OVUM, a reproductive and fertility wellness brand, highlights the potential of artificial intelligence (AI) to revolutionize the in vitro fertilization (IVF) field.
With IVF success rates still low and innovation progress slow, OVUM emphasizes that the introduction of AI presents opportunities for better quality treatments and improved IVF success rates.
According to recent statistics from the Human Fertility and Embryology Authority (HFEA), live birth rates per embryo transferred are currently 25% and 19% for patients aged 35-37 and 38-39 years, respectively. These numbers underscore the need for advances in IVF science, and the integration of AI technology into IVF clinics has long been awaited. Currently, the success rate of in vitro fertilization worldwide is hovering around 30%, and research efforts to improve these results are rapidly increasing. As a result, AI and machine learning are emerging as potential solutions in IVF clinics.
The use of AI in IVF clinics holds great promise for addressing the challenges facing infertile couples. In vitro fertilization involves removing an egg from a woman’s ovary, fertilizing it in a laboratory, and then implanting the resulting embryo into the woman’s uterus. However, the lack of consistent success rates and clinic-to-clinic variability highlight the need for improved technology. OVUM asks, “Will AI help mitigate these variability and improve IVF success rates?”
AI refers to mathematical algorithms that automate decision-making and analysis performed by clinicians and embryologists. The ability of algorithms to process and sort vast amounts of data presents great opportunities for the role of AI in in vitro fertilization. By leveraging data from previous IVF cycles, AI suggests individualized IVF protocols and assists her in selecting the most suitable embryo for transfer, two key aspects of IVF treatment.
OVUM highlights that the human subjectivity inherent in the decision-making process contributes to clinic-to-clinic variability. AI integration eliminates the subjectivity of human assessments, enabling objective ranking of embryos and patient protocol decisions based on data-driven insights.
Embryo selection is one area where AI is getting a lot of attention and could be the first AI application in IVF clinics. Currently, embryologists manually select the most viable embryos suitable for transplantation based on visual observation and chromosomal test results. However, this time-consuming process is prone to bias and error due to differences in training, clinic practice, and scoring methods. Fertility experts at OVM share that AI tools can overcome these limitations by leveraging pattern recognition and reference datasets to recommend embryos that are most likely to lead to successful pregnancies.
The potential impact of AI in IVF also extends to treatment protocols. Currently, protocols can be highly variable and often require a trial-and-error approach to find the optimal individualized protocol for each patient. This process can be emotionally and financially taxing for couples undergoing multiple IVF cycles. AI helps physicians leverage large datasets otherwise unavailable to develop optimal individualized fertility treatment plans based on patient characteristics.
OVUM founder Jenny Wordsworth, a lawyer and member of the British Fertility Association, commented on the factors to consider before introducing AI across the fertility field: RCTs to validate the efficacy of AI in the IVF field may hinder progress. By the time the RCT is published, the AI algorithms are already obsolete. We should consider alternative validation methods for this new technology given its unique properties as a clinical decision support tool.
“Regulatory bodies such as the HFEA play an important role in evaluating new therapies such as AI tools for embryo selection. A sandbox approach may allow a faster pace of innovation by approving AI for a period of time and then allowing real-world evidence to be evaluated.
“The role of the embryologist has evolved, and certain tasks such as measuring follicles or counting cells within an embryo can now be effectively delegated to AI. Before you deploy AI, you need to understand AI: education and time will help build trust and demonstrate that AI enhances practice without displacing expertise.
“Transparency is a key concern, as AI often operates as a ‘black box’ without revealing its decision-making process. To establish trust, we need to choose more transparent and interpretable models that allow experts to see and understand how AI works.
“Safety and rigorous reporting are essential for clinicians and patients to trust AI models. essential for development.
“Data availability is essential for mainstream use of AI in the clinic. More than 3 million women worldwide undergo IVF each year, and the more data we have, the better AI can help improve outcomes.”
