Dear Certara forum users,
I am building a popPK model for a parent drug and its metabolite (rich data,single dose) using NLME. I want to estimate the correlation between the residual errors of parent drug and its metabolite, because their measurements were from a same blood sample. my questions are:
1. do I need to specify L2 data item, and if yes, how to do it in NLME? (could you please provide an example to demonstrate, including details like data format*); 2. how to add sigma block using PML, for example, I am using combined additive and proportional model for both parent and metabolite. 3. My codes* are shown as follows, I fix the fraction of parent metabolized (Fm=0.3) based on literature value to solve the identifiability issue. Any suggestion about my codes?
Thanks in advance,any suggestion is greatly appreciated.
Jing Niu
CTM
University of Maryland
test(){
deriv(A1 = - (Clr * C) + (Aa * Ka)- (Cl2 * (C - C2))- (CLpar2met * C))
urinecpt(A0 = (Clr * C))
deriv(Aa = - (Aa * Ka))
deriv(A2 = (Cl2 * (C - C2)))
deriv(Amet = (CLpar2met * C)- (CLmet * Cmet)- (Cl_met2 * (Cmet - Cmet2)))
urinecpt(Amet0 = (CLmet * Cmet))
deriv(Amet2 = (Cl_met2 * (Cmet - Cmet2)))
C = A1 / V
dosepoint(Aa, tlag = (Tlag), idosevar = AaDose, infdosevar = AaInfDose, infratevar = AaInfRate)
C2 = A2 / V2
error(CEps = 0.0365714)
observe(CObs = C + CEps * sqrt(1 + (C)^2 * (CMultStdev/sigma())^2))
Cmet = Amet / Vmet
error(CEps_met = 0.05)
observe(CObs_met = Cmet + CEps_met * sqrt(1 + (Cmet)^2 * (MultStdev/sigma())^2))
Cmet2 = Amet2 / Vmet2
stparm(Cl = tvCl)
stparm(Fm = tvFm)
stparm(Tlag = tvTlag * exp(nTlag))
stparm(Ka = tvKa * exp(nKa))
stparm(V = tvV (LBM/48)^dVdLBM * exp(nV))
stparm(Clr = tvCl * (1-tvFm) * (CrClcut120/95)^dClrdCrCl exp(nClr))
stparm(CLpar2met = tvCl * tvFm * exp(nCLpar2met))
stparm(V2 = tvV2 * exp(nV2))
stparm(Cl2 = tvCl2 * exp(nCl2))
stparm(Vmet = tvVmet * exp(nVmet))
stparm(CLmet = tvCLmet * exp(nCLmet))
stparm(Vmet2 = tvVmet2 * exp(nVmet2))
stparm(Cl_met2 = tvCl_met2 * exp(nCl_met2))
stparm(CMultStdev = tvCMultStdev)
stparm(MultStdev = tvMultStdev)
fcovariate(Age)
fcovariate(Weight)
fcovariate(LBM)
fcovariate(Height)
fcovariate(BSA)
fcovariate(ECOG())
fcovariate(isFemale0F1M)
fcovariate(CrClnew)
fcovariate(CrClcut120)
fcovariate(Occ)
fixef(tvCl = c(0, 16.58102, ))
fixef(tvFm (freeze) = c(0, 0.3, ))
fixef(tvTlag = c(0, 0.225859, ))
fixef(tvKa = c(0, 2.28469, ))
fixef(tvV = c(0, 98.1745, ))
fixef(tvV2 = c(0, 57.4144, ))
fixef(tvCl2 = c(0, 19.6853, ))
fixef(tvVmet = c(0, 50, ))
fixef(tvCLmet = c(0, 25, ))
fixef(tvVmet2 = c(0, 20, ))
fixef(tvCl_met2 = c(0, 10, ))
fixef(dVdLBM(enable=c(0)) = c(0, 0.9, ))
fixef(dClrdCrCl(enable=c(0)) = c(0, 0.5, ))
fixef(tvCMultStdev = c(0, 0.237202, ))
fixef(tvMultStdev = c(0, 0.2, ))
ranef(diag(nKa, nTlag, nV, nV2, nCl2, nCLpar2met, nClr, nCLmet, nVmet, nCl_met2, nVmet2) = c(0.66896944, 0.5961447, 0.075934645, 0.19267901, 0.0656101, 0.16775341, 0.20547087, 0.18828786, 0.31245868, 1, 1))
ranef(diag() = c(), same(), same())
}