Biomarker-Driven Oncology Trial Design and Subgroup Characterization: Challenges and Potential Solutions.

In oncology drug development, using biomarkers to select a study population more likely to benefit from a therapeutic effect is critical to increase the efficiency of a clinical trial in demonstrating effectiveness. This perspective delves into therapeutic product approvals that were tested in pivotal trials with all-comers populations, but ultimately received US Food and Drug Administration approval for use within specific patient subgroups identified by biomarkers. Despite initial designs for efficacy and safety assessments in overall populations, a favorable benefit-risk assessment was primarily established in biomarker-positive subgroups. Analyzing these cases, we summarize key considerations pivotal to totality of evidence for regulatory benefit-risk assessments for biomarker-defined subgroup versus all-comers approvals, including biological and clinical rationales, biomarker prevalence, safety data, overall trial design, and subgroup efficacy characterization. Furthermore, a decision tree is proposed to guide optimal clinical trial design, delineating between patient enrichment and stratification, accounting for key factors including biological and clinical rationale, marker type (discreate or continuous), prevalence, assay readiness, and turnaround times for marker assessment. Finally, a recommended approach for subgroup characterization involves prespecifying magnitude of improvement that would be considered clinically meaningful in the biomarker-negative subgroup, which can be supplemented with methodologies such as Bayesian to incorporate evidence from similar studies when available. In summary, this perspective underscores the importance of clinical trial innovations, statistical methodologies and regulatory considerations, to optimize biomarker-driven drug development for patients with cancer.

Biomarkers for Precision Patient Selection in Cancer Therapy Approvals in the US, from 2011 to 2023.

During the period of 2011-2023, the US Food and Drug Administration (US FDA) granted 139 accelerated and 329 regular approvals for 86 and 152 cancer therapeutic products, respectively. The percentage of approvals for a biomarker-defined population was numerically higher in accelerated approvals in comparison to regular approvals, that is, 48% vs. 40%. From 2011-2016 to 2017-2023, there was an increasing number of approvals with biomarker-defined populations in lung and breast cancers, serving as the primary driver for the overall increase in the percentage of approvals for biomarker-defined populations in solid tumors relative to hematological malignancies. Over the years, approvals were incorporating a more diverse collection of distinct biomarkers, from 3 in 2011 to 16 in 2022. Overall, HER2, hormone receptor (HR), EGFR, ALK, BRAF, and PD-L1-defined populations received the highest numbers of approvals. The FDA decision on approving a biomarker-defined or an all-comers population may depend on a number of factors and may evolve over time based on emerging evidence. The review discusses selected FDA approvals where a pivotal trial enrolled an all-comers population but the approved indication was restricted to a biomarker-defined population, as well as challenges in clinical trial design in the context of precision medicine. The prominent role of biomarkers in optimizing trial design and identifying a population most likely to benefit from treatment underlines the significance of a comprehensive understanding of disease biology and drug mechanisms. Our review illustrates that biomarker-driven approaches enhance the likelihood of identifying optimal patient populations, potentially streamlining trials through accelerated approval pathways for cancer drug development.