pkpdpkpd 20070404 22:52 Posting: # 627 Views: 8,527 

Is it possible to use WinNonLin to assess the achievement of steady state on the basis of predose concentrations? Regards, PKPDPKPD 
Helmut Hero Vienna, Austria, 20070405 02:30 @ pkpdpkpd Posting: # 628 Views: 7,741 

Dear PKPDPKPD! » Is it possible to use WinNonLin to assess the achievement of steady state on the basis of predose concentrations? Yes. Using the example of this post we have: +++ 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 Strg+F9) 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 'NonTransposed 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' steadystate. Now look at the 'Estimate'column, which gives a value of 0.018542 for slope. A common method for the assessment of SSconditions is either doing a ttest (0.05,2sided), 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: +++ 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 ASCIImodel  which is pretty simple: MODEL * HJ Weimann Drug concentrations and directly derived parameters In: W Cawello (ed.), Parameters for CompartmentFree Pharmacokinetics ShakerVerlag, Aachen pp 2338 (2003)— Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
pkpdpkpd 20070405 16:33 @ Helmut Posting: # 633 Views: 7,460 

Dear Helmut! Thanks for your instructions. However, I have two problems:
PKPDPKPD PS. In the linear regression while assessing the slope, should it be 95% or 90% CI? 
Helmut Hero Vienna, Austria, 20070405 17:16 @ pkpdpkpd Posting: # 634 Views: 7,502 

Dear PKPDPKPD! » Thanks for your instructions. However, I have two problems: » 1. The version 5.01 of WinNonLin that I have do not have "Linear" function in the PK/PD/NCA Wizard. Just looked it up in the release notes, linear models were introducted in v5.1 (23 Oct, 2006). If you have a valid license (which I assume), you may update at no costs. » 2. The approach I would like to use for the assessment of steady state is repeated measures ANOVA of log concentrations instead of linear regression you are describing, since I am comparing the predose concentrations in several subjects on three consecutive days. » If I have one dependent variable (concentration) and subject as a random effect (??), and day as a fixed effect (???), how can I use Lin Mix to do the calculations. OK, ANOVA is not included in WinNonlin; you will have to fight through a Linear Mixed Effects Model (which is always a little bit tricky). One hint: all effects are fixed! Since I haven't done this myself yet, maybe another member of the forum can fill in the gap? ...or ask Pharsight's support  and be patient! I know some colleagues are using repeated measures ANOVA; I never could understand why. The outcome is always a yes/no result. What if you get a significant result  would you really throw away the entire study? If you are testing individual subjects, you have the option  providing you have stated such a procedure in the protocol  to exclude only these subjects from the evaluation since they did not reach steady state. » In the linear regression while assessing the slope, should it be 95% or 90% CI? 95% since p = 1alpha, where alpha=0.05. This is only a convention. In BE we are only using a 90% CI, because in patients BA of the test can either be lower (5%) or higher (5%) then BA of the reference. Therefore the individual patient's risk is kept at 5%, but for the population of all patients the risk is 10% (2 x alpha). — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
pkpdpkpd 20070405 17:39 @ Helmut Posting: # 635 Views: 7,420 

Dear Helmut, Thanks once again. » OK, ANOVA is not included in WinNonlin; you will have to fight through a Linear Mixed Effects Model (which is always a little bit tricky). One hint: all effects are fixed! » Since I haven't done this myself yet, maybe another member of the forum can fill in the gap? » ...or ask Pharsight's support  and be patient! It's true. LinMix is a catastrophy and I am fighting through it. Till now not very succesfull. BEBAC members: please, help!!! » I know some colleagues are using repeated measures ANOVA; I never could understand why. » The outcome is always a yes/no result. » What if you get a significant result  would you really throw away the entire study? » If you are testing individual subjects, you have the option  providing you have stated such a procedure in the protocol  to exclude only these subjects from the evaluation since they did not reach steady state. An interesting approach. Till now (I am pretty fresh) have not seen any protocols with individual assessment of the achievment of steady state. Is it because it is more time consuming???? And what is about multiple comparisons in this case? » » In the linear regression while assessing the slope, should it be 95% or 90% CI? » » 95% since p = 1alpha, where alpha=0.05. This is only a convention. » » In BE we are only using a 90% CI, because in patients BA of the test can either be lower (5%) or higher (5%) then BA of the reference. » Therefore the individual patient's risk is kept at 5%, but for the population of all patients the risk is 10% (2 x alpha). Does it mean, that I use 95% CI when I assess steady state by subject and 90% CI when I assess by entire study? PKPDPKPD 
Helmut Hero Vienna, Austria, 20070405 18:40 @ pkpdpkpd Posting: # 637 Views: 7,488 

Dear PKPDPKPD! » » ...or ask Pharsight's support  and be patient! » It's true. LinMix is a catastrophy and I am fighting through it. Till now not very succesfull. Full ACK, and the manual isn't very helpful either. I guess Pharsight would call it 'steep learning curve' and want you to sign up in one of their courses... I'm waiting for a correct implementation of a paired design (e.g., comparing steady state AUC with single dose AUC in the same subjects) since February 25^{th}, 2007... » » I know some colleagues are using repeated measures ANOVA; I never could understand why. » » The outcome is always a yes/no result. » » What if you get a significant result  would you really throw away the entire study? » » If you are testing individual subjects, you have the option  providing you have stated such a procedure in the protocol  to exclude only these subjects from the evaluation since they did not reach steady state. » An interesting approach. Till now (I am pretty fresh) have not seen any protocols with individual assessment of the achievment of steady state. Is it because it is more time consuming???? And what is about multiple comparisons in this case? It's not time consuming (just ran 24 subjects on a 2x2.8GHz Xeon, 2GB RAM in <10 seconds). Whether you apply model 502 (v5.2) or an ASCIImodel of the linear regression, you'll end up with a nice table listing the estimated slopes and their CIs for all subjects. What do you mean with multiple comparisons? » Does it mean, that I use 95% CI when I assess steady state by subject and 90% CI when I assess by entire study? If you mean assessment of steady state I would always use the 95% CI (the 90% CI used in bioequivalence is a rare exception). You also may opt for a multivariate analysis based on the onesample Hotelling T^{2} statistic. Such an approach would not only give you information whether steady state was reached or not, but also when. Since this test is not included (and I guess will never be) in WinNonlin, you have to go for alternatives. The cheapest commercial package I know, supporting Hotelling's T^{2} is NCSS 2007; if you are familiar with the Rlanguage, you may misuse this package under the GPL. — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
pkpdpkpd 20070405 21:37 @ Helmut Posting: # 638 Views: 7,415 

Thank you, Helmut. 
Helmut Hero Vienna, Austria, 20070406 00:23 @ Helmut Posting: # 639 Views: 7,657 

» I'm waiting for a correct implementation of a paired design (e.g., comparing steady state AUC with single dose AUC in the same subjects) since February 25^{th}, 2007... Does Pharsight monitor this site? Just received the model specification from their support after 40 days of useless emails (RTFM); in case somebody needs it (a paired design is neither given in the manual, nor the support site): Bioequivalence Wizard > Type of Study > Parallel/Other Choose Treatment and Reference value > Next Drag 'subject' from the 'Variable Collection' to 'Classification Variables' Model Specification: subject+treatment > Next and proceed as usual WinNonlin's results are identical with NCSS 2001 and EquivTest/PK. — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
apapanas Junior Greece, 20180103 14:44 @ Helmut Posting: # 18136 Views: 1,712 

Dear Helmut, For your information, I discovered a defect in the calculation of univariate confidence intervals using WNL. I have already contacted Certara, who recognised the issue and shall proceed to relevant update. So, I would not recommend using the linear model 502 for confirmation of steadystate achievement for the time being. Kindest regards, Antigoni 
Helmut Hero Vienna, Austria, 20180104 17:11 @ apapanas Posting: # 18141 Views: 1,609 

Hi Antigoni, » […] I discovered a defect in the calculation of univariate confidence intervals using WNL. I have already contacted Certara, who recognised the issue and shall proceed to relevant update. So, I would not recommend using the linear model 502 for confirmation of steadystate achievement for the time being. Interesting. How did you discovered that? Using my example data in R:
In Phoenix/WinNonlin 8.0: Linear Model 502 Even in bloody M$Excel 2000 (!) I got an agreement with R up to the fifth significant digit:
— Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
mittyri Senior Russia, 20180104 23:13 @ Helmut Posting: # 18144 Views: 1,559 

Hi Antigoni and Helmut, That's really weird As I see the problem is in quantile function, looks like approximation is not correct for low DF R: > qt(0.025, 1:7) WNL 502: 16.50068 For compliance the same solution could be implemented as R did: For central qt, a C translation of Hill, G. W. (1970) Algorithm 396: Student's tquantiles. Communications of the ACM, 13(10), 619–620. altered to take account of Hill, G. W. (1981) Remark on Algorithm 396, ACM Transactions on Mathematical Software, 7, 250–1. — Kind regards, Mittyri 
Helmut Hero Vienna, Austria, 20180105 00:37 @ mittyri Posting: # 18147 Views: 1,564 

Hi Mittyri, » As I see the problem is in quantile function, looks like approximation is not correct for low DF Wow! R: for (df in 1:7) cat(sprintf("%9.6f", qt(0.025, df, lower.tail=FALSE)), "\n") Spreadsheets: M$Excel 2000 OO Calc 4.1.1 Gnumeric 1.12.15 tinv(x, y) was introduced as a custom function in PHX/WNL v6.4. Hence, no checking possible in earlier versions. However: v6.4 v7.0 v8.0 Since in my example both the estimate and its standard error are correct, something must be wrong ‘behind the curtains’ in PHX/WNL when calculating the CI. — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
Helmut Hero Vienna, Austria, 20180108 00:40 @ mittyri Posting: # 18148 Views: 1,419 

Hi Mittyri and Antigoni, » As I see the problem is in quantile function, looks like approximation is not correct for low DF Confirmed. I checked the 64bitversions of PHX/WNL 6.3, 6.4, 7.0, and 8.0 (Linear Mixed Effects and WNL Linear Model 502, 1–7 degrees of freedom). The critical tvalue is not reported in Model 502. But we can calculate it from the confidence limit(s), the estimate, and its standard error as (UnivarCI_Upper – Estimate) / StdError or (Estimate – UnivarCI_Lower) / StdError .tinv(0.025, df) introduced in v6.4 is practically correct.df R/OO/Gnumeric LME (rep’d) %RE 502 (calc) %RE tinv(0.025, df) %RE Given that, use only LME (map time as Regressor, concentration as Dependent, drag time from Regressors/Covariates to Model Specification). After execution I suggest these workarounds:
tinv(x, y) is three orders of magnitude “better” than what is given by LME/BE. Why is it not used?df R/OO/Gnumeric LME = BE %RE tinv(0.025, 28) %RE If you don’t trust in the open source software I used, below an excerpt of R.A. Fisher’s Statistical Methods for Research Workers (1934), the Geigy tables (1980), WolframAlpha, and UsableStats: df t(p 0.025) — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
apapanas Junior Greece, 20180110 12:47 @ Helmut Posting: # 18157 Views: 1,177 

Dear Helmut, Thank you for investigating the issue further and for providing recommendations! Antigoni 