runReverseDosimetry: Estimate exposure from montecarlo results and biomonitoring...
In plethem: Population Life Course Exposure to Health Effects Modeling

Description Usage Arguments Value Examples

View source: R/performReverseDosimetry.R

The function estimates exposures for the observed biomonitoring data using montecarlo simulation results over a large range of exposures. The montecarlo results are obtained from a PBPK model. The biomonitoring results are obtained from a population level study. The montecarlo results and biomonitoring data should have the same units and should be for the same physiological data source (eg: metabolite concentration in the urine).

runReverseDosimetry(
  mcData,
  biomData,
  percentiles = c(5, 10, 25, 50, 75, 95, 99, 100),
  dose_list = NULL
)

`mcData`	M by N data frame where M is the the individual exposures at which the PBPK model is run and N is the number of monte carlo runs at each exposure. It is recommended that M is between 25 and 40 and N is greater than 1000.
`biomData`	List consisting of biomonitoring data. It is recommended that atleast 1000 biomonitering values be provided to ensure accuracy for results.
`percentiles`	Vector of percentiles for which exposure needs to be estimated. By default returns the 5th, 50th, 95th and 99th exposure estimate.
`dose_list`	A list of M elements that contain exposures at which monte carlo simulations were run. If no list is provided, the first column names of the mcData input are assumed to contain exposure values.

List of values related to reverse dosimetry

cdf: Cumulative Distribution function of the exposure estimate
pdf: Probability distribution function of the exposure estimate
percentiles: Data frame of percentiles and exposure estimates for the percentile

pD <- c(seq(.05,.90,.05),.94,.95,.96,.97,.98,.99,1.00)
dosing <- c(0.010, 0.011, 0.012, 0.014, 0.016, 0.018, 0.021, 0.023, 0.027, 0.030, 0.034, 0.039)
dosing <- c(dosing, 0.044, 0.050, 0.057, 0.065, 0.073, 0.083, 0.094, 0.107, 0.121, 0.137)
dosing <- c(dosing, 0.155, 0.176, 0.200)
runReverseDosimetry(mcDataExample, biomDataExample, percentiles = pD, dose_list = dosing)