Unlike traditional drug development, cell therapy logistics require extremely close, integrated relationships with contract research (CRO) and manufacturing (CDMO) organizations. Due to the direct line from patient to manufacturing and back, these partners function as critical extensions of the core team to ensure timeliness and safety.

Instead of an exclusive deal, Zymeworks shared its platform non-exclusively with multiple pharma giants. This multi-partner strategy validated the technology, generated capital, and built a portfolio of royalty interests before the company developed its own internal pipeline.

Instead of viewing partnerships like Nvidia and Eli Lilly as a competitive threat, Recursion's CEO sees it as powerful validation for the AI drug discovery space. This activity shifts the industry conversation from skepticism ('Will this work?') to urgency ('Who will win?'), benefiting pioneering companies like Recursion by confirming their founding thesis and attracting more investment and attention to the field.

Synthakyne operates as a specialized 'cytokine engineering shop.' It develops its own assets in high-value areas like oncology (IL-2, IL-12) while simultaneously licensing its platform for other indications, such as inflammation, through major partnerships with Merck and Sanofi. This strategy generates capital and validates the core technology.

While its internal pipeline targets oncology, LabGenius partners with companies like Sanofi to apply its ML-driven discovery platform to other therapeutic areas, such as inflammation. This strategy validates the platform's broad applicability while securing non-dilutive funding to advance its own assets towards the clinic.

A pre-product CRO conducts thousands of market conversations to validate demand and guide the product roadmap. This de-risks development by ensuring you build a product that customers will actually buy, a task more suited to a sales expert than a founder.

Responding to Wall Street pressure to de-risk, large pharmaceutical firms cut internal early-stage research. This led to an exodus of talent and the rise of contract research organizations (CROs), creating an infrastructure that, like cloud computing for tech, lowered the barrier for new biotech startups.

The relationship between AI startups and pharma is evolving rapidly. Previously, pharma engaged AI firms on a project-by-project, consulting-style basis. Now, as AI models for drug discovery become more robust, pharma giants are seeking to license them as enterprise-wide software suites for internal deployment, signaling a major inflection point in AI integration.

For smaller biotechs, the key to a successful CRO relationship is treating them as a genuine partner. This requires moving beyond a transactional, fear-based dynamic to one of open communication and mutual respect. Biotechs should actively solicit CRO feedback, as they possess valuable cross-industry insights and can identify sponsor-side behaviors that need to change.