CURATE.AI COR-Tx Trial for Post Brain Radiotherapy Patients
Study Details
Study Description
Brief Summary
Cognitive deficit is common in patients who have undergone whole brain or partial brain radiotherapy. To counteract intellectual deterioration, the conventional strategies includes drug- based treatments such as donezepil and memantine, which have shown to only provide marginal improvement and, cognitive training regimens, both of which are usually administered at fixed dose/intensities often leading to sub-optimal responses. This study aims to address this clinically relevant problem by harnessing the CURATE.AI platform to identify N-of-1cognitive training profiles the can enhance learning trajectories through individualised calibration and training regimens. CURATE.AI is a phenotypic personalised medicine (PPM) platform that correlates a patient's phenotypic response (cognitive performance) to a certain input (training intensity) based exclusively on the patient's data. This PPM platform is independent of biological system or interventional agent and can be applied to any disorder treatment where dosing/intensity could be better personalised. CURATE.AI is expected to optimise/personalise cognitive training in post-brain radiotherapy patients by dynamically modulating the intensity of a digital cognitive test battery that measures executive processing, multitasking and perceptual learning tasks. In addition, this clinical feasibility trial aims to assess this cognitive test battery as a potential analogous or complementary diagnostic tool as compared to traditional cognitive evaluations performed by a clinician.
Condition or Disease | Intervention/Treatment | Phase |
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N/A |
Detailed Description
Brain radiotherapy causes downstream cognitive deficits. Drug-based cognitive decline treatments show little improvement and side effects may reduce patient compliance. Regimens are usually administered at a fixed dose that doesn't incorporate high patient variability, leading to sub-optimal responses.
Effective cognitive training can improve cognitive performance. Artificial intelligence platforms show great potential for training personalisation. The CURATE.AI platform can be used to identify N-of-1 (single subject) training profiles that can be used to optimise learning trajectories through individualised calibration and training regimens, potentially leading to improved outcomes compared to standard static or adaptive training strategies. CURATE.AI uses only a subject's own performance data to identify the intensity needed for his/her best output. As the subject evolves during the course of intervention, the training intensities are dynamically modulated to maintain performance within a given range.
Here the investigators propose to test the feasibility of CURATE.AI, with a digital cognitive test battery as the interface, as an adaptive training platform for cognitive training addressed to improve brain cancer radiotherapy patients' cognitive performance. The acceptability, implementation and limited efficacy of the digital intervention (DI) will be explored. In addition, the investigators propose to test the feasibility of the digital cognitive test battery potential as a digital diagnostic (DD) tool as compared to traditional cognitive evaluations performed by a clinician. User experience and usability will also be explored.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Experimental: CURATE.AI A cognitive evaluation and a Digital Diagnostic (DD) session performed anytime before radiotherapy will serve as the baseline. After the radiotherapy treatment, which can last between 1 to 6.5 weeks, patients will have a variable recovery time (0 to 4 weeks). Subsequently, patients will be subject to a cognitive evaluation and a DD session, right before starting the Digital Intervention (DI) training. This training will comprise ten weeks of DI (three 10-15 minute sessions per week). Patients will complete cognitive evaluations and DD sessions at the end of DI, and 16 and 32 weeks after the end of DI. |
Device: CURATE.AI
CURATE.AI will be utilised to provide personalised training intensity recommendations (low, medium or high) to the patients during the digital cognitive test battery DI session. The difficulty of each task will be modulated by CURATE.AI by adjusting the frequency of critical events that demand evaluation and/or response.
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Outcome Measures
Primary Outcome Measures
- Patient acceptability of the digital cognitive test battery DI/DD obtained during a semi-structured interview [One visit 60 minutes (at the end of the 10 week intervention)]
Qualitative summary of patient acceptability of the digital cognitive test battery DI/DD
- Patient adherence to the DI/DD [up to 12 months]
Percentage of completed DI/DD sessions
- Patient attrition rate to the DI/DD [up to 12 months]
Percentage of patients that drop out of DI/DD
- Percentage of CURATE.AI profiles successfully created and applied [up to 12 months]
- Timely delivery of DI/DD at indicated time points [up to 12 months]
Percentage of DI/DD sessions successfully delivered by study team at indicated time points
- Digital intervention limited efficacy [up to 12 months]
Change in cognitive performance as measured by the standard of care cognitive evaluations pre-post digital intervention
- Digital diagnostic limited efficacy [up to 12 months]
Correlation between standard of care cognitive evaluations scores and digital diagnostic scores
Secondary Outcome Measures
- 1. Usability of the digital cognitive test battery DI/DD obtained during a semi-structured interview [One visit 60 minutes (at the end of the 10 week intervention)]
Qualitative summary of patient usability of the digital cognitive test battery DI/DD
Eligibility Criteria
Criteria
Inclusion Criteria:
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Age >21 years.
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ECOG performance status 0 to 2.
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Patients with a neoplastic condition (benign or malignant) involving the brain or skull requiring radiotherapy (with or without chemotherapy).
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Patients with a life expectancy of at least 6 months.
Exclusion Criteria:
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Pregnant or breastfeeding women.
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Patients undergoing stereotactic radiosurgery (single fraction).
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Patients who are undergoing re-irradiation to the same area of the brain.
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Patients physically incapable of using computer tablet (either due to vision loss or dominant hand weakness)
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Patients who cannot understand spoken English language.
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Patients who are unable to give informed consent.
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | National University Hospital | Singapore | Singapore | ||
2 | The N.1 Institute for Health (N.1), NUS | Singapore | Singapore |
Sponsors and Collaborators
- National University Hospital, Singapore
- National University, Singapore
- The N.1 Institute for Health (N.1)
Investigators
- Principal Investigator: Dr Balamurugan A Vellayappan, National University Cancer Institute, Singapore
Study Documents (Full-Text)
None provided.More Information
Publications
- Kee, Theodore & Weiyan, Chee & Blasiak, Agata & Chong, Jordan & Chen, Jonna & Yeo, B.T. Thomas & Ho, Dean & Asplund, Christopher. (2019). Harnessing CURATE.AI as a Digital Therapeutics Platform by Identifying N-of-1 Learning Trajectory Profiles. Advanced Therapeutics. 2. 1900023. 10.1002/adtp.201900023.
- Pantuck AJ, Lee DK, Kee T, Wang P, Lakhotia S, Silverman MH, Mathis C, Drakaki A, Belldegrun AS, Ho CM, Ho D. Modulating BET bromodomain inhibitor ZEN-3694 and enzalutamide combination dosing in a metastatic prostate cancer patient using CURATE. AI, an artificial intelligence platform. Advanced Therapeutics. 2018 Oct;1(6):1800104.
- Zarrinpar A, Lee DK, Silva A, Datta N, Kee T, Eriksen C, Weigle K, Agopian V, Kaldas F, Farmer D, Wang SE, Busuttil R, Ho CM, Ho D. Individualizing liver transplant immunosuppression using a phenotypic personalized medicine platform. Sci Transl Med. 2016 Apr 6;8(333):333ra49. doi: 10.1126/scitranslmed.aac5954.
- 2020/00249