Journal of biopharmaceutical statistics
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In this article, we propose and evaluate three alternative randomization strategies to the adaptive randomization (AR) stage used in a seamless Phase I/II dose-finding design. The original design was proposed by Wages and Tait in 2015 for trials of molecularly targeted agents in cancer treatments, where dose-efficacy assumptions are not always monotonically increasing. Our goal is to improve the design's overall performance regarding the estimation of optimal dose as well as patient allocation to effective treatments. ⋯ Unlike the original method, our proposed adaption does not require an arbitrarily specified sample size for the adaptive randomization stage. Simulations are used to compare the proposed strategies and a final strategy is recommended. Under most scenarios, our recommended method allocates more patients to the optimal dose while improving accuracy in selecting the final optimal dose without increasing the overall risk of toxicity.
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The Biological Price Competition and Innovation Act (BPCI Act) of 2009 established a pathway for the approval of biosimilars and interchangeable biosimilars in the United States. The Food Drug Administration (FDA) has issued several guidances on the development and assessment of biosimilars which implement the BPCI Act. In particular, a recent draft guidance on the interchangeability of biological products presents an overview of scientific considerations on the demonstration of interchangeability with a reference product. The present communication provides a general summary of the draft guidance and briefly observes a few current issues on interchangeability.
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Five algorithms are described for imputing partially observed recurrent events modeled by a negative binomial process, or more generally by a mixed Poisson process when the mean function for the recurrent events is continuous over time. We also discuss how to perform the imputation when the mean function of the event process has jump discontinuities. ⋯ These imputation algorithms are potentially very useful in the implementation of pattern mixture models, which have been popularly used as sensitivity analysis under the non-ignorability assumption in clinical trials. A chronic granulomatous disease trial is analyzed for illustrative purposes.
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Precision medicine has been a hot topic in drug development over the last decade. Biomarkers have been proven useful for understanding the disease progression and treatment response in precision medicine development. ⋯ In this article, we discuss the technologies and statistical issues that are related to omics biomarker discovery. We also provide an overview of the current development of biomarker-enabled cancer clinical trial designs.
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In Phase I/II trials for a combination therapy of two agents, we ideally want to explore as many dose combinations as possible with limited sample size in Phase I and to reduce the number of untried dose combinations before moving to Phase II. Efficient collection of toxicity data in Phase I would eventually improve the accuracy of optimal dose combination identification in Phase II. In this paper, we develop a novel dose-finding method based on efficacy and toxicity outcomes for two-agent combination Phase I/II trials. ⋯ Upon completion of this zone-finding stage, we allocate the next patient to the dose combination determined by adaptive randomization of the admissible toxicity and efficacy dose combinations in Phase II. Simulation studies demonstrated the utility of the proposed zone-finding stage and proved that the operating characteristic of the proposed method was no worse than the existing method. The sensitivity of the proposed method, as well as the operating characteristic of this method when the efficacy outcome is delayed, was also examined.