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Transforming Healthcare with AI-Driven Early Intervention
View the full article in PharmaTimes here.
We are delighted to share that Zhana Kuncheva, PhD, Director of Health Data Science at bioXcelerate AI, has been featured in the May 2025 issue of PharmaTimes, where she explores the critical role of technology in reshaping how we approach preventative healthcare.
The article, titled “Prevention is better than a cure, but what role can technology play in finding it?”, highlights how data-driven insight, machine learning and AI are enabling a shift from reactive treatment to proactive, personalised prevention.
Key Insights from the Article:
A System Under Pressure
With over 7 million people awaiting treatment on the NHS, and chronic diseases like diabetes, cancer and dementia on the rise, healthcare systems are at a tipping point. Zhana underscores the urgent need to focus not just on treating illness, but preventing it in the first place.
The Challenge of Early Detection
While early diagnosis is often seen as the gold standard, many conditions progress silently. Traditional screening programmes, though valuable, are often generic and resource-intensive. More personalised approaches are needed to deliver meaningful impact at scale.
The Role of AI in Precision Prevention
Zhana explains how AI and machine learning can analyse vast, complex datasets, identifying risk patterns across genetics, lifestyle and environmental factors. This enables earlier, more targeted interventions, helping clinicians act before symptoms even begin.
A Breakthrough in Risk Prediction
Zhana highlights a recent collaboration between Optima Partners, Biogen, and the University of Edinburgh that used machine learning on UK Biobank data. The study uncovered protein patterns that could predict diseases such as Alzheimer’s and type 2 diabetes up to ten years in advance, offering a powerful tool for earlier action and better outcomes.
Supporting, Not Replacing Clinicians
Technology is not here to replace healthcare professionals – it’s here to support them. From diagnostic tools to data analysis, AI can give clinicians sharper insights and improve decision-making, while also empowering patients with more personalised, preventative care pathways.
What’s Needed for Success
For this transformation to take hold, Zhana calls for investment in:
- Robust technology infrastructure to manage data at scale
- Training to equip healthcare professionals with new tools
- Public trust to ensure adoption and engagement
