How Biomarkers Are Transforming Neurology and Oncology Trials

In a recent video interview with Applied Clinical Trials, Michael Miller, chief operating officer, Quanterix, discussed how the clinical research industry is increasingly integrating biomarkers. Biomarkers are particularly beneficial in neurology, where advancements in imaging and blood tests have improved trial outcomes, and in oncology, where multiomic approaches and protein tissue imaging aid in matching therapies to mutations. Synopsis professionals should focus on the biomarker's purpose, technical requirements, and regulatory compliance. Platform trials and biomarkers are also driving accelerated drug approvals. These advancements are crucial for biopharma companies navigating the shift between private and government-funded research.

Miller: I think there's two disease areas that I think are good examples of where biomarkers can have a significant effect. One area where Quanterix has spent a lot of its efforts and had had an impact is on neurology. As an example there, for decades, progress was difficult because there weren't good biomarkers for understanding changes in the brain and then a number of groups developed imaging methods to be able to image amyloid plaques in the brain for Alzheimer's, and then eventually in CSF as well, in terms of cerebral spinal fluid, and then that allowed researchers and in clinical trials to see what is really happening when drugs are given to individuals with those plaques. Now, even more exciting is that in recent years, now there's blood biomarkers, and that's where some of our ultra-sensitive technology has played a role, had been able to further enhance the accessibility of enrolling people in clinical trials that might not have had the opportunity, or reducing the cost of clinical trials, because you can use a blood test to identify somebody who might be appropriate for a trial, as opposed to having to wait for a PET scan or a spinal tap to do these other methods. That's one really good example where biomarkers have undergone an evolution from complex but very good gold standards to something simpler that can then speed the efficiency of a trial.

I think another example is in oncology. We know cancer is a genetic disease, where mutations dominate the behavior of the cancer and the therapies are matched to the mutations, and that's been a mainstay or work where a lot of progress has been made in terms of identifying who's appropriate for a particular therapy, but there's more progress that needs to be made there. I think that's where you're seeing now, going to multiomic approaches, and then using protein tissue imaging, which is what Akoya does, who we recently acquired, can then help with the phenotype, to then further go from the genotype, and then look at the phenotype below that, that further segment populations and really find individuals who will respond to the drugs with a better response rate.