Seedy19: A 35x Return From Biotech Investing

Episode Summary

Executive Summary: The conversation explores how a generalist investor learned biotech through real-world exposure, public research, and asymmetric catalyst-driven trades. The guest argues biotech offers unusually large, fast returns because valuations can re-rate sharply around FDA readouts, approvals, M&A, and proxy trades. He explains how he built a 35x account using common stock, covered calls, and put writing, then highlights current ideas in Vera, Eras, and other names, while stressing that momentum, diligence, and timing matter more than formal science training.

Main Topics: How the guest entered biotech investing (Priority: 5/5): He came from a non-science background, worked in Big Four consulting, and got pulled into healthcare during COVID through a pharmaceutical rotation. Curiosity, reading, and conversations with others led him into biotech investing. Biotech as a high-asymmetry market (Priority: 5/5): He frames biotech as one of the few sectors where valuations can move dramatically on binary outcomes tied to real assets and drugs, creating both huge upside and total loss risk. Portfolio construction and trade structure (Priority: 5/5): He explains using common stock, covered calls, and put writing rather than calls, focusing on knowing downside floors, catalyst timing, and asymmetric setups. Case studies of winning biotech trades (Priority: 5/5): He cites Eurogen, Abivax, Nectar Therapeutics, Q32 Bio, and Bright Minds as examples where FDA catalysts, mispricing, or proxy trades produced massive gains. Current ideas: Vera and Eras (Priority: 4/5): He argues Vera is a likely acquisition candidate after a clean approval and that Eras is undervalued relative to RevMed because it offers a similar RAS-related opportunity at a lower valuation. How to source ideas as a generalist (Priority: 4/5): He recommends tracking specialist biotech hedge funds via 13Fs, reading company decks, using AI tools to translate science into plain English, and monitoring momentum and catalyst flow. Sector outlook and overhyped areas (Priority: 4/5): He remains bullish on biotech broadly, especially oncology, immunology, neuro, rare disease, and cardiovascular, while warning that crowded shorts and low-quality names remain dangerous and some AI-biotech narratives are overstated.

Key Arguments: Biotech is unusually attractive because real clinical and regulatory events can rapidly re-rate stocks, unlike more linear growth sectors. The guest’s strongest edge comes from understanding downside, catalyst timing, and de-risked setups rather than trying to predict every upside move in advance. Using common stock plus options strategies like covered calls and puts can capture upside while managing risk better than pure call buying. Post-data investing can be easier than pre-data speculation because the asset is de-risked and institutions often step in after proof points. Proxy trades matter: if one molecule or platform is validated by M&A or market success, similar assets can re-rate quickly even if they are smaller or less known. Comparables are useful, but valuation must also incorporate story quality, legal risk, safety, durability, and how much big pharma is willing to pay. Generalists can now enter biotech more effectively because AI tools help decode papers, trial data, and company decks. Momentum is a major force in this market cycle, and many biotech names still have strong re-rating potential despite recent rallies. Shorting biotech is risky because headlines and binary events can cause abrupt squeezes, especially in crowded names. The most attractive therapeutic areas today are oncology, immunology, neuro, rare disease, and certain cardiovascular niches, while AI in biotech is more of an accelerator than the main investment thesis.

Data Points: Portfolio return: 35-fold - The guest says his whole account returned 35x in 2025 using equities, covered calls, and put writing. Follower growth: From a couple hundred to 21k followers - He says public idea sharing on X helped his account and audience grow substantially over the year. Eurogen stock move: $3.50 to $38 - A PDUFA/approval setup with mixed ODAC led to a major re-rating after approval. Eurogen trade return: 7.3x - He was called out at $10 after buying around $3.50 and selling calls. Abivax stock move: Up 2,000% - He describes Abivax as a mispriced, cash-constrained but promising UC asset after positive phase two and blinded vendor data. Abivax downside estimate: 95% to 100% - He says the company had about one week of runway left, implying extreme downside if the asset failed. Nectar Therapeutics stock move: 20 cents to $19 - He cites a litigation/mispricing situation where a known signal eventually led to a huge re-rating. Q32 Bio / QATI stock move: $15 to $150 - He says leaked embargoed data allowed him to buy early, and the stock later surged. RevMed market cap: $40 billion - Used as the benchmark for the RAS/oncology opportunity and comparative valuation discussion. RevMed commercial status: Pre-commercial / zero revenue - He notes the company had not yet sold a drug but was still valued at around $40 billion. Eras stock move: $3 to about $20 - He says ERAS ran from roughly $3 at the start of the year to about $20. Bright Minds stock move: $1 to $75 - A proxy trade after a similar molecule was acquired for billions triggered a huge rally. Longboard acquisition value: About $2.2 billion to $2.5 billion - He references the takeout as the catalyst that exposed Bright Minds’ value. XBI level: About $66 to $170-$180 - He cites the biotech ETF’s sharp recovery from last year’s bear-market lows. RevMed prior price: About $30 two years ago - Used to show how much the stock has rerated before reaching nearly $200. Vera takeout window: 3 to 12 months after FT approval - He cites a study suggesting clean post-approval assets often get acquired within months. Premium valuation bands: 2.2x to 3x sales - He says takeouts often happen around these multiples depending on disease and asset quality.

Pivotal Quotes: "Biotech's probably one of the only industries where you could make enormous returns very, very quickly. Lose everything too." — CD: He summarizes why biotech attracts him despite the risk. "I think momentum is this decade or this era of investing is all about momentum, and you want to be on the right side of it." — CD: He explains how he sources ideas and interprets market behavior. "The only variable is whether it goes up 100% or 1,000%." — CD: He describes his view on Abivax after strong evidence but before the market fully priced it in.

Implications: Biotech remains a fertile but unforgiving arena for generalists who can learn fast, follow catalysts, and manage downside. AI lowers the learning barrier, but durable returns still depend on reading trial data, judging de-risking, and respecting binary risk.