Re: NONMEM

From: Timothy H Waterhouse WATERHOUSE_TIMOTHY_H@Lilly.com Subject: Re: [NMusers] NONMEM Date: Fri, 15 Sep 2006 12:04:57 -0400 Hi all, While it's true, as far as I know, that "existing methods" (meaning software such as POPT, PFIM etc) don't allow for optimal design for precise estimation of other statistics, I think this is a relatively simple problem to address. If the feature of interest (such as AUC or tmax) can be written as a function of your PK parameters, a c-optimal design will give you precise estimates of this feature, and can be obtained using a function of the FIM. The problem with c-optimal designs is that they often give you a singular FIM, meaning they have zero efficiency for parameter estimation. This was actually addressed in a talk by Anthony Atkinson at the DEMA conference in Southampton last weekend. He used a combination of the "c" and "D" criteria to find designs which are efficient for both, using a simple PK model as an example. His methods were for fixed effects models, but I think they will extend to mixed effects models using the usual approximate information matrix. If you want to design for maximum power, minimum bias, etc, the information matrix may not be quite as helpful... Tim