Click here for the transcript of this interview: https://aging-us.net/2022/06/22/longevity-aging-series-ep-1-drs-alex-zhavoronkov-and-frank-pun/

Aging (Aging-US) and FOXO Technologies have teamed up to present a special collaboration on aging research with a new monthly video series: the Longevity & Aging Series. This series of video interviews invites Aging researchers to speak with researcher and host Dr. Brian Chen. Dr. Chen is an adjunct faculty member at the Herbert Wertheim School of Public Health and Human Longevity Science at the University of California San Diego. He is also the Chief Science Officer of FOXO Technologies.

In the first episode of the Longevity & Aging Series, Drs. Alex Zhavoronkov and Frank Pun discuss, in detail, their recently published research paper, “Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.”

DOI - https://doi.org/10.18632/aging.203960

Corresponding author - Alex Zhavoronkov - [email protected]

Press release - https://aging-us.net/2022/06/22/aging-aging-us-and-foxo-present-the-longevity-aging-series/

Video of first episode - https://www.youtube.com/watch?v=Td8tK5SX0kA

Abstract

Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to classify a multiplicity of mechanisms driving the aging process is the hallmarks of aging. In addition to the classic nine hallmarks of aging, processes such as extracellular matrix stiffness, chronic inflammation and activation of retrotransposons are also often considered, given their strong association with aging. In this study, we used a variety of target identification and prioritization techniques offered by the AI-powered PandaOmics platform, to propose a list of promising novel aging-associated targets that may be used for drug discovery. We also propose a list of more classical targets that may be used for drug repurposing within each hallmark of aging. Most of the top targets generated by this comprehensive analysis play a role in inflammation and extracellular matrix stiffness, highlighting the relevance of these processes as therapeutic targets in aging and age-related diseases. Overall, our study reveals both high confidence and novel targets associated with multiple hallmarks of aging and demonstrates application of the PandaOmics platform to target discovery across multiple disease areas.

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Keywords - aging, artificial intelligence, deep learning, drug discovery, multi-omics, target identification

About Aging-US

Launched in 2009, Aging-US publishes papers of general interest and biological significance in all fields of aging research and age-related diseases, including cancer—and now, with a special focus on COVID-19 vulnerability as an age-dependent syndrome. Topics in Aging-US go beyond traditional gerontology, including, but not limited to, cellular and molecular biology, human age-related diseases, pathology in model organisms, signal transduction pathways (e.g., p53, sirtuins, and PI-3K/AKT/mTOR, among others), and approaches to modulating these signaling pathways.

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