Workshops

19 hands-on sessions from R/Pharma 2025

Explore all workshops from the R/Pharma 2025 conference, organized by theme. Each workshop includes detailed descriptions, prerequisites, key learning outcomes, and links to materials.

🤖 AI & Large Language Models

Getting Started with LLM APIs in R

Sara Altman (Posit PBC)

Beginner

Learn to integrate LLMs into R workflows using {ellmer}. Build chatbots, implement tool calling, and design effective system prompts. No AI background required!

Key Tools: {ellmer}, {shinychat}

Guided Tour to Building LLM-Based Tooling

Devin Pastoor, Xu Fei, Aathira Anil Kumar (A2-AI)

Intermediate

From prototypes to production: Build enterprise AI solutions bridging R and Python. GxP-compliant workflows with AWS Bedrock and MCP servers.

Key Tools: {ellmer}, AWS Bedrock, MCP

Integrating LLM with Clinical Data Review

Zhen Wu, Peng Zhang (CIMS Global)

Intermediate

Build {DataChat} - an R Shiny app for conversational clinical data exploration. Emphasis on data privacy, statistical validity, and RAG implementation.

Key Tools: {ellmer}, {shinychat}, {ragnar}

📊 Clinical Reporting & Analysis

Cardinal: Harmonizing Clinical Reporting

Abinaya Yogasekaram, Emily De La Rua

Beginner

Hands-on with standardized TLG templates using {gtsummary}. CDISC-aligned outputs for meta-analysis and regulatory submissions.

Key Tools: {cardinal}, {gtsummary}, {cards}

Advanced Clinical Reporting

David Gohel (Ardata)

Intermediate

Create sophisticated Word reports programmatically. Complex tables, ggplot2 integration, and complete CSR generation.

Key Tools: {officer}, {flextable}

Polished, Branded Documents with Quarto

Isabella Velásquez (Posit)

Beginner

Create websites, PDFs, presentations, and dashboards with consistent branding using brand.yml.

Key Tools: Quarto, brand.yml

Polars: Blazing Fast Python Framework

Michael Chow, Jeroen Janssens (Posit)

Intermediate

High-performance clinical trial data exploration with Apache Arrow and Great Tables integration.

Key Tools: Polars, Apache Arrow, Great Tables

pointblank: Understand, Validate, Document Data

Rich Iannone (Posit)

Intermediate

Data quality workflows that scale from quick checks to validating 35+ database tables daily. Beautiful automated documentation.

Key Tools: {pointblank}

🔧 Development & Validation

Introduction to Building R Packages

Nicola Rennie

Beginner

Transform scripts into packages! Learn structure, documentation, testing, and sharing. You’ll build your own package!

Key Tools: {devtools}, {usethis}, {testthat}

R Validation Discussion

Doug Kelkhoff (R Validation Hub)

Advanced

Discussion on Metric Repository for open quality assessment. Standardization and industry adoption strategies.

Key Tools: {riskmetric}, {riskassessment}

datasetjson: Read and Write CDISC Dataset JSON

Michael Stackhouse, Sam Hume, Nick Masel, Eli Miller

Intermediate

Work with Dataset-JSON format in R and Python. Modern data sharing for pharma workflows.

Key Tools: {datasetjson}, Python datasetjson

📈 Statistical Methods & Modeling

Flexible Trial Design with rpact

Daniel Sabanes Bove, Friedrich Pahlke

Intermediate

Clinical trial planning and simulation. Group sequential, adaptive designs, and p-value combination tests.

Key Tools: {rpact}, RPACT Cloud

Debugging Stan Programs

Daniel Lee

Advanced

Practical strategies for debugging Stan models. From non-identifiable parameters to runtime performance.

Key Tools: Stan, CmdStan

R Classification with tidymodels

Harshavardhan Bajoria

Beginner

Machine learning classification using the tidymodels framework. Preprocessing, training, and evaluation.

Key Tools: {tidymodels}, {recipes}, {parsnip}

Bayesian Survival & Multistate Models

Eric Novik, Jacqueline Buros-Novik, Juho Timonen (Generable)

Advanced

Bayesian time-to-event analysis with Stan. Multistate models for competing risks in clinical trials.

Key Tools: Stan, {bmstate}

🧬 Specialized Applications

SDTM Programming with {sdtm.oak}

Rammprasad Ganapathy

Intermediate

EDC-agnostic SDTM dataset creation. Modular programming framework with reusable algorithms.

Key Tools: {sdtm.oak}

Python for Clinical Study Report

Nan Xiao, Yilong Zhang

Intermediate

Python workflows for TFLs and eCTD packages. Modern toolchain with uv, polars, and plotnine.

Key Tools: Python, polars, plotnine, rtflite

Supercharge Shiny with HPC Cluster

Michael Mayer (Posit)

Advanced

Offload computations to HPC clusters from Shiny apps. Remote job submission and resource management.

Key Tools: Shiny, HPC, Posit Connect

From Data to Insights with {teal}

Nina Qi, Dony Unardi (Genentech)

Intermediate

Interactive clinical trial data exploration with the {teal} 1.0 framework. Build scalable, reproducible apps.

Key Tools: {teal}, Shiny

📋 Workshop Statistics

AI/LLM

Clinical Reporting

Development

Statistical/Specialized

🎯 Find Your Workshop

By Experience Level:

🟢 Beginner (5 workshops) - No prior specialized knowledge required
🟡 Intermediate (10 workshops) - Some experience with topic area
🔴 Advanced (4 workshops) - Significant experience recommended

By Topic:

Looking for AI/ML? → Start with Getting Started with LLM APIs
Need clinical reporting? → Try Cardinal TLGs or officer/flextable
Want to build packages? → Building R Packages
Interested in Bayesian methods? → Bayesian Survival Models

Popular Combinations:

AI Pathway: Getting Started → Guided Tour → Clinical Data Privacy
Reporting Pathway: Cardinal → officer/flextable → Quarto
Developer Pathway: Building Packages → Validation Discussion

Pro Tip

Many workshops have associated GitHub repositories with code examples and exercises. Look for the “Resources” section in each workshop page for direct links!

All workshops from R/Pharma 2025 Conference | Last updated: November 2025

--- title: "Workshops" subtitle: "19 hands-on sessions from R/Pharma 2025" toc: false --- Explore all workshops from the R/Pharma 2025 conference, organized by theme. Each workshop includes detailed descriptions, prerequisites, key learning outcomes, and links to materials. ## 🤖 AI & Large Language Models ::::: columns ::: {.column width="48%"} ### [Getting Started with LLM APIs in R](ai-llm/getting-started-llm-apis.qmd) **Sara Altman** (Posit PBC) [Beginner]{.badge .badge-beginner} Learn to integrate LLMs into R workflows using `{ellmer}`. Build chatbots, implement tool calling, and design effective system prompts. No AI background required! **Key Tools:** `{ellmer}`, `{shinychat}` ::: ::: {.column width="48%"} ### [Guided Tour to Building LLM-Based Tooling](ai-llm/guided-tour-llm-tooling.qmd) **Devin Pastoor, Xu Fei, Aathira Anil Kumar** (A2-AI) [Intermediate]{.badge .badge-intermediate} From prototypes to production: Build enterprise AI solutions bridging R and Python. GxP-compliant workflows with AWS Bedrock and MCP servers. **Key Tools:** `{ellmer}`, AWS Bedrock, MCP ::: ::::: ::: workshop-card ### [Integrating LLM with Clinical Data Review](ai-llm/llm-clinical-data-privacy.qmd) **Zhen Wu, Peng Zhang** (CIMS Global) [Intermediate]{.badge .badge-intermediate} Build **{DataChat}** - an R Shiny app for conversational clinical data exploration. Emphasis on data privacy, statistical validity, and RAG implementation. **Key Tools:** `{ellmer}`, `{shinychat}`, `{ragnar}` ::: ------------------------------------------------------------------------ ## 📊 Clinical Reporting & Analysis ::::: columns ::: {.column width="48%"} ### [Cardinal: Harmonizing Clinical Reporting](clinical-reporting/cardinal-tlgs.qmd) **Abinaya Yogasekaram, Emily De La Rua** [Beginner]{.badge .badge-beginner} Hands-on with standardized TLG templates using `{gtsummary}`. CDISC-aligned outputs for meta-analysis and regulatory submissions. **Key Tools:** `{cardinal}`, `{gtsummary}`, `{cards}` ::: ::: {.column width="48%"} ### [Advanced Clinical Reporting](clinical-reporting/officer-flextable.qmd) **David Gohel** (Ardata) [Intermediate]{.badge .badge-intermediate} Create sophisticated Word reports programmatically. Complex tables, ggplot2 integration, and complete CSR generation. **Key Tools:** `{officer}`, `{flextable}` ::: ::::: ::::: columns ::: {.column width="48%"} ### [Polished, Branded Documents with Quarto](clinical-reporting/branded-quarto.qmd) **Isabella Velásquez** (Posit) [Beginner]{.badge .badge-beginner} Create websites, PDFs, presentations, and dashboards with consistent branding using `brand.yml`. **Key Tools:** Quarto, brand.yml ::: ::: {.column width="48%"} ### [Polars: Blazing Fast Python Framework](clinical-reporting/polars-python.qmd) **Michael Chow, Jeroen Janssens** (Posit) [Intermediate]{.badge .badge-intermediate} High-performance clinical trial data exploration with Apache Arrow and Great Tables integration. **Key Tools:** Polars, Apache Arrow, Great Tables ::: ::::: ::: workshop-card ### [pointblank: Understand, Validate, Document Data](clinical-reporting/pointblank.qmd) **Rich Iannone** (Posit) [Intermediate]{.badge .badge-intermediate} Data quality workflows that scale from quick checks to validating 35+ database tables daily. Beautiful automated documentation. **Key Tools:** `{pointblank}` ::: ------------------------------------------------------------------------ ## 🔧 Development & Validation ::::: columns ::: {.column width="48%"} ### [Introduction to Building R Packages](development-validation/building-r-packages.qmd) **Nicola Rennie** [Beginner]{.badge .badge-beginner} Transform scripts into packages! Learn structure, documentation, testing, and sharing. **You'll build your own package!** **Key Tools:** `{devtools}`, `{usethis}`, `{testthat}` ::: ::: {.column width="48%"} ### [R Validation Discussion](development-validation/r-validation-discussion.qmd) **Doug Kelkhoff** (R Validation Hub) [Advanced]{.badge .badge-advanced} Discussion on Metric Repository for open quality assessment. Standardization and industry adoption strategies. **Key Tools:** `{riskmetric}`, `{riskassessment}` ::: ::::: ::: workshop-card ### [datasetjson: Read and Write CDISC Dataset JSON](development-validation/datasetjson.qmd) **Michael Stackhouse, Sam Hume, Nick Masel, Eli Miller** [Intermediate]{.badge .badge-intermediate} Work with Dataset-JSON format in R and Python. Modern data sharing for pharma workflows. **Key Tools:** `{datasetjson}`, Python datasetjson ::: ------------------------------------------------------------------------ ## 📈 Statistical Methods & Modeling ::::: columns ::: {.column width="48%"} ### [Flexible Trial Design with rpact](statistical-methods/rpact-trial-design.qmd) **Daniel Sabanes Bove, Friedrich Pahlke** [Intermediate]{.badge .badge-intermediate} Clinical trial planning and simulation. Group sequential, adaptive designs, and p-value combination tests. **Key Tools:** `{rpact}`, RPACT Cloud ::: ::: {.column width="48%"} ### [Debugging Stan Programs](statistical-methods/debugging-stan.qmd) **Daniel Lee** [Advanced]{.badge .badge-advanced} Practical strategies for debugging Stan models. From non-identifiable parameters to runtime performance. **Key Tools:** Stan, CmdStan ::: ::::: ::::: columns ::: {.column width="48%"} ### [R Classification with tidymodels](statistical-methods/r-classification-tidymodels.qmd) **Harshavardhan Bajoria** [Beginner]{.badge .badge-beginner} Machine learning classification using the tidymodels framework. Preprocessing, training, and evaluation. **Key Tools:** `{tidymodels}`, `{recipes}`, `{parsnip}` ::: ::: {.column width="48%"} ### [Bayesian Survival & Multistate Models](statistical-methods/bayesian-survival.qmd) **Eric Novik, Jacqueline Buros-Novik, Juho Timonen** (Generable) [Advanced]{.badge .badge-advanced} Bayesian time-to-event analysis with Stan. Multistate models for competing risks in clinical trials. **Key Tools:** Stan, `{bmstate}` ::: ::::: ------------------------------------------------------------------------ ## 🧬 Specialized Applications ::::: columns ::: {.column width="48%"} ### [SDTM Programming with {sdtm.oak}](specialized/sdtm-oak.qmd) **Rammprasad Ganapathy** [Intermediate]{.badge .badge-intermediate} EDC-agnostic SDTM dataset creation. Modular programming framework with reusable algorithms. **Key Tools:** `{sdtm.oak}` ::: ::: {.column width="48%"} ### [Python for Clinical Study Report](specialized/python-csr-submission.qmd) **Nan Xiao, Yilong Zhang** [Intermediate]{.badge .badge-intermediate} Python workflows for TFLs and eCTD packages. Modern toolchain with uv, polars, and plotnine. **Key Tools:** Python, polars, plotnine, rtflite ::: ::::: ::::: columns ::: {.column width="48%"} ### [Supercharge Shiny with HPC Cluster](specialized/hpc-cluster-shiny.qmd) **Michael Mayer** (Posit) [Advanced]{.badge .badge-advanced} Offload computations to HPC clusters from Shiny apps. Remote job submission and resource management. **Key Tools:** Shiny, HPC, Posit Connect ::: ::: {.column width="48%"} ### [From Data to Insights with {teal}](specialized/teal-framework.qmd) **Nina Qi, Dony Unardi** (Genentech) [Intermediate]{.badge .badge-intermediate} Interactive clinical trial data exploration with the `{teal}` 1.0 framework. Build scalable, reproducible apps. **Key Tools:** `{teal}`, Shiny ::: ::::: ------------------------------------------------------------------------ ## 📋 Workshop Statistics ::::::: {layout-ncol="4"} ::: stats-box **3** AI/LLM ::: ::: stats-box **5** Clinical Reporting ::: ::: stats-box **3** Development ::: ::: stats-box **8** Statistical/Specialized ::: ::::::: ------------------------------------------------------------------------ ## 🎯 Find Your Workshop **By Experience Level:** - 🟢 **Beginner** (5 workshops) - No prior specialized knowledge required - 🟡 **Intermediate** (10 workshops) - Some experience with topic area - 🔴 **Advanced** (4 workshops) - Significant experience recommended **By Topic:** - Looking for **AI/ML**? → Start with [Getting Started with LLM APIs](ai-llm/getting-started-llm-apis.qmd) - Need **clinical reporting**? → Try [Cardinal TLGs](clinical-reporting/cardinal-tlgs.qmd) or [officer/flextable](clinical-reporting/officer-flextable.qmd) - Want to **build packages**? → [Building R Packages](development-validation/building-r-packages.qmd) - Interested in **Bayesian methods**? → [Bayesian Survival Models](statistical-methods/bayesian-survival.qmd) **Popular Combinations:** - **AI Pathway**: Getting Started → Guided Tour → Clinical Data Privacy - **Reporting Pathway**: Cardinal → officer/flextable → Quarto - **Developer Pathway**: Building Packages → Validation Discussion ------------------------------------------------------------------------ ::: callout-tip ## Pro Tip Many workshops have associated GitHub repositories with code examples and exercises. Look for the "Resources" section in each workshop page for direct links! ::: ------------------------------------------------------------------------ *All workshops from R/Pharma 2025 Conference \| Last updated: November 2025*