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  • [NMusers] NONMEM
    for other type events such as compartment resets 3 for reset events which re initialize the PK kinetic system and 4 for reset and dose events a combination of 1 and 3 SS is the steady state data item for PREDPP and can have 4 possible values 0 indicating that the dose is not a steady state dose 1 indicating a steady state dose with reset 2 indicating steady state dose without reset and 3 which is very similar to 1 The above is a very basic summary from the NONMEM online help which is accessed by the commands nmhelp SUPER nmhelp EVID nmhelp SS from the command prompt Have a look for more detail COVA and RATD have no special meaning in NONMEM and appear to have been user defined variables covariates perhaps supplied by the author of the quoted code Justin From Mark Sale Next Level Solutions mark nextlevelsolns com Subject Re NMusers NONMEM Date Thu 14 Sep 2006 08 21 14 0700 My 2 cents First you need to define what you mean by optimal Traditional statistical optimal design e g ANOVA is aimed at getting parameter estimates as precisely estimated as possible a laudable goal in traditional statistics nicely implemented in a number of applications I m most familiar with Steve Duffuls http www bichat inserm fr equipes Emi0357 download html but I ll let him tell you how wonderful it is The three central problems IHMO with existing methods are 1 Limited to D or ED or perhaps C S optimal for model parameters What if we want to get a model with the smallest mean absolute error What if we want a study design that estimates some other statistic survival time AUC difference between treatment A and placebo etc as precisely as possible 2 No little flexibility in sample number they address sample times only the sample number is usually fixed What if our question is the more realistic what is the optimal study design which I think means getting and adequate answer for the lowest cost to answer this question if samples cost 200 each and subjects cost 5000 to enroll and 1000 week to keep in the study 3 They don t tell you if a study is adequate only which design is best for a given number of subjects samples We have done a small demonstration project optimizing a BE study Essentially Find the optimal number of subjects number of samples sample times to result in a successful BE study e g 1 beta 90 1 alpha 90 given a specified cost of samples and subjects NCA pk was done Model also included uncertainty about model parameters The algorithm used for the optimization was my favorite algorithm Genetic algorithm Interestingly the resulting design was quite close to what we usually do except the GA answer had fewer sample times than the traditionally designed study and so was a little cheaper It also was clear that D optimal was very different from NCA optimal sampling times I haven t had time to continue persuing this any grad student interested I m happy to share the code that I have Mark Mark Sale MD Next Level Solutions LLC www NextLevelSolns com From Andrew Hooker andrew hooker farmbio uu se Subject Re NMusers NONMEM Date Thu 14 Sep 2006 18 28 51 0200 Hi Mark I agree with most of your assessment about the current state of optimal design The designs are generally based on getting the best possible parameter estimates of your model and it important to develop methods for looking at other test statistics Two points 1 In PopED www rfpk washington edu we have to ability to optimize over the number of samples per individual in a study the number of individuals in a study and other design variables other than sample times See M Foracchia A Hooker P Vicini and A Ruggeri PopED a software for optimal experimental design in population kinetics Comput Methods Programs Biomed 74 29 46 2004 2 To me it is not so surprising that the optimal design that you attempted using NCA resulted in sample times similar to the designs people come up with normally without any fancy optimal design for these studies because most people design their studies based on NCA type thought processes anyway The question that comes to mind is why shouldn t we use the information we gain from population mixed effect models in our design calculations It would be interesting to compare the performance of your NCA based design and the D optimal design you calculated Andy Andrew Hooker Ph D Assistant Professor of Pharmacometrics Div of Pharmacokinetics and Drug Therapy Dept of Pharmaceutical Biosciences Uppsala University Box 591 751 24 Uppsala Sweden Tel 46 18 471 4355 www farmbio uu se research php avd 5 From Mark Sale Next Level Solutions mark nextlevelsolns com Subject Re NMusers NONMEM Date Thu 14 Sep 2006 09 50 09 0700 Andy There are several practical obstacles to this The first reason that no one uses a formal optimization based on a pop pk model to optimize NCA or other study endpoints it that it is pretty hard We estimated saving about 10 of sample assay costs maybe 100 samples per study 10 000 dollars in a 500 000 study and the sample assay budget came from a different group than the people designing the study so the study designers didn t lose a lot of sleep over assay costs prefering the CYA approach It took me several of weeks of work to do the optimization another downside The second study optimization would obviously go a lot faster but it isn t clear that there is a business case for it until someone writes a general application to do it Hence my offer of any code I have to anyone who wants to pursue it It also is very computationally intensive running Monte Carlo simualtion on 1000 s of designs doing the pk and statistics for each design ANOVA for NCA etc Probably the pay off for BE studies is marginal The payoff for large expensive difficult to recruit studies may be significant and they wouldn t be much harder to optimize Another practical issue is that the stats groups were skeptical because we basically would control the SE of the AUC finding an optimal SE not a minimal value by controling sample number and times They told us that stats was responsible for estimating the SE of the parameters not clin pharm They prefered to use historical values for SE of AUC and worst case scenario at that and so the formal power analysis which was done by stats didn t reflect the optimization only the SE of the NCA quantities from an historical study These are all reasons why I gave up on this a while ago But I think in theory it is a very practical way to formally optimize study designs much more powerful than just doing some simulations in Trial Simulator and manually tweaking some study parameters Mark Sale MD Next Level Solutions LLC www NextLevelSolns com From Stephen Duffull stephen duffull stonebow otago ac nz Subject Re NMusers NONMEM Date Fri 15 Sep 2006 08 00 34 1200 Hi all The example you quote seems to be more suitable for producing a limited series of Monte Carlo simulations than for producing a truly optimal design If you want to do it in the most appropriate way you will need to use a tool designed specifically for the purpose I think it is worth a note here that in my experience of optimizing designs for both industry and academia I have never been asked to find an optimal design What I do get asked is to provide a sufficient design that requires minimum effort for example fewest patients reduced number of doses fewest samples per patient etc The term sufficient means a design that meets the needs for which the model is intended to be used It is also my experience that it is almost impossible to do this within any acceptable time frame using NONMEM or some other package that has MC sim estimation and that an information theoretic approach is both practical and very quick at doing this PopED http depts washington edu rfpk rd software popED html PFIM http www bichat inserm fr equipes Emi0357 download html Of course I have to plug POPT www winpopt com WinPOPT www winpopt com POPT requires MATLAB and WinPOPT runs independently of any other software Also I think that France Mentre has released PFIM OPT for S or R Steve Professor Stephen Duffull Chair of Clinical Pharmacy School of Pharmacy University of Otago PO Box 913 Dunedin New Zealand E stephen duffull otago ac nz P 64 3 479 5044 F 64 3 479 7034 Design software www winpopt com From Nick Holford n holford auckland ac nz Subject Re NMusers NONMEM Date Fri 15 Sep 2006 08 31 05 1200 Steve If I may split the academic hair a little more I suspect that in fact your collaborators would have initially asked you for an optimal design i e these are the words they would have used when asking you to help them But you would have offered a sufficient design as being good enough I accept that methods based on the Fisher information matrix FIM are much faster than brute force Monte Carlo MC methods but the FIM methods are limited to minimizing parameter precision as the objective There are other objectives for trial design e g power which can be tediously explored using MC methods but which are only indirectly optimized using FIM methods Nick Nick Holford Dept Pharmacology Clinical Pharmacology University of Auckland 85 Park Rd Private Bag 92019 Auckland New Zealand email n holford auckland ac nz tel 64 9 373 7599x86730 fax 373 7556 http www health auckland ac nz pharmacology staff nholford From Mark Sale Next Level Solutions mark nextlevelsolns com Subject Re NMusers NONMEM Date Thu 14 Sep 2006 13 49 20 0700 I agree with Steve optimal design for studies is not generally available Instead we use simulation to plagarize Steves term to find a sufficient design by tweaking parameters and doing MC simulation I would however suggest that given sufficient computational power formal optimization is possible on a reasonable time line a couple of days For most optimizations i e BE studies NCA pk studies dose response survival etc you won t use NONMEM anyway You use SAS or Splus in some non iterative alorithm like ANOVA that is very fast So for most trial optimizations you don t need the NONMEM estimation only the simulation But we currently don t have the tools to do this Mark Sale MD Next Level Solutions LLC www NextLevelSolns com From Stephen Duffull stephen duffull stonebow otago ac nz Subject Re NMusers NONMEM Nick If I may split the academic hair a little more Of course I suspect that in fact your collaborators would have initially asked you for an optimal design i e these are the words they would have used when asking you to help them But you would have offered a sufficient design as being good enough Sometimes but not always Many sponsors really do want the minimally effective design and don t ask for an optimal design And of course some sponsors know what they want but inadvertently use the term optimal anyway So I don t agree with your assertion here I accept that methods based on the Fisher information matrix FIM are much faster than brute force Monte Carlo MC methods but the FIM methods are limited to minimizing parameter precision as the objective Hair split you mean maximize precision Not true although I accept that this is their most common use in practice In addition to maximizing precision FIM based designs can be used to 1 determine designs for model discrimination 2 determine designs with minimum bias 3 determine designs for power to reject the null hypothesis for model building decisions only 4 determine designs that carry the highest probability of success GLMs And of course any combination of the above including with the standard maximizing parameter precision I m not of course advocating that FIM based methods should replace all MC methods but I think both have a complementary role Steve Professor Stephen Duffull Chair of Clinical Pharmacy School of Pharmacy University of Otago PO Box 913 Dunedin New Zealand E stephen duffull otago ac nz P 64 3 479 5044 F 64 3 479 7034 Design software www winpopt com From Stephen Duffull stephen duffull stonebow otago ac nz Subject Re NMusers NONMEM Date Fri 15 Sep 2006 09 25 45 1200 Mark I agree with Steve optimal design for studies is not generally available Instead we use simulation to plagarize Steves term to find a sufficient design by tweaking parameters and doing MC simulation I would however suggest that given sufficient computational power formal optimization is possible on a reasonable time line a couple of days I would suggest that using a information theoretic technique you would get rid of the simulation component completely and do this more efficiently using an FIM approach I do not advocate simulation where quicker methods are available If you use simulation then 1 how do you know what designs to choose 2 how do you determine when you have a minimally effective design could there be another design around the corner that you didn t think of which is more efficient Why not just let an FIM search do its business get the answer for the most efficient sufficient design In a sense the most efficient design is how you would determine optimal or best just that the design is cast from finding the minimum experimental effort rather than some other goal Steve Professor Stephen Duffull Chair of Clinical Pharmacy School of Pharmacy University of Otago PO Box 913 Dunedin New Zealand E stephen duffull otago ac nz P 64 3 479 5044 F 64 3 479 7034 Design software www winpopt com From Mark Sale Next Level Solutions mark nextlevelsolns com Subject Re NMusers NONMEM Date Thu 14 Sep 2006 14 55 07 0700 I would suggest that using a information theoretic technique you would get rid of the simulation component completely and do this more efficiently using an FIM approach I do not advocate simulation where quicker methods are available Absolutely the only problem is the quicker method often don t answer the question you want answered they tell you how to get the smallest SE of model parameters not how to do the cheapest most powerful study fastest If you use simulation then 1 how do you know what designs to choose You optimize based on user defined criteria 1 alpha 0 9 1 beta 0 9 minimal cost shortest duration 2 how do you determine when you have a minimally effective design could there be another design around the corner that you didn t think of which is more efficient That what optimization does I can reference you to a text GA unlike FIM does NOT guarantee the best answer the textbooks always say near optimal solution But some analysis more sophisticated than I understand done mostly at Illinois University has examined GA deceptive searches and you can be pretty sure that properly done GA is truly optimal but not guaranteed Also as an aside I have combined search algorithms and greatly increased the robustness of the search specifically addressing the problem you mention Why not just let an FIM search do its business get the answer for the most efficient sufficient design In a sense the most efficient design is how you would determine optimal or best just that the design is cast from finding the minimum experimental effort rather than some other goal Absolutely again if your goal is minimal SE of model parameters If your goal is cheapest most power fastest I m not sure FIM will work Mark Sale MD Next Level Solutions LLC www NextLevelSolns com From Gastonguay Marc marcg metrumrg com Subject Re NMusers NONMEM Date Thu 14 Sep 2006 19 12 58 0400 Steve I m curious to learn of examples where FIM based optimization methods have been useful for achieving designs that minimize bias 2 in your post below of parameter estimates It was my understanding that in order to assess bias of parameter estimates it is necessary to run batches of MC simulation estimation cycles and compare estimated values back to a reference true value e g simulation model parameter values Thanks in advance for your insight Marc Marc R Gastonguay Ph D President CEO Metrum Research Group LLC 2 Tunxis Rd Suite 112 Tariffville CT 06081 Direct 860 670 0744 Main 860 735 7043 Fax 860 760 6014 Email marcg metrumrg com Web www metrumrg com From Stephen Duffull stephen duffull stonebow otago ac nz Subject Re NMusers NONMEM Date Fri 15 Sep 2006 11 58 49 1200 Marc Thought that I might escape comment on this I m curious to learn of examples where FIM based optimization methods have been useful for achieving designs that minimize bias 2 in your post below of parameter estimates I know of no examples for NL MEM That doesn t mean it can t be done of course It was my understanding that in order to assess bias of parameter estimates it is necessary to run batches of MC simulation estimation cycles and compare estimated values back to a reference true value e g simulation model parameter values As a gross simplification I might suggest that bias in parameter estimates can arise from 2 main sources I am sure someone will correct me here 1 due to not finding the true maximum of the likelihood 2 due to model misspecification The latter case is a special construct since bias doesn t truly exist it

    Original URL path: http://nonmem.org/nonmem/nm/99sep132006.html (2016-04-25)
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  • [NMusers] importData in S as numeric format
    be able to project forward with ADDL rbind ing it to a matrix of the subject s observational data then doing sorts on ID and TIME to shuffle the lines into the appropriate position In using the following SPLUS code for the data file data csv the data are not read in as numeric I have constructed the file in EXCEL with missing observations as What changes are needed to the csv file or to the SPLUS R code to bring this in as numeric SubjInit AAA BBB CCC ID 2314 2315 2316 Dose 1500 1500 1500 Tau 6 6 6 Cmpnd 2 2 2 0 0 0 0 0 5 21 6 11 1 22 1 36 5 23 6 22 5 2 9 9 11 5 11 2 4 5 67 3 9 11 3 6 3 76 2 28 10 1 12 3 8 4 56 10 2 18 9 19 10 4 25 2 18 5 15 5 19 27 2 19 20 5 25 6 28 7 20 15 4 30 5 39 4 22 10 7 19 2 31 1 24 8 4 13 1 20 8 336 504 672 tab importData data csv

    Original URL path: http://nonmem.org/nonmem/nm/99sep082006.html (2016-04-25)
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  • [NMusers] NONMEM VI Progress Update
    bugs have been or will be corrected and we are in the process of obtaining a better understanding of the new estimation methods The documentation of NONMEM VI will be comprised of 1 a brief document titled Introduction to NONMEM VI prepared by Stuart Beal and edited by Alison Boeckmann and myself 2 a README file that provides instructions for installation 3 a revised and expanded NONMEM Users Guide VIII the Help Guide in pdf format 4 folders containing the individual help items in both ascii and html format html version made available by Niclas Jonsson and 5 the current versions of User Guides I VII in pdf format In addition the distributed NONMEM and NM TRAN code will retain most of the comments inserted by the authors of the code Stuart Beal and Alison Boeckmann respectively Over the next year some portions of NONMEM Users Guides I VII will be updated and will be distributed to licensed users when completed We estimate that documentation and testing of the final code for NONMEM VI Level 1 0 will be complete by mid October with distribution to licensed users during the last week of October Tom Ludden NONMEM Project Team ICON

    Original URL path: http://nonmem.org/nonmem/nm/99aug302006.html (2016-04-25)
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  • [NMusers] Can we increase maximum number of function evaluations?
    the objective function during the Estimation Step Default a generous number Each evaluation of the objective function requires one pass through the data set This is also referred to as a function evalua tion MAXEVAL 0 omits the Estimation Step it is useful with POSTHOC MAXEVALS 1 may be specified when a MSFI record is present It requests that NONMEM re use the value from the pre vious run and is the default with MSFI Second Mark has shown some verbatim code for increasing the number of differential equation evaluations used by the differential equation solver This has little to do with the job that NONMEM is doing i e estimating the model parameters but has to do with the work required to solve the differential equations Mark gives an example for increasing the rather small number of DE evaluations that is supplied by default The online help indicates the verbatim option FIRST should start immediately after the FIRST verbatim code Verbatim lines which must be positioned immediately after the declarations which are part of the normal subroutine header and prior to the FIRST executable statement of the subroutine must precede the first line of abbreviated code and must start with the line FIRST I am not sure if it makes any difference to do it the way that Mark wrote it However it is essential to have at least one blank between and COMMON If not then NM TRAN will treat this record as a Fortran comment statement Nick Nick Holford Dept Pharmacology Clinical Pharmacology University of Auckland 85 Park Rd Private Bag 92019 Auckland New Zealand email n holford auckland ac nz tel 64 9 373 7599x86730 fax 373 7556 http www health auckland ac nz pharmacology staff nholford From Bill Bachman bachmanw comcast net Subject RE NMusers

    Original URL path: http://nonmem.org/nonmem/nm/99aug272006.html (2016-04-25)
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  • [NMusers] Time to event variable
    anybody shed a light on how to model the multiple hazards i e multiple doses and different data structure with and with rechallenge Thanks a lot From Matthew Riggs riggsmm yahoo com Subject Re NMusers Time to event variable Date Fri 25 Aug 2006 05 55 28 0700 PDT Hi Wenhui There s an example that may help you by Cox and Sheiner Repeated measures time to event with time

    Original URL path: http://nonmem.org/nonmem/nm/99aug242006.html (2016-04-25)
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  • [NMusers] Transference of data into NONMEM
    www nextlevelsolns com downloads html Mark Sale MD Next Level Solutions LLC www NextLevelSolns com From Paul Westwood pwestwood02 qub ac uk Subject RE NMusers Transference of data into NONMEM Date 21 Aug 2006 15 06 32 0000 Thanks for the replies Tried what you suggested and it was saved as a prn file but i was then unable to open it Ran NONMEM and it got so far but then there seemed to be no space between the dose and the concentration values which caused an error with MDV and the number of characters Can you think what s happening or what i m doing wrong Paul From Mark Sale Next Level Solutions com Subject RE NMusers Transference of data into NONMEM Date Mon 21 Aug 2006 08 19 02 0700 Paul You need to right justify everything except any rows that are commented out as the first character in these rows must be in column 1 Excel by default left justifies text and right justifies numbers So if you don t right justify everything the numbers on the right will be adjacent to no space between any text for missing DVs or doses following it I prefer prn file over csv since I can read them more easily and I always hand verify some fraction of the data BTW you need to close the file in Excel before running NONMEM NONMEM doesn t know about sharing sort of like my children when it comes to files if it is open in Excel NONMEM will be unable to open it Mark Sale MD Next Level Solutions LLC www NextLevelSolns com From Bachman William MYD bachmanw iconus com Subject RE NMusers Transference of data into NONMEM Date Mon 21 Aug 2006 11 49 53 0400 The csv files are preferred

    Original URL path: http://nonmem.org/nonmem/nm/98aug212006.html (2016-04-25)
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  • [NMusers] Optimal study design software available now
    at www winpopt com POPT a MATLAB dependent version can also be downloaded at this site WinPOPT can be used to optimize designs over multiple drugs multiple responses from a single drug models defined by ODEs designs that are constrained for example to have fixed sampling times for designs after the first or a steady state dose for designs with multiple study arms WinPOPT can be run across a network

    Original URL path: http://nonmem.org/nonmem/nm/99aug212006.html (2016-04-25)
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  • [NMusers] Automated NONMEM model selection patent issued
    US patent office has granted patent 7 085 690 for Unsupervised machine learning based mathematical model selection http patft uspto gov netacgi nph Parser Sect1 PTO1 Sect2 HITOFF d PALL p 1 u 2Fnetahtml 2FPTO 2Fsrchnum htm r 1 f G l 50 s1 7 085 690 PN OS PN 7 085 690 RS PN 7 085 690 This method is described in the April 2006 issue of Journal of

    Original URL path: http://nonmem.org/nonmem/nm/97aug182006.html (2016-04-25)
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