updated R sources

R/ConcTime.R

@@ -26,3 +26,45 @@ ConcTime <- function(Weight, Dose, N = 20){
         select(Subject, Time, Conc)
     return(ggConc)
 }
+
+
+#' Create a dataset of the concentration-time curve of multiple dosing
+#'
+#' \code{ConcTimeMulti} will create a dataset of the concentration-time curve of multiple dosing
+#' 
+#' @param Weight Body weight (kg)
+#' @param Dose Dose of single caffeine (mg)
+#' @param N The number of simulated subjects
+#' @param Tau The interval of multiple dosing (hour)
+#' @param Repeat The number of dosing
+#' @return The dataset of concentration and time of simulated subjects of multiple dosing
+#' @export
+#' @examples 
+#' ConcTimeMulti(Weight = 20, Dose = 200, N = 20, Tau = 8, Repeat = 4)
+#' ConcTimeMulti(20, 200)
+#' @seealso \url{http://asancpt.github.io/CaffeineEdison}
+#' @import dplyr
+
+ConcTimeMulti <- function(Weight, Dose, N = 20, Tau = 8, Repeat = 4){
+    Subject <- seq(1, N, length.out = N) # 
+    Time <- seq(0, 96, length.out = 481) # 
+    Grid <- expand.grid(x = Subject, y = Time) %>% select(Subject=x, Time=y)
+
+    ggsuper <- Dataset(Weight, Dose, N) %>% select(CL, V, Ka, Ke) %>% 
+        mutate(Subject = row_number()) %>% 
+        left_join(Grid, by = "Subject") %>% 
+        mutate(Conc = Dose / V * Ka / (Ka - Ke) * (exp(-Ke * Time) - exp(-Ka * Time))) %>% 
+        group_by(Subject) %>% 
+        mutate(ConcOrig = Conc, 
+               ConcTemp = 0)
+    ## Superposition
+    for (i in 1:Repeat){
+        Frame <- Tau * 5 * i
+        ggsuper <- ggsuper %>% 
+            mutate(Conc = Conc + ConcTemp) %>% 
+            mutate(ConcTemp = lag(ConcOrig, n = Frame, default = 0))
+    }
+
+    ggsuper <- ggsuper %>% select(Subject, Time, Conc)
+    return(ggsuper)
+}

R/Dataset.R

@@ -28,3 +28,44 @@ Dataset <- function(Weight, Dose, N = 20){
            Half_life = 0.693 / Ke) %>% select(Tmax, Cmax, AUC, Half_life, CL, V, Ka, Ke)
   return(MVNdata)
 }
+
+#' Create a dataset for simulation of multiple dose of caffeine 
+#'
+#' \code{DatasetMulti} will create a dataset for simulation of multiple dose of caffeine 
+#'
+#' @param Weight Body weight (kg)
+#' @param Dose Dose of multiple caffeine (mg)
+#' @param N The number of simulated subjects
+#' @param Tau The interval of multiple dosing (hour)
+#' @return The dataset of pharmacokinetic parameters of subjects after multiple caffeine dose following multivariate normal
+#' @export
+#' @examples 
+#' DatasetMulti(Weight = 20, Dose = 200, N = 20, Tau = 8)
+#' DatasetMulti(20,500)
+#' @seealso \url{http://asancpt.github.io/CaffeineEdison}
+#' @importFrom mgcv rmvn
+#' @import dplyr
+
+DatasetMulti <- function(Weight, Dose, N = 20, Tau = 24){
+    #set.seed(20140523+1)
+    MVN <- rmvn(N, CaffMu, CaffSigma);  
+    MVNdata <- data.frame(MVN, stringsAsFactors = FALSE) %>% 
+        select(eta1 = X1, eta2 = X2, eta3 = X3) %>% 
+        mutate(CL = 0.09792 * Weight * exp(eta1), # L/hr
+               V  = 0.7219 * Weight * exp(eta2), # L, TVV =THETA[2] * (1 + ABST*THETA[7]) [1] 0.7218775
+               Ka = 4.268 * exp(eta3), # /hr
+               Ke = CL / V,
+               Half_life = 0.693 / Ke,
+               Tmax = (log(Ka) - log(Ke)) / (Ka - Ke),
+               Cmax = Dose / V * Ka / (Ka - Ke) * (exp(-Ke * Tmax) - exp(-Ka * Tmax)),
+               AUC  = Dose / CL
+               ) %>%  
+        mutate(AI = 1/(1-exp(-1*Ke*Tau)),
+               Aavss = 1.44 * Dose * Half_life / Tau,
+               Cavss = Dose / (CL * Tau), 
+               Cminss = Dose * exp(-Ke * Tau) / (V * (1 - exp(-Ke * Tau))),
+               Cmaxss = Dose / (V * (1 - exp(-Ke * Tau)))) %>% 
+        select(TmaxS = Tmax, CmaxS = Cmax, AUCS = AUC, AI, Aavss, Cavss, Cmaxss, Cminss)
+    return(MVNdata)
+}
+

R/Plot.R

@@ -27,3 +27,32 @@ Plot <- function(ConcTime, log = FALSE){
     if (log == TRUE) p <- p + scale_y_log10() #limits = c(0.1, max(80, ggConc$Conc))))
     return(p)
 }
+
+#' Create concentration-time curve after multiple doses of caffeine
+#'
+#' \code{PlotMulti} will create concentration-time curve after multiple doses of caffeine
+#'
+#' @param ConcTimeMulti Concentration-time dataset having column names Subject, Time, and Conc (case-sensitive)
+#' @param log y axis log 
+#' @return The concentration-time curve
+#' @export
+#' @examples 
+#' PlotMulti(ConcTimeMulti(Weight = 20, Dose = 200, N = 20, Tau = 8, Repeat = 4))
+#' @seealso \url{http://asancpt.github.io/CaffeineEdison}
+#' @import dplyr
+#' @import ggplot2
+
+PlotMulti <- function(ConcTimeMulti, log = FALSE){
+    p <- ggplot(ConcTimeMulti, aes(x=Time, y=Conc)) + #, group=Subject, colour = Conc)) + #Subject)) +
+        xlab("Time (hour)") + ylab("Concentration (mg/L)") +
+        scale_x_continuous(breaks = seq(0, 96, 12)) +
+        #scale_colour_gradient(low="navy", high="red", space="Lab") +
+        geom_line(aes(group = Subject, colour = Conc)) + 
+        stat_summary(fun.y = "mean", colour = "#F0E442", size = 1, geom = "line") +
+        geom_hline(yintercept = 80, colour="red") + 
+        geom_hline(yintercept = 40, colour="blue") + 
+        geom_hline(yintercept = 10, colour="green") + theme_linedraw()
+
+    if (log == TRUE) p <- p + scale_y_log10() #limits = c(0.1, max(80, ggConc$Conc))))
+    return(p)
+}

data-raw/test.R

@@ -0,0 +1,18 @@
+# Tests -------------------------------------------------------------------
+
+Weight <- 20
+Dose <- 400
+N <- 20
+Tau <- 8
+
+edisonlib <- c("mgcv", "psych", "ggplot2", "dplyr", "markdown", "knitr", "tibble")
+lapply(edisonlib, function(pkg) {
+    if (system.file(package = pkg) == '') install.packages(pkg)
+})
+lapply(edisonlib, library, character.only = TRUE) # if needed # install.packages(mylib, lib = localLibPath)
+
+library(roxygen2)
+roxygenize()
+
+remove.packages("caffsim")
+devtools::install_github("asancpt/caffsim")

data-raw/use_data.R

@@ -1,3 +1,5 @@
+# use_data ----------------------------------------------------------------
+
 UnitTable <- read.csv("data-raw/UnitCSV.csv", as.is = TRUE)
 
 CaffSigma <- matrix(c(0.1599, 6.095e-2, 9.650e-2, 
@@ -37,25 +39,6 @@ devtools::use_data(CaffSigma,
                    Seed,
                    round_df,
                    Get_os,
+                   UnitTable,
                    internal = TRUE, overwrite = TRUE)
-devtools::use_data(UnitTable, overwrite = TRUE)
-
-Weight <- 20
-Dose <- 400
-N <- 20
-Tau <- 8
-
-edisonlib <- c("mgcv", "psych", "ggplot2", "dplyr", "markdown", "knitr", "tibble")
-lapply(edisonlib, function(pkg) {
-    if (system.file(package = pkg) == '') install.packages(pkg)
-})
-lapply(edisonlib, library, character.only = TRUE) # if needed # install.packages(mylib, lib = localLibPath)
-
-library(roxygen2)
-roxygenize()
-
-
-remove.packages("caffsim")
-
 
-devtools::install_github("asancpt/caffsim")