Evidence map›Paper›PMID 39984618›Full record

ArticleNPJ precision oncology2025

Personalized dose selection platform for patients with solid tumors in the PRECISE CURATE.AI feasibility trial.

Agata Blasiak, Anh T L Truong, Nigel Foo, Lester W J Tan, Kirthika S Kumar, Shi-Bei Tan, Chong Boon Teo, Benjamin K J Tan, Xavier Tadeo, Hon Lyn Tan and 4 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Trial
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  3. AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026
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  14. Prevalence and clinical impact ofFrontiers in oncology · 2026
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Agata BlasiakThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore. agatablasiak@gmail.com.
Anh T L TruongThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0003-1551-4437
Nigel FooThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.
Lester W J TanThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0003-0323-4964
Kirthika S KumarThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.
Shi-Bei TanThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0001-6388-4390
Chong Boon TeoYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Benjamin K J TanYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Xavier TadeoThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0003-0356-826X
Hon Lyn TanDepartment of Haematology-Oncology, National University Cancer Institute, Singapore (NCIS), National University Health System, Singapore, Singapore.
Cheng Ean CheeYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Wei Peng YongDepartment of Haematology-Oncology, National University Cancer Institute, Singapore (NCIS), National University Health System, Singapore, Singapore.
Dean HoThe Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore. biedh@nus.edu.sg.ORCID http://orcid.org/0000-0002-7337-296X
Raghav SundarThe N.1 Institute for Health (N.1), National University of Singapore, Singapore, Singapore. raghav.sundar@yale.edu.ORCID http://orcid.org/0000-0001-9423-1368

Funding

Ministry of Education - Singapore (MOE) R-397-000-333-114Ministry of Health -Singapore (MOH) MOH-OFLCG18May-0028MOH | National Medical Research Council (NMRC) MOH-OFLCG18May-0003MOH | National Medical Research Council (NMRC) NMRC/CG/M005/2017MOH | National Medical Research Council (NMRC) NMRC/TA/0014/2020National Research Foundation Singapore (National Research Foundation-Prime Minister's office, Republic of Singapore) A20G8b0102National Research Foundation Singapore (National Research Foundation-Prime Minister's office, Republic of Singapore) AISG-GC-2019-002National University of Singapore (NUS) R-719-000-037-733
6 · The paper itself

Abstract

In oncology, the conventional reliance on the maximum tolerated dose (MTD) strategy for chemotherapy may not optimize treatment outcomes for individual patients. CURATE.AI is an AI-derived platform that utilizes a patient's own, small dataset to dynamically personalize only their own dose recommendations. The primary objective of this feasibility trial was to assess the logistical and scientific feasibility of providing dynamically personalized AI-derived chemotherapy dose recommendations for patients with advanced solid tumors at/for treatment with single-agent capecitabine, capecitabine in combination with oxaliplatin (XELOX), or capecitabine in combination with irinotecan (XELIRI). CURATE.AI demonstrated adaptability to clinically relevant situations encountered by patients often treated with palliative intent of care. High rates of user adherence were demonstrated, which could be in part due to the high engagement of the physicians in selecting data and boundaries for CURATE.AI operations.

Identifiers

PMID39984618
PMCPMC11845749

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.