Package index • mipdtrial

All functions

adjust_dose_checks(): Checks for dose_update_number obtained from dose_update scheme

calc_auc_from_sim(): Get AUC from a simulation

check_when(): Check / clean when element

collect_tdms(): Simulate TDM collection

create_cov_object(): Create a list of PKPDsim covariates for modeling

create_design(): Create timing designs (static or adaptive) for use in simulated trial, such as sampling designs, target designs etc.

create_regimen_update_design(): Create scheme for updating dose or interval during dose optimization trial

create_sampling_design(): Function for creating sampling designs.

create_target_design(): Create target object

dose_grid_search(): Perform a grid search for a particular target by simulating a grid of doses

calc_concentration_from_regimen() calc_auc_from_regimen(): Calculate exposure metrics

filter_rows_0_100(): Filter rows with values 0 or 100

generate_iiv() generate_ruv(): Generate variability terms

get_dose_update_core(): Core function to calculate the dose update number for a row in a regimen update data.frame

get_dose_update_numbers_from_design(): Get dose number to update dose/interval at from the regime update scheme and a provided regimen.

get_quantity_from_variable(): Get quantities from variables in sim results

get_sampling_time_core(): Core function to calculate the sampling time for a row in a sampling schema data.frame.

get_sampling_times_from_scheme(): Calculate sampling times based on a given sampling schema and a regimen.

is_on_target(): Checks if a value (or vector of values) is within the specified target range

is_single_valid_number(): Checks that an object represents a single finite number

map_adjust_dose(): Adjust doses to achieve a target metric using MAP Bayesian estimation.

map_adjust_interval(): Adjust intervals to achieve a target metric using MAP Bayesian estimation by adapting the dosing interval

mipd_target_types(): Accepted PK/PD exposure targets

mipdtrial mipdtrial-package: MIPDtrial package

model_based_starting_dose(): Model-based starting dose

round_to_multiple(): Round to a multiple of any number (e.g. round to the nearest 5, 10, 100)

sample_and_adjust_by_dose(): Adjust dosing using MIPD on TDMs at specified dose numbers

simulate_dose_interval(): Simulate different doses/intervals in a dose/interval grid

simulate_fit(): Get MAP Bayesian parameters

update_regimen(): Update a regimen with a new dose