AIM: Recent publications indicate a strong interest in applying Bayesian 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.
AIM: Recent publications indicate a strong interest in applying Bayesian 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.
Authors: Nicolas Penel; Nicolas Isambert; Pierre Leblond; Charles Ferte; Alain Duhamel; Jacques Bonneterre Journal: Invest New Drugs Date: 2009-01-10 Impact factor: 3.850
Authors: N R Cutler; J J Sramek; D J Greenblatt; P Chaikin; N Ford; L J Lesko; B Davis; R L Williams Journal: J Clin Pharmacol Date: 1997-09 Impact factor: 3.126
Authors: Stefan Sturm; Marie-Laure Delporte; Salah Hadi; Scott Schobel; Lothar Lindemann; Robert Weikert; Georg Jaeschke; Michael Derks; Giuseppe Palermo Journal: Br J Clin Pharmacol Date: 2017-12-18 Impact factor: 4.335