WinNonlin 5.2.1 vs. 6 beta [🇷 for BE/BA]

posted by yjlee168 Homepage – Kaohsiung, Taiwan, 2008-09-29 20:45 (5659 d 13:53 ago) – Posting: # 2439
Views: 56,440

Dear Helmut,

We used WNL v5.1.1 here. What WNL actually does in estimation of lambdaz is to include the last three data points first. And calculate its adjusted R2 for this step. Then include one more data point (i.e. the 4th data point from the last) and calculate adj. R2 again. If the difference between these two adj. R2s is less than or equal to 0.0001, then stop including further. If not, then include the 4th data points and add one more data points (i.e. the 5th data point from the last)... It will not stop until it reaches Cmax. That's why WNL may include Cmax to estimate lambdaz. WNL should stop including at the data point next to Cmax. The result you got from WNL v6 beta seems not meet its stop criterion. The adj. R2 for Ex. 04 including Cmax is 0.9941 win WNL v5.1.1 (or your WNL 5.2.1); however, v6 beta got 0.9937 only.

WLN v6 beta - Ex. 04 (quoted from your previous post)
...
 Final Parameters
 ---------------
 Rsq                                                       0.9968
 Rsq_adjusted                                              0.9937
...

WLN - Ex. 04
Model:  Plasma Data, Extravascular Administration
Number of nonmissing observations:   12
Dose time:      0.00
Dose amount:    80000.00
Calculation method:  Linear Trapezoidal with Linear Interpolation
Weighting for lambda_z calculations:  Uniform weighting
Lambda_z method:  Find best fit for lambda_z,  Log regression

Summary Table
-------------
      Time         Conc.      Pred.    Residual      AUC       AUMC      Weight
-------------------------------------------------------------------------------
     0.0000       0.0000                           0.0000     0.0000
     0.2500        30.10                            3.763     0.9406
     0.5000        211.0                            33.90      15.07
     0.7500        1221.                            212.9      142.7
      1.000        1485.                            551.2      442.8
      1.500 *      1837.      1816.      20.72      1382.      1503.      1.000
      2.000 *      1615.      1704.     -89.15      2245.      2999.      1.000
      3.000 *      1621.      1500.      120.8      3863.      7046.      1.000
      4.000 *      1411.      1321.      90.29      5379. 1.230e+004      1.000
      8.000 *      763.0      793.3     -30.25      9727. 3.580e+004      1.000
      12.00 *      424.0      476.4     -52.45 1.210e+004 5.818e+004      1.000
      24.00 *      109.0      103.2      5.765 1.530e+004 1.044e+005      1.000

*) Starred values were included in the estimation of Lambda_z.

Final Parameters
---------------
Rsq                                                       0.9951
Rsq_adjusted                                              0.9941
Corr_XY                                                  -0.9975
No_points_lambda_z                                        7
Lambda_z                                                  0.1274
Lambda_z_lower                                            1.5000
Lambda_z_upper                                           24.0000


❝ For both cases we should consider contacting Pharsight’s support to clarify the issue.


Yes, I agree with you. However, if you don't agree to include Cmax to estimate lambdaz, then WNL (v5.x.x) should not be used for this purpose.

All the best,
-- Yung-jin Lee
bear v2.9.1:- created by Hsin-ya Lee & Yung-jin Lee
Kaohsiung, Taiwan https://www.pkpd168.com/bear
Download link (updated) -> here
Thread locked

Complete thread:

UA Flag
Activity
 Admin contact
22,957 posts in 4,819 threads, 1,636 registered users;
118 visitors (1 registered, 117 guests [including 8 identified bots]).
Forum time: 09:38 CET (Europe/Vienna)

With four parameters I can fit an elephant,
and with five I can make him wiggle his trunk.    John von Neumann

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5