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Slope Financial Model

Health-tech Startup Financials (Free Excel Download)

Software platform that automates and orchestrates clinical trial supply chains - connecting sponsors, CROs, sites, labs, vendors, and patients in one real-time ecosystem.

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About this model

Slope automates and orchestrates clinical-trial supply chains, connecting sponsors, CROs, sites, labs, vendors, and patients. Its platform addresses the operational coordination required to move trial materials and information across a complex network of institutional participants.

It is enterprise trial-operations software where each live trial can expand platform usage. Growth depends on sponsor logos, trials launched, implementation, workflow coverage, stakeholder adoption, and retention as customers run successive programmes and add more supply-chain processes.

The model forecasts sponsor logos, trials on platform, subscription or trial fees, implementation, usage expansion, and retention. It includes enterprise sales cycles, onboarding, customer success, cloud and integration costs, gross margin, product investment, cash burn, and runway.

A turnkey financial model

Live formulas, no hardcoded values

Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.

All assumptions in one tab

Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.

Statements always balancing

For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.

Distinct schedules for clarity

Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.

No hidden macros or external links

There are no unexplained external workbook links or macros to undermine auditability or portability.

Changes flow through the model

Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.

About Slope

slope.io
Read the pitch deck
Slope pitch deck cover
View on makeslides.com
Total raised
$20.0M
Funding round
Series A
Founded
2021
Category
Health-tech
Customer
B2B2C
Geography
Global

How to build a detailed financial model for Slope

A complete walkthrough of the business, drivers, and assumptions behind the downloadable Slope model - distilled from its pitch deck and publicly available information.

Product & value proposition

  • Software layer: study protocols transform into structured workflows with digital twins, real-time chain-of-custody tracking across samples, lab kits, drugs, devices, equipment, and shippers.
  • Fulfillment layer: on-demand lab kitting, procurement, and direct-to-patient shipments.
  • Support layer: tech-enabled Slope project managers acting as a CRO touchpoint.
  • Core value: saves 13+ hours per patient visit across all stakeholders; automates workflows 50–100% depending on function.
  • Available via web and iOS apps; context-specific views per stakeholder role.

Market

  • Problem framing: 80% of clinical trials are more than one month behind schedule; 77% of sites routinely unprepared for enrollment/follow-up visits; modern study designs require up to 70% more samples than legacy designs.

Revenue model

Three revenue streams, all per-study / per-connection:

SOFTWARE

  • One-time study startup fee (per study)
  • Monthly fee per connected site
  • Monthly fee per connected vendor

FULFILLMENT

  • Lab Kit Fee - based on monthly activity (volume-based)
  • Shipping Fee - based on monthly activity (volume-based)

SUPPORT

  • Monthly project management fee
  • Procurement fees (variable over study duration)

Pricing is described as scaling with studies - the more sites/vendors connected and the more activity, the higher the revenue. No specific dollar rates disclosed.

Traction & metrics

  • 4,500+ global users
  • 660 research sites
  • 50,000+ managed samples, lab kits, et al.
  • ~$23.9M of capital raised to date
  • 20 full-time employees
  • Emerged from stealth in 2019
  • No revenue figures, ARR, or customer count (# of sponsors / studies) disclosed.

Unit economics

Efficiency data (value, not economics):

  • Research site: 2.5 hours saved per patient visit
  • Sponsor/CRO ClinOps: 7.0 hours saved per patient visit
  • Lab workflows: 0.5 hours saved per patient visit
  • Kitting services: 3.3 hours saved per patient visit
  • Total: 13.3 hours saved per patient visit across all stakeholders

Competition / moat

  • Moat framing: replacing manual spreadsheet coordination by sponsors' project managers; connecting all stakeholders (sponsors, CROs, sites, vendors, patients, labs) in one ecosystem with real-time chain of custody.

Team & funding ask / use of funds

Team:

  • Rust Felix - CEO & Co-founder. Amazon supply chain / predictive algorithms, enterprise data center sales (Google, NSA). BS/MS Mechanical Engineering.
  • Michael Felix - CTO & Co-founder. UI/UX design professor, supply chain software/hardware. BS Environmental Design / MA Industrial Design.
  • Kate Cantera - COO. Decade of executive health system leadership, healthtech team building. BA Psychology / DPT.

Funding ask:

  • Raising: $20M Series A
  • Use of proceeds: product development, sales & marketing team build, research site network expansion, executive team additions.
  • Prior capital raised: ~$23.9M

Recommended financial model

Archetype + why: Usage-based SaaS + services revenue model. Slope has three distinct revenue streams: (1) a recurring SaaS component (monthly per-site, per-vendor fees + study startup), (2) a usage/volume-based fulfillment component (lab kits, shipping), and (3) a managed services component (PM + procurement fees). The right model is a multi-stream revenue build that separates these three buckets, driven by study count and site/vendor connections as primary top-line drivers.

Forecast horizon & granularity:

  • 5 years (Year 1–5), monthly for Year 1–2, annual thereafter.
  • Quarterly for sensitivity / board reporting.

Key drivers & assumptions:

*Growth drivers:*

  • Active studies (count): starting estimate ~15–25 studies at Series A stage; grow to ~100+ by Year 3. Rationale: 660 sites across an unknown number of studies; no study count disclosed.
  • Sites per study: avg ~20–40 research sites per study. Rationale: 660 sites ÷ estimated studies; no per-study breakdown in deck.
  • Vendors per study: avg ~5–10 vendors per study. Rationale: consistent with multi-vendor supply chain scope described.
  • New studies added per month: ramp from ~2–3/month post-Series-A to ~8–10/month by Year 3.
  • Study duration (months): 18–36 months average. Rationale: typical Phase II/III trial lengths; not in deck.
  • Gross churn (study completion ≠ churn but study pipeline turnover): model as study attrition + backfill.

*SOFTWARE revenue:*

  • One-time study startup fee: $10K–$25K per study. Rationale: SaaS enterprise onboarding for clinical software; no rate in deck.
  • Monthly per-site fee: $200–$500/site/month. Rationale: standard B2B SaaS per-unit pricing in clinical ops space.
  • Monthly per-vendor fee: $100–$300/vendor/month.

*FULFILLMENT revenue:*

  • Lab kit fee: volume-based; estimated $5–$15 per kit unit managed. No rate in deck. 50,000+ managed items provides scale validation.
  • Shipping fee: pass-through + margin; ~15–25% margin on shipping costs.

*SUPPORT revenue:*

  • Monthly PM fee per study: $3K–$8K/month/study. Rationale: typical CRO PM labor costs.
  • Procurement fee: 5–10% of procurement value.

*Cost drivers:*

  • Headcount: 20 FTEs at Series A. grow to ~50–60 by end of Year 2 post-raise; Series A proceeds earmarked for S&M + product + exec team.
  • COGS: fulfillment and kitting services have meaningful COGS (labor, materials, 3PL); software and support are higher margin. Blended gross margin estimated 50–65% given services mix.
  • S&M: heavy investment post-Series A; model as % of revenue ramping from ~40–50% down to ~25% at scale.
  • R&D: ~20–25% of revenue; product-heavy company with iOS + web + workflow engine.
  • G&A: ~10–15%.

*Capital:*

  • Series A raise: $20M
  • Prior capital: ~$23.9M

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

  • Base: study ramp at ~2–3/month post-raise, avg 25 sites/study, blended ARPU per site/vendor at midpoints.
  • Bull: faster study acquisition (4–5/month), higher avg site count per study (35–45), fulfillment volume outpacing software.
  • Bear: slower study ramp (1–2/month), study attrition, lower PM fees as competition pressures support pricing.

Required sheets / outputs:

  1. Assumptions - all drivers centralized with / flags
  2. Study Pipeline - active study count, new adds, completions, by month
  3. Revenue Build - three-stream P&L: Software / Fulfillment / Support, each with own unit drivers
  4. Headcount Plan - by function (S&M, Product/Eng, ClinOps/PM, G&A)
  5. P&L - Gross margin by stream, EBITDA, net income
  6. Cash Flow - burn rate, runway from $20M raise
  7. Balance Sheet (summary)
  8. KPI Dashboard - ARR equivalent (recurring software + support), total managed items, active sites, active studies, burn multiple

Frequently asked

Is the Slope financial model free?+

Yes. The Slope model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.

What's included in the model?+

A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.

How was this model built?+

It was built from Slope's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.

Can I change the assumptions?+

Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.

Have more financial modelling questions? Contact us

Alex Tapio, ex-Deloitte financial modelling expert

Created by ex-finance professionals

Hey, I’m Alex and I created Finamodel.

Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.

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I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.

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