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Hi,

My colleagues and I were having a discussion on calculations regarding the omega and omegastderr output and getting this into useful terms that can help you better understand the variability for the purposes of reporting. We are hoping experts in the extranet community could help to clarify.

I know that the output on the omega block generates a variance.

For proportional/exponential error models

CV=sqrt(omega)*100

For additive error models

SD=sqrt(omega)

Are these conventions correct dependent the error model structure you select?

For the omegastderr, how does this term relate to the final parameter estimate? What math is involved to get this into an %RSE term?

To our understanding, for a given parameter

%RSE=(Omegastderr)/SQRT(Omega)*100

Is this correct? From what I can tell this is different than the calculation that is done with NONMEM output. Any insight would be greatly appreciated.

Lance

Hello,

I am running a 2-compartment linear model, when I don't click closed form to use differential equations, the model is not converging with error message:

Initial parameter values result in -LL = NaN

Can we explore the impact of introducing correlations between random effects in PK/PD modeling on the accuracy of predictions and the understanding of complex drug disposition mechanisms?

Hello, I am working on a model, and I need to test the model with plasma concentration to be log-transformed.

Is there an option in the software to transform drug exposure data from normal scale to log scale, or should it be done first before uploading the dataset?

Also, How can I transform estimated PK parameters back to normal scale after the analysis using the software?

Dear all,

For a popPK model I am working on, I estimated interoccasion variability (IOV) for CL for 4 different occasions, assuming the IOV estimates to be the same for all 4 occasions due to limited data availability. Therefore, I obtained 4 identical omega estimates and 4 identical standard error estimates for the four occasions (i.e. IOV on CL for occasion 1 =  IOV on CL for occasion 2 = IOV on CL for occasion 3 = IOV on CL for occasion 4). My understanding is that I only need to report one estimate and its standard error for IOV on CL as my model output, instead of reporting the same set of values 4 times defined by the occasions. However, I do not know what to report for the shrinkage associated with IOV on CL. In the Omega sheet, 4 different shrinkage values were shown associated with the 4 occasions, ranging from 0.3 to 0.9. From looking at published studies, people report only one shrinkage value for each IOV tested. How can I obtain an overall shrinkage value to report for the IOV on CL? The number of data points for each occasion are different (e.g. intense sampling on occasion 1 and 4, sparse sampling on occasion 2 and 3), in case this matters.

Thank you for your help!

I have some activity data from mice in time bins. The observed data is in percent of time they are mooving. If the mice are stimulated many will move around 100% of the time. However, some of the mice that moove 100% of the time are more stimulated than others so we observe a ceiling effect. So the real Emax is higher than the observed Emax which is limited by a ceiling of the measurements. I would like to convert my PD model with a ceiling effect so that. eg (0,0.3,0.9,1.2,1.5) preddicted from the model is converted to (0.30,90,100,100). I tried

logit(Emax*E/EC50+E)

or 

E= ln (EB / (1 - EB))

EB= Emax*E/EC50+E

However both ln and logit does not work in the model structure. Is there another way to do this effect prediction with a ceiling? 

BR Frederik

Hello, I have a question about communicating the covariate impact to people who are unfamiliar with the Nonlinear mixed effect methodology used in PopPk analysis.

So, suppose we have body weight influencing drug (X) clearance, and an increase in body weight is associated with a decrease in CL, with the impact estimated by the model (- 0.5).

Can we say that increasing body weight by 10 kg intervals results in a 5% reduction in drug clearance?

Thanks     

Hi all, 

1. What method does Phoenix use to assess significance of covariate relationships with PK parameters in pop PK model?

2. After I add a binary categorical covariate to the model. In the result tab, I can get a boxplot of "eta with cov" and "str with cov". What method did Phoenix to generate those plots and  Can I use those plots to assess the signification of correlation?

Thanks,

Linda

Lead users at each company should already have received this notification last month and reminder yesterday with Draft Release notes so check you junk folders if you have not seen this please.  If you want to be added to that distribution list then please contact me.

We will give a general session for all existing users to discuss these new features on Thursday at 10 am EST, the session will last no more than an hour and will be recorded.  You may register below.

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With the next release of Integral 23.10.1, Certara will release a new feature for its industry-leading data repository that will support data storage requirements where 21 CFR (Code of Federal Regulations) Part 11 signature compliance is not necessary. The feature will allow specifically licensed Integral users to interact with designated folder structures without needing to securely sign for every interaction.  This feature will be available to both fully licensed users and partners, and the feature will work in the same repository where eSignature can still be required for 21 CFR Part 11 clinical studies.

For our users to preview this,  on Friday, 13th October, we propose to upgrade www.integral-staging.certara.com/ to the 23.10.1 release candidate, please anticipate a short down time from 11a.m EDT when the repository will be unavailable.

User action will be required: 

Complete and save work, and logout before 11 am (EST)

The Phoenix Integral 23.10.1 plug-in (or Integral Client 23.10.1) will be required and we will distribute the download links shortly.
Be sure to use the most recent versions of Phoenix 8.2.2, or 8.3.4, 8.3.5 or 8.4 with 23.10.1, prior versions are not tested or supported with this version of Integral. 

Thanks, Simon DAVIS

Senior Manager, Support

Greetings,

I'm developing a model in which the parent drug is metabolized to an active metabolite and a portion of the oral dose is metabolized in the GI to the active metabolite. I am trying to model the amount that is metabolized from the dose in addition to remaining amount goes to the central compartment of the parent drug.

I found this model created by one member who tried to build the structural model using graphical model, however, he did not account for fraction of the dose went to the parent and metabolite compartments. 

Can I get help on how to model the fraction formed?

I am attaching the model and a schematic description of a model that shows the structural model details.

Hello,

I am working on an indirect response model (limited inhibition of Kin), I have baseline values for each subject measured at the start of study. I need to use these values and fix them as E0 where E0 = Kin/Kout so that I can only estimate either Kin or Kout but not both at the same time.

I think there is a way to have these baseline values in a separate column in dataset and set them as covariate in the model code text. Can someone please help me with an example PML code that I can use to accomplish this? 

For dataset, do I add these at each timepoint for each individual as I would for other covariates or only at time=0 where they are actually measured?

If my thinking of approaching this is off, how can I take care of this? I don't want to fix E0 to a single value without implementing the interindividual variability observed with baseline measurements. 

Thanks a lot

Hello,

I am attempting to save relevant modeling plots as vector images. I have tried a couple of things without success

1. Print PDF (does not show up as vector image)

2. Export as JP or PNG (these are not vector files)

3. Copy high resolution image and paste to word document - this does produce a vector image but it is cut off (see file attachment).

Anyone else encounter this issue? Trying to fix this instead of using a third-party licensed program to convert the non-vector output into vector

In a recent training it became evident that some users had not found the folder referenced in;   C:\Program Files (x86)\Certara\Trial Simulator\Docs\Trial Simulator Examples Guide.pdf

If you browse to C:\Users\Public\Documents\Certara\Trial Simulator Projects\Examples  you’ll find over 30 completed projects;

 Simon.

Hi Experts,

Could you please give me some suggestions about my mistake when running modeling?

why is the %CV so high in the Theta sheet? 

Appreciate your help!

Drug administration by IV and dosage is 0.9mg/kg. Cmax=19ug/mL.

 Hi there,

Could you illustrate to make the Phoenix equivalent to this NONMEM twist,  to get the the average concentration calculated on the fly, in period btw. current and since last effect response record.

Thx

Thomas

$PK

IF(NEWIND.NE.2)THEN ; set up variables for new subject

LAUC = 0 ; previous AUC

LTM = TIME ; previous time

LAVE = 0 ; average concentration since previous record

ENDIF

KA=THETA(1)

CL=THETA(2)

V=THETA(3)

$DES

DADT(1)=-KA*A(1)

DADT(2)=KA*A(1)-CL/V*A(2)

DADT(3)=A(2)

$ERROR

CP=A(2)/V

AUC=A(3)/V

DTIM = TIME - LTM ; Time difference

DAUC = AUC - LAUC ; Difference in AUC

IF(DTIM.EQ.0)THEN

CAVE = LAVE ; Time has not changed, average concentration is the same

ELSE

CAVE = DAUC/DTIM

ENDIF

; Record current AUC and TIME for next call

LAUC = AUC

LTM = TIME

LAVE = CAVE

BASE = FID1

EFF = EM*CAVE**HILL/(EC**HILL+CAVE**HILL)

IPRE = BASE - EFF

IF(IPRE.LT.0) IPRE=0

Y = IPRE + EPS(1)