A Digital Future For Women’s Health

I spent some time with the excellent Women’s Health Investment piece by @chrissyfarr et al (https://ovsecondopinion.substack.com/p/why-were-betting-big-on-womens-health). At the risk of mansplaining women’s health, some observations, with an Ob/Gyn/reproductive endocrinologist bias:

The article is spot on that women’s health is only now emerging from healthcare’s analog past — what I leaned in med school, residency and fellowship decades ago. While oncology and immunology have taken advantage of the Rosetta stones of. genetics, and increasingly epigenetics, to more precisely define and stratify disease entities, women’s health (like neurology and psychiatry) remain analog disciplines — diagnoses relying on pattern-recognition “I know it when I see it”/“clinical judgement” disciplines.

Invariably this leads to lumping together different entities into imprecisely defined patient populations, which in turn leads to heterogeneous clinical trial populations, difficulty in powering studies and overall inefficiency in discovery and development. Which in turn makes rational investing in the space more difficult.

One of the most important lessons of the “classroom” portion of med school is learning how our bodies are bioengineered to perform different functions, and how that design makes discovery easier or more difficult. The GI tract, for example, needs to freely communicate with the outside world — so its easy to get inside and biopsy and retrieve different types of cells without disrupting normal function.

Contrast that with the CNS when we study cognition, or the brain/ovary/uterus during. conception and early pregnancy. Nature did a good job protecting these systems — which makes them very tough to study on a cellular and/or molecular basis. So we are left with ill-defined and handicapped-from-the-beginning projects like Alzheimer’s disease (“age-associated decline in cognition agnostic to cause”), and in women’s health…

…pre-eclampsia, premenstrual syndrome, polycystic ovarian syndrome, dysmenorrhea, symptoms related in an ill-defined way to peri-menopause and menopause, as well as the baffling way that endometriosis can cause symptoms so inconsistently from one patient to the next.

These ill-defined entities lead to systemic, non-targeted therapies. And in women’s health, much of our treatment involves turning the menstrual cycle on and off, the mechanism of just about every drug for cycle regulation, uterine fibroids, endometriosis, contraception and fertility. Oral contraceptives, GnRH agonists, and GnRH antagonists all converge on the prevention (or stimulation) of ovulation, and therefore stopping the cyclic release of estrogens and progestins by the ovaries. Not quite key-in-the-lock precision medicine.

Reading through the paper a few times, I really appreciate how the authors (in addition to @chrissyfarr, @lesliejz, @lilymshaw, @deenashakir — who I keep encountering whenever innovation in women’s health is discussed at a high level) stress the need to collect more data. They get that we need more stuff to measure — and that technology will enable us to circumvent some of our bioengineered defenses. Particularly gratifying to see the shout-out to @pirayebeim and @celmatix — old friends in which we are proud investors.

In 2012 I made my own Ideas I’d Like To Fund list for women’ health. Lots of overlap here — and a prediction that women’s health will be the fastest growing and most innovative corner of the healthcare world for the next ten plus years.




bio fund manager, Columbia prof, ex-reproductive endocrinologist, roadie for @PriyaMayadas

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Know Your Potential Patients Before Your Competition Does

A little less conversation a little more action: healthcare and behavior change

Decide For Yourself

Regrow Hair Naturally In 3 Weeks — My Personal Experience

What Happens When Your Body Clock is Broken

Rare Disease Day 2022: A Recap

~>Free Download Ultrasound: The Requisites, Second Edition (Requisites in Radiology) Full-Acces

Are We Dumbing Down Clinical Decision Making in Healthcare?

Robot representing artificial intelligence

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
David Sable

David Sable

bio fund manager, Columbia prof, ex-reproductive endocrinologist, roadie for @PriyaMayadas

More from Medium

Mateo Price Has The Launch Codes

Women In Marketing 2021 Edition ft. Mrunal Kshirsagar from Perfect Skills

Your Guide to Preparing a Winning NSF SBIR/STTR Proposal

The Importance of Promoting Innovation