Hello Mark, In addition to the above suggestions, PsN sse script takes any rawres file given that it follows naming conventions (details are mentioned in sse user manual) or one could read the Covariance matrix into mrgsolve or RxODE and simulate with uncertainty as well.
Best Regards Mahmoud.Abdelwahab On Sat, Dec 17, 2022, 7:30 PM Mark Sale <mark.s...@certara.com> wrote: > Thanks Rob, > I need to do this programmatically (in R), for an automated method. > Computational load is an issue for using SIR or bootstrap. I did see that > you can do simulation only in SSE, and thought I could programmatically > write a rawres output file, in R, just sampling from the $COV output > parameters SEEs and use that. Using SSE with no-estimate_simulation is my > back up plan if I can't get NWPRI working. > Specifically, this works (I need the output tables for diagnostics, so > need the -keep_tables): > sse run1.mod -samples=5 -rawres_input=raw_results_run1.csv > -no-estimate_simulation -keep_tables > > I'm thinking that may be easier than trying to use NWPRI. > > thanks > > > Mark Sale M.D. > Vice President > Integrated Drug Development > mark.s...@certara.com > Remote-Forestville CA > Office Hours 9 AM – 5 PM Eastern Time > +1 302-516-1684 > www.certara.com > > > -----Original Message----- > From: Heine, Rob ter <r.terhe...@radboudumc.nl> > Sent: Saturday, December 17, 2022 7:51 AM > To: Leonid Gibiansky <lgibian...@quantpharm.com> > Cc: Mark Sale <mark.s...@certara.com>; nmusers@globomaxnm.com > Subject: Re: [NMusers] Simulate with parameter uncertainty > > [You don't often get email from r.terhe...@radboudumc.nl. Learn why this > is important at https://aka.ms/LearnAboutSenderIdentification ] > > Dear Mark, > > Another option to simulate with parameter uncertainty is to use the rawres > output file from a bootstrap or SIR procedure you obtained with PsN. This > can be done using the -rawres_input=… in combination with > -no-estimate_simulation option for SSE. It will use the set of parameter > values in the rawres file as input for simulation. > > Sincerely, > Rob > > > Op 17 dec. 2022 om 4:44 PM heeft Leonid Gibiansky < > lgibian...@quantpharm.com> het volgende geschreven: > > > > Is it is only CL (then you can just use SE and normal distribution) or > you need predictions and use whole parameter matrix (then you need to use > PRIORS): make sure to set TRUE=PRIOR on the simulation step). > > Leonid > > > > Roughly (See guide for IVAR value): > > > > $PRIOR TNPRI (PROBLEM 2) IVAR=2 PLEV=0.999 $MSFI ../.../FILE.MSF > > ONLYREAD $SUBROUTINES > > > > $PK > > ... > > $ERROR > > ... > > > > $PROBLEM XXX, simulations > > $INPUT > > $DATA .... REWIND IGNORE=C > > > > $THETA > > ... > > > > $OMEGA > > .. > > > > $SIGMA > > ... > > > > $SIMULATION (1334) (5778 UNIFORM) ONLYSIMULATION PARAFILE=ON > > RANMETHOD=P TRUE=PRIOR SUBPROBLEMS=3 > > > > $TAB FILE=...tab > > > > > > > >> On 12/17/2022 10:16 AM, Mark Sale wrote: > >> Hi, > >> I'm pretty sure this is possible, I think I even did it long ago, but > I need to simulate a model with parameter uncertainty, i.e., sample mean > and variance from prior distribution of typical value of CL, then sample > individual Cls from that distribution of mean/variance. Can anyone help me > with the code to do this? > >> Thanks > >> Mark > >> Mark Sale M.D. > >> Vice President > >> Integrated Drug Development > >> mark.s...@certara.com > >> Remote-Forestville CA > >> Office Hours 9 AM - 5 PM Eastern Time > >> +1 302-516-1684 > >> https://nam11.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww. > >> certara.com%2F&data=05%7C01%7Cmark.sale%40certara.com%7Caf45e1bf43604 > >> fb3f63508dae0467790%7C7287abd30220456e98514352bae208c9%7C1%7C0%7C6380 > >> 68890546783907%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2 > >> luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000%7C%7C%7C&sdata=l2TeAtlq2N > >> ltv%2FEC5Z9mZD7lk0r7tLz42hkiWYFfDgY%3D&reserved=0 > >> This message (including any attachments) may contain confidential, > proprietary, privileged and/or private information. The information is > intended to be for the use of the individual or entity designated above. 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