Solid TumorPhase 1/2NCT05381038

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

A Phase 1/2 study testing QPOP, CURATE.AI and Azacitidine + docetaxel in people with Solid Tumor and Gastrointestinal Cancer, run by National University Hospital, Singapore at 1 site in Singapore.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts

Official record

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Trial 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. Read more about this study

Who is it for?: Ages 21 to 99 years
Conditions the study is for: Solid Tumor, Gastrointestinal Cancer, Breast Cancer
What is being tested?: QPOP, CURATE.AI and Azacitidine + docetaxel
Type of treatment: Injection or infusion, Medical device
Could I receive a placebo?: No, everyone receives an active treatment
How many people: 10 participants
Where: 1 siteSingapore
Study dates: 13 Feb 2023to 4 Apr 2027
Phase: Phase 1/2
Are there results?: Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

Ages 21 to 99 years
All sexes
No healthy volunteers
Adult, Older adult

Who may be able to join

Males and females ≥ 21 years of age.
Eastern Cooperative Oncology Group (ECOG) Performance Status of 0 to 2.
Patients must meet the following clinical laboratory criteria within 21 days of starting treatment:
Absolute neutrophil count (ANC) ≥ 1,000/mm3 and platelet ≥ 50,000/mm3
Total bilirubin ≤ 1.5 x the upper limit of the normal range (ULN). Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) ≤ 3 x ULN of ≤ 5 ULN if involvement of the liver.
Calculated creatinine clearance ≥ 30 mL/min or creatinine < 1.5 x ULN.

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Diagnosed with breast or gastric cancer, where docetaxel, paclitaxel or irinotecan is indicated for palliative therapy.
Patients who have undergone QPOP drug screen (e.g. under QGAIN (2019/00924) or NGAIN trial (2021/00009) where the drug screen indicated potential benefit of combining azacitidine with taxane or irinotecan.
Patients must have raised response marker above upper limit of local laboratory normal (e.g. CEA and/or CA19-9, CA 15-3, CA 125, AFP, and methylation markers such as but not limited to DNMT).

Who cannot join

Patients who are lactating or pregnant.
Patients with clinically significant hypersensitivity to one or more of the selected regimen's constituent drug(s) (e.g. patients with clinically significant hypersensitivity to irinotecan may not be enrolled on azacitidine + irinotecan, but may be allowed on azacitidine + paclitaxel or azacitidine + docetaxel).
Contraindication to any of the required concomitant drugs or supportive treatments.
Any clinically significant medical disease or psychiatric condition that, in the co-investigator's opinion, may interfere with protocol adherence or a subject's ability to give informed consent.
Major surgery within 28 days prior to start of the treatment.
Active congestive heart failure (New York Heart Association [NYHA] Class III or IV), symptomatic ischaemia, or conduction abnormalities uncontrolled by conventional intervention. Myocardial infarction within 4 months prior to informed consent obtained.
Patients who previously underwent chemotherapy treatment with either docetaxel, paclitaxel and/or irinotecan may still be able to enrol into treatment with the same drug in combination with azacitidine provided they fulfil all other criteria and approval is sought by PI and Sponsor (e.g. patients previously treated with paclitaxel and are enroling for treatment with paclitaxel + azacitidine).
Patients with clinical suspicion or diagnosis of Gilbert's syndrome will not be allowed to enrol with azacitidine + irinotecan, but may be allowed to enrol for treatment with azacitidine + docetaxel or azacitidine + paclitaxel provided they fulfil all other criteria.

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

Wei Peng Yong contact

6779 5555

Wei_Peng_Yong@nuhs.edu.sg

Singapore1 site, 1 recruiting

National University Hospital
Singapore, 119074
Wei Peng Yong, 69082222, Wei_Peng_Yong@nuhs.edu.sg
Wei Peng Yong
Recruiting

Other trials in Singapore

About this study

Official title: Optimizing and Personalising Azacitidine Combination Therapy for Treating Solid Tumours Using the Quadratic Phenotypic Optimization Platform (QPOP) and an Artificial Intelligence-based Platform (CURATE.AI)

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.

Read the detailed description

Several drug combinations and modulation in drug dosing are given to promote cancer cell elimination in cancer patients. While advances in omics tools have led to greater understanding of the complexity of diseases such as cancer, they have also led to the understanding that large networks of molecular interactions contribute to both disease progression and therapeutic resistance. The rational design of drug combinations is a challenge because complex molecular networks contribute to feedback mechanisms of drug resistance and compensatory oncogenic drivers that limit the efficacy of targeted inhibitors. This challenge is compounded by the vast number of available drugs to identify optimal drug combinations from.

In addition to the complexities in identifying optimal drug combinations, optimal dosing remains a challenge as drug synergy is both dose, time- and patient- dependent. The final drug concentration in the body must fall within a narrow range that maximises cancer elimination while minimizing toxic side effects. The complexity of this task increases significantly with the number of drugs given in combination due to increasing parameters and stochastic behaviour of a biological system. Currently, the established approach is to select maximum tolerated doses (MTD) - the highest drug doses that do not cause unacceptable side effects. Treatment efficacy does not guide dose selection. Combined with limited personalisation, this dosing strategy often results in sub-optimal outcomes of the treatment.

In this pilot feasibility study, participants will undergo QPOP drug selection, a stage of CURATE.AI profile generation, and a stage of CURATE.AI profile-based, efficacy-driven drug dosing.

As there are no prior clinical trial cohorts using CURATE.AI in participants with solid tumours and there are existing data for breast and gastric cancer for input into QPOP, this feasibility pilot study will focus on the practicality and feasibility of using QPOP and CURATE.AI in this clinical context.

At the end of the participation of the first 10 patients, an interim analysis will be conducted using the data generated from these participants, which will include formal power and statistical sample size calculations. Based on these outcomes, the investigators will consider cohort expansion or an RCT. Specifically, the interim analysis will aid the decisions on whether to proceed with future RCTs; their design (superiority, equivalence or non-inferiority); logistical and practical aspects of running a large-scale RCT; patient population selection for the RCT; and potential applicability of CURATE.AI in a wider range of systemic therapy regimens, response markers and/or expansion of the current cohort to elicit further data on secondary endpoints and/or new randomized cohorts.

Although not standard of care treatment for breast and gastric cancer, azacitidine combination therapy is chosen by the investigators as azacitidine combination therapy as azacitidine is a potent DNA methyltransferase inhibitor (DNMT) that can increase the sensitivity of a range of metastatic or advanced solid tumours, such as breast and gastric cancer, to treatment with docetaxel, paclitaxel, or irinotecan after developing resistance. Studies have also demonstrated the possibility of low dose treatment with chemotherapeutic agents when given together with azacitidine. However, cytotoxicity of azacitidine increases with dose and exposure time, which highlights the need to rapidly identify the optimal azacitidine-containing drug combinations and for personalised dose modulation during treatment. As such, QPOP drug selection and CURATE.AI dose modulation pipeline is in the ideal position to optimise treatment with azacitidine in combination with docetaxel, paclitaxel, or irinotecan via a personalised manner to maximise efficacy while minimising toxicities.

Participants will undergo QPOP drugs selection optimisation, and those participants who are identified via QPOP to potentially benefit from azacitidine in combination with docetaxel, paclitaxel, or irinotecan will transition to the CURATE.AI stage of the trial after treatment fails. Participants who have undergone QPOP drug selection (e.g. under QGAIN (2019/00924) or NGAIN trial (2021/00009)) are allowed to enrol for the CURATE.AI modulation period of this study at the approval of the Principal Investigator and Sponsor.

CURATE.AI will facilitate personalised treatment to each of the participants by recommending optimal doses in a dynamic fashion. In this phase, only azacitidine dose in the selected azacitidine combination will be modulated by CURATE.AI. Criteria for recruitment allow a high variability in the participant population to reflect a true variability in the cases faced in the clinical practice.

Conditions: Solid Tumor, Gastrointestinal Cancer, Breast Cancer
Being tested: QPOP, CURATE.AI, Azacitidine + docetaxel, Azacitidine + paclitaxel, Azacitidine + irinotecan
Keywords: QPOP, Cancer, Artificial Intelligence, CURATE.AI, Chemotherapy, Azacitidine, docetaxel, paclitaxel, irinotecan
Medical subject headings: Gastrointestinal Neoplasms, Breast Neoplasms, Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

QPOPDevice
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.
CURATE.AIDevice
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.
Azacitidine + docetaxelDrug
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.
Azacitidine + paclitaxelDrug
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.
Azacitidine + irinotecanDrug
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.

Study groups in NCT05381038
Study group	Role	What they receive
QPOP + CURATE.AI	Experimental	Participants will undergo two study stages: QPOP drug selection and CURATE.AI-guided dosing modulation. In the QPOP drug selection stage, participants will undergo a baseline biopsy for organoid generation and subsequently receive treatment as per SOC. During this time, QPOP will identify optimal drug combinations for the participant based on ex vivo experiments on the participant's organoid. Participants who are identified via QPOP to potentially benefit from azacitidine in combination therapy (azacitidine + docetaxel, azacitidine + paclitaxel or azacitidine + irinotecan) will move on to the CURATE.AI-guided dosing modulation stage with treatment with azacitidine. Azacitidine treatment will begin once disease progression after SOC treatment is determined based on CT scans. Only azacitidine dose in the selected azacitidine combination will be modulated by CURATE.AI Receives: Device: QPOP; Device: CURATE.AI; Drug: Azacitidine + docetaxel; Drug: Azacitidine + paclitaxel; Drug: Azacitidine + irinotecan

What is being measured

The primary outcome is the main question the study is designed to answer.

QPOP applicability: percentage of participants with successful application of QPOP drug selection.
A decision on whether we "successfully apply" the QPOP drug selection requires expert judgement and cannot be made based on a purely numerical process. The expert panel will consider the following factors with careful regard for the individual circumstances of each participant:
1. The goodness-of-fit of the QPOP derived equation is acceptable to allow for a reliable list of effective drug combinations;
2. The drugs list is generated sufficiently early for the participant to potentially benefit
Measured: up to 18 months
CURATE.AI applicability: percentage of participants in whom the investigators successfully apply CURATE.AI profile.
A decision on whether we "successfully apply" the CURATE.AI profile requires expert judgement and cannot be made based on a purely numerical process. The expert panel will consider the following factors with careful regard for the individual circumstances of each participant:
1. Error/variance (biological/analytical) is sufficiently small to allow accurate predictions;
2. Profile can be generated sufficiently early for the participant to potentially benefit;
3. Dose-dependent relationship is observed;
4. Profile is actionable (i.e. fulfils the co-investigator's pre-specified safety requirements);
5. Systemic changes in the participant which require profile recalibration are rare or readily assimilated into the CURATE.AI algorithm.
Measured: up to 18 months

Secondary outcomes (6)

Physician adherence: percentage of QPOP recommended drug combinations that were used by the co-investigator.
Measured: up to 18 months
Patient adherence: percentage of participants who always adhered to the prescribed dose whenever they took their medication, as measured by the standardised pharmacovigilance protocol.
Measured: up to 18 months
Timely delivery of CURATE.AI recommendations to the clinician: percentage of CURATE.AI recommendations provided in time for the next chemotherapy cycle, across all participants and cycles.
Measured: up to 18 months
CURATE.AI relevance: percentage of dosing events across all participants and cycles in which CURATE.AI recommendation is considered in the clinical decision-making process
Measured: up to 18 months
Physician adherence: percentage of CURATE.AI recommended doses that were used by the co-investigator.
Measured: up to 18 months
Clinically significant dose changes
percentage of participants in whom the CURATE.AI-guided cumulative dose is substantially (≥10%) different from the projected SOC cumulative dose, which is defined as the maximum dose of the modulated drug*, azacitidine, multiplied by the number of completed chemotherapy cycles.
- The maximum dose of the modulated drug azacitidine is 120mg/m2 once daily given on days 1-2 and days 8-9, every 21 days, in combination with weekly docetaxel, paclitaxel or irinotecan for two weeks followed by one week of rest.
Measured: up to 18 months

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

13 Feb 20234 Apr 2027

First posted19 May 2022
Study start13 Feb 2023
Primary completion4 Oct 2026 (estimated)
Study completion4 Apr 2027 (estimated)

Resources

Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
Publications (15)Papers the sponsor has linked to this study.
Other trials for Solid TumorStudies of the same condition, open and under way.
What the trial phases meanHow a treatment moves from first tests in people to approval.

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design

Study type: Interventional
Phase: Phase 1/2
Primary purpose: Treatment
Allocation: Not applicable
Intervention model: Sequential
Model description: 10 participants diagnosed with breast or gastric cancer undergoing or planned for treatment will be enrolled. The participants will undergo QPOP drug selection optimisation, and those participants who are identified via QPOP to potentially benefit from azacitidine in combination with docetaxel, paclitaxel or irinotecan will transition to the CURATE.AI dose modulation phase of the trial. Only azacitidine dose in the selected azacitidine combination will be modulated by CURATE.AI
Masking: None (open label)
Enrolment: 10 participants (estimated)

IDs, dates and publications

ClinicalTrials.gov ID: NCT05381038
Sponsor's protocol ID: 2021/01159
Status last verified: Sep 2025
First submitted: 22 Mar 2022
Last updated: 23 Sep 2025
Results posted: No
Data monitoring committee: No
FDA-regulated drug: No
FDA-regulated device: No
Individual data sharing: No

Publications

Rozenblatt-Rosen O, Deo RC, Padi M, Adelmant G, Calderwood MA, Rolland T, Grace M, Dricot A, Askenazi M, Tavares M, Pevzner SJ, Abderazzaq F, Byrdsong D, Carvunis AR, Chen AA, Cheng J, Correll M, Duarte M, Fan C, Feltkamp MC, Ficarro SB, Franchi R, Garg BK, Gulbahce N, Hao T, Holthaus AM, James R, Korkhin A, Litovchick L, Mar JC, Pak TR, Rabello S, Rubio R, Shen Y, Singh S, Spangle JM, Tasan M, Wanamaker S, Webber JT, Roecklein-Canfield J, Johannsen E, Barabasi AL, Beroukhim R, Kieff E, Cusick ME, Hill DE, Munger K, Marto JA, Quackenbush J, Roth FP, DeCaprio JA, Vidal M. Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins. Nature. 2012 Jul 26;487(7408):491-5. doi: 10.1038/nature11288.
PubMed 22810586
Chandarlapaty S. Negative feedback and adaptive resistance to the targeted therapy of cancer. Cancer Discov. 2012 Apr;2(4):311-9. doi: 10.1158/2159-8290.CD-12-0018. Epub 2012 Mar 22.
PubMed 22576208
Logue JS, Morrison DK. Complexity in the signaling network: insights from the use of targeted inhibitors in cancer therapy. Genes Dev. 2012 Apr 1;26(7):641-50. doi: 10.1101/gad.186965.112.
PubMed 22474259
Norton L, Simon R. The Norton-Simon hypothesis revisited. Cancer Treat Rep. 1986 Jan;70(1):163-9. No abstract available.
PubMed 3510732
Peters WP, Rosner GL, Vredenburgh JJ, Shpall EJ, Crump M, Richardson PG, Schuster MW, Marks LB, Cirrincione C, Norton L, Henderson IC, Schilsky RL, Hurd DD. Prospective, randomized comparison of high-dose chemotherapy with stem-cell support versus intermediate-dose chemotherapy after surgery and adjuvant chemotherapy in women with high-risk primary breast cancer: a report of CALGB 9082, SWOG 9114, and NCIC MA-13. J Clin Oncol. 2005 Apr 1;23(10):2191-200. doi: 10.1200/JCO.2005.10.202. Epub 2005 Mar 14.
PubMed 15767638
Frei E 3rd, Elias A, Wheeler C, Richardson P, Hryniuk W. The relationship between high-dose treatment and combination chemotherapy: the concept of summation dose intensity. Clin Cancer Res. 1998 Sep;4(9):2027-37.
PubMed 9748116
Rashid MBMA, Toh TB, Hooi L, Silva A, Zhang Y, Tan PF, Teh AL, Karnani N, Jha S, Ho CM, Chng WJ, Ho D, Chow EK. Optimizing drug combinations against multiple myeloma using a quadratic phenotypic optimization platform (QPOP). Sci Transl Med. 2018 Aug 8;10(453):eaan0941. doi: 10.1126/scitranslmed.aan0941.
PubMed 30089632
de Lima M, Giralt S, Thall PF, de Padua Silva L, Jones RB, Komanduri K, Braun TM, Nguyen HQ, Champlin R, Garcia-Manero G. Maintenance therapy with low-dose azacitidine after allogeneic hematopoietic stem cell transplantation for recurrent acute myelogenous leukemia or myelodysplastic syndrome: a dose and schedule finding study. Cancer. 2010 Dec 1;116(23):5420-31. doi: 10.1002/cncr.25500. Epub 2010 Jul 29.
PubMed 20672358
Jabbour E, Giralt S, Kantarjian H, Garcia-Manero G, Jagasia M, Kebriaei P, de Padua L, Shpall EJ, Champlin R, de Lima M. Low-dose azacitidine after allogeneic stem cell transplantation for acute leukemia. Cancer. 2009 May 1;115(9):1899-905. doi: 10.1002/cncr.24198.
PubMed 19235255
Singal R, Ramachandran K, Gordian E, Quintero C, Zhao W, Reis IM. Phase I/II study of azacitidine, docetaxel, and prednisone in patients with metastatic castration-resistant prostate cancer previously treated with docetaxel-based therapy. Clin Genitourin Cancer. 2015 Feb;13(1):22-31. doi: 10.1016/j.clgc.2014.07.008. Epub 2014 Aug 1.
PubMed 25178642
Cohen AL, Ray A, Van Brocklin M, Burnett DM, Bowen RC, Dyess DL, Butler TW, Dumlao T, Khong HT. A phase I trial of azacitidine and nanoparticle albumin bound paclitaxel in patients with advanced or metastatic solid tumors. Oncotarget. 2016 Dec 26;8(32):52413-52419. doi: 10.18632/oncotarget.14183. eCollection 2017 Aug 8.
PubMed 28881739
Lee V, Wang J, Zahurak M, Gootjes E, Verheul HM, Parkinson R, Kerner Z, Sharma A, Rosner G, De Jesus-Acosta A, Laheru D, Le DT, Oganesian A, Lilly E, Brown T, Jones P, Baylin S, Ahuja N, Azad N. A Phase I Trial of a Guadecitabine (SGI-110) and Irinotecan in Metastatic Colorectal Cancer Patients Previously Exposed to Irinotecan. Clin Cancer Res. 2018 Dec 15;24(24):6160-6167. doi: 10.1158/1078-0432.CCR-18-0421. Epub 2018 Aug 10.
PubMed 30097434
Sharma A, Vatapalli R, Abdelfatah E, Wyatt McMahon K, Kerner Z, A Guzzetta A, Singh J, Zahnow C, B Baylin S, Yerram S, Hu Y, Azad N, Ahuja N. Hypomethylating agents synergize with irinotecan to improve response to chemotherapy in colorectal cancer cells. PLoS One. 2017 Apr 26;12(4):e0176139. doi: 10.1371/journal.pone.0176139. eCollection 2017.
PubMed 28445481
Moro H, Hattori N, Nakamura Y, Kimura K, Imai T, Maeda M, Yashiro M, Ushijima T. Epigenetic priming sensitizes gastric cancer cells to irinotecan and cisplatin by restoring multiple pathways. Gastric Cancer. 2020 Jan;23(1):105-115. doi: 10.1007/s10120-019-01010-1. Epub 2019 Sep 25.
PubMed 31555951
Li LH, Olin EJ, Buskirk HH, Reineke LM. Cytotoxicity and mode of action of 5-azacytidine on L1210 leukemia. Cancer Res. 1970 Nov;30(11):2760-9. No abstract available.
PubMed 5487063

Interested in taking part?

Wei Peng Yong

6779 5555

Wei_Peng_Yong@nuhs.edu.sg

Talk to your doctor first and take this page with you. Only the study team can confirm whether you can join.

Questions to ask the study team

What is the study trying to find out?
What would I need to do, and how often would I visit?
Could I receive a placebo instead of the treatment?
What are the possible risks and benefits for me?
Will it cost me anything? Are travel or time paid for?
Can I keep seeing my own doctor during the study?
What happens when the study ends?

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Study at a glance

From the registry record, last updated by the sponsor on 23 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.

Official title: Optimizing and Personalising Azacitidine Combination Therapy for Treating Solid Tumours Using the Quadratic Phenotypic Optimization Platform (QPOP) and an Artificial Intelligence-based Platform (CURATE.AI)
ClinicalTrials.gov ID: NCT05381038
Acronym / sponsor ID: 2021/01159
Conditions: Solid Tumor, Gastrointestinal Cancer, Breast Cancer
Keywords: QPOP, Cancer, Artificial Intelligence, CURATE.AI, Chemotherapy, Azacitidine, docetaxel, paclitaxel
Phase: Phase 1/2
Study type: Interventional
Recruitment status: Recruiting
Enrolment: 10 participants (estimated)
Lead sponsor: National University Hospital, SingaporeUniversity, hospital or other
Collaborators: The N.1 Institute for Health (N.1), Cancer Science Institute of Singapore
Study start: 13 Feb 2023 (actual)
Primary completion: 4 Oct 2026 (estimated)
Study completion: 4 Apr 2027 (estimated)
First posted: 19 May 2022 (actual)
Results: Not posted in the source record

Clinical summary

The research question as the sponsor registered it. This describes what the study plans to test, not what it found.

Detailed description

In this pilot feasibility study, participants will undergo QPOP drug selection, a stage of CURATE.AI profile generation, and a stage of CURATE.AI profile-based, efficacy-driven drug dosing.

Study design

Primary purpose: Treatment
Allocation: Not applicable
Intervention model: Sequential
Masking: None (open label)
Number of arms: 1
Model description: 10 participants diagnosed with breast or gastric cancer undergoing or planned for treatment will be enrolled. The participants will undergo QPOP drug selection optimisation, and those participants who are identified via QPOP to potentially benefit from azacitidine in combination with docetaxel, paclitaxel or irinotecan will transition to the CURATE.AI dose modulation phase of the trial. Only azacitidine dose in the selected azacitidine combination will be modulated by CURATE.AI

Arm	Type	Receives
QPOP + CURATE.AI	Experimental	Device: QPOP, Device: CURATE.AI, Drug: Azacitidine + docetaxel, Drug: Azacitidine + paclitaxel, Drug: Azacitidine + irinotecanParticipants will undergo two study stages: QPOP drug selection and CURATE.AI-guided dosing modulation. In the QPOP drug selection stage, participants will undergo a baseline biopsy for organoid generation and subsequently receive treatment as per SOC. During this time, QPOP will identify optimal drug combinations for the participant based on ex vivo experiments on the participant's organoid. Participants who are identified via QPOP to potentially benefit from azacitidine in combination therapy (azacitidine + docetaxel, azacitidine + paclitaxel or azacitidine + irinotecan) will move on to the CURATE.AI-guided dosing modulation stage with treatment with azacitidine. Azacitidine treatment will begin once disease progression after SOC treatment is determined based on CT scans. Only azacitidine dose in the selected azacitidine combination will be modulated by CURATE.AI

Who may qualify

Ages: 21 to 99 years
Sex: All
Healthy volunteers: Not accepted
Age groups: Adult, Older adult

Key inclusion criteria (9 listed)

Males and females ≥ 21 years of age.
Eastern Cooperative Oncology Group (ECOG) Performance Status of 0 to 2.
Patients must meet the following clinical laboratory criteria within 21 days of starting treatment:
Diagnosed with breast or gastric cancer, where docetaxel, paclitaxel or irinotecan is indicated for palliative therapy.
Patients who have undergone QPOP drug screen (e.g. under QGAIN (2019/00924) or NGAIN trial (2021/00009) where the drug screen indicated potential benefit of combining azacitidine with taxane or irinotecan.

Key exclusion criteria (8 listed)

Patients who are lactating or pregnant.
Patients with clinically significant hypersensitivity to one or more of the selected regimen's constituent drug(s) (e.g. patients with clinically significant hypersensitivity to irinotecan may not be enrolled on azacitidine + irinotecan, but may be allowed on azacitidine + paclitaxel or azacitidine + docetaxel).
Contraindication to any of the required concomitant drugs or supportive treatments.
Any clinically significant medical disease or psychiatric condition that, in the co-investigator's opinion, may interfere with protocol adherence or a subject's ability to give informed consent.
Major surgery within 28 days prior to start of the treatment.

Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.

Interventions

Intervention	Type	Arms
QPOPQPOP 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	QPOP + CURATE.AI
CURATE.AICURATE.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.	Device	QPOP + CURATE.AI
Azacitidine + docetaxelAzacitidine 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	QPOP + CURATE.AI
Azacitidine + paclitaxelAzacitidine 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	QPOP + CURATE.AI
Azacitidine + irinotecanAzacitidine 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.	Drug	QPOP + CURATE.AI

Primary outcome

QPOP applicability: percentage of participants with successful application of QPOP drug selection.
Time frame: up to 18 months
A decision on whether we "successfully apply" the QPOP drug selection requires expert judgement and cannot be made based on a purely numerical process. The expert panel will consider the following factors with careful regard for the individual circumstances of each participant: 1. The goodness-of-fit of the QPOP derived equation is acceptable to allow for a reliable list of effective drug combinations; 2. The drugs list is generated sufficiently early for the participant to potentially benefit
CURATE.AI applicability: percentage of participants in whom the investigators successfully apply CURATE.AI profile.
Time frame: up to 18 months
A decision on whether we "successfully apply" the CURATE.AI profile requires expert judgement and cannot be made based on a purely numerical process. The expert panel will consider the following factors with careful regard for the individual circumstances of each participant: 1. Error/variance (biological/analytical) is sufficiently small to allow accurate predictions; 2. Profile can be generated sufficiently early for the participant to potentially benefit; 3. Dose-dependent relationship is observed; 4. Profile is actionable (i.e. fulfils the co-investigator's pre-specified safety requirements); 5. Systemic changes in the participant which require profile recalibration are rare or readily assimilated into the CURATE.AI algorithm.

6 secondary outcomes

Physician adherence: percentage of QPOP recommended drug combinations that were used by the co-investigator.
Time frame: up to 18 months
Patient adherence: percentage of participants who always adhered to the prescribed dose whenever they took their medication, as measured by the standardised pharmacovigilance protocol.
Time frame: up to 18 months
Timely delivery of CURATE.AI recommendations to the clinician: percentage of CURATE.AI recommendations provided in time for the next chemotherapy cycle, across all participants and cycles.
Time frame: up to 18 months
CURATE.AI relevance: percentage of dosing events across all participants and cycles in which CURATE.AI recommendation is considered in the clinical decision-making process
Time frame: up to 18 months
Physician adherence: percentage of CURATE.AI recommended doses that were used by the co-investigator.
Time frame: up to 18 months
Clinically significant dose changes
Time frame: up to 18 months

Results and safety

This study is still under way. Results are not available in the source record yet.

Research links

Official record on ClinicalTrials.govLast updated by the sponsor 23 Sep 2025.
Background: PubMed 22810586Rozenblatt-Rosen O, Deo RC, Padi M, Adelmant G, Calderwood MA, Rolland T, Grace M, Dricot A, Askenazi M, Tavares M, Pevzner SJ, Abderazzaq F, Byrdsong D, Carvunis AR, Chen AA, Cheng J, Correll M, Duarte M, Fan C, Feltkamp MC, Ficarro SB, Franchi R, Garg BK, Gulbahce N, Hao T, Holthaus AM, James R, Korkhin A, Litovchick L, Mar JC, Pak TR, Rabello S, Rubio R, Shen Y, Singh S, Spangle JM, Tasan M, Wanamaker S, Webber JT, Roecklein-Canfield J, Johannsen E, Barabasi AL, Beroukhim R, Kieff E, Cusick ME, Hill DE, Munger K, Marto JA, Quackenbush J, Roth FP, DeCaprio JA, Vidal M. Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins. Nature. 2012 Jul 26;487(7408):491-5. doi: 10.1038/nature11288.
Background: PubMed 22576208Chandarlapaty S. Negative feedback and adaptive resistance to the targeted therapy of cancer. Cancer Discov. 2012 Apr;2(4):311-9. doi: 10.1158/2159-8290.CD-12-0018. Epub 2012 Mar 22.
Background: PubMed 22474259Logue JS, Morrison DK. Complexity in the signaling network: insights from the use of targeted inhibitors in cancer therapy. Genes Dev. 2012 Apr 1;26(7):641-50. doi: 10.1101/gad.186965.112.
Background: PubMed 3510732Norton L, Simon R. The Norton-Simon hypothesis revisited. Cancer Treat Rep. 1986 Jan;70(1):163-9. No abstract available.
Background: PubMed 15767638Peters WP, Rosner GL, Vredenburgh JJ, Shpall EJ, Crump M, Richardson PG, Schuster MW, Marks LB, Cirrincione C, Norton L, Henderson IC, Schilsky RL, Hurd DD. Prospective, randomized comparison of high-dose chemotherapy with stem-cell support versus intermediate-dose chemotherapy after surgery and adjuvant chemotherapy in women with high-risk primary breast cancer: a report of CALGB 9082, SWOG 9114, and NCIC MA-13. J Clin Oncol. 2005 Apr 1;23(10):2191-200. doi: 10.1200/JCO.2005.10.202. Epub 2005 Mar 14.
Background: PubMed 9748116Frei E 3rd, Elias A, Wheeler C, Richardson P, Hryniuk W. The relationship between high-dose treatment and combination chemotherapy: the concept of summation dose intensity. Clin Cancer Res. 1998 Sep;4(9):2027-37.
Background: PubMed 30089632Rashid MBMA, Toh TB, Hooi L, Silva A, Zhang Y, Tan PF, Teh AL, Karnani N, Jha S, Ho CM, Chng WJ, Ho D, Chow EK. Optimizing drug combinations against multiple myeloma using a quadratic phenotypic optimization platform (QPOP). Sci Transl Med. 2018 Aug 8;10(453):eaan0941. doi: 10.1126/scitranslmed.aan0941.
Background: PubMed 20672358de Lima M, Giralt S, Thall PF, de Padua Silva L, Jones RB, Komanduri K, Braun TM, Nguyen HQ, Champlin R, Garcia-Manero G. Maintenance therapy with low-dose azacitidine after allogeneic hematopoietic stem cell transplantation for recurrent acute myelogenous leukemia or myelodysplastic syndrome: a dose and schedule finding study. Cancer. 2010 Dec 1;116(23):5420-31. doi: 10.1002/cncr.25500. Epub 2010 Jul 29.
Background: PubMed 19235255Jabbour E, Giralt S, Kantarjian H, Garcia-Manero G, Jagasia M, Kebriaei P, de Padua L, Shpall EJ, Champlin R, de Lima M. Low-dose azacitidine after allogeneic stem cell transplantation for acute leukemia. Cancer. 2009 May 1;115(9):1899-905. doi: 10.1002/cncr.24198.
Background: PubMed 25178642Singal R, Ramachandran K, Gordian E, Quintero C, Zhao W, Reis IM. Phase I/II study of azacitidine, docetaxel, and prednisone in patients with metastatic castration-resistant prostate cancer previously treated with docetaxel-based therapy. Clin Genitourin Cancer. 2015 Feb;13(1):22-31. doi: 10.1016/j.clgc.2014.07.008. Epub 2014 Aug 1.
Background: PubMed 28881739Cohen AL, Ray A, Van Brocklin M, Burnett DM, Bowen RC, Dyess DL, Butler TW, Dumlao T, Khong HT. A phase I trial of azacitidine and nanoparticle albumin bound paclitaxel in patients with advanced or metastatic solid tumors. Oncotarget. 2016 Dec 26;8(32):52413-52419. doi: 10.18632/oncotarget.14183. eCollection 2017 Aug 8.
Background: PubMed 30097434Lee V, Wang J, Zahurak M, Gootjes E, Verheul HM, Parkinson R, Kerner Z, Sharma A, Rosner G, De Jesus-Acosta A, Laheru D, Le DT, Oganesian A, Lilly E, Brown T, Jones P, Baylin S, Ahuja N, Azad N. A Phase I Trial of a Guadecitabine (SGI-110) and Irinotecan in Metastatic Colorectal Cancer Patients Previously Exposed to Irinotecan. Clin Cancer Res. 2018 Dec 15;24(24):6160-6167. doi: 10.1158/1078-0432.CCR-18-0421. Epub 2018 Aug 10.
Individual participant dataSharing planned: No

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Referral and contact

AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.

Wei Peng Yong contact

6779 5555

Wei_Peng_Yong@nuhs.edu.sg

Wei Peng Yong principal investigator

National University Hospital, Singapore

1 site in 1 country: see every site and its status.

Questions about this trial

What is this clinical trial studying?

A Phase 1/2 study testing QPOP, CURATE.AI and Azacitidine + docetaxel in people with Solid Tumor and Gastrointestinal Cancer, run by National University Hospital, Singapore at 1 site in Singapore.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 9 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: looking for participants now, as of the sponsor's last update on 23 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

What does this combined phase mean?

Phase 1 studies test a treatment in a small group of people for the first time or in a new way, mainly to check safety and find the right dose.

Phase 2 studies give the treatment to a larger group to see whether it has the intended effect and to keep checking safety.

Not every study follows the same path, and some studies (observational studies, device studies) have no phase.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Wei Peng Yong (6779 5555, Wei_Peng_Yong@nuhs.edu.sg), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

QPOP applicability: percentage of participants with successful application of QPOP drug selection. (time frame: up to 18 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT05381038, which also lists 15 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Sep 2025.