Quantitative Systems Pharmacology Modeling Support
in Development of Novel Diabetes Treatments
Dr. Britta Goebel
Head of Translational Disease Modeling (Diabetes-CV & I&I)
at Sanofi, Frankfurt
Thursday Nov 14, 2019, 12:00 to 1:00 pm EST
(World Diabetes Day)
Register for free at https://www.rosa
Hi all,
Thank you for your suggestions I really appreciate it. I will also
have a look to these resources.
Thanks again,
Carlos
On Wed, 6 Nov 2019 at 17:21, Mark Sale wrote:
>
> good point Steve, no USEFUL (unbiased?) information.
> But, I'd suggest it is an error to include >LLOQ predose but
good point Steve, no USEFUL (unbiased?) information.
But, I'd suggest it is an error to include >LLOQ predose but exclude
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Hi all
In theory a sample that has an expected concentration=0 and if you using an
additive error then this sample will provide information about \sigma_add.
However, this will only be the case if the assay result is reported exactly as
is (which would allow negative observations). However, si
If >LLOQ has information, then !>LLOQ MUST also have information.
and Yes, we evacuated for 6 days, back home now.
Mark Sale M.D.
Senior Vice President, Pharmacometrics
Nuventra Inc.
2525 Meridian Parkway, Suite 200
Durham, NC 27713
Phone (919)-973-0383
ms...@nuventra.com
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Mark
I disagree (more than a little). If a sample is reported as BQL and the
expected value is 0 (i.e., pre-dose, not endogenous), what information is there
about assay precision. If the error model is additive (or additive +
proportional), the sample will contribute zero to the objective fun
Dennis,
I may have to disagree, a little. There is information, a little, in a pre dose
BQL, about assay precision. I think you might agree that is a pre dose sample
is NOT BQL (which happens), tells you (and NONMEM) something about the assay.
Converse, even a BQL predose sample has a small amou
Hi Carlos,
Adding to what the others suggested, please note that, if that EVID=0
record is the very first record for that patient, NONMEM will predict
all compartments to be empty (all amounts = 0) at that time (unless you
initialise as discussed below).
If indeed there were no doses before that s
Hi NMUsers community for you excellent suggestions. I will work through it.
Thanks,
Carlos
On Wed, 6 Nov 2019 at 15:12, Bill Denney wrote:
>
> Hi Carlos,
>
> It is commonly used. For most datasets, there will be at least one
> observation that occurs before dosing to estimate the baseline val
Dear Carlos,
You could also use an EVID=2 to do a read-out of a certain compartment.
Cheers,
Rob
-Oorspronkelijk bericht-
Van: owner-nmus...@globomaxnm.com Namens Bill
Denney
Verzonden: woensdag 6 november 2019 16:12
Aan: Carlos ST ; nmusers@globomaxnm.com
Onderwerp: RE: [NMusers] Using
Bill
I think that the issue is more complicated than you acknowledge.
Assuming that the drug is not an endogenous substance, the pre-dose
concentration is likely to be BQL. However, there are two kinds of BQL values:
1. Samples that are truly zero because they were obtained pre-dose
Hi Carlos,
It is commonly used. For most datasets, there will be at least one
observation that occurs before dosing to estimate the baseline value, and in
almost every scenario, the modeling dataset should mirror the real world
actions. So, there is no issue with it, and usually you will have an
Dear NMUsers,
I would like advice in the best practice to use evid 0 before dosing,
which is to say an observation just before a dosing (*to estimate the
value in that compartment just before dosing event).
Thank you,
Carlos,
Hi Ruben,
I'm using NM7.4.3. But would INTERACTION matter to POSTHOC estimation? I
personally don't think so. Could you maybe explain?
You are right it should be LOG(VAR). I made this typo when re-naming these
variables to make the code clearer before posting here. It was correct in my
origina
Hi Shan,
Constant should have no influence on estimation, from my understanding. I've
already omitted all constants terms. Thanks anyway for your information!
Warm regards,
Tingjie
On Wed, Nov 6, 2019, at 13:22, Shan Pan wrote:
> Dear Tingjie,
>
> I don't know the answer but this might be hel
Hi Tingjie,
You used METHOD=COND LAPLACE in the default posthoc estimate. Whether
INTERACTION is implied depends on your version of NONMEM. Could you check?
I do not entirely understand the following section:
$ERROR
IPRED = F ; Predicted DV
ADDI = 5.76 ; Variance of additive error
PROR = 0.039601
Dear Tingjie,
I don't know the answer but this might be helpful: see the link below on
slide 3 and annotation on the right side.
http://holford.fmhs.auckland.ac.nz/docs/modelling-likelihoods-using-nonmem-vi.pdf
"*Actually its not quite - 2LL but proportional to it. It is missing a
constant (-NOB
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