Re: NONMEM

From: Mark Sale - Next Level Solutions mark@nextlevelsolns.com Subject: Re: [NMusers] NONMEM Date: Thu, 14 Sep 2006 08:21:14 -0700 My 2 cents: First, you need to define what you mean by optimal. Traditional statistical optimal design - e.g. ANOVA is aimed at getting parameter estimates as precisely estimated as possible - a laudable goal in traditional statistics, nicely implemented in a number of applications, I'm most familiar with Steve Duffuls ( http://www.bichat.inserm.fr/equipes/Emi0357/download.html), but I'll let him tell you how wonderful it is. The three central problems, IHMO with existing methods are: 1. Limited to D (or ED, or perhaps C|S) optimal for model parameters. What if we want to get a model with the smallest mean absolute error? What if we want a study design that estimates some other statistic (survival time, AUC, difference between treatment A and placebo, etc) as precisely as possible? 2. No/little flexibility in sample number - they address sample times only, the sample number is (usually) fixed. What if our question is (the more realistic) - what is the optimal study design (which I think means getting and "adequate" answer for the lowest cost) to answer this question if samples cost $200 each and subjects cost $5000 to enroll and $1000/week to keep in the study. 3. They don't tell you if a study is adequate - only which design is best, for a given number of subjects/samples. We have done a small demonstration project optimizing a BE study. Essentially: Find the optimal number of subjects, number of samples, sample times to result in a "successful" BE study (e.g., 1-beta = 90%, 1-alpha = 90%), given a specified cost of samples and subjects. NCA pk was done. Model also included uncertainty about model parameters. The algorithm used for the optimization was (my favorite algorithm) Genetic algorithm. Interestingly, the resulting design was quite close to what we usually do - except the GA answer had fewer sample times than the traditionally designed study (and so was a little cheaper). It also was clear that D optimal was very different from NCA optimal sampling times. I haven't had time to continue persuing this - any grad student interested, I'm happy to share the code that I have. Mark Mark Sale MD Next Level Solutions, LLC www.NextLevelSolns.com