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Biotech

What we learned from Biotech YC applications

Aggregate insights from real applications roasted on YC Roaster — the patterns YC partners look for, and the weaknesses that come up over and over.

Apps analyzed

19

Average score

3.85 /5

Updated

Jun 15, 2026

Score breakdown — Biotech average

App Completeness4.32/5
Early Traction3.27/5
Team Quality4.09/5
Market4.17/5
GTM3.56/5
Scalability3.97/5
Monetization3.53/5

Biggest weaknesses

Where Biotech applications consistently fall short.

  • 1. Early Traction3.27/5
  • 2. Monetization3.53/5
  • 3. GTM3.56/5

Strongest dimensions

Where Biotech applications tend to do well.

  • 1. App Completeness4.32/5
  • 2. Market4.17/5
  • 3. Team Quality4.09/5

Score distribution

0-1
0
1-2
0
2-3
1
3-4
9
4-5
9

What our AI judge actually said

Anonymized critique from real Biotech applications (shared with founder consent).

Eight months full time with zero revenue, just $5 activation fees from four labs, no proof pilots convert to paid.

7.3/10·Smart team with rare insight on frontier research, but traction is all pilots, no revenue proof.

June for a deployable prototype is late when one founder is part-time until July and you have zero users.

6.9/10·Strong problem and wedge, but execution velocity is too slow to matter without dramatic acceleration.

You have 8 pilots and 100% say they'll pay, but your revenue is still zero, willingness to pay is not a business model.

8.0/10·Rare founder-market fit and fast execution, but you need 10 paying customers to prove this scales beyond pilots.

Zero revenue after 8 months and pilots that need founder calls means this might be consulting dressed up as software, not a scalable product yet

7.8/10·Real product, real researchers want it, strong team, but prove pilots convert to cash and self-service actually works without you

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