An exciting development is the novel application of big data and artificial intelligence in IVF treatment.
For example, big data and artificial intelligence can be used to predict and optimise an individual patient’s bodily response to varying dosages of different fertility drugs based on medical condition, to maximise chances of success in IVF treatment, in what is referred to as “precision fertility medicine”.
In recent years, Singapore has emerged as a hub for collating big data on the genomics of various Asian ethnic populations for application in drug discovery and precision medicine, which is facilitated by the country’s diverse multi-racial population originating from different parts of Asia. For example, the “Life Whisperer Genetics” AI algorithm developed by the American health care company Presegen is non-invasive, low-cost, and provides results instantaneously, thereby making it preferable to the tedious and time-consuming pre-implantation genetic testing of IVF embryos.
This would certainly be a cause of legal and ethical concern, because non-medical sex selection of IVF embryos is banned by health regulations in Singapore[X9] . As such socially-desirable characteristics are complex traits determined by the combination of multiple genes, polygenic risk scores are used to estimate an individual embryo’s likelihood of developing an adult-onset, multifactorial trait by analysing the combination of specific genetic variants within its genome.
Such figures might even be higher in Singapore, given the prevalent “kiasu” mentality in the country.