This year’s ASCO and AACR conferences showcased a powerful shift toward diagnostics and treatment approaches that combine biological depth with technological agility. From advanced liquid biopsy methods to AI-enhanced decision tools, the future of cancer care is arriving.

cfDNA Moves Beyond Mutations

Across both conferences, cell-free DNA (cfDNA) remained a focal point, with researchers pushing beyond mutation detection into richer biological signals like fragmentomics — analysing the size and pattern of cfDNA fragments to infer their tissue of origin and cancer status. These fragment patterns, when combined with epigenetic features such as methylation, nucleosome positioning, and promoter accessibility, now support insights from early detection to residual disease monitoring.

At Hurdle, our platform is designed to help partners rapidly validate and deploy these complex, multimodal biomarkers. Traditional wet-lab routes are slow, bespoke, and brittle. We’re building a systemised, AI-enabled biomarker discovery engine to streamline that journey—from biomarker discovery to regulated clinical use—10x faster than current models.

The Rise of Multimodal Diagnostics

Liquid biopsy innovation is happening within a broader redefinition of diagnostics—from siloed modalities to integrated decision platforms. Studies presented at ASCO showcased how AI frameworks that combine imaging, pathology, genomic, and EHR data outperform traditional single-modality approaches. In one example, combining radiographic features with lab results and clinical notes led to better identification of treatment-limiting conditions. Another study integrated digital pathology and structured patient data to predict cancer recurrence more accurately.

These are not isolated breakthroughs—they point toward a future where multimodal biomarker pipelines are operationalised in real-world care. That’s precisely the future we’re building infrastructure for. Hurdle’s platform is already supporting multi-omics diagnostics at scale, and our goal is to make tools like these plug-and-play for partners across pharma, health systems, and research.

AI as the Diagnostic Backbone

AI underpins much of this evolution. From interpreting unstructured clinical data to guiding treatment decisions, AI systems are shouldering the growing cognitive load clinicians face. In radiology, AI tracks nuanced tumor changes over time. In pathology, it’s predicting molecular signatures directly from H&E slides. This is diagnostics as a dynamic system, not a static snapshot—a paradigm shift that mirrors Hurdle’s worldview: real-time, adaptive, and scalable.

Still, these capabilities are only impactful if clinicians can access them seamlessly. That’s why Hurdle focuses not only on assay development, but on the full infrastructure stack—regulatory readiness, global lab integration, data management, clinician-friendly interfaces, and more. Our mission is to eliminate the operational and technical “hurdles” that often block diagnostics from reaching the bedside.

An Invitation to Collaborate

For researchers and clinicians interested in collaborating or accelerating translational science, we see an urgent opportunity. The fusion of biology and data science is no longer a future concept—it’s a live pipeline, and Hurdle exists to help it reach patients faster.