Programs, events, and resources to help young scientists learn about, and create careers in, biotech startups and venture capital.
We maintain a database of biopharma startup funding and exit activity. The database covers $17B worth of venture investments from 2018 to today and hundreds of companies and investors.
See which investors fund companies like yours. This is best for Series A rounds and beyond, data for seed rounds is more sparse. All of these investors have funded at least one therapeutics company since January 2018.
Search for recently funded startups (have raised venture money since January 2018). These companies may or may not be hiring, but typically companies hire aggressively after a fundraise.
See how venture funding in 2019 compares to 2018's record levels of funding.
Our database contains additional detailed data on startups, IPOs and M&A activity. To learn more, contact us.
1:42 Panel start
2:56 Panelist introductions
15:00 How to get into venture
18:51 Getting in front of VCs
23:10 How early-stage funds source deals
25:12 How VCs start companies
30:14 Accelerators and incubators
31:29 What do late-stage funds look for?
33:07 What do early-stage funds look for?
34:33 What do VCs look for in a team?
37:39 How do VCs evaluate deals?
42:06 Advice for first-time scientific founders
43:52 Value of grit
46:25 How to handle feedback
49:33 How long does it take VCs to make an investment?
51:23 Interesting trends in biotech
52:07 Opportunities in CNS / neuro
55:37 Next-gen immuno-oncology
56:25 Getting to clinical proof of concept faster and cheaper
59:15 Precision medicine -- what it really means and why it matters
1:00:02 Programming organisms, new therapeutic modalities
1:00:42 Digital therapeutics -- need for evidence
1:02:45 What makes a great team?
1:07:38 Biotech VCs vs. angel investors
1:10:17 IP for early-stage companies
1:14:11 IP for late-stage companies
1:16:04 IP attorney's thoughts on startup IP
1:17:39 Valuing platforms vs products
1:23:31 The case for the entrepreneur
1:25:47 Lean startup principles applied to biotech