Synthetic data & the future of Women's Health: A synergistic relationship

Objectives: The aim of this perspective is to report the use of synthetic data as a viable method in women's health given the current challenges linked to obtaining life-course data within a short period of time and accessing electronic healthcare data. Methods: We used a 3-point perspective method to report an overview of data science, common applications, and ethical implications. Results: There are several ethical challenges linked to using real-world data, consequently, generating synthetic data provides an alternative method to conduct comprehensive research when used effectively. The use of clinical characteristics to develop synthetic data is a useful method to consider. Aligning this data as closely as possible to the clinical phenotype would enable researchers to provide data that is very similar to that of the realworld. Discussion: Population diversity and disease characterisation is important to optimally use data science. There are several artificial intelligence techniques that can be used to develop synthetic data. Conclusion: Synthetic data demonstrates promise and versatility when used efficiently aligned to clinical problems. Therefore, exploring this option as a viable method in women's health, in particular for epidemiology may be useful.