First conversation · Wednesday, October 28, 2026

Putting validated definitions in front of every sponsor that needs them.

A first look, prepared for Matt Veatch and the Navidence team. It's a cold read: built from public sources and our own life sciences database before we've talked. After today we'll update it with what you tell us.

Navidence · 9 people · seed, 2026RWE · HEOR · Epidemiology buyersPrepared by Brian Elbert, BioCreative Strategies
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Our 30 minutes

What we'd like to cover

Who we are

A consultancy that builds and operates AI-native commercial systems for life sciences.

We build life sciences companies their own commercial system: custom software that finds the market, runs LinkedIn and email, and carries every conversation into a sales pipeline. It's built on our method and our own pre-built kit, so it stands up in weeks, on our stack or yours, with any model. We build it with your team, so they become fluent in AI as it grows, and you own it from the first day.

Brian Elbert · Founder & President

Fifteen years selling into life sciences: the operating room, blood centers, cell and gene therapy, and CRO services. First commercial hire more than once, building the system from nothing each time. He started BioCreative in 2024 because every company he sold for had good science and good people, and nothing connecting the market data, the outreach and the pipeline.

What we believe
  • A person decides at the edge. Every field traces to its source and stays empty when the source doesn't say it. Nothing is sent without someone approving it.
  • You own all of it, from day one. The data, the database, the repository, the agents. Build-along, not build-dependency.
  • Depth over breadth. In a market as specific as RWE, knowing every account that matters beats reaching many that don't.
  • The method is the asset; the model is rented. AI is a tool in the toolbox. What lasts is the foundation built around it.
  • Fluency comes with the system. Your team learns to run and extend it while we build.
Our read of Navidence

What we see from the outside. Tell us where we're wrong.

What you've built

Computable Operational Definitions: validated, reusable definitions of the patients, exposures and outcomes in a real-world study, so study design starts from precision instead of being rebuilt every time. RWE Sherpa, and Navigate: Code Lists since May.

  • January
    Seed round; Andrew Ecob steps up to Chief Commercial Officer
  • March to May
    Datavant, Trio Health, Panalgo and RTI International; Navigate: Code Lists launches
  • August
    Komodo Health; ten posters at ISPE
  • September
    "Precision or Illusion?" with PurpleLab; the RISE Summit panel on precise definitions

1 Partners carry the lists. Sponsors still need the conversation.

Five platforms now put your definitions in front of analysts. The people who decide how a study is designed, the RWE, HEOR and epidemiology leads at sponsors, still need to understand why validation matters. That's an education job, done sponsor by sponsor.

How much of this year's growth came through partners, and how much did you sell direct?

2 The moment a sponsor needs you is public.

A new observational study, a post-marketing requirement, a label expansion, a new head of RWE. Each one leaves a trace, usually before a vendor gets a call.

How do you hear about these today?

3 Nine people, enterprise buyers.

Selling to Merck, AstraZeneca and Novo Nordisk with a team of nine means leverage matters more than headcount. The website's only door today is a Contact Us form.

What would the commercial side need to look like for 2027?
Your market, already mapped

The RWE, HEOR and epidemiology leaders you sell to.

This is what our database holds today for your buyers, before any work for you. The build fills it in, finds and verifies emails, and keeps it current.

721people in RWE, HEOR and epidemiology roles
161organizations, 114 of them drug developers
527at director level and above
100%with a LinkedIn profile; emails found in step one

The sponsors with the deepest teams

People in our database, by sponsor. Filter by role above.

RWE / RWDHEOREpidemiology
SponsorRole

A sample of leaders, shown by role only. Names, profiles and fit scores live in your system, not on a web page.

Buying moments

The signals we'd wire to every account.

Each one is public. We'd tie it to the sponsor and the person who owns study design, and give your team a short weekly list of who's moving and why. What we'd build for you

+

A new observational study is registered

ClinicalTrials.gov, the EU PAS Register.

Why it matters: someone is defining a cohort right now. Who we'd reach: the study lead and the head of epidemiology.
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FDA asks for post-marketing evidence

Post-marketing requirements and commitments in approval letters.

Why it matters: a regulator-facing study whose definitions must hold up. Who we'd reach: RWE and pharmacovigilance leads.
+

A label expansion or new indication

FDA and EMA approvals, supplemental filings.

Why it matters: new populations, new outcomes, new code lists. Who we'd reach: HEOR and medical affairs.
+

A new head of RWE or HEOR

Hires and promotions at the sponsors you target.

Why it matters: new leaders set new standards in their first six months. Who we'd reach: the new leader, early.
+

Their posters at ISPOR and ISPE

Abstracts by sponsor and disease area.

Why it matters: you can see which definitions they're using, and where validation is thin. Who we'd reach: the authors.
+

A biotech heads into Phase 3 or launch

Funding rounds, pivotal readouts, launch planning.

Why it matters: evidence planning starts before launch. Who we'd reach: the first RWE or HEOR hire.
What a signal turns into (an illustration, not a real send)
"Saw your team registered a new observational study in [disease area] this month. The cohort definition is usually where studies like this get rebuilt from scratch. We keep validated, documented definitions for [the patients and outcomes involved], ready to drop into the protocol. Worth fifteen minutes before it locks?"
Drafted by the messaging agent from the signal and your positioning. A person on your team edits and approves it before anything goes out.
What we'd build

One commercial system, built on a foundation, run by agents, owned by you.

The same four-layer method we run BioCreative on. Each layer builds on the one below. Click through.

Context and data, stood up together

Your own database: every sponsor, CRO and RWD vendor that matters, the RWE, HEOR and epidemiology people at each, scored to your fit. Next to it, the context that gives it meaning: your positioning, your proof, your definitions of a good account. Precision first, the way you'd want a study built.

The work, written out, and the tools it calls

Finding and verifying emails, reading a registry for new studies, scoring an account, drafting in your voice, building a list for a campaign. Each is written down step by step, so it runs the same way every time and anyone can check it.

Agents that do the work, screens where you see it

A signals agent watching for buying moments. A research agent keeping accounts current. A messaging agent drafting for approval. A campaign manager running email and LinkedIn. Your dashboard, in your brand, where it all shows up, and every reply lands in one pipeline.

Run as one system

The pieces run together, are checked, and get better every week. We run it with your team at first; over time your team runs it. It lives on your own server and repository, with any model.

1 · The foundation: context and data
2 · Skills and tools
3 · Agents and surfaces
4 · The operating system

The core build

  • Your market database and an account and contact map, kept current
  • Email on dedicated, warmed domains, sequences in your voice
  • LinkedIn outreach from your own profiles
  • Live signals linked to every account
  • A sales pipeline run on Miller Heiman, shaped to how you sell
  • A dashboard and reports, plus training for your team
Build it with us

See it working, and start building yourselves if you want.

You've built an AI-native product. We'd like your commercial side to work the same way, with your team fluent in it. That's the part of this work we enjoy most.

See it

CellScale, a full demo

A complete commercial system on a demo company: market map, accounts, signals, composed messages and the pipeline. Picture it with your 700 leaders in it.

Use it

LifeSci Lens

Our market intelligence app on our life sciences database: trends, questions answered from the data, watched accounts, a live feed. We'll set you up with a login.

Build it

Free starter kits on GitHub

The Academy's starter templates: the foundation project and the Lens pack. Your team can start building on our method today, with or without us.

Where we'd start

The first five steps. Weeks, not months.

Foundation

Your ideal customer, and the market map built from our 700-plus leaders, filled in, in a database you own.

Contacts

Verified emails for the people who matter most.

Signals

The buying moments wired to each account, with a short weekly list of who's moving and why.

Campaigns

Email and LinkedIn in your voice, from your team, every reply in one pipeline.

Dashboard

Reports on top, and your team trained to run and extend it.

From here

Whatever's useful next.