The company once invested 13% of revenue in R&D but saw stagnant growth. The issue was that new products were primarily replacing older ones, not creating new markets. This improved profitability but highlighted the need to balance R&D between incremental improvements and true market expansion.

A COVID-19 trial struggled for patients because its sign-up form had 400 questions; the only person who could edit the PHP file was a grad student. This illustrates how tiny, absurd operational inefficiencies, trapped in silos, can accumulate and severely hinder massive, capital-intensive research projects.

The collapse of Katerra, which burned through $2-3 billion in VC funding, shows that simply applying factory models to construction is not enough. The startup's failure highlights that deep, systemic issues like logistics, regulation, and on-site complexity cannot be solved by capital alone.

Industrial biotech startups often fail trying to scale cost-effectively. Since customers rarely pay a premium for sustainability alone, directly replacing a cheap petrochemical is a losing battle. A better strategy is to develop unique products with novel functionalities.

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.

Large pharma companies are discovering that implementing AI to solve one part of the drug development workflow, like target discovery, creates new bottlenecks downstream. The subsequent, non-optimized stages become overwhelmed, highlighting the need for a holistic, fully choreographed approach to AI adoption across the entire R&D pipeline.

A common failure mode for well-funded biotechs is growing headcount too rapidly. Immunocore's CEO advises new leaders to pace themselves, emphasizing that drug development is a marathon. Prematurely scaling creates fixed expenses that can drain capital before key scientific milestones are hit.

Unlike most biotechs that start with researchers, CRISPR prioritized hiring manufacturing and process development experts early. This 'backwards' approach was crucial for solving the challenge of scaling cell editing from lab to GMP, which they identified as a primary risk.

According to Novartis's CEO, a top reason for rejecting potential biotech partners is their underinvestment in Chemistry, Manufacturing, and Controls (CMC). Startups often neglect this unglamorous work, leading to deal failure because the acquirer can't be sure the drug can be scaled efficiently and safely.