The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve... Show moreThe search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.Robust validation of biomarkers of aging will be critical to their clinical translation; here, authors review the key challenges and propose recommendations to overcome them. Show less
Reproducibility of indicators and metrics is an important topic as it underlies an increasing part of the approach taken to research evaluation. But reproducibility of metrics is not the critical... Show moreReproducibility of indicators and metrics is an important topic as it underlies an increasing part of the approach taken to research evaluation. But reproducibility of metrics is not the critical question. The more important question is around access to the data to create metrics, and around who owns the metrics and the transparency of the algorithms and data elements. In short, is it not about producibility rather than reproducibility? With Dimensions, Digital Science has taken a first step in making publication and citation data more openly available. But, perhaps more importantly, Dimensions links other types of data to the familiar bibliometrics landscape to allow the community to go beyond citation-based indicators. The team at Digital Science believes in the “separation of powers” - data should be developed and hosted by providers and the community should own the metrics used to measure itself. Work has started to collaborate with the scientometric and research management community to support their development and implementation of metrics based on the Dimensions data and platform. Show less
