Lei, Paulo,
There is no need to feel any pain due to "flip-flop" when elimination is
by a mixed order process. The "flip-flop" only causes difficulty in
assigning 'ka' and 'k' because of the symmetry of the sum of two
exponentials. If you have a mixed order process there is no 'k' and
therefore no symmetry of exponentials and therefore no "flip-flop".
Best wishes,
Nick
On 9/07/2015 7:57 a.m., Paolo Denti wrote:
Dear Lei,
I feel your pain, cuz I have also battled with models with stubborn
flip-flop and I started concocting all sort of codes similar to yours
to prevent it - you can probably find some desperate posts of mine
about this on NMUSERS :).
In my experience, the only code that sort of works without causing too
many side-effects is the one that prevents flip-flop of the typical
values (the THETAs). Unfortunately, this does not work every time, but
all the other codes accounting for individual parameters (such as the
one you propose) introduce funny correlations between the parameters
and the ETAs, they reshape the between-subject variability, and they
may end up causing more trouble than they solve.
In your case with nonlinear clearance, it may be even more complicated
than usual.
In my experience, the best option is to use priors on ka and volume,
even weakly informative. These should help stabilising your model.
Adding priors may seem "artificial", but if you think about it, it is
doing exactly what you are trying to achieve with all these tricky
codes. One cannot solve the flip-flop problem only with data from oral
administration, the only way is to add external information, like the
fact that you expect ka to be larger than ke, or include IV data that
helps you identify the correct value of volume. With the priors you do
just that, and in a more natural way than "cheating" NONMEM with funny
codes.
Good luck!
Paolo
On 2015/07/08 22:41, Lei Diao wrote:
Dear NONMEM Users,
I have a popPK model for which the Ka is constrained to be larger
than Ke at the individual level to avoid flip-flop. The question is
that if there is an additional nonlinear clearance component (M-M),
how should I constrain between the absorption rate (KA) and terminal
phase elimination rate (KE) since nonlinear clearance causes the KE
to change with time? Is there any reference on this topic?
KA and KE constraining in the absence of nonlinear clearance in NM code:
KE=((K+K23+K32)-SQRT((K+K23+K32)*(K+K23+K32)-4*K*K32))/2
KA=KE+THETA(5)*EXP(ETA(3))
Thanks a lot for your input!
Lei Diao
Biogen
--
------------------------------------------------
Paolo Denti, PhD
Pharmacometrics Group
Division of Clinical Pharmacology
Department of Medicine
University of Cape Town
K45 Old Main Building
Groote Schuur Hospital
Observatory, Cape Town
7925 South Africa
phone: +27 21 404 7719
fax: +27 21 448 1989
email:[email protected]
------------------------------------------------
------------------------------------------------------------------------
UNIVERSITY OF CAPE TOWN
This e-mail is subject to the UCT ICT policies and e-mail disclaimer
published on our website at
http://www.uct.ac.za/about/policies/emaildisclaimer/ or obtainable
from +27 21 650 9111. This e-mail is intended only for the person(s)
to whom it is addressed. If the e-mail has reached you in error,
please notify the author. If you are not the intended recipient of the
e-mail you may not use, disclose, copy, redirect or print the content.
If this e-mail is not related to the business of UCT it is sent by the
sender in the sender's individual capacity.
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(7)80 48 55 50
email: [email protected]
http://holford.fmhs.auckland.ac.nz/
Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop,
B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models
- tests of assumptions and predictions. Journal of Pharmacology & Clinical
Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin
Pharmacol. 2015;79(1):18-27.