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.

While the FDA is often blamed for high trial costs, a major culprit is the consolidated Clinical Research Organization (CRO) market. These entrenched players lack incentives to adopt modern, cost-saving technologies, creating a structural bottleneck that prevents regulatory modernization from translating into cheaper and faster trials.

A significant portion of biotech's high costs stems from its "artisanal" nature, where each company develops bespoke digital workflows and data structures. This inefficiency arises because startups are often structured for acquisition after a single clinical success, not for long-term, scalable operations.

The biotech sector lacks mid-cap companies because successful small firms are typically acquired by large pharma before reaching that stage. This creates a barbell structure of many small R&D shops and a few commercial giants. The assets, not the companies, transition from small to large.

Unlike software startups that can "fail fast" and pivot cheaply, a single biotech clinical program costs tens of millions. This high cost of failure means the industry values experienced founders who have learned from past mistakes, a direct contrast to Silicon Valley's youth-centric culture.

The biotech ecosystem is a continuous conveyor belt from seed funding to IPO, culminating in acquisition by large biopharma. The recent industry-wide stall wasn't a failure of science, but a halt in M&A activity that backed up the entire system.

The "takeout candidate" thesis often fails because corporate development teams at large firms won't risk their careers on optically cheap but unprofitable assets. They prefer to overpay for proven, de-risked companies later, making cheapness a poor indicator of an impending acquisition.

Exonic is building a platform for bioengineers to compete on open-source biological modeling, aiming to turn drug discovery into a meritocratic competition. This mirrors the model of crowdsourced hedge fund Numerai, applying a "wisdom of the crowd" approach to disrupt the closed, expensive R&D processes of large pharmaceutical companies.

Many engineers at large companies are cynical about AI's hype, hindering internal product development. This forces enterprises to seek external startups that can deliver functional AI solutions, creating an unprecedented opportunity for new ventures to win large customers.