DEEPDʘSE

Research partners

Timing atrelapse risk

Circadian disruption is strongly linked to addiction relapse. DeepDose passively tracks phase state from the phone and wearables — then times medicines, light, and sleep to when the body is ready. Built for community treatment populations and academic study.

Delivery

Smartphone-delivered support

Continuous passive capture — light, movement, sleep timing, social jet lag — without daily questionnaires. Matches the UK push for digital treatment tools people already carry.

Mechanism

Circadian disruption & relapse

Irregular sleep and phase drift precede craving and return to use in published addiction science. Phase-aware prompts target the window when timing support may matter most.

Population

Community treatment settings

Polypharmacy, chaotic sleep, and real-world adherence — not idealised trial beds. Proxy DLMO from wearables, TipTraQ validation when clinical grade is needed, clinician-shared records.

Governance

Federated research data

Chronobiobank keeps intimate sleep architecture on-device; consent-gated aggregates for studies — aligned with the national addiction healthcare data roadmap.

Research instrument

From wellness signal to study-grade readout

Layer 1–2 estimate proxy DLMO continuously on-device. Layer 3 upgrades with TipTraQ for validated sleep staging and respiratory traces. Outputs — Biological Time Index, body-clock alignment, dosing windows — are structured for endpoints, not engagement metrics alone.

Technology stack → · Proxy DLMO methodology → · Science & trust →

Industry partnership

Built for doctoral and fellowship programmes

Deepdose is opening industry partnerships with UK universities for addiction healthcare research — including SSA Flagship schemes, NIHR career development, and MRC fellowship routes under Addiction Healthcare Goals. We provide the platform, passive phase instrumentation, governed data access, and clinical validation path; academic leads own protocol, ethics, and publication.

  • Hypothesis-led studies in community drug and alcohol treatment
  • Endpoints: phase drift, sleep regularity, window adherence, relapse proximity
  • Dynamic consent and UK GDPR — model weights isolated from participant UI
  • Training and dissemination with clinicians and recovery workers
Science & trust →

Academic or clinical collaboration enquiries: contact the founder via About. We do not claim government endorsement — we align with published Addiction Healthcare Goals priorities. About the founder →