RE: NONMEM dataset development

From: "Nick Holford" n.holford@auckland.ac.nz Subject: RE: [NMusers] NONMEM dataset development Date: Mon, September 6, 2004 4:00 am Renee, > > Dear all, > > A few questions about developing the data set for NONMEM. > > 1. In NONMEM user manual V, it says that less than 50 data records are > allowed for each individual. Does it mean that maximum 50 data records, > which include dose records and observation records, are allowed for each > individual? How to change this limit? My understanding of this limit is that it refers to the number of observation records (not all records for an individual). You can increase the number of observations per subject by changing the PARAMETER NO in NSIZES and TSIZES then recompiling NONMEM. e.g. to allow 500 obs/subject C NO: MAX NO. OF OBSERVATION RECORDS / INDIVIDUAL RECORD PARAMETER (NO=500) You may also want to change these parameters in NSIZES as well. This will increase other array sizes that depend on NO. LADD 250500 LIM1 50000 LIM2 50000 > 2. Is it correct that AMT and DV observed at the time when dose is given > cannot be recorded in the same data record? If you are using PREDPP e.g. ADVAN1 you must have AMT and DV values on different records. There are two ways that having AMT and DV on the same record can be coded. Case 1: If you have a DV value on the same record as an AMT value and do not define a MDV data item then NM-TRAN will add MDV=1 for the AMT record and the DV value will be ignored. NONMEM will run but NM-TRAN will give you q warning like this: (DATA WARNING 5) RECORD 1, DATA ITEM 4: 11.9 THE DV DATA ITEM IS POSITIVE, BUT THE MDV DATA ITEM IS 1 Case 2: If you define an MDV=0 item for a record with AMT>0 then NONMEM considers this a data error. > 3. Some covariables are not available for some patients. Is it correct that > dot or 0 should be used to indicate the missing values? You may use any value you want to indicate a missing covariate value. NONMEM treats a dot and 0 as the same thing. It is probably a good idea to use a negative value (e.g. -99) to signal a missing value. This makes it clearer to a human reader of the data file that this is a strange value. You must of course write your own code to handle the case of a missing covariate. NONMEM does not do anything sensible by default with missing covariates. > 3. Some patients have the study drug for more than one occasion. NONMEM is > employed to work out the BOV. Therefore, data item OCC is added in the data > set to indicate the sequence of the occasion. Apart from that, what else > should be included in the data set? Does the ID# for each occasion of the > same patient keep the same? Estimation of BSV and BOV is a good idea. It requires that you have a data item (e.g. called OCC) to signal different occasions. An occasion can be defined in any way you like but often each dose is considered a different occasion. The ID data item should be the same for any given subject who has one or more different occasions of data. I think of the ID data item as the covariate for BSV while the OCC data item is the covariate for BOV. 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 http://www.health.auckland.ac.nz/pharmacology/staff/nholford/