#load the prepared the input dataset. "param" includes at least one variable "ID" and covariates, pk parameters for each ID load('param.RData') param$DOSEINT <- map(param$REGIMEN, from=c(2,3), to=c(336, 504)) param[!duplicated(param[c('NDOSE','REGIMEN')]),] -> param2 param2$DOSEINT <- map(param2$REGIMEN, from=c(2,3), to=c(336, 504)) param2$INFTIME <- c(2,2,1,1,1,NA,0.5,0.5,0.5) param2$DU <- c('mg', rep('mg/kg',2), rep('mg',4), rep('mg/kg',2)) param2$DOSECMT <- c(1,2,2,1,1,2,2,2,1) st.2w <- c(0.5,1,2,4,6,8,24,48,72,168,336) st.3w <- c(0.5,1,2,4,6,8,24,48,72,168,336,504) st.4w <- c(0.5,1,2,4,6,8,24,48,72,168,336,672) st.8w <- c(st.4w, 1344) write.csv(param2, file='../../nm/0data/param2.csv', row.names=F, na='.', quote=F) read.csv('../../nm/0data/param2.csv', header=T, na.strings='.', as.is = T) -> param2 #one dose regimen for all subjects sim <- create.sim.dataset(read.dose.info=F, di = 336, num.dose = 3, dose = 3, dose.unit = c('mg/kg'), dose.cmt = 1, obs.cmt = 1, smp.time = list(st.2w), smp.time.as.is = F, inf.time = 0.5, auc.interval=T, auc.cmt = 3, cov.df = param, id.var = 'ID', bw.var='BBWT', output.suffix = NULL, export=TRUE, export.path='../../nm/0data/', ss = TRUE, ss.with.addl = TRUE, addl = 100, auc.ss.interval =FALSE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 4, skip.dir.check=TRUE) #A loading dose is given at the same time sim1 <- create.sim.dataset(read.dose.info=F, di = c(0,336), num.dose = c(1,2), dose = c(3, 200), dose.unit = c('mg/kg','mg'), dose.cmt = c(2,1), obs.cmt = 1, smp.time = list(NA, st.2w), smp.time.as.is = F, inf.time = c(-1,1), auc.interval=T, auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's1', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 1, skip.dir.check=TRUE) #three sequential dosing regimens for each person (including different dose intervals, doses, dose units, dose compartment and multipe AUC compartments) sim2 <- create.sim.dataset(read.dose.info=F, di = c(336, 504, 672), num.dose = 2, dose = c(3, 240, 10), dose.unit = c('mg/kg', 'mg', 'mg/kg'), dose.cmt = c(1, 1, 2), obs.cmt = c(1), smp.time = list(st.2w, st.3w, st.4w), smp.time.as.is = F, inf.time = c(1, 0.5, 2), auc.interval=T, auc.cmt = c(3,5), cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's2', export=TRUE, ss = TRUE, smp.time.ss = NA, only.ss = FALSE, num.dose.ss = 2, skip.dir.check=TRUE) #read dosing information from "cov.df" sim3 <- create.sim.dataset(read.dose.info=T, di = 'DOSEINT', num.dose = 3, dose = 'NDOSE', dose.unit = 'DU', dose.cmt = 'DOSECMT', obs.cmt = 1, smp.time = list(st.2w, st.3w), smp.time.as.is = F, inf.time = 'INFTIME', auc.interval=T, auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's3', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NA, only.ss = FALSE, num.dose.ss = 2, skip.dir.check=TRUE) #real example: 6 doses of 360 mg Q3W, followed by 8 doses of 480 Q4W sim4 <- create.sim.dataset(read.dose.info=F, di = c(504, 672), num.dose = c(6,9), dose = c(360, 480), dose.unit = c('mg', 'mg'), dose.cmt = 1, obs.cmt = 1, smp.time = list(st.3w, st.4w), smp.time.as.is = F, inf.time = 0.5, auc.interval=T, auc.cmt = 3, cov.df = param, id.var = 'ID', bw.var='BBWT', output.suffix = 's4', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 1, skip.dir.check=TRUE) sim5 <- create.sim.dataset(read.dose.info=F, di = 336, num.dose = 26, dose = 3, dose.unit = c('mg/kg'), dose.cmt = 1, sec.dose.cmt = 2, obs.cmt = 1, smp.time = list(st.2w), smp.time.as.is = F, inf.time = NA, sec.inf.time = -2, auc.interval=T, auc.cmt = 3, cov.df = param, id.var = 'ID', bw.var='BBWT', output.suffix = 's5', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 4, skip.dir.check=TRUE) sim6 <- create.sim.dataset(read.dose.info=F, di = 672, num.dose = 13, dose = 480, dose.unit = c('mg'), dose.cmt = 1, obs.cmt = 1, smp.time = list(st.4w), smp.time.as.is = F, inf.time = 1, auc.interval=T, auc.cmt = 3, cov.df = param, id.var = 'ID', bw.var='BBWT', output.suffix = 's6', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 2, skip.dir.check=TRUE) sim7 <- create.sim.dataset(read.dose.info=F, di = 1344, num.dose = 7, dose = 960, dose.unit = c('mg'), dose.cmt = 1, obs.cmt = 1, smp.time = list(st.8w), smp.time.as.is = F, inf.time = 1, auc.interval=T, auc.cmt = 3, cov.df = param, id.var = 'ID', bw.var='BBWT', output.suffix = 's7', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 1, skip.dir.check=TRUE) ##steady state by ADDL sim8 <- create.sim.dataset(read.dose.info=T, di = 'DOSEINT', num.dose = 'NUMDOSE', dose = 'NDOSE', dose.unit = 'DU', dose.cmt = 'DOSECMT', obs.cmt = 1, smp.time = list(st.2w, st.3w), smp.time.as.is = F, inf.time = 'INFTIME', auc.interval=T, auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's8', export=TRUE, export.path='../../nm/0data/', ss = TRUE, ss.with.addl = TRUE, addl = 100, auc.ss.interval =TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 3, skip.dir.check=TRUE) sim9 <- create.sim.dataset(read.dose.info=F, di = 336, num.dose = 3, dose = 3, dose.unit = 'mg/kg', dose.cmt = 1, sec.dose.cmt = 2, obs.cmt = 1, smp.time = list(st.2w), smp.time.as.is = F, inf.time = NA, sec.inf.time = -2, auc.interval=T, auc.cmt = c(3,5), cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's9', export=TRUE, export.path='../../nm/0data/', ss = TRUE, ss.with.addl = T, addl = 100, auc.ss.interval =T, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 2, skip.dir.check=TRUE) # run NONMEM '../../0sim/tvCL-nivo-sim-ss-s8-addl.ctl' # run NONMEM '../../0sim/tvCL-nivo-sim-ss-s9-addl.ctl' #Using smp.time.ss argument when only steady state dataset is generated, smp.time can be NULL #smp.time.ss is not required if smp.time argument is given appropriate values sim8b <- create.sim.dataset(read.dose.info=T, di = 'DOSEINT', num.dose = 'NUMDOSE', dose = 'NDOSE', dose.unit = 'DU', dose.cmt = 'DOSECMT', sec.dose.cmt = 'SDOSECMT', obs.cmt = 1, smp.time = list(st.2w, st.3w), smp.time.as.is = F, inf.time = 'INFTIME', sec.inf.time = 'SINFTIME', auc.interval=T, auc.cmt = 3, cov.df = param3, id.var = 'ID', bw.var='BBWT', output.suffix = 's8b', export=T, export.path='../../nm/0data/', ss = T, ss.with.addl = T, addl = 100, auc.ss.interval =T, smp.time.ss = list(c(1,2,3,504), c(2,4,6,336)), only.ss = F, num.dose.ss = 'NUMDOSE', skip.dir.check=TRUE) sim9b <- create.sim.dataset(read.dose.info=F, di = c(504), num.dose = 2, dose = c(3), dose.unit = c('mg/kg'), dose.cmt = 2, obs.cmt = 1, smp.time = NULL, smp.time.as.is = F, inf.time = 0.5, auc.interval=T, auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's9b', export=T, export.path='../../nm/0data/', ss = T, ss.with.addl = T, addl = 100, auc.ss.interval =T, smp.time.ss = list(c(1,2,3,504)), only.ss = T, num.dose.ss = 3, skip.dir.check=TRUE) #QD dosing with a no-dose period in between; also use multiple AUC compartments sim.qd <- create.sim.dataset(read.dose.info=F, di = rep(c(24,96,48),3), num.dose = rep(c(5,1,3),3), dose = rep(c(3,0,3),3), dose.unit = c('mg/kg'), dose.cmt = 1, obs.cmt = 2, smp.time = rep(list(st.qd, st.q4d, st.q2d),3), inf.time = 1, auc.interval=rep(c(T,F,T),3), auc.cmt = c(3,5,7), cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 'qd', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 4, skip.dir.check=TRUE) #With a bigger AUC interval than the dosing interval sim.bigAUCINT <- create.sim.dataset(read.dose.info=F, di = 24, num.dose = c(5,2,3), dose = 3, dose.unit = c('mg/kg'), dose.cmt = 1, obs.cmt = 1, smp.time = list(st.qd), inf.time = 1, auc.interval=c(T,F,T), auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 'bigAUCINT', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 4, skip.dir.check=TRUE) # Ipi + Nivo combination regimen # W1 W3 W5 W7 W9 W11 W13 W15 W17 W19 W21 W23 # I3 I3 I3 I3 # -- N1 N1 -- N1 N1 -- N1 N1 -- N1 N1 sim10 <- create.sim.dataset(read.dose.info=F, di = 336, num.dose = rep(c(1,1,1), 4), dose = rep(c(0, 1, 5),4), dose.unit = c('mg/kg'), dose.cmt = 1, obs.cmt = 1, smp.time = list(st.2w), inf.time = rep(c(0,1,0.5), 4), auc.interval=c(T), auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's10', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, only.ss = FALSE, num.dose.ss = 3, skip.dir.check=TRUE) #process the output from s8, s9 (steady state only) exp8 <- process.simout(nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s8-addl/', nm.output.ss = 's8', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSESIM'), dose.no='all', scenario = '') ct8 <- process.simout(nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s8-addl/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSESIM'), dose.no='all', scenario = 'Various', cmt = 1, addl = 100) exp9 <- process.simout(nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s9-addl/', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSESIM'), dose.no='all', scenario = '3 mg/kg Q2W', cmt=2) ct9 <- process.simout(nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s9-addl/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSESIM'), dose.no='all', scenario = '3 mg/kg Q2W', cmt=1, addl = 100) noquote(paste0(names(sim5[[1]]), collapse=' ')) noquote(paste0(names(sim5[[2]]), collapse=' ')) noquote(paste0(names(sim8), collapse=' ')) #run NONMEM simulation under '../../nm/0sim/' #=================================================== #process the simulation output #Get the summary exposure (Cmin, Cmax and Cavg) after the 1,2,8 and 12 doses and steady state system.time(exp4 <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s4/simout.s4', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s4/simout.ss.s4', type = 'summary.exposure', keep.col = c('BBWT'), dose.no=c(1,2,8,12), scenario = '360 mg Q3W, 480 mg Q4W')) #Get summary exposure after every dose simulated (including steady state) system.time(exp4all <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s4/', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s4/', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '360 mg Q3W, 480 mg Q4W')) #Get summary exposure after every dose simulated (including steady state) system.time(exp4dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s4/', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '360 mg Q3W, 480 mg Q4W')) #Get summary exposure steady state only system.time(exp4ss <- process.simout(nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s4/', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '360 mg Q3W, 480 mg Q4W')) #Derive a new exposure metric CAVGD28 based on the CAVG1 and CAVG2, and CMIND28 = CMIN2 exp5cavgd28 <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s5/', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s5/', type = 'summary.exposure', keep.col = c('BBWT'), dose.no=c(1,2), derive.new.var=list('CAVGD28 = (CAVG1+CAVG2)/2', 'CMIND28 = CMIN2') ,scenario = '3 mg/kg Q2W') #Note: the drive.new var argument should be used with cautions for different dosing regimens head(exp5cavgd28) ##Concentration vs time profiles #Get concentration vs time profile for all doses (including steady state) ct4 <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s4/', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s4/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '360 mg Q3W, 480 mg Q4W') #CT profile for dosing history only ct4dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s4/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '360 mg Q3W, 480 mg Q4W') #CT profile for steady state only ct4ss <- process.simout(nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s4/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '360 mg Q3W, 480 mg Q4W') #Get concentration vs time profile for the first ten doses (including steady state) ct4m <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s4/', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s4/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no=c(1:10), scenario = '360 mg Q3W, 480 mg Q4W') ct4mdh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s4/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no=c(1:7), scenario = '360 mg Q3W, 480 mg Q4W') ct4mss <- process.simout(nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s4/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no=c(1:7), scenario = '360 mg Q3W, 480 mg Q4W') ##More scenarios ct5 <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s5/', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s5/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '3 mg/kg Q2W') ct5dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s5/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '3 mg/kg Q2W') exp5dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s5/', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '3 mg/kg Q2W') ct6 <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s6/', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s6/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '480 mg Q4W') ct6dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s6/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '480 mg Q4W') exp6dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s6/', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '480 mg Q4W') ct7 <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s7/', nm.path.ss = '../../nm/0sim/tvCL-nivo-sim-ss-s7/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '960 mg Q8W') ct7dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s7/', type = 'conc.vs.time', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '960 mg Q8W') exp7dh <- process.simout(nm.path = '../../nm/0sim/tvCL-nivo-sim-s7/', type = 'summary.exposure', keep.col = c('BBWT','DI','NDOSE'), dose.no='all', scenario = '960 mg Q8W') #============Plots plot1 <- ct.plot.overlaid(ct.df = list(ct5, ct6), time.window = c(0, 672), export = F, scale=list(y=list(relation='free'))) #without SS ct.plot.overlaid(ct.df = list(ct5dh, ct6dh), time.window = c(0, 672), export = F, layout=c(1,1)) #another example ct.plot.overlaid(ct.df = list(ct5, ct6), time.window = c(672, 672*2), xlab='Time [Week]', export = F) plot2 <- ct.plot.overlaid(ct.df = list(ct5, ct6), export = F) plot3 <- ct.plot.with.pi(ct.df = list(ct5, ct6, ct7), safety.margin = c(387, 603), export = F) #another example ct.plot.with.pi(ct.df = list(ct5dh, ct6dh), safety.margin = c(387, 603), xlab='Time [Month]', export = F) plot4 <- smr.exp.vs.time(exp.df = list( exp5dh, exp4dh, exp6dh), exp = 'CMAX', export = F) #another example smr.exp.vs.time(exp.df = list( exp5dh, exp4dh, exp6dh), exp = 'CMAX', xlab='Time [Day]', export = F) #count the data and calculate a percentage param$WTCUT <- cut2(param$BBWT,cuts=c(65, 90)) count.pct(data=param, count.var = 'ID', count.by.var1 = c('WTCUT','SEX')) count.pct(data=exp5d1, count.var = 'ID', cov.df=param, count.by.var1 = 'WTCUT', count.by.var2='TTYPEF2') count.pct(data=exp5d1, subset='SEX==1', count.var = 'ID', cov.df=param, count.by.var1 = 'WTCUT', count.by.var2='TTYPEF2', overall=T, cat.results=T) count.pct(data=exp5d1, count.var = 'ID', cov.df=param, count.by.var1 = c('WTCUT','SEX'), count.by.var2=c('TTYPEF2'), overall=T, cat.results=T, report.all=F) count.pct(data=exp5d1, count.var = 'ID', cov.df=param, count.by.var1 = c('WTCUT'), count.by.var2=c('SEX','TTYPEF2'), overall=F) count.pct(data=exp5d1, count.var = 'ID', cov.df=param, count.by.var1 = c('WTCUT','SEX'), count.by.var2=c('RACE','TTYPEF2'), overall=F) #count unique values count.pct(data=exp5d1, count.var = 'CMAX1', count.unique = FALSE, cov.df=param, count.by.var1 = 'WTCUT', count.by.var2='TTYPEF2', overall=T, cat.results=T, report.all=F) count.pct(data=exp5d1, count.var = 'CMAX1', count.unique = TRUE, cov.df=param, count.by.var1 = c('WTCUT','SEX'), count.by.var2=c('TTYPEF2'), overall=T) # png(file='../plots/ct-plot-overlaid-1.png', width=1000, height=600); print(plot1); dev.off() # png(file='../plots/ct-plot-overlaid-2.png', width=1000, height=600); print(plot2); dev.off() # png(file='../plots/ct-plot-with-pi.png', width=1000, height=600); print(plot3); dev.off() # png(file='../plots/Cmax-vs-time.png', width=1000, height=600); print(plot4); dev.off() # system('rm ../plots/*-b.png') # plot3b <- ct.plot.with.pi(ct.df = list(ct5dh, ct6dh, ct7dh), safety.margin = c(387, 603)) # png(file='../plots/ct-plot-with-pi-b.png', width=1000, height=600); print(plot3b); dev.off() # # plot4b <- smr.exp.vs.time(exp.df = list( exp5dh, exp6dh, exp7dh), exp = 'CMAX') # png(file='../plots/Cmax-vs-time-b.png', width=1000, height=600); print(plot4b); dev.off() read.csv('../../nm/0data/param3.csv', header=T, na.strings='.', as.is = T) -> param3 #oral dose are introduced into two compartments (e.g. to model zero order and first order simultaneously) #read dose info from cov.df sim11 <- create.sim.dataset(read.dose.info=T, di = 'DOSEINT', num.dose = 'NUMDOSE', dose = 'NDOSE', dose.unit ='DU', dose.cmt = 'DOSECMT', sec.dose.cmt = 'SDOSECMT' , obs.cmt = 1, smp.time = list(st.2w, st.3w), smp.time.as.is = F, inf.time = 'INFTIME', sec.inf.time = 'SINFTIME', auc.interval=T, auc.cmt = 3, cov.df = param3, id.var = 'ID', bw.var='BBWT', output.suffix = 's11', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, ss.with.addl = F, addl = NULL, only.ss = T, num.dose.ss = 3, skip.dir.check=TRUE) sim11b <- create.sim.dataset(read.dose.info=T, di = 'DOSEINT', num.dose = 'NUMDOSE', dose = 'NDOSE', dose.unit ='DU', dose.cmt = 'DOSECMT', sec.dose.cmt = 'SDOSECMT' , obs.cmt = 1, smp.time = list(st.2w, st.3w), smp.time.as.is = F, inf.time = 'INFTIME', sec.inf.time = 'SINFTIME', auc.interval=T, auc.cmt = 3, cov.df = param3, id.var = 'ID', bw.var='BBWT', output.suffix = 's11b', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, ss.with.addl = T, addl = 100, only.ss = T, num.dose.ss = 3, skip.dir.check=TRUE) #dosing info provided through arugments directly sim12 <- create.sim.dataset(read.dose.info=F, di = c(336,504,336), num.dose = c(2,2,3), dose = c(240, 3, 10), dose.unit =c('mg','mg/kg','mg/kg'), dose.cmt = 1, sec.dose.cmt = c(NA, 2, 2), obs.cmt = 2, smp.time = list(st.2w, st.3w, st.2w), smp.time.as.is = F, inf.time = c(-1, NA, NA), sec.inf.time = c(NA,-2, -2), auc.interval=T, auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's12', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, ss.with.addl = F, addl = NULL, only.ss = F, num.dose.ss = 3, skip.dir.check=TRUE) sim12b <- create.sim.dataset(read.dose.info=F, di = c(336,504,336), num.dose = c(2,2,3), dose = c(240, 3, 10), dose.unit =c('mg','mg/kg','mg/kg'), dose.cmt = 1, sec.dose.cmt = c(NA, 2, 2), obs.cmt = 2, smp.time = list(st.2w, st.3w, st.2w), smp.time.as.is = F, inf.time = c(-1, NA, NA), sec.inf.time = c(NA,-2, -2), auc.interval=T, auc.cmt = 3, cov.df = param2, id.var = 'ID', bw.var='BBWT', output.suffix = 's12b', export=TRUE, export.path='../../nm/0data/', ss = TRUE, smp.time.ss = NULL, ss.with.addl = T, addl = 100, only.ss = TRUE, num.dose.ss = 3, skip.dir.check=TRUE)