List of recently funded biotech startups

by Richard Murphey

2020 is shaping up to be the biggest year for biotech venture funding on record, with almost $17B invested in biopharma startups through Q3 2020.

Where is this money going? This post will examine the kinds of biotech startups that venture capitalists are investing in. The post includes:

  • A tool for searching for biotech startups and investors by disease area, development stage and location
  • A list of biopharma startups that raised venture capital in the last 30 days
  • A qualitative and quantitative description of the characteristics of companies that receive venture funding

A quick note on terminology: in this post (as in all my other posts), I define "biotech" as companies developing FDA-regulated prescription medicines. So no diagnostics, tools, devices or service companies. I use "biotech" and "biopharma" interchangeably.

Biotech startup and investor search

Search for biotech startups and investors that have raised money or made investments since January 2018. Most VC-backed startups these days are oncology or rare disease companies at preclinical stage or earlier, and most are located in the San Francisco Bay Area or Boston. If you're searching for companies that don't meet any of those criteria, you'll get more search results if you leave at least one search field blank.

Search for biotech 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 biotech startups

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.

Our data has good coverage of Series A rounds and beyond, but it is harder to find data on seed funding. Most of the active Series A investors in biotech do seed investing as well, but often in companies they create in-house. In the last few years, tech VCs have become more active seed investors in biotech. A tech fund called Nfx has a good list of tech seed investors who have done some biotech.

The easiest way to build DCF models

Build robust biotech valuation models in the browser. Then download a fully built excel model, customized with your inputs.

List of recently funded biotech startups

Below is a list of biotech startups that have received venture funding in the last 30 days. It is updated on a weekly basis. Our coverage of Series A and later deals is on par with that of paid subscription databases, but we can't guarantee we catch everything. If we miss something let us know.

What are the characteristics of the top biotech startups?

If we define “top biotech startups” as “innovative biotherapeutics companies started in the last 50 years that were acquired for or currently trade at $10B+”, the most surprising characteristic is that most of these companies have relatively inexperienced CEOs (CEOs under the age of 40). It’s hard to find comprehensive data on CEO age and biotech startup performance, but I did a writeup of this topic here.

If we define “top biotech startups” as “biotech startups that went public from 2018-Q1 2019” (here I’m just focused on therapeutics companies, not device, diagnostic, agtech, etc):

  • ~25% developing small molecule drugs
  • ~25% developing gene or cell therapy
  • ~20% developing large molecule drugs
  • 30% developing cancer drugs
  • 20% developing rare disease drugs

This data comes from our startup database and analysis of IPO prospectuses.

More qualitatively, successful biotech startups:

  • Develop drugs for severe unmet medical needs (ie cancer, or severe / neglected rare diseases)
  • Have some novel biological / biochemical insight that gives them a better understanding of disease biology or a better way to hit a well-understood target
    • If you are drugging a novel target, you really won’t know if it “works” until you test it in people. That takes a long time and a lot of money, and the risk that it works in animals / in vitro but fails in people is high
    • If you are developing some chemical / biologic that can drug a pathway or target that is known to be a big driver of disease but hasn’t previously been druggable, you can get a sense for whether it’s working a bit earlier / for less money
  • Have good disease models that correlate with human clinical outcomes
  • Have robust data to show the target is valid, the molecule hits the target enough / the right way / without too much non-specific activity, the molecule has drug-like qualities, is safe, etc.
  • Have a tractable clinical development plan: can get initial data on whether the drug is effective in humans quickly / cheaply. Phase 2 / 3 failure is the biggest driver of the cost of drug development. Reducing the cost and risk of your clinical program is important
    • Phase 1 or 2 study with biomarker endpoints that are predictive of clinical outcomes endpoints
    • Homogenous, well-defined, ideally genetically defined patient populations
    • Take advantage of expedited FDA pathways like accelerated approval, breakthrough designation, fast track, etc. (cancer, severe rare disease)
  • Have some experience on the management team. While you want diversity on your management team, you need people with technical and professional experience in the various aspects of drug development.
  • Have an intellectually honest “truth seeking” culture. You want a management team and investor syndicate that is willing to kill programs as early as possible if they don’t work. Often this means that VCs run the companies through the early stages, as their jobs aren’t on the line if the program fails. If the management team just wants to push programs forward even if the data suggest that’s a bad idea (or if the management team doesn’t listen when told the data suggest things aren’t going as planned), that’s a bad sign

The easiest way to build DCF models

Build robust biotech valuation models in the browser. Then download a fully built excel model, customized with your inputs.

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