")\n CcpropSd <- 0.5 ; label("PK proportional residual error (fraction)")\n tumorSizepropSd <- 0.5 ; label("Tumor size proportional residual error (fraction)")\n tumorSizeaddSd <- 30 ; label("Tumor size additive residual error (tumor volume)")\n })\n model({\n ts0 <- exp(lts0)\n tsmax <- exp(ltsmax)\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n kg <- exp(lkg)\n kd <-exp(lkd)\n \n kel <- cl / vc\n tumorSize(0) <- ts0\n \n \n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n d/dt(tumorSize) <- kg*tumorSize^(2/3)-kd*tumorSize\n \n Cc <- central / vc\n Cc ~ prop(CcpropSd)\n tumorSize ~ prop(tumorSizepropSd) + add(tumorSizeaddSd)\n })\n}
#> 51 tgi_sat_genVonBertalanffy <- function() {\n description <- "One compartment TGI model where tumor growth is limited by a loss term, with saturation."\n ini({\n lts0 <- 0.3; label("Initial tumor size (TS0)") \n ltsmax <- 0.9; label("Maximum tumor size at saturation (TSmax)")\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n lkg <- 0.7; label("Birth rate")\n lkd <- 0.7; label ("Death rate")\n lgamma <- 0.95; label("proliferative cells as a fraction of the full tumor volume (gamma)")\n CcpropSd <- 0.5 ; label("PK proportional residual error (fraction)")\n tumorSizepropSd <- 0.5 ; label("Tumor size proportional residual error (fraction)")\n tumorSizeaddSd <- 30 ; label("Tumor size additive residual error (tumor volume)")\n })\n model({\n ts0 <- exp(lts0)\n tsmax <- exp(ltsmax)\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n kg <- exp(lkg)\n kd <-exp(lkd)\n gamma <- exp(lgamma)\n \n kel <- cl / vc\n tumorSize(0) <- ts0\n \n \n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n d/dt(tumorSize) <- kg*tumorSize^(gamma)-kd*tumorSize\n \n Cc <- central / vc\n Cc ~ prop(CcpropSd)\n tumorSize ~ prop(tumorSizepropSd) + add(tumorSizeaddSd)\n })\n}
#> 52 tgi_sat_logistic <- function() {\n description <- "One compartment TGI model with with exponential tumor growth that decelerates linearly, with saturation."\n ini({\n lts0 <- 0.3; label("Initial tumor size (TS0)") \n ltsmax <- 0.9; label("Maximum tumor size at saturation (TSmax)")\n lka <- 0.45 ; label("Absorption rate (Ka)")\n lcl <- 1 ; label("Clearance (CL)")\n lvc <- 3.45 ; label("Central volume of distribution (V)")\n lkgl <- 0.7; label("Zero-order linear growth rate")\n CcpropSd <- 0.5 ; label("PK proportional residual error (fraction)")\n tumorSizepropSd <- 0.5 ; label("Tumor size proportional residual error (fraction)")\n tumorSizeaddSd <- 30 ; label("Tumor size additive residual error (tumor volume)")\n })\n model({\n ts0 <- exp(lts0)\n tsmax <- exp(ltsmax)\n ka <- exp(lka)\n cl <- exp(lcl)\n vc <- exp(lvc)\n kgl <- exp(lkgl)\n \n kel <- cl / vc\n tumorSize(0) <- ts0\n \n \n d/dt(depot) <- -ka*depot\n d/dt(central) <- ka*depot-kel*central\n d/dt(tumorSize) <- kge*tumorSize*(1-(tumorSize/tsmax))\n \n Cc <- central / vc\n Cc ~ prop(CcpropSd)\n tumorSize ~ prop(tumorSizepropSd) + add(tumorSizeaddSd)\n })\n}
#> Description
#> 1 One compartment PK model with linear clearance
#> 2 One compartment PK model with linear clearance using differential equations
#> 3 Two compartment PK model with linear clearance
#> 4 Two compartment PK model with linear clearance using differential equations
#> 5 Two compartment PK model with linear clearance using differential equations
#> 6 Two compartment PK model with time-dependent clearance using differential equations (structured like nivolumab PK model)
#> 7 Three compartment PK model with linear clearance
#> 8 Three compartment PK model with linear clearance using differential equations
#> 9 Phenylalanine model for absorption and metabolism in healthy subjects and patients with PKU
#> 10 Two compartment PK model with Michealis-Menten clearance using differential equations
#> 11 One compartment indirect response model with inhibition of kin.
#> 12 One compartment indirect response model with inhibition of kin.
#> 13 One compartment indirect response model with inhibition of kin.
#> 14 One compartment indirect response model with inhibition of kout.
#> 15 One compartment indirect response model with inhibition of kout.
#> 16 One compartment indirect response model with inhibition of kout.
#> 17 One compartment indirect response model with stimulation of kin.Parameterized using rate cosntants
#> 18 One compartment indirect response model with stimulation of kin.
#> 19 One compartment indirect response model with stimulation of kin.
#> 20 One compartment indirect response model with stimulation of kout.Parameterized using rate cosntants
#> 21 One compartment indirect response model with stimulation of kout.
#> 22 One compartment indirect response model with stimulation of kout.
#> 23 One compartment indirect response model with inhibition of kin and circadian kin_t.
#> 24 One compartment indirect response model with inhibition of kin and circadian kin_t.
#> 25 One compartment indirect response model with inhibition of kout and circadian kin_t.
#> 26 One compartment indirect response model with inhibition of kout and circadian kin_t.
#> 27 One compartment indirect response model with stimulation of kin and circadian kin_t.Parameterized using rate cosntants
#> 28 One compartment indirect response model with stimulation of kin and circadian kout_t.Parameterized using rate constants
#> 29 One compartment indirect response model with stimulation of kout and circadian kin_t.Parameterized using rate cosntants
#> 30 One compartment indirect response model with stimulation of kout and circadian kout_t.Parameterized using rate cosntants
#> 31 One compartment precursor-dependent indirect response model with inhibition of drug response. Parameterized with clearance and volume. (effect).
#> 32 One compartment precursor-dependent indirect response model with inhibition of drug response (effect).
#> 33 One compartment precursor-dependent indirect response model with inhibition of drug response (effect). Parameterized with clearance and volume
#> 34 One compartment precursor-dependent indirect response model with inhibition of drug response (effect). Parameterized with clearance and volume
#> 35 Two compartment PK model with linear clearance for average monoclonal antibodies (Davda 2014)
#> 36 PK double absorption model with simultaneous zero order and first order absorptions
#> 37 PK double absorption model with simultaneous first order and zero order absorptions
#> 38 PK double absorption model with simultaneous first order absorptions
#> 39 Liraglutide PK model in adolescents (Carlsson Petri 2021)
#> 40 Exenatide immediate-release PK model (Cirincione 2017)
#> 41 Dupilumab PK model (Kovalenko 2020)
#> 42 Tralokinumab PK model (Soehoel 2022)
#> 43 Lebrikizumab PK model (Zhu 2017)
#> 44 Signal transduction model for delayed concentration effects on cancer cell growth
#> 45 Oncology tumor growth model in xenograft models
#> 46 One compartment TGI model with with exponential tumor growth, without saturation.
#> 47 One compartment TGI model with with exponential tumor growth, without saturation.
#> 48 One compartment TGI model with with linear tumor growth, without saturation.
#> 49 One compartment TGI model with with exponential tumor growth, without saturation.
#> 50 One compartment TGI model where tumor growth is limited by a loss term, with saturation.
#> 51 One compartment TGI model where tumor growth is limited by a loss term, with saturation.
#> 52 One compartment TGI model with with exponential tumor growth that decelerates linearly, with saturation.
#>
#> $MB$model_catalog$select_group
#> $MB$model_catalog$select_group$`Model Library`
#> $MB$model_catalog$select_group$`Model Library`$PK_1cmt_des
#> [1] "mod_2"
#>
#> $MB$model_catalog$select_group$`Model Library`$PK_2cmt_des
#> [1] "mod_4"
#>
#> $MB$model_catalog$select_group$`Model Library`$PK_2cmt_no_depot
#> [1] "mod_5"
#>
#> $MB$model_catalog$select_group$`Model Library`$PK_2cmt_tdcl_des
#> [1] "mod_6"
#>
#> $MB$model_catalog$select_group$`Model Library`$PK_3cmt_des
#> [1] "mod_8"
#>
#> $MB$model_catalog$select_group$`Model Library`$phenylalanine_charbonneau_2021
#> [1] "mod_9"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_0cpt_transitEx
#> [1] "mod_10"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_inhi_kin
#> [1] "mod_11"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_inhi_kin_CLV
#> [1] "mod_12"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_inhi_kin_r0rmaxcrmax
#> [1] "mod_13"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_inhi_kout
#> [1] "mod_14"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_inhi_kout_CLV
#> [1] "mod_15"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_inhi_kout_r0rmaxcrmax
#> [1] "mod_16"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_stim_kin
#> [1] "mod_17"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_stim_kin_CLV
#> [1] "mod_18"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_stim_kin_r0rmaxcrmax
#> [1] "mod_19"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_stim_kout
#> [1] "mod_20"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_stim_kout_CLV
#> [1] "mod_21"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_1cpt_stim_kout_r0rmaxcrmax
#> [1] "mod_22"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_inhi_kin_kin_t
#> [1] "mod_23"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_inhi_kin_kout_t
#> [1] "mod_24"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_inhi_kout_kin_t
#> [1] "mod_25"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_inhi_kout_kout_t
#> [1] "mod_26"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_stim_kin_kin_t
#> [1] "mod_27"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_stim_kin_kout_t
#> [1] "mod_28"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_stim_kout_kin_t
#> [1] "mod_29"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_circ_1cpt_stim_kout_kout_t
#> [1] "mod_30"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_prec_1cpt_inhi_CLV
#> [1] "mod_31"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_prec_1cpt_inhi_r0rmaxcrmax
#> [1] "mod_32"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_prec_1cpt_stim_CLV
#> [1] "mod_33"
#>
#> $MB$model_catalog$select_group$`Model Library`$indirect_prec_1cpt_stim_r0rmaxcrmax
#> [1] "mod_34"
#>
#> $MB$model_catalog$select_group$`Model Library`$PK_double_sim_01
#> [1] "mod_36"
#>
#> $MB$model_catalog$select_group$`Model Library`$PK_double_sim_10
#> [1] "mod_37"
#>
#> $MB$model_catalog$select_group$`Model Library`$PK_double_sim_11
#> [1] "mod_38"
#>
#> $MB$model_catalog$select_group$`Model Library`$Cirincione_2017_exenatide
#> [1] "mod_40"
#>
#> $MB$model_catalog$select_group$`Model Library`$Kovalenko_2020_dupilumab
#> [1] "mod_41"
#>
#> $MB$model_catalog$select_group$`Model Library`$tgi_no_sat_Koch
#> [1] "mod_46"
#>
#> $MB$model_catalog$select_group$`Model Library`$tgi_no_sat_expo
#> [1] "mod_47"
#>
#> $MB$model_catalog$select_group$`Model Library`$tgi_no_sat_linear
#> [1] "mod_48"
#>
#> $MB$model_catalog$select_group$`Model Library`$tgi_no_sat_powerLaw
#> [1] "mod_49"
#>
#> $MB$model_catalog$select_group$`Model Library`$tgi_sat_VonBertalanffy
#> [1] "mod_50"
#>
#> $MB$model_catalog$select_group$`Model Library`$tgi_sat_genVonBertalanffy
#> [1] "mod_51"
#>
#> $MB$model_catalog$select_group$`Model Library`$tgi_sat_logistic
#> [1] "mod_52"
#>
#>
#>
#> $MB$model_catalog$select_plain
#> $MB$model_catalog$select_plain$PK_1cmt_des
#> [1] "mod_2"
#>
#> $MB$model_catalog$select_plain$PK_2cmt_des
#> [1] "mod_4"
#>
#> $MB$model_catalog$select_plain$PK_2cmt_no_depot
#> [1] "mod_5"
#>
#> $MB$model_catalog$select_plain$PK_2cmt_tdcl_des
#> [1] "mod_6"
#>
#> $MB$model_catalog$select_plain$PK_3cmt_des
#> [1] "mod_8"
#>
#> $MB$model_catalog$select_plain$phenylalanine_charbonneau_2021
#> [1] "mod_9"
#>
#> $MB$model_catalog$select_plain$indirect_0cpt_transitEx
#> [1] "mod_10"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_inhi_kin
#> [1] "mod_11"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_inhi_kin_CLV
#> [1] "mod_12"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_inhi_kin_r0rmaxcrmax
#> [1] "mod_13"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_inhi_kout
#> [1] "mod_14"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_inhi_kout_CLV
#> [1] "mod_15"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_inhi_kout_r0rmaxcrmax
#> [1] "mod_16"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_stim_kin
#> [1] "mod_17"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_stim_kin_CLV
#> [1] "mod_18"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_stim_kin_r0rmaxcrmax
#> [1] "mod_19"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_stim_kout
#> [1] "mod_20"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_stim_kout_CLV
#> [1] "mod_21"
#>
#> $MB$model_catalog$select_plain$indirect_1cpt_stim_kout_r0rmaxcrmax
#> [1] "mod_22"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_inhi_kin_kin_t
#> [1] "mod_23"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_inhi_kin_kout_t
#> [1] "mod_24"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_inhi_kout_kin_t
#> [1] "mod_25"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_inhi_kout_kout_t
#> [1] "mod_26"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_stim_kin_kin_t
#> [1] "mod_27"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_stim_kin_kout_t
#> [1] "mod_28"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_stim_kout_kin_t
#> [1] "mod_29"
#>
#> $MB$model_catalog$select_plain$indirect_circ_1cpt_stim_kout_kout_t
#> [1] "mod_30"
#>
#> $MB$model_catalog$select_plain$indirect_prec_1cpt_inhi_CLV
#> [1] "mod_31"
#>
#> $MB$model_catalog$select_plain$indirect_prec_1cpt_inhi_r0rmaxcrmax
#> [1] "mod_32"
#>
#> $MB$model_catalog$select_plain$indirect_prec_1cpt_stim_CLV
#> [1] "mod_33"
#>
#> $MB$model_catalog$select_plain$indirect_prec_1cpt_stim_r0rmaxcrmax
#> [1] "mod_34"
#>
#> $MB$model_catalog$select_plain$PK_double_sim_01
#> [1] "mod_36"
#>
#> $MB$model_catalog$select_plain$PK_double_sim_10
#> [1] "mod_37"
#>
#> $MB$model_catalog$select_plain$PK_double_sim_11
#> [1] "mod_38"
#>
#> $MB$model_catalog$select_plain$Cirincione_2017_exenatide
#> [1] "mod_40"
#>
#> $MB$model_catalog$select_plain$Kovalenko_2020_dupilumab
#> [1] "mod_41"
#>
#> $MB$model_catalog$select_plain$tgi_no_sat_Koch
#> [1] "mod_46"
#>
#> $MB$model_catalog$select_plain$tgi_no_sat_expo
#> [1] "mod_47"
#>
#> $MB$model_catalog$select_plain$tgi_no_sat_linear
#> [1] "mod_48"
#>
#> $MB$model_catalog$select_plain$tgi_no_sat_powerLaw
#> [1] "mod_49"
#>
#> $MB$model_catalog$select_plain$tgi_sat_VonBertalanffy
#> [1] "mod_50"
#>
#> $MB$model_catalog$select_plain$tgi_sat_genVonBertalanffy
#> [1] "mod_51"
#>
#> $MB$model_catalog$select_plain$tgi_sat_logistic
#> [1] "mod_52"
#>
#>
#> $MB$model_catalog$select_subtext
#> [1] "One compartment PK model with linear clearance using differential equations"
#> [2] "Two compartment PK model with linear clearance using differential equations"
#> [3] "Two compartment PK model with linear clearance using differential equations"
#> [4] "Two compartment PK model with time-dependent clearance using differential equations (structured like nivolumab PK model)"
#> [5] "Three compartment PK model with linear clearance using differential equations"
#> [6] "Phenylalanine model for absorption and metabolism in healthy subjects and patients with PKU"
#> [7] "Two compartment PK model with Michealis-Menten clearance using differential equations"
#> [8] "One compartment indirect response model with inhibition of kin."
#> [9] "One compartment indirect response model with inhibition of kin."
#> [10] "One compartment indirect response model with inhibition of kin."
#> [11] "One compartment indirect response model with inhibition of kout."
#> [12] "One compartment indirect response model with inhibition of kout."
#> [13] "One compartment indirect response model with inhibition of kout."
#> [14] "One compartment indirect response model with stimulation of kin.Parameterized using rate cosntants"
#> [15] "One compartment indirect response model with stimulation of kin."
#> [16] "One compartment indirect response model with stimulation of kin."
#> [17] "One compartment indirect response model with stimulation of kout.Parameterized using rate cosntants"
#> [18] "One compartment indirect response model with stimulation of kout."
#> [19] "One compartment indirect response model with stimulation of kout."
#> [20] "One compartment indirect response model with inhibition of kin and circadian kin_t."
#> [21] "One compartment indirect response model with inhibition of kin and circadian kin_t."
#> [22] "One compartment indirect response model with inhibition of kout and circadian kin_t."
#> [23] "One compartment indirect response model with inhibition of kout and circadian kin_t."
#> [24] "One compartment indirect response model with stimulation of kin and circadian kin_t.Parameterized using rate cosntants"
#> [25] "One compartment indirect response model with stimulation of kin and circadian kout_t.Parameterized using rate constants"
#> [26] "One compartment indirect response model with stimulation of kout and circadian kin_t.Parameterized using rate cosntants"
#> [27] "One compartment indirect response model with stimulation of kout and circadian kout_t.Parameterized using rate cosntants"
#> [28] "One compartment precursor-dependent indirect response model with inhibition of drug response. Parameterized with clearance and volume. (effect)."
#> [29] "One compartment precursor-dependent indirect response model with inhibition of drug response (effect)."
#> [30] "One compartment precursor-dependent indirect response model with inhibition of drug response (effect). Parameterized with clearance and volume"
#> [31] "One compartment precursor-dependent indirect response model with inhibition of drug response (effect). Parameterized with clearance and volume"
#> [32] "PK double absorption model with simultaneous zero order and first order absorptions"
#> [33] "PK double absorption model with simultaneous first order and zero order absorptions"
#> [34] "PK double absorption model with simultaneous first order absorptions"
#> [35] "Exenatide immediate-release PK model (Cirincione 2017)"
#> [36] "Dupilumab PK model (Kovalenko 2020)"
#> [37] "One compartment TGI model with with exponential tumor growth, without saturation."
#> [38] "One compartment TGI model with with exponential tumor growth, without saturation."
#> [39] "One compartment TGI model with with linear tumor growth, without saturation."
#> [40] "One compartment TGI model with with exponential tumor growth, without saturation."
#> [41] "One compartment TGI model where tumor growth is limited by a loss term, with saturation."
#> [42] "One compartment TGI model where tumor growth is limited by a loss term, with saturation."
#> [43] "One compartment TGI model with with exponential tumor growth that decelerates linearly, with saturation."
#>
#> $MB$model_catalog$msgs
#> NULL
#>
#> $MB$model_catalog$hasmdl
#> [1] TRUE
#>
#> $MB$model_catalog$isgood
#> [1] TRUE
#>
#>
#> $MB$ts_details
#> $MB$ts_details$months
#> $MB$ts_details$months$verb
#> [1] "Months"
#>
#> $MB$ts_details$months$conv
#> [1] 4.133598e-07
#>
#>
#> $MB$ts_details$weeks
#> $MB$ts_details$weeks$verb
#> [1] "Weeks"
#>
#> $MB$ts_details$weeks$conv
#> [1] 1.653439e-06
#>
#>
#> $MB$ts_details$days
#> $MB$ts_details$days$verb
#> [1] "Days"
#>
#> $MB$ts_details$days$conv
#> [1] 1.157407e-05
#>
#>
#> $MB$ts_details$hours
#> $MB$ts_details$hours$verb
#> [1] "Hours"
#>
#> $MB$ts_details$hours$conv
#> [1] 0.0002777778
#>
#>
#>
#> $MB$elements
#> $MB$elements$element_1
#> $MB$elements$element_1$isgood
#> [1] TRUE
#>
#> $MB$elements$element_1$ui
#> $MB$elements$element_1$ui$ui_mb_model
#> [1] ""
#>
#> $MB$elements$element_1$ui$time_scale
#> [1] "weeks"
#>
#> $MB$elements$element_1$ui$element_name
#> [1] "Model 1"
#>
#> $MB$elements$element_1$ui$catalog_selection
#> [1] "mod_1"
#>
#> $MB$elements$element_1$ui$base_from
#> [1] "catalog"
#>
#>
#> $MB$elements$element_1$id
#> [1] "element_1"
#>
#> $MB$elements$element_1$idx
#> [1] 1
#>
#> $MB$elements$element_1$fcn_obj_name
#> [1] "MB_obj_1_fcn"
#>
#> $MB$elements$element_1$rx_obj_name
#> [1] "MB_obj_1_rx"
#>
#> $MB$elements$element_1$ts_obj_name
#> [1] "MB_obj_1_ts"
#>
#> $MB$elements$element_1$msgs
#> NULL
#>
#> $MB$elements$element_1$code_previous
#> [1] ""
#>
#> $MB$elements$element_1$update_model_code
#> [1] FALSE
#>
#> $MB$elements$element_1$components_table
#> data frame with 0 columns and 0 rows
#>
#> $MB$elements$element_1$selected_component_id
#> NULL
#>
#> $MB$elements$element_1$components_list
#> list()
#>
#> $MB$elements$element_1$checksum
#> [1] "3c32b3786df13af7692ea80f98ffba18"
#>
#> $MB$elements$element_1$base_model_name
#> [1] ""
#>
#> $MB$elements$element_1$base_model
#> [1] ""
#>
#>
#>
#> $MB$current_element
#> [1] "element_1"
#>
#> $MB$checksum
#> [1] "24933f86b657b9503f22440e8c4d3cac"
#>
#>
#> $MOD_TYPE
#> [1] "MB"
#>
#> $id
#> [1] "MB"
#>
#> $FM_yaml_file
#> [1] "/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/formods/templates/formods.yaml"
#>
#> $MOD_yaml_file
#> [1] "/private/var/folders/pq/7srbf_fx3rd3k706hgxkg61r0000gp/T/RtmpsHsa6m/temp_libpathea835f893037/ruminate/templates/MB.yaml"
#>
#> $shiny_token
#> [1] "non_shiny"
#>