R/extractInputTab.R
In shirewoman2/Consultancy: Standardized tools for using R within the Simcyp Consultancy Team
Defines functions
extractInputTab
Documented in
extractInputTab
#' INTERNAL: Extract info from a tab formatted like the main "Input Sheet" tab
#' in Simulator output Excel files
#'
#' @param deets details to extract (the coded name)
#' @param sim_data_file sim_data_file
#' @param sheet what sheet to read
#'
#' @returns list of details from a tab formatted like the main "Input Sheet" tab
#' in Simulator output Excel files
extractInputTab <- function(deets = "all",
sim_data_file,
sheet,
VBE = FALSE,
CustomDosing = FALSE){
if(deets[1] == "all"){
MyInputDeets <- AllExpDetails$Detail[
str_detect(AllExpDetails$DataSource, "Input Sheet")]
} else {
MyInputDeets <- deets
}
InputDeets_DF <- AllExpDetails %>% filter(DataSource == "Input Sheet")
Out <- list()
InputTab <- suppressMessages(tryCatch(
readxl::read_excel(path = sim_data_file, sheet = sheet,
col_names = FALSE),
error = openxlsx::read.xlsx(sim_data_file, sheet = sheet,
colNames = FALSE)))
# If openxlsx read the file, the names are different. Fixing.
if(names(InputTab)[1] == "X1"){
names(InputTab) <- paste0("...", 1:ncol(InputTab))
}
Out[["ExcelResultsTimeStamp"]] <-
timeConv(as.numeric(InputTab[2, 1]), dataSource = "Excel")
# When Inhibitor 1 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Inhibitor 1"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_inhib$|Inhibitor1")]
}
# When Inhibitor 2 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Inhibitor 2"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_inhib2$|Inhibitor2")]
}
# When primary metabolite 1 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Sub Pri Metabolite1"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_met1|PrimaryMetabolite1")]
}
# When primary metabolite 2 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Sub Pri Metabolite2"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_met2|PrimaryMetabolite2")]
}
# When secondary metabolite is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Sub Sec Metabolite"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_secmet|SecondaryMetabolite")]
}
# When Inhibitor 1 metabolite is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Inh 1 Metabolite"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_inhib1met|Inhibitor1Metabolite")]
}
# We'll select details based on whether this was a Discovery simulation.
Out[["SimulatorUsed"]] <- ifelse(str_detect(InputTab[1, 1], "Discovery"),
"Simcyp Discovery", "Simcyp Simulator")
DiscoveryCol <- switch(Out[["SimulatorUsed"]],
"Simcyp Discovery" = c("Simulator and Discovery",
"Discovery only"),
"Simcyp Simulator" = c("Simulator only",
"Simulator and Discovery"))
# Need to filter to keep only details that we can possibly find based on
# what type of simulator was used
MyInputDeets <- intersect(MyInputDeets,
AllExpDetails$Detail[
AllExpDetails$SimulatorAvailability %in% DiscoveryCol])
InputDeets_DF <- InputDeets_DF %>%
filter(SimulatorAvailability %in% DiscoveryCol)
# Looking for locations of columns.
InputDeets_DF <- InputDeets_DF %>%
mutate(CompoundID = case_when(is.na(CompoundID) ~ "Trial Design",
.default = CompoundID))
if(VBE){
# I don't think there would be more than one compound in a VBE sim, so
# setting the compound ID to "substrate".
InputDeets_DF <- InputDeets_DF %>%
filter(CompoundID %in% c("substrate", "Trial Design"))
}
ColLocations <- c("substrate" = 1,
"Trial Design" = which(t(InputTab[5, ]) == "Trial Design"),
"inhibitor 1" = which(t(InputTab[5, ]) == "Inhibitor 1"),
"inhibitor 2" = which(t(InputTab[5, ]) == "Inhibitor 2"),
"primary metabolite 1" = which(t(InputTab[5, ]) == "Sub Pri Metabolite1"),
"primary metabolite 2" = which(t(InputTab[5, ]) == "Sub Pri Metabolite2"),
"secondary metabolite" = which(t(InputTab[5, ]) == "Sub Sec Metabolite"),
"inhibitor 1 metabolite" = which(t(InputTab[5, ]) == "Inh 1 Metabolite"))
InputDeets_DF <- InputDeets_DF %>%
mutate(NameCol = ColLocations[CompoundID],
ValueCol = NameCol + 1) %>%
# If the NameCol is empty, it's b/c that compound ID or else a column with
# "Trial Design" wasn't found on that tab, so remove any empty NameCol
# rows.
filter(complete.cases(NameCol))
## Main set of parameters -----------------------------------------
# Dealing w/potential replicate values. CompoundType and pKa may be
# replicated but will have the same value, so when we take the unique
# value, that will drop away.
# Checking for any ADAMI parameters. (May need to adapt this later for
# other variations on ADAM models or anything else where there will be
# multiple cells with identical labels.)
ADAMIrow <- which(InputTab$...1 == "ADAMI Parameters")
if(length(ADAMIrow) == 0){
InputDeets_DF <- InputDeets_DF %>%
filter(!str_detect(Detail, "ADAMI"))
ADAMIreps <- NA
NonADAMIreps <- NA
MyInputDeets <- intersect(MyInputDeets, InputDeets_DF$Detail)
} else {
ADAMIreps <- InputDeets_DF %>%
filter(str_detect(Detail, "ADAMI")) %>%
pull(Detail)
NonADAMIreps <- sub("_ADAMI", "", ADAMIreps)
}
# sub function for finding correct cell
pullValue <- function(deet){
# Setting up regex to search
ToDetect <- InputDeets_DF %>%
filter(Detail == deet) %>% pull(Regex_row)
NameCol <- InputDeets_DF$NameCol[which(InputDeets_DF$Detail == deet)]
Row <- which(str_detect(InputTab[, NameCol] %>% pull(), ToDetect)) +
(InputDeets_DF %>% filter(Detail == deet) %>% pull(OffsetRows))
if(length(Row) == 0){
Val <- NA
} else {
if(deet %in% ADAMIreps){Row <- Row[Row > ADAMIrow]}
if(deet %in% NonADAMIreps){Row <- Row[Row < ADAMIrow]}
Val <- InputTab[Row,
InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == deet)]] %>% pull()
# If it's a kp scalar value other than the main one, then we need to
# 1st check whether the value listed is "User" and then get the value
# in the cell right below that if it is.
kpcheck <- str_detect(deet, "kp_scalar_") &
deet %in% paste0("kp_scalar", AllCompounds$Suffix) == FALSE
if(kpcheck){
if(complete.cases(Val) && Val == "Predicted"){
Val <- NA
} else {
NameColBelow <- InputTab[Row + 1,
InputDeets_DF$NameCol[
which(InputDeets_DF$Detail == deet)]] %>% pull()
if(str_detect(tolower(NameColBelow),
tolower(gsub(paste0("kp_scalar_|",
str_c(AllCompounds$Suffix, collapse = "|")),
"",
sub("additional_organ", "Additional Organ", deet))))){
Val <- InputTab[Row + 1, InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == deet)]] %>% pull()
} else {
Val <- NA
}
}
}
}
# If SimStartDayTime is not found, which will happen with animal
# sims, it may be possible to piece together from other data.
if(length(Val) == 0 & deet == "SimStartDayTime"){
StartDay <- as.character(InputTab[which(InputTab$...1 == "Start Day"), 2])
StartTime <- as.character(InputTab[which(InputTab$...1 == "Start Time"), 2])
StartTime <- str_split(sub("m", "", StartTime), "h")[[1]]
Val <-
paste0("Day ", StartDay, ", ",
formatC(as.numeric(StartTime[1]), width = 2, flag = "0"), ":",
formatC(as.numeric(StartTime[2]), width = 2, flag = "0"))
rm(StartDay, StartTime)
}
# Ontogeny profile along w/CompoundType and pKa are often listed twice
# in output for some reason. Only keeping the unique set of values for
# all deets. This will still throw a warning if there is more than one
# value, but we'd want to know that anyway, so that's why I'm not just
# keeping the 1st value listed.
Val <- sort(unique(Val))
# Accounting for when fu,p is scripted
if(length(Val) > 0 &&
(any(complete.cases(Val)) &&
str_detect(deet, "^fu_") & any(str_detect(Val, "script")))){
InputDeets_DF$Class[InputDeets_DF$Detail == deet] <- "character"
assign("InputDeets_DF", InputDeets_DF, envir = parent.frame())
}
suppressWarnings(
Val <- switch(InputDeets_DF$Class[InputDeets_DF$Detail == deet],
"character" = as.character(Val),
"numeric" = as.numeric(Val))
)
if(length(Val) > 1){
Val <- str_comma(Val)
}
# Tidying up some specific idiosyncracies of simulator output
Val <- ifelse(length(Val) == 0 ||
(complete.cases(Val) & Val == "n/a"), NA, Val)
Val <- ifelse(str_detect(deet, "^Unit"),
str_trim(gsub("\\(unbound\\)|\\(blood\\)|\\(unbound blood\\)|Dose \\(|\\)|CMax \\(|TMax \\(|AUC \\(|CL \\(Dose/AUC\\)\\(|\\(blood\\)",
"", Val)), Val)
return(Val)
}
# pullValue doesn't work for CL, so those are separate. Also need
# to do StartDayTime_x, SimulatorVersion, and ADCSimulation separately.
MyInputDeets1 <-
MyInputDeets[!str_detect(MyInputDeets,
"CLint_|Interaction_|^StartDayTime|Transport_|ADCSimulation|SimulatorVersion|OrganTissue")]
if(length(MyInputDeets1) > 0){
for(i in MyInputDeets1){
# print(i)
Out[[i]] <- pullValue(i)
}
}
## Some overall simulation details -----------------------------------
# Checking whether this was an ADC sim.
if("ADCSimulation_sub" %in% MyInputDeets){
Out[["ADCSimulation_sub"]] <-
any(str_detect(as.character(InputTab[, 1]),
InputDeets_DF %>% filter(Detail == "ADCSimulation_sub") %>%
pull(Regex_row)), na.rm = T)
}
# Checking simulator version
Out[["SimulatorVersion"]] <- ifelse(str_detect(InputTab[1, 1], "Discovery"),
as.character(InputTab[1, 1]),
str_extract(as.character(InputTab[3, 1]),
"Version [12][0-9]"))
### Checking on release profiles -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE)){
ReleaseProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
Suffix <- AllCompounds$Suffix[AllCompounds$CompoundID == i]
if(any(str_detect(t(InputTab[, as.numeric(ColLocations[i])]), "Release Mean"),
na.rm = TRUE)){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i]]), "CR/MR Input"))[1] + 1
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]), "Release Mean"))
EndRow <- EndRow[which.max(EndRow)] + 1 # Looking for last "Release Mean" row and then the next row will be the CV for that.
Release_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(Release_temp) <- c("NameCol", "ValCol")
# Older versions of simulator do not have CV. Checking.
ReleaseCV <- Release_temp$ValCol[which(str_detect(Release_temp$NameCol, "CV"))]
if(all(is.null(ReleaseCV))){ReleaseCV <- NA}
suppressWarnings(
ReleaseProfs[[i]] <- data.frame(
CR_MR_input = Out[[paste0("CR_MR_Input", Suffix)]],
Time = Release_temp$ValCol[which(str_detect(Release_temp$NameCol, "Time"))],
Release_mean = Release_temp$ValCol[which(str_detect(Release_temp$NameCol, "Release Mean"))],
Release_CV = ReleaseCV) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
Release_CV = Release_CV / 100, # Making this a fraction instead of a number up to 100
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, Time, Release_mean, Release_CV)
)
rm(StartRow, EndRow, Release_temp)
} else if(
paste0("CR_MR_Input",
AllCompounds$Suffix[AllCompounds$CompoundID == i]) %in%
names(Out) == TRUE &&
complete.cases(Out[[paste0("CR_MR_Input",
AllCompounds$Suffix[AllCompounds$CompoundID == i])]]) &&
Out[[paste0("CR_MR_Input",
AllCompounds$Suffix[AllCompounds$CompoundID == i])]] ==
"Weibull"){
Suffix <- AllCompounds$Suffix[AllCompounds$CompoundID == i]
ReleaseProfs <- data.frame(
CR_MR_input = Out[[paste0("CR_MR_Input", Suffix)]],
Parameter = c("Fmax", "alpha", "beta", "lag"),
Value = c(Out[[paste0("ReleaseProfile_Fmax", Suffix)]],
Out[[paste0("ReleaseProfile_alpha", Suffix)]],
Out[[paste0("ReleaseProfile_beta", Suffix)]],
Out[[paste0("ReleaseProfile_lag", Suffix)]]),
CV = c(Out[[paste0("ReleaseProfile_Fmax_CV", Suffix)]],
Out[[paste0("ReleaseProfile_alpha_CV", Suffix)]],
Out[[paste0("ReleaseProfile_beta_CV", Suffix)]],
Out[[paste0("ReleaseProfile_lag_CV", Suffix)]])) %>%
mutate(CV = CV / 100, # Making this a fraction instead of a number up to 100
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, CR_MR_input, Parameter, Value, CV)
} else {
ReleaseProfs <- NULL
}
}
ReleaseProfs <- bind_rows(ReleaseProfs)
if(nrow(ReleaseProfs) == 0){ReleaseProfs <- NULL}
} else {
ReleaseProfs <- NULL
}
### Checking on dissolution profiles ------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations])), "Dissolution( Mean)? \\(\\%"),
na.rm = TRUE)){
DissoProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
# There may be more than one tissue. Checking for this.
DissoTissueRows <- which(str_detect(t(InputTab[, ColLocations[i]]),
"^Dissolution Profile"))
# If the results do not specify any tissues, then start rows will be
# different. Last row will be the same, though.
LastRow <- which(str_detect(t(InputTab[, ColLocations[i]]), "Dissolution( Mean)? \\(\\%"))
LastRow <- LastRow[which.max(LastRow)] + 1 # Looking for last "Dissolution (%)" row and then the next row will be the CV for that.
if(length(DissoTissueRows) > 0){
StartRows <- which(str_detect(t(InputTab[, ColLocations[i]]), "^Dissolution Profile")) + 1
# It could be that one compound has dissolution profiles and another
# compound does not. Checking that here since I did not check it in
# the original "if" statement at the top of this section.
if(all(is.na(StartRows))){
next
}
if(length(StartRows) > 1){
EndRows <- c(StartRows[2:length(StartRows)], NA) - 2
EndRows[length(StartRows)] <- LastRow
} else {
EndRows <- LastRow
}
DissoTissues <- gsub("\\(|\\)", "",
str_extract(
t(InputTab[, ColLocations[i]])[DissoTissueRows],
"\\(.*\\)"))
} else {
# If the tissue is not specified, then there will be only 1 set of values.
StartRows <- which(str_detect(t(InputTab[, ColLocations[i]]), "Dissolution( Mean)? \\(\\%"))[1] - 1
DissoTissues <- "not specified"
EndRows <- LastRow
# It could be that one compound has dissolution profiles and another
# compound does not. Checking that here since I did not check it in
# the original "if" statement at the top of this section.
if(all(is.na(StartRows))){
next
}
}
DissoProfs[[i]] <- list()
for(tiss in 1:length(StartRows)){
Disso_temp <- InputTab[StartRows[tiss]:EndRows[tiss],
ColLocations[i]:(ColLocations[i]+1)]
names(Disso_temp) <- c("NameCol", "ValCol")
# Older versions of simulator do not have CV. Checking.
DissoCV <- Disso_temp$ValCol[which(str_detect(Disso_temp$NameCol, "CV"))]
if(all(is.null(DissoCV))){DissoCV <- NA}
suppressWarnings(
DissoProfs[[i]][[tiss]] <-
data.frame(
Time = Disso_temp$ValCol[which(str_detect(Disso_temp$NameCol, "Time"))],
Dissolution_mean = Disso_temp$ValCol[which(str_detect(Disso_temp$NameCol, "Dissolution( Mean)? \\(\\%"))],
Dissolution_CV = DissoCV) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
Dissolution_CV = Dissolution_CV / 100, # Making this a fraction instead of a number up to 100
File = sim_data_file,
Tissue = DissoTissues[[tiss]],
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]]))
)
rm(Disso_temp, DissoCV)
}
DissoProfs[[i]] <- bind_rows(DissoProfs[[i]])
}
DissoProfs <- bind_rows(DissoProfs) %>%
select(File, Tissue, CompoundID, Compound, Time,
Dissolution_mean, Dissolution_CV)
} else {
DissoProfs <- NULL
}
### Concentration-dependent fu -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations + 1])),
"Concentration-dependent fu profile"),
na.rm = TRUE)){
CDfupProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i] + 1]),
"Concentration-dependent fu profile"))[1] + 2
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"fu [0-9]"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has conc-dependent fu,p profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(is.na(StartRow)){
next
}
CDfup_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(CDfup_temp) <- c("NameCol", "ValCol")
CDfupProfs[[i]] <- data.frame(
Conc = CDfup_temp$ValCol[which(str_detect(CDfup_temp$NameCol, "Conc"))],
fup = CDfup_temp$ValCol[which(str_detect(CDfup_temp$NameCol, "fu [0-9]"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, Conc, fup)
rm(StartRow, EndRow, CDfup_temp)
}
CDfupProfs <- bind_rows(CDfupProfs)
} else {
CDfupProfs <- NULL
}
### Concentration-dependent B/P -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations + 1])),
"Concentration-dependent B/P profile"),
na.rm = TRUE)){
CDBPProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i] + 1]),
"Concentration-dependent B/P profile"))[1] + 2
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"B/P [0-9]"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has conc-dependent B/P profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(is.na(StartRow)){
next
}
CDBP_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(CDBP_temp) <- c("NameCol", "ValCol")
CDBPProfs[[i]] <- data.frame(
Conc = CDBP_temp$ValCol[which(str_detect(CDBP_temp$NameCol, "Conc"))],
BP = CDBP_temp$ValCol[which(str_detect(CDBP_temp$NameCol, "B/P [0-9]"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, Conc, BP)
rm(StartRow, EndRow, CDBP_temp)
}
CDBPProfs <- bind_rows(CDBPProfs)
} else {
CDBPProfs <- NULL
}
### pH-dependent luminal degradation -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations])),
"Degradation rate constant"), na.rm = TRUE)){
pHLumDeg <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"Degradation rate constant"))[1] - 1
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"Degradation rate constant [0-9]{1,} 1.h"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has pH-dependent fu,p profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(length(StartRow) == 0 || is.na(StartRow)){
next
}
pHLumDeg_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(pHLumDeg_temp) <- c("NameCol", "ValCol")
pHLumDeg[[i]] <- data.frame(
pH = pHLumDeg_temp$ValCol[which(str_detect(pHLumDeg_temp$NameCol, "pH"))],
DegradationRateConstant = pHLumDeg_temp$ValCol[which(str_detect(pHLumDeg_temp$NameCol, "Degradation rate constant [0-9]{1,} 1.h"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, pH, DegradationRateConstant)
rm(StartRow, EndRow, pHLumDeg_temp)
}
pHLumDeg <- bind_rows(pHLumDeg)
} else {
pHLumDeg <- NULL
}
### pH-dependent solubility -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations + 1])),
"Solubility-pH profile|User defined pH-Solubility"),
na.rm = TRUE)){
pHSol <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i] + 1]),
"Solubility-pH profile|User defined pH-Solubility"))[1] + 1
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"Entry [0-9]{1,} Solubility"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has pH-dependent fu,p profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(is.na(StartRow)){
next
}
pHSol_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(pHSol_temp) <- c("NameCol", "ValCol")
pHSol[[i]] <- data.frame(
pH = pHSol_temp$ValCol[which(str_detect(pHSol_temp$NameCol, "pH"))],
Solubility = pHSol_temp$ValCol[which(str_detect(pHSol_temp$NameCol, "Entry [0-9]{1,} Solubility"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, pH, Solubility)
rm(StartRow, EndRow, pHSol_temp)
}
pHSol <- bind_rows(pHSol)
} else {
pHSol <- NULL
}
## Pulling CL info ----------------------------------------------------
MyInputDeets2 <- MyInputDeets[str_detect(MyInputDeets, "CLint_")]
if(length(MyInputDeets2) > 0){
for(j in MyInputDeets2){
Suffix <- str_extract(j, "_sub$|_inhib$|_inhib2$|_met1$|_met2$|_secmet$|_inhib1met$")
NameCol <- InputDeets_DF$NameCol[InputDeets_DF$Detail == j]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
CLRows <- which(
InputTab[ , NameCol] == "Enzyme" |
str_detect(InputTab[ , NameCol] %>%
pull(),
"^Biliary (CLint|Clearance)") |
str_detect(InputTab[ , NameCol] %>%
pull(),
"^Additional HLM CLint|^Additional Systemic Clearance|^Additional HKM CLint") |
str_detect(InputTab[ , ValueCol] %>%
pull(),
"In Vivo Clear") |
str_detect(InputTab[ , NameCol] %>%
pull(),
"(Liver|Intestine|Biliary) Clearance"))
CLRows <- CLRows[complete.cases(InputTab[CLRows + 1, NameCol])]
if(Out[["SimulatorUsed"]] == "Simcyp Discovery"){
# Discovery sims have a slightly different setup on the Input
# Sheet and only the 1st CLRows value should be used b/c that
# section will contain all the info we need.
CLRows <- CLRows[1]
MyNames <- as.character(t(
InputTab[CLRows:nrow(InputTab), NameCol]))
DiscoveryDeets <-
data.frame(
Detail = c("CLiv_InVivoCL",
"CLpo_InVivoCL",
"CLint_biliary",
"CLint_biliary_fuinc",
"CLrenal",
"CL_AddSystemic",
"CL_PercentAvailReabsorption"),
RegexRow = c("CL.*iv.*[(]mL",
"CL.*po.*[(]mL",
"Biliary Clearance ..L/min",
"Biliary fu inc",
"CL R .mL",
"^Additional Systemic Clearance",
"^Percent.*re-absorption"))
for(i in 1:nrow(DiscoveryDeets)){
MyRow <- which(str_detect(MyNames, DiscoveryDeets$RegexRow[i]))
if(length(MyRow) == 0){
Out[[paste0(DiscoveryDeets$Detail[i], Suffix)]] <- NA
} else {
suppressWarnings(
Out[[paste0(DiscoveryDeets$Detail[i], Suffix)]] <-
as.numeric(InputTab[MyRow + CLRows - 1, ValueCol])
)
}
rm(MyRow)
}
# Liver and intestinal CL
LivOrInt <- c("Liver", "Intestine")[
c(any(str_detect(MyNames, "Liver")), any(str_detect(MyNames, "Intestine")))]
LivIndCL <-
data.frame(
Detail = c("CL_XXX_Type",
"CL_XXX__UseSaturableKinetics",
"CLint_XXX",
"CL_Km_XXX",
"CL_Vmax_XXX",
"CL_XXX_fuinc",
"CL_XXX_UseMetabolite",
"CL_XXX_MetabPerc",
"CL_XXX_ScrapingsCorrectionFactor",
"CL_XXX_ElutionCorrectionFactor"),
RegexRow = c(paste(i, "Clearance Type"),
"Use Saturable Kinetics",
"CLint",
"Km \\(",
"Vmax \\(",
"fu inc",
"Use Metabolite",
"Metabolite .%",
"\\(scrapings\\) Correction Factor",
"\\(elution\\) Correction Factor")
)
if(length(LivOrInt[complete.cases(LivOrInt)]) > 0){
for(i in LivOrInt[complete.cases(LivOrInt)]){
OrganRows <- range(
which(str_detect(MyNames, i) |
str_detect(MyNames,
paste0(str_sub(i, 1, 1), "M")))
)
for(k in 1:nrow(LivIndCL)){
MyRow <- which(str_detect(MyNames[OrganRows[1]:OrganRows[2]],
LivIndCL$RegexRow[k]))
if(length(MyRow) == 0){
Out[[paste0(sub("XXX", i, LivIndCL$Detail[k]), Suffix)]] <- NA
} else {
suppressWarnings(
Out[[paste0(sub("XXX", i, LivIndCL$Detail[k]), Suffix)]] <-
as.character(InputTab[MyRow + CLRows - 1, ValueCol])
)
}
rm(MyRow)
}
}
}
} else {
# Regular Simulator data extraction starts here.
# Checking for interaction data
IntRowStart <- which(str_detect(InputTab[, NameCol] %>%
pull(), "Ind max|^Ki |^MBI|Interaction"))[1] - 1
if(complete.cases(IntRowStart)){
CLRows <- CLRows[CLRows < min(IntRowStart)]
}
for(i in CLRows){
# CL for a specific enzyme
if(str_detect(as.character(InputTab[i, NameCol]), "Enzyme")){
LastRow_i <- which(is.na(InputTab[, NameCol]))
LastRow_i <- LastRow_i[LastRow_i > i][1] - 1
Enzyme <- gsub(" ", "", InputTab[i, NameCol + 1])
Pathway <- gsub(" |-", "", InputTab[i - 1, NameCol + 1])
if(as.character(InputTab[i+1, NameCol]) == "Genotype"){
Genotype <- InputTab[i+1, NameCol + 1]
Genotype <- gsub("\\*", "star", Genotype)
Genotype <- gsub("/", "", Genotype)
Enzyme <- paste0(Enzyme, "_", Genotype)
CLrow <- i + 2
} else if((str_detect(Enzyme, "User") &
!str_detect(InputTab[i+1, NameCol], "CLint|Vmax")) |
str_detect(tolower(InputTab[i + 1, NameCol]),
"ontogeny")){
CLrow <- i + 2
} else {
CLrow <- i + 1
}
CLType <- str_extract(InputTab[CLrow, NameCol],
"CLint|Vmax|t1/2|Ind max")
if(CLType == "CLint"){
# NOTE TO CODERS: I'd been including units for CLint in
# the past, but I realized that I hadn't included units
# for other enzymes, so I decided later to omit them.
# Keeping this bit of code, albeit commented out, so
# that we can add them back easily if we want.
# Units <- str_extract(InputTab[CLrow, NameCol],
# "\\(.*\\)")
# Units <- gsub("\\(|\\)", "", Units)
# Units <- gsub("/| ", "_", Units)
# # Dealing with mu since it's causing some problems
# # downstream when a symbol
# Units <- gsub(rlang::chr_unserialise_unicode("<U+00B5>"),
# "u", Units)
suppressWarnings(
Out[[paste0(
paste("CLint", Enzyme, Pathway, # Units,
sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow, NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("fu_mic", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow+1, NameCol + 1])
)
# Check for any UGT-specific CL parameters
if(str_detect(Enzyme, "UGT") &
any(str_detect(t(InputTab[i:LastRow_i, NameCol]),
"rUGT"))){
rUGTSysInfo <- InputTab[i:LastRow_i, c(NameCol, ValueCol)] %>%
rename(Name = 1, Value = 2) %>%
filter(str_detect(Name, "rUGT"))
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTSystem",
Suffix)]] <-
rUGTSysInfo[which(str_detect(rUGTSysInfo$Name,
"rUGTSystem")), ] %>%
pull(Value)
suppressWarnings(
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTScalar_liver",
Suffix)]] <-
rUGTSysInfo[which(
str_detect(tolower(rUGTSysInfo$Name),
"rugtscalar.*liver")), ] %>%
pull(Value) %>% as.numeric())
suppressWarnings(
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTScalar_intestine",
Suffix)]] <-
rUGTSysInfo[which(
str_detect(tolower(rUGTSysInfo$Name),
"rugtscalar.*intestine")), ] %>%
pull(Value) %>% as.numeric())
suppressWarnings(
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTScalar_kidney",
Suffix)]] <-
rUGTSysInfo[which(
str_detect(tolower(rUGTSysInfo$Name),
"rugtscalar.*kidney")), ] %>%
pull(Value) %>% as.numeric())
rm(rUGTSysInfo)
}
rm(Enzyme, Pathway, CLType)
next
}
if(CLType == "Vmax"){
suppressWarnings(
Out[[paste0(
paste("Vmax", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow, NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("Km", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow+1, NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("fu_mic", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow+2, NameCol + 1])
)
rm(Enzyme, Pathway, CLType)
next
}
if(CLType == "t1/2"){
suppressWarnings(
Out[[paste0(
paste("HalfLife", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow, NameCol + 1])
)
rm(Enzyme, Pathway, CLType)
next
}
}
# Biliary CL
if(str_detect(as.character(InputTab[i, NameCol]), "^Biliary (CLint|Clearance)")){
suppressWarnings(
Out[[paste0("CLint_biliary", Suffix)]] <-
as.numeric(InputTab[i, NameCol + 1])
)
}
# Other HLM CL
if(str_detect(as.character(InputTab[i, NameCol]), "^Additional HLM CLint")){
suppressWarnings(
Out[[paste0("CLint_AddHLM", Suffix)]] <-
as.numeric(InputTab[i, NameCol + 1])
)
}
# Other HKM CL
if(str_detect(as.character(InputTab[i, NameCol]), "^Additional HKM CLint")){
suppressWarnings(
Out[[paste0("CLint_AddHKM", Suffix)]] <-
as.numeric(InputTab[i, NameCol + 1])
)
}
# in vivo CL
if(str_detect(as.character(InputTab[i, ValueCol]),
"In Vivo Clearance")){
MyNames <- as.character(t(
InputTab[i:min(
c(IntRowStart, CLRows[which(CLRows == i) + 1] - 1,
nrow(InputTab)), na.rm = T), NameCol]))
suppressWarnings(
Out[[paste0("CLiv_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"CL.*iv.*[(](m)?L")) + i - 1,
ValueCol])
)
suppressWarnings(
Out[[paste0("CLbiliary_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"Biliary Clearance")) + i - 1,
ValueCol])
)
suppressWarnings(
Out[[paste0("CLadditional_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"Additional Systemic Clearance")) + i - 1,
ValueCol])
)
suppressWarnings(
Out[[paste0("CLpo_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"^CL .po.")) + i - 1,
ValueCol])
)
}
}
rm(CLRows, IntRowStart, NameCol, Suffix)
}
}
}
## Pulling interaction info -------------------------------------------
MyInputDeets3 <- MyInputDeets[str_detect(MyInputDeets, "Interaction_")]
if(length(MyInputDeets3) > 0){
for(j in MyInputDeets3){
Suffix <- str_extract(j, "_sub$|_inhib$|_inhib2$|_met1$|_secmet$|_inhib1met$")
NameCol <- InputDeets_DF$NameCol[InputDeets_DF$Detail == j]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
IntRows <- which(str_detect(InputTab[ , NameCol] %>% pull(),
"^Enzyme$|^Transporter$"))
IntRows <- IntRows[complete.cases(InputTab[IntRows + 1, NameCol])]
# Only IntRows after the first instance of an
# interaction type of term is found in NameCol. NB: I
# thought it would work to just look for cells after
# "interaction", but "interaction" hasn't always been
# listed in the output files I've found.
IntRowStart <- which(str_detect(InputTab[, NameCol] %>%
pull(), "Ind [mM]ax|Ind [sS]lope|^Ki |^MBI"))[1] - 1
TransporterTissues <- IntRows[which(
str_detect(t(InputTab[IntRows, NameCol]), "Transporter"))]
TransporterTissues <- TransporterTissues[which(
str_detect(t(InputTab[TransporterTissues - 1, NameCol]),
"Organ/Tissue"))] - 1
TransporterTissues <- data.frame(
Row = TransporterTissues,
Tissue = as.character(t(InputTab[TransporterTissues, ValueCol])))
if(complete.cases(IntRowStart)){
IntRows <- IntRows[IntRows >= IntRowStart]
for(i in IntRows){
Enzyme <- gsub(" |\\(|\\)|-|/", "_", InputTab[i, NameCol + 1])
Enzyme <- gsub("_{2,}", "_", Enzyme)
Enzyme <- sub("_$", "", Enzyme)
NextEmptyCell <- which(is.na(InputTab[, NameCol + 1]))
NextEmptyCell <- NextEmptyCell[NextEmptyCell > i][1]
# If there's another interaction listed
# before the next empty cell, need to
# account for that.
NextInt <- IntRows[which(IntRows == i) + 1] - 1
NextInt <- ifelse(i == IntRows[length(IntRows)],
nrow(InputTab), NextInt)
ThisIntRows <- i:(c(NextEmptyCell, NextInt)[which.min(c(NextEmptyCell, NextInt))])
ThisIntRows <- setdiff(ThisIntRows, NextEmptyCell)
# Induction
IndParam1stRow <- which(str_detect(InputTab[ThisIntRows, NameCol] %>% pull(),
"Ind max|Ind Slope"))
if(length(IndParam1stRow) > 0){
IndModelCheck <- list(str_detect(t(InputTab[ThisIntRows, NameCol]), "Ind max"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "Ind Slope"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "Ind( )?C50"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "fu inc"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "\u03B3"))
IndModelCheck <- sapply(IndModelCheck, FUN = function(x) which(x == TRUE))
# Note: I can't seem to get regex to work for
# detecting a Greek character; I figured that the
# Hill coefficient gamma is the only time that an
# induction parameter name is only going to be one
# character long.
suppressWarnings(
Out[[paste0(
paste("IndMax", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[1]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("IndSlope", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[2]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("IndC50", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[3]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("Ind_fu_inc", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[4]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("Ind_gamma", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[5]][1]], NameCol + 1])
)
rm(IndModelCheck)
}
# competitive inhibition
Ki <- which(str_detect(InputTab[ThisIntRows, NameCol] %>% pull(),
"Ki "))
if(length(Ki) > 0){
EnzTrans <- as.character(InputTab[i, NameCol])
if(EnzTrans == "Transporter"){
Enzyme <-
paste0(Enzyme, "_",
# setting the tissue
TransporterTissues %>%
filter(Row <= i) %>%
filter(Row == max(Row)) %>%
pull(Tissue))
}
suppressWarnings(
Out[[paste0(
paste("Ki", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[Ki], NameCol + 1])
)
# fu mic or fu inc
IncType <- str_extract(InputTab[ThisIntRows[Ki+1], NameCol] %>%
pull(),
"inc|mic")
suppressWarnings(
Out[[paste0(
paste(switch(IncType,
"inc" = "Ki_fu_inc",
"mic" = "Ki_fu_mic"),
Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[Ki+1], NameCol + 1])
)
rm(IncType, EnzTrans)
}
# MBI
MBI <- which(str_detect(InputTab[ThisIntRows, NameCol] %>% pull(),
"MBI Kapp"))
if(length(MBI) > 0){
suppressWarnings(
Out[[paste0(
paste("MBI_Kapp", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[MBI], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("MBI_kinact", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[MBI+1], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("MBI_fu_mic", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[MBI+2], NameCol + 1])
)
}
rm(Enzyme, NextEmptyCell, NextInt,
ThisIntRows, IndParam1stRow, Ki, MBI)
}
}
rm(Suffix, IntRows, IntRowStart, NameCol)
}
}
## Dealing with StartDayTime_x --------------------------------------
MyInputDeets4 <- MyInputDeets[str_detect(MyInputDeets, "^StartDayTime")]
if(length(MyInputDeets4) > 0){
for(j in MyInputDeets4){
NameCol <- InputDeets_DF$NameCol[which(InputDeets_DF$Detail == j)]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
Row_day <- which(str_detect(InputTab[, NameCol] %>% pull(), "Start Day"))
# If this is not present, which sometimes happens with a custom
# dosing schedule, then will need to pull info from custom
# dosing sheet lower in script.
if(length(Row_day) == 0){
CustomDosing <- c(CustomDosing, TRUE)
} else {
Val_day <- InputTab[Row_day, InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == j)]] %>% pull()
Row_time <- which(str_detect(InputTab[, NameCol] %>% pull(), "Start Time"))
Val_time <- InputTab[Row_time, InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == j)]] %>% pull()
# Dealing with inconsistencies in time format
Val_time <- sub("m", "", Val_time)
Val_time <- str_split(Val_time, pattern = "h")[[1]]
Val_time <- str_c(str_pad(Val_time, width = 2, pad = "0"),
collapse = ":")
Out[[j]] <- paste(paste0("Day ", Val_day),
Val_time, sep = ", ")
}
}
}
## Transport parameters ----------------------------------------------
MyInputDeets5 <- MyInputDeets[str_detect(MyInputDeets, "Transport_")]
MyInputDeets5 <- InputDeets_DF %>%
filter(Detail %in% MyInputDeets5 & complete.cases(NameCol)) %>%
pull(Detail)
if(length(MyInputDeets5) > 0){
for(j in MyInputDeets5){
Suffix <- str_extract(j, "_sub$|_inhib$|_inhib2$|_met1$|_secmet$|_inhib1met$")
NameCol <- InputDeets_DF$NameCol[InputDeets_DF$Detail == j]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
# There can be transporter interactions higher up on the tab,
# but parameters that are actually just transport parameters all
# come after the title "Transport".
StartTrans <- which(InputTab[, NameCol] %>% pull() == "Transport")
if(length(StartTrans) > 0){
TransRows <- which(str_detect(InputTab[ , NameCol] %>% pull(),
"^Transporter"))
TransRows <- TransRows[TransRows > StartTrans]
if(length(TransRows) > 0){
# Sometimes, the organ is only listed once and then not listed
# again for subsequent transporters until it changes.
OrganRows <- which(str_detect(InputTab[, NameCol] %>% pull(),
"Organ/Tissue"))
OrganRows <- OrganRows[OrganRows >= min(TransRows) - 1 &
OrganRows < max(TransRows)]
# BBB transporter parameters are set up differently, so
# removing any organ rows for those scenarios.
BrainRows <- OrganRows + 1
BrainRows <- BrainRows[which(str_detect(
InputTab[BrainRows, NameCol] %>% pull(), "BBB|BCSFB|ISF.ICF"))]
OrganRows <- setdiff(OrganRows, BrainRows - 1)
for(i in TransRows){
# Last row always seems to contain RAF/REF or ISEF,T
TransRowLast <- which(str_detect(InputTab[ , NameCol] %>% pull(),
"RAF/REF|ISEF"))
TransRowLast <- TransRowLast[TransRowLast > i]
TransRowLast <- ifelse(length(TransRowLast) == 0,
nrow(InputTab), TransRowLast[1])
TransRowNames <- InputTab[i:TransRowLast, NameCol] %>% pull(1)
Transporter <- gsub(" |\\(|\\)|-|/", "_", InputTab[i, NameCol + 1])
Transporter <- gsub("_{2,}", "_", Transporter)
Transporter <- sub("_$", "", Transporter)
Transporter <- case_match(Transporter,
"Apical_Efflux_Kidney" ~ "General_Apical_Efflux",
.default = Transporter)
Location <- gsub(" |\\(|\\)|-|/", "",
InputTab[c(i:TransRowLast)[which(TransRowNames == "Location")],
ValueCol] %>% pull(1))
Organ <- InputTab[max(OrganRows[OrganRows < i]), ValueCol] %>%
pull() %>% str_comma() # This should have length 1, but adding str_comma just in case.
# Organ <- which(str_detect(as.character(t(
# InputTab[(i-1):TransRowLast, NameCol])), "Organ/Tissue"))
# Organ <- ifelse(length(Organ) > 0,
# as.character(InputTab[((i-1):TransRowLast)[Organ], ValueCol]),
# "")
ParamPrefix <- paste("Transporter", Organ, Transporter, Location, sep = "_")
# Either CLint,T or Jmax and Km values will be listed
if(any(str_detect(TransRowNames, "CLint,T"))){
suppressWarnings(
Out[[paste0(ParamPrefix, "_CLintT", Suffix)]] <-
as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "CLint,T"))],
ValueCol] %>% pull(1))
)
} else if(any(str_detect(TransRowNames, "Jmax"))){
suppressWarnings(
Out[[paste0(ParamPrefix, "_Jmax", Suffix)]] <-
as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "Jmax"))],
ValueCol] %>% pull(1))
)
suppressWarnings(
Out[[paste0(ParamPrefix, "_Km", Suffix)]] <-
as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "Km"))],
ValueCol] %>% pull(1))
)
}
# Checking for fuinc values b/c they're not always there
fuinc <- as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "fuinc"))],
ValueCol] %>% pull(1))
if(length(fuinc) > 0){
suppressWarnings(
Out[[paste0(ParamPrefix, "_fuinc", Suffix)]] <- fuinc
)
}
rm(fuinc)
# Checking for RAF/REF values b/c they're not always there
RAFREF <- as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "ISEF|RAF|REF"))],
ValueCol] %>% pull(1))
if(length(RAFREF) > 0){
suppressWarnings(
Out[[paste0(ParamPrefix, "_RAFREF", Suffix)]] <- RAFREF
)
}
rm(RAFREF)
rm(TransRowLast, Transporter, TransRowNames, Location,
ParamPrefix)
}
}
}
}
}
Out <- Out[sort(names(Out))]
Out[["pH_dependent_solubility"]] <- pHSol
Out[["DissolutionProfiles"]] <- DissoProfs
Out[["ReleaseProfiles"]] <- ReleaseProfs
Out[["ConcDependent_fup"]] <- CDfupProfs
Out[["ConcDependent_BP"]] <- CDBPProfs
Out[["pH_dependent_solubility"]] <- pHSol
Out[["pH_dependent_LumindalDegradation"]] <- pHLumDeg
# Returning --------------------------------------------------------------
return(Out)
}
shirewoman2/Consultancy documentation built on June 1, 2025, 6:05 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions extractInputTab
Documented in extractInputTab
#' INTERNAL: Extract info from a tab formatted like the main "Input Sheet" tab
#' in Simulator output Excel files
#'
#' @param deets details to extract (the coded name)
#' @param sim_data_file sim_data_file
#' @param sheet what sheet to read
#'
#' @returns list of details from a tab formatted like the main "Input Sheet" tab
#' in Simulator output Excel files
extractInputTab <- function(deets = "all",
sim_data_file,
sheet,
VBE = FALSE,
CustomDosing = FALSE){
if(deets[1] == "all"){
MyInputDeets <- AllExpDetails$Detail[
str_detect(AllExpDetails$DataSource, "Input Sheet")]
} else {
MyInputDeets <- deets
}
InputDeets_DF <- AllExpDetails %>% filter(DataSource == "Input Sheet")
Out <- list()
InputTab <- suppressMessages(tryCatch(
readxl::read_excel(path = sim_data_file, sheet = sheet,
col_names = FALSE),
error = openxlsx::read.xlsx(sim_data_file, sheet = sheet,
colNames = FALSE)))
# If openxlsx read the file, the names are different. Fixing.
if(names(InputTab)[1] == "X1"){
names(InputTab) <- paste0("...", 1:ncol(InputTab))
}
Out[["ExcelResultsTimeStamp"]] <-
timeConv(as.numeric(InputTab[2, 1]), dataSource = "Excel")
# When Inhibitor 1 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Inhibitor 1"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_inhib$|Inhibitor1")]
}
# When Inhibitor 2 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Inhibitor 2"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_inhib2$|Inhibitor2")]
}
# When primary metabolite 1 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Sub Pri Metabolite1"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_met1|PrimaryMetabolite1")]
}
# When primary metabolite 2 is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Sub Pri Metabolite2"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_met2|PrimaryMetabolite2")]
}
# When secondary metabolite is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Sub Sec Metabolite"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_secmet|SecondaryMetabolite")]
}
# When Inhibitor 1 metabolite is not present, don't look for those values.
if(any(str_detect(t(InputTab[5, ]), "Inh 1 Metabolite"), na.rm = T) == FALSE){
MyInputDeets <- MyInputDeets[!str_detect(MyInputDeets, "_inhib1met|Inhibitor1Metabolite")]
}
# We'll select details based on whether this was a Discovery simulation.
Out[["SimulatorUsed"]] <- ifelse(str_detect(InputTab[1, 1], "Discovery"),
"Simcyp Discovery", "Simcyp Simulator")
DiscoveryCol <- switch(Out[["SimulatorUsed"]],
"Simcyp Discovery" = c("Simulator and Discovery",
"Discovery only"),
"Simcyp Simulator" = c("Simulator only",
"Simulator and Discovery"))
# Need to filter to keep only details that we can possibly find based on
# what type of simulator was used
MyInputDeets <- intersect(MyInputDeets,
AllExpDetails$Detail[
AllExpDetails$SimulatorAvailability %in% DiscoveryCol])
InputDeets_DF <- InputDeets_DF %>%
filter(SimulatorAvailability %in% DiscoveryCol)
# Looking for locations of columns.
InputDeets_DF <- InputDeets_DF %>%
mutate(CompoundID = case_when(is.na(CompoundID) ~ "Trial Design",
.default = CompoundID))
if(VBE){
# I don't think there would be more than one compound in a VBE sim, so
# setting the compound ID to "substrate".
InputDeets_DF <- InputDeets_DF %>%
filter(CompoundID %in% c("substrate", "Trial Design"))
}
ColLocations <- c("substrate" = 1,
"Trial Design" = which(t(InputTab[5, ]) == "Trial Design"),
"inhibitor 1" = which(t(InputTab[5, ]) == "Inhibitor 1"),
"inhibitor 2" = which(t(InputTab[5, ]) == "Inhibitor 2"),
"primary metabolite 1" = which(t(InputTab[5, ]) == "Sub Pri Metabolite1"),
"primary metabolite 2" = which(t(InputTab[5, ]) == "Sub Pri Metabolite2"),
"secondary metabolite" = which(t(InputTab[5, ]) == "Sub Sec Metabolite"),
"inhibitor 1 metabolite" = which(t(InputTab[5, ]) == "Inh 1 Metabolite"))
InputDeets_DF <- InputDeets_DF %>%
mutate(NameCol = ColLocations[CompoundID],
ValueCol = NameCol + 1) %>%
# If the NameCol is empty, it's b/c that compound ID or else a column with
# "Trial Design" wasn't found on that tab, so remove any empty NameCol
# rows.
filter(complete.cases(NameCol))
## Main set of parameters -----------------------------------------
# Dealing w/potential replicate values. CompoundType and pKa may be
# replicated but will have the same value, so when we take the unique
# value, that will drop away.
# Checking for any ADAMI parameters. (May need to adapt this later for
# other variations on ADAM models or anything else where there will be
# multiple cells with identical labels.)
ADAMIrow <- which(InputTab$...1 == "ADAMI Parameters")
if(length(ADAMIrow) == 0){
InputDeets_DF <- InputDeets_DF %>%
filter(!str_detect(Detail, "ADAMI"))
ADAMIreps <- NA
NonADAMIreps <- NA
MyInputDeets <- intersect(MyInputDeets, InputDeets_DF$Detail)
} else {
ADAMIreps <- InputDeets_DF %>%
filter(str_detect(Detail, "ADAMI")) %>%
pull(Detail)
NonADAMIreps <- sub("_ADAMI", "", ADAMIreps)
}
# sub function for finding correct cell
pullValue <- function(deet){
# Setting up regex to search
ToDetect <- InputDeets_DF %>%
filter(Detail == deet) %>% pull(Regex_row)
NameCol <- InputDeets_DF$NameCol[which(InputDeets_DF$Detail == deet)]
Row <- which(str_detect(InputTab[, NameCol] %>% pull(), ToDetect)) +
(InputDeets_DF %>% filter(Detail == deet) %>% pull(OffsetRows))
if(length(Row) == 0){
Val <- NA
} else {
if(deet %in% ADAMIreps){Row <- Row[Row > ADAMIrow]}
if(deet %in% NonADAMIreps){Row <- Row[Row < ADAMIrow]}
Val <- InputTab[Row,
InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == deet)]] %>% pull()
# If it's a kp scalar value other than the main one, then we need to
# 1st check whether the value listed is "User" and then get the value
# in the cell right below that if it is.
kpcheck <- str_detect(deet, "kp_scalar_") &
deet %in% paste0("kp_scalar", AllCompounds$Suffix) == FALSE
if(kpcheck){
if(complete.cases(Val) && Val == "Predicted"){
Val <- NA
} else {
NameColBelow <- InputTab[Row + 1,
InputDeets_DF$NameCol[
which(InputDeets_DF$Detail == deet)]] %>% pull()
if(str_detect(tolower(NameColBelow),
tolower(gsub(paste0("kp_scalar_|",
str_c(AllCompounds$Suffix, collapse = "|")),
"",
sub("additional_organ", "Additional Organ", deet))))){
Val <- InputTab[Row + 1, InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == deet)]] %>% pull()
} else {
Val <- NA
}
}
}
}
# If SimStartDayTime is not found, which will happen with animal
# sims, it may be possible to piece together from other data.
if(length(Val) == 0 & deet == "SimStartDayTime"){
StartDay <- as.character(InputTab[which(InputTab$...1 == "Start Day"), 2])
StartTime <- as.character(InputTab[which(InputTab$...1 == "Start Time"), 2])
StartTime <- str_split(sub("m", "", StartTime), "h")[[1]]
Val <-
paste0("Day ", StartDay, ", ",
formatC(as.numeric(StartTime[1]), width = 2, flag = "0"), ":",
formatC(as.numeric(StartTime[2]), width = 2, flag = "0"))
rm(StartDay, StartTime)
}
# Ontogeny profile along w/CompoundType and pKa are often listed twice
# in output for some reason. Only keeping the unique set of values for
# all deets. This will still throw a warning if there is more than one
# value, but we'd want to know that anyway, so that's why I'm not just
# keeping the 1st value listed.
Val <- sort(unique(Val))
# Accounting for when fu,p is scripted
if(length(Val) > 0 &&
(any(complete.cases(Val)) &&
str_detect(deet, "^fu_") & any(str_detect(Val, "script")))){
InputDeets_DF$Class[InputDeets_DF$Detail == deet] <- "character"
assign("InputDeets_DF", InputDeets_DF, envir = parent.frame())
}
suppressWarnings(
Val <- switch(InputDeets_DF$Class[InputDeets_DF$Detail == deet],
"character" = as.character(Val),
"numeric" = as.numeric(Val))
)
if(length(Val) > 1){
Val <- str_comma(Val)
}
# Tidying up some specific idiosyncracies of simulator output
Val <- ifelse(length(Val) == 0 ||
(complete.cases(Val) & Val == "n/a"), NA, Val)
Val <- ifelse(str_detect(deet, "^Unit"),
str_trim(gsub("\\(unbound\\)|\\(blood\\)|\\(unbound blood\\)|Dose \\(|\\)|CMax \\(|TMax \\(|AUC \\(|CL \\(Dose/AUC\\)\\(|\\(blood\\)",
"", Val)), Val)
return(Val)
}
# pullValue doesn't work for CL, so those are separate. Also need
# to do StartDayTime_x, SimulatorVersion, and ADCSimulation separately.
MyInputDeets1 <-
MyInputDeets[!str_detect(MyInputDeets,
"CLint_|Interaction_|^StartDayTime|Transport_|ADCSimulation|SimulatorVersion|OrganTissue")]
if(length(MyInputDeets1) > 0){
for(i in MyInputDeets1){
# print(i)
Out[[i]] <- pullValue(i)
}
}
## Some overall simulation details -----------------------------------
# Checking whether this was an ADC sim.
if("ADCSimulation_sub" %in% MyInputDeets){
Out[["ADCSimulation_sub"]] <-
any(str_detect(as.character(InputTab[, 1]),
InputDeets_DF %>% filter(Detail == "ADCSimulation_sub") %>%
pull(Regex_row)), na.rm = T)
}
# Checking simulator version
Out[["SimulatorVersion"]] <- ifelse(str_detect(InputTab[1, 1], "Discovery"),
as.character(InputTab[1, 1]),
str_extract(as.character(InputTab[3, 1]),
"Version [12][0-9]"))
### Checking on release profiles -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE)){
ReleaseProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
Suffix <- AllCompounds$Suffix[AllCompounds$CompoundID == i]
if(any(str_detect(t(InputTab[, as.numeric(ColLocations[i])]), "Release Mean"),
na.rm = TRUE)){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i]]), "CR/MR Input"))[1] + 1
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]), "Release Mean"))
EndRow <- EndRow[which.max(EndRow)] + 1 # Looking for last "Release Mean" row and then the next row will be the CV for that.
Release_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(Release_temp) <- c("NameCol", "ValCol")
# Older versions of simulator do not have CV. Checking.
ReleaseCV <- Release_temp$ValCol[which(str_detect(Release_temp$NameCol, "CV"))]
if(all(is.null(ReleaseCV))){ReleaseCV <- NA}
suppressWarnings(
ReleaseProfs[[i]] <- data.frame(
CR_MR_input = Out[[paste0("CR_MR_Input", Suffix)]],
Time = Release_temp$ValCol[which(str_detect(Release_temp$NameCol, "Time"))],
Release_mean = Release_temp$ValCol[which(str_detect(Release_temp$NameCol, "Release Mean"))],
Release_CV = ReleaseCV) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
Release_CV = Release_CV / 100, # Making this a fraction instead of a number up to 100
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, Time, Release_mean, Release_CV)
)
rm(StartRow, EndRow, Release_temp)
} else if(
paste0("CR_MR_Input",
AllCompounds$Suffix[AllCompounds$CompoundID == i]) %in%
names(Out) == TRUE &&
complete.cases(Out[[paste0("CR_MR_Input",
AllCompounds$Suffix[AllCompounds$CompoundID == i])]]) &&
Out[[paste0("CR_MR_Input",
AllCompounds$Suffix[AllCompounds$CompoundID == i])]] ==
"Weibull"){
Suffix <- AllCompounds$Suffix[AllCompounds$CompoundID == i]
ReleaseProfs <- data.frame(
CR_MR_input = Out[[paste0("CR_MR_Input", Suffix)]],
Parameter = c("Fmax", "alpha", "beta", "lag"),
Value = c(Out[[paste0("ReleaseProfile_Fmax", Suffix)]],
Out[[paste0("ReleaseProfile_alpha", Suffix)]],
Out[[paste0("ReleaseProfile_beta", Suffix)]],
Out[[paste0("ReleaseProfile_lag", Suffix)]]),
CV = c(Out[[paste0("ReleaseProfile_Fmax_CV", Suffix)]],
Out[[paste0("ReleaseProfile_alpha_CV", Suffix)]],
Out[[paste0("ReleaseProfile_beta_CV", Suffix)]],
Out[[paste0("ReleaseProfile_lag_CV", Suffix)]])) %>%
mutate(CV = CV / 100, # Making this a fraction instead of a number up to 100
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, CR_MR_input, Parameter, Value, CV)
} else {
ReleaseProfs <- NULL
}
}
ReleaseProfs <- bind_rows(ReleaseProfs)
if(nrow(ReleaseProfs) == 0){ReleaseProfs <- NULL}
} else {
ReleaseProfs <- NULL
}
### Checking on dissolution profiles ------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations])), "Dissolution( Mean)? \\(\\%"),
na.rm = TRUE)){
DissoProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
# There may be more than one tissue. Checking for this.
DissoTissueRows <- which(str_detect(t(InputTab[, ColLocations[i]]),
"^Dissolution Profile"))
# If the results do not specify any tissues, then start rows will be
# different. Last row will be the same, though.
LastRow <- which(str_detect(t(InputTab[, ColLocations[i]]), "Dissolution( Mean)? \\(\\%"))
LastRow <- LastRow[which.max(LastRow)] + 1 # Looking for last "Dissolution (%)" row and then the next row will be the CV for that.
if(length(DissoTissueRows) > 0){
StartRows <- which(str_detect(t(InputTab[, ColLocations[i]]), "^Dissolution Profile")) + 1
# It could be that one compound has dissolution profiles and another
# compound does not. Checking that here since I did not check it in
# the original "if" statement at the top of this section.
if(all(is.na(StartRows))){
next
}
if(length(StartRows) > 1){
EndRows <- c(StartRows[2:length(StartRows)], NA) - 2
EndRows[length(StartRows)] <- LastRow
} else {
EndRows <- LastRow
}
DissoTissues <- gsub("\\(|\\)", "",
str_extract(
t(InputTab[, ColLocations[i]])[DissoTissueRows],
"\\(.*\\)"))
} else {
# If the tissue is not specified, then there will be only 1 set of values.
StartRows <- which(str_detect(t(InputTab[, ColLocations[i]]), "Dissolution( Mean)? \\(\\%"))[1] - 1
DissoTissues <- "not specified"
EndRows <- LastRow
# It could be that one compound has dissolution profiles and another
# compound does not. Checking that here since I did not check it in
# the original "if" statement at the top of this section.
if(all(is.na(StartRows))){
next
}
}
DissoProfs[[i]] <- list()
for(tiss in 1:length(StartRows)){
Disso_temp <- InputTab[StartRows[tiss]:EndRows[tiss],
ColLocations[i]:(ColLocations[i]+1)]
names(Disso_temp) <- c("NameCol", "ValCol")
# Older versions of simulator do not have CV. Checking.
DissoCV <- Disso_temp$ValCol[which(str_detect(Disso_temp$NameCol, "CV"))]
if(all(is.null(DissoCV))){DissoCV <- NA}
suppressWarnings(
DissoProfs[[i]][[tiss]] <-
data.frame(
Time = Disso_temp$ValCol[which(str_detect(Disso_temp$NameCol, "Time"))],
Dissolution_mean = Disso_temp$ValCol[which(str_detect(Disso_temp$NameCol, "Dissolution( Mean)? \\(\\%"))],
Dissolution_CV = DissoCV) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
Dissolution_CV = Dissolution_CV / 100, # Making this a fraction instead of a number up to 100
File = sim_data_file,
Tissue = DissoTissues[[tiss]],
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]]))
)
rm(Disso_temp, DissoCV)
}
DissoProfs[[i]] <- bind_rows(DissoProfs[[i]])
}
DissoProfs <- bind_rows(DissoProfs) %>%
select(File, Tissue, CompoundID, Compound, Time,
Dissolution_mean, Dissolution_CV)
} else {
DissoProfs <- NULL
}
### Concentration-dependent fu -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations + 1])),
"Concentration-dependent fu profile"),
na.rm = TRUE)){
CDfupProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i] + 1]),
"Concentration-dependent fu profile"))[1] + 2
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"fu [0-9]"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has conc-dependent fu,p profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(is.na(StartRow)){
next
}
CDfup_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(CDfup_temp) <- c("NameCol", "ValCol")
CDfupProfs[[i]] <- data.frame(
Conc = CDfup_temp$ValCol[which(str_detect(CDfup_temp$NameCol, "Conc"))],
fup = CDfup_temp$ValCol[which(str_detect(CDfup_temp$NameCol, "fu [0-9]"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, Conc, fup)
rm(StartRow, EndRow, CDfup_temp)
}
CDfupProfs <- bind_rows(CDfupProfs)
} else {
CDfupProfs <- NULL
}
### Concentration-dependent B/P -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations + 1])),
"Concentration-dependent B/P profile"),
na.rm = TRUE)){
CDBPProfs <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i] + 1]),
"Concentration-dependent B/P profile"))[1] + 2
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"B/P [0-9]"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has conc-dependent B/P profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(is.na(StartRow)){
next
}
CDBP_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(CDBP_temp) <- c("NameCol", "ValCol")
CDBPProfs[[i]] <- data.frame(
Conc = CDBP_temp$ValCol[which(str_detect(CDBP_temp$NameCol, "Conc"))],
BP = CDBP_temp$ValCol[which(str_detect(CDBP_temp$NameCol, "B/P [0-9]"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, Conc, BP)
rm(StartRow, EndRow, CDBP_temp)
}
CDBPProfs <- bind_rows(CDBPProfs)
} else {
CDBPProfs <- NULL
}
### pH-dependent luminal degradation -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations])),
"Degradation rate constant"), na.rm = TRUE)){
pHLumDeg <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"Degradation rate constant"))[1] - 1
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"Degradation rate constant [0-9]{1,} 1.h"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has pH-dependent fu,p profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(length(StartRow) == 0 || is.na(StartRow)){
next
}
pHLumDeg_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(pHLumDeg_temp) <- c("NameCol", "ValCol")
pHLumDeg[[i]] <- data.frame(
pH = pHLumDeg_temp$ValCol[which(str_detect(pHLumDeg_temp$NameCol, "pH"))],
DegradationRateConstant = pHLumDeg_temp$ValCol[which(str_detect(pHLumDeg_temp$NameCol, "Degradation rate constant [0-9]{1,} 1.h"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, pH, DegradationRateConstant)
rm(StartRow, EndRow, pHLumDeg_temp)
}
pHLumDeg <- bind_rows(pHLumDeg)
} else {
pHLumDeg <- NULL
}
### pH-dependent solubility -----------------------------------------
if(Out[["SimulatorUsed"]] != "Simcyp Discovery" &&
exists("InputTab", inherits = FALSE) &&
any(str_detect(unlist(c(InputTab[, ColLocations + 1])),
"Solubility-pH profile|User defined pH-Solubility"),
na.rm = TRUE)){
pHSol <- list()
for(i in names(ColLocations)[!names(ColLocations) == "Trial Design"]){
StartRow <- which(str_detect(t(InputTab[, ColLocations[i] + 1]),
"Solubility-pH profile|User defined pH-Solubility"))[1] + 1
EndRow <- which(str_detect(t(InputTab[, ColLocations[i]]),
"Entry [0-9]{1,} Solubility"))
EndRow <- EndRow[which.max(EndRow)]
# It could be that one compound has pH-dependent fu,p profiles and
# another compound does not. Checking that here since I did not check it
# in the original if statement at the top of this section.
if(is.na(StartRow)){
next
}
pHSol_temp <- InputTab[StartRow:EndRow, ColLocations[i]:(ColLocations[i]+1)]
names(pHSol_temp) <- c("NameCol", "ValCol")
pHSol[[i]] <- data.frame(
pH = pHSol_temp$ValCol[which(str_detect(pHSol_temp$NameCol, "pH"))],
Solubility = pHSol_temp$ValCol[which(str_detect(pHSol_temp$NameCol, "Entry [0-9]{1,} Solubility"))]) %>%
mutate(across(.cols = everything(), .fns = as.numeric),
File = sim_data_file,
CompoundID = i,
Compound = as.character(Out[AllCompounds$DetailNames[
AllCompounds$CompoundID == i]])) %>%
select(File, CompoundID, Compound, pH, Solubility)
rm(StartRow, EndRow, pHSol_temp)
}
pHSol <- bind_rows(pHSol)
} else {
pHSol <- NULL
}
## Pulling CL info ----------------------------------------------------
MyInputDeets2 <- MyInputDeets[str_detect(MyInputDeets, "CLint_")]
if(length(MyInputDeets2) > 0){
for(j in MyInputDeets2){
Suffix <- str_extract(j, "_sub$|_inhib$|_inhib2$|_met1$|_met2$|_secmet$|_inhib1met$")
NameCol <- InputDeets_DF$NameCol[InputDeets_DF$Detail == j]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
CLRows <- which(
InputTab[ , NameCol] == "Enzyme" |
str_detect(InputTab[ , NameCol] %>%
pull(),
"^Biliary (CLint|Clearance)") |
str_detect(InputTab[ , NameCol] %>%
pull(),
"^Additional HLM CLint|^Additional Systemic Clearance|^Additional HKM CLint") |
str_detect(InputTab[ , ValueCol] %>%
pull(),
"In Vivo Clear") |
str_detect(InputTab[ , NameCol] %>%
pull(),
"(Liver|Intestine|Biliary) Clearance"))
CLRows <- CLRows[complete.cases(InputTab[CLRows + 1, NameCol])]
if(Out[["SimulatorUsed"]] == "Simcyp Discovery"){
# Discovery sims have a slightly different setup on the Input
# Sheet and only the 1st CLRows value should be used b/c that
# section will contain all the info we need.
CLRows <- CLRows[1]
MyNames <- as.character(t(
InputTab[CLRows:nrow(InputTab), NameCol]))
DiscoveryDeets <-
data.frame(
Detail = c("CLiv_InVivoCL",
"CLpo_InVivoCL",
"CLint_biliary",
"CLint_biliary_fuinc",
"CLrenal",
"CL_AddSystemic",
"CL_PercentAvailReabsorption"),
RegexRow = c("CL.*iv.*[(]mL",
"CL.*po.*[(]mL",
"Biliary Clearance ..L/min",
"Biliary fu inc",
"CL R .mL",
"^Additional Systemic Clearance",
"^Percent.*re-absorption"))
for(i in 1:nrow(DiscoveryDeets)){
MyRow <- which(str_detect(MyNames, DiscoveryDeets$RegexRow[i]))
if(length(MyRow) == 0){
Out[[paste0(DiscoveryDeets$Detail[i], Suffix)]] <- NA
} else {
suppressWarnings(
Out[[paste0(DiscoveryDeets$Detail[i], Suffix)]] <-
as.numeric(InputTab[MyRow + CLRows - 1, ValueCol])
)
}
rm(MyRow)
}
# Liver and intestinal CL
LivOrInt <- c("Liver", "Intestine")[
c(any(str_detect(MyNames, "Liver")), any(str_detect(MyNames, "Intestine")))]
LivIndCL <-
data.frame(
Detail = c("CL_XXX_Type",
"CL_XXX__UseSaturableKinetics",
"CLint_XXX",
"CL_Km_XXX",
"CL_Vmax_XXX",
"CL_XXX_fuinc",
"CL_XXX_UseMetabolite",
"CL_XXX_MetabPerc",
"CL_XXX_ScrapingsCorrectionFactor",
"CL_XXX_ElutionCorrectionFactor"),
RegexRow = c(paste(i, "Clearance Type"),
"Use Saturable Kinetics",
"CLint",
"Km \\(",
"Vmax \\(",
"fu inc",
"Use Metabolite",
"Metabolite .%",
"\\(scrapings\\) Correction Factor",
"\\(elution\\) Correction Factor")
)
if(length(LivOrInt[complete.cases(LivOrInt)]) > 0){
for(i in LivOrInt[complete.cases(LivOrInt)]){
OrganRows <- range(
which(str_detect(MyNames, i) |
str_detect(MyNames,
paste0(str_sub(i, 1, 1), "M")))
)
for(k in 1:nrow(LivIndCL)){
MyRow <- which(str_detect(MyNames[OrganRows[1]:OrganRows[2]],
LivIndCL$RegexRow[k]))
if(length(MyRow) == 0){
Out[[paste0(sub("XXX", i, LivIndCL$Detail[k]), Suffix)]] <- NA
} else {
suppressWarnings(
Out[[paste0(sub("XXX", i, LivIndCL$Detail[k]), Suffix)]] <-
as.character(InputTab[MyRow + CLRows - 1, ValueCol])
)
}
rm(MyRow)
}
}
}
} else {
# Regular Simulator data extraction starts here.
# Checking for interaction data
IntRowStart <- which(str_detect(InputTab[, NameCol] %>%
pull(), "Ind max|^Ki |^MBI|Interaction"))[1] - 1
if(complete.cases(IntRowStart)){
CLRows <- CLRows[CLRows < min(IntRowStart)]
}
for(i in CLRows){
# CL for a specific enzyme
if(str_detect(as.character(InputTab[i, NameCol]), "Enzyme")){
LastRow_i <- which(is.na(InputTab[, NameCol]))
LastRow_i <- LastRow_i[LastRow_i > i][1] - 1
Enzyme <- gsub(" ", "", InputTab[i, NameCol + 1])
Pathway <- gsub(" |-", "", InputTab[i - 1, NameCol + 1])
if(as.character(InputTab[i+1, NameCol]) == "Genotype"){
Genotype <- InputTab[i+1, NameCol + 1]
Genotype <- gsub("\\*", "star", Genotype)
Genotype <- gsub("/", "", Genotype)
Enzyme <- paste0(Enzyme, "_", Genotype)
CLrow <- i + 2
} else if((str_detect(Enzyme, "User") &
!str_detect(InputTab[i+1, NameCol], "CLint|Vmax")) |
str_detect(tolower(InputTab[i + 1, NameCol]),
"ontogeny")){
CLrow <- i + 2
} else {
CLrow <- i + 1
}
CLType <- str_extract(InputTab[CLrow, NameCol],
"CLint|Vmax|t1/2|Ind max")
if(CLType == "CLint"){
# NOTE TO CODERS: I'd been including units for CLint in
# the past, but I realized that I hadn't included units
# for other enzymes, so I decided later to omit them.
# Keeping this bit of code, albeit commented out, so
# that we can add them back easily if we want.
# Units <- str_extract(InputTab[CLrow, NameCol],
# "\\(.*\\)")
# Units <- gsub("\\(|\\)", "", Units)
# Units <- gsub("/| ", "_", Units)
# # Dealing with mu since it's causing some problems
# # downstream when a symbol
# Units <- gsub(rlang::chr_unserialise_unicode("<U+00B5>"),
# "u", Units)
suppressWarnings(
Out[[paste0(
paste("CLint", Enzyme, Pathway, # Units,
sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow, NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("fu_mic", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow+1, NameCol + 1])
)
# Check for any UGT-specific CL parameters
if(str_detect(Enzyme, "UGT") &
any(str_detect(t(InputTab[i:LastRow_i, NameCol]),
"rUGT"))){
rUGTSysInfo <- InputTab[i:LastRow_i, c(NameCol, ValueCol)] %>%
rename(Name = 1, Value = 2) %>%
filter(str_detect(Name, "rUGT"))
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTSystem",
Suffix)]] <-
rUGTSysInfo[which(str_detect(rUGTSysInfo$Name,
"rUGTSystem")), ] %>%
pull(Value)
suppressWarnings(
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTScalar_liver",
Suffix)]] <-
rUGTSysInfo[which(
str_detect(tolower(rUGTSysInfo$Name),
"rugtscalar.*liver")), ] %>%
pull(Value) %>% as.numeric())
suppressWarnings(
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTScalar_intestine",
Suffix)]] <-
rUGTSysInfo[which(
str_detect(tolower(rUGTSysInfo$Name),
"rugtscalar.*intestine")), ] %>%
pull(Value) %>% as.numeric())
suppressWarnings(
Out[[paste0("CLint_", Enzyme, "_", Pathway, "_rUGTScalar_kidney",
Suffix)]] <-
rUGTSysInfo[which(
str_detect(tolower(rUGTSysInfo$Name),
"rugtscalar.*kidney")), ] %>%
pull(Value) %>% as.numeric())
rm(rUGTSysInfo)
}
rm(Enzyme, Pathway, CLType)
next
}
if(CLType == "Vmax"){
suppressWarnings(
Out[[paste0(
paste("Vmax", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow, NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("Km", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow+1, NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("fu_mic", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow+2, NameCol + 1])
)
rm(Enzyme, Pathway, CLType)
next
}
if(CLType == "t1/2"){
suppressWarnings(
Out[[paste0(
paste("HalfLife", Enzyme,
Pathway, sep = "_"),
Suffix)]] <-
as.numeric(InputTab[CLrow, NameCol + 1])
)
rm(Enzyme, Pathway, CLType)
next
}
}
# Biliary CL
if(str_detect(as.character(InputTab[i, NameCol]), "^Biliary (CLint|Clearance)")){
suppressWarnings(
Out[[paste0("CLint_biliary", Suffix)]] <-
as.numeric(InputTab[i, NameCol + 1])
)
}
# Other HLM CL
if(str_detect(as.character(InputTab[i, NameCol]), "^Additional HLM CLint")){
suppressWarnings(
Out[[paste0("CLint_AddHLM", Suffix)]] <-
as.numeric(InputTab[i, NameCol + 1])
)
}
# Other HKM CL
if(str_detect(as.character(InputTab[i, NameCol]), "^Additional HKM CLint")){
suppressWarnings(
Out[[paste0("CLint_AddHKM", Suffix)]] <-
as.numeric(InputTab[i, NameCol + 1])
)
}
# in vivo CL
if(str_detect(as.character(InputTab[i, ValueCol]),
"In Vivo Clearance")){
MyNames <- as.character(t(
InputTab[i:min(
c(IntRowStart, CLRows[which(CLRows == i) + 1] - 1,
nrow(InputTab)), na.rm = T), NameCol]))
suppressWarnings(
Out[[paste0("CLiv_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"CL.*iv.*[(](m)?L")) + i - 1,
ValueCol])
)
suppressWarnings(
Out[[paste0("CLbiliary_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"Biliary Clearance")) + i - 1,
ValueCol])
)
suppressWarnings(
Out[[paste0("CLadditional_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"Additional Systemic Clearance")) + i - 1,
ValueCol])
)
suppressWarnings(
Out[[paste0("CLpo_InVivoCL", Suffix)]] <-
as.numeric(InputTab[
which(str_detect(MyNames,
"^CL .po.")) + i - 1,
ValueCol])
)
}
}
rm(CLRows, IntRowStart, NameCol, Suffix)
}
}
}
## Pulling interaction info -------------------------------------------
MyInputDeets3 <- MyInputDeets[str_detect(MyInputDeets, "Interaction_")]
if(length(MyInputDeets3) > 0){
for(j in MyInputDeets3){
Suffix <- str_extract(j, "_sub$|_inhib$|_inhib2$|_met1$|_secmet$|_inhib1met$")
NameCol <- InputDeets_DF$NameCol[InputDeets_DF$Detail == j]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
IntRows <- which(str_detect(InputTab[ , NameCol] %>% pull(),
"^Enzyme$|^Transporter$"))
IntRows <- IntRows[complete.cases(InputTab[IntRows + 1, NameCol])]
# Only IntRows after the first instance of an
# interaction type of term is found in NameCol. NB: I
# thought it would work to just look for cells after
# "interaction", but "interaction" hasn't always been
# listed in the output files I've found.
IntRowStart <- which(str_detect(InputTab[, NameCol] %>%
pull(), "Ind [mM]ax|Ind [sS]lope|^Ki |^MBI"))[1] - 1
TransporterTissues <- IntRows[which(
str_detect(t(InputTab[IntRows, NameCol]), "Transporter"))]
TransporterTissues <- TransporterTissues[which(
str_detect(t(InputTab[TransporterTissues - 1, NameCol]),
"Organ/Tissue"))] - 1
TransporterTissues <- data.frame(
Row = TransporterTissues,
Tissue = as.character(t(InputTab[TransporterTissues, ValueCol])))
if(complete.cases(IntRowStart)){
IntRows <- IntRows[IntRows >= IntRowStart]
for(i in IntRows){
Enzyme <- gsub(" |\\(|\\)|-|/", "_", InputTab[i, NameCol + 1])
Enzyme <- gsub("_{2,}", "_", Enzyme)
Enzyme <- sub("_$", "", Enzyme)
NextEmptyCell <- which(is.na(InputTab[, NameCol + 1]))
NextEmptyCell <- NextEmptyCell[NextEmptyCell > i][1]
# If there's another interaction listed
# before the next empty cell, need to
# account for that.
NextInt <- IntRows[which(IntRows == i) + 1] - 1
NextInt <- ifelse(i == IntRows[length(IntRows)],
nrow(InputTab), NextInt)
ThisIntRows <- i:(c(NextEmptyCell, NextInt)[which.min(c(NextEmptyCell, NextInt))])
ThisIntRows <- setdiff(ThisIntRows, NextEmptyCell)
# Induction
IndParam1stRow <- which(str_detect(InputTab[ThisIntRows, NameCol] %>% pull(),
"Ind max|Ind Slope"))
if(length(IndParam1stRow) > 0){
IndModelCheck <- list(str_detect(t(InputTab[ThisIntRows, NameCol]), "Ind max"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "Ind Slope"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "Ind( )?C50"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "fu inc"),
str_detect(t(InputTab[ThisIntRows, NameCol]), "\u03B3"))
IndModelCheck <- sapply(IndModelCheck, FUN = function(x) which(x == TRUE))
# Note: I can't seem to get regex to work for
# detecting a Greek character; I figured that the
# Hill coefficient gamma is the only time that an
# induction parameter name is only going to be one
# character long.
suppressWarnings(
Out[[paste0(
paste("IndMax", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[1]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("IndSlope", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[2]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("IndC50", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[3]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("Ind_fu_inc", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[4]][1]], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("Ind_gamma", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[IndModelCheck[[5]][1]], NameCol + 1])
)
rm(IndModelCheck)
}
# competitive inhibition
Ki <- which(str_detect(InputTab[ThisIntRows, NameCol] %>% pull(),
"Ki "))
if(length(Ki) > 0){
EnzTrans <- as.character(InputTab[i, NameCol])
if(EnzTrans == "Transporter"){
Enzyme <-
paste0(Enzyme, "_",
# setting the tissue
TransporterTissues %>%
filter(Row <= i) %>%
filter(Row == max(Row)) %>%
pull(Tissue))
}
suppressWarnings(
Out[[paste0(
paste("Ki", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[Ki], NameCol + 1])
)
# fu mic or fu inc
IncType <- str_extract(InputTab[ThisIntRows[Ki+1], NameCol] %>%
pull(),
"inc|mic")
suppressWarnings(
Out[[paste0(
paste(switch(IncType,
"inc" = "Ki_fu_inc",
"mic" = "Ki_fu_mic"),
Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[Ki+1], NameCol + 1])
)
rm(IncType, EnzTrans)
}
# MBI
MBI <- which(str_detect(InputTab[ThisIntRows, NameCol] %>% pull(),
"MBI Kapp"))
if(length(MBI) > 0){
suppressWarnings(
Out[[paste0(
paste("MBI_Kapp", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[MBI], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("MBI_kinact", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[MBI+1], NameCol + 1])
)
suppressWarnings(
Out[[paste0(
paste("MBI_fu_mic", Enzyme,
sep = "_"), Suffix)]] <-
as.numeric(InputTab[ThisIntRows[MBI+2], NameCol + 1])
)
}
rm(Enzyme, NextEmptyCell, NextInt,
ThisIntRows, IndParam1stRow, Ki, MBI)
}
}
rm(Suffix, IntRows, IntRowStart, NameCol)
}
}
## Dealing with StartDayTime_x --------------------------------------
MyInputDeets4 <- MyInputDeets[str_detect(MyInputDeets, "^StartDayTime")]
if(length(MyInputDeets4) > 0){
for(j in MyInputDeets4){
NameCol <- InputDeets_DF$NameCol[which(InputDeets_DF$Detail == j)]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
Row_day <- which(str_detect(InputTab[, NameCol] %>% pull(), "Start Day"))
# If this is not present, which sometimes happens with a custom
# dosing schedule, then will need to pull info from custom
# dosing sheet lower in script.
if(length(Row_day) == 0){
CustomDosing <- c(CustomDosing, TRUE)
} else {
Val_day <- InputTab[Row_day, InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == j)]] %>% pull()
Row_time <- which(str_detect(InputTab[, NameCol] %>% pull(), "Start Time"))
Val_time <- InputTab[Row_time, InputDeets_DF$ValueCol[
which(InputDeets_DF$Detail == j)]] %>% pull()
# Dealing with inconsistencies in time format
Val_time <- sub("m", "", Val_time)
Val_time <- str_split(Val_time, pattern = "h")[[1]]
Val_time <- str_c(str_pad(Val_time, width = 2, pad = "0"),
collapse = ":")
Out[[j]] <- paste(paste0("Day ", Val_day),
Val_time, sep = ", ")
}
}
}
## Transport parameters ----------------------------------------------
MyInputDeets5 <- MyInputDeets[str_detect(MyInputDeets, "Transport_")]
MyInputDeets5 <- InputDeets_DF %>%
filter(Detail %in% MyInputDeets5 & complete.cases(NameCol)) %>%
pull(Detail)
if(length(MyInputDeets5) > 0){
for(j in MyInputDeets5){
Suffix <- str_extract(j, "_sub$|_inhib$|_inhib2$|_met1$|_secmet$|_inhib1met$")
NameCol <- InputDeets_DF$NameCol[InputDeets_DF$Detail == j]
ValueCol <- InputDeets_DF$ValueCol[InputDeets_DF$Detail == j]
# There can be transporter interactions higher up on the tab,
# but parameters that are actually just transport parameters all
# come after the title "Transport".
StartTrans <- which(InputTab[, NameCol] %>% pull() == "Transport")
if(length(StartTrans) > 0){
TransRows <- which(str_detect(InputTab[ , NameCol] %>% pull(),
"^Transporter"))
TransRows <- TransRows[TransRows > StartTrans]
if(length(TransRows) > 0){
# Sometimes, the organ is only listed once and then not listed
# again for subsequent transporters until it changes.
OrganRows <- which(str_detect(InputTab[, NameCol] %>% pull(),
"Organ/Tissue"))
OrganRows <- OrganRows[OrganRows >= min(TransRows) - 1 &
OrganRows < max(TransRows)]
# BBB transporter parameters are set up differently, so
# removing any organ rows for those scenarios.
BrainRows <- OrganRows + 1
BrainRows <- BrainRows[which(str_detect(
InputTab[BrainRows, NameCol] %>% pull(), "BBB|BCSFB|ISF.ICF"))]
OrganRows <- setdiff(OrganRows, BrainRows - 1)
for(i in TransRows){
# Last row always seems to contain RAF/REF or ISEF,T
TransRowLast <- which(str_detect(InputTab[ , NameCol] %>% pull(),
"RAF/REF|ISEF"))
TransRowLast <- TransRowLast[TransRowLast > i]
TransRowLast <- ifelse(length(TransRowLast) == 0,
nrow(InputTab), TransRowLast[1])
TransRowNames <- InputTab[i:TransRowLast, NameCol] %>% pull(1)
Transporter <- gsub(" |\\(|\\)|-|/", "_", InputTab[i, NameCol + 1])
Transporter <- gsub("_{2,}", "_", Transporter)
Transporter <- sub("_$", "", Transporter)
Transporter <- case_match(Transporter,
"Apical_Efflux_Kidney" ~ "General_Apical_Efflux",
.default = Transporter)
Location <- gsub(" |\\(|\\)|-|/", "",
InputTab[c(i:TransRowLast)[which(TransRowNames == "Location")],
ValueCol] %>% pull(1))
Organ <- InputTab[max(OrganRows[OrganRows < i]), ValueCol] %>%
pull() %>% str_comma() # This should have length 1, but adding str_comma just in case.
# Organ <- which(str_detect(as.character(t(
# InputTab[(i-1):TransRowLast, NameCol])), "Organ/Tissue"))
# Organ <- ifelse(length(Organ) > 0,
# as.character(InputTab[((i-1):TransRowLast)[Organ], ValueCol]),
# "")
ParamPrefix <- paste("Transporter", Organ, Transporter, Location, sep = "_")
# Either CLint,T or Jmax and Km values will be listed
if(any(str_detect(TransRowNames, "CLint,T"))){
suppressWarnings(
Out[[paste0(ParamPrefix, "_CLintT", Suffix)]] <-
as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "CLint,T"))],
ValueCol] %>% pull(1))
)
} else if(any(str_detect(TransRowNames, "Jmax"))){
suppressWarnings(
Out[[paste0(ParamPrefix, "_Jmax", Suffix)]] <-
as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "Jmax"))],
ValueCol] %>% pull(1))
)
suppressWarnings(
Out[[paste0(ParamPrefix, "_Km", Suffix)]] <-
as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "Km"))],
ValueCol] %>% pull(1))
)
}
# Checking for fuinc values b/c they're not always there
fuinc <- as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "fuinc"))],
ValueCol] %>% pull(1))
if(length(fuinc) > 0){
suppressWarnings(
Out[[paste0(ParamPrefix, "_fuinc", Suffix)]] <- fuinc
)
}
rm(fuinc)
# Checking for RAF/REF values b/c they're not always there
RAFREF <- as.numeric(
InputTab[c(i:TransRowLast)[which(str_detect(TransRowNames, "ISEF|RAF|REF"))],
ValueCol] %>% pull(1))
if(length(RAFREF) > 0){
suppressWarnings(
Out[[paste0(ParamPrefix, "_RAFREF", Suffix)]] <- RAFREF
)
}
rm(RAFREF)
rm(TransRowLast, Transporter, TransRowNames, Location,
ParamPrefix)
}
}
}
}
}
Out <- Out[sort(names(Out))]
Out[["pH_dependent_solubility"]] <- pHSol
Out[["DissolutionProfiles"]] <- DissoProfs
Out[["ReleaseProfiles"]] <- ReleaseProfs
Out[["ConcDependent_fup"]] <- CDfupProfs
Out[["ConcDependent_BP"]] <- CDBPProfs
Out[["pH_dependent_solubility"]] <- pHSol
Out[["pH_dependent_LumindalDegradation"]] <- pHLumDeg
# Returning --------------------------------------------------------------
return(Out)
}
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