Dr Gurpreet Singh Kalra, Medical Director, ART Fertility Clinics talks about the role of technology in in-vitro fertilisation
Technology is changing the society and is enabling its evolution. It helps us in making our lives more convenient and provides us with ways of problem solving that were never possible before. One of the recent technological advancements is the introduction of artificial intelligence (AI). In the last decade, artificial intelligence seems to have come of age. Nowadays, we humans are engaging with AI every day in some or the other way. Customised product advertisements, face recognition, voice recognition, online shopping, listening to customised music playlists or even using virtual assistance, are all in existence with the help of artificial intelligence. AI has helped us in stimulating economic growth, enhancing global health and well-being but can also be used to mislead opinions.
AI in healthcare industry
AI has a role to play in almost every industry including technology, financial services, education, gaming, automotive or health. One of the industries with a growing adoption of AI and need for more is healthcare. The adoption of AI is reshaping the Indian healthcare market significantly. As per the prediction, the applications of artificial intelligence in the healthcare space will be worth INR 431.97 Bn by end of 2021, expanding at a rate of 40% per annum.
AI in assisted reproduction
AI based advancements are increasingly becoming a part of different specialties in medical science. AI has also gained foothold in some areas of practice in the field of reproductive medicine or management of infertility, currently mainly in embryo grading with further developments expected in sperm and egg grading as well as clinical decision making.
Embryo grading
Earlier, the IVF process largely relied on human intervention. Embryo grading, one of the most important processes in IVF used in separating good-quality embryos from the bad ones, is traditionally performed by highly skilled embryologists. It was found that miscarriages are mainly caused by genetic abnormalities in the conceptions. The success rate of any IVF cycle is highly dependent on transferring good quality and genetically normal embryos.
The embryos are placed in incubators called Time-lapse imaging devices for embryos. These are incubators fitted with special cameras that take picture of each growing embryo every 5-20 minutes for 5-6 days. Embryo grading by AI is based on availability of large datasets of various morphometric parameters of a growing embryo. These datasets with the help of machine learning over time have made it possible to develop intelligent algorithms. The intelligent algorithms assess and compare the images from a growing embryo with millions of stored images and judge the risk of abnormality such as risk of a particular embryo being genetically abnormal. If predictive value of such an assessment is judged to be high, it can help in identifying an embryo with high chance of success, to be transferred instead of one that is more likely to fail implantation or end up in miscarriage. Traditionally the genetic abnormality (aneuploidy) is tested by doing an invasive test called PGT-A (pre-implantation genetic testing for aneuploidy). This investigation involves plucking a few cells out of the surface of the embryo for genetic analysis. This is an invasive test and carries a risk of damaging the embryo. Furthermore, there can be other pros and cons including unclear results and mosaicism (mixed cell lines), and therefore no clarity on which embryo is genetically normal.
AI is easing the treatment process by eliminating human errors and saving time and efforts. AI makes the embryo selection process simpler especially for women who are aged above 35 years and have lesser chances of delivering a single full-term baby.
Due to artificial intelligence, medical experts now have the capacity to identify embryos that are abnormal or have some genetic defect that may run in the family. Genetic testing technology has proven to make a difference to outcomes.
Conclusion:
Technological advancements such as use of AI in more accurate grading of embryos using time lapse imaging, has contributed towards the success of infertility treatments. With the data and algorithm getting more refined, better outcomes are expected in near future.
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