From e0ca59cb02c7d691b7254e6374272eb65271d3e6 Mon Sep 17 00:00:00 2001 From: shanmdphd Date: Mon, 5 Jun 2017 11:05:11 +0900 Subject: [PATCH] updated R sources --- R/ConcTime.R | 42 ++++++++++++++++++++++++++++++++++++++++++ R/ConcTimeMulti.R | 40 ---------------------------------------- R/Dataset.R | 41 +++++++++++++++++++++++++++++++++++++++++ R/DatasetMulti.R | 40 ---------------------------------------- R/Plot.R | 29 +++++++++++++++++++++++++++++ R/PlotMulti.R | 28 ---------------------------- R/sysdata.rda | Bin 1189 -> 6624 bytes caffsim.pdf | Bin 88233 -> 89024 bytes data-raw/test.R | 18 ++++++++++++++++++ data-raw/use_data.R | 23 +++-------------------- man/ConcTimeMulti.Rd | 2 +- man/Dataset.Rd | 2 +- man/DatasetMulti.Rd | 2 +- man/PlotMulti.Rd | 2 +- 14 files changed, 137 insertions(+), 132 deletions(-) delete mode 100644 R/ConcTimeMulti.R delete mode 100644 R/DatasetMulti.R delete mode 100644 R/PlotMulti.R create mode 100644 data-raw/test.R diff --git a/R/ConcTime.R b/R/ConcTime.R index ebc4b14..75de4db 100644 --- a/R/ConcTime.R +++ b/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) +} diff --git a/R/ConcTimeMulti.R b/R/ConcTimeMulti.R deleted file mode 100644 index ea63112..0000000 --- a/R/ConcTimeMulti.R +++ /dev/null @@ -1,40 +0,0 @@ -#' 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) -} diff --git a/R/Dataset.R b/R/Dataset.R index a7bc2dc..b14621b 100644 --- a/R/Dataset.R +++ b/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) +} + diff --git a/R/DatasetMulti.R b/R/DatasetMulti.R deleted file mode 100644 index 978c6dd..0000000 --- a/R/DatasetMulti.R +++ /dev/null @@ -1,40 +0,0 @@ -#' 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) -} - diff --git a/R/Plot.R b/R/Plot.R index 52fcbe4..865d452 100644 --- a/R/Plot.R +++ b/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) +} diff --git a/R/PlotMulti.R b/R/PlotMulti.R deleted file mode 100644 index f1eb216..0000000 --- a/R/PlotMulti.R +++ /dev/null @@ -1,28 +0,0 @@ -#' 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) -} diff --git a/R/sysdata.rda b/R/sysdata.rda index 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