Biotech companies can use several different options when designing a clinical trial. But not all study designs are created equal. In this video clip from "The Pharma & Biotech Show," recorded on Feb. 9, Dr. Frank David, author of The Pharmagellan Guide to Analyzing Biotech Clinical Trials, describes one of the best study designs out there and some challenges biotechs face when creating clinical trials.
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Frank David: I mean, I think that for me, some of the design issues that I'm always sensitive to, especially with biotechs is, first of all, you are doing a single arm or a two arm study. I think we've seen a lot of rare diseases, there's a desire to-
Brian Orelli: Do you want to just define single-arm versus two-arm?
David: A single-arm study would be basically, I just have a group of patients and I'm giving them my experimental drug and then I'm going to see what happens. A two-arm study is where half the patients or some fraction of patients are getting the experimental drug and the other are getting something else. Whether it's a placebo, whether it's some other active comparator, etc. Again, we can talk about, then separate from that once you are in the two armed, the non-single arm part of that, then there's a question of whether it's blinded or not, which is a different issue.
Really, the gold standard in biopharma would be to do a blinded randomized controlled study, which means you have at least two arms in the study and at least one of those arms is not the experimental drug and nobody neither the patients nor the people executing the study knows who's in which arm until all the data get collected and then the study gets what's called unblinded. That's the gold standard against which one has to measure everything else, basically.
If you see a study in rare disease, sometimes what happens is, it's hard to recruit patients for a placebo-controlled study because everyone wants a chance at getting the what they believe could be an active treatment. Because often these are very severe diseases, patients have very little other hope. That's fine, except at the end of the day, you're going to get some data and what are you going to compare those to? Really, it's disease by disease, but what ends up being important as an external person has to figure out, are there good data in the literature to allow you to put that number in context? For a rare diseases often there are natural history studies that have been published, for example, where you can say, if I just follow a bunch of patients with this disease, this is how much they decline in terms of their performance on whatever metric you're using. Now, if I show in my one-arm study where everybody got my experimental drug, I might be able to show that the rate of decline is much less than has been previously shown in the literature.