Who Owns Your Future?

What 23andMe Revealed About the Business of Prediction

For most of modern medical history, healthcare has been built around the treatment of disease. A patient develops symptoms, seeks evaluation, receives a diagnosis, and begins treatment. While this process remains familiar today, it is easy to overlook how dramatically the timing of intervention has shifted over the past several decades. Increasingly, medicine has moved upstream.

Consider, for instance, the evolution of cancer screening. Cervical cancer was once diagnosed primarily after symptoms developed, often at a stage when treatment options were limited. The introduction of the Papanicolaou (pap) smear fundamentally altered that trajectory by allowing clinicians to identify dysplasia before invasive cancer emerged. Similar transitions occurred with mammography, colonoscopy, and other screening modalities. The objective was no longer simply to treat disease. Instead, the objective became finding disease before patients knew it was there.

The impact of that shift cannot be overstated. Earlier detection frequently leads to earlier intervention, lower treatment costs, and improved outcomes. Entire industries have emerged around the concept that identifying disease sooner creates value for both patients and healthcare systems. In many respects, screening represents one of the greatest success stories in modern medicine.

Yet screening may not represent the final destination.

Increasingly, healthcare companies are pursuing something even further upstream. The goal is no longer simply to identify disease before symptoms develop. The goal is to estimate the probability that disease will develop, if they develop at all. If screening asks what is happening today, prediction attempts to answer what may happen tomorrow.

Viewed clinically, this is a remarkable ambition. Viewed commercially, it may represent one of the most significant business opportunities in modern healthcare.

A Simple Sample

When 23andMe launched in 2006, its value proposition appeared relatively straightforward. Consumers submitted a saliva sample and, several weeks later, received information about ancestry, geographic origins, inherited traits, and genetic relatives. The experience felt part science, part entertainment, and part personal discovery. Millions of individuals participated.

The public conversation largely focused on ancestry, answering the question “where did I come from?”

Television commercials featured family histories, unexpected ethnic backgrounds, and long-lost relatives. Consumers were encouraged to explore their past, uncover forgotten stories, and better understand where they came from. For many individuals, the transaction seemed remarkably simple: a company provided a report, the customer learned something interesting, the relationship ended.

Or so it appeared.

Consumers thought they were simply buying a report of ancestry. In reality, they were also contributing to one of the largest privately assembled genomic databases in the world. Every saliva sample generated information far beyond ancestry alone. Embedded within those samples were clues about disease susceptibility, medication metabolism, inherited conditions, and biologic traits that scientists were only beginning to understand.

Over time, it became increasingly apparent that the report may not have been the most valuable product. The database itself was.

Unlike cholesterol levels, blood pressure measurements, or hormone panels, genomic information remains relatively stable throughout life. A cholesterol value may be useful for months. A genome may remain useful for decades. More importantly, genomic information often becomes more valuable as scientific understanding improves. A DNA sequence generated in 2015 may reveal considerably more in 2035 than it did when it was first collected.

The saliva sample was the transaction consumers saw. The dataset became the asset investors valued.

When the Company Changes Hands

The distinction between product and asset remained largely theoretical until 23andMe encountered financial difficulty.

Like many healthcare-adjacent technology companies, 23andMe faced the challenge of converting an impressive scientific platform into a sustainable business model. Consumer interest in ancestry testing eventually plateaued. Growth slowed, and investor enthusiasm cooled. What had once been one of the most recognizable names in consumer genomics found itself confronting the same economic realities faced by countless other startups.

Then came a question that many consumers had likely never considered.

What happens to a genomic database when the company that owns it enters bankruptcy?

Initially, Regeneron emerged as the winning bidder for 23andMe’s assets. Shortly thereafter, however, founder Anne Wojcicki returned with a higher $305 million bid through TTAM Research Institute, a nonprofit organization she controls, ultimately regaining control of substantially all of the company’s assets, including its genomic database. TTAM subsequently pledged to maintain existing privacy protections and establish additional consumer privacy oversight mechanisms.

The outcome itself is less interesting than the public reaction it generated. Attorneys general from more than two dozen states challenged aspects of the sale process, raising questions about whether consumers had truly consented to the transfer of genetic information in the event of bankruptcy. Privacy advocates urged customers to consider deleting their data. Suddenly, a conversation that had long remained theoretical became very real.

That distinction may prove increasingly important as healthcare becomes more data-driven. Genomic information is not merely another business asset. It is deeply personal, biologically permanent, and potentially valuable for generations. Unlike a prescription history or laboratory result, genomic information can reveal details not only about an individual, but about biological relatives as well.

The Prediction Economy

If 23andMe represented the business of ancestry, the next generation of genomic companies appears increasingly focused on prediction.

Rather than helping consumers understand their past, these organizations are attempting to help consumers understand their future. Advances in genomic sequencing, artificial intelligence, and large-scale data analysis have created growing interest in polygenic risk scores, predictive health modeling, and personalized medicine. The objective is no longer simply to identify inherited traits. The objective is to estimate future risk.

Women’s health may be uniquely positioned within this emerging prediction economy.

Many conditions that affect women contain genetic components, even when the underlying biology remains incompletely understood. Breast cancer risk can be influenced by BRCA mutations and other genetic variants. Osteoporosis demonstrates significant heritability. Endometriosis frequently clusters within families. Similar observations have been made with polyendocrine metabolic ovarian syndrome, premature ovarian insufficiency, and numerous reproductive disorders.

Historically, clinicians have attempted to estimate these risks through family history. Questions about a mother’s age of menopause, a grandmother’s osteoporosis, or a family history of breast cancer have long served as imperfect proxies for genetic information. Genomic prediction promises something considerably more precise.

Imagine, however, estimating future osteoporosis risk decades before bone density begins to decline.

Imagine forecasting reproductive lifespan before fertility becomes a concern.

Imagine combining genomic information with biomarkers, wearable data, and artificial intelligence to generate continuously updated estimates of future health trajectories. Whether these capabilities fully materialize remains to be seen. The commercial appeal, however, is obvious.

Women spend enormous amounts of time attempting to understand what their future health might look like. Questions surrounding fertility, menopause, cancer risk, cardiovascular disease, cognition, and longevity drive billions of dollars in healthcare spending each year. A company capable of reducing uncertainty surrounding those questions possesses an extraordinarily compelling value proposition.

The Subscription Inside the Prediction

One of the most interesting aspects of predictive medicine is that the prediction itself may ultimately be the least important component of the business model.

Historically, diagnostic testing generated revenue through a relatively simple transaction. A laboratory performed a test, produced a result, and delivered a report. The value was largely contained within that single interaction. Prediction operates differently because prediction creates a future relationship rather than a present answer.

Consider a woman who learns she has an elevated lifetime risk of osteoporosis. The information itself is useful, but the real value emerges from what follows. Should she begin earlier screening? Does she require additional biomarkers? Would changes in exercise, nutrition, or medication alter her trajectory? A single prediction naturally generates a series of subsequent decisions.

The same pattern appears throughout healthcare. Elevated breast cancer risk may lead to enhanced imaging pathways. Cardiovascular risk may lead to preventive therapies and longitudinal monitoring. Fertility-related predictions may influence family planning decisions years before conception becomes a priority. In each scenario, the prediction serves as a starting point rather than a conclusion.

This should sound familiar.

Many healthcare companies have already moved beyond isolated transactions and toward ongoing engagement. As I’ve discussed before, menopause platforms have evolved beyond hormone prescriptions. Fertility companies increasingly support multiple stages of reproductive life. Healthcare organizations across the spectrum are recognizing that recurring relationships often create more value than episodic encounters.

Viewed through that lens, genomic prediction aligns naturally with broader healthcare trends. The test becomes the front door. The relationship becomes the business.

Who Owns Your Future?

The idea of predicting the future has long occupied science fiction and speculative literature. In the film Minority Report, for example, individuals are arrested for crimes before they occur based upon predictions generated by the PreCrime system. In the novel The Giver, society attempts to eliminate uncertainty through centralized control of information. Even the decidedly pulp-culture film Equilibrium imagines a future in which the perceived risks of human behavior justify increasingly intrusive systems of oversight. While these stories differ substantially in their details, they share a common tension: the relationship between predictive knowledge and personal autonomy.

Modern genomic prediction is obviously far removed from these fictional worlds. No company can predict an individual’s future with certainty, nor are genetic risk scores equivalent to destiny. Yet the popularity of these narratives reflects a persistent discomfort with predictive information. The more accurately we can forecast future outcomes, the more complicated our relationship with uncertainty becomes.

Consider a woman who learns at age thirty that she carries elevated genetic risk for osteoporosis, cardiovascular disease, or cognitive decline. The information may prove valuable. It may influence exercise habits, screening decisions, family planning, or preventive care. At the same time, it may alter how she views her future long before any disease actually develops. Prediction does not simply influence medical decisions. It can influence perception.

This may ultimately represent the most interesting aspect of the prediction economy. The value of predictive information is not merely that it forecasts future events. The value lies in its ability to influence present behavior. For healthcare companies, that influence creates opportunities to improve outcomes. It also creates opportunities to build products, services, and long-term relationships around the management of risk itself.

The rise of 23andMe demonstrated that consumers were willing to exchange genetic information for insight into their past. The next generation of genomic companies is asking a far more ambitious question: will consumers exchange that same information for insight into their future?

The science will continue to improve. Predictive models will become more sophisticated, new companies will emerge, and novel business models will follow. Yet the debate surrounding 23andMe demonstrates that society is still struggling to define what genomic ownership actually means. Even after the company returned to its founder’s control, the questions surrounding privacy, consent, and stewardship remained.

If our genomes become one of the most valuable assets we possess, the most important question may not be what our DNA can predict. It may be who is entrusted to hold that prediction once it exists.

© 2026 Corey R. Babb, DO, FACOOG, IF, MSCP. All rights reserved.