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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.20710 |
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| _version_ | 1866915759642378240 |
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| author | Sun, Linda Ren, Yixin Chen, Cong |
| author_facet | Sun, Linda Ren, Yixin Chen, Cong |
| contents | Dose optimization is a hallmark of Project Optimus for oncology drug development. The number of doses to include in a dose optimization study depends on the totality of evidence, which is often unclear in early-phase development. With equal sample sizes per dose, carrying three doses is clearly more advantageous than two for optimization. In this paper, we show that, even when the total sample size is fixed, it is still preferable to carry three unless there is very strong evidence that one can be dropped. A mathematical approximation is applied to guide the investigation, followed by a simulation study to complement the theoretical findings. Semi-quantitative guidance is provided for practitioners, addressing both randomized and non-randomized dose optimization while considering population homogeneity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_20710 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Two-dose vs. Three-Dose Optimization Under Sample Size Constraint Sun, Linda Ren, Yixin Chen, Cong Methodology Dose optimization is a hallmark of Project Optimus for oncology drug development. The number of doses to include in a dose optimization study depends on the totality of evidence, which is often unclear in early-phase development. With equal sample sizes per dose, carrying three doses is clearly more advantageous than two for optimization. In this paper, we show that, even when the total sample size is fixed, it is still preferable to carry three unless there is very strong evidence that one can be dropped. A mathematical approximation is applied to guide the investigation, followed by a simulation study to complement the theoretical findings. Semi-quantitative guidance is provided for practitioners, addressing both randomized and non-randomized dose optimization while considering population homogeneity. |
| title | Two-dose vs. Three-Dose Optimization Under Sample Size Constraint |
| topic | Methodology |
| url | https://arxiv.org/abs/2601.20710 |