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Trial design


Adaptive trial designs streamline oncology research, making cancer trials faster, cheaper, and more patient-friendly.


take steps to either cut your losses or move forward with an asset more likely to succeed.


Finding the best treatment Usually, when people talk about adaptive trials they’re referring to studies with one shared control arm for many different experimental arms, explains Lillian Siu, senior medical oncologist at the Princess Margaret Cancer Centre. This allows you to investigate multiple therapies at the same time to find out which is best.


“The algorithms learn, so that the arm that is more efficacious has a higher probability that a patient will be randomised into that arm.”


Dr Patrick Wen


As experimental arms show promise, you can decide to enrol more patients into them while less effective arms are dropped off. You’d then collect more data for the treatments with better odds of succeeding. The winning arm could then be graduated into further phases of research. “Or maybe that’s even sufficient evidence for you to get registration,” says Siu.


The percentage of new cancer drug candidates that have a chance of making it through clinical trials.


3.5% MIT 26


Here, you’re getting answers faster – and it might take fewer patients overall to generate the data needed to reach those conclusions. “It’s much quicker, and all your sites are already up and running,” says Wen. “So you don’t have to start from scratch [with each new treatment arm].” While adaptive studies may take more resources to set up, they can drive savings in the long term. For instance, having a shared control arm means you can avoid running separate trials to test each treatment. The Phase II INSIGhT trial, the first multi-arm adaptive trial for the brain tumour glioblastoma, is one example. Initially, there were three experimental arms


yet none of them showed an effect. But thanks to the trial’s adaptive design, this was discovered through one rather than three separate investigations. And despite none of the drugs working, INSIGhT wasn’t a failure. Its design allowed for more treatment arms to be added – so the research is ongoing. “Here, a new arm is just an amendment to the protocol,” says Wen, who is the principal investigator on INSIGhT. “If you had unlimited capacity, you could add as many arms as you want.” “You can also use this kind of adaptation to look at different doses and schedules,” adds Siu. Each study arm could be a different dose or schedule and you could find out which to move forward with sooner. “The FDA is really advocating [for] this kind of dose-range finding before we go into deeper phases of clinical trials,” she says.


Investigating biomarkers If a cancer trial is looking at targeted or immunotherapies, patients need certain biological markers (biomarkers) for treatments to be effective. These could be specific proteins the drug interacts with, for instance. Adaptive trials can help us to understand and validate those biomarkers more efficiently. This was one aim of the INSIGhT trial. Each of the three initial experimental arms had a biomarker hypothesis: one was the protein epidermal growth factor receptor (EGFR) should have an altered structure, be mutated, or present in high levels for the drug neratinib to be effective (EGFR- positive). Before starting, each participant underwent tumour genomic sequencing – looking at the sequence of DNA within the cancer – to identify the relevant biomarkers. INSIGhT is one of the first neuro-oncology trials to have this requirement. If the hypothesis was correct, the algorithm would allocate more EGFR-positive people into the neratinib arm. “Theoretically, that was the goal,” says Wen.


Clinical Trials Insight / www.worldpharmaceuticals.net


bearsky23/Shutterstock.com


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