Predict response across alternative cancer therapies
One patient.
Multiple possible outcomes.
Patient digital twins: modelling how the same patient may respond to different treatments, using multimodal data.
STARTING WITH BREAST CANCER
31 authorised options.
One individual treatment decision.
ESMO guidelines recommend an individual risk–benefit analysis for each patient, which grows more complex with every new approval.
31
Active substances authorised in the EU for breast cancer
Sources: EMA medicines database, 01.11.2026 (Aileen Health count); ESMO guideline, Loibl et al., Ann Oncol 2024.
Compare digital-twin predictions across therapies.
How it works
Retrospective model output on neoadjuvant clinical trial data (I-SPY2); research use only, not CE marked.
How to read the chart. Each dot is one patient, predicted under
two therapy options: standard of care (→) versus alternative (↑).
Continuous score 0–1: where 1 means predicted complete response.
Above the diagonal: predicted to respond better to the alternative.
Preferential responders (shaded): low predicted response under standard of care, high under the alternative.
ABOUT US
Built by people who know AI and oncology care
Founder-led and part of ABIGAIL4D, an EU Horizon project with clinical and research partners across Europe.
Our next stops
Upcoming events
Join us at one of our next stops.
4 Nov 2026
Munich
HTGF Digital Health Pitch Day 2026
5 Nov 2026
Linz
JKU Entrepreneurship Center Opening
6 Nov 2026
Amsterdam
EMA SME Info day
Past event
21 Oct 202622 Oct 2026
Barcelona
EIC Project Kickoff
Past event
22 Sep 2026
Vienna
Women in health IT Breakfast: AI in healthcare
Past event
10 Aug 202614 Aug 2026
Vienna
Office hackathon
Get notified when we have more news
