An Urgent Call to All Scientists - We Must Reframe Scientific Priorities for the Future of America with A Unified Approach to Learning Well

Robert F. Kennedy Jr.'s new team will define the next one hundred years of flourishing and thriving in America. I propose we use the tools of science for understanding and comprehension.

It is October 2024, and we face a crossroads. Science and medicine are represented as advancing at breakneck speed, but the way we fund and prioritize research is outdated, fragmented, and deeply flawed. We are chasing immediate results, throwing resources into short-term translational projects, and turning blind eyes to risk and externalized costs while neglecting the foundations of discovery and innovation. This imbalance is robbing us of the opportunity to address the root causes of the most significant challenges we face: chronic illness, environmental degradation, and the now decades-long shift from learning to earning.

It’s time for a new vision. One that recognizes the need for balanced, integrated research—a vision that unites the National Institutes of Health (NIH), the National Science Foundation (NSF), the Environmental Protection Agency (EPA), and other agencies in a shared mission. One that leverages the immense power of technology and machine learning to reinvigorate basic research and ensure that ethics remain at the heart of all we do. This is an urgent call to action. We can no longer afford to operate in silos. Cross-pollination among agencies and scientific disciplines to optimize how science learns must be the cornerstone of our approach.

Reclaiming the Power of Basic Research

Basic research has been woefully undervalued for too long, seen as a luxury rather than a necessity. Yet the most remarkable medical and technological innovations have grown from the soil of basic science. Without new discoveries in the fundamentals of biology, physics, and chemistry and all of their subdisciplines, we cannot hope to solve the complex problems of chronic illness or environmental decay.

Consider EvoDevo, the once-thriving field of evolutionary developmental biology. It promised to unravel the mysteries of how genes and environmental factors interact to shape development, providing insights into everything from congenital disorders to cancer. I would have expected that over the last 20 years we would have seen a massive number of very important resources, like video libraries and development-period specific development biopathways databases linked to functional molecular knowledge databases. It sounds simple - because it is. The impact on research done in the public interest would have been profound. That is not to imply that significant work has not been published in EvoDevo, but Pubmed only includes abstracts from 195 papers that mention “EvoDevo” and “regulatory” (as in “regulatory network” or “regulatory function”. We could have done better. The National Science Foundation should not be led astray on priorities on basic research, which has so much potential.

We have not even started to reach that potential. Like so many fields, basic research for the sake of knowledge has been starved of funding, sidelined by the rush to apply headlines, ROIs, and immediate solutions. The potential was there - and still is - to create vast developmental atlases, biopathway databases, and detailed models of developmental programs that could inform everything from regenerative medicine to disease prevention. Yet, we left basic research languishing. What could we have learned for the sake of knowledge?

In return for the huge investment in translational research, we have record levels of chronic illness, with monies squandered on the search for the next blockbuster drug. The consequences of this neglect are profound. Chronic illnesses such as heart disease, diabetes, and autoimmune disorders are often rooted in early developmental processes. Without a deeper understanding of these roots, we’re treating symptoms while ignoring causes. Imagine what could be achieved if we revitalized basic research across fields, using the lessons of EvoDevo to address the underlying mechanisms of chronic illness. This our societal ethical imperative.

Cross-Pollination: Integrating Environmental, Evolutionary, and Medical Sciences

Medical research alone cannot solve the challenges ahead. Our health is inextricably linked to the environment, and it's time we acted on that truth. For decades, the EPA has been narrowly focused on climate change. While vital, climate is not the only factor affecting human health. Pollution, toxic chemicals, and environmental degradation are insidiously driving an epidemic of chronic diseases—from respiratory disorders to cancer to neurodevelopmental conditions.

The NSF, NIH, and EPA must learn to learn together, breaking down barriers between their domains. The NSF must dramatically increase its investment in environmental toxicology and basic methylation responses to environmental toxins, studying how pollutants interact with all aspects of human biology in real-time. The EPA must coordinate its research with the NIH, understanding that protecting the environment is also about preserving the human genome and epigenome from the assault of toxic exposures. We need basic research on inexpensive and effective approaches to detoxifying soils, planets, resource streams, and people.

We need cross-agency initiatives that prioritize human health holistically. The pollutants in our air and water are as much a part of the chronic illness equation as diet and genetics. By creating integrated programs that unite researchers from all three agencies, we can not only slow the progression of environmental destruction but also mitigate its effects on public health.

Technology and Machine Learning: The Fourth Pillar of Progress

Technology is already reshaping the landscape of medicine, but we are only scratching the surface of what’s possible. Machine learning, artificial intelligence, and big data are poised to revolutionize healthcare—offering predictive diagnostics, personalized treatment plans, and insights that human researchers could never uncover alone. But we must invest in this potential now, or risk falling behind.

The future of medicine is machine-learning-optimized. These systems have the power to analyze vast datasets of genetic, environmental, and clinical information, detecting patterns that will guide us to the root causes of disease rather than just treating symptoms. Yet, we cannot approach this recklessly. Ethical oversight is critical to ensure these tools are used with minimal risk to patients - which, if studied overtly, becomes part of the objective function). The knowledge base from publicly funded research must be shared fairly and transparently.

Imagine the possibilities: Machine learning algorithms that predict how a disease will progress and how pollutants in a specific region exacerbate health risks. AI that cross-references decades of environmental and health data to identify and recommend remediation and preventive measures at the community level. With the proper infrastructure, we can harness this power to deliver better, faster, and more personalized care to all.

But none of this can happen if we cling to the status quo. We must train our research workforce to use these tools, fund the development of new machine learning prediction models, and ensure that healthcare providers across the board—from all types of medicine—can weigh in, contribute, and leverage machine learning-driven insights. This is not just about the future of healthcare; it’s about ensuring that our progress leaves no one behind.

A New Era of Ethics in Integrative Translational Research

As we push forward into this new frontier of science, ethics must be our constant guide. Too often, we’ve rushed into translational research without considering risks and long-term consequences. The promise of quick applications blinds us to the potential pitfalls, and we risk repeating the well-trodden paths to mistakes of the past.

Every advance in technology, every translational breakthrough, must be accompanied by thorough, explicit, and transparent ethical think-throughs. This is why I propose that 10% of all translational research funding be dedicated to ethics. We must ask ourselves tough questions: Who benefits from these advancements? Who could be left behind? Are we considering the long-term societal impacts or just the short-term gains? Could disease burden or mortality have been predicted and thus prevented? Where are we externalizing the costs onto others in ways that increase human pain and suffering?

The COVID-19 pandemic exposed the dangers of top-down public health decision-making, where rigid protocols left little room for adapting to new information. In contrast, distributed learning systems—where knowledge flows dynamically between experts, agencies, and communities—allowed for faster adaptation and innovation. Ethics must embrace this model, ensuring that the narrow interests of a few do not drive research but by a broad, inclusive vision that benefits all.

Profits should be a side effect of doing biomedical and clinical science well, not its main goal.

The Path Forward: Integration, Innovation, and Ethics

The time has come to reimagine how we approach science, medicine, and public health. No single agency or discipline can solve the complex, multifaceted challenges we face. By integrating the work of the NIH, NSF, EPA, and beyond, we can build a system that doesn’t just react to crises, but prevents them. We need to build - from scratch - a system that addresses the root causes of illness, whether from our biology, medicine (including vaccines), the chemical industry, or the world around us.

Cross-Pollination: Integrating Medical and Scientific Disciplines for Holistic Innovation

Ironically, the integration involves less centralization—far less—and more heterarchical cross-pollination, a true reflection of the totality of our society’s contributions to science. Colleges of Arts and Science and departments of Biological sciences should no longer be considered the less-funded, poorer cousins of the schools of medicine.

Cross-pollination between disciplines is not just a metaphor but a necessity for the future of medical and public health advancements. The value exchange between fields like medicine, basic research, and computational sciences can revolutionize how we approach complex biological systems and patient care.

Medical students, especially those pursuing clinical careers, will stand to benefit enormously from engaging with concepts in complex dynamic systems, holistic learning, and integrative critical thinking. This broader approach allows them to view patients not as isolated cases but as part of a larger, interconnected system of biological, environmental, and social factors. Such perspectives are essential for addressing chronic diseases—conditions influenced by genetic, developmental, and environmental and ecological interactions that cannot be effectively treated through reductionist methods alone.

At the same time, basic researchers have much to gain by orienting their studies toward areas of stagnation in medicine and public health. By understanding clinical needs and collaborating with medical professionals, scientists can prioritize their efforts to explore underfunded and underexplored fields such as the developmental origins of chronic illness, environmental toxicology, and systems-level biology. These areas are ripe for breakthroughs that could fundamentally shift how we prevent and treat major health concerns.

Computer Science Departments and computational biologists will play a pivotal role in this cross-pollination process. Integrating machine learning, data analytics, and computational modeling into medical education and basic research opens new possibilities. Machine learning algorithms, for example, can process vast amounts of biological and clinical data to reveal patterns that traditional research methods often overlook. These insights can directly impact fields like personalized medicine, predictive diagnostics, and environmental health by identifying links between pollutants and chronic disease outcomes. We do have the ability. We simply have not had the will. Look at aluminum, for example. Everyone in neurobiology and neurohealth knows it’s a neurotoxin; it’s still found in 60% of pediatric vaccines.

By embracing integrative and critical thinking across disciplines, future physicians and researchers will be better equipped to challenge established protocols and develop innovative solutions. At the same time, these cross-disciplinary exchanges ensure that scientific research remains relevant to real-world clinical challenges, driving progress in areas that directly impact public health.

In the same vein, researchers who adopt a more holistic approach will be more mindful of the broader implications of their work. They can contribute to scientific knowledge and the policy and public health realms by highlighting the societal and environmental contexts of disease and treatment. Environmental toxicology, for example, could benefit greatly from the insights of computational biology, machine learning, and public health experts working in concert to understand how pollutants interact with human biology and contribute to the chronic illness burden. Epidemiology, as far as I can tell, requires a complete overhaul; it is stuck in the 1980s in terms of methodology. We can, and we must, do better.

Addressing Areas of Stagnation in Science, Medicine, and Public Health

Despite technological advances, certain areas of medicine remain stagnant, particularly in chronic disease management and prevention. Research shows that aligning basic science with these areas of need can lead to more effective interventions. For example, collaborative research into the developmental origins of chronic diseases has the potential to reveal critical windows of susceptibility in early development, where targeted interventions could have the most profound long-term impact.

By encouraging these interdisciplinary collaborations, we ensure that both medical professionals and basic researchers remain agile, innovative, and focused on solving the most pressing health issues. This cross-pollination improves the quality of scientific research and creates a more robust and efficient healthcare system capable of addressing the complex and multifactorial nature of chronic illness and public health challenges.

A Unified Vision for Collaborative Progress

To achieve this vision, academic institutions and funding bodies must promote programs that actively bridge medicine, biology, computational sciences, and public health. Cross-pollination between these disciplines, facilitated through interdisciplinary grants and collaborative projects, will empower the next generation of scientists and clinicians to think beyond traditional boundaries, fostering breakthroughs that address the immediate and long-term needs of America in health and medicine. Our eyes should be on the dual prizes of the prevention of and reversal of chronic illness, including mental illness.

By embracing this holistic, integrative approach, we address individual cases while solving the larger puzzle of public health and the reversal of chronic disease. This is how we will make meaningful progress in a rapidly evolving healthcare landscape.

Closing

We must embrace machine learning, not as a tool for the future, but as an essential part of today’s scientific and healthcare infrastructure. Prediction accuracy, not goodness of fit, tells us we are on the right path. We must reinvigorate basic research, recognizing that the long-term discoveries of tomorrow are built on the work we fund today. And we must do this all with a steadfast commitment to ethics, ensuring that science serves humanity, not vice versa.

This vision is bold but achievable. It requires leadership that understands the interconnectedness of the world’s greatest challenges and demands action now. We are standing at the threshold of a new era in science, where collaboration across agencies and disciplines will define our success. The question is no longer whether we have the tools to address these challenges - but whether we have the will to use them.

Join the World Society for Ethical Science. It’s the society that will take us on the adventure of a lifetime.

Reference

Long, H., Dong, B. Special topic on EvoDevo: emerging models and perspectives. Mar Life Sci Technol 5, 431–434 (2023). https://doi.org/10.1007/s42995-023-00208-8