The paper compares performance of Nonmem estimation methods-first order conditional estimation with interaction (FOCEI), iterative two stage (ITS), Monte Carlo importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), stochastic approximation expectation–maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES), on the simulated examples of a monoclonal antibody with target-mediated drug disposition (TMDD), demonstrates how optimization of the estimation options improves performance, and compares standard errors of Nonmem parameter estimates with those predicted by PFIM 3.2 optimal design software. Gibiansky, Leonid Gibiansky, Ekaterina Bauer, Robert When the SS data item is used, one or more of the data items AMT, RATE, and II must be present in the event record to specify the steady state dosing pattern.Comparison of Nonmem 7.2 estimation methods and parallel processing efficiency on a target-mediated drug disposition model Comparison of Nonmem 7.2 estimation methods and parallel processing efficiency on a.
The user supplies the initial estimate with some combination of prior event records, e.g., reset, transient dose, and other-type event records. SS = 3 is identical to SS = 1 with one exception: with Steady State routines SS6 and SS9, the existing state vector (com- partment amounts and eta derivatives) is used as the initial estimate in the computa- tion of the steady-state amounts. This is meaningful when kinetics are linear and the superposition principle holds.ģ indicates that the dose is a steady state dose. I.e., letting t be the time on the event record, then the amounts in the compartments are updated to amounts valid for time t, and next, these amounts are added to the steady-state amounts.
#Nonmem ss plus#
The system is not totally reset: the on/off status of the compartments remains as it was at the time of the prior event record (if any), and the value of time must be greater than or equal to its value on the prior event record (if any).Ģ indicates that the dose is a steady state dose and that the compartment amounts are to be set to the sum of the steady-state amounts resulting from the given dose plus whatever those amounts would have been at the event time were the steady-state dose not given. Compartment amounts resulting from prior dose event records are "zeroed out," and infusions in progress or pending additional doses are cancelled.
It can take one of three values in any event record.Ġ indicates that the dose is not a steady state dose.ġ indicates that the dose is a steady state dose, and that the compartment amounts are to be reset to the steady-state amounts resulting from the given dose. SS labels PREDPP’s steady-state (SS) data item. MEANING: Steady-State (SS) data item for PREDPP CONTEXT: $INPUT record and NONMEM data set could you post a minimal chunk of NONMEM data set that includes SS=2 record?
Now I don't think it will be too hard to implement.Ĭan you test something for me this weekend if I can get it into the dev branch?Īlso. After some reading, I learned that I didn't really understand what SS=2 was doing :).