High-risk myeloma represents a particular challenge. These patients have a very high burden of disease, typically at presentation, rapidly progressing. So many of them historically have not been able to go on clinical trials. And which is why this is also reflected, although we have a lot of new drugs and treatments, there’s only been a handful of clinical trials that have been focused on newly diagnosed myeloma with high-risk features...
High-risk myeloma represents a particular challenge. These patients have a very high burden of disease, typically at presentation, rapidly progressing. So many of them historically have not been able to go on clinical trials. And which is why this is also reflected, although we have a lot of new drugs and treatments, there’s only been a handful of clinical trials that have been focused on newly diagnosed myeloma with high-risk features. These are mostly all phase two single-arm trials, and they do take quite a while to enroll. So in my talk, I highlight some of the studies that have taken three, four years to enroll 70, 90 patients and another four or five years for the results to read out. So all in all, starting with the new treatment regimen to finally getting results can be anywhere from five to seven, eight years, which is too long, we think, to make progress. And that’s particularly true now when we have multiple new treatments that we need to incorporate into newly diagnosed treatment platforms. So I think using innovative adaptive designs, for instance, Bayesian approaches where you can test multiple different regimens in the context of the same clinical trial, prioritize treatment regimens that look promising, deprioritize treatment regimens that are not promising. To be able to move the field faster would be really important for high-risk myeloma. So I would say we’re going to see more use of innovative designs like Bayesian approaches to treat our high-risk myeloma patients in clinical trials. So hopefully, by doing trials with these innovative designs, we can test multiple treatment regimens at the same time. As many are aware, we now have multiple bispecific antibodies, multiple CAR T-cells, multiple other novel agents. So incorporating all of these into different treatment regimens, the permutations and combinations of treatments we have to evaluate increases quite a bit. So I think these innovative designs will allow us to collect data from multiple regimens in parallel rather than sequentially. And two, I think there’s an increased focus as this meeting highlights on incorporating biomarkers and translational studies into these clinical trial designs. So what explains resistance to particular treatments? What explains exceptional responses? Can we use testing like MRD to stop treatments early for some patients or de-escalate treatments even in high-risk? These are all going to be driven by the right kind of correlative analysis that are incorporated into these trials and data collection. So I think hopefully our ability to design these studies and incorporate correlative analysis will allow us to do better data collection and better data interpretation. In terms of how this might influence drug approval or regulatory access to these treatments, again, I think these initial trials will be a signal finding. In other words, we want to know of all the different treatment regimens we can use in high-risk newly diagnosed myeloma. Are there one or two that we want to prioritize for larger, more focused trials? And that in turn will allow us to prioritize our resources better to, let’s say, pick the winner, if you will, of finding the most promising treatments that are likely to have the deepest impact on patients with high-risk myeloma.
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