Advanced Solid TumorsPhase 4SINGULARITYNCT06824792
Optimal Standard Treatment Selection for Solid Tumor Patients by Biologically-informed Multi-agent System
A Phase 4 study testing Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE. in people with Advanced Solid Tumors, run by NING LI at 1 site in China.
Trial summary
This study is an exploratory cohort study conducted under real-world conditions, aiming to evaluate the feasibility of an artificial intelligence (AI)-guided standard treatment selection model for advanced solid tumors, as well as its superiority compared to clinician-selected treatment plans. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Advanced Solid Tumors
- What is being tested?
- Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE.
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 3,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Mar 2025to 28 Feb 2030
- Phase
- Phase 4
- 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Voluntarily participate in the clinical study, fully understand and be informed about the study, sign the informed consent form, and be willing and able to comply with and complete all trial procedures.
- Aged ≥18 years, no gender restrictions.
- Patients with advanced or metastatic malignant tumors confirmed by histology or cytology.
- Able to provide tumor tissue and peripheral blood samples for multi-omics testing, or able to provide qualified whole-exome sequencing and transcriptomics data.
Who cannot join
- As assessed by the investigator, no standard treatment is available, or the patient is unsuitable for guideline-recommended anti-tumor therapies.
- Other conditions deemed unsuitable for participation in this study by the investigator.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site
Cancer Institute and Hospital, Chinese Academy of Medical Sciences (Langfang Branch)
Langfang, Hebei
Ning LI, M.D., +86 (010) 8778 8165, lining@cicams.ac.cn
Yale JIANG, M.D., +86 (010) 8778 8165, yalejiang@cicams.ac.cn
About this study
Official title: Real-world Study to Investigate Optimal Standard Treatment Selection for Solid Tumor Patients by Guided by Biologically-informed Multi-agent System
This study is an exploratory cohort study conducted under real-world conditions, aiming to evaluate the feasibility of an artificial intelligence (AI)-guided standard treatment selection model for advanced solid tumors, as well as its superiority compared to clinician-selected treatment plans. A multi-agent system based on multimodal AI models will rank the priority of standard treatment options based on the personalized information of the patients, including including demographics, clinical information, and multi-omics data. The final treatment plan will be jointly selected by the patient and the clinician from the AI-recommended options, thereby delivering a personalized treatment.
Read the detailed description
This study is an exploratory cohort study conducted under real-world conditions, aiming to evaluate the feasibility of an artificial intelligence (AI)-guided standard treatment selection model for advanced solid tumors, as well as its superiority compared to clinician-selected treatment plans. The study will prospectively collect patient data of multiple dimensions, including demographics, clinical information (pathological classification, tumor staging, imaging findings, previous treatment regimens and their effectiveness, performance status scores), and multi-omics data (DNA gene panel testing, whole-exome sequencing, transcriptome sequencing, etc.). A multi-agent system based on multimodal AI models will rank the priority of standard treatment options based on the personalized information of the patients. The final treatment plan will be jointly selected by the patient and the clinician from the AI-recommended options, thereby delivering a personalized treatment.
- Conditions
- Advanced Solid Tumors
- Being tested
- Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE.
- Keywords
- Artificial Intelligence, Real World Study, Advanced Solid Tumors, Standard Treatment, Multi-omics
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE.Drug
Also called KEYTRUDA et al.
Quasar is a biologically-informed multi-agent system developed based on multi-omics and multi-modal data. By integrating multidimensional information such as patients' demographic, clinical, and omics data (including DNA genotyping, whole-exome sequencing, transcriptome sequencing, etc.), it prioritizes standard treatment plans and recommends the optimal personalized treatment plan. Including targeted drugs, chemotherapy, immunotherapy approved by China CDE.
| Study group | Role | What they receive |
|---|---|---|
| Quasar | Experimental | This arm involves the prospective collection of individual patient data, including demographic information, clinical details (such as pathological classification, tumor staging, imaging findings, prior treatments and their efficacy, and performance status scores), and multi-omics data (DNA gene panel testing, whole-exome sequencing, and transcriptome sequencing). An artificial intelligence model (namely, Quasar) integrates this multidimensional information to prioritize standard treatment options and identify the optimal personalized treatment plan for each patient. Based on the AI-recommended treatment list, the final treatment plan is jointly selected by the patient and the physician. If treatment adjustments are required due to tumor progression, intolerance, or other reasons, the AI model will generate a new optimal treatment plan based on updated patient characteristics. This iterative process continues until the patient withdraws from the study. Receives: Drug: Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Progression-free survival (PFS)
Defined as the time from enrollment to documented disease progression per RECIST 1.1 or death due to any cause, whichever occurs first.
Measured: Every 6 weeks, up to 2 years since enrollment
Secondary outcomes (6)
Overall response rate (ORR)
Defined as the proportion of cases showing the best response of complete response (CR) or partial response (PR) (i.e., CR+PR) per RECIST 1.1 (based on CT, MRI or PET-CT), during the period from the start of the investigational drug to withdrawal from the trial.
Measured: Every 6 weeks, up to 2 years since enrollment
Duration of response (DoR)
Defined as the time from the first documented response, i.e. CR or PR, per RECIST 1.1, to disease progression or death from any cause, whichever occurs first.
Measured: Every 6 weeks, up to 2 years since enrollment
Time to treatment failure (TTF)
Defined as the time from the start of enrollment to the termination of treatment for any reason, including disease progression per RECIST 1.1, treatment toxicity, or death.
Measured: Every 6 weeks, up to 2 years since enrollment
Time to progression (TTP)
Defined as the time from enrollment to the occurrence of objective tumor progression per RECIST 1.1, excluding death.
Measured: Every 6 weeks, up to 2 years since enrollment
Best of response (BoR)
Defined as the best therapeutic effect recorded from the start of treatment until disease progression or recurrence, per RECIST 1.1.
Measured: Every 6 weeks, up to 2 years since enrollment
Treatment-emergent adverse events (TEAE)
Defined as adverse events that emerge or worsen in severity following the initiation of intervention, per CTCAE 5.0.
Measured: Every 6 weeks, up to 2 years since enrollment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Feb 2025
- Study start1 Mar 2025 (estimated)
- Primary completion29 Feb 2028 (estimated)
- Study completion28 Feb 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Advanced Solid TumorsStudies 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 4
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- NING LI
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, NING LI, Cancer Institute and Hospital, Chinese Academy of Medical Sciences
- Investigators
- Shuhang Wang, PhD, Study director, National Cancer Center of China
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06824792
- Sponsor's protocol ID
- SINGULARITY-001
- Acronym
- SINGULARITY
- Status last verified
- Feb 2025
- First submitted
- 7 Feb 2025
- Last updated
- 13 Feb 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- Yes
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Real-world Study to Investigate Optimal Standard Treatment Selection for Solid Tumor Patients by Guided by Biologically-informed Multi-agent System
- ClinicalTrials.gov ID
- NCT06824792
- Acronym / sponsor ID
- SINGULARITY / SINGULARITY-001
- Conditions
- Advanced Solid Tumors
- Keywords
- Artificial Intelligence, Real World Study, Advanced Solid Tumors, Standard Treatment, Multi-omics
- Phase
- Phase 4
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- NING LIUniversity, hospital or other
- Study start
- 1 Mar 2025 (estimated)
- Primary completion
- 29 Feb 2028 (estimated)
- Study completion
- 28 Feb 2030 (estimated)
- First posted
- 13 Feb 2025 (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.
This study is an exploratory cohort study conducted under real-world conditions, aiming to evaluate the feasibility of an artificial intelligence (AI)-guided standard treatment selection model for advanced solid tumors, as well as its superiority compared to clinician-selected treatment plans. A multi-agent system based on multimodal AI models will rank the priority of standard treatment options based on the personalized information of the patients, including including demographics, clinical information, and multi-omics data. The final treatment plan will be jointly selected by the patient and the clinician from the AI-recommended options, thereby delivering a personalized treatment.
Detailed description
This study is an exploratory cohort study conducted under real-world conditions, aiming to evaluate the feasibility of an artificial intelligence (AI)-guided standard treatment selection model for advanced solid tumors, as well as its superiority compared to clinician-selected treatment plans. The study will prospectively collect patient data of multiple dimensions, including demographics, clinical information (pathological classification, tumor staging, imaging findings, previous treatment regimens and their effectiveness, performance status scores), and multi-omics data (DNA gene panel testing, whole-exome sequencing, transcriptome sequencing, etc.). A multi-agent system based on multimodal AI models will rank the priority of standard treatment options based on the personalized information of the patients. The final treatment plan will be jointly selected by the patient and the clinician from the AI-recommended options, thereby delivering a personalized treatment.
Study design
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Quasar | Experimental | Drug: Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE.This arm involves the prospective collection of individual patient data, including demographic information, clinical details (such as pathological classification, tumor staging, imaging findings, prior treatments and their efficacy, and performance status scores), and multi-omics data (DNA gene panel testing, whole-exome sequencing, and transcriptome sequencing). An artificial intelligence model (namely, Quasar) integrates this multidimensional information to prioritize standard treatment options and identify the optimal personalized treatment plan for each patient. Based on the AI-recommended treatment list, the final treatment plan is jointly selected by the patient and the physician. If treatment adjustments are required due to tumor progression, intolerance, or other reasons, the AI model will generate a new optimal treatment plan based on updated patient characteristics. This iterative process continues until the patient withdraws from the study. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Voluntarily participate in the clinical study, fully understand and be informed about the study, sign the informed consent form, and be willing and able to comply with and complete all trial procedures.
- Aged ≥18 years, no gender restrictions.
- Patients with advanced or metastatic malignant tumors confirmed by histology or cytology.
- Able to provide tumor tissue and peripheral blood samples for multi-omics testing, or able to provide qualified whole-exome sequencing and transcriptomics data.
Key exclusion criteria (2 listed)
- As assessed by the investigator, no standard treatment is available, or the patient is unsuitable for guideline-recommended anti-tumor therapies.
- Other conditions deemed unsuitable for participation in this study by the investigator.
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 |
|---|---|---|
| Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE.Also: KEYTRUDA et al.Quasar is a biologically-informed multi-agent system developed based on multi-omics and multi-modal data. By integrating multidimensional information such as patients' demographic, clinical, and omics data (including DNA genotyping, whole-exome sequencing, transcriptome sequencing, etc.), it prioritizes standard treatment plans and recommends the optimal personalized treatment plan. Including targeted drugs, chemotherapy, immunotherapy approved by China CDE. | Drug | Quasar |
Primary outcome
Progression-free survival (PFS)
Time frame: Every 6 weeks, up to 2 years since enrollment
Defined as the time from enrollment to documented disease progression per RECIST 1.1 or death due to any cause, whichever occurs first.
6 secondary outcomes
Overall response rate (ORR)
Time frame: Every 6 weeks, up to 2 years since enrollment
Duration of response (DoR)
Time frame: Every 6 weeks, up to 2 years since enrollment
Time to treatment failure (TTF)
Time frame: Every 6 weeks, up to 2 years since enrollment
Time to progression (TTP)
Time frame: Every 6 weeks, up to 2 years since enrollment
Best of response (BoR)
Time frame: Every 6 weeks, up to 2 years since enrollment
Treatment-emergent adverse events (TEAE)
Time frame: Every 6 weeks, up to 2 years since enrollment
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 13 Feb 2025.
- 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.
Shuhang Wang, PhD study director
National Cancer Center of China
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A Phase 4 study testing Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE. in people with Advanced Solid Tumors, run by NING LI at 1 site in China.
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 4 inclusion and 2 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: opening soon, as of the sponsor's last update on 13 Feb 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 China. 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 phase mean?
Phase 4 studies take place after a treatment is approved, to learn more about its long-term benefits and risks in everyday use.
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 Ning LI, M.D. (+86 (010) 8778-8165, lining@cicams.ac.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Progression-free survival (PFS) (time frame: Every 6 weeks, up to 2 years since enrollment). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 13 Feb 2025.