The federal government should expand the FDA’s priority review voucher program and provide market exclusivity advantages to encourage the development of medications for addiction.
Declining U.S. manufacturing has sharply curtailed a key path to the middle class for those with high school educations or less, thereby exacerbating income inequality nationwide. The United States can address many of these problems through concerted efforts in advanced manufacturing.
The research community lacks strategies to incentivize collaboration on high-quality data acquisition and sharing. The government should fund collaborative roadmapping, certification, collection, and sharing of large, high-quality datasets in life science.
In anticipation of future known and unknown health security threats, including new pandemics, biothreats, and climate-related health emergencies, our answers need to be much faster, cheaper, and less disruptive to other operations.
To unlock the full potential of artificial intelligence within the Department of Health and Human Services, an AI Corps should be established, embedding specialized AI experts within each of the department’s 10 agencies.
The U.S. government should establish a public-private National Exposome Project (NEP) to generate benchmark human exposure levels for the ~80,000 chemicals to which Americans are regularly exposed.
The federal government is responsible for ensuring the safety and privacy of the processing of personally identifiable information within commercially available information used for the development and deployment of artificial intelligence systems
The United States is in the midst of a once in a generation effort to rebuild its transportation and mobility systems. Meeting this moment will require bold investments in new and emerging transportation technologies.
Employee ownership is a powerful solution that preserves local business ownership, protects supply chains, creates quality jobs, and grows the household balance sheets of American workers and their families.
In the nascent yet exponentially expanding world of AI in medical imaging, a well-defined standards and metrology framework is required to establish robust imaging datasets for true precision medicine, thereby improving patient outcomes and reducing spiraling healthcare costs.
Small, fast grant programs are vital to supporting transformative research. By adopting a more flexible, decentralized model, we can significantly enhance their impact.
New solutions are needed to target diseases before they are life-threatening or debilitating, moving from retroactive sick-care towards preventative healthcare.