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Implementation of a Bayesian Design in a Dose‐Escalation Study of an Experimental Agent in Healthy Volunteers
Author(s) -
Zhou Yinghui,
Whitehead John,
Korhonen Pasi,
Mustonen Mika
Publication year - 2008
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2007.00841.x
Subject(s) - bayesian probability , pharmacokinetics , clinical endpoint , adverse effect , computer science , clinical trial , medicine , endpoint determination , clinical study design , medical physics , pharmacology , artificial intelligence
Summary Bayesian decision procedures have recently been developed for dose escalation in phase I clinical trials concerning pharmacokinetic responses observed in healthy volunteers. This article describes how that general methodology was extended and evaluated for implementation in a specific phase I trial of a novel compound. At the time of writing, the study is ongoing, and it will be some time before the sponsor will wish to put the results into the public domain. This article is an account of how the study was designed in a way that should prove to be safe, accurate, and efficient whatever the true nature of the compound. The study involves the observation of two pharmacokinetic endpoints relating to the plasma concentration of the compound itself and of a metabolite as well as a safety endpoint relating to the occurrence of adverse events. Construction of the design and its evaluation via simulation are presented.