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Bayesian adaptive designs in single ascending dose trials in healthy volunteers
Author(s) -
Guédé David,
Reigner Bruno,
Vandenhende Francois,
Derks Mike,
Beyer Ulrich,
Jordan Paul,
Worth Eric,
Diack Cheikh,
Frey Nicolas,
Peck Richard
Publication year - 2014
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.12344
Subject(s) - bayesian probability , adaptive design , medicine , maximum tolerated dose , clinical trial , statistics , computer science , mathematics
Aim Recent publications indicate a strong interest in applying B ayesian adaptive designs in first time in humans ( FTIH ) studies outside of oncology. The objective of the present work was to assess the performance of a new approach that includes Bayesian adaptive design in single ascending dose ( SAD ) trials conducted in healthy volunteers, in comparison with a more traditional approach. Methods A trial simulation approach was used and seven different scenarios of dose–response were tested. Results The new approach provided less biased estimates of maximum tolerated dose ( MTD ). In all scenarios, the number of subjects needed to define a MTD was lower with the new approach than with the traditional approach. With respect to duration of the trials, the two approaches were comparable. In all scenarios, the number of subjects exposed to a dose greater than the actual MTD was lower with the new approach than with the traditional approach. Conclusions The new approach with Bayesian adaptive design shows a very good performance in the estimation of MTD and in reducing the total number of healthy subjects. It also reduces the number of subjects exposed to doses greater than the actual MTD .