Congratulations Wenping and the nlmixr team.

Husain

From: owner-nmus...@globomaxnm.com <owner-nmus...@globomaxnm.com> On Behalf Of 
Sam Liao
Sent: Thursday, April 22, 2021 11:11 AM
To: Wang, Wenping <wenping.w...@novartis.com>; nmusers@globomaxnm.com
Subject: Re: [NMusers] nlmixr 2.0 in on CRAN

Dear Wenping,
Congratulation. Thanks for the hard work.

Best regards,
Sam
On April 22, 2021 4:56 AM Wang, Wenping < 
wenping.w...@novartis.com<mailto:wenping.w...@novartis.com>> wrote:


In August 2018, the nlmixr team announced the first baby step by nlmixr – the 
release of nlmixr 1.0. Today, we proudly announce the arrival of nlmixr’s 
adulthood: nlmixr 2.0 is here. It has taken a bit longer than we’d like to see 
nlmixr getting through its adolescence, but that day has arrived! Lots of hard 
work has gone into the new version over the past 2.5 years, and we think the 
pharmacometrics community will be very happy to see all the new functionality & 
features in nlmixr 2.0.

A few highlights include:
• Automatic covariate search with covarSearchAuto
• Boostrapping with bootstrapFit
• Time-varying covariates in SAEM
• Parallel SAEM

nlmixr 2.0 no longer needs Python for its symbolic algebra computations (e.g., 
calculating derivatives for FOCEi types of algorithms). This change not only 
makes nlmixr faster, it also leaves a smoother user experience and simplifies 
installation and maintenance.

For the geekier modelers among you, you’ll find a few more advanced tricks have 
been baked in:
• ETA support on dose-based parameters like lag time and infusion duration for 
FOCEi
• Support of lag/diff and NONMEM-style NEWIND flag
• More logical expression support including ifelse() and logical expressions 
(for example, KA = (FED==1)*KA1 + (FED != 1)*KA2)
• Mean model support (i.e. no ETAs) for FOCEi
• More types of residual model support in both SAEM and FOCEi
• Censoring support using CENS and LIMIT columns

As always, the nlmixr team are grateful for the heart-warming support we’ve 
received from our users. You are our strength and inspiration. Our goal here is 
to make nlmixr a PKPD modeling tool that is truly of the modelers, by the 
modelers and for the modelers.

We hope you’ll enjoy this youthful, vibrant yet mature nlmixr. Please continue 
to send us your ideas, suggestions and bug reports via our GitHub page.

Wenping Wang
On behalf of the nlmixr team


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