The reproductive and fertility wellness brand, OVUM, highlights the potential of artificial intelligence (AI) in revolutionizing the In vitro fertilization (IVF) field.
With success rates in IVF outcomes remaining low and innovation progressing slowly, OVUM emphasizes the incorporation of AI presents a chance for higher quality treatment and improved IVF success rates.
In keeping with recent statistics from the Human Fertilisation and Embryology Authority (HFEA), the live birth rate per embryo transferred is currently at 25% and 19% for patients aged 35-37 and 38-39, respectively. These figures underscore the necessity for advancements in IVF science, and the mixing of AI technology inside IVF clinics is long overdue. Globally, current IVF success rates hover around 30%, prompting a surge in research efforts to reinforce these outcomes. Consequently, AI and machine learning are emerging as potential solutions within the IVF clinic.
Using AI in IVF clinics holds great promise for addressing the challenges faced by couples battling infertility. IVF involves the retrieval of an egg from the lady’s ovary, fertilization in a laboratory, and subsequent transfer of the resulting embryo to the lady’s uterus. Nonetheless, the shortage of consistent success rates and variations amongst clinics highlight the necessity for improved techniques. OVUM poses the query: Can AI help reduce these variabilities and increase IVF success rates?
AI refers to mathematical algorithms that automate decisions or analyses performed by clinicians or embryologists. The flexibility of algorithms to process and categorize vast amounts of knowledge presents significant opportunities for AI’s role in IVF. By leveraging data from previous IVF cycles, AI can suggest personalized IVF protocols and aid in choosing essentially the most viable embryo for transfer, two crucial elements of IVF treatment.
OVUM highlights that human subjectivity, inherent within the decision-making process, contributes to variations between clinics. The mixing of AI can eliminate the subjectivity of human assessment and objectively rank embryos or determine patient protocols based on data-driven insights.
Embryo selection is one area where AI has received considerable attention and is more likely to be the primary application of AI in IVF clinics. Currently, embryologists manually select essentially the most viable embryo for transfer based on visual observations and chromosomal testing results. Nonetheless, this time-consuming process is at risk of bias and error because of variations in training, clinic practices, and grading methodologies. Fertility experts at OVUM share that AI tools can overcome these limitations by leveraging pattern recognition and reference data sets, enabling them to recommend the embryos more than likely to lead to successful pregnancies.
The potential impact of AI in IVF extends to treatment protocols. Currently, protocols will be highly variable, and a trial-and-error approach is usually vital to seek out an optimal, personalized protocol for every patient. This process will be emotionally and financially burdensome for couples undergoing multiple IVF cycles. AI can assist physicians in formulating optimal, personalized fertility treatment plans based on patient characteristics, leveraging large data sets that might otherwise be unavailable to clinicians.
Founding father of OVUM, Jenny Wordsworth, as a lawyer and member of the British Fertility Society, comments on aspects that have to be considered before AI is implemented across the fertility sector: “We’d like to acknowledge that relying solely on high-quality randomized controlled trials (RCTs) to validate the efficacy of AI within the IVF sector may hinder progress. By the point an RCT is published, the AI algorithm is already outdated. We must always explore alternative validation methods for this latest technology, considering its unique characteristics as a clinical decision support tool.
“Regulatory bodies, akin to the HFEA, play an important role in assessing latest treatments like AI tools for embryo selection. While RCTs are vital, the newly-proposed (but not yet approved) sandbox approach by the HFEA could enable faster-paced innovation by allowing AI to be approved for a specified period, followed by real-world evidence assessment.
“The role of embryologists is evolving, and certain tasks, like measuring follicles or counting cells in embryos, will be effectively delegated to AI. Nonetheless, healthcare professionals need to grasp AI before embracing it in clinical settings. Education and time will help construct trust and show that AI enhances their practices without replacing their expertise.
“Transparency is a key concern with AI, because it often operates as a ‘black box’ without revealing its decision-making process. To determine trust, we must select more transparent and interpretable models that allow professionals to review and understand the workings of AI.
“Safety and rigorous reporting are essential for clinicians and patients to trust AI models. Open discussions on the potential risks and advantages of AI in medicine, including IVF, are crucial for developing a sturdy regulatory framework.
“Data availability is significant for the mainstream use of AI in clinics. Sharing data in a good and medically confidential manner, together with developing methods to streamline data processing, will enhance the effectiveness of AI models. With over three million women undergoing IVF globally every year, the more data we have now, the higher AI can contribute to improved outcomes.”