The Case for an Unblinded Modeler in Early Clinical Development.

Abstract

The current trend for clinical pharmacology is toward more complex studies (eg, umbrella protocols covering single and multiple ascending doses, food effect, metabolism pathways), requiring many decisions to be made during their conduct. This article discusses guidance of such early clinical studies by modeling and simulation. The ability to make use of all available information each time new data become available during the study requires the modeling scientist to be unblinded. This must of course not jeopardize the blinding of the clinical team, and this article discusses how unblinding can be prevented. Although modeling and simulation are established for guidance of the drug development process overall, they are not frequently used for guidance on a small scale, that is, during studies with the largest uncertainty, the first-in-human studies. Application of a quantitative model backbone makes early clinical drug development a more efficient process and provides additional safety for healthy subjects and patients. Real clinical impact is illustrated by 3 case studies that show different contributions from unblinded modeling: dose escalation based on safety data, modeling and predicting with explicit incorporation of in vitro data, and dose escalation supported by unblinded analysis of adverse event data, which resulted in new insights of the clinical team without being unblinded and made it possible to proceed with dose escalation and to extend the study with an up-titration group.