Glioblastoma research

Join our AI moonshot to accelerate open science

Join our research projects to benefit the glioblastoma research and patient community.

Contribute to our key scientific goals

Goal 1

Develop a better understanding of long survivors
  • To identify those most likely to benefit from treatment / most at risk
  • To discover new biology of long survivors

AI capabilities & datasets

histology-based survival predictive models

Develop histology-based survival predictive models, using Owkin’s multiple-instance learning algorithm1

AI ready

Use interpretable AI models to identify associated histological biomarker(s)

AI ready datasets

Large dataset (>300 patients) that includes long survivors, with clinical and H&E data

Goal 2

Identify novel therapeutic targets in glioblastoma
  • Target identification using novel data modalities (e.g. spatial omics)
  • Associate the targets to novel, spatially-defined glioblastoma subtypes

AI capabilities & datasets

Targets and subgroups

Co-optimization and prioritization
of targets and subgroups using end-to-end machine learning methods

team of biologists

In-house team of biologists and pharmacologists, and wet lab capabilities to validate ML findings

MOSAIC

Multimodal and spatial dataset (100 patients, 6 modalities) from Owkin’s MOSAIC project

(1) Pierre Courtiol, et al. “Deep learning-based classification of mesothelioma improves prediction of patient outcome” Nat Med 25, 1519–1525 (2019)

Mission milestones

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May to June 2024
Get data AI-ready
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June to November 2024
AI model development and research
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November 2024 to April 2025
Target validation (wet lab)
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Groundbreaking publication
We aim to share the results of this research with the scientific community through submission for publication in peer-reviewed scientific journals.