# PoD-TPI: Probability-of-Decision Toxicity Probability Interval Design to Accelerate Phase I Trials

## TL;DR

PoD-TPI is a novel phase I trial design that accelerates dose-finding by enabling real-time dose assignment despite pending toxicity outcomes, improving trial speed while maintaining safety.

## Contribution

It introduces a Bayesian decision framework that accounts for uncertainty in pending outcomes and allows flexible safety and speed trade-offs.

## Key findings

- Shortens trial duration compared to existing methods.
- Maintains safety and efficiency in dose escalation.
- Provides an intuitive tuning mechanism for decision-making.

## Abstract

Cohort-based enrollment can slow down dose-finding trials since the outcomes of the previous cohort must be fully evaluated before the next cohort can be enrolled. This results in frequent suspension of patient enrollment. The issue is exacerbated in recent immune-oncology trials where toxicity outcomes can take a long time to observe. We propose a novel phase I design, the probability-of-decision toxicity probability interval (PoD-TPI) design, to accelerate phase I trials. PoD-TPI enables dose assignment in real-time in the presence of pending toxicity outcomes. With uncertain outcomes, the dose assignment decisions are treated as a random variable, and we calculate the posterior distribution of the decisions. The posterior distribution reflects the variability in the pending outcomes and allows a direct and intuitive evaluation of the confidence of all possible decisions. Optimal decisions are calculated based on 0-1 loss, and extra safety rules are constructed to enforce sufficient protection from exposing patients to risky doses. A new and useful feature of PoD-TPI is that it allows investigators and regulators to balance the trade-off between enrollment speed and making risky decisions by tuning a pair of intuitive design parameters. Through numerical studies, we evaluate the operating characteristics of PoD-TPI and demonstrate that PoD-TPI shortens trial duration and maintains trial safety and efficiency compared to existing time-to-event designs.