Throughout my 15 years as a clinical embryologist, I gained first-hand insight into the struggles that patients living with infertility face. Over the course of my clinical work, I became closely acquainted with the shortcomings of the existing in vitro fertilization (IVF) infrastructure.
Under the existing healthcare infrastructure in the United States, IVF treatments are costly (ranging from $15,000 to upwards of $30,000 per cycle), and processes are inefficient, which prevents many people from being able to pursue or continue assisted reproductive options for building their families. My own professional experiences gave me insight into the many ways that the IVF industry could improve, and I have dedicated my career to being a part of that change. While most people are aware of the high cost of IVF treatments, not all know of the other challenges that patients face along their journeys through assisted reproductive technology (ART). Technology and, more specifically, artificial intelligence (AI) is the missing piece that will springboard IVF into the modern digital age.
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Daniella Gilboa Daniella Gilboa is an accomplished clinical embryologist, biostatistician, IVF researcher, and co-founder and CEO of AiVF. AiVF is a rapidly growing start-up empowering fertility clinics with data-driven intelligence. Throughout her career as a clinical embryologist, Gilboa helped hundreds of individuals conceive. She continues to advance scientific discovery through contributions to fertility conferences and […]
IVF technology has lagged, and IVF patients remain uninformed of their fertility journeys. The absence of personalized guidance for patients undergoing IVF therapy makes the process nerve-wracking and confusing. IVF is still somewhat a black box. While patients have access to more information than ever before, they are making decisions based on a leaflet in the doctor’s office or a quick Google search. Individuals need friendly and professional guidance to help them understand all the complexities of their individual journey.
While IVF treatments have led to over 8 million births over the past 40+ years, the actual process of embryo selection does not yet adequately control for human bias. Embryologists are responsible for a range of precision tasks as well as administrative functions in the lab. In reference to embryo scoring, research has shown variability among embryologists within the same clinic as well as at different clinics. We are humans after all and therefore prone to human bias as well as errors. New AI-enabled embryo evaluation technologies present exciting possibilities for improving the process. AI can process huge amounts of data, provide objective analysis, and identify what the human eye cannot detect. Additionally, using AI to evaluate embryos takes a fraction of the time that it would take a human to perform the same evaluation.
Access to reproductive care disproportionately affects marginalized groups, such as people of color and LGBTQ+ families. The cost of IVF treatments alone makes the process inaccessible to many. High quality and affordable fertility treatments should be available to all, not just those that can easily access them. AI can contribute to making IVF more accessible and affordable for all hopeful families.
Integrating AI platforms will allow IVF clinics to scale to meet the rising demand for ART (Assistive Reproductive Technology). The WHO estimates that 186 million people worldwide struggle with infertility. And infertility is only part of the picture. AI provides rapid evaluation and tools to enhance efficiencies to clinic processes. There is also potential to reduce the number of cycles a patient must undergo. The average success rate for a cycle of IVF for a woman under 35 years of age is only about 45% and the rates decline for older women. This means that many patients may undergo numerous treatment cycles. Given that each cycle has financial and emotional costs, it’s essential that clinicians maximize the odds of successful implantation for each cycle.
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
We are entering the age of IVF 3.0 – the next wave of fertility care. While IVF has been around for almost 50 years, progress towards optimizing processes has not kept pace with rapid innovation in other sectors. By augmenting the embryologist in selecting the most viable embryo, there is potential for AI to help a patient conceive in one or two cycles, reducing the inherent cost of IVF therapy, and making the treatment more accessible to diverse populations that often don’t have ease of access to treatments today. AI is a powerful tool that has many potential applications in healthcare, including assisting embryologists, who are by and large highly overworked, in more efficiently helping patients on their fertility journeys.
Machine learning brings IVF into the 21st century and could aid innumerable families in accessing assisted reproductive technology. The first step is applying data-driven analyses of embryo quality to help predict potential for viable pregnancy, aiming to minimize the number of cycles that a patient must go through. These advanced data analytics will enable more people to seek fertility treatments at a lower cost. AI platforms have the potential to lighten the heavy burden on embryologists and streamline the IVF process.
I founded AiVF because IVF is one of the most significant innovations in medicine in the last 50 years, and it is time to power it with advanced AI technology. AI has the capacity to make the IVF process efficient and accessible to all who wish to grow their families. Under the current status quo, the IVF industry cannot keep up with the growing demand for ART.
Photo: luismmolina, Getty Images
Daniella Gilboa is an accomplished clinical embryologist, biostatistician, IVF researcher, and co-founder and CEO of AiVF. AiVF is a rapidly growing start-up empowering fertility clinics with data-driven intelligence. Throughout her career as a clinical embryologist, Gilboa helped hundreds of individuals conceive. She continues to advance scientific discovery through contributions to fertility conferences and academic journals and is an active member of the American Society for Reproductive Medicine (ASRM).
