Utilization of the Poisson and ZIP in population PK/PD modeling requires coding the appropriate distribution into the software selected for analysis. Example code will be given as appropriate for NONMEM implementation however, the fundamentals are applicable to other software programs. [Pg.706]

The non-linear mixed effects model is the most widely used method and has proven to be very useful for continuous measures of drug effect, categorical response data, and survival-type data. The nonlinear mixed-effects modeling software (NONMEM) introduced by Sheiner and Beal is one of the most commonly used programs for population analysis. A detailed review of software for performing population PK/PD analysis is available. [Pg.2806]

Parameter estimation without an appropriate assessment of reliabihty of the estimates yields no conhdence in such estimates. Estimation of uncertainty enables the use of such parameter estimates in data synthesis. Embarking on data synthesis (e.g., clinical trial simulation) using model parameter estimates without associated uncertainty or poorly dehned uncertainty will produce unreliable outcomes. Sometimes it is impossible to obtain standard errors for population model parameter estimates when small sample sizes are used for population PK/PD modeling. The bootstrap with winsorization has been proposed for the estimation of inestimable uncertainty—standard errors—for population PK/PD parameters that are usually not obtainable using software such as NONMEM because of small sample size [Pg.831]

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