AI-Assisted Analgesia Copilot System
Recruiting now
Conditions studied: Nociception, Artificial Intelligence (AI), Target Controlled Infusion (TCI), Remifentanil Consumption
In brief
The primary objective of the SEASCAPE project is to design, develop, and to apply a clinical implementation tool of a machine learning (ML) and artificial intelligence (AI)-based co-pilot system for the real-time monitoring and control of nociception during general anesthesia (GA). The ultimate clinical purpose is to optimize individualized pain management by achieving precise titration of intravenous opioids (specifically remifentanil), thereby minimizing the incidence of over- and under-dosing. This optimization is projected to enhance patient outcomes, reduce opioid-related complications, and improve overall cost-effectiveness of anesthetic procedures. The main scientific question guiding this work is: Can a novel algorithm be generated and validated to provide superior analytical precision for analgesic management by reliably differentiating genuine nociceptive responses from confounding physiological variables-such as inadequate neuromuscular blockade or changes in depth of anesthesia-thereby significantly improving the clinical decision-making framework for intraoperative nociception control? This project addresses the recognized challenge in anesthesiology: defining an objective measure to quantify nociception and antinociception during GA. Study Population: Patients scheduled for elective surgical procedures requiring general anesthesia (GA). Existing Intervention: The standard anesthetic regimen includes continuous intravenous infusion of the remifentanil for intraoperative analgesia, typically governed by a Target Controlled Infusion (TCI) system utilizing a pharmacokinetic/pharmacodynamic (PK/PD) model (Eleveld TCI model). Project Focus: The research seeks to improve the accuracy and efficacy of this existing analgesic strategy by integrating a multivariate patient data stream with the newly developed SEASCAPE co-pilot AI. This aims to refine the remifentanil dose predictions beyond the current TCI model's capabilities, personalized system.
Key facts
- Study ID
- NCT07253012
- Run by
- Pontificia Universidad Catolica de Chile
- People needed
- 150
- Starts
- 2026-01-29
- Expected to finish
- 2027-10-27
- Last updated by the study team
- 2026-03-09
Who can join
Age: any. Sex: any. Healthy volunteers: not accepted.
You may qualify if…
- Patients scheduled for elective surgery with general anesthesia.
- Surgeries scheduled to last at least two hours.
You may not qualify if…
- Patients undergoing emergency surgery.
- Pregnant women.
- Presence of a mental or intellectual disability before the hospitalization.
- Drug dependence.
- Surgeries scheduled for more than 4 hours.
- Intraoperative complications requiring changes in routine behavior.
Where it is running
- Hospital Clinico UC Christus — Santiago, Chile (enrolling)
- Division de Anestesiologia — Santiago, Chile
Full record on ClinicalTrials.gov
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