Hey {{first_name|default:there}}, it’s Vadim 👋
An exciting update in case you missed it:
Our previous poll made it pretty clear - getting investors to actually respond is the #1 challenge for many of you right now.
So I'm putting together a dedicated training on investor outreach. This will cover not just how to get responses, but how to build real, authentic relationships with investors that can stay with you well beyond your current raise and even your current company.
If that’s something that would be helpful for you, you can get on the waitlist here, so you don't miss it.
Now, on to today's issue.
Once investors start responding and you're moving them through your funnel, the next question I hear from almost every founder is: "What should I put in my data room?"
This is not a trivial question - most data room guides are built for tech startups and seldom address the complexity for biotech or life science founders navigating IP, regulatory, and scientific data.
🧭 HERE’S WHAT WE’LL COVER TODAY:
Why most biotech data rooms slow down fundraising instead of speeding it up
The 3-layer data room architecture (and what goes in each layer)
What changes by subsector - therapeutics, devices, SaaS, diagnostics
How to build a data room in 30-days without a legal team or burning out
Bonuses like data room tools & AI prompts for getting organized fast
Let’s jump in!
FOUNDER STORY
Do you, founder, take this VC to be your lead investor?
Here's what's funny about data rooms: most biotech founders lose sleep over their setup, but most investor conversations never even get to that stage. They end much earlier, for reasons that have nothing to do with due diligence materials.
But for the ones that do get there? A messy or poorly structured data room is the last thing you want slowing down a deal that's actually moving forward.
The good news: setting one up isn't that complicated. You probably already have most of the materials. It's just a matter of organizing them thoughtfully and knowing what goes where, especially the biotech-specific pieces like scientific data, IP, and regulatory documentation that most generic startup guides completely miss.
But there is also a larger dynamic to be aware of: a VC investment, especially at seed or Series A, is a relationship that's often harder and more expensive to unwind than a marriage.
So, in my view, the data room isn't just a file-sharing exercise.
It's a trust ceremony.
What is a trust ceremony, you may ask?
Well, you can think of it this way:
"Do you, Founder, take this VC as your lead investor? Do you accept that they are bought into your science, that they will bring in other high-quality investors into this round and the next, and that they will support you through pivots, down rounds, and 3am existential crises?"
"And do you, Investor, take this founder as your Series A commitment? Do you accept that they will act with integrity and consistency, that the data they've shared is complete and accurate, and that they will deploy your capital with the same care they'd give their own?"
“I do..”
“I do.”
"You may now open the data room"
(Am I the only one that’s tearing up? :)
In seriousness, the real question behind every data room decision is: do I trust this person enough to share this, and have they earned it? Do I truly trust them to do business together for years to come?
The framework below is built around these questions. It gives you a structure that protects you while making it easy for the right investors to move forward.
Feel free to use it as your starting point and adapt it to your specific relationships and circumstances.
FRAMEWORK
The 3-layer data room set-up
The approach I recommend is built on one principle: progressive disclosure. You don't hand over the keys to everything after a first meeting.
Instead, you structure your room in layers that match the investor's level of commitment, and the data room itself only opens once an NDA is in place.
Your non-confidential pitch deck and one-pager are your outreach toolkit. You share those freely through email, DocSend, and in meetings.
But the moment you're sharing financials, cap tables, or anything proprietary, that's the data room. And the data room lives behind an NDA.
Here's the full structure at a glance:
Now let's break down what goes in each layer, and why.
YOUR OUTREACH TOOLKIT
Before we get into the data room itself, let's be clear about what lives outside of it. These are the non-confidential materials you share freely to generate investor interest:
Non-confidential pitch deck (the version you send cold or present in first meetings)
Executive summary / one-pager
Company website and LinkedIn presence
These are marketing materials. Their job is to get you to the meeting where an investor says, "This is interesting, let's go deeper."
That's when the NDA gets signed and the data room opens.
LAYER 1: THE DATA ROOM
Share after: NDA signed, good first meeting or strong inbound signal
This is the core room that proves your business is real. Once an NDA is in place, you can walk the investors through the building blocks of your business:
Cap table (clean, current, in a format like Carta or a simple spreadsheet)
Historical P&L + monthly burn rate (show the path from revenue through cash outflow)
Company milestone timeline (key dates: founded, key hires, grants, data readouts)
Pipeline overview (high-level: programs, stages, key upcoming milestones)
Corporate documents (articles of incorporation, bylaws, shareholder agreements)
An investor associate should be able to review this in 20-30 minutes.
LAYER 2: THE DILIGENCE ROOM
Share after: NDA signed, clear deep interest, partner meeting request, or early term sheet discussions
This is where investors build their investment memo. Everything in this layer should help an investor answer: "Can I make the case for this company at my partner meeting?"
Financial model + forward projections (12-18 months at seed-Series A; further out for later stages)
Key metrics / traction data (more on what this means by subsector below)
Curated scientific data (preclinical results summaries, mechanism of action overview, development timeline with stage gates)
IP landscape summary (patent portfolio overview (what's filed, what's granted, what's pending) without sharing the full formal opinions)
Competitive landscape analysis (with your honest assessment of differentiation)
Customer / partner validation (LOIs, letters of support, pilot results)
Regulatory correspondence summaries (FDA meeting summaries, pre-sub feedback highlights, regulatory pathway plan)
Team bios + org chart (role clarity, key hires planned, advisory board)
An important factor to note: in the early stage, investors generally don't need, and don’t expect, 3-5 year financial projections.
What they do want to understand is your key milestones for the next 12-18 months and what you'll need to get there. Do you expect to sign a major contract with a provider? Are you expecting crucial toxicity data? What is your cash-conversion cycle?
Also: the key word in this layer is curated.
You're sharing the story of your science in a way that's rigorous and transparent, but you're not handing over raw datasets, formal legal opinions, or proprietary know-how.
Those are confirmatory materials that belong in Layer 3.
LAYER 3: THE VAULT (CONFIRMATORY DILIGENCE)
Share after: NDA signed + term sheet in hand (or deep-stage diligence with high-trust investors)
This is where investors verify that everything in Layer 2 holds up under scrutiny. Layer 2 tells the story; Layer 3 proves the story is true. If someone asks for this material before demonstrating serious intent, whether through a term sheet or a clear, substantive diligence process, that's a red flag about them, not about you.
Here’s what’s typically included:
Raw preclinical / clinical data packages (the underlying datasets, protocols, and full study reports behind the curated summaries in Layer 2)
Formal FTO opinions (freedom-to-operate - the full legal analysis confirming your product doesn't infringe existing patents, not just the summary)
Trade secrets and proprietary know-how (formulations, assay designs, algorithms - the things that make your science hard to replicate)
Detailed licensing agreements (full terms, inbound and outbound)
CMC / manufacturing documentation (process details, supplier contracts, scale-up plans)
Employment agreements, advisor contracts, option grants
How to protect your IP: Your trade secrets and raw scientific data should never be in the same folder as your financials or pipeline overview. Most modern data room platforms let you set permissions at the folder level, so Layer 3 only opens when the relationship warrants it. If you're using Google Drive or Dropbox, create separate shared folders with different access links.
What changes by company type
Here's how I think about what traction means across different types of companies, and what kind of data you should share:
Therapeutics | Medical Device | Health SaaS / Tools | Diagnostics | |
|---|---|---|---|---|
Layer 2 science & traction | MOA summary, preclinical data highlights, development timeline | 510(k) or PMA pathway status, design control documentation | MRR/ARR, retention cohorts, usage analytics | Clinical validation study summaries, analytical performance overview |
Layer 2 regulatory & IP | Pre-IND/IND meeting summaries, patent portfolio overview | Predicate device analysis, bench testing results summary | HIPAA compliance documentation (if applicable) | CLIA/CAP certification status, LDT pathway |
Layer 3 confirmatory | Raw preclinical datasets, full IND package, CMC process details | Design history file, full biocompatibility testing data | Source code architecture (if relevant), full customer contracts | Full assay performance data, reagent sourcing details, sample logistics |
If you’re an early-stage founder, don’t worry - there is no expectation to have all of this on day one.
The purpose of this framework is so you can know what to expect and so you're never scrambling when an investor asks for something specific.
The Do's and Don'ts
Some general guidance as you get your data room ready:
Do:
Name files consistently. Use a convention like: CompanyName_DocumentType_Date_Version (e.g., "Acme_PatentPortfolio_2026Q1_v2.pdf")
Include an Index document. A one-page table of contents at the top level that maps what's in each folder. Investors appreciate this as it signals you've thought about their experience.
Keep it live. Update as studies complete, patents progress, and metrics change. Stale documents erode trust faster than missing ones.
Make every deck claim traceable. If your slide says "$500k in LOIs," there should be a folder with those letters.
Track who's viewing what. Most VDR tools show analytics - who opened what, for how long. This tells you who's serious.
Offer a 15-minute walkthrough call. Investors usually appreciate a brief call to explain your room's structure. It shows confidence and saves everyone time.
Don't:
Don't open the data room before an NDA is signed. Your non-con deck and one-pager are your outreach toolkit. Everything else is confidential.
Don't share Layer 2 or 3 before the investor has earned it. Layer 2 opens when there's genuine interest. Layer 3 opens with a term sheet or deep-trust relationship. The burden of proof is on them.
Don't include raw data without summaries. Investors want insights, not spreadsheets. Include a one-page summary at the top of any data-heavy section.
Don't include board meeting minutes unless specifically asked. Same for tax returns and office leases. Investors will request these if they need them.
Don't use folder names like "Documents" or "misc." If you can't name a folder clearly, its contents probably don't belong there.
Don't forget version control. Date your files. When an investor sees "PitchDeck_FINAL_v3_REAL_FINAL.pdf," it doesn’t reflect well on you.
YOUR 30-DAY DATA ROOM SPRINT
Don't try to build the perfect data room in a weekend. Here's a realistic 30-day plan:
Week 1: Foundation (4-5 hours)
Choose your data room platform (see bonus tools below)
Create your 3-layer folder structure
Write your Table of Contents / Index document
Ensure your outreach toolkit is ready (non-con deck, one-pager)
Week 2: Financials & Corporate (5-6 hours)
Prepare clean monthly P&L and burn rate spreadsheet
Export and verify current cap table
Gather corporate formation documents (articles, bylaws)
Draft a company milestone timeline
Week 3: Science & IP (5-6 hours)
Prepare curated preclinical/scientific data summaries for Layer 2 (not raw data, highlight key findings)
Create a patent portfolio overview (one-page summary of what's filed, granted, and pending)
Compile pipeline overview with stage gates and key data readouts
Organize regulatory correspondence summaries chronologically
Identify which raw datasets, formal legal opinions, and trade secrets belong in Layer 3 only
Week 4: Polish & pressure-test (3-4 hours)
Cross-check: does every pitch deck claim have a supporting document?
Apply consistent file naming across all documents
Set up access permissions and layered sharing links
Invite a trusted advisor or board member to "test drive" the room and give feedback
Total time investment: ~18-21 hours across 30 days. That's less than 5 hours a week to go from nothing to investor-ready. And once it's built, maintaining it takes 1-2 hours a month.
BONUS RESOURCES
A few resources to help you get started.
Data Room Platforms
Not every founder needs a $500/month enterprise VDR. Here's how I think about it by stage:
Early-stage / Pre-seed (free or nearly free): Google Drive, Notion, or Dropbox. These work fine for Layer 1. The limitation: no view analytics, limited permissions, no watermarking. Acceptable when you're sharing with 5-10 investors.
Seed / Series A fundraise (purpose-built, $30-100/month): DocSend, Papermark, or Visible.vc. These give you link-level permissions, viewer analytics (who looked at what, for how long), and password protection. DocSend is particularly popular with biotech founders because you can see exactly which slides investors spend time on.
Active DD / Biotech-specific (enterprise, $200+/month): Ansarada, Intralinks, Firmroom, or Peony. These offer NDA-gated access, dynamic watermarking, screen-capture blocking, and regulatory compliance features (GxP, HIPAA). Use these when you're deep in diligence with multiple parties or managing pharma partnership conversations.
What to look for in any platform: granular folder-level permissions, view analytics, watermarking, mobile access, and the ability to revoke access after a process ends.
AI prompts for data room prep
Copy-paste these into ChatGPT or Claude to accelerate your data room setup. Replace everything in [brackets] with your details.
Prompt #1: Build Your Data Room Table of Contents
You are an experienced biotech venture capital associate preparing for a partner meeting. I'm building an investor data room for my [therapeutics / medical device / health SaaS / diagnostics] company at the [pre-seed / seed / Series A] stage.
Here's my company snapshot:
Lead program/product: [one sentence description]
Team size: [X employees]
IP status: [e.g., 2 patents filed, 1 granted, FTO completed]
Regulatory status: [e.g., pre-IND, 510(k) submitted, FDA breakthrough designation]
Key traction: [e.g., $200K in LOIs, 3 pilot customers, Phase 1 data expected Q3]
Create a Table of Contents organized in three tiers: (1) Overview Room - shared after a strong first meeting with any investor (2) Diligence Room - shared with investors showing serious interest or requesting deep dive (3) Vault - shared only after NDA execution and term sheet discussions
For each tier, list specific document names (not general categories). For example, write 'Monthly P&L Statement (Jan 2024–Present)' not 'Financial documents.'
Flag any items I likely don't have yet with [TO BUILD] and estimate how long each would take to create. Format as a numbered outline.
Prompt #2: Data Room Gap Analysis
You are a biotech-focused VC associate conducting due diligence on an early-stage investment. Your job is to review this data room and identify what's missing, what's unnecessary, and what needs improvement before a partner meeting.
Company type: [therapeutics / medical device / health SaaS / diagnostics] Stage: [pre-seed / seed / Series A] Raise target: [$X]
Here is every document currently in my data room: [Paste your full file list here, including folder names and document titles]
Please provide:
MISSING - Documents an investor at this stage would expect but aren't listed. Rank by priority (must-have vs. nice-to-have) and estimate time to create each.
REMOVE - Documents that add clutter, create unnecessary risk, or aren't relevant at this stage. Explain why.
UPGRADE - Documents that exist but likely need improvement (e.g., raw data that needs a summary page, outdated files that need refreshing).
RESTRUCTURE - Any folder organization changes that would make this easier for an associate to navigate in under 10 minutes.
Prompt #3: Write Section Executive Summaries
You are a biotech startup CEO writing data room cover pages for investor review. Your reader is a VC associate who has 5 minutes to understand each section before briefing a partner. Write in a professional but direct tone — no jargon without explanation, no filler.
Company: [Name] One-line description: [What you do in plain English] Stage: [pre-seed / seed / Series A]
Write a one-paragraph executive summary (150-200 words) for each of the following data room sections. Each summary should answer: What's in this section? What's the key takeaway? What should the reader pay attention to first?
Sections to summarize:
Financial Overview - Key highlights: [e.g., 18 months runway, $50K MRR, 40% month-over-month growth]
IP & Regulatory - Key highlights: [e.g., 3 patent families filed, pre-IND meeting scheduled Q2, FTO opinion complete]
Pipeline / Product - Key highlights: [e.g., lead compound in IND-enabling studies, second program in discovery]
Team & Governance - Key highlights: [e.g., 8 FTEs, 3 scientific advisors from top-5 pharma, independent board member]
Format each summary with the section name as a header, followed by the paragraph. These will be placed as the first page in each data room folder.
THAT’S A WRAP!
I'd love to hear from you: What's your data room experience been like? Did you overshare early on? Hold things too close? Have an investor ask for something that caught you off guard?
And if you’d like a second pair of eyes on your data room: reply to this email with a screenshot of your folder structure and/or your main questions or challenges, and I'll do my best to give you specific feedback on your current setup.
Hope this helps and see you next week!
- Vadim
PS: If you have someone on your team helping with fundraising or know another founder who could benefit from being in this community - I’d love to include them. They can join us here: [Join the Community]