Feel Therapeutics Financial Model

• Proprietary Digital Precision Medicine Platform ingesting data from wearable devices, mobile phone sensors (voice, video, text) and proprietary algorithms to produce digital biomarkers across 10+ domains: mood, mental stress, psychophysiological monitoring, physical symptoms, psychomotor activity, physical activity, sleep, social activity, cognitive functioning, vitals, body energy.
• Solution links remote monitoring → proprietary algorithms → real-time support & adherence tools → clinician dashboard & coaching → digital CBT + psycho-education → medication (adjunct).
• Core problem addressed: no objective monitoring tools exist for mental health (contrast with thermometers, stethoscopes, glucose meters in other specialties).
• Two product tracks: (a) Feel DTx - a digital therapeutic program (depression, anxiety, ADHD); (b) wearable device seeking FDA 510k Class II clearance.

• Mental illness will be the leading cause of disability by 2030, costing $6 Trillion.
• 1 out of 4 people will experience a mental disorder.
• >45% of patients with chronic conditions struggle with behavioral health.
• No explicit TAM/SAM/SOM breakdown or addressable market sizing presented in the deck.

• Near-term: pharma/biotech research partnerships (clinical trial data / biomarker validation services) - consistent with 23 active studies and CNS pipeline focus.
• Medium-term: Drug+ prescription channel (FDA-cleared DTx adjunct to medication).
• Potential DTC subscription or employer/health-plan channel (not stated).

• 23 research & clinical studies active 2018–2024.
• 6 therapeutic areas in CNS pipeline; 6 further TAs in broader pipeline (Oncology, Hematology, etc.).
• Total patients enrolled across studies: 2,727 across 9 countries.
• MDD: 5 countries, 817 subjects
• GAD: 5 countries, 427 subjects
• PTSD: 1 country, 95 subjects
• Healthy w/ risk factors: 5 countries, 1,154 subjects
• ADHD: 1 country, 100 subjects
• Eating Disorders: 1 country, 80 subjects
• MS: 1 country, 50 subjects (starting 2024)
• 87% precision in detecting changes in mood state (peer-reviewed publication).
• 7 publications; 1 pending.
• 5 patents (2 granted, 3 pending).
• No revenue figures or ARR disclosed.

• IP: 2 granted patents (emotion detection from physiological + digital data; continuation method), 3 patents pending (ADHD biomarker, insomnia biomarker, depression relapse biomarker).
• Clinical evidence: 23 studies, 2,727 patients, 7+ peer-reviewed publications.
• Advisory network: Former CEO of Biogen, Former FDA Director (Personalized Medicine & Biomarkers), Professors of Psychiatry at Harvard, UC Davis, UCSF.
• Competitive landscape not explicitly shown; moat framed around clinical evidence and proprietary algorithms rather than comparative positioning.

Team:

• George Eleftheriou - Co-Founder & CEO; Former McKinsey, Columbia.
• Haris Tsirbas, PhD - Co-Founder & CTO; PhD Biomedical Engineering.
• Sharon Kaplow - VP Clinical Operations; Former Clinical Lead AbleTo.
• 31 team members (USA & Europe); 9 post-docs; 4 Professors of Psychiatry.
• 800+ team member publications; 16,000+ citations.

Investors (existing): Felicis, Satori Capital, SOSV, anthemis, SeedtoB, Metavallon; JLabs (J&J Innovation) company.

Burn rate: $180k core gross monthly burn.

Funding ask:

• Total round: $3.5M convertible note; $30M cap, 20% discount.
• Already closed: $2.5M (Satori Neuro-led).
• Remaining: $1M.

Use of funds / milestones:

• FDA 510k Class II clearance for wearable device (comparable: Empatica received FDA clearance → Sanofi Series B).
• Launch as Drug+ and FDA clearance of Feel DTx as adjunct to medication (comparable: Otsuka/Click Therapeutics DTx for MDD).
• No granular budget breakdown disclosed.

Runway implied: $1M remaining ask / $180k monthly burn = ~5.6 months of incremental runway.

Archetype + why: Milestone-gated pre-revenue biotech/DTx operating model. Feel is pre-commercial with dual revenue pathways: (a) research/pharma services revenue (near-term) and (b) DTx product launch post-FDA clearance. The appropriate model is a research-services + DTx product P&L with burn-and-runway bridge, not a SaaS ARR or DTC model. Closest to a clinical-stage digital health model where milestones (FDA clearance) gate commercialisation.

Forecast horizon & granularity:

• Monthly for 24 months (through Series A deployment); annual summary for years 3–5.
• Key inflection modelled: FDA 510k clearance at ~month 12 (milestone from deck), DTx Drug+ launch at ~month 18.

Key drivers & assumptions:

*Burn / Cost side:*

• Core gross monthly burn: $180k.
• Team size: 31; headcount growth rate: +15% p.a. as clinical ops scale post-FDA.
• R&D as % of total opex: ~55%, consistent with 9 post-docs and active study pipeline.
• G&A + Sales: remainder after R&D.

*Research services revenue (pre-FDA):*

• Number of active pharma/biotech study contracts: 3–5 at any time (based on 23 studies over 6 years ≈ ~4/year average).
• Average contract value per study: $150k–$300k (digital biomarker feasibility / Phase II); rationale: small pilot studies in CNS.
• Contract duration: 12–18 months.
• Revenue recognition: ratable over contract life.

*DTx product revenue (post-FDA clearance):*

• Pricing model: B2B prescription / payer reimbursement; $1,200–$2,400/patient/year (consistent with comparable DTx e.g., Pear Therapeutics, Click Therapeutics).
• Ramp: 100 patients year 1 post-launch → 1,000 year 2 → 5,000 year 3; dependent on payer coverage decisions.
• Gross margin on DTx: 70–80% (software-dominant delivery).
• Wearable device ASP: $250–$400/unit; COGS ~40% (hardware).

*Funding:*

• Cash inflow: $1M close of current round; existing $2.5M assumed partially deployed.
• Next capital event: Series A assumed ~month 18–24 post-FDA milestone; size $8–15M.

Scenarios (Base / Bull / Bear - which variables flex):

• Base: FDA clearance at month 12; 3 active research contracts/year; DTx launch at month 18; Series A raised at month 20.
• Bull: FDA clearance at month 9; 5 contracts/year with higher ACV; DTx reimbursement via major payer in year 1; Series A at month 15 on stronger terms.
• Bear: FDA clearance delayed to month 18+; research contract pipeline slow (1–2/year); DTx launch delayed; bridge round required.

Required sheets / outputs:

1. Assumptions dashboard (all drivers in one place).
2. Headcount & compensation build (31-person base, monthly).
3. Research services revenue model (contract pipeline, recognition schedule).
4. DTx revenue model (patient ramp, pricing, payer mix).
5. Wearable hardware revenue (optional / secondary line).
6. Operating P&L (monthly + annual).
7. Burn & runway bridge (cash in / cash out / ending balance).
8. Milestone tracker (FDA 510k, DTx clearance, Series A).
9. Scenario toggle (Base / Bull / Bear).