Investors bet against new drug launches because the shift from a research-focused culture to a commercial one is seen as an 'unnatural transition.' Companies are graded harshly on early results, creating a predictable valuation dip that hedge funds exploit, as seen with Portola Pharmaceuticals.

Unlike other sectors, a massive rally in a biotech stock often signals a significant de-risking event, such as positive trial data. This new certainty allows for more confident revenue projections, making it a potentially safer entry point despite the higher price.

An investor's best career P&L winners are not immediate yeses. They often involve an initial pass by either the investor or the company. This shows that timing and building relationships over multiple rounds can be more crucial than a single early-stage decision, as a 'missed round' isn't a 'missed company'.

After reacquiring a "failed" ALS drug, Neuvivo's team re-analyzed the 200,000 pages of trial data. They discovered a programming error in the original analysis. Correcting this single mistake was a key step in reversing the trial's outcome from failure to success.

To save money, Rhythm's leadership considered canceling a clinical study because the prevailing scientific logic suggested their drug wouldn't work. The study's unexpected, resounding success became the company's pivotal turning point, highlighting the value of pursuing scientifically contrarian ideas.

Rather than abandoning an investment category after a failure, some VCs intentionally fund the same idea again in a new company. This strategy is not about repeating mistakes, but a high-conviction bet that the core idea was simply ahead of its time and that a change in timing or underlying technology will enable its success.

The fundamental purpose of any biotech company is to leverage a novel technology or insight that increases the probability of clinical trial success. This reframes the mission away from just "cool science" to having a core thesis for beating the industry's dismal odds of getting a drug to market.

One of the few working quantitative models in biotech is to systematically purchase stocks after they have crashed on bad news. This low-batting-average, high-slugging-percentage approach is terrifying but can work by getting favorable odds on a recovery, provided the company has sufficient cash runway to survive.

Lonsdale recounts passing on brilliant founders with seemingly terrible ideas, only to watch them pivot and build billion-dollar companies like Cursor. The lesson for early-stage investors is to prioritize backing exceptional, world-class talent, even if their initial concept seems flawed, as they possess the ability to find a winning strategy.