Catalyst Awardee

Project Description

Identifying Predictive Biomarkers of Effective Immunity in Aging Populations

Wayne Koff, PhD

Competition Sponsor: US National Academy of Medicine

The world is aging at an unprecedented rate, and we are not prepared. By 2050 nearly 1.6 billion people will be over age 65, creating widespread public health challenges. This aging population will dramatically increase the burden of non-communicable diseases and enhance our vulnerability to infectious diseases. The human immune system holds the key to improving human health, and within this system lies an immense capacity for disease prevention. Technological innovations are now allowing us to reimagine and reshape the future of human health by understanding and harnessing the immune system in new ways. We have embarked on an ambitious effort to decode the human immune system, identify the biomarkers of effective immunity, and utilize this information to accelerate the development of novel therapeutics, vaccines, and diagnostics for diseases of aging populations. We use licensed vaccines to probe immunity across the age spectrum and differentiate responders from non-responders, and then utilize artificial intelligence and machine learning to develop predictive models for effective human immunity. We have recently conducted pilot trials with licensed hepatitis B and shingles vaccines in adults and elderly subjects, and performed the most comprehensive immunologic and systems biological assessment of host responses ever undertaken. Catalytic support will enable data integration and frontier supercomputing analyses to identify biomarkers of effective immunity, which we will then validate in larger-scale trials in well-studied cohorts of aging individuals. These studies may open the door for transformative new approaches to enhancing human immunity, preventing disease, and prolonging healthy lives among aging populations.

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