Incorporation of healthy volunteers data on receptor occupancy into a phase II proof‐of‐concept trial using a Bayesian dynamic borrowing design

• Published in: Biometrical journal Vol. 65; no. 8; pp. e2200305 - n/a
• Main Authors: Di Stefano, Fulvio, Rodrigues, Christelle, Galtier, Stephanie, Guilleminot, Sandrine, Robert, Veronique, Gasparini, Mauro, Saint‐Hilary, Gaelle
• Format: Journal Article
• Language: English
• Published: Germany Wiley - VCH Verlag GmbH & Co. KGaA 01-12-2023
• Subjects: Bayesian; Bayesian analysis; borrowing; Clinical outcomes; Clinical trials; Design; early phase; historical data; Inflammation; Pathophysiology; Patients; Pharmacokinetics; phase II; physiology‐based pharmacokinetics; receptor occupancy; Receptors; Simulation; early phase; phase II; physiology-based pharmacokinetics; historical data; Bayesian; receptor occupancy; borrowing
• DOI: 10.1002/bimj.202200305
• EISSN: 1521-4036
• ISSN: 0323-3847

Receptor occupancy in targeted tissues measures the proportion of receptors occupied by a drug at equilibrium and is sometimes used as a surrogate of drug efficacy to inform dose selection in clinical trials. We propose to incorporate data on receptor occupancy from a phase I study in healthy volunteers into a phase II proof‐of‐concept study in patients, with the objective of using all the available evidence to make informed decisions. A minimal physiologically based pharmacokinetic modeling is used to model receptor occupancy in healthy volunteers and to predict it in the patients of a phase II proof‐of‐concept study, taking into account the variability of the population parameters and the specific differences arising from the pathological condition compared to healthy volunteers. Then, given an estimated relationship between receptor occupancy and the clinical endpoint, an informative prior distribution is derived for the clinical endpoint in both the treatment and control arms of the phase II study. These distributions are incorporated into a Bayesian dynamic borrowing design to supplement concurrent phase II trial data. A simulation study in immuno‐inflammation demonstrates that the proposed design increases the power of the study while maintaining a type I error at acceptable levels for realistic values of the clinical endpoint.