A Semi-Mechanistic Dose-Finding Design in Oncology Using Pharmacokinetic/Pharmacodynamic Modeling

Authors

Xiao Su
Yisheng Li
Peter Müller
Chia-Wei Hsu
Haitao Pan
Kim-Anh Do

Publication Date

11-1-2022

Journal

Pharmaceutical Statistics

Abstract

While a number of phase I dose-finding designs in oncology exist, the commonly used ones are either algorithmic or empirical model-based. We propose a new framework for modeling the dose-response relationship, by systematically incorporating the pharmacokinetic (PK) data collected in the trial and the hypothesized mechanisms of the drug effects, via dynamic PK/PD modeling, as well as modeling of the relationship between a latent cumulative pharmacologic effect and a binary toxicity outcome. This modeling framework naturally incorporates the information on the impact of dose, schedule and method of administration (e.g., drug formulation and route of administration) on toxicity. The resulting design is an extension of existing designs that make use of pre-specified summary PK information (such as the area under the concentration-time curve [AUC] or maximum serum concentration [C

Keywords

Humans, Maximum Tolerated Dose, Bayes Theorem, Dose-Response Relationship, Drug, Medical Oncology, Computer Simulation, Research Design, Neoplasms, Area under the concentration-time curve (AUC), Dose response, Maximum tolerated dose, Pharmacologic effect, Phase I trial, Toxicity

DOI

10.1002/pst.2249

PMID

35748220

PMCID

PMC10134386

PubMedCentral® Posted Date

11-1-2023

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes