Kannapolis, North Carolina, is a desolate town, plagued by unemployment since the main employer, a textile mill, suddenly closed its doors eleven years ago. In the aftermath of this shutdown, an elderly billionaire, David Murdock, who is curious about longevity and its genetic secrets, turned an enormous piece of land into a lucrative biotech complex. Not so bad, you might think, to revive the local economy, but the new campus mostly employed highly skilled scientists from renowned universities, not Kannapolis.

To the Kannapolites, Murdock offered a deal: let me extract your DNA for research on personalized diagnostics and treatments and you will get a $10 Walmart gift card. Many residents took the deal, and handed over their biological materials for an unlimited time. Without the resources to pay for the expensive treatments and cutting-edge medicine that could come from their genetic material, ordinary residents of the town are unlikely ever to reap the benefits of supplying their blood, urine and personal information.

We may not all receive that gift card, yet we may all be Kannapolites.

Kannapolis is a poignant example of the dark side of the Data Revolution—the successor to the Industrial Revolution, with personal data as the new coal, oil or shale gas to be extracted or traded away, enshrined in an updated Faustian pact.

We don’t deny the power of aggregating data, particularly when the effort aims to advance medical research. But the Kannapolis story well epitomizes the inexorable inequalities on the path to personalized medicine. We must remain lucid about who will primarily contribute to and who will reap the promised health benefits that result from sharing our genetic and personal data. The way forward is to make sure that tomorrow’s biomedical enterprise helps those who are not part of the global wealthy minority.

The goal of personalized medicine is to tailor diagnostics and treatments to our individual genetic makeup, which will increase the rate of success in curing patients. In short, it means providing “the right patient with the right drug at the right dose at the right time.”

Yet, these ambitions collide with hard truths. Geneticists realize that before they can personalize diagnostic tests and cures, they have to decode the complex machineries behind our genes and their variants. To do so, they need a lot of data—not only genetic, biological and clinical but also lifestyle information—about a lot of individuals from diverse backgrounds.

The second hard truth is that personalized medicine will only succeed if pharmaceutical companies adopt a business model allowing them to develop diagnostics and therapies targeted to a patient's own genetic mutations—something very different from how they operate today. Bringing a drug to market is already a slow, incremental and extremely expensive process; personalizing it will only make it more so. The other murky side of this medical revolution  therefore, is the question of  who will be able to pay for accessing its promised benefits.

What is troubling here, as we enter the age of personal genomics, is that we face an increasing socio-economic disparity between the elites and the majority of citizens— data-provider ones. In a healthcare model where everybody contributes their most intimate data, it could merely be a wealthy few reaping the benefits of this collective endeavor.

Economic status is still a distressing hurdle not only to trials but also to disease detection and treatment. If data-driven medicine requires citizens to share their biological information, and be proactive about their health future, we should ideally help them gain access to the most sophisticated genetic counseling, prevention care and cutting-edge trials and treatments. The cost of genetic counseling and testing can range from under $100 to over $2,000, depending on what tests are required and what health insurances cover. Many targeted cancer therapies can cost thousands of dollars per month. These financial hurdles are significant when health insurers restrict access to tests and treatments considered too expensive or unnecessary.

The success of personalized medicine will depend on our capacity to empower patients by lowering the economic and financial barriers to benefiting from the best course for prevention or care. One option is working with health insurance companies to modify approval and reimbursement processes, thus facilitating access to genetic tests and targeted therapies. If the “right drug” exists, we would have to appeal to a form of health solidarity – an important but controversial notion in today’s health politics.

There is no easy “tech or policy fix” to democratizing medicine. We should unveil the diverse forms of inequality – who has access to knowledge and care, who drives the biomedical research agenda – and question the motives of those who seek data commodification for corporate profit, but forget to share tangible benefits with the data-providers. We believe that the first step should focus on citizen empowerment by helping individuals from different abilities and resources understand and lucidly act upon the complex information contained in their genes.

Yet, taking an increasing role in their own diagnosis and treatment is a complex, even insurmountable challenge, for some groups within society. Educating citizens in personalized medicine is a start, but the health divide will never be closed solely by education. It also requires including in the biomedical enterprise the need and voices of those at the margins, the underprivileged, the elderly and rural populations as well as immigrant communities.

As we witness an increasing individualization of medicine, we see the development of patient-led research powered by social networks, where families discover biological explanations for diseases, look for cures, and receive psychological support. Some groups of patients even use crowdsourcing platforms to accelerate clinical trial recruitment, test new treatments and share data on diseases that have been neglected by commercial research. Benefits go beyond the patient cohort: for example,PatientsLikeMe provides services to the pharmaceutical industry that allow them to “listen” to patients on their medications in real-world setting while allowing submission of adverse event data to the U.S. Food and Drug Administration.

Will tomorrow’s medicine privilege only well off, educated groups who can leverage resources in favor of their medical interests and needs? Not if we think creatively about how to help leaders in health research manage public expectations for more equality in access to the promises of personalized medicine. Social networks of patients are only part of the answer, though a powerful one as it bets on inclusiveness, diversity, and knowledge-sharing. It brings the “social” – as a form of solidarity – back into big-data-driven medicine. Such empowerment will thrive if those at the sharp end of personalized medicine start a conversation with the public. With such discussion on our collective health futures, we might all gain in the process for once.

The opinions expressed here are solely those of the authors.

This article was originally published in Scientific American.