Related Experiment Video
Updated: Jan 27, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
A Bayesian model-free approach to combination therapy phase I trials using censored time-to-toxicity data
Graham M Wheeler1, Michael J Sweeting2, Adrian P Mander3
1Cancer Research UK and UCL Cancer Trials Centre, University College London, UK.
None:
The product of independent beta probabilities escalation (PIPE) design for dual-agent phase I dose-escalation trials is a Bayesian model-free approach for identifying multiple maximum tolerated dose combinations of novel combination therapies. Despite only being published in 2015, the PIPE design has been implemented in at least two oncology trials. However, these trials require patients to have completed follow-up before clinicians can make dose-escalation decisions. For trials of radiotherapy or advanced therapeutics, this may lead to impractically long trial durations due to late-onset treatment-related toxicities. In this paper, we extend the PIPE design to use censored time-to-event (TITE) toxicity outcomes for making dose escalation decisions. We show via comprehensive simulation studies and sensitivity analyses that trial duration can be reduced by up to 35%, particularly when recruitment is faster than expected, without compromising on other operating characteristics.
More Related Videos
07:40A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
07:59Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
Published on: June 9, 2023
Related Concept Videos
Censoring Survival Data
Model Approaches for Pharmacokinetic Data: Physiological Models
Model Approaches for Pharmacokinetic Data: Compartment Models
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Statistical Software for Data Analysis and Clinical Trials
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...