Accelerated Approval or Risk Reduction? How Response Biomarkers Advance Therapeutics through Clinical Trials in Cystic Fibrosis

• Published in: Trends in molecular medicine 2020-12, Vol.26 (12), p.1068-1077
• Main Authors: Mayer-Hamblett, N., VanDevanter, D.R.
• Format: Article
• Language: English
• Subjects: clinical correlation; clinical trials; drug development; response biomarkers
• ISSN: 1471-4914; 1471-499X
• DOI: 10.1016/j.molmed.2020.08.002

Progress in the development of new therapies for cystic fibrosis (CF) has benefited from therapeutically responsive biomarkers to streamline drug development. Paradoxically, these response biomarkers have been proven to be essential even in the presence of data demonstrating a lack of correlation with clinical outcomes across individuals with CF. This finding is unsurprising, particularly in the setting of a rare disease given complex disease processes and an often-limited pool of clinically effective therapies by which to link biomarkers and clinical responsiveness. While many response biomarkers will be unable to progress from their status as markers of biological efficacy to either established correlates of clinical efficacy or surrogate endpoints, they remain critical to the overall success of therapeutic development. Therapeutic drug development in cystic fibrosis (CF) benefits from streamlined drug development programs relying on reliable early-phase response biomarkers.While the rare disease setting remains a compelling setting for the use of surrogate endpoints to reduce the burden and/or time of late-phase development efforts, the CF experience demonstrates that proven response biomarkers exhibit a complicated association with clinical response, prohibiting further progression towards their evaluation as surrogates.Quantifying the levels of uncertainty associated with the use of less established response biomarkers and understanding where they reside on the continuum of qualification with respect to their association with clinical outcomes provides an optimal framework for their application throughout therapeutic drug development.