Times Square Capital mitigates biotech risk by investing after a company's first drug receives FDA approval. The investment thesis then focuses on the more predictable execution and market expansion risk (e.g., scaling sales, new indications) rather than the binary, high-stakes outcome of initial clinical trials.

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.

It's a fool's errand to predict specific trial results. A robust quantitative approach to biotech focuses on underlying drivers and base rates. It positions a portfolio so the random, unpredictable nature of trial events plays out favorably over time, guided by factors like valuation and specialist ownership.

Investors without a scientific background can de-risk biotech portfolios by avoiding early-stage "science projects" (Phase 1-2). Instead, they should focus on companies that have completed Phase 3 trials. This strategy shifts the primary risk from unpredictable scientific development to more analyzable commercial execution.

Even with big wins, a venture portfolio can fail if not constructed properly. The relative size of your investments is often more critical than picking individual winners, as correctly sized successful investments must be large enough to overcome the inevitable losers in the portfolio.

While investing in a crowded therapeutic space feels safer, returns are capped. A high-risk area like pancreatic cancer offers a better investment profile. A 50% chance of a 10x upside yields a 5x probability-adjusted return, outperforming a crowded space with an 80% chance of a 2x return.

Neurocrine mitigates the high risk of its late-stage psychiatry programs, which have uncertain outcomes until Phase 3, by investing in an obesity asset. This program offers the ability to see clear efficacy signals in early Phase 1B trials, providing faster data for decision-making and balancing portfolio risk and cost.

Rahul Aras learned from his first venture that combining a novel target, a new modality (gene therapy), and a unique delivery device created too many unknowns. At Iterion, he prioritized minimizing such variables to create a more manageable risk profile for investors and partners, focusing on a single core innovation.

While biotech cannot easily replicate tech's rapid iteration cycles due to high costs and long feedback loops, it can adopt the capital efficiency model of tech seed investing. The strategy is to kill flawed projects quickly and cheaply, ensuring that when you lose, you lose small.