Dose optimisation with simultaneous pharmacokinetic estimation in adaptive clinical trials. (April 2020)

• Record Type: Journal Article
• Authors: Soeny, Kabir; Bogacka, Barbara; Jones, Byron
• Other Names: Fox Jean-Paul guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 29:Number 4(2020)
• Page Start: 1149
• Page End: 1166
• Publication Date: 2020-04
• Subjects: Target concentration -- drug toxicity -- mixed effects models -- multiple dose regimen -- D-optimal designs -- two-stage design; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280219852582
• Languages: English
• ISSNs: 0962-2802

Abstract

Determination of the optimal dose is a critical objective in the drug developmental process. An optimal dose prevents over- and under-exposure to the treatment drug thereby facilitating superior patient experience and reduced costs to the healthcare system. In this paper, we present a method for model-based dose optimisation with simultaneous pharmacokinetic estimation of the model parameters. Multiple doses of the drug are considered and the objective is to maintain the blood concentration of the drug around a pre-decided target concentration. We consider an adaptive setting wherein the model parameters are estimated from the blood samples collected at D-optimal time points from all subjects enrolled so far in the trial. The estimated parameters are then used to determine the optimal dose regimen for the next cohort. This procedure continues until the condition of a pre-decided stopping rule is met. Simulation studies and sensitivity analysis are undertaken to validate the methodology. We also evaluate the performance of the methodology when carried out in a non-adaptive setting. A two-stage design is then presented which combines the advantages of the adaptive as well as the non-adaptive approach. We demonstrate that our methodology enables pharmacokinetic estimation and dose regimen optimisation simultaneously in an ethical and cost-effective manner protecting the subjects from the ill-effects of suboptimal dose regimens and economising the number of subjects required in the trial.