# Pepper Bio Financial Model

AI-driven "transomics" drug discovery platform that identifies disease-causal targets and predicts drug efficacy/toxicity across multi-omic data layers.

- Canonical: https://finamodel.com/startups/pepper-bio
- Excel download: https://finamodel.com/startup-models/pepper-bio.xlsx
- Category: Biotech/Pharma
- Model type: Biotech rNPV
- Funding round: Seed
- Funding: $6.5M
- Founded: 2023
- Geography: US-based (CEO contact: jonhu@pepper.bio); commercial focus US & EU5 for internal pipeline TAM.
- Customer: B2B

## About the company

Pepper Bio uses a transomics platform combining genomics, transcriptomics, proteomics, and phosphoproteomics to identify causal disease targets and predict drug efficacy or toxicity. It claims stronger target identification than NLP over scientific literature and traditional multiomic analysis, with applications from discovery through patient stratification.

Near-term revenue comes from pharma service contracts for target identification, mechanism studies, lead optimisation, toxicity, and clinical stratification. The company expects deal economics to progress from $100,000-plus upfronts toward larger upfronts, milestones, and sub-10% royalties, while developing internal oncology assets including hepatocellular carcinoma.

Pepper Bio had generated under $1 million from three partnerships with large or public biopharma companies, each worth roughly $100,000–$400,000. The model should forecast partnership timing, upfronts, milestones, internal-pipeline R&D, clinical entry, probability-adjusted asset value, royalties, and runway.

## What's included

- 5-year monthly revenue build with stage-appropriate growth assumptions
- Full P&L, headcount plan, and operating-expense schedule
- Cash-flow statement, runway, and burn-rate tracking
- Valuation via exit multiple with a DCF cross-check
- Returns analysis with MOIC and IRR
- Unit economics including CAC, LTV, payback, and cohort retention

## Product & value proposition

- Proprietary "transomics" platform integrating genomics, transcriptomics, proteomics, and phosphoproteomics to identify causal disease targets (not just correlative ones).
- Claims 12x better than leading NLP over 30M+ scientific sources and 4x better than traditional multiomic analyses at target ID.
- Platform applicable across full drug development workflow: target discovery → lead discovery → lead optimization → toxicity prediction → IND filing → clinical trial patient stratification.
- Two core capabilities: (1) Understand disease (what drives/sustains it), (2) Understand drug (full impact on patient).

## Market

- Oncology drug market: $201B (2021), 9.7% CAGR.
- Neurodegenerative drug market: $34B (2020), 4.9% CAGR.
- Inflammatory diseases drug market: $98B (2020), 9.3% CAGR.
- Short-term TAM (pre-clinical omics R&D tech in oncology, neurology, inflammatory - i.e. partnership addressable market): $3.3B.
- Internal pipeline oncology SOM (US & EU5, 3 cancer indications): $5.3B total across Lymphoma ($1.5B), Liver cancer / HCC ($1.5B), NSCLC EGFRm ($2.3B).
- Jumbo pharma platform deals benchmark: $1B+ (e.g. Roche, Bayer, BMS, Gilead comparable deals).

## Revenue model

Two-track model:

**Track 1 - Pharma partnerships (near-term revenue)**
- Service contracts with pharma/biopharma for target ID, mechanism studies, lead optimization, toxicity prediction, and clinical patient stratification.
- Current deal structure: upfront fees per drug program.
- Deal progression roadmap:
  - Current: $100K+ upfront, total deal value $100K+
  - 2023 Q3+: $1M+ upfront + $10M+ milestones per drug program, total deal value $10M–$100M+
  - Late 2024 (drug in clinic): $10M+ upfront + $100M+ milestones + tiered royalties (<10%), total deal value $100M–$1B+

**Track 2 - Internal pipeline**
- Develop proprietary drugs in oncology (starting with HCC/liver cancer, then lymphoma and NSCLC).
- Pre-clinical efficacy data shown for HCC target; expect IND/clinic entry in HCC "next year" (relative to deck date).
- Revenue eventually from drug sales / licensing / royalties (long horizon).

## Traction & metrics

- Total revenue to date: <$1M from 3 completed/active partnerships.
- Partnership 1: Top 5 pharma - mechanism for novel modality - $100K–$400K - 7 months duration.
- Partnership 2: Public commercial-stage biopharma - target ID for AML - $100K–$400K - 3 months duration.
- Partnership 3: Public clinical-stage biopharma - mechanism for clinical asset - $100K–$400K - 8 months duration.
- No customer count, retention rate, or ARR figure disclosed beyond the above.

## Unit economics

- Contract value per deal (current): $100K–$400K per engagement.
- Contract duration: 3–8 months per engagement.
- Implied ACV range: ~$150K–$600K annualised per engagement (rough extrapolation from duration; not stated).
- No CAC, LTV, gross margin, or payback period data disclosed in deck.
- Cost structure not disclosed (R&D-intensive; lab / compute / headcount driven).

## Competition / moat

- Moat framed as technology superiority over:
  - NLP/literature mining (12x better).
  - Traditional multiomic analyses (4x better).
- Differentiation: phosphoproteomics layer provides functional/causal signal vs. static/correlative genomic/transcriptomic data.
- No named competitors cited in deck.
- IP/patents: not mentioned.
- Published validation data: pre-clinical HCC mouse model shown.

## Team & funding ask / use of funds

**Team:**
- Samantha Dale Strasser, PhD - CSO & Co-founder; PhD MIT (EECS, multi-omics); NSF Graduate Research Fellow; Churchill Scholar; Goldwater Scholar; developed Pepper's core technology.
- Jon Hu - CEO & Co-founder; MBA Harvard Business School; former CEO of Atidiv (200→300 people), COO Techweek.
- Simon Fricker, PhD - CDO; PhD University of Warwick; 25+ years drug industry; founding member AnorMED (acq. by Genzyme); worked on 3 FDA-approved drugs.

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## Recommended financial model

- **Archetype + why:** Dual-track biotech platform model - (A) near-term B2B services revenue model (contract research / pharma partnerships) with milestone-escalation schedule, plus (B) long-term internal pipeline P&L with R&D burn, IND/clinical timelines, and probability-weighted terminal value. The partnership track resembles a services/SaaS ramp (recurring contract revenue growing in deal size); the pipeline track requires a standard biotech NPV / probability-of-success model. A 3-statement integrated model with a pipeline NPV module is appropriate. Do NOT model as a pure SaaS ARR model - deal sizes and structures are milestone-gated, not subscription.

- **Forecast horizon & granularity:**
  - Partnership revenue: quarterly, 2023–2027 (5 years), building from existing 3 contracts to a larger partner base.
  - Internal pipeline: annual, 2023–2030+, with milestone gates (IND, Phase I, Phase II, approval/licensing event).
  - Burn / cash: monthly for 18-month runway model; quarterly thereafter.

- **Key drivers & assumptions:**

  *Partnership track:*
  - Number of active partnerships per year
  - Average deal size (upfront + milestones) - model each deal tier separately
  - Deal duration / contract length
  - Royalty rate on partnered drugs
  - Revenue recognition: recognize upfront at contract start, milestones on achievement

  *Internal pipeline track:*
  - Programs in development
  - R&D cost per program per year
  - Time to IND/clinic for HCC
  - Probability of success (POS) by stage
  - Peak sales / royalty income on approval

  *Cost / OpEx:*
  - Headcount
  - R&D spend as % of revenue
  - G&A
  - Partnership R&D costs are low-effort/scalable per deck messaging

  *Capital:*
  - Burn rate

- **Scenarios (Base / Bull / Bear):**
  - Flex variables: number of partnership deals closed per year, average deal size, time to IND/clinic, probability of success on internal programs, royalty rates.
  - Bear: partnership ramp slow (3→5 deals, deals stay at $100K range, HCC IND delayed 12 months).
  - Base: partnership ramp per deck trajectory (2023 Q3 uplift materialises, 1 jumbo deal by 2025), HCC IND 2024.
  - Bull: 1 jumbo platform deal ($100M+) closes in 2024, second drug enters clinic 2025, licensing event on lead program.

- **Required sheets / outputs:**
  1. Assumptions & inputs (centralized toggles: deal ramp, deal sizes by tier, pipeline stage timelines, POS, royalty rates, headcount, burn)
  2. Partnership revenue schedule (by contract, by tier, upfront + milestone + royalty)
  3. Internal pipeline timeline & milestone tracker
  4. P&L (IS): revenue, R&D expense, G&A, operating loss, EBITDA
  5. Cash & runway (burn bridge from current raise / existing cash)
  6. Pipeline NPV module (probability-weighted DCF per program, 10–15% discount rate)
  7. Scenario toggle (Base / Bull / Bear outputs)
  8. KPI dashboard: active partnerships, total deal value pipeline, burn rate, runway, programs in clinic

## Frequently asked questions

### Is the Pepper Bio financial model free?

Yes. The Pepper Bio model is a free Excel download with live formulas.

### Can I change the assumptions?

Yes. The workbook is editable and its live formulas recalculate when assumptions change.