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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT04848935
Other study ID # 2020/00249
Secondary ID
Status Recruiting
Phase N/A
First received
Last updated
Start date June 14, 2021
Est. completion date July 1, 2022

Study information

Verified date November 2021
Source National University Hospital, Singapore
Contact Dr Balamurugan A Vellayappan
Phone +65 67795555
Email bala_vellayappan@nuhs.edu.sg
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial 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.


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.


Recruitment information / eligibility

Status Recruiting
Enrollment 15
Est. completion date July 1, 2022
Est. primary completion date January 1, 2022
Accepts healthy volunteers No
Gender All
Age group 21 Years to 99 Years
Eligibility Inclusion Criteria: - Age >21 years. - ECOG performance status 0 to 2. - Patients with a neoplastic condition (benign or malignant) involving the brain or skull requiring radiotherapy (with or without chemotherapy). - Patients with a life expectancy of at least 6 months. Exclusion Criteria: - Pregnant or breastfeeding women. - Patients undergoing stereotactic radiosurgery (single fraction). - Patients who are undergoing re-irradiation to the same area of the brain. - Patients physically incapable of using computer tablet (either due to vision loss or dominant hand weakness) - Patients who cannot understand spoken English language. - Patients who are unable to give informed consent.

Study Design


Related Conditions & MeSH terms


Intervention

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.

Locations

Country Name City State
Singapore National University Hospital Singapore
Singapore The N.1 Institute for Health (N.1), NUS Singapore

Sponsors (3)

Lead Sponsor Collaborator
National University Hospital, Singapore National University, Singapore, The N.1 Institute for Health (N.1)

Country where clinical trial is conducted

Singapore, 

References & Publications (3)

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. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Patient acceptability of the digital cognitive test battery DI/DD obtained during a semi-structured interview Qualitative summary of patient acceptability of the digital cognitive test battery DI/DD One visit 60 minutes (at the end of the 10 week intervention)
Primary Patient adherence to the DI/DD Percentage of completed DI/DD sessions up to 12 months
Primary Patient attrition rate to the DI/DD Percentage of patients that drop out of DI/DD up to 12 months
Primary Percentage of CURATE.AI profiles successfully created and applied up to 12 months
Primary Timely delivery of DI/DD at indicated time points Percentage of DI/DD sessions successfully delivered by study team at indicated time points up to 12 months
Primary Digital intervention limited efficacy Change in cognitive performance as measured by the standard of care cognitive evaluations pre-post digital intervention up to 12 months
Primary Digital diagnostic limited efficacy Correlation between standard of care cognitive evaluations scores and digital diagnostic scores up to 12 months
Secondary 1. Usability of the digital cognitive test battery DI/DD obtained during a semi-structured interview Qualitative summary of patient usability of the digital cognitive test battery DI/DD One visit 60 minutes (at the end of the 10 week intervention)
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