RE: Proper way to handle the pre-first dose PK observation for non-endogenous drug
Yaming,
As you pointed-out DV=Prediction. Including these data-points biases your estimate of the additive component of variability. My opinion is just to exclude the observations to get a better estimate of additive variability.
On a side note Additive+Proportortional is similar to a lognormal-error structure. In a lognormal error structure zero observations have to be excluded anyway.
Matt.
Quoted reply history
From: owner-nmusers
Behalf Of Yaming Hang
Sent: Wednesday, November 07, 2012 4:04 PM
To: nmusers
Subject: [NMusers] Proper way to handle the pre-first dose PK observation for non-endogenous drug
Dear NONMEM Users,
I'd like to get some advice from you with regard to how to handle the pre-first dose PK observation when the drug is not an endogenous substance.
I tried too different approaches, one approach is treating them as missing values (DV=0, EVID=0, MDV=1), another is treating them as true 0s (DV=0, EVID=0, MDV=0). My error structure is proportional + additive. There were very little difference for all parameters except for the SD of the additive error. When these pre-first dose concentrations were treated as missing, the estimated omega for additive error is 3.92, and when they were treated as true 0s, the sigma became 2.85.
To me, in theory, these values provide no information about the model parameters because the system will predict them to be 0 at time 0 anyway for any point in the parameter space. Is what happened here that because DV is exactly the same as prediction, therefore the estimation of additive residual error variance has been brought down?
Which way is more appropriate? I'd really appreciate it if you can share your experience/insight.
Yaming Hang, Ph.D.
Pharmacometrics
Biogen Idec
14 Cambridge Center
Cambridge, MA 02142
Office: 781-464-1741
Fax: 617-679-2804
Email: Yaming.Hang
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