Last week we published the first in our Biotech 101 series. In the piece, we covered the FDA approval process – the steps a developing stage treatment must go through in order to achieve FDA approval and reach consumer markets. This time around, we will be looking at a key component of the FDA approval process in a little more detail – clinical trials. Specifically, how to read and interpret clinical trial results. In the development stage biotech space, clinical trial results are the primary driver behind any volatility, and can make or break entire companies. Many biotech traders wait for trial results to hit press, and take a position based on the inference of the results. The quicker they enter the more of an advantage they have over other traders looking to play the data. With this in mind, knowing how to interpret data quickly and accurately is an important quality in biotech investing. So, without further ado, here are the most widely used terms in trial data reporting, and how you should be interpreting them.
Efficacy
First up efficacy. Efficacy is probably the most important element of any trial, once safety and tolerability has been confirmed (both of these we will cover a little later). If efficacy is confirmed in the trial, it essentially means the treatment in question works. When a company reports on efficacy, it will do so by addressing what are called endpoints – generally broken down into primary and secondary types. The primary endpoint is the more important of the two, and secondary endpoints are generally used to reinforce primary endpoint data when submitting a new drug application (NDA). So, for example, imagine Roche Holding AG (OTC:RHHBY) is testing out a new eczema treatment. Two symptoms of eczema are itching and dry skin. Roche might target a reduction in itching as its primary endpoint, and a reduction in the amount of dry skin as its secondary endpoint. Before the trial commences, the company will set benchmarks against which it can measure both of these symptoms before and after treatment. The data released from the trial might say something like this:
Example Eczema Drug met both its primary and secondary endpoints, with the data revealing a statistically significant reduction in itching and dry skin across the patient population.
If a sentence such as this makes an appearance in data release, it means the company has demonstrated efficacy for its candidate, and markets will generally perceive this announcement as positive. If a treatment does not meet its endpoints (particularly its primary endpoint) this is essentially saying it does not work and markets will perceive this as negative.
Safety and Tolerability
Safety and tolerability are two major components of any trial data, and – alongside efficacy – should be the go-to reference points on any data release. The difference between these two elements are widely misunderstood, but the best way to think about is this: safety refers to negative symptoms associated with taking a treatment (referred to as adverse events in clinical trial data), while tolerability refers to the level to which a patient can suffer these adverse events. Essentially, it’s a risk-benefit analysis. When the FDA looks at safety and tolerability data, it considers whether the adverse events are worth tolerating in order to derive benefit from the treatment of the underlying condition. What we would ideally look for in clinical trial data is the reporting of no adverse events, however, more often than not, there will be adverse events – the trick is to consider these through the eyes of the FDA. Is it worth going through some minor headaches in order to fend off liver disease? Yes. Is it worth losing your sight? Probably not.
Affirmation
Finally, we look for some affirmation that the company is anticipating moving forward to the next stage of the clinical development phase. If Gilead Sciences Inc. (NASDAQ:GILD) has a development stage candidate in a phase 2 trial, for example, we would look for a statement at the end of the results release that indicates the company plans to move forward with a phase 3 trial. If the data relates to a phase 3 trial, we would look for a timeframe within which, by which, the company question expects to file an NDA with the FDA. An example might read a little bit like this:
Based on these results, we anticipate the initiation of registration for a phase 3 pivotal trial during the second quarter of 2016.
So there we go. When trial data hits, look for these three elements first. Using efficacy, safety and tolerability, and affirmation statements, you can quickly gain insight into the success or otherwise of a development stage candidate, and in turn, react accordingly.