Let's Pool Our Medical Data for a Healthier Future

We all face the reality of illness at some point in our lives. The critical questions are: How severe will it be? Can we survive it? And can we effectively treat it? Throughout history, humans have sought explanations for why we get sick. Initially, explanations revolved around divine intervention, but gradually, we've moved closer to scientific hypotheses.

The Evolution of Medical Understanding

From Ancient Wisdom to Modern Science

Even in ancient times, figures like Avicenna (Ibn Sina) laid down principles for testing medicines that resonate with modern practices. His Canon of Medicine, written over a thousand years ago, emphasized the need for:

• Ensuring the disease and medicine are of comparable strength.
• Using pure medicines.
• Testing on human subjects.

Combining narrative, hypotheses, and human testing has yielded remarkable results, even with limited technology.

A Historic Breakthrough: Yellow Fever

Consider Carlos Finlay, a late 1800s scientist who hypothesized that mosquitoes, not dirty clothing, transmitted yellow fever. Despite facing ridicule for two decades, Finlay conducted experiments on human volunteers in Cuba. These volunteers lived in tents and were intentionally exposed to yellow fever. The study definitively proved that mosquitoes were the vector, not some mysterious substance in clothing. This breakthrough underscores the importance of human testing in medical advancements.

The Cornerstone of Modern Medicine: Informed Consent

Informed consent is a principle that separates ethical medical research from unethical experimentation. It asserts that agreement to participate in a study without full understanding is not true agreement. This safeguard protects individuals from harm and exploitation in clinical studies.

Clinical Studies: The Foundation of Medical Progress

Clinical studies, incorporating narrative, hypothesis, experimentation, and informed consent, form the bedrock of modern medical research. Whether in the North, South, East, or West, clinical studies are essential for investigating new drugs and treatments. These studies involve testing on human subjects, collecting data (like blood samples), and ensuring participants' consent to prevent exploitation.

The Changing Landscape of Medical Research

The Data Revolution

The world around clinical studies is evolving rapidly. We can now gather vast amounts of data about our genomes, environments, and lifestyle choices. Health is increasingly understood as an interaction between our bodies, genomes, choices, and environment. However, traditional clinical methods struggle to effectively study these complex interactions because they rely on person-to-person interaction.

The Problem with Silos

Informed consent, while crucial for protection, inadvertently creates data silos. Data collected for specific conditions, like prostate cancer or Alzheimer's, is often isolated and inaccessible to researchers outside those fields. This restricts collaboration and innovation, preventing physicists or computer scientists from accessing and analyzing valuable medical data.

The Cost of Data Isolation

The consequences of data isolation are significant. Facebook, for example, would never make changes to its advertising algorithm based on a sample size as small as a Phase 3 clinical trial. Yet, in medical research, we often cannot combine data from past trials to achieve statistically significant samples. This limitation hinders progress in combating diseases like cancer, which affects a large percentage of the population and has a high failure rate for treatments.

The Promise of Shared Medical Data

Measuring Ourselves: A New Era of Health Data

Fortunately, things are changing. We can now measure ourselves in ways previously confined to the healthcare system. This "digital exhaust," or the data generated by our daily activities, can provide valuable insights into our health. For example, tracking our food choices through simple photo apps can reveal how diet affects our well-being.

The Power of Genotype Data

Genetic testing provides clues about our predispositions to certain diseases. Sharing this information, along with blood work and medical records, can create a powerful data commons for research.

Building a Data Commons

A data commons is a public good built from voluntarily shared private data. It leverages standardized legal tools and technologies to create a resource that benefits everyone. Unlike privacy, which emphasizes control through restriction, sharing can be a form of control that fosters collaboration and innovation.

The Power of Collective Sharing

Digital commons don't require universal participation. Even a small percentage of contributors can generate massive and valuable resources, as demonstrated by the success of free software and Wikipedia. In biology, studies show that a vast majority of people are willing to share their bio samples for research when given the opportunity and choice.

Unlocking the Potential of Medical Data

The Role of Mathematics

Mathematicians are drawn to large datasets because they can identify subtle correlations and patterns. In healthcare, these correlations can reveal connections between lifestyle choices, genetic variations, and health outcomes. Open-source infrastructure is available to facilitate this research, but it needs data to function effectively.

A Call to Action: Be Unreasonable

The challenge is to overcome the barriers to data sharing and embrace a more collaborative approach to medical research. This requires a willingness to be "unreasonable" and challenge the status quo. Start by accessing your own medical data, even if it proves difficult. Share it if you feel compelled, especially if you or your family have been affected by illness.

The Future of Medical Research

The Athena Breast Health Network, a study of 150,000 women in California, is paving the way by returning data to participants in a computable form, making it easy to contribute to research. This initiative will reveal how many people are willing to be unreasonable and contribute to a data commons.

Ultimately, achieving spectacular results in healthcare doesn't require everyone's participation, just the dedication of a few willing to challenge the system and share their data for the greater good.