Augscape.

AUG_P326 / Project Record

Advanced Digital Health System.

A digital health project designed to organise psychological, functional genomic, pharmacogenomic, epigenetic and longitudinal evidence before healthcare decisions are made.

ADHS is a model-design stage Augscape portfolio project, positioned for responsible digital health development, research partnership and controlled evidence-layer infrastructure.

Project Identity

ADHS.

Advanced Digital Health System

Current valuation

£ TBC

Stage

[02] Model Design

Sector

Digital Health
Personal Health Intelligence

Market

Personalised Healthcare
Mental Health / Genomics / Decision Support

Potential routes

[02] Investor or Strategic Partnership Participation
[03] In-House Spin-Off Formation
[04] Model Acquisition or Controlled IP Transfer

01 / Project Overview

Building an evidence layer between lived experience and healthcare interpretation.

ADHS is an Augscape digital health project designed around a persistent healthcare information gap: people often enter assessment, medication review or personalised-care pathways without structured evidence about symptoms, functioning, medication response, biological context or change over time.

The project is framed as an evidence-assisted personal health intelligence model. It is not intended to diagnose, prescribe or replace clinicians. Its purpose is to improve the quality, structure and continuity of information available before professional review.

The proposed model combines psychological profiling, longitudinal self-report, functional genomic context, pharmacogenomic medication support, epigenetic health-state monitoring and user-held evidence into a governed decision-support environment.

02 / Project Thesis

Better healthcare decisions need better source information.

ADHS is built around the view that many healthcare decisions begin with an imperfect translation chain. The individual must organise and explain complex internal experience, while the clinician must interpret that information within appointment, pathway and evidence constraints.

Important detail can be lost in that process. Symptoms may be described inconsistently, functional patterns may not be tracked, medication effects may be poorly recorded, neurodevelopmental masking may be missed and biological context may sit outside the conversation.

The thesis is that user-held evidence should be structured before clinical interaction, with clear boundaries around evidence maturity, clinical relevance, consent, safety and professional interpretation.

ADHS is therefore positioned as a governed evidence layer: organising information, supporting users and producing review-ready summaries without presenting emerging evidence as certainty.

03 / Research Basis

Associated Research Outputs.

ADHS has been developed in response to research findings on personalised healthcare evidence, psychological self-report, functional genomics, pharmacogenomics, epigenetic monitoring and the limits of automated interpretation.

04 / Intended Users

A health-technology project requiring clinical caution, technical capability and controlled participation.

Participant
Platform relevance
Expected value
Individuals and patients
Build clearer records of symptoms, functioning, medication history, biological context and change over time.
Improved self-understanding and appointment preparation.
Clinicians and reviewers
Receive better-structured summaries that separate user-reported information, recognised evidence and emerging evidence.
Improved review context without replacing professional judgement.
Research and university partners
Support evidence review, ethics, model design, algorithmic development and validation planning.
Scientific credibility and safer development route.
Digital health and testing providers
Provide platform capability, interoperability, secure data architecture, genomics and pharmacogenomics infrastructure.
Responsible technical delivery and evidence integration.
Clinical governance and data-protection advisors
Shape consent, safety routing, evidence labelling, claims boundaries and sensitive data handling.
Reduced clinical, product and compliance risk.

05 / Current Route

Developing the model before wider commercial progression.

ADHS is currently positioned within the model design phase. The focus is on refining the evidence structure, user route, safety boundary, consent model, professional-summary output and technical architecture before wider validation or commercialisation.

Potential next steps may include research partnership, university collaboration, controlled prototype development, clinical-governance review, private-provider pilot scoping or strategic digital health partnership.

Further materials may be shared by invitation and, where appropriate, under NDA. Potential future routes may include investor or strategic partnership participation, in-house spin-off formation, model acquisition or controlled IP transfer.

Participation

Model design and participation enquiries should reference project code AUG_P326.