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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.11333 |
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| _version_ | 1866914036402094080 |
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| author | Chen, Kai Zhao, Yixuan Takeda, Kentaro Yuan, Ying |
| author_facet | Chen, Kai Zhao, Yixuan Takeda, Kentaro Yuan, Ying |
| contents | The US Food and Drug Administration (FDA) launched Project Optimus and issued guidance to reform dose-finding and selection trials, shifting the paradigm from identifying the maximum tolerable dose (MTD) to determining the optimal biological dose (OBD), which optimizes the risk and benefit of treatments. The FDA's guidance emphasizes the importance of collecting sufficient toxicity and efficacy data across multiple doses and considering late-onset cumulative toxicity that often results in tolerability issues. To address these challenges, we propose the BE-BOIN (Backfill time-to-Event Bayesian Optimal INterval) design, which allows backfilling patients into safe and effective doses during dose escalation and accommodates late-onset toxicities. BE-BOIN enables the collection of additional safety and efficacy data to enhance the accuracy and reliability of OBD selection and supports real-time dose decisions for new patients. Our simulation studies show that BE-BOIN accurately identifies the MTD and OBD while significantly reducing trial duration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_11333 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | BE-BOIN: A Dose Optimization Design Accommodating Backfill and Late-Onset Toxicity Chen, Kai Zhao, Yixuan Takeda, Kentaro Yuan, Ying Methodology The US Food and Drug Administration (FDA) launched Project Optimus and issued guidance to reform dose-finding and selection trials, shifting the paradigm from identifying the maximum tolerable dose (MTD) to determining the optimal biological dose (OBD), which optimizes the risk and benefit of treatments. The FDA's guidance emphasizes the importance of collecting sufficient toxicity and efficacy data across multiple doses and considering late-onset cumulative toxicity that often results in tolerability issues. To address these challenges, we propose the BE-BOIN (Backfill time-to-Event Bayesian Optimal INterval) design, which allows backfilling patients into safe and effective doses during dose escalation and accommodates late-onset toxicities. BE-BOIN enables the collection of additional safety and efficacy data to enhance the accuracy and reliability of OBD selection and supports real-time dose decisions for new patients. Our simulation studies show that BE-BOIN accurately identifies the MTD and OBD while significantly reducing trial duration. |
| title | BE-BOIN: A Dose Optimization Design Accommodating Backfill and Late-Onset Toxicity |
| topic | Methodology |
| url | https://arxiv.org/abs/2509.11333 |