The success of biotech companies and their stocks is often affected by what happens in clinical trials. But how companies design these trials has a big impact on what data they can get out of them.
In this video clip from "The Pharma & Biotech Show," recorded on Feb. 9, Motley Fool contributor Brian Orelli asks Dr. Frank David, author of The Pharmagellan Guide to Analyzing Biotech Clinical Trials, what investors should look for in biotech studies as it relates to patient population.
Brian Orelli: I think investing in biotechs is as much about avoiding bad companies as it is about finding exemplary companies, so maybe we could talk a little, walk through some of the chapters in your book and talk about how to set up and run clinical trials and what red flags investors should be looking at for each of them. Let's start with patient populations is the breakdown of the patients that are enrolled in the study.
Frank David: Yeah, I mean, when I look at the patient population of a study that's planned or in progress, first of all, let's take a step back, which is anytime you're looking at one of these and anytime I look at them first I'm trying to figure out what the goals of the study actually are. Because if you're running a first-in-human safety study that has very different goals in terms of what you're going to get out of it, then if you're running a phase 2b study or a phase 3 study where you're really trying to nail down efficacy.
That being said, for an efficacy type of study, if I'm looking at the patient population, some of the things I'm looking at are how relevant it is to clinicians, is it defined in such a way that it actually is going to matter clinically? How does it fit into what else is known about the drug and the mechanism of action and the disease? Whether it seems fit for purpose from a regulatory point of view, is certainly important in terms of later-stage studies and I think also the amount of heterogeneity or homogeneity within that population is also pretty critical. You do see a lot of examples and there's a common tension for drug developers. Do I try to make a land grab and have a pretty broad inclusion criteria or do I focus in more narrowly? That's a risk reward calculation that every company engages in when they set up a trial, often you can be a little bit more certain of success if you define the population a little bit more narrowly, but that might affect how much you can get out of it at the end if you're successful.
