Developing AI Agents in Life Sciences (Gothenburg)

SciLifeLab Data Centre · Korallrevet, Natrium, Medicinaregatan 7B, Gothenburg · 2026-06-09

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Welcome

We are delighted to invite you to our hands-on workshop on Developing AI Agents in Life Sciences, organised by SciLifeLab Data Centre.

AI agents are emerging as autonomous systems that orchestrate scientific workflows by interacting with digital tools and data sources. In life science research, they can simplify complex analyses by automating data integration, run computational models, and coordinate experimental steps, making research pipelines more efficient and reproducible.

In this on-site workshop, held at Korallrevet, Natrium building (Medicinaregatan 7B) in Gothenburg, we will introduce and discuss AI agents in life science, and engage in collaborative practical sessions.

Welcome!

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Speakers & Facilitators

• Johan Alfredéen ([email protected]): Data Engineer (AI), SciLifeLab Data Centre
• Mahbub Ul Alam ([email protected]): Data Engineer (AI), SciLifeLab Data Centre
• Dinh Long Huynh ([email protected]): PhD Candidate, Uppsala University

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Event Details

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Target Audience

This workshop is open to researchers, PhD students, and research infrastructure staff interested in hands-on experience with AI agents. Participants from any university affiliation, as well as industry researchers, are welcome.

Prerequisites:

• Basic Python programming skills
• Familiarity with Jupyter notebooks is helpful
• You must bring your own laptop

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What You Will Learn

The workshop will feature a series of engaging presentations, interactive discussions, and collaborative sessions focusing on:

• Introduction to AI agent technologies
• Applications, opportunities, and challenges of AI agents in life science
• Hands-on tutorials with reasoning models, LangGraph, and MCP servers
• Discussions on the role of AI agents in shaping the future of life science

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Agenda

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Download Presentation Slides

Presentation 1 — Introduction: Exploring how AI agents can transform life sciences · Johan Alfredéen

Demonstration — AI agents in action · Mahbub Ul Alam

Hands-on Session 1 — Developing AI agents with LangGraph & ReAct · Dinh Long Huynh, Mahbub Ul Alam

Hands-on Session 2 — AI agent collaboration with the Model Context Protocol (MCP) · Mahbub Ul Alam, Johan Alfredéen, Dinh Long Huynh

Presentation 2 — Deploying AI Agents: Legal, Technical, and Practical Considerations · Johan Alfredéen

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Workshop Sessions

Each session directory contains its own detailed README.md with full instructions, notebook guidance, and troubleshooting.

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Getting Started: Docker Setup

All workshop materials run inside Docker containers. No local Python environment setup is required.

⚠️ Docker Desktop must be installed and running on your laptop.

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Step 1: Install Docker Desktop

Docker Desktop is the recommended way to run Docker on your personal machine. It includes everything you need: the Docker engine, CLI, and a graphical interface.

🍎 macOS

1. Go to https://docs.docker.com/desktop/install/mac-install/
2. Choose the installer for your chip:
   • Apple Silicon (M1/M2/M3/M4): download the Apple Silicon .dmg
   • Intel: download the Intel Chip .dmg
3. Open the downloaded .dmg file and drag Docker into your Applications folder
4. Launch Docker from Applications and follow the onboarding prompts
5. Verify the installation by opening a terminal and running:

   docker --version
   

🐧 Linux

Docker Desktop is available for Ubuntu, Debian, and Fedora.

1. Go to https://docs.docker.com/desktop/install/linux-install/ and select your distribution
2. Follow the distribution-specific instructions (typically adding the Docker apt/rpm repository and installing the package)
3. After installation, start Docker Desktop from your application launcher
4. Verify:

   docker --version
   

Alternatively, you can install Docker Engine directly (without the Desktop GUI) by following https://docs.docker.com/engine/install/. This is sufficient for running workshop containers.

🪟 Windows

1. Go to https://docs.docker.com/desktop/install/windows-install/
2. Download the Docker Desktop Installer
3. Run the installer. When prompted, ensure “Use WSL 2 instead of Hyper-V” is selected (recommended)
4. After installation, Docker Desktop will start automatically
5. Open PowerShell or Command Prompt and verify:

   docker --version
   

WSL 2 note: Docker on Windows works best with WSL 2 (Windows Subsystem for Linux 2). If it is not already enabled, Docker Desktop will guide you through enabling it during setup. More information at https://learn.microsoft.com/en-us/windows/wsl/install.

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Step 2: Ensure your API key is ready (on the day of the workshop)

You will be registered as a user in our SciLifeLab OpenLLM pilot program. Please make sure you have access to the API key. You will receive instructions by email on how to obtain it before the workshop.

⚠️ Optionally, you can also use your own OpenAI API key (for ChatGPT models) if you have one.

🔑 Do not share this key with others or commit it to any public repository.

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Step 3: Pull and Run the Workshop Images

We strongly recommend pulling the pre-built images from Docker Hub. This is the fastest way to get started and is the only setup we will support during the workshop.

⚠️ Pulling pre-built images from Docker Hub is the only setup we will support during the workshop due to time constraints.

Session 1: LangGraph Agent Development

Pull the image:

docker pull long2406/scilifelab-langgraph-workshop:v2

Run the container: replace sk-... with your Scilifelab Open LLM API key (mandatory) and OpenAI API key (optional)

docker run -p 8888:8888 \
  -e PILOT_API_KEY="sk-..." \
  -e OPENAI_API_KEY="sk-..." \
  long2406/scilifelab-langgraph-workshop:v2

Then open http://localhost:8888 in your browser and navigate to langgraph_lab.ipynb.

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Session 2: MCP Agent Collaboration

Pull the image:

docker pull mahbub1969/scilifelab-gothenburg-workshop-mcp:v1

Run the container

⚠️ Replace sk-... with your Scilifelab Open LLM API key (default, OPENLLM_API_KEY) and OpenAI API key (optional, OPENAI_API_KEY):

docker run -p 7860:7860 \
  -e OPENLLM_API_KEY="sk-..." \
  -e OPENAI_API_KEY="sk-..." \
  mahbub1969/scilifelab-gothenburg-workshop-mcp:v1

Then open http://localhost:7860 in your browser and navigate to 1-mcp-from-scratch/mcp_workshop.ipynb.

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Step 3 (Optional, not recommended): Build the Images Locally

If you prefer to build the images yourself from the provided Dockerfiles, you can do so as follows.

⚠️ Building locally is not recommended for the workshop. Build times can be significant and we cannot troubleshoot build issues during the session. Use the pre-built images above unless you have a specific reason to build locally.

Session 1:

cd Section_1_LangGraph/
docker build -t scilifelab-langgraph-jupyter .
# replace `sk-...` with your OpenAI API key
docker run -p 8888:8888 -e OPENAI_API_KEY="sk-..." scilifelab-langgraph-jupyter

Session 2:

cd session-2-mcp/
docker build -t scilifelab-gothenburg-workshop-mcp:v1 .
# replace `sk-...` with your OpenLLM API key
docker run -p 7860:7860 -e OPENLLM_API_KEY="sk-..." scilifelab-gothenburg-workshop-mcp:v1

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Repository Structure

/
├── README.md                        ← You are here
│
├── Section_1_LangGraph/             ← Session 1: LangGraph & ReAct agents
│   ├── README.md                    ← Full instructions for Session 1
│   ├── Dockerfile
│   ├── langgraph_lab.ipynb          ← Workshop notebook (exercises)
│   ├── langgraph_answer.ipynb       ← Reference solutions
│   └── ...
│
└── session-2-mcp/                   ← Session 2: MCP agent collaboration
    ├── README.md                    ← Full instructions for Session 2
    ├── Dockerfile
    ├── 1-mcp-from-scratch/          ← Main session notebook
    ├── 2-bonus-mcp-sdk-implementation/   ← Bonus: MCP Python SDK
    └── 3-bonus-mcp-serve-app-integration/ ← Bonus: SciLifeLab Serve + MCP

For detailed content, notebook guidance, and troubleshooting, please refer to the README.md inside each session directory.

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Questions

This event is organised by SciLifeLab Data Centre. For questions about the workshop content or the SciLifeLab Serve platform, contact us at [email protected].