Predicting synergistic drug combinations in glioblastoma

• PhD

Glioblastoma (GBM) remains one of the most lethal brain cancers, largely due to its treatment-resistant cellular heterogeneity. Building on pilot data where 80% of eight repurposed drugs—including anti-epileptics and anti-inflammatories—successfully inhibited growth in patient-derived neurosphere (PDN) models, this project will explore how GBM responds to these drugs and others at the single-cell level.

We will treat PDNs with selected compounds and generate single-cell RNA-seq data to capture dose-dependent, cell state-specific responses. Using AI-based methods, we will analyse these datasets to predict synergistic drug combinations tailored to each model. This project integrates wet-lab experimentation (drug screening, single-cell sequencing) with dry-lab analysis (AI-driven synergy prediction), aiming to uncover non-traditional, personalised therapeutic strategies for GBM and build a pipeline that connects functional data to precision drug discovery.

The Brain Cancer Research Laboratory (BCRL) develops computational and multi-omic approaches to improve diagnosis, treatment selection and monitoring for patients with brain cancer. Our research integrates single-cell and spatial transcriptomics, metabolomics, imaging and clinical data to understand tumour evolution, therapeutic response and resistance.

The BCRL lab is co-led by Dr Saskia Freytag, Dr Sarah Best and Dr Jim Whittle, bringing together bioinformaticians, laboratory scientists and clinician-scientists in a highly multidisciplinary environment. Key collaborations span major Australian neuro-oncology centres and international partners. Recent work includes generation of a single-cell and spatial atlas of glioma (Moffet et al., Neuro-Oncology Advances 2023 5(1):vdad117) and translational analyses from perioperative precision medicine trials in IDH-mutant glioma (Drummond et al., Nature Medicine 2025).