CRUK/SU2C Data for Children’s and Young People’s Cancer Programme Award

Funding over a maximum of five years to support the development of data/AI-driven approaches that aim to address common challenges in children’s and young people’s cancers.

Cancer Research UK (CRUK) and Stand Up to Cancer (SU2C) are co-funding the Data for Children’s and Young People’s Cancer Programme Award to support the development of novel data/AI-driven solutions that address common research challenges facing the children’s and young people’s cancer research community.

Funding is available over a maximum of five years to support innovative ideas and tools for data-driven cancer research to generate novel insights about children’s and young people’s cancers, while also creating or improving data and/or data resources for the wider research community. 

Applications can include both the creation of new data and/or the use of existing data, development of data tools, consent and governance methods, or analytical approaches, including AI. Proposals in target identification or AI implementation are particularly welcomed.

The award can support cleaning, annotation, curation, and linking of existing data, data storage costs, as well as facilitation of data sharing. Additionally, the award can fund the generation of new data and associated running costs of maintaining it. Proposed projects should focus on addressing at least one research question related to children’s and young people’s cancer and one data challenge.  

Applications are welcome from UK-based teams/consortia, and international collaborations and consortia including at least one UK collaborator. Applicants from any research area are eligible, including fields outside of cancer. 

The CRUK data strategy (pdf link) has a particular focus on optimising the value of cancer datasets, given that access to large-scale multimodal data is consistently identified as a critical need in developing and applying AI across the cancer research pipeline. 

Proposals should aim to improve survival and long-term quality of life for children and young people affected by cancer and explain how they will develop new, scalable and generalisable data solutions to common research challenges in children’s and young people’s cancers for the international research community. 

Research areas that could be considered include, but are not limited to:

• Generating or uniting research data to characterise and identify key features of critical biological differences between children’s and young people’s cancers and cancers in adults, with the potential of discovering novel druggable targets and pathways to develop more effective children and young people-specific treatments.
• Translation of identified targets and pathways specific to children and young people (target identification/validation/ drug screening).
• Data-driven approaches using genomic data to understand the penetrance of germline mutations in children’s and young people’s cancers.
• Generating or uniting research data to explore lead time bias in relapse and improved prediction (eg based on machine learning approaches) of high-risk cancers affecting children and young people.
• Generating or uniting long-term quality of life and treatment data of survivors of children’s and young people’s cancers to guide better treatment with long term impact in mind.

Data challenges that could be included as a component of the proposal include, but are not limited to:

• Data standardisation and linkage: Tackling the lack of standardised datasets and robust mechanisms for linking diverse data types (eg clinical, genomic, imaging) across different institutions and countries which is a major barrier to large-scale international research projects.
• Ethical and legal considerations around data sharing: Addressing complex issues related to consent and data access for children’s and young people’s cancer data, particularly in the context of cross-border data sharing.
• Multidisciplinary collaboration: Fostering partnerships that bring together children’s and young people’s cancer experts, data scientists, and computational biologists to ensure research is both clinically and biologically relevant as well as methodologically sound.
• Integration of routine clinical data: Developing effective methods for the collection and integration of real-world and routine clinical data with research-grade datasets.