Optimal Standard Treatment Selection for Solid Tumor Patients by Biologically-informed Multi-agent System

NCT ID: NCT06824792

Last Updated: 2025-02-13

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: PHASE4
• Total Enrollment: 3000 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-03-01
• Study Completion Date: 2030-02-28

Brief 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. 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.

Conditions

Advanced Solid Tumors

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

Quasar

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.

Group Type: EXPERIMENTAL

Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE.

Intervention Type: DRUG

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.

Interventions

Biologically-informed multi-agent system (Quasar) including targeted drugs Osimertinib, chemotherapy pemetrexed, immunotherapy pembrolizumab et al. approved by China CDE.

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.

Intervention Type: DRUG

Other Intervention Names

KEYTRUDA et al.

Eligibility Criteria

Inclusion Criteria

• 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.

Exclusion Criteria

• 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.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

NING LI

OTHER

Sponsor Role: lead

Responsible Party

NING LI

Vice Director of Cancer Institute and Hospital, Chinese Academy of Medical Sciences

Responsibility Role: SPONSOR_INVESTIGATOR

Principal Investigators

Shuhang Wang, PhD

Role: STUDY_DIRECTOR

National Cancer Center of China

Locations

Cancer Institute and Hospital, Chinese Academy of Medical Sciences (Langfang Branch)

Langfang, Hebei, China

Countries

China

Central Contacts

Ning LI, M.D.

Role: CONTACT

lining@cicams.ac.cn

+86 (010) 8778-8165

Yale JIANG, M.D.

Role: CONTACT

yalejiang@cicams.ac.cn

+86 (010) 8778-8713

Facility Contacts

Ning LI, M.D.

Role: primary

lining@cicams.ac.cn

+86 (010) 8778 8165

Yale JIANG, M.D.

Role: backup

yalejiang@cicams.ac.cn

+86 (010) 8778 8165

Other Identifiers

SINGULARITY-001

Identifier Type: -

Identifier Source: org_study_id