11P Quantitative vessel tortuosity (QVT) score could enable early decision-making in clinical trials by reducing the time required for progression assessment

Background: The immune system is a central determinant of health and disease, but its complexity and plasticity pose a challenge for comprehensive assessment.To realise the potential of complex immune analysis for diagnostic and precision medicine, it's essential to overcome existing challenges in assay and analytical standardization and throughput.Methods: IMU Biosciences couples advanced flow cytometry with a proprietary analytical pipeline to rapidly and reproducibly derive biological and clinical insights from the peripheral immune system.Our novel machine learning (ML) platform enables high throughput real-time immune cell classification, facilitating standardised, robust and reproducible characterization of over 2000 immune cell subsets, states and phenotypes.We profiled 719 blood samples from 47 renal and 86 skin cancer patients enrolled in the EXACT study with high-resolution spectral flow cytometry spanning 60+ markers and contextualised them alongside a reference set of 1000+ healthy individuals.Results: At the cohort level, cancer samples diverged significantly from healthy donors, revealing distinct global disease-and treatment-associated alterations to immune architecture Latent representations of healthy immune structure further allowed quantification of individual-level deviations from the reference in cancer samples.Building on this variability, we identified immune signatures that predicted treatment efficacy and toxicity outcome, supporting patient stratification and early intervention strategies.Given the depth of longitudinal sampling, we further characterised latent trajectories of adverse event development, yielding mechanistic insights into toxicity.In addition, IMU's direct profiling of immune checkpoint inhibitor (ICI) target-bound immune cells enabled dynamic monitoring of treatment response throughout the disease course. Conclusions:This study underscores the transformative potential of next-generation flow cytometry combined with ML analytics to generate high resolution immune profiling data at population-scale to enable precision immune medicine, patient stratification, and biomarker discovery in cancer.