Who will make money if hormone monitoring moves from occasional tests to daily care?

Hormone monitoring aims to measure the body’s chemical messengers often enough, and accurately enough, to change what a person or clinician does next. It brings together fields that developed separately: laboratory science, consumer fertility tests, wearable sensors, virtual care and hormone medicines. The opportunity has drawn attention as regulators reopened menopause care, home tests became quantitative and investors backed sensors aspiring to replicate for hormones the convenience continuous glucose monitors brought to diabetes. Yet the established businesses remain laboratory assays, repeat fertility-test strips and clinician-led care. The first durable profits are therefore more likely to accrue to companies selling validated recurring consumables and to care networks that translate results into sound decisions—not to every app or wearable capable of producing a hormone-shaped graph. Hormone replacement therapy (HRT) is the central caveat: better access to menopause care may expand treatment, but routine serial hormone testing is generally not how menopause therapy is selected or adjusted today.

The invisible signals in a Bronx basement

In 1960, two researchers at the Bronx Veterans Administration Hospital in New York published a method for something medicine had long sought but never achieved: measuring insulin directly in human blood at the minute concentrations at which the body uses it.¹ Rosalyn Yalow was a physicist; Solomon Berson was a physician. Their tools were radioactive insulin, antibodies and patience.

Yalow had travelled far to reach that bench. Born in the Bronx in 1921, she earned a doctorate in nuclear physics at the University of Illinois when few women entered the field. She brought to medicine a physicist’s instinct for tracing tiny quantities with radioactive labels.² Berson brought the clinical questions. Their partnership lasted more than two decades.

Their method can be pictured as musical chairs. An antibody has a limited number of binding sites shaped for one molecule—in this case, insulin. Researchers add a known amount of radioactively labelled insulin, then a patient’s blood. The patient’s unlabelled insulin competes for those sites. More insulin in the sample leaves more labelled molecules unbound, and a radiation counter measures the difference. Compared with known standards, that count yields a concentration. But the analogy ends at the bench: accuracy depends on calibration against reference material, whether an antibody confuses similar molecules with the target, and how a sample was collected and stored.

The method was called radioimmunoassay, and its importance extended well beyond diabetes. Physicians had long known that hormones govern reproduction, growth, metabolism and responses to stress. They could not, however, routinely count them. Endocrinology had been a discipline of inference: doctors observed symptoms and reasoned backwards to a gland. Yalow and Berson made it a discipline of numbers. In 1977, Yalow received the Nobel Prize in Physiology or Medicine for radioimmunoassays of peptide hormones; Berson had died in 1972 and was ineligible to share it.²

The prize also carried a lesson that still applies. Measuring a hormone does not establish what to do with the result. A number needs a reference range, a demonstrated relationship to disease and a decision that changes because of it. Half a century later, that gap between measurement and action still determines who gets paid.

The factory and the forensic lab

Radioimmunoassay produced two important descendants. The first is the modern immunoassay: the factory version. Antibodies still do the recognition, but light-emitting or enzyme labels have replaced most radioactivity. Automated analysers in hospital and commercial laboratories can process thousands of samples a day. Immunoassays are fast, inexpensive per test and well suited to larger protein hormones, including thyroid-stimulating hormone and the pituitary hormones FSH and LH.

The second is liquid chromatography tandem mass spectrometry, or LC-MS/MS: the forensic version. It separates molecules in a sample, then weighs and fragments them, identifying a hormone by its mass signature rather than by antibody binding. It is slower, requires skilled staff and more sample preparation, and costs more to establish. But it can better distinguish chemically similar steroid hormones, including estradiol and testosterone, at low concentrations. The factory-and-forensics analogy has limits: neither method is best for every use. The appropriate choice depends on the clinical question, specimen and laboratory workflow.

A number is only as good as its calibration

The accuracy problem persisted. The US Centers for Disease Control and Prevention runs a hormone standardisation programme through which manufacturers and laboratories can compare testosterone and estradiol results with a reference method.³ The programme exists because a CDC review found that results for those hormones could vary markedly among methods and laboratories, owing to inconsistent calibration and insufficient assay specificity at low concentrations.⁴

This unglamorous problem sits upstream of every consumer-facing claim. Antibodies, calibrators, sample-preparation kits, instruments and reagents determine whether a hormone number is meaningful. The companies supplying them form the first link in the value chain.

The heirs

Roche is a prominent modern heir to Yalow and Berson’s ambition of making difficult measurements routine. In December 2024, the Swiss group launched its cobas Mass Spec solution, an automated mass-spectrometry system intended for ordinary hospital laboratories, with a steroid-hormone panel among its first tests.⁵ The commercial proposition is to bring the forensic method closer to the factory floor.

Other suppliers occupy adjacent positions. Siemens Healthineers $SHL.DE, Danaher $DHR through its Beckman Coulter business, Abbott Laboratories $ABT, Revvity $RVTY, the Italian specialist DiaSorin $DIA.MI, Japan’s Sysmex and QuidelOrtho sell automated immunoassay analysers and the reagents used on them.⁶ Thermo Fisher Scientific $TMO and Agilent Technologies $A make the mass spectrometers, chromatography systems and consumables used by reference laboratories for high-specificity steroid work; Agilent’s latest annual report described a reorganisation that placed diagnostics alongside its LC and LC-MS platforms.⁷ Bio-Rad Laboratories supplies diagnostics and quality-control materials that laboratories use to demonstrate continued accuracy.⁸ None reports hormone testing as a material business segment.

It is tempting to conclude that automated mass spectrometry will make personalised hormone care routine. The history of standardisation suggests patience. Automation can remove labour and workflow bottlenecks, making a precise estradiol result faster and less expensive. It cannot create a clinical reason for repeated testing or establish the treatment target against which successive results should be judged. Those depend on clinical evidence, which tends to arrive more slowly than laboratory equipment.

Before hormones could move from laboratories into daily life, one test had to show that ordinary people would buy, perform and trust a private biological measurement.

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The test that left the laboratory

Late in 1977, American pharmacists received a letter from Warner/Chilcott introducing e.p.t., the Early Pregnancy Test.⁹ An answer that had required a doctor’s visit and laboratory work could now be bought in a box and read at home. The idea was a decade old: in 1967, Margaret Crane, a designer at the drug company Organon, sketched a simple home kit after seeing pregnancy tests performed in the company’s laboratory.⁹ It took another ten years, and a new regulatory framework, for such kits to reach American shelves.

The pregnancy test succeeded commercially because it answered a narrow question that led to a clear decision. It detects hCG, human chorionic gonadotropin, a hormone produced after embryo implantation. Its presence signals a specific biological event. Unlike a broad wellness score, a positive pregnancy test can prompt a doctor’s appointment and a change of plans. That clarity established a template: an intimate urine sample, a simple readout, pharmacy distribution and a recurring consumable.

Two routes for a test

Regulation helped shape that template. The Medical Device Amendments of 1976 gave the US Food and Drug Administration a framework for reviewing devices, including diagnostic kits, according to their intended use, instructions and reliability.⁹ Twelve years later, Congress passed the Clinical Laboratory Improvement Amendments of 1988, or CLIA, establishing quality standards for laboratories that test human samples.¹⁰ Tests considered simple enough to pose a low risk if performed incorrectly can be “waived”; waived tests include FDA-cleared home-use products, though the CDC notes that waived does not mean error-proof.¹¹

The result was two routes. One sends samples to regulated laboratories, with trained staff, quality control and reference methods. The other clears limited-use products for home testing for a specified purpose. The distinction matters because consumer hormone products may be marketed more broadly than the uses for which their tests have been cleared.

From a line to a curve

Fertility testing was an obvious next market. Ovulation strips detect the surge of luteinising hormone, or LH, shortly before ovulation. Clearblue, the brand of Swiss Precision Diagnostics, built global retail distribution around repeat purchases of pregnancy and ovulation tests.⁶

A newer group of companies turned the strip into a data stream. Mira, Inito, Oova and Proov sell readers—often linked to a phone—that quantify hormones in urine rather than simply displaying a line.⁶ Mira’s Ultra4, launched in August 2025, reads four hormones from one strip: LH, FSH, and urinary breakdown products of estrogen and progesterone known as E3G and PdG.¹² Proov focuses on PdG to confirm ovulation; Oova targets fertility and polycystic ovary syndrome.⁶

E3G and PdG can be useful cycle signals because they rise and fall over time and urine is easy to collect at home. But they are metabolites: products excreted after the body breaks hormones down. They reflect levels over preceding hours, and urine concentration can affect the reading. They are not interchangeable with blood estradiol or progesterone results. Treating them as equivalent confuses measurements from different specimens and time windows.

The business model is familiar: a reader supports repeat strip sales. Fertility monitoring, however, has a natural ceiling. Users may conceive, stop trying, change methods or conclude that they have enough information. High margins on strips therefore do not necessarily translate into high lifetime value when the reason to test is temporary.

Panels in the post, and the next wave

Everlywell and LetsGetChecked took a different route, selling mail-in kits that consumers use to collect a sample at home before a laboratory performs the analysis.⁶ They brought laboratory-style hormone panels to people who had not sought a doctor’s test. But a panel taken once remains a snapshot.

Two younger companies illustrate the market’s next ambitions. Eli Health sells a saliva test, the Hormometer, beginning with cortisol and positioning it as a wellness product rather than a substitute for clinical testing.¹³ Level Zero Health raised $6.9m in pre-seed funding in February 2025 to develop a wearable intended to sense hormones continuously in interstitial fluid, the fluid surrounding cells beneath the skin.¹⁴ Neither had established a clinical monitoring business by September 2026.

What "lab-quality" can and cannot mean

The phrase “lab-quality at home” carries substantial weight in this market; Mira used it in launching Ultra4.¹² It is the company’s claim. Even a technically accurate measurement may be taken at the wrong time of day or point in the cycle, misunderstood or irrelevant to a decision the user faces. Home testing has earned durable trust when it answers a single question clearly, as pregnancy tests do. Mira’s launch was a product event, not independent validation of every interpretation its app might attach to the results; none of these companies publishes retention data showing how many users continue testing beyond their first few cycles.

The most consequential hormone market, however, did not begin in a pharmacy aisle. It began with hormone medicines and was reshaped by a trial that made a generation of doctors and patients wary of them.

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The trial that froze a market

On 31 May 2002, the data and safety monitoring board of the Women’s Health Initiative recommended stopping one of the largest hormone trials ever run.¹⁵ The estrogen-plus-progestin trial, which began recruiting in 1993, enrolled 16,608 postmenopausal women aged 50 to 79 who still had a uterus.¹⁵¹⁶ After an average of 5.2 years, the board concluded that the measured health risks outweighed the benefits.¹⁶ Results published that July in the Journal of the American Medical Association reached a global audience.

The figures mattered because their interpretation shaped what followed. Compared with placebo, women taking the combined tablet had more heart attacks, strokes, blood clots and invasive breast cancers, but fewer hip fractures and colorectal cancers.¹⁶ For every 10,000 women using the therapy for a year, the trial estimated seven additional coronary events, eight additional strokes, eight additional pulmonary emboli and eight additional invasive breast cancers, alongside six fewer colorectal cancers and five fewer hip fractures.¹⁶ Small absolute differences became consequential when applied across millions of women. In March 2004, the estrogen-alone trial in women who had had a hysterectomy was also stopped early after an increased stroke risk and no coronary-heart-disease benefit.¹⁵

How menopause became a drug market

Estrogen therapy for hot flushes, night sweats and other menopausal symptoms had been a large pharmaceutical market for decades before WHI. Progestogens were added for women with a uterus to protect its lining. The trial tested one daily tablet combining conjugated equine estrogens with medroxyprogesterone acetate, then the most widely prescribed regimen.¹⁶

The clinical decision was never simply whether a blood level was “low.” Estrogen falls at menopause in every woman. The relevant questions were, and remain, whether symptoms, age, time since the last period, uterine status, contraindications, delivery route and personal risk supported treatment.

What the trial showed, and what it did not

WHI provided strong evidence about one regimen in one population: women aged 50 to 79, many years past menopause.¹⁶ It was not a verdict on every dose, route, formulation or patient. Later analyses and professional guidance distinguished women near menopause from older women further beyond it. The Menopause Society describes hormone therapy as an evidence-based option for defined indications, including troublesome hot flushes, and warns against misinformation about its risks and benefits.¹⁷

Both parts of the record matter. The original findings were real, as was the later conclusion that the balance of benefit and risk varies by patient, timing and treatment.

The aftershock

Prescribing fell, branded franchises lost momentum, and concern about hormone therapy became embedded in clinical practice and public discussion. Pfizer $PFE and Bayer $BAYN.DE, long-standing makers of branded hormone products, and privately owned specialists including Theramex and Besins Healthcare, which focus on women’s health and estradiol and progesterone therapies, operated in a market whose assumptions had changed rapidly.⁶

Today’s listed drug groups connect to the theme differently. Viatris $VTRS, Amneal Pharmaceuticals $AMRX and Teva sell generic and specialty medicines, including hormone products; their performance depends on volume, formulary access and generic competition.⁶¹⁸ Organon $OGN, spun out of Merck in 2021, has the group’s most direct women’s-health heritage, with contraception and fertility products including Follistim AQ and Elonva; it carries the same Organon name associated with the early home pregnancy test.¹⁹ AbbVie $ABBV sells Orilissa and Oriahnn, hormone-modulating treatments for endometriosis and uterine fibroids rather than menopause HRT.²⁰ None discloses revenue tied to hormone monitoring.

The data gap at the heart of HRT

For routine menopause care, the most useful information is usually already available: symptoms and medical history. What is not missing is a blood level that determines whether to prescribe. The American College of Obstetricians and Gynecologists (ACOG) says routine hormone testing before menopausal hormone therapy is not recommended because levels fluctuate during the menopausal transition, while symptoms and history guide treatment. It also says saliva and urine hormone tests are not FDA-approved for this purpose.²¹

The harder missing evidence is longitudinal and linked: which symptoms improved, on what formulation and dose, with what adherence, bleeding, sleep, other medicines, adverse events and long-term outcomes, in comparable populations. Such data could improve treatment research. They would not support consumers adjusting prescription hormones based on an app.

The opposite overstatement is also wrong. Targeted hormone testing has clinical value in selected diagnostic, reproductive and endocrine settings, and ACOG’s guidance on compounded therapy recognises defined exceptions in which serum measurement can help.²² The narrower conclusion is that routine test-led HRT adjustment remains unproven, even as hormone assays retain important clinical uses.

Two decades after WHI, regulators reopened the question of how these medicines should be discussed, creating a catalyst for consultation and care, though not necessarily for testing.

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The warning comes off, but the blood test does not become a compass

On 12 February 2026, FDA Commissioner Marty Makary announced that the agency had approved revised labels for six menopausal hormone-therapy products.²³ The boxed warnings—the black-bordered alerts at the top of prescribing information—would no longer include statements about cardiovascular disease, breast cancer and probable dementia that had appeared since the WHI era.²³

The change had been building. In late 2025, the FDA asked manufacturers to revise their labels after reviewing the scientific literature, saying it wanted safety information that better clarified the balance of benefit and risk.²⁴ Supporters portrayed the decision as a correction to two decades of excessive fear. More narrowly, it was a revision to how the agency communicates risk. The new labels still include contraindications and product-specific warnings; clinicians must still consider each patient’s history, route of administration, formulation and reason for treatment.²³

Why it matters, and what it leaves unchanged

For this theme, the label change is a meaningful turning point. Removing a prominent warning may reduce a barrier for appropriate candidates and for clinicians trained amid the post-WHI caution. That could generate more consultations, prescriptions and follow-up visits.

It does not, however, create a new reason to test. The FDA did not give a consumer product an indication for selecting a hormone dose, and its decision did not establish that a wearable can diagnose a hormonal condition. Any resulting demand flows first to care: someone must assess the patient, review her history and prescribe where appropriate.

The care companies

Several companies have positioned themselves to meet that demand.⁶ Midi Health and Evernow are privately held virtual menopause clinics whose clinicians consult, prescribe and follow up. Maven Clinic sells reproductive and family-health support, including menopause services, to employers and health plans. Noom, known for weight management, has extended into menopause-related care. Among listed companies, Hims & Hers Health $HIMS combines consumer marketing, telehealth and pharmacy operations, and has been expanding in women’s health. Teladoc Health $TDOC operates virtual primary-care and chronic-condition programmes for employers and insurers.²⁵ Neither company separately discloses hormone-therapy revenue.

The human bottleneck

The scarce input is qualified clinician time. A hormone result needs interpretation in the context of a patient’s history, medicines and risks before it can guide a decision. That interpretation is also where legal and safety responsibility lies. The most defensible recurring-care model combines consultation, safe prescribing, follow-up and pharmacy fulfilment. A dashboard alone provides none of them.

Testing the telehealth story

The financial record tempers the enthusiasm. Hims reported 2025 revenue growth of 59%, to $2.3bn, showing the reach of its consumer-acquisition and prescribing model.²⁶⁶ But it does not disclose women’s-health revenue, and its 4.5% operating margin leaves less room for error if customer-acquisition costs rise. Teladoc reported $2.5bn of 2025 revenue, down 1.5% from a year earlier, and does not report hormone care separately.⁶ For both companies, the evidence supports an argument about distribution: each has users and an established prescribing infrastructure through which menopause care could pass. It does not show that menopause care is yet a material driver of either business.

The data that could actually improve protocols

Better HRT protocols require specific, longitudinal data rather than more charts: structured symptom records; route and formulation; adherence and refill persistence; blood pressure and other relevant safety signals; bleeding patterns; and outcomes from clinician-supervised studies. Wearable data on sleep, skin temperature and activity may add context, particularly when night sweats disrupt sleep. None is a pharmacokinetic target—a measured drug level with a known therapeutic range that guides dosing for some other medicines.

Testosterone illustrates how demand can outrun evidence. No testosterone product is FDA-approved for menopausal women, despite growing off-label interest, and in August 2026 the FDA published a Federal Register notice concerning its use in menopausal women.²⁷ Evidence remains limited on dosing, safety monitoring and outcomes—the areas in which better measurement could eventually help, but has not yet been validated.

As clinicians reconsidered care pathways, consumer technology found a different route into the body: contextual signals gathered each night rather than chemistry.

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A ring can hear the weather, not the molecules

A woman goes to sleep wearing an Oura ring. Overnight, its sensors record skin temperature, heart rate and sleep. In the morning, the Natural Cycles app can use the ring’s temperature trend to assign a fertility status for the day.²⁸ The experience can resemble hormone monitoring, but it is principally an inference from contextual signals.

Basal body temperature is an after-effect. After ovulation, progesterone raises resting temperature by a fraction of a degree until the next period. Tracking it is like seeing wet streets and inferring rain: useful evidence, but indirect. Physiology complicates the inference. Fever, alcohol, disrupted sleep, late nights and long-haul travel can shift temperature for reasons unrelated to reproduction.

Software as a regulated product

Natural Cycles turned that indirect signal into a regulated medical device. The Swedish company was founded by physicists Elina Berglund Scherwitzl and Raoul Scherwitzl, who developed an algorithm to identify fertile days from temperature readings. In 2018, the FDA cleared it as a contraceptive app, the first such clearance.²⁹ The decision showed that software, rather than a chemical assay, could receive regulatory recognition for a defined reproductive-health use. In 2021, Natural Cycles began accepting temperature data from the Oura ring, allowing users who wear it to forgo a morning thermometer.³⁰ Its 2025 accounts reported revenue of SEK 512m, or about $52m: a meaningful business, though small beside major device makers.⁶

The context layer

Oura, Clue, Apple $AAPL, Samsung Electronics and Garmin $GRMN comprise the context layer.⁶ Their products collect temperature trends, cycle logs, sleep, activity, symptoms and medication records. Their advantage is daily data collection from people already wearing or carrying devices; that context may also help interpret a hormone result. None measures estradiol, progesterone or testosterone. The Oura–Natural Cycles integration illustrates how layers can connect, with one company’s sensor supplying another’s algorithm. But interoperability is not evidence of clinical benefit, and neither company has disclosed a revenue-sharing arrangement.²⁸

Distribution is the context layer’s principal asset. Samsung reports 77 million active users of its health platform.⁶ Apple does not separately disclose Apple Watch or health revenue. Garmin does report results: 2025 revenue rose 15.1% to $7.2bn, while its operating margin reached 25.9%, the highest among wearable makers that disclose comparable figures.⁶ Those profits came from fitness, outdoor and other devices, not hormone sensing.

The glucose precedent

The strongest case for hormone sensing draws on diabetes. In 1999, the FDA approved Medtronic MiniMed’s continuous glucose monitor, the first in the United States; Dexcom’s first sensor followed in 2006.³¹ Early systems required calibration against fingerstick tests and were used mainly alongside them. Broad adoption followed years of improving accuracy and accumulating clinical evidence.³¹

Dexcom $DXCM now illustrates the sensor business model: a wearable that samples interstitial fluid, a consumable replaced every week or two, software and clinical interpretation. In 2024, it launched Stelo, the first over-the-counter glucose biosensor in the United States, for adults who do not use insulin.³² Senseonics pursued an implanted alternative; its Eversense 365, cleared by the FDA in September 2024, lasts a year.³³

The economics show both the potential and the cost of reaching scale. Dexcom’s 2025 revenue rose 15.6% to $4.7bn, and its operating margin reached 19.6%, up from about 11% in 2021.⁶ Senseonics grew revenue 57%, but from a $35m base, while its operating loss was almost twice its revenue.⁶ Dexcom has shown that a sensor-and-consumable model can be profitable at scale. Senseonics shows how capital-intensive and prolonged the route to scale can be.

Why "a CGM for hormones" is harder

The glucose comparison needs qualification. Glucose circulates at millimolar concentrations; sex hormones in blood are measured in picomoles or nanomoles, millions of times less concentrated. Much of each sex hormone is bound to carrier proteins, and the relationship between interstitial-fluid and blood levels remains uncertain. Hormones also pulse and cycle across hours, days and months. Most importantly, glucose has established action thresholds: a reading can tell a person with type 1 diabetes whether to take insulin or eat. Estradiol in a menopausal woman using HRT has no comparable threshold.

A continuous hormone sensor would therefore need to solve chemistry, interference, calibration, interstitial-fluid behaviour and clinical usefulness simultaneously. Level Zero says it is working with research partners on its interstitial-fluid platform.³⁴ Its financing demonstrates investor interest, but it has not produced a commercial result. Dexcom and Senseonics provide precedents for manufacturing, reimbursement and adoption of body-worn sensors. They do not establish that continuous sex-hormone sensing works, and neither earns revenue from measuring sex hormones.

The question therefore shifts from what a user sees to what must happen behind the scenes for a signal to become a clinical answer.

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Where a number becomes a prescription

Follow one blood sample. A woman in her late forties, with irregular periods and poor sleep, has blood drawn at a patient service centre on her way to work. Her doctor has ordered a thyroid test and other checks to rule out causes besides menopause. A courier takes the tube to a regional laboratory, where it is scanned, logged and spun. An automated analyser, using reagent packs and quality-control samples, runs the tests. Results enter an electronic report and appear on the clinician’s screen. The clinician considers them alongside her symptoms, history and risks; decides on treatment; sends a prescription to a pharmacy; and schedules follow-up.

That journey contains the value chain.

Walking the chain

At the start are the inputs: antibodies, calibrators, reagent packs, mass spectrometers, sample-preparation kits and the software that runs them. This is the layer served by Roche, Siemens Healthineers, Beckman Coulter, Abbott, Thermo Fisher, Revvity, DiaSorin, Sysmex, Bio-Rad, Agilent and QuidelOrtho.

Next come collection and analysis. Quest Diagnostics $DGX and Labcorp $LH in the United States, Australia’s Sonic Healthcare $SHL.AX and SYNLAB, a private European network owned by the investment firm Cinven, operate collection centres, courier networks, laboratories and reporting systems.⁶

Apps can then add context: the date of the last period, symptoms, medicines, temperature, sleep and cycle history.

Only then can a clinician determine whether the information changes a diagnosis, counselling, prescription, timing or follow-up. Pharmacies and drug manufacturers supply treatment. In principle, outcomes and adverse events inform the next decision. In practice, that feedback loop remains the chain’s weakest link.

Where the money settles

The mature profit pool is near the start of the chain. Each sample uses controlled inputs, and laboratories that have validated a platform are reluctant to change it. Switching requires revalidating tests, retraining staff and managing potential differences from prior results. Bio-Rad’s annual report describes the model: laboratories standardise on platforms and then buy the associated kits and consumables, making much of its clinical-diagnostics revenue recurring.⁸ This switching cost protects suppliers whether a sample is tested for hormones or cholesterol.

Laboratory economics differ. Quest, Labcorp, Sonic and SYNLAB own collection routes, payer contracts, logistics, clinician-ordering links and high-throughput operations. Hormone panels are a small, undisclosed part of their menus. Their profits depend on test volumes, reimbursement, labour costs and acquisitions. Labcorp’s second quarter of 2026 illustrated the distinction: total requisitions rose 3.0%, organic requisitions rose 1.8%, and price and mix added further revenue.³⁵ Reported revenue growth, therefore, did not reflect test demand alone.

The home route

A second route bypasses the phlebotomist. Everlywell and LetsGetChecked send kits whose samples still go to regulated laboratories. Mira, Inito, Oova and Proov sell readers and strips that analyse samples at home. Clearblue sells simpler tests to the mass market. Home collection removes the trip to a collection centre, but it still relies on proper sample collection, the limits of each product’s cleared claims and appropriate interpretation.

The care and medicine route

At the far end, specialist platforms can own the patient relationship and follow-up, while drug suppliers may own a branded formulation, a generic manufacturing position or a pharmacy channel. The care provider, rather than the sensor maker, generally bears responsibility for screening contraindications and monitoring safety. That responsibility raises costs but can also create a defensible position.

What the data say about the links

Empor’s links table tests whether the layers move together. The clearest relationship is between laboratories and their suppliers: when combined clinical-laboratory revenue grows faster, assay-supplier revenue growth has tended to improve roughly two quarters later, with five of the six suppliers tested showing the pattern.⁶ The mechanism is plausible: more tests consume more reagents, while suppliers receive orders after laboratories see the volume. bioMérieux shows no such link, consistent with its focus on infectious disease. The pattern covers only a few years of results. It is evidence rather than proof, and it says nothing specific about hormones.

Other links are weaker. Laboratory growth does not consistently flow through to therapy companies. Viatris has tended to move with it, while Amneal and Teva have moved against it, because their broader generic portfolios overwhelm any hormone signal.⁶ The most obvious demographic measure also fails the test. The number of American women aged 45 to 54 in the labour force, a rough proxy for the working population most affected by menopause, was 15.8 million in the second quarter of 2026, essentially unchanged from a year earlier.⁶ Revenue growth across laboratories, assay suppliers, wearables and care platforms has tended to move against that series rather than with it; only Teva moves as the theme would predict. Demographics make the potential market sizeable. They do not, by themselves, create growth.

Will data cut out the laboratory?

A common claim is that home data will disintermediate the laboratory. Laboratories retain meaningful advantages: reference methods, quality systems, broad test menus, reimbursement and clinicians’ trust. The more plausible near-term outcome is a hybrid, in which home collection and apps feed laboratories and care teams rather than replace them.

Once the chain is visible, the meaningful contests become clearer: which layer can sustain repeat revenue and convert a novel signal into an action.

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The quiet contest for the reagent drawer

When a hospital laboratory chooses an immunoassay platform, it commits to years of service contracts, reagent deliveries, quality controls, staff training and a defined test menu. The analyser is only one part of the purchase. That quiet decision by laboratory directors and purchasing committees turns hormone measurement into an installed-base business.

The contenders

Roche and Siemens Healthineers compete on menu breadth and automation: the ability to run chemistry, immunoassay and, increasingly, mass spectrometry on connected laboratory lines. In July 2026, Roche described its US effort to place high-precision instruments, including its mass-spectrometry workflow, in routine laboratories.³⁶ Thermo Fisher and Agilent compete where specificity is most important, supplying the LC-MS/MS systems that reference laboratories use for difficult steroid measurements. Beckman Coulter, Abbott, Revvity, DiaSorin, Sysmex, Bio-Rad and QuidelOrtho compete through immunoassay menus, quality-control products, service and purchasing relationships.

Company size does not equal hormone exposure. Siemens Healthineers was the largest company in the assay layer by reported revenue, with €23.4bn, about $25.8bn, in the year to September 2025 and a 14.7% operating margin.⁶ Most of that revenue came from imaging and other businesses unrelated to hormones. Roche’s diagnostics division recorded CHF 13.8bn in 2025 sales, up 2%, while Abbott’s diagnostics sales fell 4.5% to $8.9bn.⁶ Hormones remain an undisclosed line item for both.

The smaller specialists have closer ties to immunochemistry. DiaSorin’s LIAISON platform includes specialty immunoassays for endocrine and vitamin D testing, while Sysmex, better known for blood-cell analysers, has built an immunochemistry line called HISCL.³⁷³⁸ Neither reports hormone-only revenue. DiaSorin had the highest operating margin among assay companies with full accounts, at 25.5% in 2025, but revenue rose only 0.8%. Its market value fell from about $10.9bn at the end of 2021 to $4.4bn as pandemic testing receded.⁶ Sysmex’s revenue slipped 1.7% in the year to March 2026, following four years of double-digit growth.⁶

Bio-Rad’s clinical-diagnostics segment illustrates the recurring-consumables model: $1.6bn of revenue, up 1.6% in 2025, supported by laboratories that have built quality-control routines around its products.⁸ QuidelOrtho illustrates the limitation. It operates the VITROS laboratory platform and has a large installed base, yet 2025 revenue fell 1.9%, its net loss equalled 41.5% of revenue, and its market value shrank to about $705m.³⁹⁶ An installed base alone does not ensure attractive economics.

Two boundary cases

Hologic appears central to the theme because of its women’s-health focus. But its diagnostics business, which generated $1.8bn of revenue in the year to September 2025, relies mainly on molecular tests; it is also a major breast-imaging supplier. Neither business constitutes a recurring hormone-assay franchise.⁶ Blackstone and TPG completed their acquisition of Hologic on 7 April 2026, after which its shares stopped trading.⁴⁰ Its results now sit outside public markets.

bioMérieux $BIM.PA is the other boundary case: a large diagnostics company focused chiefly on infectious-disease testing, making it a misleading proxy for hormone monitoring.⁶

The laboratory contest

Further down the chain, Quest, Labcorp and Sonic compete through network economics rather than proprietary hormone science. Quest’s 2025 revenue grew 11.8%, with a 14.5% operating margin and roughly 2,250 patient service centres. Labcorp grew 7.2%, with a 10.9% margin, while Sonic grew 13.5% in its year to June 2026.⁶ Those results reflected broad testing volumes, acquisitions, price and mix—not a disclosed hormone-testing trend.

Both US leaders remained below their pandemic-era profitability, when Quest’s operating margin reached 22.1% and Labcorp’s reached 23.2%.⁶ Route density and payer access are the central competitive assets. On disclosed margins, Quest has executed better than Labcorp, and its lead has persisted for four years. That gap, however, says nothing specific about hormones.

Investors have rewarded Quest’s relative steadiness. Its price-to-earnings ratio rose to about 24 times from 11 times at the end of 2021.⁶ That valuation can be explained by resilience in the broader laboratory business; it does not require a hormone-monitoring thesis.

The consumer contest

The home market remains unsettled. Clearblue has global retail distribution. Mira and Inito offer quantitative, multi-hormone readings paired with repeat-strip sales, while Oova and Proov address narrower uses. Eli and Level Zero remain technology options rather than commercial peers. The key commercial measure—how many users continue buying strips after their first few cycles—is not reliably disclosed by any of them.⁶

How durable are the prices?

The claim that consumables always win needs qualification. Immunoassays face hospital procurement pressure and competition from laboratory-developed tests. Mass spectrometry may offer greater specificity, but it is capital- and labour-intensive; higher throughput could reduce the price of each test as readily as it increases volume. Consumer products also carry marketing costs and serve fertility journeys that often have a natural end.

A narrower proposition holds: consumables can be attractive when the installed base remains useful, the assay remains trusted and replenishment grows faster than prices decline. The assay layer’s combined revenue grew about 2% in the latest fiscal year, suggesting durability rather than rapid expansion.⁶

A daily data stream could create a new profit pool, but only for a company that earns trust to interpret it and retains the relationship beyond the first prescription.

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The care platforms want to own the follow-up

A woman opening a menopause telehealth app after months of poor sleep and hot flushes is not principally seeking a chart. She wants a clinician who will listen, a plan, perhaps a prescription and someone to contact if treatment does not help. That bundle is the product.

Specialists against aggregators

Two models compete for that relationship. Focused providers such as Midi and Evernow build their clinicians, intake and follow-up around menopause.⁶ Larger platforms approach the same patient through other routes. Maven reaches people through employer benefits; Noom through weight-management coaching, where menopause-related weight changes provide a bridge; Hims through direct-to-consumer marketing and its pharmacy; and Teladoc through health plans and employers that already pay for virtual care.

Why care may capture more than measurement

Care is where symptoms, contraindications, treatment preferences and follow-up meet. A laboratory can reproduce a validated test result; a trusted clinical relationship, multistate licensure, payer contracts and an outcomes record are harder to replicate. Care may therefore capture more value than measurement because it holds the decision.

Clinician supply remains the constraint. A focused provider depends on trained clinicians and patient trust, and can expand only as quickly as it hires. A large platform can distribute more quickly but may find it harder to reproduce specialist protocols and outcomes.

What the financial record allows

Hims has the stronger disclosed growth record, though its figures temper the headline. Gross margin—the share of revenue remaining after product and fulfilment costs—fell to 73.8% in 2025 from 82.0% in 2023. Its market value of about $6.3bn equates to 57 times trailing earnings.⁶ Those are demanding expectations for a company whose menopause business cannot be measured externally.

Teladoc’s record is less favourable. Its market value fell from $14.4bn at the end of 2021 to $1.1bn, and its shares traded at about 0.6 times revenue despite free cash flow of about 11% of revenue.⁶ Its Integrated Care segment earns access fees from employers and insurers for virtual and chronic-care services.²⁵ Neither company is a pure HRT investment; menopause care could expand while either stock still disappoints.

Where the drugmakers stand

Drugmakers sit at the end of the chain. A differentiated formulation—a patch, gel or ring, a newer molecule, or a product supported by its own safety evidence—can preserve economics, as can favourable formulary placement. Generics may gain volume, but competition limits much of the upside.

Organon’s Women’s Health franchise generated $1.78bn of revenue in 2025, down about 1%; that total includes contraception, fertility and products beyond menopause.¹⁹ Teva, with $17.3bn of revenue growing 4.3%, Viatris, whose $14.3bn of revenue fell 3.0% alongside a large net loss, and Amneal, which grew 8% on $3.0bn of revenue, are diversified generic and specialty drugmakers. Hormone products are a small, undisclosed share of each portfolio.⁶ Bayer’s pharmaceuticals division grew 1.7% to €17.8bn.⁶ AbbVie’s reproductive-condition drugs and Pfizer’s long-running hormone products provide context, not evidence of monitoring-led revenue. Gedeon Richter, the Budapest-listed drugmaker with a substantial women’s-health business, belongs in the same discussion, though its disclosures could not be compared with the others on a like-for-like basis.

The pattern is consistent: if menopause care expands, drug volumes may rise, but the economics will favour the holder of a defensible product rather than the monitoring company that prompted the visit.

The compounding question

Compounded “bioidentical” hormones, mixed by pharmacies for individual patients, rest on an appealing proposition: that measured hormone levels should determine each woman’s dose. That proposition elevates consumer testing. ACOG’s clinical consensus provides the counterweight. It advises against using saliva, serum or urine hormone tests to individualise compounded menopausal therapy because levels vary and do not reliably track symptoms; it also notes that compounded products lack the safety and efficacy testing of approved medicines.²² “Personalised” and “measured more often” are different ideas, and care providers must enforce that distinction.

The bull and bear cases agree that people want more information. They differ on whether that information changes safe decisions often enough to justify its cost.

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The promise is not a dashboard

Picture two mornings a few years from now. In the first, a woman opens an app, sees a hormone-trend chart, finds it interesting and changes nothing. In the second, a validated measurement identifies an avoidable problem, a clinician acts, the patient improves and a subsequent measurement confirms that the decision worked. The investment question is the distance between those outcomes.

The bull chain

For the second outcome to become common, several links must hold. A sensor or home test must measure hormones accurately and repeatedly without a blood draw, perhaps in saliva or interstitial fluid. Its results must be reproducible against reference methods of the kind maintained by the CDC programme. It must secure a cleared clinical intended use from regulators, who review diagnostic tests as medical devices according to their claims.⁴¹ Prospective studies must then show that it changes decisions and improves outcomes. Payers or employers must fund it, and a company must build a viable loop of sensor, consumable and care around it. If those conditions are met, value could shift from central laboratories towards sensor consumables, data standards and care coordination—broadly the model Dexcom established in glucose monitoring.

The bear chain

The bear case is equally specific. Measuring low hormone concentrations may remain difficult outside laboratories. Signals may not map reliably to decisions. Consumers may stop buying strips once a short-term question has been answered. Regulators may limit broad claims, while specialist capacity remains constrained. Menopause care could expand through symptom-led consultations rather than testing. In that scenario, laboratories, assay suppliers and therapy providers retain the cash flow, while continuous hormone monitoring remains a small wellness category.

The HRT test

HRT is where the promise meets the clinical record. The premise is that daily estrogen or progesterone data could make HRT adjustment as straightforward as using glucose readings to dose insulin. Current care is guided principally by symptoms and risks. Hormone levels fluctuate during the menopausal transition; formulations and delivery routes produce different blood profiles; and no established target ranges tell a clinician that a dose is right in the way glucose ranges can guide insulin decisions. The proposition remains unproven. Establishing it would require the outcome trials that no company has yet reported.

What could move the money

Four developments could shift where profits accrue. Automated mass spectrometry in routine laboratories could make precise steroid measurement inexpensive enough to order when clinically relevant. Independent validation of frequent saliva or interstitial-fluid sensors could establish a clinical use beyond fertility. Employer-funded menopause benefits could reduce patient-acquisition costs for specialist providers. And trials linking treatment exposure to symptoms and safety outcomes could create protocols that give a measurement a defined role in care.

Privacy underlies all four. Reproductive and hormone data are especially sensitive. Useful longitudinal datasets require consented sharing among apps, laboratories, clinicians and researchers; a breach or misuse could lead users to withhold the data on which the bull case depends.

The evidence standard is therefore clear. A useful signal must precede revenue, and evidence must distinguish a testing habit from a clinically useful measurement—and a useful measurement from a durable improvement in care.

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Four signals before the sales line moves

Evidence must arrive in sequence: reliable measurement, repeated use, clinical action and lasting outcomes. Four signals track that progression.

Repeat tests per retained home-monitor user. This shows whether a reader becomes a habit. Strip reorders appear in customer cohorts before they can materially affect reported sales, making them an early test of whether home monitoring is a recurring business or a one-off purchase. As of September 2026, Mira, Inito, Oova, Proov and Eli did not reliably disclose the measure; as private companies, they release such figures selectively, often around funding rounds.⁶ Replenishment that continues beyond the first few fertility cycles would support the recurring-revenue case. Rising device sales with weak strip reorders would undermine it.

Routine-laboratory steroid testing by mass spectrometry. This indicates whether high-specificity testing is moving from specialist settings into routine laboratories. Instrument placements precede reagent revenue, so the measure would show whether automated mass spectrometry can become a broader consumables business or remains a premium niche. Roche reported US commercial progress in July 2026, but its annual and quarterly disclosures included neither placements nor hormone-reagent revenue.³⁶ Disclosed placements, throughput and reagent pull-through, corroborated by independent laboratory uptake, would support the case. A broader menu without routine use would not.

Organic laboratory volume. This measures whether demand for testing is rising, rather than revenue being lifted by prices or acquisitions. It has tended to lead assay-supplier orders by one or two quarters. Labcorp and Quest report requisition data quarterly; Labcorp’s organic requisitions rose 1.8% in the second quarter of 2026.³⁵ Quest was due to report next on 20 October and Labcorp on 27 October.⁶ Sustained organic growth accompanied by a disclosed endocrine or women’s-health mix would support the theme. Growth driven chiefly by pricing, acquisitions or unrelated tests would not.

Menopause-care starts, persistence and outcomes. This would show whether easier access is producing appropriate, durable care rather than a short-lived increase in consultations. Treatment starts and persistence precede prescription revenue, but no comparable public measure existed as of September 2026. Specialist providers, payers and registries were the likeliest sources, and may report only annually. Clinician-supervised evidence on appropriate starts, persistence, symptom relief and adverse-event monitoring would support the case; rising consultations without adherence or outcome data would not.

No demographic series or company-wide revenue beat can answer a question this narrow. These four signals could.

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The companies that sell certainty will be paid first

Yalow and Berson turned an invisible molecule into a number. The remaining challenge is to turn that number into a better decision, reliably enough that patients, clinicians and payers will pay to repeat it.

The earliest and most dependable revenue is therefore likely to remain with companies that sell validated certainty: assay-reagent makers; laboratories whose quality systems and networks produce trusted results; and specialist care providers that can safely turn data into treatment and follow-up. Sensor consumables could join that group only if frequent hormone sensing is independently validated and shown to improve care.

Branded therapies may benefit if access to menopause care expands. Generic drugmakers may gain volume without securing comparable economics. Large wearable and telehealth platforms have distribution and optionality, but their disclosures do not show a material hormone-monitoring profit pool today. A sound theme can still produce poor returns when investors pay for the wrong layer.

The winning technology will not necessarily be the one that measures the most hormones or produces the most frequent readings. It will be the one that resolves a decision reliably enough to earn repeat use.

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Glossary

• Antibody: A binding protein used in immunoassays to recognise a target molecule; it can also bind similar molecules.
• Assay: A laboratory method for measuring the amount of a substance in a sample.
• Calibration: Aligning a test result with a known reference so results can be compared across runs and laboratories.
• CLIA: The US framework for certifying and overseeing the quality of clinical laboratory testing.
• E3G: Estrone-3-glucuronide, a urinary estrogen metabolite used in fertility tracking.
• FSH and LH: Follicle-stimulating hormone and luteinising hormone, pituitary hormones used in reproductive and endocrine assessment.
• HRT/MHT: Hormone replacement therapy, also called menopausal hormone therapy.
• Immunoassay: An antibody-based testing method designed for high-throughput laboratory use.
• Interstitial fluid: Fluid between cells, sampled by continuous glucose monitors and proposed for use by some hormone-sensor developers.
• LC-MS/MS: Liquid chromatography tandem mass spectrometry, a high-specificity measurement method.
• PdG: Pregnanediol glucuronide, a urinary progesterone metabolite.
• Reagent: A chemical, antibody or calibrator consumed each time a laboratory runs a test.
• Therapeutic drug monitoring: Measuring drug levels to guide treatment; that logic does not automatically apply to menopausal hormones.