Fertility Future: Integrating Hormone Therapy, Artificial Intelligence, and Automation to Improve Reproductive Outcomes

Presenter: Melanie Stepchuk

Faculty Sponsor: Reena Randhir

School: Springfield Technical Community College

Research Area: Biology

Session: Poster Session 2, 11:30 AM - 12:15 PM, Auditorium, A34

ABSTRACT

The developments in hormone therapy are reshaping fertility treatment. There are treatment alternatives for people who encounter age-related or medical issues. The rate of live births through assisted reproductive technology has increased over the past decade. But the unpredictability of success, safety, and long-term effects including rare but serious complications (e.g., ovarian hyperstimulation syndrome and thromboembolic events) is a problem. The future of fertility treatment is in the integration of Artificial Intelligence (AI) and automation combined with traditional hormone therapies. This research explored scientific articles on PubMed, targeting studies between 2010-2025 to investigate new technologies and approaches in fertility treatments. Currently, AI is revolutionizing fertility treatment. Real-time hormone trackers are being employed to monitor menstrual cycles, enabling individualized and accurate timing of treatment rather than standardized treatment for all. Fertilo is a new technology, currently in FDA- cleared Phase 3 trial plan, is designed to decrease the stimulation phase from the conventional 9-12 days to only 2-3 days of medication, hopefully lowering the physical and economic costs. The integration of automation in in vitro fertilization labs makes fertility treatment easier, more efficient, and more economical. The introduction of Pergoveris, which is a combination of recombinant human follicle-stimulating hormone and recombinant human luteinizing hormone in a single pre-filled injection pen, may reduce the injection burden by combining two hormones in one pen. Recent research shows that AI-assisted embryo selection can outperform traditional visual assessment in predicting embryo viability and may improve clinical outcomes compared to traditional visual assessment methods. In general, these developments are indicative of more effective, accessible, and patient-centered fertility care, and the increasing use of technology in this field.

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