physiology.data | R Documentation |
This data set contains values from Davies and Morris (1993) necessary to paramaterize a toxicokinetic model for human, mouse, rat, dog, or rabbit. The temperature for each species are taken from Reece (2015), Jordon (1995), and Stammers (1926). Mean residence time for the small intestine is from Grandoni et al. (2019). Human small intestine radius is from Yu et al. (1999). Rat small intestine radius is from Griffin and O'Driscoll (2008).
physiology.data
A data.frame containing 18 rows and 7 columns.
John Wambaugh and Nisha Sipes
davies1993physiologicalhttk
\insertRefbrown1997physiologicalhttk
\insertRefbirnbaum1994physiologicalhttk
\insertRefreece201514httk
\insertRefstammers1926bloodhttk
\insertRefjordan1995temperaturehttk
\insertRefgrandoni2019buildinghttk
\insertRefgriffin2008modelshttk
# We can add a new species (for example, wolverines) by adding new information
# to the physiology.data and tissue.data tables. It can be convenient to start by
# by replicating the data from another species and adjusting as appropriate:
# Copy physiology data from rabbit:
new.species <- physiology.data[,"Rabbit"]
names(new.species) <- physiology.data[,"Parameter"]
rabbit.BW <- new.species["Average BW"]
# Rausch and Pearson (1972) https://doi.org/10.2307/3799057 :
new.species["Average BW"] <- 31.2
# Thiel et al. (2019) https://doi.org/10.1186/s12983-019-0319-8 :
new.species["Average Body Temperature"] <- 38.5
# Add new physiology data column to physiology.data table"
physiology.data <- cbind(physiology.data, new.species)
colnames(physiology.data)[length(colnames(physiology.data))] <- "Wolverine"
# Copy tissue data from rabbit:
new.tissue.data <- subset(tissue.data,Species=="Rabbit")
new.tissue.data$Species <- "Wolverine"
# Add new tissue data rows to tissue.data table:
tissue.data <- rbind(tissue.data, new.tissue.data)
# Species is now available for calculations:
calc_mc_css(chem.cas="80-05-7",
species="wolverine",
parameterize.arg.list=list(default.to.human=TRUE),
suppress.messages=TRUE,
samples = 100)
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