About this Research Topic
The ISPY2 clinical trial is designed to maximize the efficiency of the trial by minimizing the number of participants and time required to evaluate an experimental drug.
The trial uses a master protocol that ensures that regulatory policies allow the investigation of multiple treatment regimens in the same study, as well as new drugs to enter or exit it without stopping the investigation.
Collaboration between scientists and statisticians provided improved biomarker classifications based on the responsiveness to drug treatment. Using the predictive biomarkers (associated with breast cancer subtypes) allows for more precise target therapy, with the ultimate goal of improving patient outcome.
Standard biomarkers used in tha past decade did not prove useful in treatment optimization. The results obtained in this study so far demostrate that this model can accelerate the development of new treatments, as well as assign patients the treatment that will provide the best response, less toxic.
The scope of this topic is to present a novel approach in clinical trials and a need of constant collaborations between academics and industry. The ultimate goal is to achieve a complete response to treatment with targeted, less toxic agents. The study demonstrates that the use of the response predictive subtypes can be used to dictate the treatment pathway, an improvement over current standard methods. This new dynamic approach will accelerate the development of new cancer treatments, while reducing the therapies that would not be useful and add toxicity.
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
The trial uses a master protocol that ensures that regulatory policies allow the investigation of multiple treatment regimens in the same study, as well as new drugs to enter or exit it without stopping the investigation.
Collaboration between scientists and statisticians provided improved biomarker classifications based on the responsiveness to drug treatment. Using the predictive biomarkers (associated with breast cancer subtypes) allows for more precise target therapy, with the ultimate goal of improving patient outcome.
Standard biomarkers used in tha past decade did not prove useful in treatment optimization. The results obtained in this study so far demostrate that this model can accelerate the development of new treatments, as well as assign patients the treatment that will provide the best response, less toxic.
The scope of this topic is to present a novel approach in clinical trials and a need of constant collaborations between academics and industry. The ultimate goal is to achieve a complete response to treatment with targeted, less toxic agents. The study demonstrates that the use of the response predictive subtypes can be used to dictate the treatment pathway, an improvement over current standard methods. This new dynamic approach will accelerate the development of new cancer treatments, while reducing the therapies that would not be useful and add toxicity.
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
Keywords: Clinical trial, breast cancer, ISPY 2, toxicity, adaptive clinical trial
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