Advanced Solid Tumors
Conditions
Keywords
Artificial Intelligence, Real World Study, Advanced Solid Tumors, Standard Treatment, Multi-omics
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.
Interventions
DRUGBiologically-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.
Sponsors
NING LI
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Progression-free survival (PFS) | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Duration of response (DoR) | Every 6 weeks, up to 2 years since enrollment | 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. |
| Time to treatment failure (TTF) | Every 6 weeks, up to 2 years since enrollment | 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. |
| Overall response rate (ORR) | Every 6 weeks, up to 2 years since enrollment | 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. |
| Best of response (BoR) | Every 6 weeks, up to 2 years since enrollment | Defined as the best therapeutic effect recorded from the start of treatment until disease progression or recurrence, per RECIST 1.1. |
| Treatment-emergent adverse events (TEAE) | Every 6 weeks, up to 2 years since enrollment | Defined as adverse events that emerge or worsen in severity following the initiation of intervention, per CTCAE 5.0. |
| Time to progression (TTP) | Every 6 weeks, up to 2 years since enrollment | Defined as the time from enrollment to the occurrence of objective tumor progression per RECIST 1.1, excluding death. |
Countries
China
Contacts
Primary ContactNing LI, M.D.
Backup ContactYale JIANG, M.D.
Outcome results
None listed