Re: [NMusers] RE: question about random seed for simulation

From: Devin Pastoor <devin.pastoor_at_gmail.com>
Date: Fri, 10 Mar 2017 00:24:09 +0000

Hi Penny,

I would highly encourage you to check out mrgsolve. It will be the fastest
(and IMO easiest) to do flexible designs.

That said, given that you seem to just be changing the sampling, per your
email, why don't you just simulate the richest design you need, then in
post processing filter out various sub-designs as needed? That means no
need to mess with multiple simulations and normalizing seeds.



For example, on scenario at 2 and 11 hrs post dose, one 1.5, 12, etc, you'd
simulate 1.5, 2, 11, 12. This would also allow you easily handle many more
scenarios in a single simulation.

Furthermore, you can even flexibly control the sampling times on a
patient-by-patient level (eg if you were to recommend a sampling window) by
dynamically filtering. You could use code, in R approximately like:

library(dplyr)
library(PKPDmisc)

peak_time <- function(.nsamples = 1) {
# sample .nsamples values from the provided vector
 sample(c(1.5, 2), .nsamples)
}

peak_time <- function(.nsamples = 1) {
# sample .nsamples values from the provided vector
 sample(c(11, 12), .nsamples)
}

# data from nonmem saved to
output_df <- read_nonmem("outputtable")

# for fixed times
output_from_design <- output_df %>%
filter(TIME %in% c(2, 12))

# for flexible sampling per id
output_from_design <- output_df %>%
group_by(ID) %>%
filter(TIME %in% c(peak_time(), trough_time())

# do what you want with output_from_design, which will have random samples
from peak and trough for each individual)



This post-processing is not specific to nonmem, and can be used with any of
the simulation softwares.

Devin

On Thu, Mar 9, 2017 at 7:01 PM Kyle Baron <kyleb_at_metrumrg.com> wrote:

>
> To Ruben's question: mrgsolve simulates the subjects up front as well.
> The subjects are identical across runs if the seed and number of subjects
> does not change.
>
> An illustration:
> http://mrgsolve.github.io/2017/03/09/reproducible-results-with-set.seed/
>
> Best regards,
> Kyle
>
>
> On Thu, Mar 9, 2017 at 5:11 PM, Faelens, Ruben (Belgium) <
> Ruben.Faelens_at_sgs.com> wrote:
>
> Hi Penny,
>
>
>
> Nonmem indeed calculates each subject one after the other. The random
> values will therefore change. Maybe you can set the random seed every time
> you simulate t=0, based on the subject ID?
>
> This may also depend on your data file; have you tried ordering on time
> (so the first 50 rows are all t=0 for subject 1 to 50) ?
>
>
>
> This largely depends on the simulation software and its design:
>
> As an example: Simulo samples all subjects together at simulation start,
> after which it runs the trial design; so the same subjects are sampled
> independent of subsequent trial design.
>
>
>
> I do not know about other tools (TS.2, simulx, mrgsolve), maybe the
> authors of these tools can specify?
>
>
>
> Kind regards,
>
> Ruben Faelens
>
>
>
> *From:* owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com]
> *On Behalf Of *Zhu, Penny
> *Sent:* donderdag 9 maart 2017 19:19
> *To:* nmusers_at_globomaxnm.com
> *Subject:* [NMusers] question about random seed for simulation
>
>
>
> Dear All
>
> I have finished a multiple dose simulation for 600 subjects and want to
> perform a single dose simulation (different sampling time) on the same
> subjects (same ETA as the first simulation). I used the same seed for the
> simulation step, it turned out the first subject was the same and the rest
> of the subjects are not and I am not sure whether this was due to the fact
> that the two simulation has different number TIME records. If so, I wonder
> what is the proper way to set the simulation seed so that the ETAs for the
> second simulation will be identical to the first one.
>
>
>
> I know that I could output the individual parameter estimate from the
> first simulation and import them into the second one. But I was thinking
> if the random seed can be synchronized between the two simulation, it could
> be an easier solution.
>
>
>
> Your help is very much appreciated!
>
>
>
> Thank you very much and best regards!
>
>
>
> *Penny (Peijuan) Zhu, Ph.D.*
>
> Associate Director Clinical Pharmacology
>
>
>
> Cell: 862-926-9079 <(862)%20926-9079>
>
>
>
> PD Bio-Pharma CDMA
>
> Sandoz
>
> 1N025, 100 College Road West
>
> Princeton, NJ 08540
>
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>
>
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> --
> Kyle Baron, PharmD, PhD
> Senior Scientist
> Metrum Research Group
>
>

Received on Thu Mar 09 2017 - 19:24:09 EST

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