Author: Jeremy Zhou
Covestor model: Biotech and Medtech
When it comes to investing in biotech, it is useful to be clear about definitions. Biotech firms are not Big Pharma companies such as Pfizer (PFE) or Eli Lilly (LLY). Biotech firms are not generic drug makers such as Teva Pharmaceuticals (TEVA) or Watson (WPI). Biotech is not the same as the specialty pharma sector that includes Forest Lab (FRX) or Medicis Pharma (MRX).
The one salient feature that defines most of the biotech sector is the absence of approved drugs. There are definitely some biotech companies that have a robust pipeline of approved drugs, such as Amgen (AMGN) and Celgene (CELG), but they are the minority.
Essentially biotech investors assume the role of venture capitalist by funding drug companies with high failure risk in the public equity market.
Typical financial valuation models that required a history of revenues and incomes do not work well with biotech companies because they usually have neither. Balance sheets analysis is also not much help because it is consisted of mostly cash to be spent on R&D.
The most sensible approach is to look at a company’s drug pipeline, the stage of its various drug candidates, the indications being targeted, and the novelty and feasibility of the candidates’ mechanism of actions. Mechanism of action (MOA) simply means how the drug works.
For example, the MOA of Lipitor is HMG-CoA Reductase or commonly known as statins. MOA matters a lot because it tells investors whether the drug candidate is a me-too drug or a breakthrough drug. If it’s a me-too drug, then its chance of approval is higher, but its market size will be lower. If it’s a breakthrough drug, then the scenario reverses.
The process of evaluating biotech could be complex, but it could also be distilled down to one simple principle: play only if the odds are favorable. To qualify as favorable, the expected return of the investment must be positive. In addition, to estimate the expected return, you should know the probabilities of positive and negative outcomes, and the associated upside and downside.
For many biotech firms, the range of probabilities is often binary: approved or not approved, or positive or negative trial outcome. Hence, if the potential gain times the probability of winning exceeds the potential loss times the probability of losing, you have positive expected return.
It’s important to fully appreciate – not just understand – this concept of expected return because it naturally leads to prudent risk management and diversification. Expected return is not guaranteed return no matter how good the odds. Rather, it means over time if you invest in a good number of biotech companies, you should achieve an actual return that is very close to the expected return.
Biotech investing is very much like flipping a coin, and assigning a 50/50 chance of approval or non-approval provides a solid margin of safety. Just make sure your upside more than enough cover your downside.
