|On this page…|
You can import tabular data to the SimBiology® desktop or to the MATLAB® Workspace. The supported file types are .xls, .csv, and .txt. You can specify that the data is in a NONMEM® formatted file. The import process interprets the columns according to the NONMEM definitions. For more information see Support for Importing NONMEM Formatted Files.
From the SimBiology desktop, you can filter the raw data to suppress outliers, visualize data using common plots (such as plot, semilog, scatter, or stairs), and perform basic statistical analysis. You also can use functions to process and visualize the data at the command line.
Note: If your data set contains dosing information that is infusion data, the data set must contain the rate and not an infusion duration.
Regardless of whether unit conversion functionality is on or off, dosing in the data file must be expressed in amounts (or as amount/time for infusion rate). By default Unit Conversion is off, so you must ensure that units for the data are consistent with each other. If you want to turn on unit conversion, see Unit Conversion for Imported Data .
You can specify that the data is in a NONMEM formatted file. The following table highlights the interpretation of this data in SimBiology software.
Text or numeric values that identify the record. The import process assumes that contiguous data with the same value contains data from one individual. If the data contains non-contiguous references to the same value, the import process assigns the second ID encountered an indexed valued derived from the group first encountered. For example, if the ID columns contains [1 1 1 2 2 2 1 1 1], the IDs assigned are 1, 2, 1_1.
Monotonically increasing positive values within each group, indicating time of observation or dose. The data file can specify clock (2:30) or decimal values (6.25). The import process assigns a value of 0 to the first TIME value in the data file. The import process assigns subsequent values relative to the first value. For example the import process interprets [10:05 10:30 11 12:30 21.3] as: [0 0.25 0.95 2.25 14.2].
If the data file also contains a DATE column, the import process uses it with the TIME column in calculating the relative TIME values. The column cannot contain Inf.
|DATE, DAT1, DAT2, or DAT3|
Defines the day of the observation or the dose. The column can contain the month as a number (9) or a string (Sep). Specify date in the following formats:
Note the following additional assumptions:
|DV||Numeric value of an observation. Column cannot contain Inf or –Inf.|
|MDV||Defines whether a row describes an observation: |
|EVID||Defines the type of event described for the row in the record:|
If a column contains values for dose, but EVID is not 1, the import process ignores the value. You see a warning and the value is ignored.
If EVID is set to 2, then only those specified row data are imported as covariate data. However, if you have an EVID column as well as one or more covariate columns, but do not specify a value of 2 anywhere in the EVID column, then SimBiology imports all the row data as covariate values.
The import process does not support values 3 and 4. You see a warning and the value is ignored.
|CMT||Indicates which compartment is used for observation value or
for dose received. The interpretation also depends on EVID: |
|AMT||Positive number indicating dose. 0 or NaN specifies no dose administered. The column cannot contain Inf.|
|RATE||Positive number indicating rate of infusion. 0 specifies an infinite rate (equivalent to a bolus dose), and NaN specifies no rate. The column cannot contain Inf.|
|II||Positive number defining the time between doses.|
|ADDL||When the data specifies a number of identical serial doses at specific intervals (defined by II), ADDL specifies the number of doses in the series excluding the initial dose. If the data specifies II but not ADDL, then SimBiology assumes that the dosing occurs for the duration of that data record.|
The import process does not support (and therefore ignores) the rows containing the following values or definitions:
EVID values 3 and 4
SS column for specifying steady state doses
PCMT column to define whether to compute a prediction for the row
CALL column for calling the ERROR or the PK subroutine
If rate is specified as being less than zero, it is assumed to be zero
If you are creating a file containing population data that you want to later import into SimBiology, create the data file with the following columns:
Group column — Specify text or numeric values. The rows in the file that have the same Group column value are for the same individual.
Time column — Specify monotonically increasing positive values within each group that define the time of the dose, observation and/or covariate measurements.
Zero or more dosing columns — Create one dosing column for each compartment being dosed. In each column, specify positive values representing doses in amount that are added to a species. Use 0 or NaN to specify that no dose was applied at the specified time. This is useful for times when an observation was recorded but no dose was applied.
Zero, or more rate columns — Specify positive values. Zero specifies an infinite rate and NaN specifies that no rate applies. The rate column is associated with a dosing column and defines the rate at which the dose is administered.
Zero or more observation columns — Specify numeric values or NaNs. You can only specify one observation value at a particular time for each group. NaN values define that no observation was recorded at the specified time. This is useful for times when a dose was applied but no observation was recorded.
Zero or more covariate columns — Specify numeric values or NaNs. Each value defines the covariate value at the specified time. NaN values define that no covariate observation was recorded at the specified time.
If you set an EVID value of 2 for some rows, then SimBiology imports only those rows as covariate data. If you do not mention an EVID value of 2 anywhere and have one or more covariate columns, then SimBiology imports all the row data as covariate data.