Faced with China's superior speed and cost in executing known science, the U.S. biotech industry cannot compete by simply iterating faster. Its strategic advantage lies in
Startups often fail by making a slightly better version of an incumbent's product. This is a losing strategy because the incumbent can easily adapt. The key is to build something so fundamentally different in structure that competitors have a very hard time copying it, ensuring a durable advantage.
The next leap in biotech moves beyond applying AI to existing data. CZI pioneers a model where 'frontier biology' and 'frontier AI' are developed in tandem. Experiments are now designed specifically to generate novel data that will ground and improve future AI models, creating a virtuous feedback loop.
Using AI for incremental efficiency gains (10% thinking) is becoming table stakes. True competitive advantage lies in 10X thinking: using AI to fundamentally reimagine your business model, services, and market approach. Companies that only optimize will be outmaneuvered by those that transform.
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.
China is no longer just a low-cost manufacturing hub for biotech. It has become an innovation leader, leveraging regulatory advantages like investigator-initiated trials to gain a significant speed advantage in cutting-edge areas like cell and gene therapy. This shifts the competitive landscape from cost to a race for speed and novel science.
The mantra 'ideas are cheap' fails in the current AI paradigm. With 'scaling' as the dominant execution strategy, the industry has more companies than novel ideas. This makes truly new concepts, not just execution, the scarcest resource and the primary bottleneck for breakthrough progress.
Nubar Afeyan argues that companies should pursue two innovation tracks. Continuous innovation should build from the present forward. Breakthroughs, however, require envisioning a future state without a clear path and working backward to identify the necessary enabling steps.
The future of biotech moves beyond single drugs. It lies in integrated systems where the 'platform is the product.' This model combines diagnostics, AI, and manufacturing to deliver personalized therapies like cancer vaccines. It breaks the traditional drug development paradigm by creating a generative, pan-indication capability rather than a single molecule.
Attempting to hoard technology like a state secret is counterproductive for the US. The nation's true competitive advantage has always been its open society, which enables broad participation and bottom-up innovation. Competing effectively, especially in AI, means leaning into this openness, not trying to emulate closed, top-down systems.
The next decade in biotech will prioritize speed and cost, areas where Chinese companies excel. They rapidly and cheaply advance molecules to early clinical trials, attracting major pharma companies to acquire assets that they historically would have sourced from US biotechs. This is reshaping the global competitive landscape.