MM elimination vs dose

From: "Bonate, Peter" Peter.Bonate@genzyme.com Subject: [NMusers] MM elimination vs dose Date: Fri, 30 Sep 2005 12:25:03 -0400 Dear all, I am having trouble with something and I was hoping that someone would have some brilliant solution for me. I am fitting a 3-compartment model IV in 95 patients with rich data using FO-approximation. My base model has BSA and Age on CL as power functions. When I include dose on clearance as a power model, the OFV decreases from 13620.35 to 13516.61. The power term (SE) was -0.341 (0.152). Further, if I plot AUC(0-infinity) vs dose there is evidence of nonlinearity based on a power model. A 2-fold increase in dose results in a ~2.3 fold increase in AUC. The next model I tried was a Michaelis-Menten model where BSA and Age was included on Vmax. The OFV was 13619.24. No change from the base model. I also tried different starting values for Vmax and Km and get around the same solution each time, so local minima I don't apply here. Even when I compare a 3-compartment model with no covariates to a 3-compartment model with MM elimimation the OFV does not change (14138.61 vs. 14138.79, respectively). But as soon as a put Dose on CL (OFV=13560.37), BSA on CL (OFV=13651.29), and AGE on CL (OFV = 13942.51), the OFV decreases from the base model of 14138.61. Even taking into account the problems with the distribution of the likelihood ratio test and FO-approximation, these seem to be real decreases. So has anyone any ideas for why dose drops the OFV in a linear compartmental model but a MM elimination model won't work. All models minimized successfully without any singularities. Is the nonlinearity so mild that it can't be supported by a nonlinear compartmental model? Thanks for your help, Pete Bonate Peter L. Bonate, PhD, FCP Director, Pharmacokinetics Genzyme Corporation 4545 Horizon Hill Blvd San Antonio, TX 78229 phone: 210-949-8662 fax: 210-949-8219 email: peter.bonate@genzyme.com

From: Sam Liao sliao@pharmaxresearch.com Subject: Re: [NMusers] MM elimination vs dose Date: Fri, 30 Sep 2005 13:31:15 -0400 Dear Peter: I am not surprise to hear the problem you had on the MM elimination model. Based on my expereience, in order to estimate the Vmax and Km reliably, you will need a cross-over study with subjects received at least two different doses. Sam Liao Pharmax Research

From: Nick Holford n.holford@auckland.ac.nz Subject: Re: [NMusers] MM elimination vs dose Date: Sat, 01 Oct 2005 05:43:09 +1200 Peter, Non-linear PK can influence other processes apart from elimination. Have you looked for non-linear changes in volume of distribution? You may also want to consider changes in bioavailability with dose -- there could be an issue with the IV formulation as doses increase. I doubt if your drug is eliminated via the skin so why not look for a biologically based allometric scaling function for clearance rather than the discredited BSA scaling method? Finally, IMHO FO is ok for quick and dirty teaching projects but not for serious work... Nick -- Nick Holford, Dept Pharmacology & Clinical Pharmacology University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand email:n.holford@auckland.ac.nz tel:+64(9)373-7599x86730 fax:373-7556

From: "Gobburu, Jogarao V" GOBBURUJ@cder.fda.gov Subject: Re: [NMusers] MM elimination vs dose Date: Fri, 30 Sep 2005 15:34:16 -0400 I agree with Nick. In fact, I would strongly advocate use of simple NCA analysis to understand the nature of the nonlinearity, before embarking on mixed effects modeling. Joga

From: "Janet R. Wade" janet.wade@exprimo.com Subject: Re: [NMusers] MM elimination vs dose Date: Sat, 1 Oct 2005 09:13:25 +0200 Dear Pete Do you have data from more than one dose level per subject? If so, then your 'issue' reminds me of something I once encountered and where the PK also appeared to be non-linear with respect to dose (to my surprise since there was no previous indication of this). In my case it eventually turned out that the dose effect was no longer significant once I incorporated IOV on CL. Kind regards Janet Janet R Wade Exprimo NV http://www.exprimo.com/ _______________________________________________________