3rd National Event | 17 October 2026 · Bern

Bits to
Breakthroughs.

A study-a-thon on data-driven approaches in health and medicine, connecting clinicians and data scientists.

Scientists collaborating in a lab environment

Live Data

OMOP.model_v3

Team analyzing data on screen

Turning collaboration into actionable outcomes.

Bits to Breakthroughs brings together clinicians, data scientists, and key stakeholders for an intensive study-a-thon. Our focus is squarely on collaboration, open science, and achieving reproducible outcomes in healthcare.

We believe that by sharing knowledge and avoiding duplicated effort, we can explore more meaningful questions and accelerate the path from raw data (bits) to genuine medical advancements (breakthroughs).

01

Connect

Bridging the gap between clinical expertise and data science capability.

02

Solve

Intensive, hands-on tackling of defined medical study questions.

Scientific Focus 2026

Sepsis Context &
Data Modelling

Medical Laboratory

Study Questions

Focusing on causal and observational design in a sepsis context. We aim to define rigorous questions that can be answered reliably with available data.

Data Charts and Graphs

OMOP Data Modelling

Bringing complementary perspectives around OMOP data modelling to ensure standardisation and seamless interoperability across systems.

Abstract Artificial Intelligence

AI Model Development

Exploring the development and validation of AI models built upon robust, harmonised data structures to support clinical decision-making.

When & Where

Conference Venue in Bern

17 October 2026

Full-day intensive study-a-thon

Bern, Switzerland

Detailed venue information provided upon successful registration.

Travel Information

Registration

Space is strictly limited to ensure effective, hands-on collaboration. Secure your spot early.

Register Interest

Featured Speakers

Organisers

Collaborators & Partners

Programme Overview

08:30

Welcome & Context Setting

Defining the core sepsis study questions and objectives for the day.

10:00

Data Deep Dive (OMOP)

Understanding the underlying data structure, terminologies, and inherent limitations.

13:00

Collaborative Modelling

Cross-functional teams work on specific problem sets, bridging clinical insight and data science.

16:30

Synthesis & Next Steps

Sharing preliminary findings, validating models, and planning future publications.