The partnership will combine grant funding with technical support and usage credits for Anthropic’s Claude AI model to “extend the benefits of AI in areas where markets alone will not,” according to a Thursday (May 14) announcement.
The biggest portion of the project is aimed at global health, especially in low- and middle-income countries where an estimated 4.6 billion people lack access to essential medical services, per the announcement. The organizations plan to use AI to accelerate the development of vaccines and therapies for neglected diseases.
“Together, we will explore how AI can make it faster and easier for scientists to screen potential vaccine candidates, including vaccines that protect against diseases like polio, computationally before moving into pre-clinical development,” the announcement said. “This could help shorten the early-stage development timeline.”
Anthropic is also working with the Institute for Disease Modeling, a research group within the Gates Foundation, to improve the forecasts that decide where and how to deploy treatment for illnesses like malaria and tuberculosis, according to the announcement.
Beyond healthcare, the partnership will also develop tools to improve “educational outcomes” for K-12 students in the United States, sub-Saharan Africa and India, while also supporting programs to encourage economic mobility, the announcement said.
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The effort is the latest in a series of examples of AI being deployed for health-related discoveries.
For example, it was reported this week that Moderna is partnering with Anthropic rival OpenAI to develop new drugs. Last month, it was reported that the Mayo Clinic has developed an AI model called REDMOD that can detect pancreatic cancer on routine abdominal CT scans up to three years before a clinical diagnosis. The model can spot subtle signs of disease before tumors are visible, when curative treatment could still be possible.
Researchers analyzed nearly 2,000 CT scans, including scans from patients later diagnosed with pancreatic cancer that were originally interpreted as normal. REDMOD identified 73% of those prediagnostic cancers at a median of around 16 months before diagnosis, close to double the detection rate of specialists examining the same scans without the help of AI.
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