Aethernova

Aethernova is a Scottish digital-health company developing a clinician-supervised multimodal human phenotype intelligence architecture.

We combine structured XR environments with multimodal behavioural, cognitive, physiological and contextual signals — including gaze, movement, interaction patterns, voice, task performance and other sensor-derived data — together, where relevant and appropriately governed, with existing clinical, laboratory, genomic/omics and longitudinal health data.

Our aim is to build a richer and more integrated understanding of how an individual functions, characterise phenotype heterogeneity, and investigate meaningful longitudinal functional change over time.

Our initial application is neurodevelopment, including autism and ADHD, where we are developing technology to support professional understanding, assessment, interpretation and personalised care pathways. The underlying architecture is designed to extend into other areas where heterogeneous or changing human function is important, including healthy ageing, cognitive and functional change, rehabilitation, remote and community care, and clinical research.

Aethernova is not developing autonomous diagnostic AI. Our approach is designed around clinician and professional oversight, calibrated uncertainty, explainability, auditability and human decision-making.

For translational research and clinical development, the same architecture could support richer human phenotyping across the therapeutic-development pathway. Potential applications include phenotype-based patient stratification, cohort characterisation and trial enrichment, digital biomarkers and endpoints, longitudinal treatment-response monitoring, and exploratory investigation of responder and non-responder patterns. Multimodal behavioural and physiological data could also be analysed alongside existing clinical, laboratory, microbiome, genomic/omics and other relevant datasets to investigate cross-modal associations and potentially identify clinically meaningful subgroups or trajectories.

This could be relevant to pharmaceutical, biotech and AI-enabled drug-discovery organisations, therapeutics developers, clinical-trial sponsors and CROs seeking better ways to characterise heterogeneous patient populations and measure meaningful human outcomes during translational and clinical development. Aethernova would complement rather than replace molecular discovery, conventional clinical endpoints or expert clinical judgement.

For UNITE Open Call 2, we are particularly interested in complementary consortium partners offering:

• clinical, social-care or community validation environments
• older-adult, neurodevelopmental or other relevant clinical populations
• hospitals, care providers, living labs and real-world deployment settings
• well-characterised cohorts, biobanks or existing longitudinal clinical datasets
• expertise in cognitive, behavioural and functional outcome measurement
• multimodal sensing, physiological signals, wearables and biomarker technologies
• pharmaceutical, biotech and AI-enabled drug-discovery companies, therapeutics developers, clinical-trial sponsors and CROs interested in stratification, cohort characterisation, digital biomarkers/endpoints or longitudinal treatment-response measurement
• clinical validation, implementation science, health economics, regulatory and adoption expertise
• access to rural, underserved or geographically dispersed populations

We are particularly interested in collaborations exploring how multimodal human phenotype intelligence can support earlier recognition of meaningful functional change, more personalised care, better patient and cohort stratification, richer digital measures for clinical research, equitable access to assessment and monitoring, and more effective use of professional capacity.