I am trying to use a healthy volunteer population PK model in a monte carlo simulation to calculate a probability of target attainment analysis. In order to do this I need to inflate the variability of my clearance value to be more representative of a patient population. This is standard practice and easy for me when I have a diagonal omega matrix. But in this model, my omega matrix (covariance matrix) has off diagonal omega values associated with clearnace. So if I want to double the %CV value for clearance, and then in turn omega values, how do I calculate the impact of this clearance inflation on the off diagonal omega values?
Inflating clearance %CV for monte carlo simulation of off-diagonal omega matrix
Started by
dan.hines
, Sep 27 2019 05:49 PM
PPK NLME MCS PTA block omega
1 reply to this topic
#2
Posted 28 September 2019 - 03:42 AM
you can keep the correlation matrix as is and inflate the stdev part:
...
user R on any other software to compute your "new " var cov matrix based on:
mu <- c(0, 0, 0) # eta means
# this is your correlation matrix of omega
corMat <- matrix(c(1, 0.78, 0.23,
0.78, 1, 0.27,
0.23, 0.27, 1),
ncol = 3)
# you diagonals squareroots
stddev <- c(1.23, 0.92, 1.32) * inflationfactor
covMat <- stddev %*% t(stddev) * corMat
plug the new covMat into your pml code
- Simon Davis likes this
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