• Avoid or consider a speculative short in RXRX: the speaker sees its roughly $2 billion valuation as unsupported by its pipeline and flags about $375 million in annual cash burn and dilution risk; no price target was provided.
• Treat TWST cautiously rather than shorting outright: the business is growing, but its roughly $10 billion valuation assumes sustained high growth despite low margins and projected losses through 2028.
• Do not act on the ASML “blowout earnings” claim—it was unverified hearsay, and trading on material nonpublic information carries legal risk.
• Avoid averaging down in NKTR without a clear, independently researched investment thesis; the speaker offered no evidence-based turnaround case.

Recursion Pharmaceuticals (RXRX)

• The speaker was strongly bearish and called Recursion a compelling short, arguing its roughly $2 billion valuation was unsupported by its pipeline.
  • He criticized several programs as targeting mechanisms he viewed as unexciting, crowded, or previously explored by pharmaceutical companies.
  • He said some programs appeared to have been paused, discontinued, or unsuccessful, and questioned whether the company’s AI platform had materially improved drug discovery.
  • He highlighted approximately $375 million in annual cash burn and about $500 million in cash, raising concerns about financing needs and dilution. He also noted that shares outstanding had increased from roughly 300 million to 500 million.
  • He considered a PI3K-alpha program the most potentially interesting asset, but said the area was competitive and that the opportunity did not, in his view, justify the valuation.
  • He cited a share price of about $4.49 during the discussion and said the stock had rallied recently.

Takeaways

• The discussion presents RXRX as a high-risk, speculative biotech: the investment case depends on clinical progress and on whether its platform produces valuable drugs—not simply on the use of AI.
• The speaker’s bearish view centers on pipeline quality, cash burn, dilution, and competition. These are points to investigate independently; the transcript does not establish that any specific program has definitively failed.
• No price target or explicit short-entry level was given.

Twist Bioscience (TWST)

• The speaker described Twist as a real operating business with a history of robust growth, while arguing that its valuation was very demanding.
  • He cited historical revenue growth rates ranging roughly from 20% to 46% and referred to recent year-over-year growth of 23%.
  • He projected growth could accelerate to about 40%, but acknowledged that this would require exceptionally strong sequential growth and called the longer-term assumptions in his model very optimistic.
  • He pointed to low gross margins, continuing losses, and a forecast in his model of losses continuing until 2028.
  • He said the company’s biopharma-related revenue was a small part of the business and argued that much of its activity was not directly tied to AI drug discovery.
  • He cited a market capitalization of about $10 billion and called the valuation excessive, but said he was reluctant to short a company with strong, compounding growth.

Takeaways

• TWST offers exposure to biological research tools and DNA synthesis, but the transcript’s bull case rests on sustained high growth while the bear case rests on valuation, margins, and profitability.
• The speaker’s view was mixed: skeptical of the price, but cautious about shorting because the business had continued to grow.
• Treat the 40% growth assumption as a speculative scenario, not a company outlook or a stated price target.

Moderna (MRNA)

• The speaker said he was still short Moderna and expressed frustration with the stock trading around $210.
• He provided no detailed discussion of Moderna’s business, pipeline, valuation, or reasons for the short position.

Takeaways

• The transcript signals a bearish position, but gives too little supporting analysis to assess the thesis.
• No price target, catalyst, or timeline was mentioned.

Nektar Therapeutics (NKTR)

• The speaker said Nektar had continued to fall and described a personal holding that had declined about 50%.
  • He said the position had shrunk from roughly 30% to 15% of the portfolio as it fell.
  • When asked about adding, he said he did not know the company well and did not think one should buy more.

Takeaways

• The speaker’s comments are a caution against averaging down without a well-understood investment thesis.
• He did not provide a detailed view of Nektar’s prospects, a price target, or a timeline.

ASML (ASML)

• The speaker challenged a viewer who claimed to work at ASML and warned them not to share or seek to share insider information.
• He said he had heard the quarter had gone well and that the company might report “blowout” numbers, while accusing the viewer of making unsupported claims.

Takeaways

• The positive earnings comment was presented as hearsay, not verified analysis. Do not treat it as a reliable forecast or trade signal.
• The exchange underscores the legal and investment risks of trading on material nonpublic information. No price target or recommendation was given.

Liquidia (LQDA)

• Liquidia was briefly mentioned in connection with proposed resolutions involving United Therapeutics.
• The speaker also said he was “still in” what appears to be a Liquidia position, but the surrounding discussion did not provide a clear investment thesis or detailed analysis.

Takeaways

• The transcript offers insufficient information to evaluate the position. No price target, timeline, or specific recommendation was stated.

Schrödinger (SDGR) and Ginkgo Bioworks (DNA)

• SDGR and DNA appear in the episode title, but the transcript does not provide substantive company-specific discussion of either ticker.

Takeaways

• There is not enough information in this transcript to draw investment conclusions about these companies.

AI-enabled drug discovery and biotech tools

• The speaker was broadly skeptical that AI, by itself, creates a compelling drug-development investment case.
  • For Recursion, he argued that several targets and development timelines sounded similar to conventional drug-development work, rather than clear evidence of an AI-driven advantage.
  • For Twist, he saw a potentially valuable tools business, but questioned whether its products were meaningfully benefiting from AI.
  • He distinguished between biotech companies developing drugs and “tech bio” or tools businesses serving research markets.

Takeaways

• Evaluate AI-biotech companies by the quality of their products or drug candidates, clinical evidence, commercial traction, cash needs, and valuation—not by the AI label alone.
• The transcript expresses skepticism toward AI as a standalone investment thesis; it does not establish that AI has no useful role in drug development.