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steady state in WinNonlin (example) [Software]

posted by Helmut Homepage - Vienna, Austria, 2007-04-05 02:30  - Posting: # 628
Views: 11,357

Dear PKPDPKPD!

» Is it possible to use WinNonLin to assess the achievement of steady state on the basis of pre-dose concentrations?

Yes.
Using the example of this post we have:
+-----+-------+
|  t  |   c   |
+-----+-------+
|  24 | 21.05 |
|  48 | 25.04 |
|  72 | 25.08 |
|  96 | 25.94 |
| 120 | 25.97 |
+-----+-------+


In WinNonlin (v5.2) open a new workbook and enter these values.
Use only the last three values:
Data > Exclude > Selection
Tools > PK/PD/NCA Wizard (or StrgF9)
Select 'Linear' > Next > Model 502 (Linear) > Next > Finish
Click on the 'Data Variables' icon
Drag the time variable to the 'X variable' field, drag the concentration variable to the 'Y variable' field > OK
Model > Start Modeling (or click the 'calculator' icon)
A new linear workbook opens, navigate to the 'Non-Transposed Final Parameters' tab.
There are two parameters, namely 'INT' and 'SLOPE'.
'INT' is the estimated Cmin, but we are interested in 'SLOPE', which should be zero in 'true' steady-state.
Now look at the 'Estimate'-column, which gives a value of 0.018542 for slope.
A common method for the assessment of SS-conditions is either doing a t-test (0.05,2-sided), or looking at the 95% confidence interval,* which should include zero.
WinNonlin gives you the confidence interval in the columns 'PlanarCI_Lower' and 'PlanarCI_Uper' with -0.279250 and 0.316334. Since zero is included in the CI, steady state conditions are reached.

I added a little noise to the data:
+-----+-------+
|  t  |   c   |
+-----+-------+
|  24 | 18.71 |
|  48 | 22.44 |
|  72 | 22.44 |
|  96 | 25.63 |
| 120 | 23.25 |
+-----+-------+

Now we get a slope of 0.016875 (95% CI -1.981561 to 2.015311); still in steady state.

I'm not sure when Pharsight introduced linear models in WinNonlin (maybe in v5.0), in older versions you may use the 'LinMix Wizard' (which is a little bit confusing for a beginner), or use this ASCII-model - which is pretty simple:
MODEL
  COMMANDS
    NFUNCTIONS 1
    NPARAMETERS 2
    PNAMES  'inter', 'slope'
  END
  FUNCTION 1
    F = inter + slope * X
  END
EOM




Cheers,
Helmut Schütz
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