Adverse Drug ReactionsNCT07808866
Multi-Agent Collaborative ADR Prediction With Human-Machine Decision Comparison
An observational study of Adverse Drug Reactions and Clinical Decision Support, run by Peking University Third Hospital at 2 sites in China.
Trial summary
This study develops a multi-agent collaborative prediction model to forecast adverse drug reactions using real-world clinical medical records. It validates model performance via evidence-based data and compares decision outputs between the AI model and clinical physicians, aiming to improve early identification of… Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Adverse Drug Reactions, Clinical Decision Support
- What is being tested?
- Retrospective medical record data analysis only, no clinical intervention
- How many people
- 20,000 participants
- Where
- 2 sitesChina
- Study dates
- 19 Jun 2026to 19 Dec 2027
- Phase
- Observational
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: This study includes two types of research subjects: Retrospective de-identified adverse drug reaction (ADR) medical records: A total of 253 ADR consultation cases covering anti-infectives, cardiovascular agents, anti-tumor drugs, central nervous system drugs and digestive system drugs. Each case contains complete medical history, medication records, ADR occurrence process and clinical outcome data, as well as at least one clinically confirmed definite ADR event. Clinical evaluators: 20 licensed physicians or pharmacists holding intermediate or higher professional titles, with clinical pharmacy practice and regular participation in hospital ADR monitoring and consultation work.
Who may be able to join
- Cases shall involve drug categories including anti-infectives, cardiovascular agents, anti-tumor drugs, central nervous system drugs, digestive system drugs, etc. Each case must contain at least one definite adverse drug reaction (ADR) event, with complete supporting documentation (medical history, medication history, ADR occurrence process, and clinical outcome).
Who cannot join
- Cases with incomplete supporting documentation lacking medical history, medication history, ADR occurrence process or clinical outcome.
- Cases only with suspected or possible ADRs without definite clinical confirmation.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
China2 sites, 2 recruiting
- Recruiting
Peking University Third Hospital
Beijing, Beijing Municipality
Hongmei Jing, Dr., 010-82266782, hongmeijing@bjmu.edu.cn
- Not yet recruiting
Peking University Third Hospital
Beijing
About this study
Official title: Multi-Agent Collaborative Framework for Adverse Drug Reaction Prediction: Evidence-Based Verification and Human-Machine Decision Comparative Study
This study develops a multi-agent collaborative prediction model to forecast adverse drug reactions using real-world clinical medical records. It validates model performance via evidence-based data and compares decision outputs between the AI model and clinical physicians, aiming to improve early identification of drug adverse events. Only de-identified historical medical data will be analyzed; no new clinical interventions will be conducted, with no additional risks to participants.
Read the detailed description
This observational study first retrospectively collects desensitization cases related to adverse drug reactions to construct a predictive model, and then prospectively enrolls patients to evaluate model efficacy and conduct comparative research with expert blind assessment.
- Conditions
- Adverse Drug Reactions, Clinical Decision Support
- Being tested
- Retrospective medical record data analysis only, no clinical intervention
- Medical subject headings
- Drug-Related Side Effects and Adverse Reactions
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Retrospective medical record data analysis only, no clinical interventionOther
This study only analyzes de-identified historical electronic medical record data to build a multi-agent AI prediction model for adverse drug reactions. No drugs, medical devices, or clinical treatment interventions will be applied to any human subjects.
What is being measured
The primary outcome is the main question the study is designed to answer.
Coverage rate of known ADRs
Measured: Up to 8 weeks
Objective question accuracy
Measured: Up to 24 weeks
Concordance rate of predicted unknown ADRs
Measured: Up to 8 weeks
Expert-rated subjective answer quality
Measured: Up to 24 weeks
Secondary outcomes (4)
Subgroup differences in ADR recognition coverage rate
Measured: Up to 24 weeks
Inter-rater consistency
Measured: Up to 24 weeks
Subgroup differences in answer quality score
Measured: Up to 24 weeks
Rater acceptance scale score
Measured: Up to 24 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Sep 2026
- Study start19 Jun 2026
- Primary completion19 Jun 2027 (estimated)
- Study completion19 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Adverse Drug ReactionsStudies 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
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 20,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Peking University Third Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Hongmei Jing, Peking University Third Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07808866
- Sponsor's protocol ID
- LLSC-2026288
- Status last verified
- Jun 2026
- First submitted
- 18 Aug 2026
- Last updated
- 9 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 9 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multi-Agent Collaborative Framework for Adverse Drug Reaction Prediction: Evidence-Based Verification and Human-Machine Decision Comparative Study
- ClinicalTrials.gov ID
- NCT07808866
- Acronym / sponsor ID
- LLSC-2026288
- Conditions
- Adverse Drug Reactions, Clinical Decision Support
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 20,000 participants (estimated)
- Lead sponsor
- Peking University Third HospitalUniversity, hospital or other
- Study start
- 19 Jun 2026 (actual)
- Primary completion
- 19 Jun 2027 (estimated)
- Study completion
- 19 Dec 2027 (estimated)
- First posted
- 9 Sep 2026 (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 develops a multi-agent collaborative prediction model to forecast adverse drug reactions using real-world clinical medical records. It validates model performance via evidence-based data and compares decision outputs between the AI model and clinical physicians, aiming to improve early identification of drug adverse events. Only de-identified historical medical data will be analyzed; no new clinical interventions will be conducted, with no additional risks to participants.
Detailed description
This observational study first retrospectively collects desensitization cases related to adverse drug reactions to construct a predictive model, and then prospectively enrolls patients to evaluate model efficacy and conduct comparative research with expert blind assessment.
Study design
- Observational model
- Other
- Time perspective
- Other
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- This study includes two types of research subjects: Retrospective de-identified adverse drug reaction (ADR) medical records: A total of 253 ADR consultation cases covering anti-infectives, cardiovascular agents, anti-tumor drugs, central nervous system drugs and digestive system drugs. Each case contains complete medical history, medication records, ADR occurrence process and clinical outcome data, as well as at least one clinically confirmed definite ADR event. Clinical evaluators: 20 licensed physicians or pharmacists holding intermediate or higher professional titles, with clinical pharmacy practice and regular participation in hospital ADR monitoring and consultation work.
Key inclusion criteria (1 listed)
- Cases shall involve drug categories including anti-infectives, cardiovascular agents, anti-tumor drugs, central nervous system drugs, digestive system drugs, etc. Each case must contain at least one definite adverse drug reaction (ADR) event, with complete supporting documentation (medical history, medication history, ADR occurrence process, and clinical outcome).
Key exclusion criteria (2 listed)
- Cases with incomplete supporting documentation lacking medical history, medication history, ADR occurrence process or clinical outcome.
- Cases only with suspected or possible ADRs without definite clinical confirmation.
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 |
|---|---|---|
| Retrospective medical record data analysis only, no clinical interventionThis study only analyzes de-identified historical electronic medical record data to build a multi-agent AI prediction model for adverse drug reactions. No drugs, medical devices, or clinical treatment interventions will be applied to any human subjects. | Other | – |
Primary outcome
Coverage rate of known ADRs
Time frame: Up to 8 weeks
Objective question accuracy
Time frame: Up to 24 weeks
Concordance rate of predicted unknown ADRs
Time frame: Up to 8 weeks
Expert-rated subjective answer quality
Time frame: Up to 24 weeks
4 secondary outcomes
Subgroup differences in ADR recognition coverage rate
Time frame: Up to 24 weeks
Inter-rater consistency
Time frame: Up to 24 weeks
Subgroup differences in answer quality score
Time frame: Up to 24 weeks
Rater acceptance scale score
Time frame: Up to 24 weeks
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 9 Sep 2026.
- 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.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Adverse Drug Reactions and Clinical Decision Support, run by Peking University Third Hospital at 2 sites 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 1 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: looking for participants now, as of the sponsor's last update on 9 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites 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.
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 Weilong Zhang (010-82266782, zhangwl2012@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Coverage rate of known ADRs (time frame: Up to 8 weeks). The study lists 4 primary outcomes in all. 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 9 Sep 2026.