Oral follicle-stimulating hormone receptor agonist affects granulosa cells differently than recombinant human FSH

The influence of the pharmaceutical industry on the development of gonadotrophins and ovarian stimulation protocols in assisted reproductive technologies

Introduction

This review examines the evolution of gonadotrophins in ovarian stimulation (OS) protocols for assisted reproductive techniques (ART). Since the advent of in vitro fertilisation (IVF) in the late 1970s, the pharmaceutical industry has played a pivotal role in advancing gonadotrophin production, improving drug purity and optimising delivery methods. Despite significant progress, questions remain about the robustness of the evidence supporting the use of different gonadotrophins and the impact of industry-driven research on clinical practice. The review critically examines the evolution, evidence and future directions of gonadotrophin use in ART.

Methods

A comprehensive literature search was carried out in multiple databases to select articles/reviews on historical developments, manufacturing and analytical techniques, regulatory frameworks and clinical trials undertaken to assess gonadotrophin production, formulation processes and their integration into clinical practice. The analysis included mainly evidence from pharmaceutical sponsored randomised controlled trials (RCTs) as well as single arm, registration or post approval studies. Studies on new molecular entities were reviewed. Systematic reviews and meta-analyses, national registries were consulted. Laboratory developments, regulatory challenges, economic constraints, were considered.

Results

Over the past four decades, ART has seen remarkable improvements, including increased live birth rates in women of advanced ovarian age, reduced multiple births, and the advent of patient-friendly pen devices. Innovations such as recombinant FSH (rFSH) and biosimilars have expanded treatment options. However, the high cost of drug development as well as the complexity of the ART process have contributed to underpowered trials and reliance on meta-analyses, which often fail to account for confounding factors.

Discussion

While gonadotrophins have been shown to be effective for OS, unresolved issues, such as the role of supplementing LH activity in OS protocols, highlight the need for more robust trials. Collaboration between stakeholders is essential to standardise trial designs, define key outcomes and minimise bias. Emerging technologies, including AI and genetic testing, offer opportunities to refine embryo assessment and implantation outcomes, thus improving trial design. A renewed focus on rigorous, transparent trials and interdisciplinary collaboration is essential to advance patient care and address unmet challenges in ART treatment. Beyond gonadotrophins, alternative therapeutic avenues to improve oocyte competence and implantation success warrant exploration.

Machine learning in time-lapse imaging to differentiate embryos from young vs old mice†

Time-lapse microscopy for embryos is a non-invasive technology used to characterize early embryo development. This study employs time-lapse microscopy and machine learning to elucidate changes in embryonic growth kinetics with maternal aging. We analyzed morphokinetic parameters of embryos from young and aged C57BL6/NJ mice via continuous imaging. Our findings show that aged embryos accelerated through cleavage stages (from 5-cells) to morula compared to younger counterparts, with no significant differences observed in later stages of blastulation. Unsupervised machine learning identified two distinct clusters comprising of embryos from aged or young donors. Moreover, in supervised learning, the extreme gradient boosting algorithm successfully predicted the age-related phenotype with 0.78 accuracy, 0.81 precision, and 0.83 recall following hyperparameter tuning. These results highlight two main scientific insights: maternal aging affects embryonic development pace, and artificial intelligence can differentiate between embryos from aged and young maternal mice by a non-invasive approach. Thus, machine learning can be used to identify morphokinetics phenotypes for further studies. This study has potential for future applications in selecting human embryos for embryo transfer, without or in complement with preimplantation genetic testing.

Hypogonadotropic Hypogonadism

Delayed puberty is defined as absent testicular enlargement in boys or breast development in girls at an age that is 2 to 2.5 SDS later than the mean age at which these events occur in the population (traditionally, 14 years in boys and 13 years in girls). One cause of delayed/absent puberty is hypogonadotropic hypogonadism (HH), which refers to inadequate hypothalamic/pituitary function leading to deficient production of sex steroids in males and females. Individuals with HH typically have normal gonads, and thus HH differs from hypergonadotropic hypogonadism, which is associated with primary gonadal insufficiency.