NCT07515118

AI-TOP Study Artificial Intelligence for Trigger Optimization.

An Artificial Intelligence Based Approach for Selecting the Optimal Day for Triggering.

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 644 (estimated)
• Sponsor: Fundacion Dexeus · Academic / Other
• Sex: Female
• Age: 18 Years – 42 Years
• Healthy volunteers: Not accepted

Summary

To evaluate, in a randomized controlled trial, whether AI-guided monitoring and ovulation triggering leads to clinical outcomes comparable to those achieved through physician-led decision-making in patients undergoing ovarian stimulation for IVF.

Detailed description

Assisted Reproductive Technology is undergoing a major transformation with the introduction of artificial intelligence (AI), which is reshaping how medical treatments are carried out. In IVF, one of the persistent challenges has been maximizing the number of oocytes retrieved while efficiently managing clinical workload-particularly by reducing weekend procedures-without compromising outcomes. Although a patient's response may vary between cycles, evidence shows that adjusting the trigger day by one day does not significantly affect clinical results, enabling more flexible scheduling. AI enables a shift from standardized protocols to personalized treatments, improving clinical outcomes, streamlining processes and enhancing operational efficiency. Recent research shows that AI-based models can optimize ovarian stimulation, improve trigger-day selection, and increase the number of fertilized oocytes compared to decisions made solely by physicians. AI algorithms have also accurately predicted the number of oocytes retrieved, contributing to more effective protocols and higher live birth rates. Beyond trigger timing, AI has been shown to improve workflow efficiency in IVF clinics by optimizing monitoring schedules and balancing clinical workload without negatively affecting cycle outcomes. Based on this growing evidence, a randomized controlled trial was designed to compare clinical outcomes of controlled ovarian stimulation when trigger and retrieval decisions are made solely by the physician versus when the physician is assisted by AI guidance.

Conditions

• Infertility
• Ovarian Stimulation
• Artificial Intelligence

Interventions

Type	Name	Description
DEVICE	STIMAI®.	The AI algorithm used in this study is STIMAI®. STIMAI® is an artificial intelligence-based software that assists clinicians by providing data-driven insights to optimize the fertility treatment process and support conception. The software is designed as a clinical decision support tool and does not replace the physician's judgment; final clinical decisions will remain under the responsibility of the treating physician The physician will consult the AI application, which predicts the number of MII oocytes for different trigger days. If the algorithm recommends triggering today or tomorrow, the physician will choose which option to follow.
OTHER	Routine clinical management	As soon as 2-3 follicles of 17 mm are detected, the physician will determine the timing of ovulation triggering based on clinical judgment.

Timeline

• Start date: 2026-04-01
• Primary completion: 2027-04-01
• Completion: 2027-09-01
• First posted: 2026-04-07
• Last updated: 2026-04-07

Locations

5 sites across 1 country: Spain