AI Marketing for Biotechnology

Great science, invisible company. Investors fund what they understand.

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Who This Is For

Biotech founders, CSOs, and communications leads who need to build investor and recruiter attention between funding rounds — not just at the raise when it's already too late.

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The Real Problem

What's Broken in Biotechnology Marketing

Scientific credibility does not translate to investor or talent visibility

A great preprint in Nature and zero LinkedIn presence means investors and recruits diligence you through a Google search and find almost nothing. The science is real; the story is missing.

Founders and C-suite at pre-Series A and Series B biotechs

Company goes silent between milestones — audience disappears when you need it

Biotech companies publish on milestones and go dark in between. The audience you need at your next raise doesn't exist yet because you haven't been building it for the last 18 months.

Communications leads and marketing heads at biotech firms

Competing labs with louder brands win talent even when science is weaker

Scientists choose employers they've heard of and feel excited by. A lab that documents its work, culture, and discoveries online outrecuits a lab that only posts job listings.

HR directors and operations leads at biotech companies

The AI-Native Answer

How I Close the Gap With AI

biotech marketing 2026scientific storytelling LinkedInbiotech investor relations contentCSO personal brand strategybiotech thought leadershipscience communication strategy

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Science translation system

A repeatable pipeline that turns papers, preprints, and milestones into three layers of content: expert-level, investor-level, and public-level — drafted with AI, accuracy-checked by your scientists.

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Founder/CSO visibility program

Position your scientific founders as the credible voice of the field — consistent LinkedIn presence built on a 3-hour-monthly input from the founder, AI handling the heavy drafting.

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Milestone momentum engine

Every publication, patent, and partnership becomes a 10-piece content wave instead of a single forgotten announcement.

My Edge

Why This Works Specifically for Biotechnology

Science translation system: one paper → three audience layers of content

Expert-level accuracy for HCPs and scientists, investor-accessible summary for LPs and VCs, public-interest angle for journalists and recruits — all from a single source document.

Founder/CSO visibility that requires 3 hours monthly, not a comms department

I extract thinking from a monthly founder session, then AI produces 12–16 posts per month. The founder gets LinkedIn authority without spending their science time on social media.

Milestone momentum: every result becomes 10+ pieces, not one announcement

Publications, patents, partnerships — each becomes a wave: pre-announcement teaser, announcement post, technical explainer, Q&A, related science thread, and media hook. One event, sustained visibility.

The Three-Phase Roadmap

Phase 1 · Now

Content System

Positioning + AI-leveraged content engine. The foundation everything else compounds on.

Phase 2 · Next

Automation

Lead nurture, lifecycle flows, and distribution automation built on the working content layer.

Phase 3 · Later

AI Agents

Agent-assisted qualification, FAQ handling, and service workflows — once the data and audience exist.

Common Questions

Will simplifying the science damage credibility?

Layered content protects rigor: the expert layer stays precise; the accessible layers link down to it. Translation is not dilution — it is distribution.

We are pre-revenue — why market at all?

Biotech "customers" are investors, partners, and talent. All three are audiences, and all three diligence you online before any meeting.

What about scientific accuracy with AI drafting?

AI drafts structure and plain language; your scientists review claims. The system enforces a source-citation rule on every scientific statement.

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