Optimizing and Personalising Azacitidine Combination Therapy for Treating Solid Tumours QPOP and CURATE.AI

Summary

This pilot feasibility study aims to set the foundation to investigate the applicability of QPOP drug selection followed by CURATE.AI-guided dose optimisation of the selected azacitidine combination therapy for solid tumours using CURATE.AI within the current clinical setting.

QPOP will identify drug interactions towards optimal efficacy and cytotoxicity from the pre-specified drug pool based on ex vivo experimental data from the individual participant's tissue sample model. With these drug interactions, QPOP will identify the optimal drugs for the specific participant whose biopsy provided the cells for the ex vivo experimentation. Subsequently, CURATE.AI will be used to guide dosing for the selected combination therapy for that participant.

Individualised CURATE.AI profiles will be generated based on each participant's response to a set of drug doses. Subsequently, the personalised CURATE.AI profile will be used to recommend the efficacy-driven dose. CURATE.AI will operate only within the safety range for each drug pre-specified for each participant.

This pilot feasibility study will inform the investigators on the logistical and scientific feasibility of performing a large-scale randomised controlled trial (RCT) with the selected azacitidine combination therapy regimens and response markers. A secondary objective is to collect toxicity and efficacy data using established and exploratory response markers within and in-between cycles as exploratory outcomes.

Conditions

• Solid Tumor
• Gastrointestinal Cancer
• Breast Cancer

Interventions

DEVICE

QPOP

QPOP is a mechanism-agnostic platform for optimizing drug selection. QPOP uses a quadratic equation to describe the patient-specific drug-drug interaction space based solely on experimentally derived drug-response data on individual patient's tissue sample, from which optimal drug combinations can be identified. Drug selection via QPOP allows for identification of an optimal combination therapy without the need for exhaustive testing of every combination. The first stage of the trial aims to generate a personalised QPOP drugs list for each participant based on experimentally derived data from ex vivo testing in the participant's tissue sample. Optimal drugs from a pre-specified drug pool will be recommended by the QPOP team.

DEVICE

CURATE.AI

CURATE.AI - a small data, AI-derived technology platform based on this discovery - allows personalised guidance of an individual's dose modulations based only on that individual's data. Additionally, CURATE.AI is mechanism-independent, and dynamically adapts to changes experienced by the participant, providing dynamic dose optimisation throughout the duration of the participant's treatment. The second stage of the trial aims to obtain a personalised CURATE.AI profile for each participant, based on their phenotypic response to a set of drug doses from the drug combinations with azacitidine identified and recommended by the QPOP team. The doses will be recommended by the CURATE.AI team, when relevant to the clinical decision-making process. Once an actionable profile is obtained, dose recommendations are based on the profile and aimed to treat the participant. The maximum period of involvement with this study when azacitidine may be adjusted by CURATE.AI is 18 months.

DRUG

Azacitidine + docetaxel

Azacitidine subcutaneous injection Day 1, 2 and Day 8, 9 + 30 mg/m2 docetaxel intravenously Day 1 and 8 Each chemotherapy cycle will be 21 days.

DRUG

Azacitidine + paclitaxel

Azacitidine subcutaneous injection Day 1, 2 and Day 8, 9 + 80 mg/m2 paclitaxel intravenously Day 1 and 8 Each chemotherapy cycle will be 21 days.

DRUG

Azacitidine + irinotecan

Azacitidine intravenously subcutaneous injection Day 1, 2 and Day 8, 9 + 100 mg/m2 irinotecan intravenously Day 1 and 8. Each chemotherapy cycle will be 21 days.

Sponsors & Collaborators

• The N.1 Institute for Health (N.1)

  collaborator OTHER

• Cancer Science Institute of Singapore

  collaborator UNKNOWN

• National University Hospital, Singapore

  lead OTHER

Principal Investigators

• Wei Peng Yong · National University Hospital, Singapore

Study Design

Allocation

NA

Purpose

TREATMENT

Masking

NONE

Model

SEQUENTIAL

Eligibility

Min Age

21 Years

Max Age

99 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2023-02-13

Primary Completion

2026-10-04

Completion

2027-04-04

Countries

• Singapore

Study Locations