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.

Beyond the thesis, first-time biotech funds must explicitly align with LPs on the 6-to-9-year journey from seed to exit. Daniel Fero stresses finding LPs who understand their capital will be locked up for a long duration, unlike in crossover funds with shorter horizons. This "psychological fit" on capital flow expectations is crucial for a stable fund.

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.

Tech-focused venture firms are finding their AI investment thesis fails in biotech. Despite massive paper profits in tech AI, their biotech AI portfolios show negative returns. This is because AI has yet to solve the complex biological bottlenecks of drug development, particularly in clinical trials, which remain slow and costly.

The biotech industry recently endured its own "dot-com bust." Post-COVID hype gave way to investor impatience with the sector's fundamental realities: it takes over 10 years and massive capital ($200B/year industry-wide) to get a drug approved, leading to a sharp market correction.

Drug development can take a decade, a timeframe that misaligns with typical investor horizons and employee careers. Success requires navigating fluctuating capital market cycles and implementing strategies to retain key scientific talent for the long haul.

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.

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.

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.