Gelomics Teams With Google Australia to Build AI for Cancer Trial Design

Gelomics has partnered with Google Australia on a cancer drug-discovery platform meant to identify which patient groups may respond to an experimental treatment. The company is targeting clinical-trial design first, while individual treatment guidance remains a longer-term goal requiring clinical validation.

A tissue model instead of a flat dish

The platform starts with LunaX, which grows three-dimensional human tissue models in a specialised gel, including tumours derived from patient biopsies. Google characterizes the approach as an alternative to conventional flat plastic dishes, which it says cannot reproduce how cells behave inside the body.

Gelomics says LunaX can establish standardised tissue models within two to three weeks and retain them for long-term testing. It uses Google Cloud’s Gemini Enterprise Agent Platform to predict and optimise the cell-culture conditions needed to produce those models; Gelomics says standardisation helps separate a drug effect from variation in the biological sample.

Connecting a biopsy to a trial cohort

Alongside the lab-grown model, Gelomics maps each original biopsy cell by cell with the Queensland Spatial Biology Centre. That produces molecular data on the arrangement of proteins and genes in a tumour. The company then trains machine-learning models to link those maps with laboratory-tested drug responses and clinical outcomes, with the goal of predicting drug efficacy from a molecular map alone.

Google and Gelomics position that prediction step as a way to design smaller, more targeted trials around patients most likely to benefit. They say this could reduce exposure to ineffective therapies, avoid losing viable drugs tested in unsuitable patient populations, and lessen reliance on animal testing. Those are intended benefits rather than reported trial outcomes.

Gelomics aims to release a prototype for early-stage drug development in mid-2027. The partnership builds on the company’s involvement in Google’s AI First Accelerator Program, making the next milestone a drug-development prototype rather than a system for clinical care.