AUTHOR=Soczyńska Julia , Gawełczyk Wiktor , Papierkowska Julia , Muzyka Adrian , Majcherczyk Krzysztof , Obrycka Patrycja , Żołyniak Mateusz , Woźniak Sławomir 

TITLE=The future of embryo engineering and fertility research in interdisciplinary collaboration

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2025.1619050

DOI=10.3389/fcell.2025.1619050

ISSN=2296-634X

ABSTRACT=The increasing prevalence of marital infertility and the persistent desire for offspring have become more significant issues over past decades. Considering the potential genetic, hormonal, and anatomical causes, it is evident that the analysis of infertility is complex, necessitating the development of innovative therapies to address various challenges and dilemmas. The interdisciplinary collaboration of multiple fields fosters scientific progress, such as the development of new research models, reproductive mini-organoids, enhancing the chances of successful parenthood even in challenging cases. Since the fifth decade of the 20th centurymarked by the in vitro fertilization of an egg cell, the birth of Louise Brown (the first test-tube baby), the methods of embryo cryopreservation, the discovery of induced pluripotent stem cells (iPSC), and the genetic editing technology CRISPR-Cas9-research has been advancing towards promising directions for studying infertility causes and testing potential therapeutic interventions in controlled conditions. Gene therapy stands as a significant pillar, with 2017 witnessing promising experimental advancements in repairing mutations responsible for hypertrophic cardiomyopathy. Attempts were also made to create Human Immunodeficiency Virus (HIV) immunity by disabling the CCR5 gene, leading to the birth of twins with this variation. Progress in innovative therapies has kept pace with advancements in artificial intelligence, poised to revolutionize reproductive medicine by minimizing human errors. Machine learning (ML) algorithms are being integrated into embryo selection processes, predicting their implantation potential, raising concerns among various nations about eugenics and the interference with human nature. These concerns form a highly debated legal and political pillar. The growing automation is driven by arguments related to the increasing problems of future challenges, such as environmental changes or declining gamete quality. Scenarios under consideration include the development of advanced assisted reproduction technologies and support programs. Theoretical possibilities of alternative methods for organism development are being explored, though they remain constrained by the necessity of rigorous human studies.