continuous markov chain model

Phoenix Certara Forums Modelling and Simulation
1

Attached is a really nice piece of work on modeling and simulation of adverse events with erlotinib using a continuous Markov chain. Is it possible to implement this approach in Phoenix? If so, how is this accomplished? I searched the forum here and hadn’t found anything, however if this has been discussed, please let me know.

Thanks!

Lance

2

[quote=“Lance Wollenberg, username:lwollenberg”]

Attached is a really nice piece of work on modeling and simulation of adverse events with erlotinib using a continuous Markov chain. Is it possible to implement this approach in Phoenix? If so, how is this accomplished? I searched the forum here and hadn’t found anything, however if this has been discussed, please let me know.

Thanks!

Lance

[/quote]Markov Erlotinib Model.pdf (761 KB)

3

Hi Lance,

PML has all the infrastructure to enable you to fit discrete or continuous markov multistate models.

from the publication:

DADT(3) = KBB1*A(4)-KFF1*A(3)                       ; No rash
DADT(4) = KFF1*A(3)+KBB2*A(5)-KBB1*A(4)-KFF2*A(4)     ; Mild rash
DADT(5) = KFF2*A(4)+KBB3*A(6)-KBB2*A(5)-KFF3*A(5)     ; Moderate rash
DADT(6) = KFF3*A(5)-KBB3*A(6)                       ; Severe rash

these are just ODE with parameters controlling the probabilities to 
transition from one state to another 
some models assume a hierarchy where you cannot pass 
from mild to severe ( you just missed to observe it ) 
and talk about a latent kind of state.
other multistate models have what we all absorbent 
state where if you attain it your are kicked out e.g. Death State.