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Up-and-down designs (UDDs) are a family of statistical experiment designs used in dose-finding experiments in science, engineering, and medical research. Dose-finding experiments have binary responses: each individual outcome can be described as one of two possible values, such as success vs. failure or toxic vs. non-toxic. Mathematically the binary responses are coded as 1 and 0. The goal of dose-finding experiments is to estimate the strength of treatment (i.e., the "dose") that would trigger the "1" response a pre-specified proportion of the time. This dose can be envisioned as a percentile of the distribution of response thresholds. An example where dose-finding is used is in an experiment to estimate the LD50 of some toxic chemical with respect to mice.
In an adaptive design of a clinical trial, the parameters and conduct of the trial for a candidate drug or vaccine may be changed based on an interim analysis. Adaptive design typically involves advanced statistics to interpret a clinical trial endpoint. This is in contrast to traditional single-arm clinical trials or randomized clinical trials (RCTs) that are static in their protocol and do not modify any parameters until the trial is completed. The adaptation process takes place at certain points in the trial, prescribed in the trial protocol. Importantly, this trial protocol is set before the trial begins with the adaptation schedule and processes specified. Adaptions may include modifications to: dosage, sample size, drug undergoing trial, patient selection criteria and/or "cocktail" mix. The PANDA provides not only a summary of different adaptive designs, but also comprehensive information on adaptive design planning, conduct, analysis and reporting.
References
- J. W. Dixon and A. M. Mood (1948), "A Method for Obtaining and Analyzing Sensitivity Data," Journal of the American Statistical Association , 43, 109–126.
- B. T. Neyer (1994), "A D-Optimality-Based Sensitivity Test," Technometrics , 36, 61–70.
- B. T. Neyer (1992), “Analysis of Sensitivity Tests,” MLM-3736, EG&G Mound Applied Technologies, Miamisburg, Ohio
- H. A. Dror and D. M. Steinberg (2008), "Sequential Experimental Designs for Generalized Linear Models," Journal of the American Statistical Association , 103, Number 481, 288–298.