Clinical trial NCT04848935: CURATE.AI COR-Tx Trial for Post Brain Radiotherapy Patients
Official title: CURATE.AI Optimised Digital COgnitive Rehabilitation Therapy (COR-Tx) for Post Brain Radiotherapy Patients: CURATE.AI COR-Tx Mixed-methods Feasibility Clinical Trial
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Cognitive Decline
Keywords: Oncology
Digital therapeutics
Cognitive evaluation
Digital diagnostic
Cognitive training
Phenotypic Personalised Medicine (PPM)
Multi-Attribute Task Battery (MATB)
Training intensity
Radiotherapy
CURATE.AI
Lead sponsor: National University Hospital, Singapore
Sponsor class: OTHER
Collaborators: name: National University of Singapore
name: The N.1 Institute for Health (N.1)
First posted: 2021-04-19
Enrollment: 15
Sex: ALL
Minimum age (years): 21
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: TREATMENT

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.

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.

Eligibility criteria: 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.

Primary outcomes:
measure: Patient acceptability of the digital cognitive test battery DI/DD obtained during a semi-structured interview
timeFrame: One visit 60 minutes (at the end of the 10 week intervention)
measure: Patient adherence to the DI/DD
timeFrame: up to 12 months
measure: Patient attrition rate to the DI/DD
timeFrame: up to 12 months
measure: Percentage of CURATE.AI profiles successfully created and applied
timeFrame: up to 12 months
measure: Timely delivery of DI/DD at indicated time points
timeFrame: up to 12 months
measure: Digital intervention limited efficacy
timeFrame: up to 12 months
measure: Digital diagnostic limited efficacy
timeFrame: up to 12 months
Secondary outcomes:
measure: 1. Usability of the digital cognitive test battery DI/DD obtained during a semi-structured interview
timeFrame: One visit 60 minutes (at the end of the 10 week intervention)
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: National University Hospital
city: Singapore
country: Singapore
facility: The N.1 Institute for Health (N.1), NUS
Study officials:
affiliation: National University of Singapore
name: Dr Balamurugan A Vellayappan
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: 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.
citation: 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.