A New Dimension in Drug Discovery: How 3D Genomics is Unlocking Disease Biology
A three-dimensional view of the genome is rapidly transforming our understanding of disease, offering scientists a clearer picture of biological mechanisms and revealing new avenues for targeted therapies.
For decades, advances in genomics have revolutionized the study of disease, yet effective treatments remain elusive for many complex and common disorders. Conditions like inflammatory bowel disease and multiple sclerosis, often rooted in immune system dysfunction, continue to challenge researchers striving to pinpoint the genes truly responsible for disease risk. Dr. Dan Turner, Chief Scientific Officer at Enhanced Genomics, has dedicated his career to overcoming this hurdle. With over 20 years of experience in genetics, molecular biology, and genomics research, he now spearheads scientific strategy and research at the company.
Moving Beyond Statistical Association
Turner describes his role as ensuring scientific rigor and alignment across Enhanced Genomics’ research programs. “I oversee the company’s scientific direction and look after all of our research activities,” he explains. “Essentially, I make sure that the work we do is rigorous, focused and aligned with our goals. It’s a role that keeps me involved in everything from high-level strategy to the fine details of our scientific projects.”
At the core of Enhanced Genomics’ research is 3D multi-omics – an innovative approach that combines the physical folding of the genome with other molecular data to map how genes are activated or deactivated. By capturing this three-dimensional context, researchers can move beyond simple statistical associations and begin to uncover the causal biology driving disease.
Despite decades of genetic research, many common diseases still lack effective treatments, largely due to the difficulty in identifying the relevant genes. “At Enhanced, we’re focused on rapidly identifying high-confidence, genetically validated drug targets for common diseases,” Turner says. “Despite decades of genetic research, most common diseases still lack effective treatments, largely because it’s so difficult to identify the relevant genes.”
The Challenge of Non-Coding Regions
Over the past two decades, thousands of genome-wide association studies (GWAS) have identified genetic variants linked to disease. However, the majority of these variants reside in non-coding regions of the genome – areas that influence gene expression rather than directly altering protein sequences, making them more challenging to interpret.
“For variants in coding regions, we can predict whether they change a protein’s amino acid sequence,” Turner explains. “But most GWAS variants lie in non-coding regions, where they act differently – usually in regulatory regions that control how much protein is produced.”
Within the cell nucleus, DNA folds into a complex 3D structure. This folding brings regulatory elements into close proximity with their target genes, even over significant genomic distances. Understanding this folding, Turner emphasizes, is crucial for connecting non-coding variants to their effects.
Enhanced Genomics has developed a novel assay that profiles this 3D genome folding across the entire genome in a single experiment. “Folding brings regulatory regions close to the genes they control. At Enhanced, we’ve developed an assay that profiles this 3D genome folding across the entire genome in a single experiment.” By integrating this genome folding data with other information, such as chromatin accessibility and gene expression, researchers can identify the underlying regulatory networks driving disease. “This is what we mean by 3D multi-omics,” Turner says. “It allows us to pinpoint which genes matter, in which cell types, and in which contexts.”
Why Context is Critical
Traditional genomics often assumes that a disease-associated variant impacts the nearest gene in the linear DNA sequence. However, this assumption is frequently incorrect. “This is wrong about half the time,” Turner states. “Without 3D context, conventional approaches often miss valuable targets or prioritize incorrect ones, adding cost and time to drug discovery. By providing an integrated view of the genome, 3D multi-omics allows us to focus on the highest-confidence targets, accelerating development and increasing the likelihood of success.”
The emphasis on confidence isn’t simply about speed. The cost of pursuing the wrong drug target can be substantial. By incorporating genetic validation into the discovery process, 3D multi-omics helps researchers concentrate on targets with demonstrable causal evidence, rather than mere correlation. “With our 3D multi-omics approach, genetic validation is built into the technology itself,” Turner says. “Rather than stopping at genetic associations, we can map long-range physical interactions between regulatory regions of the genome and the genes they control, turning an association into validation.”
Building a Baseline with Healthy Cell Atlases
To effectively interpret disease-associated variants, it’s essential to first understand what a healthy cell looks like. Enhanced Genomics, along with other research groups, is constructing multi-omic atlases that characterize normal gene regulation across different cell types. These atlases serve as a baseline for comparison when studying disease.
“Our platform is disease-agnostic, but we are currently applying it to immune-mediated and autoimmune conditions,” Turner says. “We’ve systematically developed full multi-omic profiles, including 3D genomics, across a wide range of healthy cells. This gives us a reference atlas of what the genome should look like in its normal state.” Once a cell type is profiled, it can be repeatedly used as a reference point for interpreting new GWAS data.
By overlaying disease-associated variants onto this healthy 3D structure, researchers can identify disruptions in normal gene regulation. These disruptions can directly indicate the causal genes and pathways involved in disease.
From Data to Decision-Making
A key goal of this work is to make target selection more data-driven. Turner describes how combining large-scale genomics data with structured prioritization can narrow down potential candidates for therapeutic development. “We start by taking a GWAS for the chosen disease indication and systematically interrogating all the relevant omics data across cell types. Because we’ve already generated these datasets, the process is rapid and comprehensive,” he says.
This process generates a longlist of genes with genetic support. A second layer of assessment then considers practical and commercial factors, such as safety, feasibility, and intellectual property. “From there, we refine that longlist into a very high-confidence shortlist of targets to advance,” Turner explains. While these workflows are often proprietary, the underlying principle – integrating genetic and functional data to increase confidence – is becoming increasingly common in the field. As more groups adopt similar approaches, the focus in early discovery is shifting from the quantity of hypotheses to the quality of evidence.
Strategic Focus on Inflammatory Bowel Disease
Selecting disease areas where genetically validated targets can have the greatest impact is a strategic component of this approach. Turner outlines the reasoning behind these decisions. “We’ve designed a two-phase selection process that weighs suitability for our platform from both quantitative and qualitative perspectives,” he says. “Quantitatively, we draw on historical industry data to identify therapeutic areas where genetically backed targets have a strong record of success, and within those, we highlight diseases with unexplained genetic risk factors in intergenic regions.”
Qualitative considerations include whether new cell types need to be characterized, how easily biological validation can be achieved, and the potential clinical and commercial value. Using this framework, Enhanced Genomics has prioritized inflammatory bowel disease (IBD) as its initial focus, given the condition’s significant unmet need and strong genetic component.
Reshaping the Future of Drug Discovery
Turner envisions 3D multi-omics as part of a broader evolution in how researchers approach complex disease. Instead of treating genomics, transcriptomics, and epigenomics as separate disciplines, the aim is to integrate them within a structural framework that reflects how biology operates within the cell.
“3D multi-omics makes the process of defining causality direct, scalable and accessible at a genome-wide level in the most relevant cell types. This clarity is hugely significant,” he says. “I think that 3D multi-omics will reshape drug discovery in the next decade as profoundly as next-generation sequencing has reshaped genetics.”
“Instead of building discovery programs on partial signals or investing heavily just to validate a handful of hypotheses, we can start with genetically grounded insights that are ready to translate into drug development.” This approach moves research beyond single-gene studies towards understanding how genome structure shapes regulation, ultimately informing more precise therapeutic strategies.
“Complex and common diseases, whether autoimmune, neurodegenerative or metabolic, have been notoriously resistant to traditional discovery approaches,” Turner says. “With 3D multi-omics we finally have a way to illuminate the biology behind them, and that gives us a credible path to developing the next wave of truly effective therapies.”
He concludes: “In my view, this isn’t just an incremental step forward. Ten years from now, I believe we’ll look back on this moment as the beginning of a new era in pharma, one defined by sharper insight, greater conviction and a new generation of therapeutics that genuinely change lives.”
