Experts Discuss How Organoids Are The Future of Women’s Health Research
Hear how researchers are leveraging organoids and organ-on-a-chip technology to advance women’s health research.
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Organoids – miniature, simplified versions of human organs grown in the lab – and organ-on-a-chip devices – microfluidic systems that simulate the physiological functions of tissues and organs – are transforming how scientists study disease. These advanced models offer a more human-relevant alternative to traditional 2D cell cultures and animal studies, allowing researchers to replicate complex cellular environments, test treatments more accurately and investigate disease mechanisms in a more physiologically meaningful way.
This technological leap is especially significant for women’s health, a field historically sidelined in biomedical research. From the exclusion of female subjects in early clinical trials, to the lack of suitable models for conditions like endometriosis or metastatic breast cancer –research into diseases that primarily or disproportionately affect women has long faced scientific barriers.
Organoids and organ-on-a-chip technologies offer new ways to bridge these gaps. By enabling researchers to mimic female-specific tissues, track hormonal fluctuations and personalize experiments using patient-derived cells, these models hold promise for uncovering novel insights and accelerating the development of more effective diagnostics and treatments for women.
At the WORD+ 2025 conference, three researchers working at the forefront of this field shared their perspectives on how these emerging technologies are being used to advance women’s health research. Technology Networks asked each researcher the same two questions.
How is your research in organoids and/or organ-on-a-chip technology helping to fill existing gaps in women's health research?
Mhairi (“Vari”) Morris, PhD (M(M):
My research uses patient-derived breast cancer organoids co-cultured with fat cells (from subcutaneous vs visceral fat) to investigate the impact of exercise on modulating the tumor microenvironment in obesity-related breast cancer.
Most cancer-related deaths are caused by secondary metastasis, and this is driven by a small subset of cells called cancer stem cells (CSCs), which can self-renew. However, there is nothing in the literature about how exercise affects these CSCs.
Using this novel model, I hope to visualize how the different cell types interact to help us understand how exercise may reduce the pro-cancerous effects of obesity in breast cancer.
Stefaan Verbruggen, PhD (SV):
Women’s health is traditionally an understudied field of research, often due to a lack of appropriate animal or lab-based models to test treatments on.
At Queen Mary University of London, our research in organoids and organ-on-a-chip technology is helping to accelerate these fields by creating more accurate models for studying complex diseases that disproportionately affect women. For example, much of the pain in late-stage breast cancer comes from bone metastases, and our organ-on-a-chip model allows us to closely mimic how cancer cells spread to bones and interact with bone tissue. This research is critical for developing more targeted therapies and improving treatment outcomes for women with metastatic breast cancer.
Similarly, our work on modeling the dysregulation of the vaginal microbiome aims to address a significant gap in understanding how microbial imbalances contribute to conditions such as bacterial vaginosis, pelvic inflammatory disease and increased susceptibility to HIV. These models can show us how shifts in microbial communities affect women's health on a cellular level, which is essential for developing better diagnostics and personalized treatments.
Both of these projects highlight how we can now better replicate the human physiology, helping to fill crucial gaps in women's health research and improve patient care.
Emma Laporte, PhD (EL):
I think any research into women's health is filling a gap, and better models always help.
There are no good in vivo models for endometriosis specifically, including rodent models. As mice do not menstruate, they also don’t get endometriosis. So, good in vitro models are very, very useful.
RLS:
M(M:
While 3D models like organoid and organ-on-a-chip technologies provide more physiologically relevant models than traditional 2D cultures, one of the biggest challenges is reproducibility and variability from batch-to-batch and patient-to-patient. This makes it difficult to create consistent, scalable models for breast cancer research.
Validating findings generated using these technologies in a clinical setting is also difficult due to tumor heterogeneity and lack of representation in model systems (e.g., hormonal fluctuations, age-related changes and ethnic/genetic variations).
What I hope to see in the next 5–10 years is the expansion of biobanks with diverse patient-derived organoids to reflect different ethnic backgrounds, ages, lifestyles and socioeconomic factors – as well as the development of high-throughput screening platforms using organoid technology to rapidly test new drug and lifestyle interventions (e.g., exercise combined with drug treatment).
In addition, it would be great to see the integration of AI and machine learning to analyze large datasets from 3D models with the aim of developing personalized treatment strategies, such as personalized exercise prescriptions.
SV:
One of the biggest challenges in using organ-on-a-chip technologies to advance women’s health is the complexity of accurately replicating the human microenvironment, particularly capturing the many genetic and cellular differences between different patients. The cellular interactions, tissue-specific behaviors and dynamic environments we aim to model are incredibly complex, and current technology still struggles to fully replicate these intricate systems. For instance, in our breast cancer metastasis model, replicating the interactions between cancer cells and the bone microenvironment requires precise tissue engineering and integration of multiple cell types, which can be difficult to achieve consistently.
Another challenge is the scalability and reproducibility of these models. While they provide significant insights on a small scale, translating findings into clinical settings or larger population studies remains a hurdle.
Looking ahead to the next 5–10 years, I hope to see more refined organ-on-a-chip models that can better simulate the full range of biological interactions. I also envision greater integration of machine learning with high-throughput screening platforms and large biobanks of patient data, which together show promise in accelerating this research, especially for rare conditions.
Ultimately, I hope these technologies will lead to more personalized, effective treatments and better outcomes for women worldwide.
EL:
The biggest gap that we have right now is that we only mimic the epithelium layer, so we are missing a lot of the other cell types that are important in the endometrium. We can combine it with stromal cells, but we should also include immune cells, nerves and endothelial cells, because all these different cell types have an impact on the disease. I think that's something that we're lacking.
But of course, the more complex you go with your models, the lower your output will be. I think for the early stages of our drug discovery program, it's good to have these very simple models that we can scale up.
I would like to see more funding specifically for women's health. That would be really nice.
There is a women's health program at the BioInnovation Institute in Copenhagen where they will look for programs within women's health and from research within women's health. For example, in Belgium, we don't have any specific funding for our type of research, so you always have to compete with all the other things – whereas cancer and many other diseases have their specific agencies.
