Adaptive, Precision Trials Change The Clinical Paradigm
By Matthew Pillar, Editor, Bioprocess Online
“The greatest factor impeding the creation of innovative drugs for common diseases is the enormous cost and risk of clinical trials that constitute the largest single component of the R&D budget. In fact, phase three trials are by far the biggest expense and the biggest risk of new drug development, typically incurring 90% or more of that drug’s development costs.”
With those lines, Allan Shaw puts a fine point on the crippling effect of clinical trial design on biopharma innovators’ budgets. Our recent conversation about clinical trials on episode 67 of the Business of Biotech podcast opened a floodgate of Shaw-isms on the topic. Here are a few of favorite exchanges from the discussion:
On what’s wrong with the current approach to clinical trials:
Particularly in the big diseases, the traditional model is akin to trying to buy a suit off the rack. One size does not fit all. We used to think breast cancer was breast cancer until we got smart about it and realized there are infinite types of breast cancer. It’s not limited to a particular pathology. The science has moved well ahead of the traditional processes. It's time to rethink how we do this and stop crossing the road because we always have. The predominant highly empirical statistical methods are generally inflexible and restrict innovation for overly large trials.
On how precision medicine and adaptive trials are changing the clinical trials paradigm:
Shaw: Why are we trying to come up with general trial designs, when patients can’t be generalized? Everyone’s different. It's not homogeneous. Doctors don't treat populations, they treat individuals.
It’s incredibly expensive to undertake these studies. Everything's about following the money. You can really learn a lot by where the money goes. When you look at these big studies, the risk benefit doesn't work. When you look at more precision approaches focused on subtype and patients, those studies have a much higher probability of success. Those characteristics are why orphan drug trials have been very successful. They focus on a subset of patients suffering from a distinctive mutation, or absence of a specific protein, or something else you can selectively screen for to enrich your studies. And because of that, rather than running 20,000-person studies on cardiovascular disease, you can, in certain cases, get a drug approved with 50 patients. You can often bypass that very costly phase three. Once you develop and demonstrate safety and proof of concept, you’re off to the races. The FDA has made a lot of concessions in that respect.
You see where the money's going right now, it's going into oncology and it's going into orphan disease. Just look at the sheer number of drugs that are being developed and approved. Adaptive clinical trial designs allow you to make changes on the fly. You can actually learn from what you've been doing, and if something's clearly not working, you can modify it. It's all part of the recipe that you prepare up front.
On the biopharma’s challenge to changing the paradigm to biomarker screening and highly specific patient populations:
Shaw: It really requires you to have your house in order and your ducks in a row. You really must understand your compound, its properties, and mechanisms of action. It puts more emphasis on having robust preclinical data to understand the pharmacokinetics and pharmacodynamics so important to determining the right dose. If you know the mechanism, then you know what you're looking for in terms of biomarkers,
On embracing the pivotability required of adaptive trial design, or “zigging” when you’re expected to “zag:”
Shaw: When you think about the industrial jeopardy that about 90% of what we work on isn't going to work, zigging is part of the business. When you were talking with Ian Walters [CEO at Portage Bio] recently, he made the point that biopharma leaders must know what to do the 80% of the time it doesn't work. He said 20% of drug development is picking the right assets, and 80% is figuring out what to do when it doesn't work. So, you need to know how to build adaptability into it. It seems too obvious and too logical that we should build flexibility into our studies. That embraces a couple of different concepts that are generally drawing a lot of steam right now, including adaptive and real-world studies, patient subtypes, precision medicine, and the wearable and monitoring technologies driving compliance in decentralized trials, to improve probabilities of success.
On The FDA’s role in enabling change to clinical trials:
Shaw: The FDA has really been embracing adaptive studies. But it's going to require collaboration among regulators, payers, and industry actors to keep moving the needle. It’s happening slowly, but, uh, you know, from my perspective, the easiest way to make things work. You can learn from past examples, such as the Orphan Drug Act. It’s illustrative of how you can make something out of nothing. Before the Orphan Drug Act, the number of orphan drugs that were under development was spotty. Our hearts went out to patients, but not a lot was being done to help them. I’d argue that the Act did more to stimulate that than it intended to. Multiple drugs are now being approved for orphan indications.
Obviously, there’s more that can be done on that front. They can provide better, faster priority reviews, maybe even provide vouchers that create an incentive for people. The FDA has demonstrated administrative flexibility with orphan drugs in terms of adjusting end points and considering post-market approvals. They can offer additional market exclusivity. All these things translate into higher probabilities for approval.
Tune in to episode 67 of the Business of Biotech podcast for a whole lot more of Allan Shaw’s advice on the business of clinical trials.