Reacción a "Non-invasive method assesses the quality of mouse oocytes and embryos"

In this article, Albert Parra and collaborators have used, in a very well-developed study, artificial intelligence (AI) methods combined with a type of microscopy called hyperspectral microscopy (i.e. they generate images with much higher resolution than other types of microscopy), to know the quality of mouse oocytes and embryos from a metabolic point of view, without causing them harm. The model, called METAPHOR, analyses hundreds of images containing information on many metabolites in the embryos and oocytes in just a few minutes. The results have shown differences in oocyte quality as a function of age, and the authors propose that it may be of great interest in areas such as fertility preservation and personalised reproductive medicine.

However, as Ojosnegros' team [another of the authors] admits, the experiments were conducted with a limited number of samples in an animal model and more research will be needed to understand the ability to correlate METAPHOR classification with implantation ability. Researchers are currently refining the technology to screen human embryos and have created a spin-off company to bring the technology to assisted reproduction clinics in the coming years.

In assisted reproduction, there are multiple instances where AI could help improve the ability to predict live births, such as gamete and embryo selection and the development of personalised fertility drugs. While the team that developed METAPHOR demonstrates that it can be used to obtain metabolic information from live embryos and oocytes, without causing harm, there is published work that has already performed this analysis in humans. Recently, in a paper published by Sakkas et al. in which, in a rather similar way, they evaluated metabolic images of human embryos from 120 couples by fluorescence imaging microscopy, they failed to find a relationship between the pattern of metabolism of embryos that lead to pregnancy compared to those that did not.

Studies with oocytes and embryos that allow their selection and classification are promising and are progressing at an increasing rate. Parra's work may not take long to be applied in humans, but more studies are needed to know its true application in embryo selection and increased live birth rates. Overall, the widespread and rapidly growing field of AI represents a powerful and exciting opportunity for the field of reproductive biology and the IVF [in vitro fertilisation] industry.