Synthema

Synthetic hematological data
over federated computing frameworks

Synthetic hematological data
over federated computing frameworks
In 2020, haematological diseases made up 5% of global cancer cases, and their scattered data in Europe led to research and economic challenges
SYNTHEMA is here to break the data silos
Previous slide
Next slide

Our Mission

Establish a cross-border hub to develop and validate Artificial Intelligence techniques for anonymisation and synthetic data generation in rare hematological diseases.

SYNTHEMA aims to generate reliable, high-quality synthetic data that can shape new virtual patients to further enhance dia-gnostic capacity, assess treatment options and predict outcomes in rare hematological diseases.

The Challenge

Hematological diseases are a large group of disorders resulting from abnormalities in blood cells, lymphoid organs and coagulation factors.
They suffer from a relatively low number of patients and the prevalence of data silos in unconnected clinical sites and registries.

different disorders
0 +
are considered rare diseases
0 %

Our work in the rare disease space

We are devoted to expanding the landscape of personalized medicine in rare hematological diseases.
We aim to increase the number of existing samples in the rare hematological disease space.
SYNTHEMA focuses on two highly representative use cases: Sickle Cell Disease (SCD) and Acute Myeloid Leukaemia (AML).

Virtual patients

Novel methods to generate synthetic multimodal
clinical, omics & imaging data

Privacy-by-design

Built-in privacy through the combination of federated
learning (FL), secure multi-party computation (SMPC)
and differential privacy (DP)

Virtual patients

Novel methods to generate synthetic multimodal clinical, omics & imaging data

Privacy-by-design

Built-in privacy through the combination of federated learning (FL), secure multi-party computation (SMPC) and differential privacy (DP)

Ethics and data protection

Ensuring value-sensitive design for
AI development and GDPR compliance
for data collection and processing

Collaboration is key

Embracing open science practices and multidisciplinary
training in rare hematological

Ethics and data protection

Ensuring value-sensitive design for
AI development and GDPR compliance
for data collection and processing

Collaboration is key

Embracing open science practices and multidisciplinary training in rare hematological

A multidisciplinary team

Funded by the European Union under Horizon Europe, this initiative embodies the pan-European collaboration of top experts, selected for their acknowledged excellence and complementarity bringing knowledge, expertise and state-of-the-art clinical, computational, business, ethical and legal background while minimizing overlaps.
Years
0
Partners
0
Countries
0