Aging and drug discovery

We hypothesize that altered intensities of a few morphogenic pathways account for most/all the phenotypes of aging. Investigating this has revealed a novel approach to rejuvenate multiple mammalian tissues by defined pharmacology. Specifically, we pursued the simultaneous youthful in vivo calibration of two determinants: TGF-beta which activates ALK5/pSmad 2,3 and goes up with age, and oxytocin (OT) which activates MAPK and diminishes with age. The dose of Alk5 inhibitor (Alk5i) was reduced by 10-fold and the duration of treatment was shortened (to minimize overt skewing of cell-signaling pathways), yet the positive outcomes were broadened, as compared with our previous studies. Alk5i plus OT quickly and robustly enhanced neurogenesis, reduced neuro-inflammation, improved cognitive performance, and rejuvenated livers and muscle in old mice. Interestingly, the combination also diminished the numbers of cells that express the CDK inhibitor and marker of senescence p16 in vivo. Summarily, simultaneously re-normalizing two pathways that change with age in opposite ways (up vs. down) synergistically reverses multiple symptoms of aging.

Section: Resultssupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Rejuvenation of brain, liver and muscle by simultaneous pharmacological modulation of two signaling determinants, that change in opposite directions with age

Mehdipour

Etienne

Chen

et al. 2019

“…The deep aging clock research is expected to increase in popularity. Recent workshops at the National Institutes of Health (NIH) [53] and at the leading industry conferences [15] highlighted the need for development of the comprehensive deep age predictors. The authors expect this trend to continue with the inevitable commercialization in the insurance and consumer wellness industries.…”

Section: Discussionmentioning

confidence: 99%

“…Many efforts are underway to apply deep learning techniques to predict the outcomes of clinical trials [13, 14]. However slowly, the artificial intelligence technologies started propagating into aging and longevity research and are rapidly increasing in popularity resulting in the formation of dedicated conference sessions and entire conferences [15] and focused reviews [16].…”

Section: Introductionmentioning

confidence: 99%

Deep biomarkers of aging and longevity: from research to applications

Zhavoronkov

Li²,

Ma³

et al. 2019

Self Cite

Multiple recent advances in machine learning enabled computer systems to exceed human performance in many tasks including voice, text, and speech recognition and complex strategy games. Aging is a complex multifactorial process driven by and resulting in the many minute changes transpiring at every level of the human organism. Deep learning systems trained on the many measurable features changing in time can generalize and learn the many biological processes on the population and individual levels. The deep age predictors can help advance aging research by establishing causal relationships in non-linear systems. Deep aging clocks can be used for identification of novel therapeutic targets, evaluating the efficacy of the various interventions, data quality control, data economics, prediction of health trajectories, mortality, and many other applications. Here we present the current state of development of the deep aging clocks in the context of the pharmaceutical research and development and clinical applications.

“…In the following, we provide an overview of the discussed research topics. The meeting followed on the heels of the 5 th ARDD [1].…”

Section: Introductionmentioning

confidence: 99%

Latest advances in aging research and drug discovery

Bakula

Ablasser

Aguzzi

et al. 2019

Self Cite

An increasing aging population poses a significant challenge to societies worldwide. A better understanding of the molecular, cellular, organ, tissue, physiological, psychological, and even sociological changes that occur with aging is needed in order to treat age-associated diseases. The field of aging research is rapidly expanding with multiple advances transpiring in many previously disconnected areas. Several major pharmaceutical, biotechnology, and consumer companies made aging research a priority and are building internal expertise, integrating aging research into traditional business models and exploring new go-to-market strategies. Many of these efforts are spearheaded by the latest advances in artificial intelligence, namely deep learning, including generative and reinforcement learning. To facilitate these trends, the Center for Healthy Aging at the University of Copenhagen and Insilico Medicine are building a community of Key Opinion Leaders (KOLs) in these areas and launched the annual conference series titled “Aging Research and Drug Discovery (ARDD)” held in the capital of the pharmaceutical industry, Basel, Switzerland (www.agingpharma.org). This ARDD collection contains summaries from the 6th annual meeting that explored aging mechanisms and new interventions in age-associated diseases. The 7th annual ARDD exhibition will transpire 2nd-4th of September, 2020, in Basel.