Backfill Bayesian Ordered Lattice Design for Phase I Clinical Trials

The Bayesian Ordered Lattice Design (BOLD) method for Phase I clinical trials is extended to address an important challenge. It is widely understood that conventional Phase I trial designs are not consistently effective in determining safe and active dose levels. The US FDA launched the Project Optimus, aimed at reforming the paradigms of dose optimization and selection. We propose a backfill BOLD design (BF-BOLD) that centers on BOLD for dose-finding but also adds an activity evaluation for each patient. Our method for determining the optimal biological dose (OBD) first involves identifying the maximum tolerated dose (MTD) and then assessing activity rates among dose levels below the identified MTD. This approach is straight-forward and does not require complex statistical modeling. The results of the simulation indicate that performing dose-finding trials with backfilling can both enhance safety and activity assessment, thereby improving treatment sustainability while also preserving the potential for efficacy of the Recommended Phase II Dose (RP2D). We also demonstrate the applicability of the backfill design for reducing overdose rates, and as a more attractive alternative to small-scale dose expansion trials that follow dose escalation. Backfill designs are an important design approach for early phase trials.

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Journal
medRxiv
Published
2026-04-06
DOI
https://doi.org/10.64898/2026.04.02.26350086
Primary Topic
Statistical Methods in Clinical Trials
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article
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article

Backfill Bayesian Ordered Lattice Design for Phase I Clinical Trials

Gi-Ming Wang, Curtis M. Tatsuoka
medRxiv
Statistical Methods in Clinical Trials
article

Backfill Bayesian Ordered Lattice Design for Phase I Clinical Trials

Gi-Ming Wang, Curtis M. Tatsuoka
article en

Abstract

The Bayesian Ordered Lattice Design (BOLD) method for Phase I clinical trials is extended to address an important challenge. It is widely understood that conventional Phase I trial designs are not consistently effective in determining safe and active dose levels. The US FDA launched the Project Optimus, aimed at reforming the paradigms of dose optimization and selection. We propose a backfill BOLD design (BF-BOLD) that centers on BOLD for dose-finding but also adds an activity evaluation for each patient. Our method for determining the optimal biological dose (OBD) first involves identifying the maximum tolerated dose (MTD) and then assessing activity rates among dose levels below the identified MTD. This approach is straight-forward and does not require complex statistical modeling. The results of the simulation indicate that performing dose-finding trials with backfilling can both enhance safety and activity assessment, thereby improving treatment sustainability while also preserving the potential for efficacy of the Recommended Phase II Dose (RP2D). We also demonstrate the applicability of the backfill design for reducing overdose rates, and as a more attractive alternative to small-scale dose expansion trials that follow dose escalation. Backfill designs are an important design approach for early phase trials.

medRxiv
University of Maryland, Baltimore (US), Institute of Bioinformatics (IN), Case Western Reserve University (US)
Responsible consumption and production
Openalex Percentile: Top 22%
Statistical Methods in Clinical Trials
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Backfill Bayesian Ordered Lattice Design for Phase I Clinical Trials — Gi-Ming Wang, Curtis M. Tatsuoka · medRxiv (2026) | TGRS Research Map | TGRS