Public articles linked to the same research event.
Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics This review proposes and organizes a framework of emerging clinical trial models for central nervous system tumors, including master protocol designs, Bayesian adaptive frameworks, trials as active discovery platforms embedding longitudinal tissue sampling, window-of-opportunity designs and multi-omic profiling, and decentralized models with artificial intelligence tools, arguing that trials should be reimagined as dynamic, biologically integrated, learning-based systems rather than static tests of individual agents in order to accelerate therapeutic progress in neuro-oncology.
This review proposes and organizes a framework of emerging clinical trial models for central nervous system tumors, including master protocol designs, Bayesian adaptive frameworks, trials as active discovery platforms embedding longitudinal tissue sampling, window-of-opportunity designs and multi-omic profiling, and decentralized models with artificial intelligence tools, arguing that trials should be reimagined as dynamic, biologically integrated, learning-based systems rather than static tests of individual agents in order to accelerate therapeutic progress in neuro-oncology.
This review proposes and organizes a framework of emerging clinical trial models for central nervous system tumors, including master protocol designs, Bayesian adaptive frameworks, trials as active discovery platforms embedding longitudinal tissue sampling, window-of-opportunity designs and multi-omic profiling, and decentralized models with artificial intelligence tools, arguing that trials should be reimagined as dynamic, biologically integrated, learning-based systems rather than static tests of individual agents in order to accelerate therapeutic progress in neuro-oncology.
This review proposes and organizes a framework of emerging clinical trial models for central nervous system tumors, including master protocol designs, Bayesian adaptive frameworks, trials as active discovery platforms embedding longitudinal tissue sampling, window-of-opportunity designs and multi-omic profiling, and decentralized models with artificial intelligence tools, arguing that trials should be reimagined as dynamic, biologically integrated, learning-based systems rather than static tests of individual agents in order to accelerate therapeutic progress in neuro-oncology.