Re: truncation & simulation

Ron I guess, the model over-estimates variances of the random effects (could be due to non-normality of the distributions or some outliers in the data). Instead of truncation, I would suggest to sample from the 100 subjects that you have in your dataset: For each study, randomly select 12 subjects (I would do it without replacement) out of 100 that you have in your dataset. Use the PK parameters of those subjects for simulations. If you expect population of the BE trial to differ from the population of the trial that you had in your model, use ETAs of those 100 patients (correlated, as a vector) instead of PK parameters, and compute PK parameters based on the expected patient covariates. Leonid -------------------------------------- Leonid Gibiansky, Ph.D. President, QuantPharm LLC web: www.quantpharm.com e-mail: LGibiansky at quantpharm.com tel: (301) 767 5566 Ron Mathôt wrote: > Dear NONMEM users, > > Currently I am working on the simulation of a bio-equavalence trial. For the reference compound a population PK model has been derived on basis of data from 100 patients. Values for between-and within-patient variability are available for all PK parameters. The simulation comprises a randomized cross-over study with 12 patients taking the test and reference compound. Two-hunderd trials are simulated and summarized. During the simulations I noticed that truncation of the simulated of PK parameters significantly influences the power of the study to confirm bio-equivalence. For instance truncation of simulated oral clearances of both compounds from a range of 1-300 L/hr to 5 - 30 L/hr doubled the number of positive trials (due to decreased within- patient variability). Post-hoc estimates form the popPK study indicated that clearance values of the reference compound are all within the latter range of 5 to 30 L/hr. I expect that oral clearance of the test compound will not differ more than 5% from the reference compound. In my opinion simulation of trials with the smallest range will produce more reliable estimates of the power to detect bio-equivalence. > > I would greatly appreciate your comments on this subject. > Best regards, > > Ron Mathôt > > Department of Hospital Pharmacy and Clincal Pharmacology > Erasmus University Medical Center > Rotterdam > The Netherlands