Global Health Summit 2026

Despite the wealth of human genetic diversity in Africa, enormous gaps in genomic data from the region exist, limiting our ability to truly understand the impact of genetic variation on global health. Leveraging African genomic data presents a transformative opportunity for global health, due to the potential for the discovery of novel disease-associated variants, and to improve our understanding of disease mechanisms. African genomic medicine can improve the precision of diagnostics, therapeutics, and drug response predictions for populations worldwide. Crucially, advancing African genomics is not only a scientific imperative but also a pathway to equity. By investing in locally led genomic initiatives, strengthening bioinformatics capacity, and ensuring ethical, community-centred governance of data, global health partners can make the implementation of genomics for health in African populations a reality. This talk explores how empowering African researchers, institutions, and communities to steward their genomic resources can catalyze novel discoveries with benefits that extend beyond the continent, shaping a more inclusive and effective global health ecosystem.

This talk presents our recent work applying Oxford Nanopore sequencing to 1,019 individuals from the 1000 Genomes Project. We integrated linear and pan-genome graph approaches to discover more than 167,000 sequence-resolved structural variants (SV) across all major SV classes. Nanopore reads of unrestricted length enabled precise characterization of mobile element insertions, complex inversions, and repeat-associated SV formation mechanisms, providing a high-resolution view of human structural variation. This open dataset illustrates how nanopore reads improve the detection and interpretation of polymorphic SVs at a population scale. Finally, I will highlight how nanopore sequencing of tumor genomes uncovered haplotype-resolved complex somatic rearrangements, and how integrating genetic and epigenetic information revealed somatic retrotransposition as a contributor to genomic instability.

A fundamental challenge in human genomics is the development of reference frameworks that accurately represent population diversity and capture the full spectrum of genetic and regulatory variation. Many existing resources remain limited by ancestry bias and linear representations, constraining basic research into human evolution, population structure, and genotype–phenotype relationships. In this talk, I will describe how large-scale pangenomic initiatives in Asia are addressing these challenges by scaling from national to continental efforts. I will first present advances from the Chinese Population Pangenome Consortium (CPC) Phase II, which has generated population-representative, long-read–based reference resources across diverse Chinese populations. These data substantially improve the resolution of structural variation, complex genomic regions, and haplotype diversity, enabling refined inference of population structure, demographic history, and signals of local adaptation. By moving beyond single-reference models, CPC provides a more accurate substrate for comparative and evolutionary genomic analyses. Building on this foundation, the Asian Population Pangenome Consortium (APC) extends the pangenomic framework across Asia through coordinated international collaboration and federated data governance. APC aims to construct high-quality X-omic reference resources that integrate genome sequence with additional regulatory and functional layers, enabling systematic investigation of how genetic and regulatory variation are distributed across populations. I will discuss how scaling pangenomics from CPC to APC advances core questions in population genetics and human evolutionary biology, while establishing a rigorous and inclusive reference foundation upon which future biomedical and global health applications can be built.

During this decade, there are three main drivers to innovation in the life sciences — genomics (including DNA and RNA sensing), imaging from molecular resolution to whole organisms, and AI to interpret the data. I will provide an overview of each of these technologies and how they have and will transform our ability to understand living systems. I will, in particular, highlight the opportunities and challenges in delivering this innovation to practising healthcare, drawing on my experience at Genomics England and in other European genomic medicine settings. Finally, I will end with a new use of AI in modelling future patient trajectories.

The NIHR BioResource is a resource of well characterised patients with a common or rare condition, and healthy volunteers willing to be recontacted to participate in translational and clinical research. It has enrolled >350,000 participants to date, holds >11TB of genomic data and >1.6M biological samples. BioResource has recently embarked on a large long-read sequencing (LRS) programme using Oxford Nanopore Technologies across its Rare Diseases, Eating Disorders, and Genes & Cognition cohorts. The NIHR BioResource has already delivered major programmes with direct impact in UK clinical care delivery. The addition of LRS, alongside other multi-omics technologies, can enable the discovery of novel mechanisms and biomarkers to better our understanding of disease biology, and improve diagnostic rate, treatments and clinical care.

Critically ill pediatric patients often have genetic disorders requiring a rapid diagnosis to guide urgent care decisions. Standard genetic testing typically takes weeks and requires multiple tests. Nanopore long-read genome sequencing (LR-GS) delivers genome-wide results within days, with the potential to be a one-test-fits-all solution. As one of the first centers in Europe, we implement ultrarapid LR-GS for critically ill patients. We enrolled 26 critically ill patients (median age 2 months) suspected of having a genetic disorder at the intensive care unit to perform ultrarapid nanopore LR-GS alongside standard genomic care. We compared diagnostic yield, turnaround time (TAT), and evaluated the impact on clinical decision making. In 11/26 cases, a genetic diagnosis was made with ultrarapid LR-GS. From sample receipt to result, the average TAT was 5.3 days (range 2.0-10.8) for LR-GS and 18.4 days (range 6.1-29.1) for standard genomic care. DNA methylation analysis from LR-GS expedited the diagnosis in 3/26 cases. In 7/11 solved cases, ultrarapid LR-GS led to immediate adjustments in patient care, e.g. medication switch or termination of treatment. Our findings underscore the potential clinical impact of ultrarapid LR-GS, including the added value of methylation analysis, for critically ill patients and highlights existing challenges, paving the way to potentially integrate ultrarapid LR-GS as a standard diagnostic assay in the future.

There is growing evidence that long-read sequencing (LRS) is superior to standard genetic testing workflows in the clinical environment. As a single assay, LRS can replace many stepwise tests performed today while also providing improved resolution of complex genomic regions, including repetitive elements, structural variants, and phased haplotypes. While an increasing number of clinical laboratories are validating LRS-based workflows, there remains a critical need for population-scale reference datasets derived from both affected and unaffected individuals to support variant filtering, prioritization, and clinical validation. An emerging and underexplored advantage of LRS is its ability to directly detect native DNA methylation without additional library preparation or bisulfite conversion. This enables the simultaneous generation of sequence, structural variation, and epigenetic information from a single experiment. In the context of rare disease diagnosis—particularly for disorders driven by epigenetic dysregulation or imprinting defects—LRS-derived methylation profiles enable the identification of disease-associated episignatures that may be invisible to sequence-only approaches. However, despite growing clinical interest, publicly available population-level methylation reference datasets generated using LRS remain limited. I will discuss the potential of LRS-derived episignatures, our efforts to build publicly-available databases and tools, and discuss current limitations around these efforts. The development of large, well-annotated LRS methylation reference datasets will be essential for distinguishing pathogenic epigenetic signatures from normal population variation, improving diagnostic yield, and enabling the clinical interpretation of epigenetic alterations alongside genetic variants. Together, integrated LRS-based genomic and epigenomic resources represent a critical next step toward comprehensive, single-assay diagnostics for rare disease evaluation.

Effectively fatal 60 years ago, childhood cancers are now curable for 85% of children who have access to contemporary treatments and supportive care. However, for 90% of children born in resource-limited settings, the picture is less promising. When viewed from a global perspective, only 20% survive their diagnosis, representing one of the largest outcome disparities in global health. The same outcome is true across the board for catastrophic diseases of childhood and represents a major gap in global child health.

Over the past decade, St. Jude has made multiple commitments to addressing the problem, ranging from the Global Initiative for Childhood Cancer and Global Access Platform for Childhood Cancer Medicines ($215 million over 6years), to dozens of quality improvement/implementation programs being implemented across our St. Jude Global Alliance network consisting of 400+ hospitals in 92 countries (~$50 million/year).

Despite major progress, for every dollar spent purchasing drugs or improving treatment services, our research shows over half of resources spent are wasted due to misdiagnosis. Efforts to date aimed at expanding access to legacy diagnostics have largely failed to scale. Meanwhile, despite a genomic revolution resulting in reduced costs and improved outcomes within high-income countries over the past decade, children in resource-limited settings are being left behind. Implementation barriers such as inequitable access to computational resources and absent governance over informatics standards remain stubbornly intractable.

Through our global network and key high-income country collaborators, we have developed a research network, conducted implementation trials, and established pilot integrated education, bio-repository, analytic and dissemination platforms. These aim to empower providers worldwide and improve outcomes for children through access to cutting-edge bioinformatics pipelines and technologies.

An estimated 350 million people worldwide live with an undiagnosed disease (PLWUD)—children and adults who remain without answers despite years of medical investigations. While advances in genomic sequencing have improved diagnostic capabilities, around 60% of cases still remain unsolved, leaving PLWUD and their families without a name for their condition and without appropriate care. This presentation explores the global challenge of undiagnosed diseases and introduces the Undiagnosed Hackathon, an innovative collaborative model designed to accelerate diagnosis for the most complex cases. Organized by the Wilhelm Foundation together with international partners, the Undiagnosed Hackathon brings together clinicians, geneticists, bioinformaticians, researchers, data scientists, AI specialists and the families from around the world for an intensive 48-hour collaborative effort to investigate cases that have remained unsolved despite whole exome or whole genome sequencing. By combining deep clinical expertise with advanced genomic technologies and open data collaboration, the Undiagnosed Hackathon creates a unique environment where experts from multiple disciplines work side by side to analyze data, explore new hypotheses, and identify potential diagnoses.

Beyond individual diagnoses, the initiative aims to develop new approaches and collaborative frameworks to solve the 60% of undiagnosed diseases that current methods cannot yet identify. The model also builds global diagnostic capacity, strengthens international networks, and demonstrates how open collaboration can accelerate discovery.

The presentation will outline the political and strategy context for genomics within the NHS in England and how this has supported the adoption and systematic implementation of genomic medicine. Genomics has the potential to transform healthcare delivery in the NHS, but evolution and advances will be required to enable a fair, scalable, and accessible precision medicine ecosystem for all.