Related Experiment Video
Updated: May 2, 2026

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery
Published on: April 14, 2016
MT-Keyboard: A Bayesian Model-assisted Interval Design to Account for Toxicity Grades and Types for Phase I Trials
Kai Chen1, Li Wang2, Ying Yuan3
1Department of Biostatistics and Data Science, The University of Texas Health Science Center, Houston, TX, USA.
Abstract:
Conventionally, dose finding trials are based on dose-limiting toxicity (DLT) that only captures the most severe toxicities, e.g., treatment related grade 3 or higher toxicity according to the NCI Common Terminology Criteria for Adverse Events. However, this approach is often problematic for certain novel targeted therapies and immunotherapies, which may not induce DLT within a clinically active dose range and are often characterized by low grade toxicities. This important issue has been highlighted and discussed in the American Statistical Association (ASA) Biopharmaceutical (BIOP) Section Open Forums, and is also an important consideration of the Project Optimus initiated by FDA to "reform the dose optimization and dose selection paradigm in oncology drug development." In this paper, we propose an easy-to-implement model-assisted Bayesian design, known as multiple toxicity keyboard (MT-Keyboard) design, to incorporate toxicity grades and types into dose finding. The MT-Keyboard design is able to accommodate binary, quasi-binary and continuous toxicity endpoints that are constructed to account for toxicity grades and types. We further extend the MT-Keyboard design, referred to as TITE-MT-Keyboard, to accommodate late-onset toxicity using the approximated likelihood approach. Simulation shows that the MT-Keyboard and TITE-MT-Keyboard designs have desirable operating characteristics, comparable to or better than some existing designs. A web-based software to implement the design will be freely available at www.trialdesign.org.
More Related Videos
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
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...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Dosage Regimens: Designs and Approaches
Kaplan-Meier Approach

