Applied Modelling in Drug Development

Flexible regression modelling in Stan via brms

Editors

Sebastian Weber - sebastian.weber@novartis.com

Björn Holzhauer - bjoern.holzhauer@novartis.com

Lukas Widmer - lukas_andreas.widmer@novartis.com

Andrew Bean - andrew.bean@novartis.com

Published

October 6, 2025

Preface

This website contains materials that were developed to accompany a series of workshops held in the Analytics department at Novartis over 2022-2024, illustrating the utility of the R package brms for solving drug- development problems. In order to highlight the versatility of that package, we have developed a collection of case studies covering a diverse set of clinical questions that were addressed via Bayesian modelling with the brms package.

Courses in Paris (France) October 8^th 2025, Graz (Austria) September 14^th 2025, Paris (France), July 4^th 2025, Göttingen (Germany), Dec 5/6^th 2024 and at JSM (Portland, OR), Aug 5^th 2024

Past course we offered recently:

Pre-conference course at the 10th Statistics & Biopharmacy conference on October 8th 2025 in Paris
Pre-conference course at the ROeS Conference 2025 on September 14th 2025.
Slides, Exercises, Additional material (see readme)
Tutorial at the “Stan4PMX workshop”.
Slides, exercises & additional material (see readme)
A course at the workshop “Hierarchical models in preclinical research” of the IBS-DR working groups Non-clinical statistics and Bayes Methods on December 5/6^th. The materials are available here: Slides & additional material (see readme)
A short course at the 2024 Joint Statistical Meetings in Portland on August 5^th. The materials are available here: Slides & additional material (see readme)

Navigating the site

The material is organized as follows:

1 Introduction introduces brms and the objectives of these vignettes
2 Basic workflow highlights the basic workflow (analysis steps and syntax) for carrying out an analysis with brms
The next series of sections contain the case studies. You can find a listing with descriptions on this page.
Sections 18 Exposing stan code and 19 Parallel computation cover more technical topics, such as exposing and injecting custom stan code to brms models, and efficient parallel computation to support sampling in brms.

Updates

This web-site is intended as a live document with updates as appropiate. Key changes to the web-site are tracked here:

8th August 2025: New case studies
- 7 Nuisance parameters, expected power and the “significance threshold”
- 17 Difference in proportions from a fitted logistic regression
13th January 2025: Linked materials from the course in Göttingen in December 2024.
31st July 2024: Linked materials from JSM Portland 2024 short course
5th June 2024: Added 8 Probability of success from a single arm trial on assessing probability of success of in Phase-III based on a single-arm trial in Phase-II
29th April 2024: Third edition course from Paul Bürkner with the new case studies on probability of success, meta-analytic priors with covariates & time-to-event modelling in Oncology phase I dose-escalation. Pre-read version.
19th April 2024: First public version at opensource.nibr.com/bamdd
5th January 2024: Release web-site in more modern quarto book based format
26th April 2023: Second edition course from Paul Bürkner with the new case studies on MMRM, time-to-event data, surrogate endpoint meta-regression and network meta-analysis
27th April 2022: First release with course from Paul Bürkner

License information

The material on this website is provided under a CC BY 4.0 license
The source code is provided under a GPL-2 license

--- format: html: author-title: "Editors" --- # Preface {.unnumbered} This website contains materials that were developed to accompany a series of workshops held in the Analytics department at Novartis over 2022-2024, illustrating the utility of the R package `brms` for solving drug- development problems. In order to highlight the versatility of that package, we have developed a collection of case studies covering a diverse set of clinical questions that were addressed via Bayesian modelling with the `brms` package. ::: {.content-visible when-profile="public"} ::: {.callout-tip} ## Courses in Paris (France) October 8th 2025, Graz (Austria) September 14th 2025, Paris (France), July 4th 2025, Göttingen (Germany), Dec 5/6th 2024 and at JSM (Portland, OR), Aug 5th 2024 Past course we offered recently: 1. Pre-conference course at the [10th Statistics & Biopharmacy conference](https://snb2025.sciencesconf.org) on October 8th 2025 in Paris * [Slides](workshops/paris2025snb/slides/bamdd_paris2025.html) * [Exercises](workshops/paris2025snb/exercises/bamdd_paris2025_exercises.html) * [Additional material (see readme)](https://github.com/Novartis/bamdd/tree/main/workshops/paris2025snb) * [R setup instructions](workshops/paris2025snb/exercises/bamdd_paris2025_exercises.html#/r-session) 2. Pre-conference course at the [ROeS Conference 2025](https://roes2025.at) on September 14th 2025. [Slides](workshops/graz2025/slides/bamdd_graz2025.html), [Exercises](workshops/graz2025/exercises/bamdd_graz2025_exercises.html), [Additional material (see readme)](https://github.com/Novartis/bamdd/tree/main/workshops/graz2025) 3. Tutorial at the ["Stan4PMX workshop"](https://stan4pmx2025.sciencesconf.org). [Slides](workshops/paris2025/slides/bamdd_paris2025.html), [exercises](workshops/paris2025/exercises/bamdd_paris2025_exercises.html) & [additional material (see readme)](https://github.com/Novartis/bamdd/tree/main/workshops/paris2025) 4. A course at the workshop ["Hierarchical models in preclinical research"](https://www.biometrische-gesellschaft.de/arbeitsgruppen/bayes-methodik/workshops/2024-goettingen.html) of the IBS-DR working groups Non-clinical statistics and Bayes Methods on December 5/6th. The materials are available here: [Slides](workshops/goettingen2024/slides/bamdd_goettingen2024.html) & [additional material (see readme)](https://github.com/Novartis/bamdd/tree/main/workshops/goettingen2024) 5. A short course at the 2024 Joint Statistical Meetings in Portland on August 5th. The materials are available here: [Slides](workshops/jsm2024/slides/bamdd_jsm2024.pdf) & [additional material (see readme)](https://github.com/Novartis/bamdd/tree/main/workshops/jsm2024) ::: ::: ## Navigating the site The material is organized as follows: - @sec-introduction introduces `brms` and the objectives of these vignettes - @sec-basic-workflow highlights the basic workflow (analysis steps and syntax) for carrying out an analysis with `brms` - The next series of sections contain the case studies. You can find a [listing with descriptions on this page](src/02_case_studies.qmd). - Sections @sec-stan-code and @sec-parallel cover more technical topics, such as exposing and injecting custom stan code to `brms` models, and efficient parallel computation to support sampling in `brms`. ## Updates This web-site is intended as a live document with updates as appropiate. Key changes to the web-site are tracked here: ::: {.content-visible when-profile="public"} - 8th August 2025: New case studies * @sec-power-expected * @sec-diffp - 13th January 2025: Linked materials from the course in Göttingen in December 2024. - 31st July 2024: Linked materials from JSM Portland 2024 short course - 5th June 2024: Added @sec-pos on assessing probability of success of in Phase-III based on a single-arm trial in Phase-II - 29th April 2024: Third edition course from Paul Bürkner with the new case studies on probability of success, meta-analytic priors with covariates & time-to-event modelling in Oncology phase I dose-escalation. Pre-read version. - 19th April 2024: First public version at [opensource.nibr.com/bamdd](http://opensource.nibr.com/bamdd) - 5th January 2024: Release web-site in more modern quarto book based format - 26th April 2023: Second edition course from Paul Bürkner with the new case studies on MMRM, time-to-event data, surrogate endpoint meta-regression and network meta-analysis - 27th April 2022: First release with course from Paul Bürkner ::: ::: {.content-visible when-profile="public"} ## License information - The material on this website is provided under a CC BY 4.0 [license](https://github.com/Novartis/bamdd/tree/main/docs/public/LICENSE) - The source code is provided under a GPL-2 [license](https://github.com/Novartis/bamdd/tree/main/LICENSE) :::