Mendizabal-Ruiz Gerardo, Paredes Omar, Borrayo Ernesto, Chavez-Badiola Alejandro
Conceivable Life Sciences, New York, USA.
Laboratorio de sistemas autónomos para diseño biotecnológico, Departamento de Bioingeniería Traslacional, Universidad de Guadalajara, Guadalajara, Mexico.
Reprod Fertil. 2025 Aug 14;6(3). doi: 10.1530/RAF-24-0077. Print 2025 Jul 1.
People in low- and middle-income countries face many obstacles when trying to access fertility treatments. These challenges include high costs, the need for specialized medical facilities, and cultural beliefs that may discourage seeking help. This paper explores how artificial intelligence (AI) and automation could help overcome some of these barriers and make fertility treatments more widely available. It examines how AI may improve the accuracy, efficiency, and consistency of different steps in fertility treatments, such as choosing the healthiest embryos, analyzing sperm, evaluating eggs, and planning treatment. The paper also discusses how automation could simplify laboratory procedures, from growing embryos and freezing them for future use to the possibility of fully automating the in vitro fertilization (IVF) process, which could help lower costs and make these treatments more accessible. Finally, this paper addresses the ethical and practical challenges associated with using these technologies, including potential biases in AI, equitable access, quality control, data privacy, job implications, and cultural sensitivities.
This paper explores how AI and automation could help make fertility treatments more accessible in low- and middle-income countries (LMICs). Many individuals and couples face difficulties conceiving, and assisted reproductive technology (ART) - which includes procedures such as intrauterine insemination (IUI) and IVF - offers them a chance to build a family. However, ART is often out of reach in LMICs due to high costs, the need for specialized medical facilities, and cultural barriers. AI and automation have the potential to improve accuracy, efficiency, and consistency in ART procedures, such as embryo selection, sperm and egg assessment, and treatment planning. Automation could also streamline laboratory processes, including embryo culture and freezing, which may eventually lead to more affordable and scalable fertility treatments. By reducing human error and dependence on highly trained specialists, AI-driven technologies could help lower costs and make ART available to more people. This paper also considers the ethical and practical challenges of using AI in reproductive medicine, including potential biases in AI algorithms, fairness in access to treatment, data privacy, workforce impact, and cultural sensitivities. Fertility treatments can be life-changing for those struggling with infertility due to medical conditions, age, or personal circumstances. They also provide opportunities for same-sex couples and individuals who want to start a family. However, in LMICs, infertility is often surrounded by social stigma, economic hardship, and limited medical resources, making access to ART even more difficult. By integrating AI and automation into reproductive medicine, it may be possible to break down these barriers, reduce costs, and create more inclusive and accessible fertility care. These advancements have the potential to bring hope to millions who dream of parenthood but currently lack the means to pursue it.
低收入和中等收入国家的人们在尝试获得生育治疗时面临许多障碍。这些挑战包括高昂的费用、对专业医疗设施的需求以及可能阻碍寻求帮助的文化观念。本文探讨了人工智能（AI）和自动化如何有助于克服其中一些障碍，并使生育治疗更广泛地可得。它研究了人工智能如何提高生育治疗不同步骤的准确性、效率和一致性，例如选择最健康的胚胎、分析精子、评估卵子以及规划治疗。本文还讨论了自动化如何简化实验室程序，从培养胚胎并将其冷冻以备将来使用到体外受精（IVF）过程完全自动化的可能性，这有助于降低成本并使这些治疗更容易获得。最后，本文探讨了与使用这些技术相关的伦理和实际挑战，包括人工智能中的潜在偏差、公平获取、质量控制、数据隐私、对工作的影响以及文化敏感性。
本文探讨了人工智能和自动化如何有助于使低收入和中等收入国家（LMICs）更容易获得生育治疗。许多个人和夫妇面临受孕困难，辅助生殖技术（ART）——包括宫内人工授精（IUI）和体外受精等程序——为他们提供了组建家庭的机会。然而，由于成本高昂、对专业医疗设施的需求以及文化障碍，辅助生殖技术在低收入和中等收入国家往往难以获得。人工智能和自动化有潜力提高辅助生殖技术程序的准确性、效率和一致性，例如胚胎选择、精子和卵子评估以及治疗规划。自动化还可以简化实验室流程，包括胚胎培养和冷冻，这最终可能导致更经济实惠且可扩展的生育治疗。通过减少人为错误和对训练有素的专家的依赖，人工智能驱动的技术可以帮助降低成本并使更多人能够获得辅助生殖技术。本文还考虑了在生殖医学中使用人工智能的伦理和实际挑战，包括人工智能算法中的潜在偏差、治疗获取的公平性、数据隐私、对劳动力市场的影响以及文化敏感性。生育治疗对于那些因医疗状况、年龄或个人情况而难以受孕的人来说可能会改变生活。它们也为同性伴侣和想要组建家庭的个人提供了机会。然而，在低收入和中等收入国家，不孕症往往伴随着社会耻辱感、经济困难和有限的医疗资源，这使得获得辅助生殖技术更加困难。通过将人工智能和自动化整合到生殖医学中，有可能打破这些障碍，降低成本，并创造更具包容性和可及性的生育护理。这些进步有可能给数百万梦想成为父母但目前缺乏实现途径的人带来希望。
