Author, as appears in the article.: Menendez J; Cuyàs E; Folguera-Blasco N; Verdura S; Martin-Castillo B; Joven J; Alarcón T

Department: Medicina i Cirurgia

URV's Author/s: Joven Maried, Jorge

Keywords: Senolytics Inflammation Cancer Biomathematics Aging

Abstract: Therapeutic strategies targeting the hallmarks of aging can be broadly grouped into four categories, namely systemic (blood) factors, metabolic manipulation (diet regimens and dietary restriction mimetics), suppression of cellular senescence (senolytics), and cellular reprogramming, which likely have common characteristics and mechanisms of action. In evaluating the potential synergism of combining such strategies, however, we should consider the possibility of constraining trade-off phenotypes such as impairment in wound healing and immune response, tissue dysfunction and tumorigenesis. Moreover, we are rapidly learning that the benefit/risk ratio of aging-targeted interventions largely depends on intra- and inter-individual variations of susceptibility to the healthspan-, resilience-, and/or lifespan-promoting effects of the interventions. Here, we exemplify how computationally-generated proxies of the efficacy of a given lifespan/healthspan-promoting approach can predict the impact of baseline epigenetic heterogeneity on the positive outcomes of ketogenic diet and mTOR inhibition as single or combined anti-aging strategies. We therefore propose that stochastic biomathematical modeling and computational simulation platforms should be developed as in silico strategies to accelerate the performance of clinical trials targeting human aging, and to provide personalized approaches and robust biomarkers of healthy aging at the individual-to-population levels.

Thematic Areas: Odontología Nutrição Medicina veterinaria Medicina iii Medicina ii Medicina i Interdisciplinar Geriatrics & gerontology Ciências biológicas ii Ciências biológicas i Cell biology Biotecnología

ISSN: 19454589

Author's mail: jorge.joven@urv.cat

Author identifier: 0000-0003-2749-4541

Record's date: 2023-02-18

Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/

Papper original source: Aging-Us. 11 (16): 6591-6601

APA: Menendez J; Cuyàs E; Folguera-Blasco N; Verdura S; Martin-Castillo B; Joven J; Alarcón T (2019). In silico clinical trials for anti-aging therapies. Aging-Us, 11(16), 6591-6601. DOI: 10.18632/aging.102180

Article's DOI: 10.18632/aging.102180

Entity: Universitat Rovira i Virgili

Journal publication year: 2019

Publication Type: Journal Publications