RECOMBINE-X

Each year, children around the world are diagnosed with cancers for which effective treatments are lacking. Many drugs that appear promising in the laboratory ultimately fail to work for these patients. We believe this is partly because laboratory testing often does not consider how a drug behaves in the body or whether it reaches the tumour in sufficient concentrations. By combining AI, pharmacology and translational research, RECOMBINE-X aims to accelerate the development of better treatments for children with hard-to-treat cancers and identify new potentially effective combinations of existing medicines. Publicly available knowledge will be brought together in a comprehensive database accessible to the international pediatric oncology community.

Bringing together information and knowledge

RECOMBINE-X seeks to identify drug combinations that not only kill cancer cells but can also reach tumours at effective concentrations in a child’s body. To achieve this, RECOMBINE-X makes use of pharmacokinetic (PK) and pharmacodynamic (PD) knowledge available across thousands of scientific publications. RECOMBINE-X will use AI, specifically Natural Language Processing (NLP), to analyse this literature and extract information on how drugs behave in the body and how they act against tumours. This knowledge will be brought together in a comprehensive database that can be used to identify promising drug combinations for pediatric cancers.

The focus is on some of the most challenging childhood cancers. These cancers often remain difficult to treat because current therapies are not effective enough or cannot reach the tumour safely.

Functional testing

Modern cancer treatments are often based on genetic abnormalities, but not all children benefit from this approach. RECOMBINE-X therefore adds a “functional” layer by testing how tumour cells respond to different drug concentrations and combinations.

Candidate treatments will be tested using advanced preclinical models, including patient-derived organoids and mouse models created from tumour tissue donated through the Princess Máxima Center’s Tumor Donation Program. The project will also use innovative technologies such as microdialysis, programmable infusion systems and focused ultrasound to better understand drug exposure and treatment response.

By combining these data with the genetic and metabolic characteristics of tumour cells from these children, doctors can select treatments that match both the response of tumour cells to realistic drug concentrations in the body and the genetic profile of those cells.

Accelerating the development of safe and effective treatments

As coordinator, the Princess Máxima Center brings together expertise in pediatric oncology, pharmacology, computational biology, experimental validation and clinical translation. RECOMBINE-X supports the Máxima mission by accelerating the development of safer and more effective treatments through AI-driven analyses, advanced modelling and sustainable research infrastructure available to researchers worldwide

Partner box

University College London (UK), Leiden Academic Centre for Drug Research (NL), UMC Utrecht (NL), Amsterdam UMC (NL), Netherlands Cancer Institute (NL).