Any tools for Bayesian estimation? (fwd)

From sduffull@chmeds.ac.nz Wed Mar 26 19:49:48 1997 Subject: Any tools for Bayesian estimation? (fwd) Regarding Bayesian methods for dos-individualisation Most Bayesian methods offer easy modelling. However it is important to note that I know of none that allow the flexibility offered by NONMEM in terms of model definition. I have some familiarity with ABBOTTBASE, USC-PACK, and SeBA programs and none of these allow complex model description (at least not more complex than 2-3 cpt linear models or 1 cpt nonlinear models). Most Bayesian programs that I have used do not allow specific modelling of residual error terms for an individual. Some methods, that would allow this, have been described, eg. Wakefield JPB 1996;24:103-31. However this technique does not appear to be commercially available yet. The SeBA programs (described by Duffull, Cancer Chemother Pharmacol 1997;39:317-26 , Duffull, BJCP 1997;43:125-135 and Duffull, Proc Aust Soc Clin Exp Phamracol Toxicol 1996;3:58) may offer a potential advantage over other Bayesian programs in that they allow within patient variability to be modelled as changes in the structural PK parameters. The SeBA programs use a Sequential Bayesian Algorithm that analyse each set of concentration-time data for each dose, thereby continuously updating the prior model. This allows the prior model to `grow' to become more like the patient. It allows description of changes that may occur in a patients PK parameter values over a course of therapy (sometimes referred to as interoccasion variability) in the absence of changes in the patient's covariates. This might be expected to be beneficial for patients who are acutely ill at the beginning of treatment and whose condition is expected to improve due to the intervention (eg gentamicin). Generally the error term used in a Bayesian program that uses MAP is assay error, only. With few exceptions the source of error from the assay significantly outways errors from other sources (eg model misspecification etc). However users can also define the variance of the residual error in the MAP algorithm as the proportional error component given by NONMEM (eg ABBOTTBASE). USCPACK allows the user to describe the variance of the residual error using a quadratic function. The SeBA programs can use proportional or proportional and additive as desired. All of the programs mentioned are executable on a PC, most are DOS based rather than Windows. I hope this has been of some use. Steve ................ Steve Duffull Dept of Clinical Pharmacology Christchurch Hospital Private Bag 4710, CHCH NZ Ph +64 3 364 0900 Fax +64 3 364 0902