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Adaptive dose-finding designs to identify multiple doses that achieve multiple response targets

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Within drug development it is crucial to find the right dose that is going to be safe and efficacious, this is often done within early phase II clinical trials. The aim of the dose-finding trial is to understand the relationship between the dose of drug and the potential effect of the drug. Increasingly, adaptive designs are being used in this area because they allow greater flexibility for dose exploration as compared to traditional fixed dose designs.

An adaptive dose-finding design usually assumes a true non-linear dose-response model and select doses that either maximise the determinant of information matrix of the design (D-optimality) or minimise the variance of the predicted dose that gives a targeted response. Our design extends the predicted dose methodology, in a limited number of patients (40), to finding two targeted doses: a minimally effective dose; and a therapeutic. In our trial doses are assumed to be given intravenously so theoretically doses are continuous and the response is a normally distributed continuous outcome.

Our design has an initial learning phase where pairs of patients are assigned to five pre-assigned doses. The next phase is fully sequential with an interim analysis after each patient to determine the choice of dose based on the optimality criterion to minimise the determinant of the covariance of the estimated target doses. The dose-choice algorithm assumes that a specific parametric dose-response model is the true relationship, and so a variety of models are considered at the interim and human judgement involved in the overall decision. I will also describe some of the discussions of the dose-decision making meetings.

This talk is part of the Cambridge Statistics Discussion Group (CSDG) series.

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