01In short
Biotech companies are hard to value: much of their worth depends on drugs that haven't been approved yet. Working for a private investor, I researched U.S. biotech stocks and built models to estimate what they were worth — and what could go wrong.
02What I did
- Researched U.S. biotech equities and developed investment theses that informed a private investor's $10K portfolio, which grew 73.9% during the internship.
- Built valuation and scenario models using discounted cash flow (DCF), comparable-company, and risk-adjusted pipeline analyses.
- Assessed each company's commercial upside and key investment risks.
03How I valued a company
Most of a biotech company's value sits in drugs that are still in clinical trials, and most drugs in trials never reach patients. So I looked at each company in three ways.
A discounted cash flow (DCF) model estimated what the company's future cash would be worth today. A comparable-company analysis checked that against how the market prices similar companies. And a risk-adjusted pipeline analysis weighted each drug's potential sales by its odds of getting through the trial phases it still had ahead of it.
Together these gave a range of values rather than a single number, along with a clear picture of where the upside came from and what could break the thesis.
A typical thesis came down to one question: is the market pricing this drug as if it will fail? Take a company whose value rests on a single drug in a late-stage trial. If the stock implies lower odds of approval than the trial data and the historical success rates for that kind of drug suggest, that gap is the opportunity. If the odds look right, there's no edge, however good the science is.
Every thesis came with an equally clear answer to what would prove it wrong: a failed trial endpoint, a safety signal, or a competitor reaching the market first.
04Science meets finance
A biotech pipeline is a list of scientific bets. Reading one well means understanding the biology: what a drug targets, how strong the early data is, and whether a trial is actually designed to show what the company claims.
My lab background meant I could ask those questions before I opened the financials, and it made the risk side of each thesis much more concrete.