Update acop2024 course

content/blog/2024-10-21-monolix2rx/index.html

@@ -128,7 +128,7 @@ <h2>Worked example</h2>
 <pre><code>## ℹ solving pred problem</code></pre>
 <pre><code>## ℹ done</code></pre>
 <pre class="r"><code>rx</code></pre>
-<pre><code>##  ── rxode2-based free-form 2-cmt ODE model ────────────────────────────────────── 
+<pre><code>##  ── rxode2-based free-form 2-cmt ODE model ────────────────────────────────────────────────────── 
 ##  ── Initalization: ──  
 ## Fixed Effects ($theta): 
 ##      ka_pop       V_pop      Cl_pop           a           b 
@@ -229,8 +229,8 @@ <h2>Worked example</h2>
 ## 
 ## ── Time (sec fit$time): ──
 ## 
-##            setup optimize covariance table compress as.nlmixr2
-## elapsed 0.002197    5e-06      7e-06 0.066    0.007       2.93
+##           setup optimize covariance table compress as.nlmixr2
+## elapsed 0.00165    3e-06      5e-06 0.046    0.006      2.082
 ## 
 ## ── Population Parameters (fit$parFixed or fit$parFixedDf): ──
 ## 
@@ -311,8 +311,8 @@ <h2>Worked example</h2>
 ## 
 ## ── Time (sec $time): ──
 ## 
-##            setup optimize covariance table compress as.nlmixr2
-## elapsed 0.002197    5e-06      7e-06 0.066    0.007       2.93
+##           setup optimize covariance table compress as.nlmixr2
+## elapsed 0.00165    3e-06      5e-06 0.046    0.006      2.082
 ## 
 ## ── Population Parameters ($parFixed or $parFixedDf): ──
 ## 

content/courses/acop2024/index.md

@@ -0,0 +1,77 @@
+---
+author: Matt Fidler, Bill Denney, Mirjam Trame, Theo Papathanasiou, Justin Wilkins
+categories:
+- workshop
+date: "2024-11-14"
+draft: false
+event: ACoP (2024)
+event_url: "https://www.go-acop.org/default.asp?id=46&keuze=meeting&mid=21"
+excerpt: This is the course at ACoP in Phoenix, Arizona on 11 November 2024.
+featured: true
+layout: single
+links:
+- icon: door-open
+  icon_pack: false
+  name: website
+  url: https://acop2024.eventscribe.net/agenda.asp?startdate=11/14/2024&enddate=11/14/2024&BCFO=&pfp=BrowsebyDay&fa=&fb=&fc=&fd=
+- icon: github
+  icon_pack: fab
+  name: code
+  url: https://github.com/nlmixr2/courses/tree/main/ACoP2024
+- icon: file-powerpoint
+  icon_pack: fa
+  name: powerpoint
+  url: https://github.com/nlmixr2/courses/raw/main/ACoP2024/Tutorial-nlmixr2_ACoP15.pptx
+location: "Phoenix, Arizona USA"
+show_post_time: true
+subtitle: "ACoP 2024"
+title: "Using Past Models to Bridge to Open Models and Open Science using nlmixr2"
+---
+
+## Workshop target audience
+
+Pharmacometricians/modelers with basic knowledge on model building,
+evaluation and qualification. Knowledge of `nlmixr2`, `Monolix` and/or
+`NONMEM` helpful. Basic knowledge of writing and executing R scripts
+is required.
+
+## Workshop overview
+
+Open science is a movement to make science available to all levels of
+society. The science in much of population-based pharmacometrics in
+the past has been focused on developing nonlinear mixed effects models
+in proprietary tools like `NONMEM` and `Monolix`. This makes it necessary
+to have licenses of whatever tool is being used to be able to explore
+models with your data. Special populations in low to middle income
+countries may not have access to these tools which makes analysis of
+additional clinical data in these regions more challenging. This
+tutorial discusses automated methods to import `NONMEM` and `Monolix` into
+the open-source framework `rxode2` and `nlmixr2` using packages like
+`nonmem2rx`, `monolix2rx` and `babelmixr2`. Once converted, you can use
+these models to make patient-based adaptive dosing decisions, simulate
+other dosing scenarios and even use the model to analyze new data and
+explore any regional differences in drug effect.
+
+## Learning Objectives
+
+- Participants learn the basics of how a `nlmixr2`/`rxode2` model is
+  written and can write a model themselves.
+
+- Participants will know how to import `NONMEM` and `Monolix` models into
+  the nlmixr2/rxode2 model function using `nonmem2rx` and `monolix2rx`
+
+- Upon completion, participants will know how to simulate new dosing
+  scenarios using `rxode2`
+
+- Upon completion, participants will know how to (re-)estimate new
+  data using `nlmixr2`
+
+- Participants will learn how to use imported models to design new
+  studies using `babelmixr2` and `PopED`
+
+- Participants learn how to individualize dosing clinically using
+  `posologyr`
+
+## Workshop materials
+
+The materials for the course are available in the [nlmixr2 courses repository](https://github.com/nlmixr2/courses/blob/main/ACoP2024/).