How can we harness the value of data to improve cancer care? What quality requirements must be adopted to ensure data are comparable, transferable, and consistently reliable? And what role will AI and data play in transforming healthcare and cancer care on a global scale?
During our “Transforming Cancer Care with AI and Data” session at the Global Health Connector Digital Summit last week, global leaders shaping the next generation of cancer care came together virtually to explore these questions. Let’s explore the key takeaways.
The session was co-hosted by All.Can International and moderated by its CEO, Eduardo Pisani, who highlighted the tremendous value that large-scale data collection brings to cancer patients, from prevention and early detection to treatment and survivorship. Also, data helps in improving health system efficiency by identifying what works best:
‘’Strong data systems are an essential investment for the future of cancer care, especially as AI and deep learning support prevention, diagnosis, and follow-up.’’
Eric Sutherland, Senior Health Economist, OECD, stressed that although health generates 30% of global data, only a fraction is used, meaning huge opportunities are being missed. The real barriers are not laws like GDPR but inconsistent interpretations, poor coordination, and organisations defaulting to “no” due to unclear risk guidelines. He called for harmonised processes under the European Health Data Space, clear accountability, and strong public trust.
His core message: using data responsibly is essential, and consistent implementation across Europe is the key to improving cancer care.
Professor Mark Lawler, Professor of Digital Health & Chair in Translational Cancer Genomics at Queen’s University Belfast, highlighted how data must be turned into intelligence to drive better cancer outcomes. Using international benchmarking, he showed that consistent, long-term cancer policies—like those implemented in Denmark—lead to major improvements, whereas fragmented strategies hinder progress.
He then discussed the European Cancer Pulse, a tool mapping cancer inequalities across Europe. Mark showcased OneLondon as an example of digital transformation reducing administrative burden, saving significant time and money, and allowing clinicians to focus more on patients.
Addressing AI, he warned that without careful governance, digital tools could widen inequalities. He stressed involving communities and ensuring equitable digital access.
Franziska Evans, a cancer survivor and Senior Entrepreneur in Residence at DeepTech Startups, Fraunhofer Heinrich Hertz Institute HHI, highlighted that AI’s potential in oncology remains largely untapped because the underlying health data is fragmented and not fit for purpose. She stressed that only a small fraction of deep-tech innovations reach patients due to poor data quality, high costs, and slow regulatory pathways.
She called for interoperable data infrastructure, clearer regulations, and patient-centred design to ensure AI truly benefits cancer care.
Benson Chuma, Co-Founder and CEO Africa, Tech Care For All, shared the African perspective on using data and AI to improve oncology access. He highlighted major challenges: healthcare workforce shortages, long delays in accessing innovations, regulatory hurdles, and infrastructure limitations.
His organisation focuses on training healthcare workers using AI and local guidelines while simultaneously making medicines and innovations accessible across the continent. AI offers opportunities to overcome barriers in diagnostics, supply chain, and education, but adoption is limited by compute capacity, local data availability, and regulatory complexities. He stressed the need for context-specific solutions and sustainable, locally adapted approaches to scale oncology care in Africa.
Key themes emerged across the discussions: the need to embed human values and patient expectations to build trust; the way strong cancer frameworks can reinforce wider health systems; and the potential of the European Health Data Space to transform interoperability if holistic patient data is included.
In conclusion? Challenges and opportunities coexist — and addressing them is essential to build trust, reduce risks, and advance a responsible data ecosystem that enables trustworthy AI for better healthcare. The path forward is complex, yet the potential for meaningful transformation is clear.
The recordings from our Digital Summit will be available soon on our YouTube channel, so keep an eye on our posts.
