Olivia Friett, editor of FemTech on Med-Tech Insights, spoke to Cyclana Bio‘s CEO, Dr. Léa Wenger, after they announced they had raised £5M to advance drug discovery for Endometriosis.
- You’ve said Cyclana Bio aims to “redefine how therapies are developed” by studying disease at the tissue level — could you elaborate?
The environment in which you perform your cellular assays matters. The ideal assay is done in an environment that completely recapitulates the physiology of the tissue environment. For example, if one is studying heart disease, ideally one would study the heart cells within an environment that mimics the heart, including the physical environment, i.e. the extracellular matrix (ECM). The ECM, which constitutes up to 90% of a tissue, provides structure to a tissue and also an adhesive template for cells within the tissue. High-fidelity modelling of the environment is especially important in disease, and possibly most important in diseases that are underpinned by fibrosis. This is because fibrosis is a tissue-level pathology, with highly cross-linked ECM that can be difficult to reverse. Fibrotic tissue can drive inflammation that causes or at least exacerbates many chronic diseases.
Indeed, generally disease emerges at the tissue level, which is why we propose that this is the scale at which they should be studied and targets to reverse disease should be identified at that scale. Nevertheless, most drug discovery methods centre the cell in their assays, for example individually culturing cells on 2D tissue culture plastic dishes. Slightly more sophisticated methods include 3D culture with Matrigel or similar, which are derived from mouse tumour stroma. Very few of these methods employed in traditional drug discovery capture the healthy much less the diseased tissue physiology. We are doing things differently at Cyclana: we are building our models to have a better faithfulness to disease physiology, leading to the ability to identify better targets to reverse disease.
2. What first drew you to exploring the extracellular matrix (ECM) as a key to understanding endometriosis?
The CSO and co-founder of Cyclana, Kevin Chalut, is a physicist by training with decades of experience applying the tools and concepts of physics to biology. He started investigating how the physical environment of cells affects their behaviour and function when he started his lab at the University of Cambridge. His observations, spanning a number of academic publications, were that the ECM plays a very essential, but mostly overlooked, role in driving cell and tissue function. In his previous academic work, he noted that you could split a population of stem cells roughly in half, put half in one type of ECM and half in a different one, and give them exactly the same chemical signals, and they would respond very differently. That is because the ECM and physical environment shapes the response of cells to external signals. Along with his co-founder and CEO Léa Wenger, Kevin has been applying these concepts to chronic inflammation and disease, and observing that a dysregulated ECM underpins inflammatory diseases, and fixing that ECM dampens the inflammatory response that is the engine of chronic disease. The realisation of the centrality of ECM in regulating tissue function and disease could have massive implications in how we understand mechanisms of disease and develop methods to treat it. Cyclana is investigating the dysregulated ECM in endometriosis, and the central thesis of Cyclana is that fixing this more fibrotic ECM will dampen the inflammation and allow the immune system to clear and reverse the disease.
3. How does focusing on the tissue level allow you to see disease mechanisms that might have been missed?
We have observed that modelling the physiological environment by incorporating the appropriate kinds of ECM is essential to capture cell signalling and function with high fidelity. More specifically, the type of ECM and physical environment shapes the response of cells to external signals. If you don’t capture the appropriate ECM, it is not possible to model cell signalling in a way that you can target the disease. What we are doing at Cyclana is modelling the tissue so that the tissue level signalling has a high fidelity to the physiological environment. That way, we can find both intracellular and extracellular novel targets and have confidence they faithfully represent true disease reversal. Interestingly, this approach will allow us to not only get better fidelity targets, but possibly also help us to extend our reach for finding novel targets that wouldn’t be seen in more traditional approaches. This opens up the possibility that we could investigate repurposed drugs that would work on endometriosis, and allow us a quicker pathway to the clinic.
4. How does Cyclana Bio’s model put the patient at the centre of drug discovery?
We aim to get as close as possible to the human tissue in the way that we model the disease. This starts with the cells. These are not modified in any way to make them last longer. We don’t try to replicate the differentiation process of these cells with stem cells; we use them as they come out of the patient, either through biopsies or through menstrual fluid. Now on top of this we add an additional layer of patient fidelity in that we also replicate the environment in which these cells evolve. This is because cells can dramatically change if taken out of their environment. So a healthy cell put in sub-optimal conditions can all of a sudden look like a diseased cell. As we collect more data, disease trends will start appearing that we can feed directly into our in vitro models in a much more reliable way than if we stopped at using the cells.
On top of these two dimensions (patient cells and patient environment), we add a third dimension of time: with menstrual fluid, we are able to collect longitudinal information about a patient’s journey, rather than using a single snapshot that may not represent their overall health. This allows us to think about tailoring treatments to specific patients and better predict outcomes.
5. Endometriosis remains under-researched. What do you see as the biggest barriers that have held back progress?
There are historical barriers that are a unique blend of societal and scientific. Some of these are explained by the chronic underfunding of research in many women’s health conditions like endometriosis, from a grass roots perspective. This has not stopped people from researching it and making great discoveries, but has hampered larger initiatives for gathering collective data. The lack of funding is self-perpetuating: without abundant basic research, fewer drugs make it to translation, and fewer clinical successes are had, which in turn disincentivises investors and pharmaceutical companies from putting money into these conditions, which then means fewer people research it. This is changing however, with active calls for women’s health research and institutes broadening their focus beyond cancer and pregnancy and investors and pharma alike recognising the opportunity.
There are also unique social and societal barriers that are breaking down, but are still holding back a lot of the clinical development. Menstrual health and symptoms of pelvic pain have long been taboo, preventing diagnosis and treatment of endometriosis. We’re now in a situation where people are much more comfortable speaking about periods, although work still needs to be done. This means women are more likely to present to the doctor and to get a diagnosis, which is important in larger population-level initiatives that try and identify driving causes of the disease, for example using genetics.
Finally, there are scientific difficulties with the disease that render it difficult to study. Endometriosis involves otherwise thought to be healthy cells (endometrial cells) in a location where they shouldn’t be (outside of the uterus). Unlike cancer, they don’t seem to massively change in identity, which means that lesions are hard to target specifically. And unlike for many other organs and diseases that affect humans, mice are especially poor surrogates. Traditional widely-used mouse strains don’t menstruate or suffer from endometriosis. The lack of good models has been a major barrier to innovation, a problem that we are trying to address by focussing on replicating human tissue in a lab.
6. You’re using menstrual fluid donations for your models. Could you share more about how that process works?
We’re very interested in the potential of menstrual fluid to be a non-invasive source of biopsy-grade tissue, which would make endometrial disorders some of the best research topics for addressing chronic disease. Many results suggest that these cells may be the ones directly seeding lesions in the abdominal cavity too. We’re currently using menstrual fluid and traditional biopsies to explore the potential to better characterise the disease and better model it.
Beyond endometriosis, menstrual fluid should provide information on the health of a woman on a much broader basis. When something changes in the blood of an individual, this can mean it’s increasing (surplus) or decreasing (degradation) in a given tissue. With menstrual fluid, we may actually get a snapshot of the changes at their root. We may even get a signature of a given cycle. This offers a whole new scale to health monitoring: the ‘monthly’ scale which is likely to be a lot less noisy than if looking daily. And in working with women in understanding their individual cycles better through the collection of menstrual fluid, we also give them a chance to join us on our discovery journey and contribute to advancement in a field where they have so far felt very neglected.
7. Do you believe your tissue-level discoveries could help in earlier diagnosis as well as treatment of endometriosis?
Our discoveries and platform could potentially help with earlier diagnosis by focusing on a different scale of endometriosis – emergence at the tissue level. Indeed, we are investigating the tissue shed in menstrual fluid and the products shed from the tissue within the fluid. Menstrual fluid is an amazing resource in that it is the only non-invasive source of regular access to biopsy grade tissue and represents a novel method of disease surveillance. We believe that with this method and platform, along with the discoveries we make about the mechanisms of the disease, it is possible that indicators of the disease will emerge earlier and with higher confidence than current biomarkers being studied.
9. Congratulations on the £5M pre-seed round — how will this investment specifically help accelerate your research and platform development?
This investment will help grow both our data collection and model building arms, so that we can get to true human-level signatures of the disease, replicated in our 3D endometrial disease models. It will also help us develop some of the candidates we have in mind to test in these models to cure the disease.
Although an activity traditionally reserved to academia, start-ups are a great place for discovery science to happen. They are versatile, efficient and fast-paced with true translational focus. We think that this is the best place to address the translational gap in women’s health conditions like endometriosis. Given our early stage, pivots and rapid shifts in how we do things can be easily accommodated and even promoted. Venture capital funding and the expertise that comes with it is very conducive to this type of research.
Typically, start-ups take advantage of government-funded research grants at an early stage to help their transition from academic research into commercial applications in areas of unmet medical need. However, given the absolute need for accountability and safeguarding of such funding, this can often deter companies from being agile and open to the shifts in direction that are a critical part of scientific discovery. With this in mind, we hope to apply for grant funding in the future, especially on our larger data collection initiatives, but once we have established pipelines in place. This will empower us to scale robust ideas and more advanced pipelines.
