Healthcare has always advanced through science. What feels different now is the speed at which technology is catching up, creating opportunities that would have been difficult to imagine even a decade ago. The convergence of better data, stronger compute capability, and more mature modelling techniques is beginning to shift medicine from reactive treatment toward earlier detection, smarter intervention, and more personalised care.

This matters because healthcare is inherently complex. Human biology doesn't follow neat patterns. Disease doesn't progress the same way in everyone. Yet we still treat most patients based on what worked for the average person in a study. That's given us huge breakthroughs, but it also means we're often diagnosing late, guessing at treatments, and missing early warning signs.

Digital Twins in the context of health

A Digital Twin is a living digital model of a real-world object, system, or process, designed to reflect how it behaves over time. In healthcare, that concept becomes really powerful because it can be applied to the most complex system of all, the human body.

A health focused Digital Twin is not simply a record of what has happened. It is a framework for understanding what is happening now, what is likely to happen next, and what interventions could change the outcome. It brings together data, context, and simulation to support better decisions, in areas where uncertainty has traditionally been accepted as unavoidable.

The long-term direction is clear. If healthcare can model the individual more accurately, it can move closer to personalised medicine that adapts to the patient, rather than forcing the patient to fit a generalised pathway.

The rise of wearables and individual data

One of the biggest accelerators of this shift is the rapid growth of individual health data. Wearables and monitoring tools are now capturing signals continuously, including sleep patterns, recovery, activity levels, cardiovascular indicators, and behavioural change. This is creating a much clearer and richer picture of health over time, rather than snapshots taken only when symptoms become severe.

On their own, these data points don't tell you much. Your heart rate spikes because you had coffee, or you're stressed, or you climbed some stairs. But when connected with clinical history, diagnostics, and longitudinal monitoring, they become genuinely useful. They can support earlier detection of risk patterns, improve how disease progression is monitored, and help identify when intervention may be required before deterioration becomes acute.

Spotlight: The EU Virtual Human Twins (VHT) programme

This is where the European Virtual Human Twins (VHT) programme becomes really significant. It is one of the most ambitious coordinated efforts currently underway to advance Digital Twins in healthcare, with the goal of improving how we understand, predict, and treat disease at an individual level.

The VHT programme is designed to accelerate the development of predictive digital representations of human biology, enabling simulation of how cells, tissues, and organs respond to disease progression or therapeutic intervention. The long term ambition is clear. To move beyond population averages and create models that reflect biological variability across individuals, supporting more personalised approaches to diagnosis, prevention, and treatment selection.

Digital Twins also have a direct role to play in advancing drug development and commercialisation. By creating simulation ready models of disease progression and treatment response, they can help researchers test hypotheses earlier, refine target selection, and design trials with greater confidence. As therapies move closer to approval, Digital Twins can support better identification of which patients are most likely to benefit, more efficient site and supply planning, and stronger evidence generation across real world settings. The long-term value is not only faster development cycles, but a clearer pathway to scale, access, and impact once a therapy receives approval.

What makes this work is the collaboration. By bringing together researchers, clinicians, industry, and policymakers, the programme aims to reduce fragmentation across data, models, and tools, and create foundations that can be adopted and trusted across health systems.

When this works, VHTs could become a meaningful accelerator for precision medicine, helping clinicians diagnose earlier, helping researchers test hypotheses faster, and helping health systems move toward interventions that are increasingly tailored to the biology of the individual, not the average of the population. If the historically expensive research phase can be optimised through simulation and stronger evidence, could this ultimately expand access and improve healthcare economics?

With great compute power comes great responsibility

For Virtual Human Twins to move from ambition into measurable healthcare impact, there are several constraints that will shape adoption. Here are 3 I can foresee becoming the defining factors over the next few years.

The first is compute power. Simulating human biology at meaningful depth requires serious computational capability, as models expand across cells, tissues, and organ systems and evolve with new evidence. This is where the EU wide collaboration behind VHT matters, bringing together great minds, shared infrastructure, and collective learning to accelerate progress and increase the chances of success at scale.

The second is sustainability. Advanced compute is energy intensive, and running these simulations takes a lot of energy. That matters. If VHTs are to deliver long term value, the infrastructure powering them must be designed responsibly, balancing innovation with efficiency, resilience, and environmental impact.

The third is regulatory and evidence pathway evolution. For VHT insight to influence drug development and clinical decision making, regulators will need clear frameworks to assess validity, transparency, and clinical relevance. A key question is whether VHT outputs can form part of real-world evidence across review cycles. As VHTs mature and their insights are validated, simulation may enhance pharmacovigilance and post market surveillance, adding a new layer of safety intelligence and risk reduction.

The future outlook: a step change for unmet need, access, and outcomes

The constraints matter, because trust matters. But the upside is hard to ignore. The greatest impact is likely to be felt in areas of unmet need, including ultra rare diseases and complex neurological conditions, where patient cohorts are small, biological variability is high, and traditional research models often struggle to deliver progress. In these settings, simulation could accelerate learning, support earlier intervention, and enable more personalised approaches to treatment.

The implications for drug development are equally significant. Better modelling and earlier insight can reduce late stage failure risk, improve trial design, and shorten decision cycles, lowering R&D cost and making investment in smaller populations more viable.

Over time, this could meaningfully improve health economics and access. If therapies can be developed more efficiently and monitored more intelligently across their lifecycle, including through stronger post market surveillance and digitally supported pharmacovigilance, personalised medicine becomes easier to scale across health systems, improving outcomes without making innovation structurally unaffordable.

Looking ahead, the convergence of AI, Digital Twins, and advanced healthcare technology has the potential to create a genuinely positive impact well beyond clinical outcomes alone. As these capabilities mature, they will drive demand for new skills and new roles across research, engineering, clinical innovation, data governance, and operational delivery, expanding the workforce that supports modern medicine. More importantly, they can unlock deeper insight into disease progression, accelerate how quickly we learn what works, and improve how early we can intervene. If applied responsibly, this shift could help reduce the burden of chronic disease, improve quality of life at scale, and make a meaningful contribution to extending healthy life expectancy.

Incredibly excited to watch European Virtual Human Twins Initiative progress and to see what Lucilla Sioli, Sandra Gallina, and the wider team achieve as they bring this vision to life across Europe!