Neurodegenerative disorders such as Alzheimer's disease, Parkinson’s disease, frontotemporal dementia, and ALS affect more than 50 million people worldwide. Neurodegeneration causes people to lose their cognitive abilities and suffer irreversible behavioral and physical deterioration.
Affected families are often emotionally and financially devastated from the burdens of caregiving. The cost to society in terms of lost human potential and taxpayer-funded healthcare are rapidly rising. Yet despite billions of dollars spent on research to date, treatments are very limited and there are no cures for these debilitating and deadly diseases. New approaches are urgently needed to solve the growing crisis of neurodegeneration.
The 10,000 Brains Project is a 501(c)(3) philanthropic initiative that seeks to accelerate the ethical and inclusive use of artificial intelligence (AI) in the fight against neurodegenerative diseases. We’re providing the leadership, expertise, and financial support needed to ensure that medical research can rapidly adopt this exciting new technology for maximum impact. We envision a future where AI-enabled tools deliver personalized diagnostics and treatments for all patients who suffer from neurodegenerative diseases.
To our knowledge, The 10,000 Brains Project is the only philanthropic effort in the world that is focused entirely on maximizing the impact of AI as a breakthrough technology for solving Alzheimer’s disease and other neurodegenerative disorders.
What's in a Name?
“10,000 Brains” gives recognition to the diversity of human brains; every person is different, and their brain health can take different paths. It also acknowledges that no single expert can untangle these mysteries alone; it requires global collaborations and diverse skillsets.
To address these challenges, The 10,000 Brains Project has formed a partnership with the Milken Institute’s Center for Strategic Philanthropy. Together, we’re conducting a comprehensive assessment of the current state of AI in neurodegeneration research. This eight-month project is a rigorous, unbiased due diligence step that will identify key gaps in the current ecosystem, potential barriers to progress, and specific areas where funders can have the greatest impact. Key stakeholders will be included in this assessment process, and the resulting roadmap for moving the field forward will be actively shared with the community upon completion in the summer of 2024.
Filling gaps in support
As the only nonprofit organization specializing in the use of AI in neurodegeneration research, The 10,000 Brains Project will use the Milken roadmap to advise other philanthropic and government funders on key AI priorities and to cultivate their support of the highest impact AI projects. To maximize the impact of our own donors’ funds, we will provide resources only to those areas that are not adequately supported by our partners in academia, philanthropy, industry, and government. Taken together, this will minimize waste and redundancy, while accelerating progress toward the ultimate goal of producing AI-enabled diagnostics, treatments, and clinical support tools for neurodegenerative disorders.
From an operational perspective, The 10,000 Brains Project functions differently than most nonprofit organizations. It operates with only a small full-time staff and is designed to wind down operations after 10 years, once its mission has been achieved.
Artificial intelligence (AI) has the potential to revolutionize virtually all aspects of medical research. This includes the discovery of new drug targets, the earlier detection of disease, and the delivery of more personalized care. Its potential impact in neuroscience is especially intriguing because of the extreme complexity of neurodegenerative diseases. Much remains to be learned about the heterogeneity of these disorders, but we already know that the underlying mechanisms involved can vary greatly depending on a person’s gender, genetics, environmental factors (e.g., exposure to air pollution or other environmental toxins), lifestyle, medical history, and stage of disease. Research using animal and cell-based models is severely limited in the context of these complex and uniquely human phenomena.
The microscope of 21st century science
Just as the microscope fundamentally changed the course of biological research, AI can now enable neuroscientists to take entirely new approaches that leverage massive datasets collected from diverse human study participants. If properly supported, a new generation of AI-savvy researchers can finally begin to grapple with the complexities of neurodegeneration and pursue breakthroughs that were not even imaginable just a few years ago.
Coordination and collaboration are critical
The academic, philanthropic, business, and government sectors are already beginning to forge ahead to explore AI’s use in the fight against neurodegeneration. Unfortunately, these efforts have been somewhat chaotic so far. Too few in the scientific community have formal training in AI, many worthy initiatives are under-resourced, and there is not enough coordination among the key players. To make the most of this once in a generation opportunity, researchers urgently need an unbiased, proactive coordinating body that can help to cut through the hype, bring attention to the most impactful opportunities, and promote the global collaborations needed to pursue them.
We will await the findings of the Milken study to set specific priorities for our programming, but a few key themes are likely to emerge.
Crossing boundaries
First, the field is beginning to de-emphasize the boundaries between traditional diagnostic categories. More and more, researchers are instead focusing on the underlying mechanisms of disease, many of which are shared across multiple neurodegenerative disorders. We therefore expect that most of our programs will be scoped to cut across Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia, ALS, and other established diagnostic classifications.
Addressing key barriers
Second, there are many significant barriers that could hinder the timely and effective adoption of AI if not addressed soon. These include, but are not limited to, a lack of datasets from diverse populations, a lack of digitized neuropathology slides, a lack of neuroscientists who are adequately trained in AI, and a lack of sufficient funding for the substantial computing resources needed to conduct AI-based research. In many cases, solving these problems will require the cultivation of large-scale collaborations, as no single stakeholder will have the resources to fully address them.