
Leading academic says high profile trial failures should drive changes in how we approach trials for drugs that target aging.
Following the recent clinical trial failures by Unity Biotechnology and resTORbio, Buck professor Brian Kennedy feels that a change in approach is potentially needed.
Longevity.Technology: When we interviewed Kennedy about his new AKG study last week, the conversation occasionally strayed beyond dietary supplements into other areas he’s involved in. Today, we thought we’d share some of those perspectives, including views on aging-related drug development and, more specifically, clinical trials.
βI get the idea that you target aging pathways, but then you try to treat disease because you need to get FDA approval and reimbursement from insurance companies β but if that strategy doesn’t work, weβve got to stop doing it,β he says. βI think we should actually try to treat aging for a change.β
βWe need to nail down the foundation here and stop giving people excuses why this won’t work … I think we should actually try to treat aging for a change.β
While Kennedy agrees that effort needs to continue to convince the FDA to recognise aging as a treatable disease, Kennedy also believes that there are alternative approaches that can be employed.
βYou donβt need the FDA to approve your trial, you need an IRB to approve your trial,β he says. βFrom an academic standpoint, as long as you can convince people that the trial is safe, you can use biomarkers and study the effects of these drugs. So I think if we start generating that kind of data, then it’ll be a lot easier to get the FDA on board, and hopefully the rest of the world on board.β
βWe need to nail down the foundation here and stop giving people excuses why this won’t work. I’m still optimistic about drugs, but if you develop a drug for A and try to treat B, and then you wonder why it doesn’t work β I’m starting to feel like the strategy may not work that well.β

Kennedy points out there’s a big difference between preventing something and treating something, and a lot of the mouse studies pursue a prevention model.
βWe need to use age-appropriate mice for disease studies as well,” he says. “You prevent some disease in young mice and then do a clinical trial to treat the disease in aging humans. Why are we surprised when this does not work very often?”
βIt’s a huge change to two big variables there. One, the disease is already happening and two, old people don’t respond the same way young mice do.β
βThere are a lot of questions to answer, but I think that the most advanced clocks are starting to look like good biomarkers.β
βIt would probably reduce the number of positive results you got, which the mouse people don’t necessarily want to do because you can’t publish the papers,β he adds. βBut even an expensive mouse study costs $500,000 and a cheap phase three trial in humans is $100 million, so I think we’re being penny wise and pound foolish right now.β
Of course, if companies are going to run trials on aging, then a clearer consensus is needed on the definition of aging, and Kennedy is encouraged by developments in the various clocks that measure biological age.
βThere’s a bunch of clocks and we don’t really know how they relate to each other yet, and how specific clocks relate to specific kinds of age-related disease,β he says. βThere are a lot of questions to answer, but I think that the most advanced clocks are starting to look like good biomarkers. Some may be better than others but I’m very optimistic about these biomarkers.β
Kennedy believes there are two key factors that should govern what biomarkers are used in trials focused on aging.
βOne is cost efficiency β if we’re going to scale something, we need a cheap way to measure aging, we can’t spend $5,000 for everybody,β he says. βAnd the other is ease of collection. I don’t want to go beyond a blood draw β and I’d rather do it from saliva. Non-invasive stuff is okay, but I’m not doing muscle biopsies and complicated things, because that doesn’t help me develop something that’s scalable to the whole population.β