Researchers from Endogene.bio at the Hospital Clinic in Barcelona are also studying diagnostic approaches for endometriosis using menstrual blood samples; teams at Eth Zurich, a renowned public research university in Switzerland, have developed a diagnostic menstrual pad that’s still in early clinical testing but will theoretically be able to record markers that can indicate cancer, endometriosis, and general inflammation; and last year saw the establishment of the Fairbairn Menstruation Science Fund at MIT, which will be devoted to using menstrual blood to diagnose endometriosis and other gynecological disorders as well as chronic systemic inflammatory diseases that more commonly impact women.
While endometriosis is a common focus for many in the menstrual blood space, both on the science and start-up side, the researchers interviewed for this piece posit that the same approach could be applied to uterine fibroids, endometrial hyperplasia, adenomyosis, PMDD, lupus, various cancers, and even fertility. Lacob already envisions their menstrual fluid data being able to reveal vital information about the ovarian environment, giving insights into not just the quantity, but the quality of eggs, a frequent blind spot in fertility care.
What We Still Don’t Know About Period Blood’s Power
All of this points to a promising future, but we may now be at the all-too-common point where companies eager to innovate are selling something before the evidence that it really works has been fully substantiated. And moving quickly requires some efficiency tactics. Xella’s platform, for example, is powered by AI. Its bot ingests and analyzes the data from a patient’s bloodwork, then makes recommendations (for follow-up testing, medications, etc), then that is all reviewed by a human physician. The use of AI in this context is concerning to some researchers in the menstrual science space because “AI is only as good as what it can train on and there is not much literature that they’re going to be able to access about menstrual blood,” says Metz. According to Xella founder Lacob, its bot has been fed female-specific clinical guidelines, published literature, and resources to be able to evaluate where there are diagnostic gaps. So it’s looking for lab values that are out of range, but also bigger patterns, says Lacob, then reporting on probable risks and how confident it is about them, plus providing clinical back-up.
