VC Bruce Booth warns that investors without deep biotech R&D experience are backing AI-driven drug discovery companies at inflated valuations. He predicts many will 'get their hands burned' due to flawed assumptions about value creation in the sector.
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The 2020-2021 biotech "bubble" pushed very early-stage companies into public markets prematurely. The subsequent correction, though painful, has been a healthy reset. It has forced the sector back toward a more suitable, long-duration private funding model where companies can mature before facing public market pressures.
Unlike tech investing, where a single power-law outlier can return the entire fund, biotech wins are smaller in magnitude. This dynamic forces biotech VCs to prioritize a higher success rate across their portfolio rather than solely hunting for one massive unicorn.
The abrupt failure of Arena Bioworks, a well-funded institute designed to spin off biotechs, highlights the current market's preference for de-risked clinical assets. Investors are shying away from long-timeline, platform-based models that require significant capital before generating clinical data, even those with elite scientific backing.
The life sciences investor base is highly technical, demanding concrete data and a clear path to profitability. This rigor acts as a natural barrier to the kind of narrative-driven, AI-fueled hype seen in other sectors, delaying froth until fundamental catalysts are proven.
AI companies raise subsequent rounds so quickly that little is de-risked between seed and Series B, yet valuations skyrocket. This dynamic forces large funds, which traditionally wait for traction, to compete at the earliest inception stage to secure a stake before prices become untenable for the risk involved.
The current AI investment climate feels as 'risk-free' as the 2021 bubble. Venture firms are likely using flawed loss-ratio models, underestimating how many AI 'unicorns' will fail to generate returns, just as they did with the B2B SaaS unicorns from the previous cycle.
A massive disconnect exists where scientific breakthroughs are accelerating, yet the biotech market is in a downturn, with many companies trading below cash. This paradox highlights structural and economic failures within the industry, rather than a lack of scientific progress. The core question is why the business is collapsing while the technology is exploding.
Despite a stable flow of absolute dollars into biotech venture, the sector's relative share of all VC funding has shrunk from ~14% to ~7%. This is due to the denominator effect of massive capital flooding into AI-focused tech companies.
The past few years in biotech mirrored the tech dot-com bust, driven by fading post-COVID exuberance, interest rate hikes, and slower-than-hoped commercialization of new modalities like gene editing. This was caused by a confluence of factors, creating a tough environment for companies that raised capital during the peak.
In the current AI hype cycle, a common mistake is valuing startups as if they've already achieved massive growth, rather than basing valuation on actual, demonstrated traction. This "paying ahead of growth" leads to inflated valuations and high risk, a lesson from previous tech booms and busts.
