Alife study shows promise of AI for IVF decision-making
Alife study shows promise of AI for IVF decision-making
Software has potential to optimise ovarian stimulation process for IVF treatment
A new study has demonstrated the potential of artificial intelligence (AI) in optimising the ovarian stimulation process for IVF treatment.
The multi-centre study analysed ‘Stim Assist™’ software from IVF software start-up Alife, which provides physicians with personalised, data-driven recommendations based on patient-specific characteristics and follicle growth.
This study is the first to prospectively investigate the clinical outcomes of IVF patients when clinicians used AI software to help in determining the optimal starting dose of follicle-stimulating hormone (FSH) and the timing of trigger injection.
"The results of our study are incredibly promising," said Dr. Eric Flisser, one of the lead authors of the study.
"We found a trend towards improved egg yield and a reduction in FSH usage when physicians used Alife's Stim Assist™.
“This suggests that AI has the potential to refine the starting dose of FSH and narrow down the timing of the trigger injection during ovarian stimulation, ultimately benefiting patients by optimising the number of mature oocytes retrieved and reducing medication costs."
Titled "Optimizing oocyte yield utilizing a machine learning model for dose and trigger decisions: a multi-center, prospective study," it was led by Dr. Chelsea Canon, a reproductive endocrinologist and infertility specialist for RMA of New York and was published in Scientific Reports.
The study, which involved 291 patients undergoing IVF treatment at two clinics in the United States, underscores the potential of AI to revolutionise the field of assisted reproductive technology.
"The use of AI in IVF represents a significant advancement in reproductive medicine," said Dr. Alan B Copperman, CEO of RMA of New York and a collaborator of the study,
"By leveraging AI to optimize ovarian stimulation decisions, we can potentially improve IVF outcomes and streamline the treatment process for patients."
Dr. Canon and Dr. Copperman’s study is the first to evaluate the efficacy of AI for optimizing ovarian stimulation using prospective post-market data.
The researchers emphasize the need for further studies to validate these findings and explore the broader application of AI in IVF treatment.