Drugs

Transcript: Director's Corner Podcast - Talking translational science

Introduction: Welcome to the Director's Corner, an audio podcast series featuring the director of FDA's Center for Drug Evaluation and Research. 

 
Anne Rowzee: Hello, I am Anne Rowzee from CDER's Office of Communications. In this session of the Director's Corner, Dr. Woodcock will be giving our listeners an overview of translational science and how the outcomes from this type of research can help speed the development and review of innovative new therapies. Hi, Dr. Woodcock.
 
Dr. Woodcock: Hi.
 
Anne Rowzee: So, let's start off with a definition of sorts. What does translational science mean at CDER?
 
Dr. Woodcock: Well, say to me, translational science means taking those discoveries that are made in the laboratory, maybe in cells or other systems or in mice or other animals and actually turning them into products that will actually help people. And that's the process of translation, and translational science is all the activities surrounding that.  Not the specific moving, a specific product along but all the other scientific support that's needed in order for that movement to happen.
 
Anne Rowzee: Okay, so then how can the results from high quality translational science programs positively affect drug development and review?
 
Dr. Woodcock: Well, drug development is often extremely hampered by not having the appropriate translational science in place, and that means that drug developers have to guess about a lot of things. 
 
So, for example, take some kind of rare disease, all right. Often they don't know how the disease really progresses in people and so they have to get some gray beards together and they say, “In my experience the disease progresses like this in three years.” But they may only have seen three people with that disease and the people who get in the trial may have a totally different progression rate. 
 
So, something called natural history studies it’s really, really important in translational science. So what happens if you follow people with a disease over the years, how do their biomarkers change or if you do imaging on them or whatever you do, how fast do they typically progress? Because people don't progress in lock step; they're all different. And how different is that range? Do some people progress in a month and others take five years? It's really important to know before you set up a clinical trial program, but often they're flying blind. They don't know that much about the disease. So, the biomarkers that are well validated, and then you understand how they change during the disease process; that's very important. 
 
Looking at targets for the drug; so a drug is something that affects a target in the body, in other words, it's supposed to impact upon something. Well, if you're just guessing, you say, I know this target is somehow involved in the disease and I basically hope that impacting it by my drug will affect a positive change; that's a pretty sketchy proposition and we know that vast, a number of candidates that are developed, you know, are going to fail and about half of candidates don't fail until the late stage trials, until Phase III. It's a huge failure rate and it adds tremendously to the cost of drug development and probably to the cost of drugs and because it's such a risky business. And having all that translational science can improve prediction tremendously and help select good candidates very early and then design trials that are efficient in figuring out whether the candidate is real acceptable or not. 
 
And translational science also works on the safety side. We haven't had that many new safety biomarkers in a very long time, so how are we going to tell whether a drug is going to cause harm or not? For example, right now we're looking at harm to the cardiac conduction system. You have to do trial on that, right? And the people; and it's expensive and it's a little risky and so forth, so wouldn't it be good if we had biomarkers that could tell us that we could rely upon to say this drug is going to affect, adversely affect the cardiac conduction system and then you could kind of kick that out of contention very early. 
 
So, translational science is enormously important in improving the efficiency enterprise, and also how much information we get out at the end of the day.
 
Anne Rowzee: Well, our listeners might be surprised to learn that CDER itself has active research programs and even laboratories on its campuses. Can you give us some examples of a translational science programs underway here at CDER?
 
Dr. Woodcock: Well, there, some of them are regulatory in nature and those are very important. For example, we have the biomarker qualification program. And that program assists those who wish to develop sort of public biomarkers, new biomarkers that everybody can use, say safety biomarkers; there are a lot of safety biomarkers in the program. And what we do is we give them advice on how to figure out whether or not that biomarker's information is valid and predictive in a way you'd expect it to be and that you could rely upon it say in clinical trials say to keep people safe, keep their kidneys safe, for example.  And that's a pretty high bar, so we give people advice.
 
And we're also working on developing the evidence standards; what kind of standard should be applied to these biomarkers for various types of decisions.  Because a decision to maybe enrich patients in a trial is one kind of low-risk decision, more or less for the patients, versus the decision that they can keep being exposed to a drug because you don't think the drug is harming their kidneys. That's a more high-risk decision that requires more robust evidence of the biomarker. So, we're doing that program and that's pretty well subscribed. 
 
We also have Critical Path Innovation Meetings and these are non-regulatory meetings with any party who has ideas to talk about novel approaches to all sorts of translational science ideas. And those are very popular. It's a brainstorming session and there's no regulatory consequences to it, and so that's been very well subscribed. There have been eight in 2015 and in the first four months of this year there have been six meetings – with another seven scheduled. So, they are very widely subscribed as I said and I think they'll help. Another thing we're doing is working through consortia. So, we are members of multiple consortia as liaisons and they are working on many of these biomarkers and other projects. 
 
Our research programs, we have many, many programs, that are looking at very targeted regulatory issues. For example, we fund at the National Center for Toxicologic Research, there's a big program looking at the toxicity of anesthetic agents in young children. It's a huge concern and they have tremendous animal model systems where they've been able to show that in primates, exposure to anesthetic agents, fetal exposure early in development for primates does lead to cognitive problems at, you know, high doses of the anesthetics. So, these are incredibly important because we, it's very difficult to do those types of experiments in people, so then these are other safety systems where we're doing research. 
 
We also do research on how would you get a generic drug on the market and show bioequivalency if it isn't a drug that is absorbed into the body systemically but has some other route. Or for example, on complex products that might be generics. And we also have even addressed things like the skepticism of the medical community about generics. We recently had some completed studies on epilepsy drugs and there was a, we got one of the leading, critics of generics and, apparently, as I've been told, that, that the study shows there was no difference there. So, having that solid data is really important.
 
Anne Rowzee: Wow. Fascinating. So, maybe to wrap up, you might give a sort of a homework assignment to the audience. What are some of the knowledge gaps that you see in translational science that you feel you'd like to see addressed?
 
Dr. Woodcock: Well, I think there's a huge, it isn't just a gap, it's like a chasm. There's a huge number of problems. Every disease should have its own translational program. They should have natural history studies. Most of the people with those diseases are not enrolled in any kind of study or they're not, their information and knowledge is not contributing to science. And many of the biomarkers and everything, they're not that difficult to obtain from people and you could correlate that with what happens to them over time we’d learn a tremendous amount of information and it would help translational science. 
 
So, what I think is happening, I see happening, I think which is very helpful is that patient groups are getting engaged in this. And they're seeing that, okay it's not enough to do the basic science, you also have to have these other pieces of the translational process because what they want is interventions that are going to modify the course of their disease or prevent or cure it. And so, to get that, you have to go from soup to nuts; you can't sort of go from soup to the first course. So, it's really important that patient groups now are stepping in and doing natural history studies, pushing researchers to collaborate more, pooling data, having bio banks, doing all the things, focused on each disease, not to focused on just research but focused on we want to improve the outcomes of this disease, and here are the steps that we need to go through. And then the interventions, whether they're devices or psychological interventions or drug interventions, whatever, can be plugged into that structure and you can evaluate what works best in that disease. So, I think that's the greatest need.
 
Now, from FDA's point of view, we need to work on better trial designs and incorporating adaptive designs. We've stepped into that space with some external partners; it's going very well like the I-SPY2 trial is graduating candidates and it really is giving us information on multiple drugs in the same disease. So, it's focused on high risk breast cancer; a really important issue and, it's really screening candidates very efficiently. And so, trials not designed around a single drug candidate; it's designed around improving the disease. 
 
We also need to work on patient focused drug development with the advent of getting the patients involved. It's like, let's find out what matters to the patient and then let's measure those things to see if we're improving the patient's life rather than simply a medical approach where you're proving this lab test or what have you. And that's really important, but it's hard. They have to be valid measures and they have to reflect the range of patients and actually be tested in the disease. You can't just sort of dream them up. 
 
Evidence standards, I talked about. We're trying to get evidentiary standards for biomarkers so that people know what gate they have to get over. And then other standards, data standards, we have a huge effort in that, and then we have a huge effort in manufacturing to modernize manufacturing which I think is going very successfully. That’s a kind of translational science, too, we’ve just approved recently the first 3-D printed drug, and we've approved some continuous manufacturing set-ups, which I think is the future of making, at least a finished dosage forms. 
 
So, across the board in CDER, from everything from surveillance methods and Sentinel all the way back to getting very first steps out of the laboratory. We're working on trying to improve that process and make it more effective.
 
Anne Rowzee: Well, it sounds like there is a lot of work underway and a lot of work still to be done but thanks so much for sitting down and talking translational science with us today.
 
Dr. Woodcock: Most welcome.
 
Exit: Thanks for listening. For more information about what you heard today, please visit our website at www.fda.gov/drugs

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