AUTHOR=Tan Benjamin Kye Jyn , Teo Chong Boon , Tadeo Xavier , Peng Siyu , Soh Hazel Pei Lin , Du Sherry De Xuan , Luo Vilianty Wen Ya , Bandla Aishwarya , Sundar Raghav , Ho Dean , Kee Theodore Wonpeum , Blasiak Agata 

TITLE=Personalised, Rational, Efficacy-Driven Cancer Drug Dosing via an Artificial Intelligence SystEm (PRECISE): A Protocol for the PRECISE CURATE.AI Pilot Clinical Trial

JOURNAL=Frontiers in Digital Health

VOLUME=3

YEAR=2021

URL=https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2021.635524

DOI=10.3389/fdgth.2021.635524

ISSN=2673-253X

ABSTRACT=<p><bold>Introduction:</bold> Oncologists have traditionally administered the maximum tolerated doses of drugs in chemotherapy. However, these toxicity-guided doses may lead to suboptimal efficacy. CURATE.AI is an indication-agnostic, mechanism-independent and efficacy-driven personalised dosing platform that may offer a more optimal solution. While CURATE.AI has already been applied in a variety of clinical settings, there are no prior randomised controlled trials (RCTs) on CURATE.AI-guided chemotherapy dosing for solid tumours. Therefore, we aim to assess the technical and logistical feasibility of a future RCT for CURATE.AI-guided solid tumour chemotherapy dosing. We will also collect exploratory data on efficacy and toxicity, which will inform RCT power calculations.</p><p><bold>Methods and analysis:</bold> This is an open-label, single-arm, two-centre, prospective pilot clinical trial, recruiting adults with metastatic solid tumours and raised baseline tumour marker levels who are planned for palliative-intent, capecitabine-based chemotherapy. As CURATE.AI is a small data platform, it will guide drug dosing for each participant based only on their own tumour marker levels and drug doses as input data. The primary outcome is the proportion of participants in whom CURATE.AI is successfully applied to provide efficacy-driven personalised dosing, as judged based on predefined considerations. Secondary outcomes include the timeliness of dose recommendations, participant and physician adherence to CURATE.AI-recommended doses, and the proportion of clinically significant dose changes. We aim to initially enrol 10 participants from two hospitals in Singapore, perform an interim analysis, and consider either cohort expansion or an RCT. Recruitment began in August 2020. This pilot clinical trial will provide key data for a future RCT of CURATE.AI-guided personalised dosing for precision oncology.</p><p><bold>Ethics and dissemination:</bold> The National Healthcare Group (NHG) Domain Specific Review Board has granted ethical approval for this study (DSRB 2020/00334). We will distribute our findings at scientific conferences and publish them in peer-reviewed journals.</p><p><bold>Trial registration number:</bold> NCT04522284</p>