NONMEM Users Network Archive

Hosted by Cognigen

RE: PRED for BLQ-like observations

From: Bauer, Robert <Robert.Bauer>
Date: Fri, 20 Nov 2015 21:04:19 +0000

Unfortunately adding records to estimation slows down estimation even with MDV=1 records. Please do a search on MDV=101 option in nm730.pdf 1 (section Ignoring Non-Impact Records During Estimation (NM73)). These records will be used only on the $TABLE step.

Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics R&D
ICON Early Phase
Office: (215) 616-6428
Mobile: (925) 286-0769

From: owner-nmusers [mailto:owner-nmusers
Sent: Friday, November 20, 2015 12:39 PM
To: nmusers
Subject: Re: [NMusers] PRED for BLQ-like observations

Did you test the run time with double the records?
I would expect that the MDV=1 records would be largely ignored in the
estimation step and not contribute much to run time.

On 21-Nov-15 08:59, Pavel Belo wrote:
> Thank you Bill,
> In my case it exactly doubles the number of records... The records
> are daily measures and the code is running slow enough. I'll split the
> code into estimation part and one that that is redundant, but uses a
> larger file and creates an output. It will be something like
> I guess the best future way is modify something in NONMEM so there is
> an option to provide only PRED in the PRED column (version 7.4?).
> Thanks!
> Pavel
> On Fri, Nov 20, 2015 at 01:06 PM, Denney, William S. wrote:
> Hi Pavel,
> The easiest way that I know is to generate your data file with one
> set of rows for estimation with M3 and another row just above or
> below with MDV=1. NONMEM will then provide PRED and IPRED in the
> rows with MDV=1.
> Thanks,
> Bill
> *From:*owner-nmusers
> [mailto:owner-nmusers avel Belo
> *Sent:* Friday, November 20, 2015 11:47 AM
> *To:* nmusers com>
> *Subject:* [NMusers] PRED for BLQ-like observations
> Hello The NONMEM Users,
> When we use M3-like approach, the outputs has PRED for non-missing
> observations and something else for BLQ (is that PRED=CUMD?). As
> in the diagnostic figures PRED for BLQs looks like noise, I remove
> them. It is not always perfect, but OK in for most frequent cases.
> When we use count data such as a scale with few possible values
> (for example, 0, 1, 2, 3, 4, 5), it makes more sense to use PHI
> function (home-made likelihood) for all observations rather than
> to treat the count as a continuous variable an apply M3-like
> approach to 1 and 5 while only (as we know, they are like LLOQ and
> ULOQ). In this case, all PRED values look like noise. A hard way
> to replace the noise with PRED value is to simulate PRED for each
> point and merge them with the DV and IPRED data. Is there an easy
> way?
> (The model runs well and better than when the count is treated as
> a continuous variable.)
> Thanks!
> Pavel

Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53
email: n.holford<mailto:n.holford<>

Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models - tests of assumptions and predictions. Journal of Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin Pharmacol. 2015;79(1):18-27.
<br /><br />
ICON plc made the following annotations.
This e-mail transmission may contain confidential or legally privileged information that is intended only for the individual or entity named in the e-mail address. If you
are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or reliance upon the contents of this e-mail is strictly prohibited. If
you have received this e-mail transmission in error, please reply to the sender, so that ICON plc can arrange for proper delivery, and then please delete the message.

Thank You,

ICON plc
South County Business Park
Dublin 18
Registered number: 145835
Received on Fri Nov 20 2015 - 16:04:19 EST

The NONMEM Users Network is maintained by ICON plc. Requests to subscribe to the network should be sent to:

Once subscribed, you may contribute to the discussion by emailing: