Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Comment
  • Published:

Navigating the future of assisted reproductive technology with micro-robotics, nanobiosensors and artificial intelligence

Technological developments in reproductive medicine, driven by the convergence of micro-robotics and nanosensors, along with decision-making aided by artificial intelligence, are enabling precise manipulation, gamete selection, embryo assessment and personalized treatment. These disruptive advances could lead to fully automated in vitro fertilization workflows. However, clinical implementation will need to address various technical, biological and ethical challenges to ensure safer and more effective fertility solutions.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Implementation of novel technologies in ART.

References

  1. Infertility Prevalence Estimates, 1990–2021. World Health Organization https://www.who.int/publications/i/item/978920068315 (2023).

  2. Kupka, M. S. et al. Fertil. Steril. 122, 875–893 (2024).

    Article  PubMed  Google Scholar 

  3. European IVF Monitoring Consortium (EIM) for the European Society of Human Reproduction and Embryology (ESHRE) et al. Hum. Reprod. 38, 2321–2338 (2023).

  4. Shan, G. et al. IEEE Trans. Biomed. Eng. 70, 1921–1930 (2023).

    Article  PubMed  Google Scholar 

  5. Shan, G. et al. IEEE/ASME Trans. Mechatron. 28, 1372–1383 (2023).

    Article  Google Scholar 

  6. Costa-Borges, N. et al. Reprod. Biomed. Online 47, 103237 (2023).

    Article  PubMed  Google Scholar 

  7. García-Vázquez, F. A. et al. Adv. Sci. 11, 2306901 (2024).

    Article  Google Scholar 

  8. Schwarz, L. et al. Adv. Sci. 7, 2000843 (2020).

    Article  CAS  Google Scholar 

  9. Parra, A. et al. Proc. Natl Acad. Sci. USA 121, e2315043121 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Reyes-San-Martin, C. et al. ACS Nano 16, 10701–10710 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Medina-Sánchez, M., Schwarz, L., Meyer, A. K., Hebenstreit, F. & Schmidt, O. G. Nano Lett. 16, 555–561 (2016).

    Article  PubMed  Google Scholar 

  12. Salehi, A. et al. Adv. Intell. Syst. 7, 2400458 (2024).

    Article  Google Scholar 

  13. Striggow, F. et al. Small 20, e2310288 (2024).

    Article  PubMed  Google Scholar 

  14. Gutierrez, N. M. et al. Nat. Commun. 16, 8340 (2025).

    Article  Google Scholar 

  15. Nauber, R. et al. Nat. Commun. 14, 728 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mariana Medina-Sánchez.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Striggow, F., Jha, P., Arora, R. et al. Navigating the future of assisted reproductive technology with micro-robotics, nanobiosensors and artificial intelligence. Nat. Nanotechnol. 21, 2–5 (2026). https://doi.org/10.1038/s41565-025-02093-x

Download citation

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41565-025-02093-x

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research