AI Fertility
Artificial intelligence in in-vitro fertilisation :
Renewing hope in starting a family
AI has already gained some currency as a selection tool for the best embryos to implant as people who undergo IVF may have several embryos to choose from .
In-vitro fertilisation ( IVF ) is the standard assisted reproductive treatment for couples unable to conceive a child . Despite its successes , most couples who rely on it still cannot conceive due to a number of challenges , including genetic abnormalities that often affect embryos created in the lab .
The standard method for embryo genetic screening is called pre-implantation genetic testing for aneuploidy , or PGT-A . While an accurate tool , it ’ s also invasive and expensive , especially for people who have several embryos to test . To address these drawbacks , artificial intelligence ( AI ) is now emerging as an important tool to help fertility experts select the healthiest embryos that are more likely to end up in a successful pregnancy .
AI has already gained some currency as a selection tool for the best embryos to implant as people who undergo IVF may have several embryos to choose from . Picking the right one is often challenging as embryologists still rely on subjective assessments based on embryo shape and structure . Although some fertility doctors tend to implant more than one embryo in the womb , this practice is controversial because it can lead to multiple pregnancies and increased risks
AI may be a game changer in fertility medicine of complications . The hope is that AI can improve the selection of embryos in a way that will speed up fertility treatment while reducing its cost .
According to the World Bank , fertility rates around the world have been declining for several years , with 2022 recording 2.148 births per woman , which is half the rate of the 1950s . In Malaysia , the current fertility rate is 1.924 births per woman . A number of factors is contributing to this decline , ranging from social issues like delayed marriage and financial constraints that necessitate a small family to health problems like genetic complications that result in infertility . Other specific factors that lead to infertility include being 40 years of age and above , fallopian tube damage , disruption of the ovarian cycle , impaired uterus function , and uterine tumour growth .
All of this is fueling the demand for IVF treatments among those who want to start a family . IVF involves the collection of mature human eggs from the ovary that are then fertilised with sperm in the laboratory . The fertilised eggs , or embryos , are then transferred into the uterus . This represents one complete IVF cycle , which can take up to three weeks .
We sat down with two fertility experts , Tee Sze Tian and Adelle Lim , for some insights into the application of AI in both fertility medicine and genetic screening . The former is Group Chief Embryologist at TMC Fertility Centre while the latter is Chief Embryologist at Alpha IVF & Women ’ s Specialists in Kuala Lumpur .
How is AI applied in fertility medicine and which problems can the technology help to solve ? Tee Sze Tian : Traditionally , embryo analysis and selection were performed with direct visualisation of embryos under light microscope or timelapse imaging . The limitation of these methods is a high degree of variation between operators due to the subjective nature of these assessment . In contrast , AI works through deep machine learning , where it learned to differentiate viable embryos from non-viable ones by studying more than 20,000 pictures and videos of embryos that previously led to pregnancy . The AI system assists the embryologists in identifying which embryo should be transferred for implantation , decreasing the possibility of inconsistency due to human variation and ensuring the best potential patient outcome .
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