Why Women's Health Technologies Remain Biased ?

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La Femtech, or technologies specifically designed to improve women's health, is a growing field. However, it still faces many biases resulting from systemic issues that primarily affect women.

Women lack time to participate in clinical trials

This is the observation of Kim Brunel and Frédéric Jallat, shared in an editorial published in Les Échos. The first is interim CEO and head of operations at Nova Gray, a company specializing in the development of tests for predicting tolerance to radiotherapy. The second is professor and scientific director of the MSc Pharmaceutical and Biotechnology Management – ESCP Business School.

The two experts denounce the limits that are still too present in femtech, a sector which has nevertheless evolved a lot in recent years. In 2022, investments in this area reached $19.7 billion, according to Bpifrance. Despite growing interest in start-ups developing this type of technology, access to health data specific to women remains insufficient.

For many years, clinical trials aimed at developing treatments only took men into account. The inclusion of women only became mandatory in France in 1997. Unfortunately, many obstacles still remain for them to participate in these trials, mainly due to a lack of time and resources.

Kim Brunel and Frédéric Jallat first cite the mental load. ” 63 % of women feel they are victims of a harmful mental load, compared to only 36 % of men », write the experts, citing a study by the Ipsos institute. Added to this is precariousness. In Europe, in-work poverty mainly affects women, who represent more than 70% of low-income workers. The situation is particularly worrying for single-parent families, 85% of which are headed by women.

Algorithms in femtech are also affected

Similarly, the experts cite biases also affecting animal testing, which precedes testing on human patients. In addition to predominantly using male specimens during testing, researchers are apparently not taking into account the hormonal specificities of females, which are nevertheless crucial.

“The production of estrogen in females complicates clinical variables, and tests are often carried out outside of periods or ovulation“, explain Kim Brunel and Frédéric Jallat. However, hormonal factors have an impact on the development of diseases.

The sexist biases of artificial intelligence (AI), already denounced in several studies, must also be taken into account. The technology is used in the algorithms that underlie applications dedicated to women's health, which also creates a concern for bias.

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