Reimagining clinical pathways for chronic diseases in women

We discover new ways for women to detect, diagnose and treat chronic diseases.

Initially, we are focused on chronic diseases that have an underlying hormonal component.

These "hormone diseases" include everything from Amenorrhea and PCOS, to Infertility and Menopause, and modulate depending on the age and stage of women.

Our research pipeline spans four verticals



Polycystic Ovary Syndrome

Polycystic Ovary Syndrome (PCOS) is the leading cause of infertility in women. It is associated with irregular cycles and hyperandrogenism, but because it is predominantly an endocrine disorder, it has several associated comorbidities such as diabetes, obesity and cardiovascular disease.

While it is estimated that 1 in 5 women worldwide are affected, this number is likely higher due to the multifactorial nature of this disorder masking accurate diagnosis.

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Gestational Diabetes

Gestational Diabetes Mellitus (GDM) is a form of diabetes that develops during pregnancy. Between 1% and 15% of pregnant women globally suffer with GDM, depending on the population studied.

GDM is closely correlated with metabolic diseases such as obesity and Type 2 Diabetes Mellitus (T2DM). More than 70% of women with GDM have an overweight or obese Body Mass Index (>25).

There is also a strong correlation between Polycystic Ovary Syndrome (PCOS) and GDM. In one study, 20.46% of women with a history of PCOS developed GDM versus 10.54% in women without a history of PCOS.

Research philosophy

Evidence-based, hybrid clinical research

We believe that some areas of women’s health will only improve if we are able to integrate digital health solutions with traditional healthcare to build smarter diagnostic tools and methods.

We are pioneering a new hybrid model of clinical research that uses machine learning to accelerate the discovery process, and a decentralised, peer-to-peer network for clinical research and best practice.

Interested in our research?

Contact us directly on [email protected] to learn more.