
Faculty, Staff and Student Publications
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
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons, Pharmacy and Pharmaceutical Sciences Commons