The Future of Medicine Is Being Built on Incomplete Biology
A new Nature Neuroscience commentary warns that phasing out animal research before female biology is well understood could lock historical male bias into the next generation of health innovation.
A few years ago, I sat in a doctor’s office and that experience marked the beginning of my journey into women’s health investing. Three years ago, I started writing what I thought was a report. It became a book about the gaps and opportunities in women’s health. Today, that book, The Billion Dollar Blindspot is available for pre-order.
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A woman takes a sleeping pill exactly as prescribed. Before bed, she swallows a standard dose of zolpidem, one of the most widely prescribed sleep medications in the world. By morning, enough of the drug remains in her bloodstream to impair reaction time, blur cognition, and increase the risk of car accidents on the drive to work.
For years, nobody fully understood why women were disproportionately affected. Then regulators discovered the problem was not the molecule itself. Women metabolized the drug more slowly. The dosage guidelines had been calibrated on a male biological model. Foundational pharmacokinetic studies had been conducted primarily in male animals.
It is the kind of story that sounds, in hindsight, impossible. How could something so basic have been missed?
For decades, biomedical research relied predominantly on male animals under the assumption that males were the “simpler” or “default” sex. Even after the NIH introduced its “Sex as a Biological Variable” policy a decade ago, neuroscience studies using only female animals remain extraordinarily rare, hovering at roughly 3%.
The future of medicine is being built on a biological model that was never fully representative to begin with.
The consequence is not merely academic. Our mechanistic understanding of disease pathways, stress responses, and drug metabolism is systematically more developed for male physiology than female physiology. That matters more than it sounds.
Modern therapeutics are built on mechanistic understanding. If the underlying mechanism is mapped primarily in males, the therapeutic itself is often implicitly optimized around male biology long before it reaches a human clinical trial.
Sometimes, in the real world, the drug fails because the biology behaves differently in women. Sometimes the drug works but produces adverse effects that were not detected during preclinical development. Both outcomes increase development costs, complicate regulatory review, and compress returns. The examples are already well documented.
And now, just as policymakers in Europe and the United States accelerate the transition away from animal research toward organoids, organ-on-chip systems, and AI-driven computational models, a more complicated problem is beginning to emerge.
The movement (the transition away from animal research) is framed, understandably, as ethical progress. New technologies — organoids, organ-on-chip systems, computational biology, predictive AI models — promise a future where medicine can advance with less animal suffering. It is an appealing vision, one which is sleek, humane and technologically elegant. But a recent commentary in Nature Neuroscience introduces a more uncomfortable possibility.
Kovlyagina and Jaric argue in the piece published in Nature Neuroscience that if animal research is phased out before female biology is adequately studied in vivo, the historical male bias embedded in biomedical research risks becoming structurally locked into the next generation of medicine itself.
Look deeper and you’ll see that this is not really a story about mice. This is a story about inheritance. Because systems rarely erase bias when they modernize. More often, they automate whatever assumptions already exist underneath them.
Artificial intelligence is perhaps the clearest example. Machine learning systems do not independently “discover” reality. They absorb patterns from historical data. If the underlying data reflects unequal representation, the outputs often reproduce those distortions with mathematical efficiency.
One example cited in the paper involved a deployed AI symptom-checking system that assigned lower urgency to some women’s reported symptoms because the clinical datasets used for training were themselves male-skewed. The machine was not intentionally discriminatory. The system inherited the structure of the data underneath it.
This is the paradox sitting quietly underneath much of the excitement around AI-driven healthcare. The technology itself may be revolutionary. But revolutions inherit infrastructure. And much of modern biomedical infrastructure was built during an era in which male biology was treated as the scientific default.
That distinction matters because modern healthcare is rapidly becoming data-driven. Diagnostic systems, drug development pipelines, predictive models, reimbursement frameworks, and AI-enabled clinical decision tools are increasingly dependent on historical datasets.
The risk is not merely that women were excluded from parts of twentieth-century biomedical research. The risk is that those exclusions become embedded into the operating system of twenty-first-century medicine. And this is where the essay in Nature Neuroscience becomes far more philosophically interesting than a standard debate about animal testing.
The authors are not arguing against technological progress. Nor are they dismissing the moral urgency of reducing animal suffering. Their argument is subtler and more unsettling.
A transition toward “animal-free” medicine is not ethically neutral if the underlying evidence base remains structurally incomplete for half the population. In other words: progress itself can carry blind spots.
From a capital allocation perspective, this creates a more stratified investment landscape than most investors currently appreciate.
Companies developing therapeutics in areas where female biology remains mechanistically undercharacterized face a different regulatory and scientific risk profile than companies operating in disease categories with more mature sex-inclusive evidence bases. Clinical endpoints become harder to define. Safety signals become less predictable. Regulatory pathways become more uncertain.
At the same time, companies prioritizing sex-inclusive preclinical work today may be building a form of long-duration advantage that the market is underestimating.
If in vivo research capacity contracts over the coming decade before these mechanistic gaps are adequately closed, the firms generating robust female-specific biological data now may ultimately control datasets, regulatory positioning, and intellectual property that competitors cannot easily recreate later using AI models alone.
That possibility changes the due diligence framework for allocators evaluating AI-enabled healthcare platforms or women’s health therapeutics. We cover this in greater depth in paid publication, Signal Not Noise.
Modern societies often assume innovation naturally produces fairness. But history suggests otherwise. Railroads expanded prosperity unevenly. Early clinical trials excluded women. Credit scoring systems inherited racial disparities. Facial recognition technologies repeatedly struggled with darker skin tones because the datasets underneath them lacked sufficient diversity.
Technology does not transcend human assumptions. It scales them. Which raises a larger question for medicine now. If the biological models underneath our healthcare systems were historically incomplete, what exactly are we scaling?
Perhaps the most striking aspect of this debate is how invisible this issue remains to most people. The phrase “women’s health” still evokes, in many institutional settings, a specialized or socially driven category rather than a foundational systems issue.
Yet the underlying challenge touches nearly every major frontier in medicine: neuroscience, longevity, metabolism, AI diagnostics, immunology, pharmacology, and preventive health.
The blind spot was never confined to one vertical. It was embedded in the baseline assumptions themselves, and baselines are extraordinarily difficult to notice while living inside them.
In the future now being imagined for medicine, the mouse may disappear soon. But the real question we should be asking is whether the blind spots disappear with the mouse.
On 28 May, I’m hosting a private conversation with some of the people who have lived this arc; operators who have built and exited in women’s health, and an investor who has backed multiple companies in the space. We will be talking about what it actually takes to build in this category, what the reimbursement and adoption curve looks like from the inside, and where the capital opportunity sits right now.
It is not a panel. It is a practitioner conversation and the kind that usually happens behind closed doors. If you want to be in the room, you can request an invitation below.
References
Kovlyagina, I. & Jaric, I. “Phasing out animal research prematurely will maintain gender inequities in medicine.” *Nature Neuroscience* (4 May 2026). DOI: [10.1038/s41593-026-02309-w](https://doi.org/10.1038/s41593-026-02309-w). Irina Kovlyagina, Institute of Physiological Chemistry, University Medical Center, Johannes Gutenberg University Mainz. Ivana Jaric, Institute of Laboratory Animal Sciences, University of Zurich.
Questions and Answers: Risk of next-morning impairment after use of insomnia drugs; FDA requires lower recommended doses for certain drugs containing zolpidem (Ambien, Ambien CR, Edluar, and Zolpimist) | FDA
Kovlyagina, I., & Jaric, I. “Phasing out animal research prematurely will maintain gender inequities in medicine.” Nature Neuroscience (2026).
NIH Office of Research on Women’s Health — “Sex as a Biological Variable (SABV)”
Arnegard ME et al. “Sex as a Biological Variable: A 5-Year Progress Report and Call to Action.” Journal of Women’s Health (2020).
Disclaimer & Disclosure
This content is for informational and educational purposes only. It does not constitute financial, investment, legal, or medical advice, or an offer to buy or sell any securities. Opinions expressed are those of the author and may not reflect the views of affiliated organisations. Readers should seek professional advice tailored to their individual circumstances before making investment decisions. Investing involves risk, including potential loss of principal. Past performance does not guarantee future results.
This is indeed a blind spot. Males and females respond differently to already approved drugs, and sex is often neglected as a biological variable when developing new therapeutics. In medicine, females often have different presentations (i.e. myocardial infarction) than males. Unfortunately, it is often easier (cheaper) to run preclinical efficacy studies in males only - and this is routine. Most scientists acknowledge the need to include sex as a variable in both mechanistic biology and drug discovery, however financial resources are often the limiting factor.
Would love to discuss this more with you.
This is a blind spot that we are purposely avoiding. Would love to chat more around this topic. I had such hope for AI, but see in my own care how it can fail us.