By Shreya Badhrinarayanan, MD, global development lead, clinical development oncology & hematology, Pfizer
Oncology and hematology clinical trials are shifting away from rigid, one-size-fits-all randomized controlled trials toward adaptive designs that evolve as new data emerge. The rise of targeted therapies, immunotherapies and complex combination regimens, together with rapid advances in tumor biology and resistance mechanisms, has exposed the limitations of static protocols and increased pressure to shorten timelines and reduce costs.
Traditional fixed trials lock in sample size, treatment arms and endpoints at the outset and often require waiting until completion to act on results. Adaptive trials build preplanned, prospectively defined opportunities to modify a study based on interim analyses. Adjustments can include stopping early for futility or efficacy, dropping or adding arms, changing sample size or expanding enrollment for responding subgroups under a single master protocol guided by statistical safeguards.
This flexibility is particularly valuable in oncology and hematology, where patient populations are heterogeneous and therapies are increasingly biomarker-driven. Adaptive designs allow investigators to identify efficacy signals sooner, allocate more patients to promising treatments, and concentrate resources on groups most likely to benefit, improving the efficiency and relevance of each trial.
Advances in analytics and artificial intelligence are accelerating the adoption of adaptive trials. Modern studies generate large, diverse datasets—from genomics to imaging and real-world outcomes—and machine learning tools can analyze incoming data in near real time to inform mid-trial decisions. AI can flag early efficacy or safety signals, support dose optimization, enhance patient selection through radiomics and computational pathology, and simulate outcomes to improve stratification and statistical power.
The practical benefits include faster development timelines and potential reductions in R&D costs by concentrating efforts on successful candidates and transitioning seamlessly between trial phases. Platform and master-protocol approaches have demonstrated the ability to evaluate multiple therapies efficiently and have contributed to accelerated approvals in recent years.
Adaptive trials also offer ethical and safety advantages. Continuous interim monitoring reduces patient exposure to ineffective or harmful treatments, enables earlier termination or modification for safety concerns, and can expand access to effective therapies within a trial. Biomarker-driven adaptations increase the likelihood that participants receive treatments aligned with their disease biology, enhancing the prospect of benefit.
Widespread adoption of adaptive designs requires ongoing attention to methodological rigor, transparent statistical planning, robust AI validation, and close collaboration with regulators and clinical teams. Clear protocols, pre-specified adaptation rules and simulations remain essential to preserve scientific validity while enabling flexibility.
As adaptive designs have entered the mainstream, the expectation is that they will play an increasing role in future oncology and hematology research. When implemented with appropriate safeguards, adaptive trials can speed the delivery of effective treatments, improve patient safety, and make clinical development more responsive to new scientific insights.
About the author: Shreya Badhrinarayanan, MD, leads global clinical development for oncology and hematology at Pfizer. She has held roles in medical monitoring and external asset evaluation at Genentech, served as a physician-scientist in the UK’s National Health Service, and was an honorary lecturer at the University of Adelaide.
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