Join us at Abu Dhabi Future Health Summit
7-9 April 2026
Longevity & Precision Health
Longevity and precision medicine focus on extending healthy life expectancy by understanding biological processes at an individual level and enabling earlier, more personalized interventions. This matters because advances in science and care create a growing opportunity to align gains in lifespan with gains in health span, supporting longer lives that are healthier, more functional, and more resilient. A life-course perspective further extends this opportunity by positioning precision medicine as a lifelong approach, from early development and adolescence through ageing, shaping health trajectories well before disease emerges.
Where the science stands:
Research in genomics and multi-omics integration is rapidly improving the ability to detect biological changes associated with ageing and disease before clinical symptoms appear. Studies combining genomic, transcriptomic, proteomic, and metabolomic data demonstrate improved risk prediction and earlier identification of disease pathways. Single-cell and longitudinal analyses are refining measures of biological age, supporting a shift from population averages toward individualized health trajectories.
Opportunities
Translate validated biomarkers into preventive and personalized care
Guide earlier, targeted interventions across the life course to delay or prevent disease
Improve efficiency and outcomes by reducing late-stage treatment reliance
Key challenges
High cost and complexity of multi-omics technologies
Limited standardization and clinical validation pathways
Integration of complex biological data into routine care
Digital Health & AI
Digital health and Artificial Intelligence enable continuous sensing, analysis, and guidance across the health journey. This matters because connected technologies and advanced analytics can support earlier insights, more responsive care, and better health outcomes at scale. Strong governance, ethical oversight, and transparent stewardship are essential to ensure that predictive technologies build trust, protect rights, and distribute benefits equitably.
Where the science stands:
Current research shows expanding application of AI in diagnostics, clinical decision support, and population health forecasting. Wearables, remote monitoring, and digital platforms increasingly capture real-time physiological and behavioral data. Studies indicate that AI systems can support clinical performance in defined tasks when combined with professional oversight and high-quality data.
Opportunities
Enable proactive risk prediction and early intervention
Scale remote and hybrid care models
Improve system efficiency through data-driven decision support
Key challenges
Data privacy, security, and governance requirements
Risk of algorithmic bias and lack of transparency
Ensuring fair access and accountability in AI-driven decision making
Health System Resilience & Sustainability
Health system resilience and sustainability refer to the capacity of health systems to anticipate change, adapt to emerging risks, and maintain essential services over time. This matters because resilient systems are better positioned to protect populations, manage uncertainty, and sustain health gains in a changing global environment. Resilience increasingly depends on integrating behavioral, cognitive, and cultural dimensions of health, as well as environmental and planetary signals, into a more holistic understanding of population well-being.
Where the science stands:
Research highlights the importance of integrated surveillance, environmental and exposure monitoring, and continuous diagnostic readiness. Global health organizations emphasize combining clinical, environmental, social, and behavioral data to support preparedness and adaptive response. Post-pandemic analyses reinforce the value of flexible workforces, interoperable data systems, and cross-sector coordination.
Opportunities
Embed predictive analytics into preparedness and system planning to improve timely access to essential services
Strengthen early warning and response mechanisms across health and environmental domains, including underserved and high-risk populations
Build workforce models and new health roles that support adaptive, data-enabled care delivery across diverse settings and resource levels
Key challenges
Fragmented data and infrastructure that limit continuity of care and equitable access
Workforce capacity constraints and skills mismatches, particularly in primary care and low-resource contexts
Difficulty translating multi-source sensing into timely operational action that reaches all populations, not only those already well served
Invest in Life Sciences
Investment in life sciences enables the translation of scientific discovery into scalable tools, technologies, and solutions that improve health outcomes. This matters because sustained and strategic investment is essential to move innovations from research into real-world use, support earlier detection and prevention, and ensure that advances in health science deliver broad and lasting impact.
Where the science stands:
Recent investment trends show growing interest in precision diagnostics, AI-enabled discovery, and platforms that integrate biological data with real-world evidence. Public, private, and philanthropic capital play a critical role in expanding equitable access to these technologies by supporting innovations that accelerate research, shorten development timelines, and enable earlier and more effective intervention.
Opportunities
Accelerate translation from scientific discovery to real-world health impact
Support integrated data, research, and innovation ecosystems
Enable broader and more equitable access to high-impact diagnostics and technologies by catalyzing collaboration across public, private, and philanthropic sectors
Key challenges
Regulatory complexity and lengthy development and approval processes vs speed of innovation
Uneven access to capital, infrastructure, and innovation capacity across regions
Misalignment between investment incentives and long-term preventive health outcomes
Apply to our Future Health Challenge in partnership with MIT Solve
With MIT Solve, we have launched our inaugural ‘Future Health Challenge: Building Anticipatory Health Systems through Population Sensing’.
With chronic diseases expected to contribute USD 47 trillion in global costs, and nearly half the world’s population lacking full access to essential health services, the Challenge is a global call for innovative sensing solutions that will help shift health systems from reactive care to predictive and anticipatory models.
Shortlisted innovators will be invited to showcase and pitch their solutions at the Abu Dhabi Future Health Summit (7–9 April 2026), with USD 300,000 in prize funding available alongside tailored mentorship, and access to international networks.